MDedge Pediatrics

TOPLINE:

Subcutaneous tocilizumab provides durable disease control rates in patients with polyarticular and systemic juvenile idiopathic arthritis (pJIA and sJIA, respectively).

METHODOLOGY:

• This long-term extension (LTE) study included 44 patients with pJIA and 38 patients with sJIA, according to the International League of Associations for Rheumatology criteria, from two 52-week phase 1b trials (NCT01904292 and NCT01904279).
• In the core trials, the dosing frequency of subcutaneous tocilizumab was determined by weight: Every 3 weeks for those < 30 kg in pJIA and every 2 weeks for those ≥ 30 kg; in sJIA, initially every 10 days for those < 30 kg, transitioning to every 2 weeks, and weekly for those ≥ 30 kg.
• Patients who had adequate disease control with subcutaneous tocilizumab, comparable with the use of intravenous tocilizumab in the core trials, continued to receive subcutaneous tocilizumab.
• The study outcome was the change in Juvenile Arthritis Disease Activity Score on 71 joints (JADAS-71, range 0-101).

TAKEAWAY:

• Disease control remained stable in both groups, with sustained improvements in median JADAS-71 scores in pJIA (−0.2 with lower frequency dosing to −0.5 with higher frequency) and sJIA (−0.1 at both dosing frequencies).
• In the pJIA group, 90% and 53% of patients weighing < 30 kg and ≥ 30 kg achieved inactive disease, respectively, whereas in the sJIA group, the respective rates were 91% and 92%.
• A total of five of 15 patients with pJIA weighing ≥ 30 kg who received subcutaneous tocilizumab every 2 weeks achieved clinical remission, whereas in other groups, the clinical remission rates ranged from 74% to 92%.
• Six patients with pJIA reported seven serious adverse events (SAEs), while five patients with sJIA experienced six SAEs. Five patients with pJIA and one patient with sJIA reported serious infections.

IN PRACTICE:

The authors concluded that subcutaneous tocilizumab treatment provided long-term disease control in patients with pJIA or sJIA, with a safety profile consistent with past studies of tocilizumab.

SOURCE:

The study was led by Hermine I. Brunner, MD, director of the Division of Rheumatology at Cincinnati Children’s Hospital Medical Center. It was published online in Rheumatology (Oxford).

LIMITATIONS:

The open-label design and lack of a control group limited the analysis. Only a few patients continued the treatment for 5 years.

DISCLOSURES:

This work was supported by F. Hoffmann-La Roche Ltd. Eight authors reported receiving honoraria and consulting or speaker fees from various pharma sources. The remaining authors declared no conflicts of interest.
 

A version of this article appeared on Medscape.com.

TOPLINE:

Subcutaneous tocilizumab provides durable disease control rates in patients with polyarticular and systemic juvenile idiopathic arthritis (pJIA and sJIA, respectively).

METHODOLOGY:

• This long-term extension (LTE) study included 44 patients with pJIA and 38 patients with sJIA, according to the International League of Associations for Rheumatology criteria, from two 52-week phase 1b trials (NCT01904292 and NCT01904279).
• In the core trials, the dosing frequency of subcutaneous tocilizumab was determined by weight: Every 3 weeks for those < 30 kg in pJIA and every 2 weeks for those ≥ 30 kg; in sJIA, initially every 10 days for those < 30 kg, transitioning to every 2 weeks, and weekly for those ≥ 30 kg.
• Patients who had adequate disease control with subcutaneous tocilizumab, comparable with the use of intravenous tocilizumab in the core trials, continued to receive subcutaneous tocilizumab.
• The study outcome was the change in Juvenile Arthritis Disease Activity Score on 71 joints (JADAS-71, range 0-101).

TAKEAWAY:

• Disease control remained stable in both groups, with sustained improvements in median JADAS-71 scores in pJIA (−0.2 with lower frequency dosing to −0.5 with higher frequency) and sJIA (−0.1 at both dosing frequencies).
• In the pJIA group, 90% and 53% of patients weighing < 30 kg and ≥ 30 kg achieved inactive disease, respectively, whereas in the sJIA group, the respective rates were 91% and 92%.
• A total of five of 15 patients with pJIA weighing ≥ 30 kg who received subcutaneous tocilizumab every 2 weeks achieved clinical remission, whereas in other groups, the clinical remission rates ranged from 74% to 92%.
• Six patients with pJIA reported seven serious adverse events (SAEs), while five patients with sJIA experienced six SAEs. Five patients with pJIA and one patient with sJIA reported serious infections.

IN PRACTICE:

The authors concluded that subcutaneous tocilizumab treatment provided long-term disease control in patients with pJIA or sJIA, with a safety profile consistent with past studies of tocilizumab.

SOURCE:

The study was led by Hermine I. Brunner, MD, director of the Division of Rheumatology at Cincinnati Children’s Hospital Medical Center. It was published online in Rheumatology (Oxford).

LIMITATIONS:

The open-label design and lack of a control group limited the analysis. Only a few patients continued the treatment for 5 years.

DISCLOSURES:

This work was supported by F. Hoffmann-La Roche Ltd. Eight authors reported receiving honoraria and consulting or speaker fees from various pharma sources. The remaining authors declared no conflicts of interest.
 

A version of this article appeared on Medscape.com.

TOPLINE:

Subcutaneous tocilizumab provides durable disease control rates in patients with polyarticular and systemic juvenile idiopathic arthritis (pJIA and sJIA, respectively).

METHODOLOGY:

• This long-term extension (LTE) study included 44 patients with pJIA and 38 patients with sJIA, according to the International League of Associations for Rheumatology criteria, from two 52-week phase 1b trials (NCT01904292 and NCT01904279).
• In the core trials, the dosing frequency of subcutaneous tocilizumab was determined by weight: Every 3 weeks for those < 30 kg in pJIA and every 2 weeks for those ≥ 30 kg; in sJIA, initially every 10 days for those < 30 kg, transitioning to every 2 weeks, and weekly for those ≥ 30 kg.
• Patients who had adequate disease control with subcutaneous tocilizumab, comparable with the use of intravenous tocilizumab in the core trials, continued to receive subcutaneous tocilizumab.
• The study outcome was the change in Juvenile Arthritis Disease Activity Score on 71 joints (JADAS-71, range 0-101).

TAKEAWAY:

• Disease control remained stable in both groups, with sustained improvements in median JADAS-71 scores in pJIA (−0.2 with lower frequency dosing to −0.5 with higher frequency) and sJIA (−0.1 at both dosing frequencies).
• In the pJIA group, 90% and 53% of patients weighing < 30 kg and ≥ 30 kg achieved inactive disease, respectively, whereas in the sJIA group, the respective rates were 91% and 92%.
• A total of five of 15 patients with pJIA weighing ≥ 30 kg who received subcutaneous tocilizumab every 2 weeks achieved clinical remission, whereas in other groups, the clinical remission rates ranged from 74% to 92%.
• Six patients with pJIA reported seven serious adverse events (SAEs), while five patients with sJIA experienced six SAEs. Five patients with pJIA and one patient with sJIA reported serious infections.

IN PRACTICE:

The authors concluded that subcutaneous tocilizumab treatment provided long-term disease control in patients with pJIA or sJIA, with a safety profile consistent with past studies of tocilizumab.

SOURCE:

The study was led by Hermine I. Brunner, MD, director of the Division of Rheumatology at Cincinnati Children’s Hospital Medical Center. It was published online in Rheumatology (Oxford).

LIMITATIONS:

The open-label design and lack of a control group limited the analysis. Only a few patients continued the treatment for 5 years.

DISCLOSURES:

This work was supported by F. Hoffmann-La Roche Ltd. Eight authors reported receiving honoraria and consulting or speaker fees from various pharma sources. The remaining authors declared no conflicts of interest.
 

A version of this article appeared on Medscape.com.

The early cancellation of a trial in southern India suggests that the use of antenatal steroids to prevent respiratory complications after late-preterm birth — a recommended practice in the United States — may not be effective in the developing world.

As reported in Obstetrics & Gynecology, researchers led by Hilda Yenuberi, MD, of Christian Medical College, Vellore, Tamil Nadu, India, stopped the randomized, triple-blinded, placebo-controlled CLAP (Corticosteroids in Late Pregnancy) study at 70% enrollment. An interim analysis found no benefit from prescribing betamethasone vs placebo to women at risk of late-preterm delivery between 34 and 36 and 6/7 weeks of gestation (primary outcome of respiratory distress: 4.9% vs 4.8%, respectively, relative risk [RR], 1.03; 95% CI, 0.57-1.84; number needed to treat = 786).

“These findings may suggest differing efficacy of antenatal corticosteroids in developing countries compared with developed countries ... that should be considered when late-preterm antenatal corticosteroids are administered,” the researchers wrote.

The use of steroids in patients at risk of delivery before 34 weeks is widely accepted as a way to prevent neonatal respiratory distress, a common and potentially deadly condition in premature infants whose lungs are not fully developed. However, there’s debate over steroid treatment in women who are expected to deliver later than 34 weeks but still preterm.

As the study notes, “the American College of Obstetricians and Gynecologists recommends a single course of betamethasone for pregnant individuals at risk of delivering between 34 and 36 6/7 weeks of gestation on the basis of the ALPS (Antenatal Late Preterm Steroid) trial.”

But other randomized trials have reached different conclusions, and steroids are not without risks. Studies have linked prenatal steroids to neurosensory disorders in babies, meaning they’re more likely to need hearing aids and eyeglasses, said Kellie Murphy, MD, MSc, professor of obstetrics and gynecology, University of Toronto, Toronto, Ontario, Canada, in an interview. Dr. Murphy, who was not involved in the new trial, added that there are links between steroids and greater likelihood of poorer performance in school,

For the new study, conducted from 2020 to 2022 at Christian Medical College and Hospital in Vellore, India, researchers randomly assigned 423 patients to betamethasone (410 in the interim analysis; average age, 26.8 years) and 424 to placebo (415 in the interim analysis; average age, 26.2 years).

The average age of participants was 26.8 years. All were between 34 and 36 6/7 weeks of gestation and expected to give birth within the next week. A quarter of participants delivered at term, which the authors wrote “may have influenced the primary outcome.” The total number of neonates was 883, including 58 twin pregnancies.

There was no significant difference in respiratory distress between groups, “defined as need for oxygen or continuous positive airway pressure or mechanical ventilation for at least 2 hours in the first 72 hours of life.” There also were no significant differences in maternal outcomes such as chorioamnionitis or length of hospitalization or neonatal secondary outcomes such as transient tachypnea of the newborn, respiratory distress syndrome, necrotizing enterocolitis, sepsis, hyperbilirubinemia, stillbirth, and early neonatal death.

Serious adverse events occurred in four neonates but none were linked to the intervention.

The study doesn’t discuss cost, but a 2019 report suggests that use of betamethasone to prevent neonatal respiratory distress is cost-effective.

“Our findings are contradictory to those of a systematic review, the major contributor of which was the ALPS trial,” the authors of the new study reported. “The primary outcome of the ALPS trial, the composite of neonatal treatment in the first 72 hours, was significantly less in the group who received betamethasone (11.6%), compared with the placebo group (14.4%; relative risk [RR], 0.80; 95% CI, 0.66-0.97).”

The study authors, who didn’t respond to requests for comment, noted that their trial included twin pregnancies and patients with gestational diabetes; the ALPS trial did not.

Perinatologist Cynthia Gyamfi-Bannerman, MD, MS, chair and professor of Obstetrics, Gynecology, and Reproductive Sciences at the University of California,San Diego, and principal investigator of the ALPS study, said in an interview that the inclusion of twins in the new trial is “a fundamental flaw.”

“Because antenatal corticosteroids have not been shown to be useful in twins at any gestational age, it is not surprising that including twins likely moved the findings to the null in this study,” she said. “Twins were purposefully excluded from the ALPS trial for this reason.”

According to the new study, “the primary outcome among singleton neonates occurred in 4.8% (18/374) who received betamethasone and 5.1% (20/393) who received placebo (RR, 0.94; 95% CI, 0.51-1.75)

What should clinicians take from the study findings? In an accompanying commentary, Blair J. Wylie, MD, MPH, of Columbia University Medical Center, New York, NY, and Syed Asad Ali, MBBS, MPH, of Aga Khan University, Karachi, Pakistan, wrote that, “in settings similar to the US-based ALPS trial, the practice of administering a course of late-preterm antenatal corticosteroids should be continued, as espoused by our professional organizations.”

However, the new study suggests that “research in high-resource environments may not be generalizable to low-resource settings,” they write.

Neonatologist Elizabeth Asztalos, MD, MSc, an associate scientist with Sunnybrook Health Sciences Center in Toronto, Canada, said in an interview that she doesn’t worry about pregnant mothers not getting steroids later than 34 weeks. “We have tools in our armamentarium in the NICU setting to help babies if they need it,” said Dr. Asztalos, who didn’t take part in the new trial. “We can put them on CPAP if they have wet lung. If they have an element of respiratory distress, we can give them surfactants. These bigger babies have more ability to recover from all this compared to a baby who was born at 24, 25, 26 weeks.”

For her part, the University of Toronto’s Dr. Murphy said decision-making about late-preterm steroids is complicated. “You don’t want to miss the opportunity to give to provide benefits for the patients” via steroids, she said. “But on the flip side, it’s a double-edged sword. It’s not easy. It’s not straightforward.”

In the big picture, she said, “people need to be really clear why they’re giving an intervention and what they hope to achieve.”

Christian Medical College supported the study. The authors, Dr. Murphy, Dr. Asztalos, and commentary co-author Dr. Ali have no disclosures. Dr. Gyamfi-Bannerman discloses being principal investigator of the ALPS trial. Commentary co-author Dr. Wylie serves on the ultrasound quality assurance committee of a trial discussed in the commentary.

The early cancellation of a trial in southern India suggests that the use of antenatal steroids to prevent respiratory complications after late-preterm birth — a recommended practice in the United States — may not be effective in the developing world.

As reported in Obstetrics & Gynecology, researchers led by Hilda Yenuberi, MD, of Christian Medical College, Vellore, Tamil Nadu, India, stopped the randomized, triple-blinded, placebo-controlled CLAP (Corticosteroids in Late Pregnancy) study at 70% enrollment. An interim analysis found no benefit from prescribing betamethasone vs placebo to women at risk of late-preterm delivery between 34 and 36 and 6/7 weeks of gestation (primary outcome of respiratory distress: 4.9% vs 4.8%, respectively, relative risk [RR], 1.03; 95% CI, 0.57-1.84; number needed to treat = 786).

“These findings may suggest differing efficacy of antenatal corticosteroids in developing countries compared with developed countries ... that should be considered when late-preterm antenatal corticosteroids are administered,” the researchers wrote.

The use of steroids in patients at risk of delivery before 34 weeks is widely accepted as a way to prevent neonatal respiratory distress, a common and potentially deadly condition in premature infants whose lungs are not fully developed. However, there’s debate over steroid treatment in women who are expected to deliver later than 34 weeks but still preterm.

As the study notes, “the American College of Obstetricians and Gynecologists recommends a single course of betamethasone for pregnant individuals at risk of delivering between 34 and 36 6/7 weeks of gestation on the basis of the ALPS (Antenatal Late Preterm Steroid) trial.”

But other randomized trials have reached different conclusions, and steroids are not without risks. Studies have linked prenatal steroids to neurosensory disorders in babies, meaning they’re more likely to need hearing aids and eyeglasses, said Kellie Murphy, MD, MSc, professor of obstetrics and gynecology, University of Toronto, Toronto, Ontario, Canada, in an interview. Dr. Murphy, who was not involved in the new trial, added that there are links between steroids and greater likelihood of poorer performance in school,

For the new study, conducted from 2020 to 2022 at Christian Medical College and Hospital in Vellore, India, researchers randomly assigned 423 patients to betamethasone (410 in the interim analysis; average age, 26.8 years) and 424 to placebo (415 in the interim analysis; average age, 26.2 years).

