Kerri Wachter

The number of cancer survivors in the United States rose from 3 million in 1971 and 9.8 million in 2001 to 11.5 million in 2007, according to a new report by the Centers for Disease Control and Prevention and the National Cancer Institute.

The numbers come from the study "Cancer Survivors in the United States, 2007," which is published in the CDC’s March 11th Morbidity and Mortality Weekly Report. The study authors defined a cancer survivor as "a person living with a history of cancer."

The new numbers highlight the need for more research on the unique physical, psychological, and social issues facing cancer survivors. There is now "a growing number of people who have faced a cancer diagnosis which affects them and their loved ones – from the time of diagnosis through the rest of their lives," the NCI’s Julia H. Rowland, Ph.D., said in a press release. "Unfortunately for many cancer survivors and those around them, the effect of cancer does not end with the last treatment. ... This report underscores the need for continued research, as well as for the development and implementation of best practices to provide optimal care and support for all cancer survivors." Dr. Rowland is the director of the NCI’s Office of Cancer Survivorship.

The study authors analyzed the number of new cancer cases (except in situ and nonmelanoma skin cancers) as well as follow-up data from the NCI’s SEER (Surveillance, Epidemiology and End Results) program in 1971-2006. They estimated the number of persons who were ever diagnosed with cancer and were alive on Jan. 1, 2007 (MMWR 2011;60:269-72).

Notably, 65% of cancer survivors on Jan. 1, 2007, received their diagnosis at least 5 years earlier. Also, people aged 65 years or older accounted for 60%. The largest group of cancer survivors was breast cancer survivors (22%), followed by prostate cancer survivors (19%) and colorectal cancer survivors (10%). Women accounted for slightly more than half (54%) of all survivors.

Clinicians can find research tools, publications and other resources through the NCI’s Office of Cancer Survivorship.

The number of cancer survivors in the United States rose from 3 million in 1971 and 9.8 million in 2001 to 11.5 million in 2007, according to a new report by the Centers for Disease Control and Prevention and the National Cancer Institute.

The numbers come from the study "Cancer Survivors in the United States, 2007," which is published in the CDC’s March 11th Morbidity and Mortality Weekly Report. The study authors defined a cancer survivor as "a person living with a history of cancer."

The new numbers highlight the need for more research on the unique physical, psychological, and social issues facing cancer survivors. There is now "a growing number of people who have faced a cancer diagnosis which affects them and their loved ones – from the time of diagnosis through the rest of their lives," the NCI’s Julia H. Rowland, Ph.D., said in a press release. "Unfortunately for many cancer survivors and those around them, the effect of cancer does not end with the last treatment. ... This report underscores the need for continued research, as well as for the development and implementation of best practices to provide optimal care and support for all cancer survivors." Dr. Rowland is the director of the NCI’s Office of Cancer Survivorship.

The study authors analyzed the number of new cancer cases (except in situ and nonmelanoma skin cancers) as well as follow-up data from the NCI’s SEER (Surveillance, Epidemiology and End Results) program in 1971-2006. They estimated the number of persons who were ever diagnosed with cancer and were alive on Jan. 1, 2007 (MMWR 2011;60:269-72).

Notably, 65% of cancer survivors on Jan. 1, 2007, received their diagnosis at least 5 years earlier. Also, people aged 65 years or older accounted for 60%. The largest group of cancer survivors was breast cancer survivors (22%), followed by prostate cancer survivors (19%) and colorectal cancer survivors (10%). Women accounted for slightly more than half (54%) of all survivors.

Clinicians can find research tools, publications and other resources through the NCI’s Office of Cancer Survivorship.

The number of cancer survivors in the United States rose from 3 million in 1971 and 9.8 million in 2001 to 11.5 million in 2007, according to a new report by the Centers for Disease Control and Prevention and the National Cancer Institute.

The numbers come from the study "Cancer Survivors in the United States, 2007," which is published in the CDC’s March 11th Morbidity and Mortality Weekly Report. The study authors defined a cancer survivor as "a person living with a history of cancer."

The new numbers highlight the need for more research on the unique physical, psychological, and social issues facing cancer survivors. There is now "a growing number of people who have faced a cancer diagnosis which affects them and their loved ones – from the time of diagnosis through the rest of their lives," the NCI’s Julia H. Rowland, Ph.D., said in a press release. "Unfortunately for many cancer survivors and those around them, the effect of cancer does not end with the last treatment. ... This report underscores the need for continued research, as well as for the development and implementation of best practices to provide optimal care and support for all cancer survivors." Dr. Rowland is the director of the NCI’s Office of Cancer Survivorship.

The study authors analyzed the number of new cancer cases (except in situ and nonmelanoma skin cancers) as well as follow-up data from the NCI’s SEER (Surveillance, Epidemiology and End Results) program in 1971-2006. They estimated the number of persons who were ever diagnosed with cancer and were alive on Jan. 1, 2007 (MMWR 2011;60:269-72).

Notably, 65% of cancer survivors on Jan. 1, 2007, received their diagnosis at least 5 years earlier. Also, people aged 65 years or older accounted for 60%. The largest group of cancer survivors was breast cancer survivors (22%), followed by prostate cancer survivors (19%) and colorectal cancer survivors (10%). Women accounted for slightly more than half (54%) of all survivors.

Clinicians can find research tools, publications and other resources through the NCI’s Office of Cancer Survivorship.

The number of cancer survivors in the United States rose from 3 million in 1971 and 9.8 million in 2001 to 11.5 million in 2007, according to a new report by the Centers for Disease Control and Prevention and the National Cancer Institute.