The average age of participants was 26.8 years. All were between 34 and 36 6/7 weeks of gestation and expected to give birth within the next week. A quarter of participants delivered at term, which the authors wrote “may have influenced the primary outcome.” The total number of neonates was 883, including 58 twin pregnancies.

There was no significant difference in respiratory distress between groups, “defined as need for oxygen or continuous positive airway pressure or mechanical ventilation for at least 2 hours in the first 72 hours of life.” There also were no significant differences in maternal outcomes such as chorioamnionitis or length of hospitalization or neonatal secondary outcomes such as transient tachypnea of the newborn, respiratory distress syndrome, necrotizing enterocolitis, sepsis, hyperbilirubinemia, stillbirth, and early neonatal death.

Serious adverse events occurred in four neonates but none were linked to the intervention.

The study doesn’t discuss cost, but a 2019 report suggests that use of betamethasone to prevent neonatal respiratory distress is cost-effective.

“Our findings are contradictory to those of a systematic review, the major contributor of which was the ALPS trial,” the authors of the new study reported. “The primary outcome of the ALPS trial, the composite of neonatal treatment in the first 72 hours, was significantly less in the group who received betamethasone (11.6%), compared with the placebo group (14.4%; relative risk [RR], 0.80; 95% CI, 0.66-0.97).”

The study authors, who didn’t respond to requests for comment, noted that their trial included twin pregnancies and patients with gestational diabetes; the ALPS trial did not.

Perinatologist Cynthia Gyamfi-Bannerman, MD, MS, chair and professor of Obstetrics, Gynecology, and Reproductive Sciences at the University of California,San Diego, and principal investigator of the ALPS study, said in an interview that the inclusion of twins in the new trial is “a fundamental flaw.”

“Because antenatal corticosteroids have not been shown to be useful in twins at any gestational age, it is not surprising that including twins likely moved the findings to the null in this study,” she said. “Twins were purposefully excluded from the ALPS trial for this reason.”

According to the new study, “the primary outcome among singleton neonates occurred in 4.8% (18/374) who received betamethasone and 5.1% (20/393) who received placebo (RR, 0.94; 95% CI, 0.51-1.75)

What should clinicians take from the study findings? In an accompanying commentary, Blair J. Wylie, MD, MPH, of Columbia University Medical Center, New York, NY, and Syed Asad Ali, MBBS, MPH, of Aga Khan University, Karachi, Pakistan, wrote that, “in settings similar to the US-based ALPS trial, the practice of administering a course of late-preterm antenatal corticosteroids should be continued, as espoused by our professional organizations.”

However, the new study suggests that “research in high-resource environments may not be generalizable to low-resource settings,” they write.

Neonatologist Elizabeth Asztalos, MD, MSc, an associate scientist with Sunnybrook Health Sciences Center in Toronto, Canada, said in an interview that she doesn’t worry about pregnant mothers not getting steroids later than 34 weeks. “We have tools in our armamentarium in the NICU setting to help babies if they need it,” said Dr. Asztalos, who didn’t take part in the new trial. “We can put them on CPAP if they have wet lung. If they have an element of respiratory distress, we can give them surfactants. These bigger babies have more ability to recover from all this compared to a baby who was born at 24, 25, 26 weeks.”

For her part, the University of Toronto’s Dr. Murphy said decision-making about late-preterm steroids is complicated. “You don’t want to miss the opportunity to give to provide benefits for the patients” via steroids, she said. “But on the flip side, it’s a double-edged sword. It’s not easy. It’s not straightforward.”

In the big picture, she said, “people need to be really clear why they’re giving an intervention and what they hope to achieve.”

Christian Medical College supported the study. The authors, Dr. Murphy, Dr. Asztalos, and commentary co-author Dr. Ali have no disclosures. Dr. Gyamfi-Bannerman discloses being principal investigator of the ALPS trial. Commentary co-author Dr. Wylie serves on the ultrasound quality assurance committee of a trial discussed in the commentary.

The early cancellation of a trial in southern India suggests that the use of antenatal steroids to prevent respiratory complications after late-preterm birth — a recommended practice in the United States — may not be effective in the developing world.

As reported in Obstetrics & Gynecology, researchers led by Hilda Yenuberi, MD, of Christian Medical College, Vellore, Tamil Nadu, India, stopped the randomized, triple-blinded, placebo-controlled CLAP (Corticosteroids in Late Pregnancy) study at 70% enrollment. An interim analysis found no benefit from prescribing betamethasone vs placebo to women at risk of late-preterm delivery between 34 and 36 and 6/7 weeks of gestation (primary outcome of respiratory distress: 4.9% vs 4.8%, respectively, relative risk [RR], 1.03; 95% CI, 0.57-1.84; number needed to treat = 786).

“These findings may suggest differing efficacy of antenatal corticosteroids in developing countries compared with developed countries ... that should be considered when late-preterm antenatal corticosteroids are administered,” the researchers wrote.

The use of steroids in patients at risk of delivery before 34 weeks is widely accepted as a way to prevent neonatal respiratory distress, a common and potentially deadly condition in premature infants whose lungs are not fully developed. However, there’s debate over steroid treatment in women who are expected to deliver later than 34 weeks but still preterm.

As the study notes, “the American College of Obstetricians and Gynecologists recommends a single course of betamethasone for pregnant individuals at risk of delivering between 34 and 36 6/7 weeks of gestation on the basis of the ALPS (Antenatal Late Preterm Steroid) trial.”

But other randomized trials have reached different conclusions, and steroids are not without risks. Studies have linked prenatal steroids to neurosensory disorders in babies, meaning they’re more likely to need hearing aids and eyeglasses, said Kellie Murphy, MD, MSc, professor of obstetrics and gynecology, University of Toronto, Toronto, Ontario, Canada, in an interview. Dr. Murphy, who was not involved in the new trial, added that there are links between steroids and greater likelihood of poorer performance in school,

For the new study, conducted from 2020 to 2022 at Christian Medical College and Hospital in Vellore, India, researchers randomly assigned 423 patients to betamethasone (410 in the interim analysis; average age, 26.8 years) and 424 to placebo (415 in the interim analysis; average age, 26.2 years).

The average age of participants was 26.8 years. All were between 34 and 36 6/7 weeks of gestation and expected to give birth within the next week. A quarter of participants delivered at term, which the authors wrote “may have influenced the primary outcome.” The total number of neonates was 883, including 58 twin pregnancies.

There was no significant difference in respiratory distress between groups, “defined as need for oxygen or continuous positive airway pressure or mechanical ventilation for at least 2 hours in the first 72 hours of life.” There also were no significant differences in maternal outcomes such as chorioamnionitis or length of hospitalization or neonatal secondary outcomes such as transient tachypnea of the newborn, respiratory distress syndrome, necrotizing enterocolitis, sepsis, hyperbilirubinemia, stillbirth, and early neonatal death.

Serious adverse events occurred in four neonates but none were linked to the intervention.

The study doesn’t discuss cost, but a 2019 report suggests that use of betamethasone to prevent neonatal respiratory distress is cost-effective.

“Our findings are contradictory to those of a systematic review, the major contributor of which was the ALPS trial,” the authors of the new study reported. “The primary outcome of the ALPS trial, the composite of neonatal treatment in the first 72 hours, was significantly less in the group who received betamethasone (11.6%), compared with the placebo group (14.4%; relative risk [RR], 0.80; 95% CI, 0.66-0.97).”

The study authors, who didn’t respond to requests for comment, noted that their trial included twin pregnancies and patients with gestational diabetes; the ALPS trial did not.

Perinatologist Cynthia Gyamfi-Bannerman, MD, MS, chair and professor of Obstetrics, Gynecology, and Reproductive Sciences at the University of California,San Diego, and principal investigator of the ALPS study, said in an interview that the inclusion of twins in the new trial is “a fundamental flaw.”

“Because antenatal corticosteroids have not been shown to be useful in twins at any gestational age, it is not surprising that including twins likely moved the findings to the null in this study,” she said. “Twins were purposefully excluded from the ALPS trial for this reason.”

According to the new study, “the primary outcome among singleton neonates occurred in 4.8% (18/374) who received betamethasone and 5.1% (20/393) who received placebo (RR, 0.94; 95% CI, 0.51-1.75)

What should clinicians take from the study findings? In an accompanying commentary, Blair J. Wylie, MD, MPH, of Columbia University Medical Center, New York, NY, and Syed Asad Ali, MBBS, MPH, of Aga Khan University, Karachi, Pakistan, wrote that, “in settings similar to the US-based ALPS trial, the practice of administering a course of late-preterm antenatal corticosteroids should be continued, as espoused by our professional organizations.”

However, the new study suggests that “research in high-resource environments may not be generalizable to low-resource settings,” they write.

Neonatologist Elizabeth Asztalos, MD, MSc, an associate scientist with Sunnybrook Health Sciences Center in Toronto, Canada, said in an interview that she doesn’t worry about pregnant mothers not getting steroids later than 34 weeks. “We have tools in our armamentarium in the NICU setting to help babies if they need it,” said Dr. Asztalos, who didn’t take part in the new trial. “We can put them on CPAP if they have wet lung. If they have an element of respiratory distress, we can give them surfactants. These bigger babies have more ability to recover from all this compared to a baby who was born at 24, 25, 26 weeks.”

For her part, the University of Toronto’s Dr. Murphy said decision-making about late-preterm steroids is complicated. “You don’t want to miss the opportunity to give to provide benefits for the patients” via steroids, she said. “But on the flip side, it’s a double-edged sword. It’s not easy. It’s not straightforward.”

In the big picture, she said, “people need to be really clear why they’re giving an intervention and what they hope to achieve.”

Christian Medical College supported the study. The authors, Dr. Murphy, Dr. Asztalos, and commentary co-author Dr. Ali have no disclosures. Dr. Gyamfi-Bannerman discloses being principal investigator of the ALPS trial. Commentary co-author Dr. Wylie serves on the ultrasound quality assurance committee of a trial discussed in the commentary.

Antibiotics had no measurable effect on the severity or duration of coughs due to acute lower respiratory tract infection (LRTI, or acute bronchitis), a large prospective study found.

In fact, those receiving an antibiotic in the primary- and urgent-care setting had a small but significant increase in overall length of illness (17.5 vs 15.9 days; P = .05) — largely because patients with longer illness before the index visit were more likely to receive these drugs. The study adds further support for reducing the prescription of antibiotics for LRTIs.

“Importantly, the pathogen data demonstrated that the length of time until illness resolution for those with bacterial infection was the same as for those not receiving an antibiotic versus those receiving one (17.3 vs 17.4 days),” researchers led by Daniel J. Merenstein, MD, a professor and director of research programs, family medicine, at Georgetown University Medical Center in Washington, wrote in the Journal of General Internal Medicine (doi: 10.1007/s11606-024-08758-y).

Dr. Merenstein

Risks

Overuse of antibiotics can result in dizziness, nausea, diarrhea, and rash, along with a roughly 4% chance of serious adverse effects including anaphylaxis; Stevens-Johnson syndrome, a serious skin and mucous membrane disorder; and Clostridioides difficile-associated diarrhea.

An estimated half of all antibiotic prescriptions for acute respiratory conditions are unnecessary. Before the COVID-19 pandemic, antibiotics were prescribed about 70% of the time for a diagnosis of uncomplicated cough and LRTI. The viral pandemic did not change this practice according to a meta-analysis of 130 studies showing that 78% of COVID-19 patients were prescribed an antibiotic.
 

The study

The study looked at a cohort of 718 patients, with a mean age of 38.9 years, 65.3% female, of whom 207 received an antibiotic and 511 did not. Of those with baseline data, 29% had an antibiotic prescribed at baseline, the most common (in 85%) being amoxicillin-clavulanate, azithromycin, doxycycline, and amoxicillin. Antibiotics had no effect on the duration or overall severity of cough in viral, bacterial, or mixed infections. Receipt of an antibiotic did, however, reduce the likelihood of a follow-up visit: 14.1% vs 8.2% (adjusted odds ratio, 0.47; 95% confidence interval, 0.26-0.84) — perhaps because it removed the motivation for seeking another consultation. Antibiotic recipients were more likely to receive a systemic corticosteroid (31.9% vs 4.5%, P <.001) and were also more likely to receive an albuterol inhaler (22.7% vs 7.6%, P <.001).

Jeffrey A. Linder, MD, MPH, a primary care physician and chief of internal medicine and geriatrics at Northwestern University Feinberg School of Medicine in Chicago, agrees that in the vast majority of LRTIs — usually acute bronchitis — antibiotics do not speed the healing process. “Forty years of research show that antibiotics do not make acute bronchitis go away any faster,” Dr. Linder, who was not involved in the current study, said in an interview. “There’s even growing evidence that a lot of pneumonia is viral as well, and 10 or 20 years from now we may often not be giving antibiotics for pneumonia because we’ll be able to see better if it’s caused by a virus.”

Northwestern Medicine

Antibiotics had no measurable effect on the severity or duration of coughs due to acute lower respiratory tract infection (LRTI, or acute bronchitis), a large prospective study found.

In fact, those receiving an antibiotic in the primary- and urgent-care setting had a small but significant increase in overall length of illness (17.5 vs 15.9 days; P = .05) — largely because patients with longer illness before the index visit were more likely to receive these drugs. The study adds further support for reducing the prescription of antibiotics for LRTIs.

“Importantly, the pathogen data demonstrated that the length of time until illness resolution for those with bacterial infection was the same as for those not receiving an antibiotic versus those receiving one (17.3 vs 17.4 days),” researchers led by Daniel J. Merenstein, MD, a professor and director of research programs, family medicine, at Georgetown University Medical Center in Washington, wrote in the Journal of General Internal Medicine (doi: 10.1007/s11606-024-08758-y).

Dr. Merenstein

Risks

Overuse of antibiotics can result in dizziness, nausea, diarrhea, and rash, along with a roughly 4% chance of serious adverse effects including anaphylaxis; Stevens-Johnson syndrome, a serious skin and mucous membrane disorder; and Clostridioides difficile-associated diarrhea.

An estimated half of all antibiotic prescriptions for acute respiratory conditions are unnecessary. Before the COVID-19 pandemic, antibiotics were prescribed about 70% of the time for a diagnosis of uncomplicated cough and LRTI. The viral pandemic did not change this practice according to a meta-analysis of 130 studies showing that 78% of COVID-19 patients were prescribed an antibiotic.
 

The study

The study looked at a cohort of 718 patients, with a mean age of 38.9 years, 65.3% female, of whom 207 received an antibiotic and 511 did not. Of those with baseline data, 29% had an antibiotic prescribed at baseline, the most common (in 85%) being amoxicillin-clavulanate, azithromycin, doxycycline, and amoxicillin. Antibiotics had no effect on the duration or overall severity of cough in viral, bacterial, or mixed infections. Receipt of an antibiotic did, however, reduce the likelihood of a follow-up visit: 14.1% vs 8.2% (adjusted odds ratio, 0.47; 95% confidence interval, 0.26-0.84) — perhaps because it removed the motivation for seeking another consultation. Antibiotic recipients were more likely to receive a systemic corticosteroid (31.9% vs 4.5%, P <.001) and were also more likely to receive an albuterol inhaler (22.7% vs 7.6%, P <.001).

Jeffrey A. Linder, MD, MPH, a primary care physician and chief of internal medicine and geriatrics at Northwestern University Feinberg School of Medicine in Chicago, agrees that in the vast majority of LRTIs — usually acute bronchitis — antibiotics do not speed the healing process. “Forty years of research show that antibiotics do not make acute bronchitis go away any faster,” Dr. Linder, who was not involved in the current study, said in an interview. “There’s even growing evidence that a lot of pneumonia is viral as well, and 10 or 20 years from now we may often not be giving antibiotics for pneumonia because we’ll be able to see better if it’s caused by a virus.”

Northwestern Medicine

Antibiotics had no measurable effect on the severity or duration of coughs due to acute lower respiratory tract infection (LRTI, or acute bronchitis), a large prospective study found.

In fact, those receiving an antibiotic in the primary- and urgent-care setting had a small but significant increase in overall length of illness (17.5 vs 15.9 days; P = .05) — largely because patients with longer illness before the index visit were more likely to receive these drugs. The study adds further support for reducing the prescription of antibiotics for LRTIs.

“Importantly, the pathogen data demonstrated that the length of time until illness resolution for those with bacterial infection was the same as for those not receiving an antibiotic versus those receiving one (17.3 vs 17.4 days),” researchers led by Daniel J. Merenstein, MD, a professor and director of research programs, family medicine, at Georgetown University Medical Center in Washington, wrote in the Journal of General Internal Medicine (doi: 10.1007/s11606-024-08758-y).

Dr. Merenstein

Risks

Overuse of antibiotics can result in dizziness, nausea, diarrhea, and rash, along with a roughly 4% chance of serious adverse effects including anaphylaxis; Stevens-Johnson syndrome, a serious skin and mucous membrane disorder; and Clostridioides difficile-associated diarrhea.

An estimated half of all antibiotic prescriptions for acute respiratory conditions are unnecessary. Before the COVID-19 pandemic, antibiotics were prescribed about 70% of the time for a diagnosis of uncomplicated cough and LRTI. The viral pandemic did not change this practice according to a meta-analysis of 130 studies showing that 78% of COVID-19 patients were prescribed an antibiotic.
 

The study

The study looked at a cohort of 718 patients, with a mean age of 38.9 years, 65.3% female, of whom 207 received an antibiotic and 511 did not. Of those with baseline data, 29% had an antibiotic prescribed at baseline, the most common (in 85%) being amoxicillin-clavulanate, azithromycin, doxycycline, and amoxicillin. Antibiotics had no effect on the duration or overall severity of cough in viral, bacterial, or mixed infections. Receipt of an antibiotic did, however, reduce the likelihood of a follow-up visit: 14.1% vs 8.2% (adjusted odds ratio, 0.47; 95% confidence interval, 0.26-0.84) — perhaps because it removed the motivation for seeking another consultation. Antibiotic recipients were more likely to receive a systemic corticosteroid (31.9% vs 4.5%, P <.001) and were also more likely to receive an albuterol inhaler (22.7% vs 7.6%, P <.001).

Jeffrey A. Linder, MD, MPH, a primary care physician and chief of internal medicine and geriatrics at Northwestern University Feinberg School of Medicine in Chicago, agrees that in the vast majority of LRTIs — usually acute bronchitis — antibiotics do not speed the healing process. “Forty years of research show that antibiotics do not make acute bronchitis go away any faster,” Dr. Linder, who was not involved in the current study, said in an interview. “There’s even growing evidence that a lot of pneumonia is viral as well, and 10 or 20 years from now we may often not be giving antibiotics for pneumonia because we’ll be able to see better if it’s caused by a virus.”

Northwestern Medicine

Early data suggested that several new multicancer early detection (MCED) tests in development show promise for identifying cancers that lack routine screening options.

Analyses presented during a session at the American Association for Cancer Research annual meeting, revealed that three new MCED tests — CanScan, MERCURY, and OncoSeek — could detect a range of cancers and recognize the tissue of origin with high accuracy. One — OncoSeek — could also provide an affordable cancer screening option for individuals living in lower-income countries.

The need for these noninvasive liquid biopsy tests that can accurately identify multiple cancer types with a single blood draw, especially cancers without routine screening strategies, is pressing. “We know that the current cancer standard of care screening will identify less than 50% of all cancers, while more than 50% of all cancer deaths occur in types of cancer with no recommended screening,” said co-moderator Marie E. Wood, MD, of the University of Colorado Anschutz Medical Campus, in Aurora, Colorado.

That being said, “the clinical utility of multicancer detection tests has not been established and we’re concerned about issues of overdiagnosis and overtreatment,” she noted.

The Early Data 

One new MCED test called CanScan, developed by Geneseeq Technology, uses plasma cell-free DNA fragment patterns to detect cancer signals as well as identify the tissue of origin across 13 cancer types.

Overall, the CanScan test covers cancer types that contribute to two thirds of new cancer cases and 74% of morality globally, said presenter Shanshan Yang, of Geneseeq Research Institute, in Nanjing, China.

However, only five of these cancer types have screening recommendations issued by the US Preventive Services Task Force (USPSTF), Dr. Yang added.

The interim data comes from an ongoing large-scale prospective study evaluating the MCED test in a cohort of asymptomatic individuals between ages 45 and 75 years with an average risk for cancer and no cancer-related symptoms on enrollment.

Patients at baseline had their blood collected for the CanScan test and subsequently received annual routine physical exams once a year for 3 consecutive years, with an additional 2 years of follow-up. 

The analysis included 3724 participants with analyzable samples at the data cutoff in September 2023. Among the 3724 participants, 29 had confirmed cancer diagnoses. Among these cases, 14 patients had their cancer confirmed through USPSTF recommended screening and 15 were detected through outside of standard USPSTF screening, such as a thyroid ultrasound, Dr. Yang explained.

Almost 90% of the cancers (26 of 29) were detected in the stage I or II, and eight (27.5%) were not one of the test’s 13 targeted cancer types.

The CanScan test had a sensitivity of 55.2%, identifying 16 of 29 of the patients with cancer, including 10 of 21 individuals with stage I (47.6%), and two of three with stage II (66.7%). 

The test had a high specificity of 97.9%, meaning out of 100 people screened, only two had false negative findings.

Among the 15 patients who had their cancer detected outside of USPSTF screening recommendations, eight (53.3%) were found using a CanScan test, including patients with liver and endometrial cancers.

Compared with a positive predictive value of (PPV) of 1.6% with screening or physical exam methods alone, the CanScan test had a PPV of 17.4%, Dr. Yang reported. 

“The MCED test holds significant potential for early cancer screening in asymptomatic populations,” Dr. Yang and colleagues concluded.

Another new MCED test called MERCURY, also developed by Geneseeq Technology and presented during the session, used a similar method to detect cancer signals and predict the tissue of origin across 13 cancer types.

The researchers initially validated the test using 3076 patients with cancer and 3477 healthy controls with a target specificity of 99%. In this group, researchers reported a sensitivity of 0.865 and a specificity of 0.989.

The team then performed an independent validation analysis with 1465 participants, 732 with cancer and 733 with no cancer, and confirmed a high sensitivity and specificity of 0.874 and 0.978, respectively. The sensitivity increased incrementally by cancer stage — 0.768 for stage I, 0.840 for stage II, 0.923 for stage III, and 0.971 for stage IV.

The test identified the tissue of origin with high accuracy, the researchers noted, but cautioned that the test needs “to be further validated in a prospective cohort study.”

MCED in Low-Income Settings

The session also featured findings on a new affordable MCED test called OncoSeek, which could provide greater access to cancer testing in low- and middle-income countries.

The OncoSeek algorithm identifies the presence of cancer using seven protein tumor markers alongside clinical information, such as gender and age. Like other tests, the test also predicts the possible tissue of origin.

The test can be run on clinical protein assay instruments that are already widely available, such as Roche cobas analyzer, Mao Mao, MD, PhD, the founder and CEO of SeekIn, of Shenzhen, China, told this news organization.

This “feature makes the test accessible worldwide, even in low- and middle-income countries,” he said. “These instruments are fully-automated and part of today’s clinical practice. Therefore, the test does not require additional infrastructure building and lab personal training.”

Another notable advantage: the OncoSeek test only costs about $20, compared with other MCED tests, which can cost anywhere from $200 to $1000.

To validate the technology in a large, diverse cohort, Dr. Mao and colleagues enrolled approximately 10,000 participants, including 2003 cancer cases and 7888 non-cancer cases.

Peripheral blood was collected from each participant and analyzed using a panel of the seven protein tumor markers — AFP, CA125, CA15-3, CA19-9, CA72-4, CEA, and CYFRA 21-1.

To reduce the risk for false positive findings, the team designed the OncoSeek algorithm to achieve a specificity of 93%. Dr. Mao and colleagues found a sensitivity of 51.7%, resulting in an overall accuracy of 84.6%.

The performance was consistent in additional validation cohorts in Brazil, China, and the United States, with sensitivities ranging from 39.0% to 77.6% for detecting nine common cancer types, including breast, colorectal, liver, lung, lymphoma, esophagus, ovary, pancreas, and stomach. The sensitivity for pancreatic cancer was at the high end of 77.6%.

The test could predict the tissue of origin in about two thirds of cases. 

Given its low cost, OncoSeek represents an affordable and accessible option for cancer screening, the authors concluded. 

Overall, “I think MCEDs have the potential to enhance cancer screening,” Dr. Wood told this news organization.

Still, questions remain about the optimal use of these tests, such as whether they are best for average-risk or higher risk populations, and how to integrate them into standard screening, she said. 

Dr. Wood also cautioned that the studies presented in the session represent early data, and it is likely that the numbers, such as sensitivity and specificity, will change with further prospective analyses.

And ultimately, these tests should complement, not replace, standard screening. “A negative testing should not be taken as a sign to avoid standard screening,” Dr. Wood said.

Dr. Yang is an employee of Geneseeq Technology, Inc., and Dr. Mao is an employee of SeekIn. Dr. Wood had no disclosures to report.

A version of this article appeared on Medscape.com.

Early data suggested that several new multicancer early detection (MCED) tests in development show promise for identifying cancers that lack routine screening options.

Analyses presented during a session at the American Association for Cancer Research annual meeting, revealed that three new MCED tests — CanScan, MERCURY, and OncoSeek — could detect a range of cancers and recognize the tissue of origin with high accuracy. One — OncoSeek — could also provide an affordable cancer screening option for individuals living in lower-income countries.

The need for these noninvasive liquid biopsy tests that can accurately identify multiple cancer types with a single blood draw, especially cancers without routine screening strategies, is pressing. “We know that the current cancer standard of care screening will identify less than 50% of all cancers, while more than 50% of all cancer deaths occur in types of cancer with no recommended screening,” said co-moderator Marie E. Wood, MD, of the University of Colorado Anschutz Medical Campus, in Aurora, Colorado.

That being said, “the clinical utility of multicancer detection tests has not been established and we’re concerned about issues of overdiagnosis and overtreatment,” she noted.

The Early Data 

One new MCED test called CanScan, developed by Geneseeq Technology, uses plasma cell-free DNA fragment patterns to detect cancer signals as well as identify the tissue of origin across 13 cancer types.

Overall, the CanScan test covers cancer types that contribute to two thirds of new cancer cases and 74% of morality globally, said presenter Shanshan Yang, of Geneseeq Research Institute, in Nanjing, China.

However, only five of these cancer types have screening recommendations issued by the US Preventive Services Task Force (USPSTF), Dr. Yang added.

The interim data comes from an ongoing large-scale prospective study evaluating the MCED test in a cohort of asymptomatic individuals between ages 45 and 75 years with an average risk for cancer and no cancer-related symptoms on enrollment.

Patients at baseline had their blood collected for the CanScan test and subsequently received annual routine physical exams once a year for 3 consecutive years, with an additional 2 years of follow-up. 

The analysis included 3724 participants with analyzable samples at the data cutoff in September 2023. Among the 3724 participants, 29 had confirmed cancer diagnoses. Among these cases, 14 patients had their cancer confirmed through USPSTF recommended screening and 15 were detected through outside of standard USPSTF screening, such as a thyroid ultrasound, Dr. Yang explained.

Almost 90% of the cancers (26 of 29) were detected in the stage I or II, and eight (27.5%) were not one of the test’s 13 targeted cancer types.

The CanScan test had a sensitivity of 55.2%, identifying 16 of 29 of the patients with cancer, including 10 of 21 individuals with stage I (47.6%), and two of three with stage II (66.7%). 

The test had a high specificity of 97.9%, meaning out of 100 people screened, only two had false negative findings.

Among the 15 patients who had their cancer detected outside of USPSTF screening recommendations, eight (53.3%) were found using a CanScan test, including patients with liver and endometrial cancers.

Compared with a positive predictive value of (PPV) of 1.6% with screening or physical exam methods alone, the CanScan test had a PPV of 17.4%, Dr. Yang reported. 

“The MCED test holds significant potential for early cancer screening in asymptomatic populations,” Dr. Yang and colleagues concluded.

Another new MCED test called MERCURY, also developed by Geneseeq Technology and presented during the session, used a similar method to detect cancer signals and predict the tissue of origin across 13 cancer types.

The researchers initially validated the test using 3076 patients with cancer and 3477 healthy controls with a target specificity of 99%. In this group, researchers reported a sensitivity of 0.865 and a specificity of 0.989.

The team then performed an independent validation analysis with 1465 participants, 732 with cancer and 733 with no cancer, and confirmed a high sensitivity and specificity of 0.874 and 0.978, respectively. The sensitivity increased incrementally by cancer stage — 0.768 for stage I, 0.840 for stage II, 0.923 for stage III, and 0.971 for stage IV.

The test identified the tissue of origin with high accuracy, the researchers noted, but cautioned that the test needs “to be further validated in a prospective cohort study.”

MCED in Low-Income Settings

The session also featured findings on a new affordable MCED test called OncoSeek, which could provide greater access to cancer testing in low- and middle-income countries.

The OncoSeek algorithm identifies the presence of cancer using seven protein tumor markers alongside clinical information, such as gender and age. Like other tests, the test also predicts the possible tissue of origin.

The test can be run on clinical protein assay instruments that are already widely available, such as Roche cobas analyzer, Mao Mao, MD, PhD, the founder and CEO of SeekIn, of Shenzhen, China, told this news organization.

This “feature makes the test accessible worldwide, even in low- and middle-income countries,” he said. “These instruments are fully-automated and part of today’s clinical practice. Therefore, the test does not require additional infrastructure building and lab personal training.”

Another notable advantage: the OncoSeek test only costs about $20, compared with other MCED tests, which can cost anywhere from $200 to $1000.

To validate the technology in a large, diverse cohort, Dr. Mao and colleagues enrolled approximately 10,000 participants, including 2003 cancer cases and 7888 non-cancer cases.

Peripheral blood was collected from each participant and analyzed using a panel of the seven protein tumor markers — AFP, CA125, CA15-3, CA19-9, CA72-4, CEA, and CYFRA 21-1.

To reduce the risk for false positive findings, the team designed the OncoSeek algorithm to achieve a specificity of 93%. Dr. Mao and colleagues found a sensitivity of 51.7%, resulting in an overall accuracy of 84.6%.

The performance was consistent in additional validation cohorts in Brazil, China, and the United States, with sensitivities ranging from 39.0% to 77.6% for detecting nine common cancer types, including breast, colorectal, liver, lung, lymphoma, esophagus, ovary, pancreas, and stomach. The sensitivity for pancreatic cancer was at the high end of 77.6%.

The test could predict the tissue of origin in about two thirds of cases. 

Given its low cost, OncoSeek represents an affordable and accessible option for cancer screening, the authors concluded. 

Overall, “I think MCEDs have the potential to enhance cancer screening,” Dr. Wood told this news organization.

Still, questions remain about the optimal use of these tests, such as whether they are best for average-risk or higher risk populations, and how to integrate them into standard screening, she said. 

Dr. Wood also cautioned that the studies presented in the session represent early data, and it is likely that the numbers, such as sensitivity and specificity, will change with further prospective analyses.

And ultimately, these tests should complement, not replace, standard screening. “A negative testing should not be taken as a sign to avoid standard screening,” Dr. Wood said.

Dr. Yang is an employee of Geneseeq Technology, Inc., and Dr. Mao is an employee of SeekIn. Dr. Wood had no disclosures to report.

A version of this article appeared on Medscape.com.

Early data suggested that several new multicancer early detection (MCED) tests in development show promise for identifying cancers that lack routine screening options.

Analyses presented during a session at the American Association for Cancer Research annual meeting, revealed that three new MCED tests — CanScan, MERCURY, and OncoSeek — could detect a range of cancers and recognize the tissue of origin with high accuracy. One — OncoSeek — could also provide an affordable cancer screening option for individuals living in lower-income countries.