The numbers come from the study "Cancer Survivors in the United States, 2007," which is published in the CDC's March 11th Morbidity and Mortality Weekly Report. The study authors defined a cancer survivor as "a person living with a history of cancer."

The new numbers highlight the need for more research on the unique physical, psychological, and social issues facing cancer survivors. There is now "a growing number of people who have faced a cancer diagnosis which affects them and their loved ones – from the time of diagnosis through the rest of their lives," the NCI’s Julia H. Rowland, Ph.D., said in a press release. "Unfortunately for many cancer survivors and those around them, the effect of cancer does not end with the last treatment. ... This report underscores the need for continued research, as well as for the development and implementation of best practices to provide optimal care and support for all cancer survivors." Dr. Rowland is the director of the NCI's Office of Cancer Survivorship.

The study authors analyzed the number of new cancer cases (except in situ and nonmelanoma skin cancers) as well as follow-up data from the NCI's SEER (Surveillance, Epidemiology and End Results) program in 1971-2006. They estimated the number of persons who were ever diagnosed with cancer and were alive on Jan. 1, 2007 (MMWR 2011;60:269-72).

Notably, 65% of cancer survivors on Jan. 1, 2007, received their diagnosis at least 5 years earlier. Also, people aged 65 years or older accounted for 60%. The largest group of cancer survivors was breast cancer survivors (22%), followed by prostate cancer survivors (19%) and colorectal cancer survivors (10%). Women accounted for slightly more than half (54%) of all survivors.

Clinicians can find research tools, publications and other resources through the NCI's Office of Cancer Survivorship.

The number of cancer survivors in the United States rose from 3 million in 1971 and 9.8 million in 2001 to 11.5 million in 2007, according to a new report by the Centers for Disease Control and Prevention and the National Cancer Institute.

The numbers come from the study "Cancer Survivors in the United States, 2007," which is published in the CDC's March 11th Morbidity and Mortality Weekly Report. The study authors defined a cancer survivor as "a person living with a history of cancer."

The new numbers highlight the need for more research on the unique physical, psychological, and social issues facing cancer survivors. There is now "a growing number of people who have faced a cancer diagnosis which affects them and their loved ones – from the time of diagnosis through the rest of their lives," the NCI’s Julia H. Rowland, Ph.D., said in a press release. "Unfortunately for many cancer survivors and those around them, the effect of cancer does not end with the last treatment. ... This report underscores the need for continued research, as well as for the development and implementation of best practices to provide optimal care and support for all cancer survivors." Dr. Rowland is the director of the NCI's Office of Cancer Survivorship.

The study authors analyzed the number of new cancer cases (except in situ and nonmelanoma skin cancers) as well as follow-up data from the NCI's SEER (Surveillance, Epidemiology and End Results) program in 1971-2006. They estimated the number of persons who were ever diagnosed with cancer and were alive on Jan. 1, 2007 (MMWR 2011;60:269-72).

Notably, 65% of cancer survivors on Jan. 1, 2007, received their diagnosis at least 5 years earlier. Also, people aged 65 years or older accounted for 60%. The largest group of cancer survivors was breast cancer survivors (22%), followed by prostate cancer survivors (19%) and colorectal cancer survivors (10%). Women accounted for slightly more than half (54%) of all survivors.

Clinicians can find research tools, publications and other resources through the NCI's Office of Cancer Survivorship.

The number of cancer survivors in the United States rose from 3 million in 1971 and 9.8 million in 2001 to 11.5 million in 2007, according to a new report by the Centers for Disease Control and Prevention and the National Cancer Institute.

The numbers come from the study "Cancer Survivors in the United States, 2007," which is published in the CDC's March 11th Morbidity and Mortality Weekly Report. The study authors defined a cancer survivor as "a person living with a history of cancer."

The new numbers highlight the need for more research on the unique physical, psychological, and social issues facing cancer survivors. There is now "a growing number of people who have faced a cancer diagnosis which affects them and their loved ones – from the time of diagnosis through the rest of their lives," the NCI’s Julia H. Rowland, Ph.D., said in a press release. "Unfortunately for many cancer survivors and those around them, the effect of cancer does not end with the last treatment. ... This report underscores the need for continued research, as well as for the development and implementation of best practices to provide optimal care and support for all cancer survivors." Dr. Rowland is the director of the NCI's Office of Cancer Survivorship.

The study authors analyzed the number of new cancer cases (except in situ and nonmelanoma skin cancers) as well as follow-up data from the NCI's SEER (Surveillance, Epidemiology and End Results) program in 1971-2006. They estimated the number of persons who were ever diagnosed with cancer and were alive on Jan. 1, 2007 (MMWR 2011;60:269-72).

Notably, 65% of cancer survivors on Jan. 1, 2007, received their diagnosis at least 5 years earlier. Also, people aged 65 years or older accounted for 60%. The largest group of cancer survivors was breast cancer survivors (22%), followed by prostate cancer survivors (19%) and colorectal cancer survivors (10%). Women accounted for slightly more than half (54%) of all survivors.

Clinicians can find research tools, publications and other resources through the NCI's Office of Cancer Survivorship.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

A slower decline in salivary cortisol measurements throughout the day appear to be associated with an increased risk in cardiovascular-related death, based on an analysis of diurnal samples from more than 4,000 individuals.

"This is the first study to show that diurnal patterns in cortisol release across the day are predictive of subsequent cardiovascular-related mortality in men and women. Our findings suggest that slope in cortisol is related to cardiovascular-related mortality, comprising a raised late-evening level of cortisol rather than a depressed morning level," wrote Meena Kumari, Ph.D., and her colleagues at the department of epidemiology and public health at University College London.