The need for these noninvasive liquid biopsy tests that can accurately identify multiple cancer types with a single blood draw, especially cancers without routine screening strategies, is pressing. “We know that the current cancer standard of care screening will identify less than 50% of all cancers, while more than 50% of all cancer deaths occur in types of cancer with no recommended screening,” said co-moderator Marie E. Wood, MD, of the University of Colorado Anschutz Medical Campus, in Aurora, Colorado.

That being said, “the clinical utility of multicancer detection tests has not been established and we’re concerned about issues of overdiagnosis and overtreatment,” she noted.

The Early Data 

One new MCED test called CanScan, developed by Geneseeq Technology, uses plasma cell-free DNA fragment patterns to detect cancer signals as well as identify the tissue of origin across 13 cancer types.

Overall, the CanScan test covers cancer types that contribute to two thirds of new cancer cases and 74% of morality globally, said presenter Shanshan Yang, of Geneseeq Research Institute, in Nanjing, China.

However, only five of these cancer types have screening recommendations issued by the US Preventive Services Task Force (USPSTF), Dr. Yang added.

The interim data comes from an ongoing large-scale prospective study evaluating the MCED test in a cohort of asymptomatic individuals between ages 45 and 75 years with an average risk for cancer and no cancer-related symptoms on enrollment.

Patients at baseline had their blood collected for the CanScan test and subsequently received annual routine physical exams once a year for 3 consecutive years, with an additional 2 years of follow-up. 

The analysis included 3724 participants with analyzable samples at the data cutoff in September 2023. Among the 3724 participants, 29 had confirmed cancer diagnoses. Among these cases, 14 patients had their cancer confirmed through USPSTF recommended screening and 15 were detected through outside of standard USPSTF screening, such as a thyroid ultrasound, Dr. Yang explained.

Almost 90% of the cancers (26 of 29) were detected in the stage I or II, and eight (27.5%) were not one of the test’s 13 targeted cancer types.

The CanScan test had a sensitivity of 55.2%, identifying 16 of 29 of the patients with cancer, including 10 of 21 individuals with stage I (47.6%), and two of three with stage II (66.7%). 

The test had a high specificity of 97.9%, meaning out of 100 people screened, only two had false negative findings.

Among the 15 patients who had their cancer detected outside of USPSTF screening recommendations, eight (53.3%) were found using a CanScan test, including patients with liver and endometrial cancers.

Compared with a positive predictive value of (PPV) of 1.6% with screening or physical exam methods alone, the CanScan test had a PPV of 17.4%, Dr. Yang reported. 

“The MCED test holds significant potential for early cancer screening in asymptomatic populations,” Dr. Yang and colleagues concluded.

Another new MCED test called MERCURY, also developed by Geneseeq Technology and presented during the session, used a similar method to detect cancer signals and predict the tissue of origin across 13 cancer types.

The researchers initially validated the test using 3076 patients with cancer and 3477 healthy controls with a target specificity of 99%. In this group, researchers reported a sensitivity of 0.865 and a specificity of 0.989.

The team then performed an independent validation analysis with 1465 participants, 732 with cancer and 733 with no cancer, and confirmed a high sensitivity and specificity of 0.874 and 0.978, respectively. The sensitivity increased incrementally by cancer stage — 0.768 for stage I, 0.840 for stage II, 0.923 for stage III, and 0.971 for stage IV.

The test identified the tissue of origin with high accuracy, the researchers noted, but cautioned that the test needs “to be further validated in a prospective cohort study.”

MCED in Low-Income Settings

The session also featured findings on a new affordable MCED test called OncoSeek, which could provide greater access to cancer testing in low- and middle-income countries.

The OncoSeek algorithm identifies the presence of cancer using seven protein tumor markers alongside clinical information, such as gender and age. Like other tests, the test also predicts the possible tissue of origin.

The test can be run on clinical protein assay instruments that are already widely available, such as Roche cobas analyzer, Mao Mao, MD, PhD, the founder and CEO of SeekIn, of Shenzhen, China, told this news organization.

This “feature makes the test accessible worldwide, even in low- and middle-income countries,” he said. “These instruments are fully-automated and part of today’s clinical practice. Therefore, the test does not require additional infrastructure building and lab personal training.”

Another notable advantage: the OncoSeek test only costs about $20, compared with other MCED tests, which can cost anywhere from $200 to $1000.

To validate the technology in a large, diverse cohort, Dr. Mao and colleagues enrolled approximately 10,000 participants, including 2003 cancer cases and 7888 non-cancer cases.

Peripheral blood was collected from each participant and analyzed using a panel of the seven protein tumor markers — AFP, CA125, CA15-3, CA19-9, CA72-4, CEA, and CYFRA 21-1.

To reduce the risk for false positive findings, the team designed the OncoSeek algorithm to achieve a specificity of 93%. Dr. Mao and colleagues found a sensitivity of 51.7%, resulting in an overall accuracy of 84.6%.

The performance was consistent in additional validation cohorts in Brazil, China, and the United States, with sensitivities ranging from 39.0% to 77.6% for detecting nine common cancer types, including breast, colorectal, liver, lung, lymphoma, esophagus, ovary, pancreas, and stomach. The sensitivity for pancreatic cancer was at the high end of 77.6%.

The test could predict the tissue of origin in about two thirds of cases. 

Given its low cost, OncoSeek represents an affordable and accessible option for cancer screening, the authors concluded. 

Overall, “I think MCEDs have the potential to enhance cancer screening,” Dr. Wood told this news organization.

Still, questions remain about the optimal use of these tests, such as whether they are best for average-risk or higher risk populations, and how to integrate them into standard screening, she said. 

Dr. Wood also cautioned that the studies presented in the session represent early data, and it is likely that the numbers, such as sensitivity and specificity, will change with further prospective analyses.

And ultimately, these tests should complement, not replace, standard screening. “A negative testing should not be taken as a sign to avoid standard screening,” Dr. Wood said.

Dr. Yang is an employee of Geneseeq Technology, Inc., and Dr. Mao is an employee of SeekIn. Dr. Wood had no disclosures to report.

A version of this article appeared on Medscape.com.

In a 2023 study published in the Annals of Emergency Medicine, European researchers fed the AI system ChatGPT information on 30 ER patients. Details included physician notes on the patients’ symptoms, physical exams, and lab results. ChatGPT made the correct diagnosis in 97% of patients compared to 87% for human doctors.

AI 1, Physicians 0

JAMA Cardiology reported in 2021 that an AI trained on nearly a million ECGs performed comparably to or exceeded cardiologist clinical diagnoses and the MUSE (GE Healthcare) system›s automated ECG analysis for most diagnostic classes.

AI 2, Physicians 0

Google’s medically focused AI model (Med-PaLM2) scored 85%+ when answering US Medical Licensing Examination–style questions. That›s an «expert» physician level and far beyond the accuracy threshold needed to pass the actual exam.

AI 3, Physicians 0

A new AI tool that uses an online finger-tapping test outperformed primary care physicians when assessing the severity of Parkinson’s disease.

AI 4, Physicians 0

JAMA Ophthalmology reported in 2024 that a chatbot outperformed glaucoma specialists and matched retina specialists in diagnostic and treatment accuracy.

AI 5, Physicians 0

Should we stop? Because we could go on. In the last few years, these AI vs Physician studies have proliferated, and guess who’s winning?

65% of Doctors are Concerned

Now, the standard answer with anything AI-and-Medicine goes something like this: AI is coming, and it will be a transformative tool for physicians and improve patient care.

But the underlying unanswered question is: Physicians spend many years and a lot of money to become really good at what they do. How, exactly, should a doctor feel about a machine that can suddenly do the job better and faster?

The Medscape 2023 Physician and AI Report surveyed 1043 US physicians about their views on AI. In total, 65% are concerned about AI making diagnosis and treatment decisions, but 56% are enthusiastic about having it as an adjunct.

Cardiologists, anesthesiologists, and radiologists are most enthusiastic about AI, whereas family physicians and pediatricians are the least enthusiastic.

To get a more personal view of how physicians and other healthcare professionals are feeling about this transformative tech, I spoke with a variety of practicing doctors, a psychotherapist, and a third-year Harvard Medical School student.

‘Abysmally Poor Understanding’

Alfredo A. Sadun, MD, PhD, has been a neuro-ophthalmologist for nearly 50 years. A graduate of MIT and vice-chair of ophthalmology at UCLA, he’s long been fascinated by AI’s march into medicine. He’s watched it accomplish things that no ophthalmologist can do, such as identify gender, age, and risk for heart attack and stroke from retinal scans. But he doesn›t see the same level of interest and comprehension among the medical community.

“There’s still an abysmally poor understanding of AI among physicians in general,” he said. “It’s striking because these are intelligent, well-educated people. But we tend to draw conclusions based on what we’re familiar with, and most doctors’ experience with computers involves EHRs [electronic health records] and administrative garbage. It’s the reason they’re burning out.”

Easing the Burden

Anthony Philippakis, MD, PhD, left his cardiology practice in 2015 to become the chief data officer at the Broad Institute of MIT and Harvard. While there, he helped develop an AI-based method for identifying patients at risk for atrial fibrillation. Now, he’s a general partner at Google Ventures with the goal of bridging the gap between data sciences and medicine. His perspective on AI is unique, given that he’s seen the issue from both sides.

“I am not a bitter physician, but to be honest, when I was practicing, way too much of my time was spent staring at screens and not enough laying hands on patients,” he said. “Can you imagine what it would be like to speak to the EHR naturally and say, ‘Please order the following labs for this patient and notify me when the results come in.’ Boy, would that improve healthcare and physician satisfaction. Every physician I know is excited and optimistic about that. Almost everyone I’ve talked to feels like AI could take a lot of the stuff they don’t like doing off their plates.”

Indeed, the dividing line between physician support for AI and physician suspicion or skepticism of AI is just that. In our survey, more than three quarters of physicians said they would consider using AI for office administrative tasks, scheduling, EHRs, researching medical conditions, and even summarizing a patient’s record before a visit. But far fewer are supportive of it delivering diagnoses and treatments. This, despite an estimated 800,000 Americans dying or becoming permanently disabled each year because of diagnostic error.

Could AI Have Diagnosed This?

John D. Nuschke, MD, has been a primary care physician in Allentown, Pennsylvania, for 40 years. He’s a jovial general physician who insists his patients call him Jack. He’s recently started using an AI medical scribe called Freed. With the patient’s permission, it listens in on the visit and generates notes, saving Dr. Nuschke time and helping him focus on the person. He likes that type of assistance, but when it comes to AI replacing him, he’s skeptical.

“I had this patient I diagnosed with prostate cancer,” he explained. “He got treated and was fine for 5 years. Then, he started losing weight and feeling awful — got weak as a kitten. He went back to his urologist and oncologist who thought he had metastatic prostate cancer. He went through PET scans and blood work, but there was no sign his cancer had returned. So the specialists sent him back to me, and the second he walked in, I saw he was floridly hyperthyroid. I could tell across the room just by looking at him. Would AI have been able to make that diagnosis? Does AI do physical exams?”

Dr. Nuschke said he’s also had several instances where patients received their cancer diagnosis from the lab through an automated patient-portal system rather than from him. “That’s an AI of sorts, and I found it distressing,” he said.

Empathy From a Robot

All the doctors I spoke to were hopeful that by freeing them from the burden of administrative work, they would be able to return to the reason they got into this business in the first place — to spend more time with patients in need and support them with grace and compassion.

But suppose AI could do that too?

In a 2023 study conducted at the University of California San Diego and published in JAMA Internal Medicine, three licensed healthcare professionals compared the responses of ChatGPT and physicians to real-world health questions. The panel rated the AI’s answers nearly four times higher in quality and almost 10 times more empathetic than physicians’ replies.

A similar 2024 study in Nature found that Google’s large-language model AI matched or surpassed physician diagnostic accuracy in all six of the medical specialties considered. Plus, it outperformed doctors in 24 of 26 criteria for conversation quality, including politeness, explanation, honesty, and expressing care and commitment.

Nathaniel Chin, MD, is a gerontologist at the University of Wisconsin and advisory board member for the Alzheimer’s Foundation of America. Although he admits that studies like these “sadden me,” he’s also a realist. “There was hesitation among physicians at the beginning of the pandemic to virtual care because we missed the human connection,” he explained, “but we worked our way around that. We need to remember that what makes a chatbot strong is that it’s nothuman. It doesn’t burn out, it doesn’t get tired, it can look at data very quickly, and it doesn’t have to go home to a family and try to balance work with other aspects of life. A human being is very complex, whereas a chatbot has one single purpose.”

“Even if you don’t have AI in your space now or don’t like the idea of it, that doesn’t matter,” he added. “It’s coming. But it needs to be done right. If AI is implemented by clinicians for clinicians, it has great potential. But if it’s implemented by businesspeople for business reasons, perhaps not.”

‘The Ones Who Use the Tools the Best Will Be the Best’

One branch of medicine that stands to be dramatically affected by AI is mental health. Because bots are natural data-crunchers, they are becoming adept at analyzing the many subtle clues (phrasing in social media posts and text messages, smartwatch biometrics, therapy session videos…) that could indicate depression or other psychological disorders. In fact, its availability via smartphone apps could help democratize and destigmatize the practice.

“There is a day ahead — probably within 5 years — when a patient won’t be able to tell the difference between a real therapist and an AI therapist,” said Ken Mallon, MS, LMFT, a clinical psychotherapist and data scientist in San Jose, California. “That doesn’t worry me, though. It’s hard on therapists’ egos, but new technologies get developed. Things change. People who embrace these tools will benefit from them. The ones who use the tools the best will be the best.”

Time to Restructure Med School

Aditya Jain is in his third year at Harvard Medical School. At age 24, he’s heading into this brave new medical world with excitement and anxiety. Excitement because he sees AI revolutionizing healthcare on every level. Although the current generations of physicians and patients may grumble about its onset, he believes younger ones will feel comfortable with “DocGPT.” He’s excited that his generation of physicians will be the “translators and managers of this transition” and redefine “what it means to be a doctor.”

His anxiety, however, stems from the fact that AI has come on so fast that “it has not yet crossed the threshold of medical education,” he said. “Medical schools still largely prepare students to work as solo clinical decision makers. Most of my first 2 years were spent on pattern recognition and rote memorization, skills that AI can and will master.”

Indeed, Mr. Jain said AI was not a part of his first- or second-year curriculum. “I talk to students who are a year older than me, graduating, heading to residency, and they tell me they wish they had gotten a better grasp of how to use these technologies in medicine and in their practice. They were surprised to hear that people in my year hadn’t started using ChatGPT. We need to expend a lot more effort within the field, within academia, within practicing physicians, to figure out what our role will be in a world where AI is matching or even exceeding human intelligence. And then we need to restructure the medical education to better accomplish these goals.”

So Are You Ready for AI to Be a Better Doctor Than You?

“Yes, I am,” said Dr. Philippakis without hesitation. “When I was going through my medical training, I was continually confronted with the reality that I personally was not smart enough to keep all the information in my head that could be used to make a good decision for a patient. We have now reached a point where the amount of information that is important and useful in the practice of medicine outstrips what a human being can know. The opportunity to enable physicians with AI to remedy that situation is a good thing for doctors and, most importantly, a good thing for patients. I believe the future of medicine belongs not so much to the AI practitioner but to the AI-enabled practitioner.”

“Quick story,” added Dr. Chin. “I asked ChatGPT two questions. The first was ‘Explain the difference between Alzheimer’s and dementia’ because that’s the most common misconception in my field. And it gave me a pretty darn good answer — one I would use in a presentation with some tweaking. Then I asked it, ‘Are you a better doctor than me?’ And it replied, ‘My purpose is not to replace you, my purpose is to be supportive of you and enhance your ability.’ ”

A version of this article appeared on Medscape.com.

In a 2023 study published in the Annals of Emergency Medicine, European researchers fed the AI system ChatGPT information on 30 ER patients. Details included physician notes on the patients’ symptoms, physical exams, and lab results. ChatGPT made the correct diagnosis in 97% of patients compared to 87% for human doctors.

AI 1, Physicians 0

JAMA Cardiology reported in 2021 that an AI trained on nearly a million ECGs performed comparably to or exceeded cardiologist clinical diagnoses and the MUSE (GE Healthcare) system›s automated ECG analysis for most diagnostic classes.

AI 2, Physicians 0

Google’s medically focused AI model (Med-PaLM2) scored 85%+ when answering US Medical Licensing Examination–style questions. That›s an «expert» physician level and far beyond the accuracy threshold needed to pass the actual exam.

AI 3, Physicians 0

A new AI tool that uses an online finger-tapping test outperformed primary care physicians when assessing the severity of Parkinson’s disease.

AI 4, Physicians 0

JAMA Ophthalmology reported in 2024 that a chatbot outperformed glaucoma specialists and matched retina specialists in diagnostic and treatment accuracy.

AI 5, Physicians 0

Should we stop? Because we could go on. In the last few years, these AI vs Physician studies have proliferated, and guess who’s winning?

65% of Doctors are Concerned

Now, the standard answer with anything AI-and-Medicine goes something like this: AI is coming, and it will be a transformative tool for physicians and improve patient care.

But the underlying unanswered question is: Physicians spend many years and a lot of money to become really good at what they do. How, exactly, should a doctor feel about a machine that can suddenly do the job better and faster?

The Medscape 2023 Physician and AI Report surveyed 1043 US physicians about their views on AI. In total, 65% are concerned about AI making diagnosis and treatment decisions, but 56% are enthusiastic about having it as an adjunct.

Cardiologists, anesthesiologists, and radiologists are most enthusiastic about AI, whereas family physicians and pediatricians are the least enthusiastic.

To get a more personal view of how physicians and other healthcare professionals are feeling about this transformative tech, I spoke with a variety of practicing doctors, a psychotherapist, and a third-year Harvard Medical School student.

‘Abysmally Poor Understanding’

Alfredo A. Sadun, MD, PhD, has been a neuro-ophthalmologist for nearly 50 years. A graduate of MIT and vice-chair of ophthalmology at UCLA, he’s long been fascinated by AI’s march into medicine. He’s watched it accomplish things that no ophthalmologist can do, such as identify gender, age, and risk for heart attack and stroke from retinal scans. But he doesn›t see the same level of interest and comprehension among the medical community.

“There’s still an abysmally poor understanding of AI among physicians in general,” he said. “It’s striking because these are intelligent, well-educated people. But we tend to draw conclusions based on what we’re familiar with, and most doctors’ experience with computers involves EHRs [electronic health records] and administrative garbage. It’s the reason they’re burning out.”

Easing the Burden

Anthony Philippakis, MD, PhD, left his cardiology practice in 2015 to become the chief data officer at the Broad Institute of MIT and Harvard. While there, he helped develop an AI-based method for identifying patients at risk for atrial fibrillation. Now, he’s a general partner at Google Ventures with the goal of bridging the gap between data sciences and medicine. His perspective on AI is unique, given that he’s seen the issue from both sides.

“I am not a bitter physician, but to be honest, when I was practicing, way too much of my time was spent staring at screens and not enough laying hands on patients,” he said. “Can you imagine what it would be like to speak to the EHR naturally and say, ‘Please order the following labs for this patient and notify me when the results come in.’ Boy, would that improve healthcare and physician satisfaction. Every physician I know is excited and optimistic about that. Almost everyone I’ve talked to feels like AI could take a lot of the stuff they don’t like doing off their plates.”

Indeed, the dividing line between physician support for AI and physician suspicion or skepticism of AI is just that. In our survey, more than three quarters of physicians said they would consider using AI for office administrative tasks, scheduling, EHRs, researching medical conditions, and even summarizing a patient’s record before a visit. But far fewer are supportive of it delivering diagnoses and treatments. This, despite an estimated 800,000 Americans dying or becoming permanently disabled each year because of diagnostic error.

Could AI Have Diagnosed This?

John D. Nuschke, MD, has been a primary care physician in Allentown, Pennsylvania, for 40 years. He’s a jovial general physician who insists his patients call him Jack. He’s recently started using an AI medical scribe called Freed. With the patient’s permission, it listens in on the visit and generates notes, saving Dr. Nuschke time and helping him focus on the person. He likes that type of assistance, but when it comes to AI replacing him, he’s skeptical.

“I had this patient I diagnosed with prostate cancer,” he explained. “He got treated and was fine for 5 years. Then, he started losing weight and feeling awful — got weak as a kitten. He went back to his urologist and oncologist who thought he had metastatic prostate cancer. He went through PET scans and blood work, but there was no sign his cancer had returned. So the specialists sent him back to me, and the second he walked in, I saw he was floridly hyperthyroid. I could tell across the room just by looking at him. Would AI have been able to make that diagnosis? Does AI do physical exams?”

Dr. Nuschke said he’s also had several instances where patients received their cancer diagnosis from the lab through an automated patient-portal system rather than from him. “That’s an AI of sorts, and I found it distressing,” he said.

Empathy From a Robot

All the doctors I spoke to were hopeful that by freeing them from the burden of administrative work, they would be able to return to the reason they got into this business in the first place — to spend more time with patients in need and support them with grace and compassion.

But suppose AI could do that too?

In a 2023 study conducted at the University of California San Diego and published in JAMA Internal Medicine, three licensed healthcare professionals compared the responses of ChatGPT and physicians to real-world health questions. The panel rated the AI’s answers nearly four times higher in quality and almost 10 times more empathetic than physicians’ replies.

A similar 2024 study in Nature found that Google’s large-language model AI matched or surpassed physician diagnostic accuracy in all six of the medical specialties considered. Plus, it outperformed doctors in 24 of 26 criteria for conversation quality, including politeness, explanation, honesty, and expressing care and commitment.

Nathaniel Chin, MD, is a gerontologist at the University of Wisconsin and advisory board member for the Alzheimer’s Foundation of America. Although he admits that studies like these “sadden me,” he’s also a realist. “There was hesitation among physicians at the beginning of the pandemic to virtual care because we missed the human connection,” he explained, “but we worked our way around that. We need to remember that what makes a chatbot strong is that it’s nothuman. It doesn’t burn out, it doesn’t get tired, it can look at data very quickly, and it doesn’t have to go home to a family and try to balance work with other aspects of life. A human being is very complex, whereas a chatbot has one single purpose.”

“Even if you don’t have AI in your space now or don’t like the idea of it, that doesn’t matter,” he added. “It’s coming. But it needs to be done right. If AI is implemented by clinicians for clinicians, it has great potential. But if it’s implemented by businesspeople for business reasons, perhaps not.”

‘The Ones Who Use the Tools the Best Will Be the Best’

One branch of medicine that stands to be dramatically affected by AI is mental health. Because bots are natural data-crunchers, they are becoming adept at analyzing the many subtle clues (phrasing in social media posts and text messages, smartwatch biometrics, therapy session videos…) that could indicate depression or other psychological disorders. In fact, its availability via smartphone apps could help democratize and destigmatize the practice.

“There is a day ahead — probably within 5 years — when a patient won’t be able to tell the difference between a real therapist and an AI therapist,” said Ken Mallon, MS, LMFT, a clinical psychotherapist and data scientist in San Jose, California. “That doesn’t worry me, though. It’s hard on therapists’ egos, but new technologies get developed. Things change. People who embrace these tools will benefit from them. The ones who use the tools the best will be the best.”

Time to Restructure Med School

Aditya Jain is in his third year at Harvard Medical School. At age 24, he’s heading into this brave new medical world with excitement and anxiety. Excitement because he sees AI revolutionizing healthcare on every level. Although the current generations of physicians and patients may grumble about its onset, he believes younger ones will feel comfortable with “DocGPT.” He’s excited that his generation of physicians will be the “translators and managers of this transition” and redefine “what it means to be a doctor.”

His anxiety, however, stems from the fact that AI has come on so fast that “it has not yet crossed the threshold of medical education,” he said. “Medical schools still largely prepare students to work as solo clinical decision makers. Most of my first 2 years were spent on pattern recognition and rote memorization, skills that AI can and will master.”

Indeed, Mr. Jain said AI was not a part of his first- or second-year curriculum. “I talk to students who are a year older than me, graduating, heading to residency, and they tell me they wish they had gotten a better grasp of how to use these technologies in medicine and in their practice. They were surprised to hear that people in my year hadn’t started using ChatGPT. We need to expend a lot more effort within the field, within academia, within practicing physicians, to figure out what our role will be in a world where AI is matching or even exceeding human intelligence. And then we need to restructure the medical education to better accomplish these goals.”

So Are You Ready for AI to Be a Better Doctor Than You?

“Yes, I am,” said Dr. Philippakis without hesitation. “When I was going through my medical training, I was continually confronted with the reality that I personally was not smart enough to keep all the information in my head that could be used to make a good decision for a patient. We have now reached a point where the amount of information that is important and useful in the practice of medicine outstrips what a human being can know. The opportunity to enable physicians with AI to remedy that situation is a good thing for doctors and, most importantly, a good thing for patients. I believe the future of medicine belongs not so much to the AI practitioner but to the AI-enabled practitioner.”

“Quick story,” added Dr. Chin. “I asked ChatGPT two questions. The first was ‘Explain the difference between Alzheimer’s and dementia’ because that’s the most common misconception in my field. And it gave me a pretty darn good answer — one I would use in a presentation with some tweaking. Then I asked it, ‘Are you a better doctor than me?’ And it replied, ‘My purpose is not to replace you, my purpose is to be supportive of you and enhance your ability.’ ”

A version of this article appeared on Medscape.com.

In a 2023 study published in the Annals of Emergency Medicine, European researchers fed the AI system ChatGPT information on 30 ER patients. Details included physician notes on the patients’ symptoms, physical exams, and lab results. ChatGPT made the correct diagnosis in 97% of patients compared to 87% for human doctors.

AI 1, Physicians 0

JAMA Cardiology reported in 2021 that an AI trained on nearly a million ECGs performed comparably to or exceeded cardiologist clinical diagnoses and the MUSE (GE Healthcare) system›s automated ECG analysis for most diagnostic classes.

AI 2, Physicians 0

Google’s medically focused AI model (Med-PaLM2) scored 85%+ when answering US Medical Licensing Examination–style questions. That›s an «expert» physician level and far beyond the accuracy threshold needed to pass the actual exam.

AI 3, Physicians 0

A new AI tool that uses an online finger-tapping test outperformed primary care physicians when assessing the severity of Parkinson’s disease.

AI 4, Physicians 0

JAMA Ophthalmology reported in 2024 that a chatbot outperformed glaucoma specialists and matched retina specialists in diagnostic and treatment accuracy.

AI 5, Physicians 0

Should we stop? Because we could go on. In the last few years, these AI vs Physician studies have proliferated, and guess who’s winning?

65% of Doctors are Concerned

Now, the standard answer with anything AI-and-Medicine goes something like this: AI is coming, and it will be a transformative tool for physicians and improve patient care.

But the underlying unanswered question is: Physicians spend many years and a lot of money to become really good at what they do. How, exactly, should a doctor feel about a machine that can suddenly do the job better and faster?

The Medscape 2023 Physician and AI Report surveyed 1043 US physicians about their views on AI. In total, 65% are concerned about AI making diagnosis and treatment decisions, but 56% are enthusiastic about having it as an adjunct.

Cardiologists, anesthesiologists, and radiologists are most enthusiastic about AI, whereas family physicians and pediatricians are the least enthusiastic.

To get a more personal view of how physicians and other healthcare professionals are feeling about this transformative tech, I spoke with a variety of practicing doctors, a psychotherapist, and a third-year Harvard Medical School student.

‘Abysmally Poor Understanding’

Alfredo A. Sadun, MD, PhD, has been a neuro-ophthalmologist for nearly 50 years. A graduate of MIT and vice-chair of ophthalmology at UCLA, he’s long been fascinated by AI’s march into medicine. He’s watched it accomplish things that no ophthalmologist can do, such as identify gender, age, and risk for heart attack and stroke from retinal scans. But he doesn›t see the same level of interest and comprehension among the medical community.

“There’s still an abysmally poor understanding of AI among physicians in general,” he said. “It’s striking because these are intelligent, well-educated people. But we tend to draw conclusions based on what we’re familiar with, and most doctors’ experience with computers involves EHRs [electronic health records] and administrative garbage. It’s the reason they’re burning out.”

Easing the Burden

Anthony Philippakis, MD, PhD, left his cardiology practice in 2015 to become the chief data officer at the Broad Institute of MIT and Harvard. While there, he helped develop an AI-based method for identifying patients at risk for atrial fibrillation. Now, he’s a general partner at Google Ventures with the goal of bridging the gap between data sciences and medicine. His perspective on AI is unique, given that he’s seen the issue from both sides.

“I am not a bitter physician, but to be honest, when I was practicing, way too much of my time was spent staring at screens and not enough laying hands on patients,” he said. “Can you imagine what it would be like to speak to the EHR naturally and say, ‘Please order the following labs for this patient and notify me when the results come in.’ Boy, would that improve healthcare and physician satisfaction. Every physician I know is excited and optimistic about that. Almost everyone I’ve talked to feels like AI could take a lot of the stuff they don’t like doing off their plates.”

Indeed, the dividing line between physician support for AI and physician suspicion or skepticism of AI is just that. In our survey, more than three quarters of physicians said they would consider using AI for office administrative tasks, scheduling, EHRs, researching medical conditions, and even summarizing a patient’s record before a visit. But far fewer are supportive of it delivering diagnoses and treatments. This, despite an estimated 800,000 Americans dying or becoming permanently disabled each year because of diagnostic error.

Could AI Have Diagnosed This?

John D. Nuschke, MD, has been a primary care physician in Allentown, Pennsylvania, for 40 years. He’s a jovial general physician who insists his patients call him Jack. He’s recently started using an AI medical scribe called Freed. With the patient’s permission, it listens in on the visit and generates notes, saving Dr. Nuschke time and helping him focus on the person. He likes that type of assistance, but when it comes to AI replacing him, he’s skeptical.

“I had this patient I diagnosed with prostate cancer,” he explained. “He got treated and was fine for 5 years. Then, he started losing weight and feeling awful — got weak as a kitten. He went back to his urologist and oncologist who thought he had metastatic prostate cancer. He went through PET scans and blood work, but there was no sign his cancer had returned. So the specialists sent him back to me, and the second he walked in, I saw he was floridly hyperthyroid. I could tell across the room just by looking at him. Would AI have been able to make that diagnosis? Does AI do physical exams?”

Dr. Nuschke said he’s also had several instances where patients received their cancer diagnosis from the lab through an automated patient-portal system rather than from him. “That’s an AI of sorts, and I found it distressing,” he said.

Empathy From a Robot

All the doctors I spoke to were hopeful that by freeing them from the burden of administrative work, they would be able to return to the reason they got into this business in the first place — to spend more time with patients in need and support them with grace and compassion.

But suppose AI could do that too?

In a 2023 study conducted at the University of California San Diego and published in JAMA Internal Medicine, three licensed healthcare professionals compared the responses of ChatGPT and physicians to real-world health questions. The panel rated the AI’s answers nearly four times higher in quality and almost 10 times more empathetic than physicians’ replies.

A similar 2024 study in Nature found that Google’s large-language model AI matched or surpassed physician diagnostic accuracy in all six of the medical specialties considered. Plus, it outperformed doctors in 24 of 26 criteria for conversation quality, including politeness, explanation, honesty, and expressing care and commitment.

Nathaniel Chin, MD, is a gerontologist at the University of Wisconsin and advisory board member for the Alzheimer’s Foundation of America. Although he admits that studies like these “sadden me,” he’s also a realist. “There was hesitation among physicians at the beginning of the pandemic to virtual care because we missed the human connection,” he explained, “but we worked our way around that. We need to remember that what makes a chatbot strong is that it’s nothuman. It doesn’t burn out, it doesn’t get tired, it can look at data very quickly, and it doesn’t have to go home to a family and try to balance work with other aspects of life. A human being is very complex, whereas a chatbot has one single purpose.”

“Even if you don’t have AI in your space now or don’t like the idea of it, that doesn’t matter,” he added. “It’s coming. But it needs to be done right. If AI is implemented by clinicians for clinicians, it has great potential. But if it’s implemented by businesspeople for business reasons, perhaps not.”