However, the data don’t suggest any significant association between cortisol slope and noncardiovascular-related mortality. Likewise, no association was apparent for the cortisol awakening response (CAR).

Many studies have investigated a possible association between cortisol levels and cardiovascular disease, using serum or plasma cortisol as a biomarker for stress. However, the results so far have been equivocal. The authors noted that the diurnal rhythm in cortisol release is likely to be a contributing factor to inconsistencies between studies (J. Clin. Endocrinol. Metab. 2011 Feb. 23 [doi:10.1210/jc.2010-2137]).

The general cortisol pattern is characterized by a relatively high cortisol level at waking that is followed by a peak in cortisol at 30 minutes after waking, followed by a decline across the day reaching the bottom of the trough at midnight.

In this study, the researchers analyzed sequential salivary samples taken from waking to bedtime in individuals from phase 7 (2002-2004) of the Whitehall II study, which was initially recruited during 1985-1988 (phase 1) from 20 London-based civil service departments.

Diurnal cortisol patterns could be determined from six saliva samples obtained over the course of a normal weekday: at waking, 30 minutes later, 2.5 hours later, 8 hours later, 12 hours later, and at bedtime. Data from the Whitehall study II also include measurement of conventional risk factors and a follow-up of overall, cardiovascular, and noncardiovascular deaths based on comprehensive medical records.

In all, 6,941 individuals participated in phase 7 with a mean age of 61 years. Saliva sample collection was initiated part way through phase 7.

Mortality follow-up was available through the National Health Services Central Register until Jan. 31, 2010; the mean duration of follow-up for phase 7 was 6.1 years.

Stress on the day of cortisol sampling was measured by questions on whether the participant had experienced a stressful event and, if yes, how stressful this was.

Z scores were created for the CAR, slope, waking cortisol, and cortisol measures at bedtime. Cox proportional hazards models were used to determine the hazard ratio (HR) using the four standardized cortisol measures as linear terms.

The final number of cortisol samples for analysis was 24,121 from 4,047 participants with cortisol measures available. The average CAR was 7.31. The average diurnal slope estimated from the hierarchical linear model was –0.1288 nmol/L per h.

Individuals who subsequently died were more likely to be obese, report more fatigue, smoke, and have raised glucose levels in phase 7 than were those who survived. Of the main causes of death, the increased risk of mortality was from an increased risk of cardiovascular death rather than death from to cancer, which had an HR of 1.17.

In all, there were 32 cardiovascular deaths. The average CARs in participants who died, compared with those who survived, were 8.35 and 7.31 after researchers adjusted for age, sex, waking time, time since waking, and social position. The concomitant diurnal slope values were –0.1143 vs. –0.1290, which was a significant difference.

No CAR association was seen for cardiovascular or noncardiovascular mortality, although a linear association was observed with mortality attributed to cardiovascular disease for slope in cortisol across the day.

However, a flatter slope in cortisol patterns across the day can happen because of low waking values or high evening values of cortisol. The researchers then examined the association of cardiovascular and noncardiovascular events with waking cortisol and cortisol measured at bedtime to assess which accounted for flatter cortisol slope patterns.

They found that waking cortisol levels were unrelated to subsequent mortality. "The failure of waking cortisol to predict deaths argues against a role for the HPA [hypothalamic-pituitary-adrenal] axis in mediating the association of fatigue with mortality," the investigators noted.

However, cortisol measures at bedtime were predictive of cardiovascular-related mortality; the hazard ratio for each standard deviation increase in z score was 1.98, "suggesting that constantly elevated rather stable low cortisol level across the day accounted for the increased death risk," the researchers noted.

"The causes of flat slopes in cortisol or raised evening levels are unknown. It is unclear whether a flatter slope in cortisol is due to stress-related elevations, resulting from a stressful day, long-term changes in circadian regulation as a result of chronic stress, or impaired central negative feedback sensitivity of the HPA axis (particularly to melanocorticoid receptors) as recently described in obesity."

In addition, obesity was independently predictive of both cardiovascular and noncardiovascular mortality (HR, 2.10 and 1.72 respectively) based on analyses of bedtime cortisol. Fatigue was also predictive of both cardiovascular and noncardiovascular deaths (HR, 2.37 and 1.72 respectively), in analyses of bedtime cortisol. Interestingly, self-reported stress on day of cortisol sampling also was independently associated with cardiovascular deaths (HR, 3.45).

"Our findings are novel in that they suggest a cause-specific association with cardiovascular mortality in a nonclinical population. The pathway by which this association occurs remains unclear, but further follow-up of our participants with cumulated numbers of deaths will allow examination of these issues in greater detail," wrote Dr. Kumari and her coinvestigators.

The authors reported that they have nothing to disclose.

Major Finding: When paired with exemestane or fulvestrant, AMG 479 produced a median progression-free survival of 3.9 months, compared with 5.7 months for patients on exemestane or fulvestrant alone (HR, 1.17; P = .435).

Data Source: A phase II study in 156 women with hormone receptor–positive metastatic or locally advanced breast cancer.

Disclosures: Dr. Kaufman received grant support from trial sponsor Amgen Inc. He has also disclosed that he is a shareholder of Amgen. Three of the study authors are employees of Amgen.

SAN ANTONIO – The investigational agent AMG 479 failed to alter resistance to hormonal therapy in patients with endocrine therapy–resistant, hormone receptor–positive metastatic breast cancer in the adjuvant setting. Indeed, the drug showed a trend toward worse progression-free survival and objective response in a phase II trial.

When AMG 479 was paired with exemestane or fulvestrant, patients in the experimental arm had a median progression-free survival of 3.9 months, compared with 5.7 months for patients on exemestane or fulvestrant alone, a nonsignificant difference.