‘The Ones Who Use the Tools the Best Will Be the Best’

One branch of medicine that stands to be dramatically affected by AI is mental health. Because bots are natural data-crunchers, they are becoming adept at analyzing the many subtle clues (phrasing in social media posts and text messages, smartwatch biometrics, therapy session videos…) that could indicate depression or other psychological disorders. In fact, its availability via smartphone apps could help democratize and destigmatize the practice.

“There is a day ahead — probably within 5 years — when a patient won’t be able to tell the difference between a real therapist and an AI therapist,” said Ken Mallon, MS, LMFT, a clinical psychotherapist and data scientist in San Jose, California. “That doesn’t worry me, though. It’s hard on therapists’ egos, but new technologies get developed. Things change. People who embrace these tools will benefit from them. The ones who use the tools the best will be the best.”

Time to Restructure Med School

Aditya Jain is in his third year at Harvard Medical School. At age 24, he’s heading into this brave new medical world with excitement and anxiety. Excitement because he sees AI revolutionizing healthcare on every level. Although the current generations of physicians and patients may grumble about its onset, he believes younger ones will feel comfortable with “DocGPT.” He’s excited that his generation of physicians will be the “translators and managers of this transition” and redefine “what it means to be a doctor.”

His anxiety, however, stems from the fact that AI has come on so fast that “it has not yet crossed the threshold of medical education,” he said. “Medical schools still largely prepare students to work as solo clinical decision makers. Most of my first 2 years were spent on pattern recognition and rote memorization, skills that AI can and will master.”

Indeed, Mr. Jain said AI was not a part of his first- or second-year curriculum. “I talk to students who are a year older than me, graduating, heading to residency, and they tell me they wish they had gotten a better grasp of how to use these technologies in medicine and in their practice. They were surprised to hear that people in my year hadn’t started using ChatGPT. We need to expend a lot more effort within the field, within academia, within practicing physicians, to figure out what our role will be in a world where AI is matching or even exceeding human intelligence. And then we need to restructure the medical education to better accomplish these goals.”

So Are You Ready for AI to Be a Better Doctor Than You?

“Yes, I am,” said Dr. Philippakis without hesitation. “When I was going through my medical training, I was continually confronted with the reality that I personally was not smart enough to keep all the information in my head that could be used to make a good decision for a patient. We have now reached a point where the amount of information that is important and useful in the practice of medicine outstrips what a human being can know. The opportunity to enable physicians with AI to remedy that situation is a good thing for doctors and, most importantly, a good thing for patients. I believe the future of medicine belongs not so much to the AI practitioner but to the AI-enabled practitioner.”

“Quick story,” added Dr. Chin. “I asked ChatGPT two questions. The first was ‘Explain the difference between Alzheimer’s and dementia’ because that’s the most common misconception in my field. And it gave me a pretty darn good answer — one I would use in a presentation with some tweaking. Then I asked it, ‘Are you a better doctor than me?’ And it replied, ‘My purpose is not to replace you, my purpose is to be supportive of you and enhance your ability.’ ”

A version of this article appeared on Medscape.com.

TOPLINE:

Diet has only a marginal impact on microbiome development in infancy, although metabolite profiles differ between breast- and formula-fed infants; circadian rhythm of the gut microbiome is detectable as early as 2 weeks after birth.

METHODOLOGY:

• A randomized, controlled interventional trial compared microbiota development in 210 newborns who were exclusively breastfed or received one of four formulas: Un-supplemented formula, Bifidobacterium-supplemented formula, galacto-oligosaccharide (GOS)-supplemented, or formula containing GOSs and bifidobacteria. Exclusively breastfed infants served as a reference group to evaluate the impact of infant formula feeding.
• Researchers tracked the infants’ microbiota and metabolite profiles in response to the different feeding modes via stool samples collected periodically during the first 1-2 years of life.
• They also made note of the time of day that the stool sample was collected to assess 24-hour oscillations of the microbiome in relation to dietary exposure.

TAKEAWAY:

• Global microbiota assembly of infants is primarily affected by age and less so by diet. All infants showed a gradual increase in gut microbe diversity, and at 24 months, there was no observable difference between the groups.
• However, gut metabolite profiles differed significantly between exclusively formula-fed and exclusively breastfed infants. None of the supplemented formulas were able to fully recreate the breast milk-related microbial environment.
• GOS-supplemented formula was more effective at promoting sustained levels of bifidobacteria than formula containing bifidobacteria.
• Metabolic and bacterial profiling revealed 24-hour fluctuations and circadian networks as early as 2 weeks after birth. Infant microbes maintained circadian rhythms when grown in continuous culture, even in the absence of external light or host cues, suggesting an intrinsic clock mechanism in bacteria.

IN PRACTICE:

“Our findings warrant the need for further analysis of circadian fluctuations of both bacteria and metabolites and their functional role in contributing to the benefits of infant nutrition,” the study authors wrote.

SOURCE:

The study was published online April 2 in Cell Host & Microbe.

LIMITATIONS:

The group size for exclusively formula-fed infants was limited, and the explicit contribution of breast milk, relative to infant formula, to bacterial rhythms remains unclear. A possible limitation of the circadian analysis is that the number of fecal samples collected during the night was lower than during the daytime and decreased with age.

DISCLOSURES:

This research was supported by Töpfer GmbH, the German Research Foundation, the Joint Programming Initiative of the European Union, and the German Ministry of Education and Research. The authors had disclosed no relevant conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Diet has only a marginal impact on microbiome development in infancy, although metabolite profiles differ between breast- and formula-fed infants; circadian rhythm of the gut microbiome is detectable as early as 2 weeks after birth.

METHODOLOGY:

• A randomized, controlled interventional trial compared microbiota development in 210 newborns who were exclusively breastfed or received one of four formulas: Un-supplemented formula, Bifidobacterium-supplemented formula, galacto-oligosaccharide (GOS)-supplemented, or formula containing GOSs and bifidobacteria. Exclusively breastfed infants served as a reference group to evaluate the impact of infant formula feeding.
• Researchers tracked the infants’ microbiota and metabolite profiles in response to the different feeding modes via stool samples collected periodically during the first 1-2 years of life.
• They also made note of the time of day that the stool sample was collected to assess 24-hour oscillations of the microbiome in relation to dietary exposure.

TAKEAWAY:

• Global microbiota assembly of infants is primarily affected by age and less so by diet. All infants showed a gradual increase in gut microbe diversity, and at 24 months, there was no observable difference between the groups.
• However, gut metabolite profiles differed significantly between exclusively formula-fed and exclusively breastfed infants. None of the supplemented formulas were able to fully recreate the breast milk-related microbial environment.
• GOS-supplemented formula was more effective at promoting sustained levels of bifidobacteria than formula containing bifidobacteria.
• Metabolic and bacterial profiling revealed 24-hour fluctuations and circadian networks as early as 2 weeks after birth. Infant microbes maintained circadian rhythms when grown in continuous culture, even in the absence of external light or host cues, suggesting an intrinsic clock mechanism in bacteria.

IN PRACTICE:

“Our findings warrant the need for further analysis of circadian fluctuations of both bacteria and metabolites and their functional role in contributing to the benefits of infant nutrition,” the study authors wrote.

SOURCE:

The study was published online April 2 in Cell Host & Microbe.

LIMITATIONS:

The group size for exclusively formula-fed infants was limited, and the explicit contribution of breast milk, relative to infant formula, to bacterial rhythms remains unclear. A possible limitation of the circadian analysis is that the number of fecal samples collected during the night was lower than during the daytime and decreased with age.

DISCLOSURES:

This research was supported by Töpfer GmbH, the German Research Foundation, the Joint Programming Initiative of the European Union, and the German Ministry of Education and Research. The authors had disclosed no relevant conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Diet has only a marginal impact on microbiome development in infancy, although metabolite profiles differ between breast- and formula-fed infants; circadian rhythm of the gut microbiome is detectable as early as 2 weeks after birth.

METHODOLOGY:

• A randomized, controlled interventional trial compared microbiota development in 210 newborns who were exclusively breastfed or received one of four formulas: Un-supplemented formula, Bifidobacterium-supplemented formula, galacto-oligosaccharide (GOS)-supplemented, or formula containing GOSs and bifidobacteria. Exclusively breastfed infants served as a reference group to evaluate the impact of infant formula feeding.
• Researchers tracked the infants’ microbiota and metabolite profiles in response to the different feeding modes via stool samples collected periodically during the first 1-2 years of life.
• They also made note of the time of day that the stool sample was collected to assess 24-hour oscillations of the microbiome in relation to dietary exposure.

TAKEAWAY:

• Global microbiota assembly of infants is primarily affected by age and less so by diet. All infants showed a gradual increase in gut microbe diversity, and at 24 months, there was no observable difference between the groups.
• However, gut metabolite profiles differed significantly between exclusively formula-fed and exclusively breastfed infants. None of the supplemented formulas were able to fully recreate the breast milk-related microbial environment.
• GOS-supplemented formula was more effective at promoting sustained levels of bifidobacteria than formula containing bifidobacteria.
• Metabolic and bacterial profiling revealed 24-hour fluctuations and circadian networks as early as 2 weeks after birth. Infant microbes maintained circadian rhythms when grown in continuous culture, even in the absence of external light or host cues, suggesting an intrinsic clock mechanism in bacteria.

IN PRACTICE:

“Our findings warrant the need for further analysis of circadian fluctuations of both bacteria and metabolites and their functional role in contributing to the benefits of infant nutrition,” the study authors wrote.

SOURCE:

The study was published online April 2 in Cell Host & Microbe.

LIMITATIONS:

The group size for exclusively formula-fed infants was limited, and the explicit contribution of breast milk, relative to infant formula, to bacterial rhythms remains unclear. A possible limitation of the circadian analysis is that the number of fecal samples collected during the night was lower than during the daytime and decreased with age.

DISCLOSURES:

This research was supported by Töpfer GmbH, the German Research Foundation, the Joint Programming Initiative of the European Union, and the German Ministry of Education and Research. The authors had disclosed no relevant conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

A recent survey highlighted ethical concerns US oncologists have about using artificial intelligence (AI) to help make cancer treatment decisions and revealed some contradictory views about how best to integrate these tools into practice. Most respondents, for instance, said patients should not be expected to understand how AI tools work, but many also felt patients could make treatment decisions based on AI-generated recommendations. Most oncologists also felt responsible for protecting patients from biased AI, but few were confident that they could do so.

METHODOLOGY:

• The US Food and Drug Administration (FDA) has  for use in various medical specialties over the past few decades, and increasingly, AI tools are being integrated into cancer care.
• However, the uptake of these tools in oncology has raised ethical questions and concerns, including challenges with AI bias, error, or misuse, as well as issues explaining how an AI model reached a result.
• In the current study, researchers asked 204 oncologists from 37 states for their views on the ethical implications of using AI for cancer care.
• Among the survey respondents, 64% were men and 63% were non-Hispanic White; 29% were from academic practices, 47% had received some education on AI use in healthcare, and 45% were familiar with clinical decision models.
• The researchers assessed respondents’ answers to various questions, including whether to provide informed consent for AI use and how oncologists would approach a scenario where the AI model and the oncologist recommended a different treatment regimen.

TAKEAWAY:

• Overall, 81% of oncologists supported having patient consent to use an AI model during treatment decisions, and 85% felt that oncologists needed to be able to explain an AI-based clinical decision model to use it in the clinic; however, only 23% felt that patients also needed to be able to explain an AI model.
• When an AI decision model recommended a different treatment regimen than the treating oncologist, the most common response (36.8%) was to present both options to the patient and let the patient decide. Oncologists from academic settings were about 2.5 times more likely than those from other settings to let the patient decide. About 34% of respondents said they would present both options but recommend the oncologist’s regimen, whereas about 22% said they would present both but recommend the AI’s regimen. A small percentage would only present the oncologist’s regimen (5%) or the AI’s regimen (about 2.5%).
• About three of four respondents (76.5%) agreed that oncologists should protect patients from biased AI tools; however, only about one of four (27.9%) felt confident they could identify biased AI models.
• Most oncologists (91%) felt that AI developers were responsible for the medico-legal problems associated with AI use; less than half (47%) said oncologists or hospitals (43%) shared this responsibility.

IN PRACTICE:

“Together, these data characterize barriers that may impede the ethical adoption of AI into cancer care. The findings suggest that the implementation of AI in oncology must include rigorous assessments of its effect on care decisions, as well as decisional responsibility when problems related to AI use arise,” the authors concluded.

SOURCE:

The study, with first author Andrew Hantel, MD, from Dana-Farber Cancer Institute, Boston, was published last month in JAMA Network Open.

LIMITATIONS:

The study had a moderate sample size and response rate, although demographics of participating oncologists appear to be nationally representative. The cross-sectional study design limited the generalizability of the findings over time as AI is integrated into cancer care.

DISCLOSURES:

The study was funded by the National Cancer Institute, the Dana-Farber McGraw/Patterson Research Fund, and the Mark Foundation Emerging Leader Award. Dr. Hantel reported receiving personal fees from AbbVie, AstraZeneca, the American Journal of Managed Care, Genentech, and GSK.

A version of this article appeared on Medscape.com.

TOPLINE:

A recent survey highlighted ethical concerns US oncologists have about using artificial intelligence (AI) to help make cancer treatment decisions and revealed some contradictory views about how best to integrate these tools into practice. Most respondents, for instance, said patients should not be expected to understand how AI tools work, but many also felt patients could make treatment decisions based on AI-generated recommendations. Most oncologists also felt responsible for protecting patients from biased AI, but few were confident that they could do so.

METHODOLOGY:

• The US Food and Drug Administration (FDA) has  for use in various medical specialties over the past few decades, and increasingly, AI tools are being integrated into cancer care.
• However, the uptake of these tools in oncology has raised ethical questions and concerns, including challenges with AI bias, error, or misuse, as well as issues explaining how an AI model reached a result.
• In the current study, researchers asked 204 oncologists from 37 states for their views on the ethical implications of using AI for cancer care.
• Among the survey respondents, 64% were men and 63% were non-Hispanic White; 29% were from academic practices, 47% had received some education on AI use in healthcare, and 45% were familiar with clinical decision models.
• The researchers assessed respondents’ answers to various questions, including whether to provide informed consent for AI use and how oncologists would approach a scenario where the AI model and the oncologist recommended a different treatment regimen.

TAKEAWAY:

• Overall, 81% of oncologists supported having patient consent to use an AI model during treatment decisions, and 85% felt that oncologists needed to be able to explain an AI-based clinical decision model to use it in the clinic; however, only 23% felt that patients also needed to be able to explain an AI model.
• When an AI decision model recommended a different treatment regimen than the treating oncologist, the most common response (36.8%) was to present both options to the patient and let the patient decide. Oncologists from academic settings were about 2.5 times more likely than those from other settings to let the patient decide. About 34% of respondents said they would present both options but recommend the oncologist’s regimen, whereas about 22% said they would present both but recommend the AI’s regimen. A small percentage would only present the oncologist’s regimen (5%) or the AI’s regimen (about 2.5%).
• About three of four respondents (76.5%) agreed that oncologists should protect patients from biased AI tools; however, only about one of four (27.9%) felt confident they could identify biased AI models.
• Most oncologists (91%) felt that AI developers were responsible for the medico-legal problems associated with AI use; less than half (47%) said oncologists or hospitals (43%) shared this responsibility.

IN PRACTICE:

“Together, these data characterize barriers that may impede the ethical adoption of AI into cancer care. The findings suggest that the implementation of AI in oncology must include rigorous assessments of its effect on care decisions, as well as decisional responsibility when problems related to AI use arise,” the authors concluded.

SOURCE:

The study, with first author Andrew Hantel, MD, from Dana-Farber Cancer Institute, Boston, was published last month in JAMA Network Open.

LIMITATIONS:

The study had a moderate sample size and response rate, although demographics of participating oncologists appear to be nationally representative. The cross-sectional study design limited the generalizability of the findings over time as AI is integrated into cancer care.