“AMG 479 in combination with either fulvestrant or exemestane does not appear to delay or reverse resistance to hormonal therapy in this population of patients with prior endocrine therapy–resistant hormone receptor–positive metastatic breast cancer,” Dr. Peter A. Kaufman said at the symposium.

AMG 479 is an investigational fully human monoclonal antibody antagonist of the type I insulinlike growth factor (IGF-I) receptor, blocking the binding of both IGF-I and IGF-II to the receptor.

Resistance to hormonal therapy is thought to possibly occur through increased IGF-I receptor (IGF-IR) signaling, and the researchers hypothesized that inhibition of the IGF-IR signaling pathway may enhance the activity of a second line of hormonal therapy in breast cancer patients, according to Dr. Kaufman of Dartmouth-Hitchcock Medical Center in Lebanon, N.H.

In this study, patients were randomized to receive either treatment with AMG 479 along with exemestane or fulvestrant, or placebo plus exemestane or fulvestrant. (The choice was left to the investigator.) Stratification factors included which hormonal therapy the patient received, as well as the extent of disease.

AMG 479(12 mg/kg) and placebo were given intravenously every 2 weeks. Exemestane (25 mg) was given orally every day; oral fulvestrant was given in a dose of 500 mg on day 1 and then at a dose of 250 mg on days 15 and 29 and every 4 weeks thereafter.

The primary end point was progression-free survival, as measured by modified RECIST (Response Evaluation Criteria in Solid Tumors) v1.0.

In all, 106 women were included in the AMG 479 group and 50 in the placebo group. In the treatment group, 98% of women were estrogen receptor positive, 70% were progesterone receptor positive, and 7% were HER2 positive.

In the placebo group, 94% of women were ER positive, 70% were PR positive, and 2% were HER2 positive.

Median progression-free survival among women who received exemestane was 4.8 months with AMG 479 and 7.3 months with placebo (HR, 1.31). Among women who received fulvestrant, it was 3.7 months and 5.4, respectively (HR, 1.11).

“There really is no difference in the overall response rate,” said Dr. Kaufman. The objective response rate for patients in the AMG 479 group was 8% vs. 13% for those in the control group.

The overall clinical benefit rate was 35% for women on AMG 479 and 31% of women on placebo, which was not significant.

Serious adverse events occurred in 25% of patients who were given AMG 479 and 18% of the placebo group. “We saw no meaningful difference in any of those symptoms,” said Dr. Kaufman. He did note elevated but nonsignificant rates of hyperglycemia, neutropenia, and thrombocytopenia for those on AMG, however.

Major Finding: When paired with exemestane or fulvestrant, AMG 479 produced a median progression-free survival of 3.9 months, compared with 5.7 months for patients on exemestane or fulvestrant alone (HR, 1.17; P = .435).

Data Source: A phase II study in 156 women with hormone receptor–positive metastatic or locally advanced breast cancer.

Disclosures: Dr. Kaufman received grant support from trial sponsor Amgen Inc. He has also disclosed that he is a shareholder of Amgen. Three of the study authors are employees of Amgen.

SAN ANTONIO – The investigational agent AMG 479 failed to alter resistance to hormonal therapy in patients with endocrine therapy–resistant, hormone receptor–positive metastatic breast cancer in the adjuvant setting. Indeed, the drug showed a trend toward worse progression-free survival and objective response in a phase II trial.

When AMG 479 was paired with exemestane or fulvestrant, patients in the experimental arm had a median progression-free survival of 3.9 months, compared with 5.7 months for patients on exemestane or fulvestrant alone, a nonsignificant difference.

“AMG 479 in combination with either fulvestrant or exemestane does not appear to delay or reverse resistance to hormonal therapy in this population of patients with prior endocrine therapy–resistant hormone receptor–positive metastatic breast cancer,” Dr. Peter A. Kaufman said at the symposium.

AMG 479 is an investigational fully human monoclonal antibody antagonist of the type I insulinlike growth factor (IGF-I) receptor, blocking the binding of both IGF-I and IGF-II to the receptor.

Resistance to hormonal therapy is thought to possibly occur through increased IGF-I receptor (IGF-IR) signaling, and the researchers hypothesized that inhibition of the IGF-IR signaling pathway may enhance the activity of a second line of hormonal therapy in breast cancer patients, according to Dr. Kaufman of Dartmouth-Hitchcock Medical Center in Lebanon, N.H.

In this study, patients were randomized to receive either treatment with AMG 479 along with exemestane or fulvestrant, or placebo plus exemestane or fulvestrant. (The choice was left to the investigator.) Stratification factors included which hormonal therapy the patient received, as well as the extent of disease.

AMG 479(12 mg/kg) and placebo were given intravenously every 2 weeks. Exemestane (25 mg) was given orally every day; oral fulvestrant was given in a dose of 500 mg on day 1 and then at a dose of 250 mg on days 15 and 29 and every 4 weeks thereafter.

The primary end point was progression-free survival, as measured by modified RECIST (Response Evaluation Criteria in Solid Tumors) v1.0.

In all, 106 women were included in the AMG 479 group and 50 in the placebo group. In the treatment group, 98% of women were estrogen receptor positive, 70% were progesterone receptor positive, and 7% were HER2 positive.

In the placebo group, 94% of women were ER positive, 70% were PR positive, and 2% were HER2 positive.

Median progression-free survival among women who received exemestane was 4.8 months with AMG 479 and 7.3 months with placebo (HR, 1.31). Among women who received fulvestrant, it was 3.7 months and 5.4, respectively (HR, 1.11).