DISCLOSURES:

The study was funded by the National Cancer Institute, the Dana-Farber McGraw/Patterson Research Fund, and the Mark Foundation Emerging Leader Award. Dr. Hantel reported receiving personal fees from AbbVie, AstraZeneca, the American Journal of Managed Care, Genentech, and GSK.

A version of this article appeared on Medscape.com.

TOPLINE:

A recent survey highlighted ethical concerns US oncologists have about using artificial intelligence (AI) to help make cancer treatment decisions and revealed some contradictory views about how best to integrate these tools into practice. Most respondents, for instance, said patients should not be expected to understand how AI tools work, but many also felt patients could make treatment decisions based on AI-generated recommendations. Most oncologists also felt responsible for protecting patients from biased AI, but few were confident that they could do so.

METHODOLOGY:

• The US Food and Drug Administration (FDA) has  for use in various medical specialties over the past few decades, and increasingly, AI tools are being integrated into cancer care.
• However, the uptake of these tools in oncology has raised ethical questions and concerns, including challenges with AI bias, error, or misuse, as well as issues explaining how an AI model reached a result.
• In the current study, researchers asked 204 oncologists from 37 states for their views on the ethical implications of using AI for cancer care.
• Among the survey respondents, 64% were men and 63% were non-Hispanic White; 29% were from academic practices, 47% had received some education on AI use in healthcare, and 45% were familiar with clinical decision models.
• The researchers assessed respondents’ answers to various questions, including whether to provide informed consent for AI use and how oncologists would approach a scenario where the AI model and the oncologist recommended a different treatment regimen.

TAKEAWAY:

• Overall, 81% of oncologists supported having patient consent to use an AI model during treatment decisions, and 85% felt that oncologists needed to be able to explain an AI-based clinical decision model to use it in the clinic; however, only 23% felt that patients also needed to be able to explain an AI model.
• When an AI decision model recommended a different treatment regimen than the treating oncologist, the most common response (36.8%) was to present both options to the patient and let the patient decide. Oncologists from academic settings were about 2.5 times more likely than those from other settings to let the patient decide. About 34% of respondents said they would present both options but recommend the oncologist’s regimen, whereas about 22% said they would present both but recommend the AI’s regimen. A small percentage would only present the oncologist’s regimen (5%) or the AI’s regimen (about 2.5%).
• About three of four respondents (76.5%) agreed that oncologists should protect patients from biased AI tools; however, only about one of four (27.9%) felt confident they could identify biased AI models.
• Most oncologists (91%) felt that AI developers were responsible for the medico-legal problems associated with AI use; less than half (47%) said oncologists or hospitals (43%) shared this responsibility.

IN PRACTICE:

“Together, these data characterize barriers that may impede the ethical adoption of AI into cancer care. The findings suggest that the implementation of AI in oncology must include rigorous assessments of its effect on care decisions, as well as decisional responsibility when problems related to AI use arise,” the authors concluded.

SOURCE:

The study, with first author Andrew Hantel, MD, from Dana-Farber Cancer Institute, Boston, was published last month in JAMA Network Open.

LIMITATIONS:

The study had a moderate sample size and response rate, although demographics of participating oncologists appear to be nationally representative. The cross-sectional study design limited the generalizability of the findings over time as AI is integrated into cancer care.

DISCLOSURES:

The study was funded by the National Cancer Institute, the Dana-Farber McGraw/Patterson Research Fund, and the Mark Foundation Emerging Leader Award. Dr. Hantel reported receiving personal fees from AbbVie, AstraZeneca, the American Journal of Managed Care, Genentech, and GSK.

A version of this article appeared on Medscape.com.

The US Food and Drug Administration (FDA) has approved the launch of the first clinical trial for chimeric antigen receptor (CAR) T-cell therapy in children with systemic lupus erythematosus.

The trial, called Reversing Autoimmunity through Cell Therapy (REACT-01), will take place at Seattle Children’s Hospital in Washington State and is expected to begin this summer.

The CAR-T therapy will target CD19 positive B-cells, an approach that has had promising results in a small number of adult patients. While the FDA has approved a number of clinical trials using CAR-T therapy to treat autoimmune diseases in adults, this is the first authorization for a CAR T-cell therapy trial to treat autoimmune disease in children.

REACT-01 will enroll 12 individuals under 18 years of age, Shaun W. Jackson, MD, PhD, the principal investigator of the trial and attending physician in Pediatric Nephrology and Pediatric Rheumatology at Seattle Children’s Hospital, told this news organization. 

The trial will be initiated in separate phases, using three age cohorts. The first phase will enroll three individuals aged at least 17 years, before moving to the second phase and enrolling three individuals aged 12-17 years. Then, phase 3 will also include children aged 5-12 years.

To be eligible for the trial, participants must have failed at least two standard immunosuppressive therapies as well as have evidence of active lupus disease affecting a major organ system, such as the heart, lungs, and kidneys.

“Seattle Children’s Hospital will be the only site for this study, although patients can travel to Seattle to receive the therapy and then return back to their primary center for ongoing care,” Dr. Jackson said. 

A version of this article appeared on Medscape.com.

The US Food and Drug Administration (FDA) has approved the launch of the first clinical trial for chimeric antigen receptor (CAR) T-cell therapy in children with systemic lupus erythematosus.

The trial, called Reversing Autoimmunity through Cell Therapy (REACT-01), will take place at Seattle Children’s Hospital in Washington State and is expected to begin this summer.

The CAR-T therapy will target CD19 positive B-cells, an approach that has had promising results in a small number of adult patients. While the FDA has approved a number of clinical trials using CAR-T therapy to treat autoimmune diseases in adults, this is the first authorization for a CAR T-cell therapy trial to treat autoimmune disease in children.

REACT-01 will enroll 12 individuals under 18 years of age, Shaun W. Jackson, MD, PhD, the principal investigator of the trial and attending physician in Pediatric Nephrology and Pediatric Rheumatology at Seattle Children’s Hospital, told this news organization. 

The trial will be initiated in separate phases, using three age cohorts. The first phase will enroll three individuals aged at least 17 years, before moving to the second phase and enrolling three individuals aged 12-17 years. Then, phase 3 will also include children aged 5-12 years.

To be eligible for the trial, participants must have failed at least two standard immunosuppressive therapies as well as have evidence of active lupus disease affecting a major organ system, such as the heart, lungs, and kidneys.

“Seattle Children’s Hospital will be the only site for this study, although patients can travel to Seattle to receive the therapy and then return back to their primary center for ongoing care,” Dr. Jackson said. 

A version of this article appeared on Medscape.com.

The US Food and Drug Administration (FDA) has approved the launch of the first clinical trial for chimeric antigen receptor (CAR) T-cell therapy in children with systemic lupus erythematosus.

The trial, called Reversing Autoimmunity through Cell Therapy (REACT-01), will take place at Seattle Children’s Hospital in Washington State and is expected to begin this summer.

The CAR-T therapy will target CD19 positive B-cells, an approach that has had promising results in a small number of adult patients. While the FDA has approved a number of clinical trials using CAR-T therapy to treat autoimmune diseases in adults, this is the first authorization for a CAR T-cell therapy trial to treat autoimmune disease in children.

REACT-01 will enroll 12 individuals under 18 years of age, Shaun W. Jackson, MD, PhD, the principal investigator of the trial and attending physician in Pediatric Nephrology and Pediatric Rheumatology at Seattle Children’s Hospital, told this news organization. 

The trial will be initiated in separate phases, using three age cohorts. The first phase will enroll three individuals aged at least 17 years, before moving to the second phase and enrolling three individuals aged 12-17 years. Then, phase 3 will also include children aged 5-12 years.

To be eligible for the trial, participants must have failed at least two standard immunosuppressive therapies as well as have evidence of active lupus disease affecting a major organ system, such as the heart, lungs, and kidneys.

“Seattle Children’s Hospital will be the only site for this study, although patients can travel to Seattle to receive the therapy and then return back to their primary center for ongoing care,” Dr. Jackson said. 

A version of this article appeared on Medscape.com.

Physicians who misuse the “copy-and-paste” feature in patients’ electronic health records (EHRs) can face serious consequences, including lost hospital privileges, fines, and malpractice lawsuits.

In California, a locum tenens physician lost her hospital privileges after repeatedly violating the copy-and-paste policy developed at Santa Rosa Memorial Hospital, Santa Rosa, California.

“Her use of copy and paste impaired continuity of care,” said Alvin Gore, MD, who was involved in the case as the hospital’s director of utilization management.

Dr. Gore said the hospital warned the doctor, but she did not change her behavior. He did not identify the physician, citing confidentiality. The case occurred more than 5 years ago. Since then, several physicians have been called onto the carpet for violations of the policy, but no one else has lost privileges, Dr. Gore said.

Copy-paste practices can save doctors’ time when dealing with cumbersome EHR systems, but they also can lead to redundant, outdated, or inconsistent information that can compromise patient care, experts said.

“EHRs are imperfect, time consuming, and somewhat rigid,” said Robert A. Dowling, MD, a practice management consultant for large medical groups. “If physicians can’t easily figure out a complex system, they’re likely to use a workaround like copy and paste.”

Copy-and-paste abuse has also led to fines. A six-member cardiology group in Somerville, New Jersey, paid a $422,000 fine to the federal government to settle copy-and-paste charges, following an investigation by the Office of the Inspector General of the Department of Health and Human Services, according to the Report on Medicare Compliance.

This big settlement, announced in 2016, is a rare case in which physicians were charged with copy-and-paste fraud — intentionally using it to enhance reimbursement.

More commonly, Medicare contractors identify physicians who unintentionally received overpayments through sloppy copy-and-paste practices, according to a coding and documentation auditor who worked for 10 years at a Medicare contractor in Pennsylvania.

Such cases are frequent and are handled confidentially, said the auditor, who asked not to be identified. Practices must return the overpayment, and the physicians involved are “contacted and educated,” she said.

Copy and paste can also show up in malpractice lawsuits. In a 2012 survey, 53% of professional liability carriers said they had handled an EHR-related malpractice claim, and 71% of those claims included copy-and-paste use.

One such case, described by CRICO, a malpractice carrier based in Massachusetts, took place in 2012-2013. “A patient developed amiodarone toxicity because the patient›s history and medications were copied from a previous note that did not document that the patient was already on the medication,» CRICO stated.

“If you do face a malpractice claim, copying and pasting the same note repeatedly makes you look clinically inattentive, even if the copy/pasted material is unrelated to the adverse event,” CRICO officials noted in a report.
 

The Push to Use Copy and Paste

Copy and paste is a great time-saver. One study linked its use to lower burnout rates. However, it can easily introduce errors into the medical record. “This can be a huge problem,” Dr. Dowling said. “If, for example, you copy forward a previous note that said the patient had blood in their urine ‘6 days ago,’ it is immediately inaccurate.”

Practices can control use of copy and paste through coding clerks who read the medical records and then educate doctors when problems crop up.

The Pennsylvania auditor, who now works for a large group practice, said the group has very few copy-and-paste problems because of her role. “Not charting responsibly rarely happens because I work very closely with the doctors,” she said.

Dr. Dowling, however, reports that many physicians continue to overuse copy and paste. He points to a 2022 study which found that, on average, half the clinical note at one health system had been copied and pasted.

One solution might be to sanction physicians for overusing copy and paste, just as they’re sometimes penalized for not completing their notes on time with a reduction in income or possible termination.

Practices could periodically audit medical records for excessive copy-paste use. EHR systems like Epic’s can indicate how much of a doctor’s note has been copied. But Dr. Dowling doesn’t know of any practices that do this.

“There is little appetite to introduce a new enforcement activity for physicians,” he said. “Physicians would see it just as a way to make their lives more difficult than they already are.”
 

Monitoring in Hospitals and Health Systems

Some hospitals and health systems have gone as far as disabling copy-and-paste function in their EHR systems. However, enterprising physicians have found ways around these blocks.

Some institutions have also introduced formal policies, directing doctors on how they can copy and paste, including Banner Health in Arizona, Northwell Health in New York, UConn Health in Connecticut, University of Maryland Medical System, and University of Toledo in Ohio.

Definitions of what is not acceptable vary, but most of these policies oppose copying someone else’s notes and direct physicians to indicate the origin of pasted material.

Santa Rosa Memorial’s policy is quite specific. It still allows some copy and paste but stipulates that it cannot be used for the chief complaint, the review of systems, the physical examination, and the assessment and plan in the medical record, except when the information can’t be obtained directly from the patient. Also, physicians must summarize test results and provide references to other providers’ notes.

Dr. Gore said he and a physician educator who works with physicians on clinical documentation proposed the policy about a decade ago. When physicians on staff were asked to comment, some said they would be opposed to a complete ban, but they generally agreed that copy and paste was a serious problem that needed to be addressed, he said.

The hospital could have simply adopted guidelines, as opposed to rules with consequences, but “we wanted our policy to have teeth,” Dr. Gore said.

When violators are identified, Dr. Gore says he meets with them confidentially and educates them on proper use of copy and paste. Sometimes, the department head is brought in. Some physicians go on to violate the policy again and have to attend another meeting, he said, but aside from the one case, no one else has been disciplined.

It’s unclear how many physicians have faced consequences for misusing copy-paste features — such data aren’t tracked, and sanctions are likely to be handled confidentially, as a personnel matter.

Geisinger Health in Pennsylvania regularly monitors copy-and-paste usage and makes it part of physicians’ professional evaluations, according to a 2022 presentation by a Geisinger official.

Meanwhile, even when systems don’t have specific policies, they may still discipline physicians when copy and paste leads to errors. Scott MacDonald, MD, chief medical information officer at UC Davis Health in Sacramento, California, told this news organization that copy-and-paste abuse has come up a few times over the years in investigations of clinical errors.
 

Holding Physicians Accountable

Physicians can be held accountable for copy and paste by Medicare contractors and in malpractice lawsuits, but the most obvious way is at their place of work: A practice, hospital, or health system.

One physician has lost staff privileges, but more typically, coding clerks or colleagues talk to offending physicians and try to educate them on proper use of copy and paste.

Educational outreach, however, is often ineffective, said Robert Hirschtick, MD, a retired teaching physician at Northwestern University Feinberg School of Medicine, Chicago, Illinois. “The physician may be directed to take an online course,” he said. “When they take the course, the goal is to get it done with, rather than to learn something new.”

Dr. Hirschtick’s articles on copy and paste, including one titled, “Sloppy and Paste,” have put him at the front lines of the debate. “This is an ethical issue,” he said in an interview. He agrees that some forms of copy and paste are permissible, but in many cases, “it is intellectually dishonest and potentially even plagiarism,” he said.

Dr. Hirschtick argues that copy-and-paste policies need more teeth. “Tying violations to compensation would be quite effective,” he said. “Even if physicians were rarely penalized, just knowing that it could happen to you might be enough. But I haven’t heard of anyone doing this.”

A version of this article appeared on Medscape.com.

Physicians who misuse the “copy-and-paste” feature in patients’ electronic health records (EHRs) can face serious consequences, including lost hospital privileges, fines, and malpractice lawsuits.

In California, a locum tenens physician lost her hospital privileges after repeatedly violating the copy-and-paste policy developed at Santa Rosa Memorial Hospital, Santa Rosa, California.

“Her use of copy and paste impaired continuity of care,” said Alvin Gore, MD, who was involved in the case as the hospital’s director of utilization management.

Dr. Gore said the hospital warned the doctor, but she did not change her behavior. He did not identify the physician, citing confidentiality. The case occurred more than 5 years ago. Since then, several physicians have been called onto the carpet for violations of the policy, but no one else has lost privileges, Dr. Gore said.

Copy-paste practices can save doctors’ time when dealing with cumbersome EHR systems, but they also can lead to redundant, outdated, or inconsistent information that can compromise patient care, experts said.

“EHRs are imperfect, time consuming, and somewhat rigid,” said Robert A. Dowling, MD, a practice management consultant for large medical groups. “If physicians can’t easily figure out a complex system, they’re likely to use a workaround like copy and paste.”