“There really is no difference in the overall response rate,” said Dr. Kaufman. The objective response rate for patients in the AMG 479 group was 8% vs. 13% for those in the control group.

The overall clinical benefit rate was 35% for women on AMG 479 and 31% of women on placebo, which was not significant.

Serious adverse events occurred in 25% of patients who were given AMG 479 and 18% of the placebo group. “We saw no meaningful difference in any of those symptoms,” said Dr. Kaufman. He did note elevated but nonsignificant rates of hyperglycemia, neutropenia, and thrombocytopenia for those on AMG, however.

Major Finding: When paired with exemestane or fulvestrant, AMG 479 produced a median progression-free survival of 3.9 months, compared with 5.7 months for patients on exemestane or fulvestrant alone (HR, 1.17; P = .435).

Data Source: A phase II study in 156 women with hormone receptor–positive metastatic or locally advanced breast cancer.

Disclosures: Dr. Kaufman received grant support from trial sponsor Amgen Inc. He has also disclosed that he is a shareholder of Amgen. Three of the study authors are employees of Amgen.

SAN ANTONIO – The investigational agent AMG 479 failed to alter resistance to hormonal therapy in patients with endocrine therapy–resistant, hormone receptor–positive metastatic breast cancer in the adjuvant setting. Indeed, the drug showed a trend toward worse progression-free survival and objective response in a phase II trial.

When AMG 479 was paired with exemestane or fulvestrant, patients in the experimental arm had a median progression-free survival of 3.9 months, compared with 5.7 months for patients on exemestane or fulvestrant alone, a nonsignificant difference.

“AMG 479 in combination with either fulvestrant or exemestane does not appear to delay or reverse resistance to hormonal therapy in this population of patients with prior endocrine therapy–resistant hormone receptor–positive metastatic breast cancer,” Dr. Peter A. Kaufman said at the symposium.

AMG 479 is an investigational fully human monoclonal antibody antagonist of the type I insulinlike growth factor (IGF-I) receptor, blocking the binding of both IGF-I and IGF-II to the receptor.

Resistance to hormonal therapy is thought to possibly occur through increased IGF-I receptor (IGF-IR) signaling, and the researchers hypothesized that inhibition of the IGF-IR signaling pathway may enhance the activity of a second line of hormonal therapy in breast cancer patients, according to Dr. Kaufman of Dartmouth-Hitchcock Medical Center in Lebanon, N.H.

In this study, patients were randomized to receive either treatment with AMG 479 along with exemestane or fulvestrant, or placebo plus exemestane or fulvestrant. (The choice was left to the investigator.) Stratification factors included which hormonal therapy the patient received, as well as the extent of disease.

AMG 479(12 mg/kg) and placebo were given intravenously every 2 weeks. Exemestane (25 mg) was given orally every day; oral fulvestrant was given in a dose of 500 mg on day 1 and then at a dose of 250 mg on days 15 and 29 and every 4 weeks thereafter.

The primary end point was progression-free survival, as measured by modified RECIST (Response Evaluation Criteria in Solid Tumors) v1.0.

In all, 106 women were included in the AMG 479 group and 50 in the placebo group. In the treatment group, 98% of women were estrogen receptor positive, 70% were progesterone receptor positive, and 7% were HER2 positive.

In the placebo group, 94% of women were ER positive, 70% were PR positive, and 2% were HER2 positive.

Median progression-free survival among women who received exemestane was 4.8 months with AMG 479 and 7.3 months with placebo (HR, 1.31). Among women who received fulvestrant, it was 3.7 months and 5.4, respectively (HR, 1.11).

“There really is no difference in the overall response rate,” said Dr. Kaufman. The objective response rate for patients in the AMG 479 group was 8% vs. 13% for those in the control group.

The overall clinical benefit rate was 35% for women on AMG 479 and 31% of women on placebo, which was not significant.

Serious adverse events occurred in 25% of patients who were given AMG 479 and 18% of the placebo group. “We saw no meaningful difference in any of those symptoms,” said Dr. Kaufman. He did note elevated but nonsignificant rates of hyperglycemia, neutropenia, and thrombocytopenia for those on AMG, however.

Major Finding: Patients with type 1 diabetes are 10 times more likely to have an enterovirus infection, compared with patients without diabetes.

Data Source: A meta-analysis of 34 case-controlled studies using molecular diagnosis of enterovirus.

Disclosures: The investigators reported that they have no relevant financial relationships.

Patients with type 1 diabetes are almost 10 times more likely to be infected with enterovirus than are individuals without diabetes, according to results of the first meta-analysis of studies using molecular diagnosis of the virus.

Although it has been suggested in the literature that enterovirus might play a role in the development of type 1 diabetes, to date there has been no systematic review of molecular studies. Researchers in Australia performed such a review of 25 controlled studies that used molecular methods to investigate such an association. They found a summary odds ratio of 9.8 (P less than .001) for identifying enterovirus in patients with type 1 diabetes, compared with patients without it.

“While the findings from this meta-analysis of observational studies cannot prove that enterovirus infection has a causal role in pathogenesis of diabetes, the results provide additional support to the direct evidence of enterovirus infection in pancreatic tissue of individuals with type 1 diabetes,” wrote authors Wing-Chi Yeung, Dr. William D. Rawlinson and Dr. Maria E. Craig of the University of New South Wales (BMJ 2011;342:d35).

For this meta-analysis, two reviewers independently conducted systematic searches for controlled observational studies of enterovirus and type 1 diabetes. They searched the PubMed (from 1965 to May 2010) and Embase (from 1974 to May 2010) databases.

They included only case-control or cohort studies that used molecular methods for viral detection (such as reverse transcription-polymerase chain reaction [RT-PCR], in situ hybridization, or immunostaining for detection of viral capsid protein) to identify current or recent infection in blood, stool, or tissue of patients with prediabetes and diabetes. “Molecular testing is now standard for diagnosis of acute enterovirus infection,” they noted.

They classified the studies into two groups – prediabetes and diabetes – depending on whether autoimmunity or type 1 diabetes (newly diagnosed, established type and eventual type 1 diabetes) was the outcome. This systematic review of 33 prevalence studies, involving 1,931 patients and 2,517 nondiabetic individuals.

They identified 34 studies – 9 involving patients with prediabetes (198 cases and 733 controls) and 25 studies of diabetes patients (1,733 cases and 1,784 controls).

Thirty studies used RT-PCR or in situ hybridization to detect enterovirus RNA; immunostaining for the enterovirus capsid protein vp1 on autopsy pancreas specimens was used on four studies. Most studies investigated children and adolescents up to age 16 years, though some included adults up to age 53 years.

The summary odds ratio of identifying enterovirus in patients with prediabetes compared with patients without diabetes was 3.7 (P less than .001). All but one of the 25 studies of patients with type 1 diabetes had odds ratios greater than one for patients with diabetes testing positive for enterovirus, with a summary odds ratio of 9.8 (P less than .001).

They used sensitivity analyses to test the robustness of the results by country and study quality.

In all, 19 studies were conducted in Europe. “There was some evidence for geographical differences; in non-European studies the odds ratio was 13.5, compared with 8.6 in European studies, though there was considerably overlap in the confidence intervals,” they wrote.

In addition, “the odds of having an enterovirus infection in people with established diabetes (OR, 11) suggest that persistent enterovirus infection is also common among patients with type 1 diabetes.”

View on the News

New Therapies To Come?

In an accompanying editorial, Dr. Didier Hober and Famara Sane, Pharm.D., noted that prospective studies have suggested “an association between enterovirus infections and the subsequent production of autoantibodies directed against pancreatic beta-cells that result in type 1 diabetes.” In fact, it is possible that persistent or consecutive enterovirus infections may play a role in progression or acceleration of type 1 diabetes (BMJ 2011; 341:c7072).

“The link between enteroviruses and the pathogenesis of type 1 diabetes probably involves and interplay between viruses, pancreatic beta-cells, the innate and adaptive immune systems, and the genotype of the patient,” they wrote.

While additional studies are necessary to understand these associations and to establish pathogenic mechanisms of enterovirus infections, clear evidence of an association between enteroviruses and type 1 diabetes “opens up the possibility of developing new preventive and therapeutic strategies to fight this disease.”

DR. HOBER is a professor of virology at the University of Lille in France. DR. SANE is a virology research assistant at the University of Lille. The authors reported that they have no relevant financial relationships.

Major Finding: Patients with type 1 diabetes are 10 times more likely to have an enterovirus infection, compared with patients without diabetes.

Data Source: A meta-analysis of 34 case-controlled studies using molecular diagnosis of enterovirus.

Disclosures: The investigators reported that they have no relevant financial relationships.

Patients with type 1 diabetes are almost 10 times more likely to be infected with enterovirus than are individuals without diabetes, according to results of the first meta-analysis of studies using molecular diagnosis of the virus.

Although it has been suggested in the literature that enterovirus might play a role in the development of type 1 diabetes, to date there has been no systematic review of molecular studies. Researchers in Australia performed such a review of 25 controlled studies that used molecular methods to investigate such an association. They found a summary odds ratio of 9.8 (P less than .001) for identifying enterovirus in patients with type 1 diabetes, compared with patients without it.

“While the findings from this meta-analysis of observational studies cannot prove that enterovirus infection has a causal role in pathogenesis of diabetes, the results provide additional support to the direct evidence of enterovirus infection in pancreatic tissue of individuals with type 1 diabetes,” wrote authors Wing-Chi Yeung, Dr. William D. Rawlinson and Dr. Maria E. Craig of the University of New South Wales (BMJ 2011;342:d35).

For this meta-analysis, two reviewers independently conducted systematic searches for controlled observational studies of enterovirus and type 1 diabetes. They searched the PubMed (from 1965 to May 2010) and Embase (from 1974 to May 2010) databases.

They included only case-control or cohort studies that used molecular methods for viral detection (such as reverse transcription-polymerase chain reaction [RT-PCR], in situ hybridization, or immunostaining for detection of viral capsid protein) to identify current or recent infection in blood, stool, or tissue of patients with prediabetes and diabetes. “Molecular testing is now standard for diagnosis of acute enterovirus infection,” they noted.

They classified the studies into two groups – prediabetes and diabetes – depending on whether autoimmunity or type 1 diabetes (newly diagnosed, established type and eventual type 1 diabetes) was the outcome. This systematic review of 33 prevalence studies, involving 1,931 patients and 2,517 nondiabetic individuals.

They identified 34 studies – 9 involving patients with prediabetes (198 cases and 733 controls) and 25 studies of diabetes patients (1,733 cases and 1,784 controls).

Thirty studies used RT-PCR or in situ hybridization to detect enterovirus RNA; immunostaining for the enterovirus capsid protein vp1 on autopsy pancreas specimens was used on four studies. Most studies investigated children and adolescents up to age 16 years, though some included adults up to age 53 years.

The summary odds ratio of identifying enterovirus in patients with prediabetes compared with patients without diabetes was 3.7 (P less than .001). All but one of the 25 studies of patients with type 1 diabetes had odds ratios greater than one for patients with diabetes testing positive for enterovirus, with a summary odds ratio of 9.8 (P less than .001).