Copy-and-paste abuse has also led to fines. A six-member cardiology group in Somerville, New Jersey, paid a $422,000 fine to the federal government to settle copy-and-paste charges, following an investigation by the Office of the Inspector General of the Department of Health and Human Services, according to the Report on Medicare Compliance.

This big settlement, announced in 2016, is a rare case in which physicians were charged with copy-and-paste fraud — intentionally using it to enhance reimbursement.

More commonly, Medicare contractors identify physicians who unintentionally received overpayments through sloppy copy-and-paste practices, according to a coding and documentation auditor who worked for 10 years at a Medicare contractor in Pennsylvania.

Such cases are frequent and are handled confidentially, said the auditor, who asked not to be identified. Practices must return the overpayment, and the physicians involved are “contacted and educated,” she said.

Copy and paste can also show up in malpractice lawsuits. In a 2012 survey, 53% of professional liability carriers said they had handled an EHR-related malpractice claim, and 71% of those claims included copy-and-paste use.

One such case, described by CRICO, a malpractice carrier based in Massachusetts, took place in 2012-2013. “A patient developed amiodarone toxicity because the patient›s history and medications were copied from a previous note that did not document that the patient was already on the medication,» CRICO stated.

“If you do face a malpractice claim, copying and pasting the same note repeatedly makes you look clinically inattentive, even if the copy/pasted material is unrelated to the adverse event,” CRICO officials noted in a report.
 

The Push to Use Copy and Paste

Copy and paste is a great time-saver. One study linked its use to lower burnout rates. However, it can easily introduce errors into the medical record. “This can be a huge problem,” Dr. Dowling said. “If, for example, you copy forward a previous note that said the patient had blood in their urine ‘6 days ago,’ it is immediately inaccurate.”

Practices can control use of copy and paste through coding clerks who read the medical records and then educate doctors when problems crop up.

The Pennsylvania auditor, who now works for a large group practice, said the group has very few copy-and-paste problems because of her role. “Not charting responsibly rarely happens because I work very closely with the doctors,” she said.

Dr. Dowling, however, reports that many physicians continue to overuse copy and paste. He points to a 2022 study which found that, on average, half the clinical note at one health system had been copied and pasted.

One solution might be to sanction physicians for overusing copy and paste, just as they’re sometimes penalized for not completing their notes on time with a reduction in income or possible termination.

Practices could periodically audit medical records for excessive copy-paste use. EHR systems like Epic’s can indicate how much of a doctor’s note has been copied. But Dr. Dowling doesn’t know of any practices that do this.

“There is little appetite to introduce a new enforcement activity for physicians,” he said. “Physicians would see it just as a way to make their lives more difficult than they already are.”
 

Monitoring in Hospitals and Health Systems

Some hospitals and health systems have gone as far as disabling copy-and-paste function in their EHR systems. However, enterprising physicians have found ways around these blocks.

Some institutions have also introduced formal policies, directing doctors on how they can copy and paste, including Banner Health in Arizona, Northwell Health in New York, UConn Health in Connecticut, University of Maryland Medical System, and University of Toledo in Ohio.

Definitions of what is not acceptable vary, but most of these policies oppose copying someone else’s notes and direct physicians to indicate the origin of pasted material.

Santa Rosa Memorial’s policy is quite specific. It still allows some copy and paste but stipulates that it cannot be used for the chief complaint, the review of systems, the physical examination, and the assessment and plan in the medical record, except when the information can’t be obtained directly from the patient. Also, physicians must summarize test results and provide references to other providers’ notes.

Dr. Gore said he and a physician educator who works with physicians on clinical documentation proposed the policy about a decade ago. When physicians on staff were asked to comment, some said they would be opposed to a complete ban, but they generally agreed that copy and paste was a serious problem that needed to be addressed, he said.

The hospital could have simply adopted guidelines, as opposed to rules with consequences, but “we wanted our policy to have teeth,” Dr. Gore said.

When violators are identified, Dr. Gore says he meets with them confidentially and educates them on proper use of copy and paste. Sometimes, the department head is brought in. Some physicians go on to violate the policy again and have to attend another meeting, he said, but aside from the one case, no one else has been disciplined.

It’s unclear how many physicians have faced consequences for misusing copy-paste features — such data aren’t tracked, and sanctions are likely to be handled confidentially, as a personnel matter.

Geisinger Health in Pennsylvania regularly monitors copy-and-paste usage and makes it part of physicians’ professional evaluations, according to a 2022 presentation by a Geisinger official.

Meanwhile, even when systems don’t have specific policies, they may still discipline physicians when copy and paste leads to errors. Scott MacDonald, MD, chief medical information officer at UC Davis Health in Sacramento, California, told this news organization that copy-and-paste abuse has come up a few times over the years in investigations of clinical errors.
 

Holding Physicians Accountable

Physicians can be held accountable for copy and paste by Medicare contractors and in malpractice lawsuits, but the most obvious way is at their place of work: A practice, hospital, or health system.

One physician has lost staff privileges, but more typically, coding clerks or colleagues talk to offending physicians and try to educate them on proper use of copy and paste.

Educational outreach, however, is often ineffective, said Robert Hirschtick, MD, a retired teaching physician at Northwestern University Feinberg School of Medicine, Chicago, Illinois. “The physician may be directed to take an online course,” he said. “When they take the course, the goal is to get it done with, rather than to learn something new.”

Dr. Hirschtick’s articles on copy and paste, including one titled, “Sloppy and Paste,” have put him at the front lines of the debate. “This is an ethical issue,” he said in an interview. He agrees that some forms of copy and paste are permissible, but in many cases, “it is intellectually dishonest and potentially even plagiarism,” he said.

Dr. Hirschtick argues that copy-and-paste policies need more teeth. “Tying violations to compensation would be quite effective,” he said. “Even if physicians were rarely penalized, just knowing that it could happen to you might be enough. But I haven’t heard of anyone doing this.”

A version of this article appeared on Medscape.com.

Physicians who misuse the “copy-and-paste” feature in patients’ electronic health records (EHRs) can face serious consequences, including lost hospital privileges, fines, and malpractice lawsuits.

In California, a locum tenens physician lost her hospital privileges after repeatedly violating the copy-and-paste policy developed at Santa Rosa Memorial Hospital, Santa Rosa, California.

“Her use of copy and paste impaired continuity of care,” said Alvin Gore, MD, who was involved in the case as the hospital’s director of utilization management.

Dr. Gore said the hospital warned the doctor, but she did not change her behavior. He did not identify the physician, citing confidentiality. The case occurred more than 5 years ago. Since then, several physicians have been called onto the carpet for violations of the policy, but no one else has lost privileges, Dr. Gore said.

Copy-paste practices can save doctors’ time when dealing with cumbersome EHR systems, but they also can lead to redundant, outdated, or inconsistent information that can compromise patient care, experts said.

“EHRs are imperfect, time consuming, and somewhat rigid,” said Robert A. Dowling, MD, a practice management consultant for large medical groups. “If physicians can’t easily figure out a complex system, they’re likely to use a workaround like copy and paste.”

Copy-and-paste abuse has also led to fines. A six-member cardiology group in Somerville, New Jersey, paid a $422,000 fine to the federal government to settle copy-and-paste charges, following an investigation by the Office of the Inspector General of the Department of Health and Human Services, according to the Report on Medicare Compliance.

This big settlement, announced in 2016, is a rare case in which physicians were charged with copy-and-paste fraud — intentionally using it to enhance reimbursement.

More commonly, Medicare contractors identify physicians who unintentionally received overpayments through sloppy copy-and-paste practices, according to a coding and documentation auditor who worked for 10 years at a Medicare contractor in Pennsylvania.

Such cases are frequent and are handled confidentially, said the auditor, who asked not to be identified. Practices must return the overpayment, and the physicians involved are “contacted and educated,” she said.

Copy and paste can also show up in malpractice lawsuits. In a 2012 survey, 53% of professional liability carriers said they had handled an EHR-related malpractice claim, and 71% of those claims included copy-and-paste use.

One such case, described by CRICO, a malpractice carrier based in Massachusetts, took place in 2012-2013. “A patient developed amiodarone toxicity because the patient›s history and medications were copied from a previous note that did not document that the patient was already on the medication,» CRICO stated.

“If you do face a malpractice claim, copying and pasting the same note repeatedly makes you look clinically inattentive, even if the copy/pasted material is unrelated to the adverse event,” CRICO officials noted in a report.
 

The Push to Use Copy and Paste

Copy and paste is a great time-saver. One study linked its use to lower burnout rates. However, it can easily introduce errors into the medical record. “This can be a huge problem,” Dr. Dowling said. “If, for example, you copy forward a previous note that said the patient had blood in their urine ‘6 days ago,’ it is immediately inaccurate.”

Practices can control use of copy and paste through coding clerks who read the medical records and then educate doctors when problems crop up.

The Pennsylvania auditor, who now works for a large group practice, said the group has very few copy-and-paste problems because of her role. “Not charting responsibly rarely happens because I work very closely with the doctors,” she said.

Dr. Dowling, however, reports that many physicians continue to overuse copy and paste. He points to a 2022 study which found that, on average, half the clinical note at one health system had been copied and pasted.

One solution might be to sanction physicians for overusing copy and paste, just as they’re sometimes penalized for not completing their notes on time with a reduction in income or possible termination.

Practices could periodically audit medical records for excessive copy-paste use. EHR systems like Epic’s can indicate how much of a doctor’s note has been copied. But Dr. Dowling doesn’t know of any practices that do this.

“There is little appetite to introduce a new enforcement activity for physicians,” he said. “Physicians would see it just as a way to make their lives more difficult than they already are.”
 

Monitoring in Hospitals and Health Systems

Some hospitals and health systems have gone as far as disabling copy-and-paste function in their EHR systems. However, enterprising physicians have found ways around these blocks.

Some institutions have also introduced formal policies, directing doctors on how they can copy and paste, including Banner Health in Arizona, Northwell Health in New York, UConn Health in Connecticut, University of Maryland Medical System, and University of Toledo in Ohio.

Definitions of what is not acceptable vary, but most of these policies oppose copying someone else’s notes and direct physicians to indicate the origin of pasted material.

Santa Rosa Memorial’s policy is quite specific. It still allows some copy and paste but stipulates that it cannot be used for the chief complaint, the review of systems, the physical examination, and the assessment and plan in the medical record, except when the information can’t be obtained directly from the patient. Also, physicians must summarize test results and provide references to other providers’ notes.

Dr. Gore said he and a physician educator who works with physicians on clinical documentation proposed the policy about a decade ago. When physicians on staff were asked to comment, some said they would be opposed to a complete ban, but they generally agreed that copy and paste was a serious problem that needed to be addressed, he said.

The hospital could have simply adopted guidelines, as opposed to rules with consequences, but “we wanted our policy to have teeth,” Dr. Gore said.

When violators are identified, Dr. Gore says he meets with them confidentially and educates them on proper use of copy and paste. Sometimes, the department head is brought in. Some physicians go on to violate the policy again and have to attend another meeting, he said, but aside from the one case, no one else has been disciplined.

It’s unclear how many physicians have faced consequences for misusing copy-paste features — such data aren’t tracked, and sanctions are likely to be handled confidentially, as a personnel matter.

Geisinger Health in Pennsylvania regularly monitors copy-and-paste usage and makes it part of physicians’ professional evaluations, according to a 2022 presentation by a Geisinger official.

Meanwhile, even when systems don’t have specific policies, they may still discipline physicians when copy and paste leads to errors. Scott MacDonald, MD, chief medical information officer at UC Davis Health in Sacramento, California, told this news organization that copy-and-paste abuse has come up a few times over the years in investigations of clinical errors.
 

Holding Physicians Accountable

Physicians can be held accountable for copy and paste by Medicare contractors and in malpractice lawsuits, but the most obvious way is at their place of work: A practice, hospital, or health system.

One physician has lost staff privileges, but more typically, coding clerks or colleagues talk to offending physicians and try to educate them on proper use of copy and paste.

Educational outreach, however, is often ineffective, said Robert Hirschtick, MD, a retired teaching physician at Northwestern University Feinberg School of Medicine, Chicago, Illinois. “The physician may be directed to take an online course,” he said. “When they take the course, the goal is to get it done with, rather than to learn something new.”

Dr. Hirschtick’s articles on copy and paste, including one titled, “Sloppy and Paste,” have put him at the front lines of the debate. “This is an ethical issue,” he said in an interview. He agrees that some forms of copy and paste are permissible, but in many cases, “it is intellectually dishonest and potentially even plagiarism,” he said.

Dr. Hirschtick argues that copy-and-paste policies need more teeth. “Tying violations to compensation would be quite effective,” he said. “Even if physicians were rarely penalized, just knowing that it could happen to you might be enough. But I haven’t heard of anyone doing this.”

A version of this article appeared on Medscape.com.

Benralizumab is now approved by the US Food and Drug Administration (FDA) for the treatment of asthma in children older than 6 years. 

Marketed as Fasenra, the medication first was approved in 2017 for patients aged 12 years or older. The drug is approved as a maintenance add-on for patients with severe eosinophilic asthma. 

AstraZeneca, which markets the drug, announced the approval for younger patients on April 11. 

The expanded indication was supported by a study that showed that the drug functions in the same way with younger children and their adolescent peers. The safety and tolerability were also consistent with the known profile of the medicine, the company said. 

For children who weigh ≥ 35 kg, the recommended dose is 30 mg. For patients aged 6-11 years who weigh < 35 kg, a new 10-mg dose will be available, according to the announcement. 

The drug, a monoclonal antibody that depletes eosinophils by binding to interleukin 5 receptor alpha on eosinophils, is administered by subcutaneous injection every 4 weeks for the first three doses and then every 8 weeks.

Benralizumab should not be used to treat acute asthma symptoms. Hypersensitivity reasons have occurred after administration of the drug. The most common adverse reactions include headache and pharyngitis.
 

A version of this article appeared on Medscape.com.

Benralizumab is now approved by the US Food and Drug Administration (FDA) for the treatment of asthma in children older than 6 years. 

Marketed as Fasenra, the medication first was approved in 2017 for patients aged 12 years or older. The drug is approved as a maintenance add-on for patients with severe eosinophilic asthma. 

AstraZeneca, which markets the drug, announced the approval for younger patients on April 11. 

The expanded indication was supported by a study that showed that the drug functions in the same way with younger children and their adolescent peers. The safety and tolerability were also consistent with the known profile of the medicine, the company said. 

For children who weigh ≥ 35 kg, the recommended dose is 30 mg. For patients aged 6-11 years who weigh < 35 kg, a new 10-mg dose will be available, according to the announcement. 

The drug, a monoclonal antibody that depletes eosinophils by binding to interleukin 5 receptor alpha on eosinophils, is administered by subcutaneous injection every 4 weeks for the first three doses and then every 8 weeks.

Benralizumab should not be used to treat acute asthma symptoms. Hypersensitivity reasons have occurred after administration of the drug. The most common adverse reactions include headache and pharyngitis.
 

A version of this article appeared on Medscape.com.

Benralizumab is now approved by the US Food and Drug Administration (FDA) for the treatment of asthma in children older than 6 years. 

Marketed as Fasenra, the medication first was approved in 2017 for patients aged 12 years or older. The drug is approved as a maintenance add-on for patients with severe eosinophilic asthma. 

AstraZeneca, which markets the drug, announced the approval for younger patients on April 11. 

The expanded indication was supported by a study that showed that the drug functions in the same way with younger children and their adolescent peers. The safety and tolerability were also consistent with the known profile of the medicine, the company said. 

For children who weigh ≥ 35 kg, the recommended dose is 30 mg. For patients aged 6-11 years who weigh < 35 kg, a new 10-mg dose will be available, according to the announcement. 

The drug, a monoclonal antibody that depletes eosinophils by binding to interleukin 5 receptor alpha on eosinophils, is administered by subcutaneous injection every 4 weeks for the first three doses and then every 8 weeks.

Benralizumab should not be used to treat acute asthma symptoms. Hypersensitivity reasons have occurred after administration of the drug. The most common adverse reactions include headache and pharyngitis.
 

A version of this article appeared on Medscape.com.