They used sensitivity analyses to test the robustness of the results by country and study quality.

In all, 19 studies were conducted in Europe. “There was some evidence for geographical differences; in non-European studies the odds ratio was 13.5, compared with 8.6 in European studies, though there was considerably overlap in the confidence intervals,” they wrote.

In addition, “the odds of having an enterovirus infection in people with established diabetes (OR, 11) suggest that persistent enterovirus infection is also common among patients with type 1 diabetes.”

View on the News

New Therapies To Come?

In an accompanying editorial, Dr. Didier Hober and Famara Sane, Pharm.D., noted that prospective studies have suggested “an association between enterovirus infections and the subsequent production of autoantibodies directed against pancreatic beta-cells that result in type 1 diabetes.” In fact, it is possible that persistent or consecutive enterovirus infections may play a role in progression or acceleration of type 1 diabetes (BMJ 2011; 341:c7072).

“The link between enteroviruses and the pathogenesis of type 1 diabetes probably involves and interplay between viruses, pancreatic beta-cells, the innate and adaptive immune systems, and the genotype of the patient,” they wrote.

While additional studies are necessary to understand these associations and to establish pathogenic mechanisms of enterovirus infections, clear evidence of an association between enteroviruses and type 1 diabetes “opens up the possibility of developing new preventive and therapeutic strategies to fight this disease.”

DR. HOBER is a professor of virology at the University of Lille in France. DR. SANE is a virology research assistant at the University of Lille. The authors reported that they have no relevant financial relationships.

Major Finding: Patients with type 1 diabetes are 10 times more likely to have an enterovirus infection, compared with patients without diabetes.

Data Source: A meta-analysis of 34 case-controlled studies using molecular diagnosis of enterovirus.

Disclosures: The investigators reported that they have no relevant financial relationships.

Patients with type 1 diabetes are almost 10 times more likely to be infected with enterovirus than are individuals without diabetes, according to results of the first meta-analysis of studies using molecular diagnosis of the virus.

Although it has been suggested in the literature that enterovirus might play a role in the development of type 1 diabetes, to date there has been no systematic review of molecular studies. Researchers in Australia performed such a review of 25 controlled studies that used molecular methods to investigate such an association. They found a summary odds ratio of 9.8 (P less than .001) for identifying enterovirus in patients with type 1 diabetes, compared with patients without it.

“While the findings from this meta-analysis of observational studies cannot prove that enterovirus infection has a causal role in pathogenesis of diabetes, the results provide additional support to the direct evidence of enterovirus infection in pancreatic tissue of individuals with type 1 diabetes,” wrote authors Wing-Chi Yeung, Dr. William D. Rawlinson and Dr. Maria E. Craig of the University of New South Wales (BMJ 2011;342:d35).

For this meta-analysis, two reviewers independently conducted systematic searches for controlled observational studies of enterovirus and type 1 diabetes. They searched the PubMed (from 1965 to May 2010) and Embase (from 1974 to May 2010) databases.

They included only case-control or cohort studies that used molecular methods for viral detection (such as reverse transcription-polymerase chain reaction [RT-PCR], in situ hybridization, or immunostaining for detection of viral capsid protein) to identify current or recent infection in blood, stool, or tissue of patients with prediabetes and diabetes. “Molecular testing is now standard for diagnosis of acute enterovirus infection,” they noted.

They classified the studies into two groups – prediabetes and diabetes – depending on whether autoimmunity or type 1 diabetes (newly diagnosed, established type and eventual type 1 diabetes) was the outcome. This systematic review of 33 prevalence studies, involving 1,931 patients and 2,517 nondiabetic individuals.

They identified 34 studies – 9 involving patients with prediabetes (198 cases and 733 controls) and 25 studies of diabetes patients (1,733 cases and 1,784 controls).

Thirty studies used RT-PCR or in situ hybridization to detect enterovirus RNA; immunostaining for the enterovirus capsid protein vp1 on autopsy pancreas specimens was used on four studies. Most studies investigated children and adolescents up to age 16 years, though some included adults up to age 53 years.

The summary odds ratio of identifying enterovirus in patients with prediabetes compared with patients without diabetes was 3.7 (P less than .001). All but one of the 25 studies of patients with type 1 diabetes had odds ratios greater than one for patients with diabetes testing positive for enterovirus, with a summary odds ratio of 9.8 (P less than .001).

They used sensitivity analyses to test the robustness of the results by country and study quality.

In all, 19 studies were conducted in Europe. “There was some evidence for geographical differences; in non-European studies the odds ratio was 13.5, compared with 8.6 in European studies, though there was considerably overlap in the confidence intervals,” they wrote.

In addition, “the odds of having an enterovirus infection in people with established diabetes (OR, 11) suggest that persistent enterovirus infection is also common among patients with type 1 diabetes.”

View on the News

New Therapies To Come?

In an accompanying editorial, Dr. Didier Hober and Famara Sane, Pharm.D., noted that prospective studies have suggested “an association between enterovirus infections and the subsequent production of autoantibodies directed against pancreatic beta-cells that result in type 1 diabetes.” In fact, it is possible that persistent or consecutive enterovirus infections may play a role in progression or acceleration of type 1 diabetes (BMJ 2011; 341:c7072).

“The link between enteroviruses and the pathogenesis of type 1 diabetes probably involves and interplay between viruses, pancreatic beta-cells, the innate and adaptive immune systems, and the genotype of the patient,” they wrote.

While additional studies are necessary to understand these associations and to establish pathogenic mechanisms of enterovirus infections, clear evidence of an association between enteroviruses and type 1 diabetes “opens up the possibility of developing new preventive and therapeutic strategies to fight this disease.”

DR. HOBER is a professor of virology at the University of Lille in France. DR. SANE is a virology research assistant at the University of Lille. The authors reported that they have no relevant financial relationships.

NATIONAL HARBOR, MD. – Oophorectomy cut the risk of contralateral breast cancer by almost half in women with a family history of BRCA mutations, according to results of a retrospective study of more than 800 women. The benefit was even greater in women diagnosed with breast cancer before age 50.

“Oophorectomy was the most significant predictor of the development of contralateral breast cancer in this group of women,” investigator Kelly A. Metcalfe, Ph.D., said.

Removing ovaries reduced the risk of contralateral breast cancer by 47% in the entire cohort (relative risk 0.53, P = .007), she reported. Women younger than age 50 had a 55% reduction (RR 0.45, P = .002), but oophorectomy had no effect on risk of contralateral breast cancer in women 50 and older.

The multicenter cohort study followed women from the date of breast cancer diagnosis until contralateral breast cancer was diagnosed, contralateral mastectomy was performed, death, or date of last follow-up.

Women were included if they were part of a family with known BRCA1 or BRCA2 mutations, had stage I or II breast cancer, were 65 years or younger at the time of diagnosis, were diagnosed in 1975 or later, and had no previous cancer diagnosis. Investigators included living and deceased patients to avoid survivorship bias.

All told, 60% of the women had records of oophorectomy. The researchers reviewed 1,866 cases of breast cancer in 615 families. A total of 846 patients – 79% living – were eligible, gave consent, and had medical charts available for review.

The mean year of birth was 1950, and the mean age at diagnosis was 42 years. The women were followed for an average of 11.5 years. Nearly two-thirds (62%) had BRCA1 mutations, and 88% had undergone genetic testing. Among 177 women who died, breast cancer was the cause of death for 83%.

In the full study cohort, 18% were diagnosed with contralateral breast cancer with a mean time between the two diagnoses of 5.7 years. At 5 years, all women in the cohort had a 13% risk of developing contralateral disease, which rose to 34% at 15 years.

“Age was a very important predictor for these women. Women who were diagnosed with young-onset breast cancer (under the age of 50) had a significantly higher risk of developing contralateral breast cancer within the first 15 years,” said Dr. Metcalfe of the nursing faculty at the University of Toronto. For younger women, the risk was 38% at 15 years, compared with 18% in women 50 and older.

At 15 years post diagnosis, a woman younger than 50 years who had not had an oophorectomy had a roughly 60% risk of developing contralateral breast cancer. The risk was roughly 20% in women 50 years or older with intact ovaries.

Family history also appeared to play an important role.

Among the whole cohort, the risk of contralateral breast cancer increased by a third with every first-degree relative diagnosed with breast cancer under age 50. “This was particularly evident in BRCA1 carriers and early-onset breast cancer,” said Dr. Metcalfe. Risk was increased by roughly 40% in each of these groups.

For women younger than 50 years at diagnosis who still have intact ovaries, the risk of developing contralateral breast cancer at 15 years was 58%. With the addition of two or more first-degree relatives diagnosed with breast cancer under the age 50, the 15-year risk rose to 68%.

The authors reported that they have no relevant financial relationships.non in the prone position (wh

NATIONAL HARBOR, MD. – Oophorectomy cut the risk of contralateral breast cancer by almost half in women with a family history of BRCA mutations, according to results of a retrospective study of more than 800 women. The benefit was even greater in women diagnosed with breast cancer before age 50.

“Oophorectomy was the most significant predictor of the development of contralateral breast cancer in this group of women,” investigator Kelly A. Metcalfe, Ph.D., said.

Removing ovaries reduced the risk of contralateral breast cancer by 47% in the entire cohort (relative risk 0.53, P = .007), she reported. Women younger than age 50 had a 55% reduction (RR 0.45, P = .002), but oophorectomy had no effect on risk of contralateral breast cancer in women 50 and older.

The multicenter cohort study followed women from the date of breast cancer diagnosis until contralateral breast cancer was diagnosed, contralateral mastectomy was performed, death, or date of last follow-up.

Women were included if they were part of a family with known BRCA1 or BRCA2 mutations, had stage I or II breast cancer, were 65 years or younger at the time of diagnosis, were diagnosed in 1975 or later, and had no previous cancer diagnosis. Investigators included living and deceased patients to avoid survivorship bias.

All told, 60% of the women had records of oophorectomy. The researchers reviewed 1,866 cases of breast cancer in 615 families. A total of 846 patients – 79% living – were eligible, gave consent, and had medical charts available for review.

The mean year of birth was 1950, and the mean age at diagnosis was 42 years. The women were followed for an average of 11.5 years. Nearly two-thirds (62%) had BRCA1 mutations, and 88% had undergone genetic testing. Among 177 women who died, breast cancer was the cause of death for 83%.

In the full study cohort, 18% were diagnosed with contralateral breast cancer with a mean time between the two diagnoses of 5.7 years. At 5 years, all women in the cohort had a 13% risk of developing contralateral disease, which rose to 34% at 15 years.

“Age was a very important predictor for these women. Women who were diagnosed with young-onset breast cancer (under the age of 50) had a significantly higher risk of developing contralateral breast cancer within the first 15 years,” said Dr. Metcalfe of the nursing faculty at the University of Toronto. For younger women, the risk was 38% at 15 years, compared with 18% in women 50 and older.

At 15 years post diagnosis, a woman younger than 50 years who had not had an oophorectomy had a roughly 60% risk of developing contralateral breast cancer. The risk was roughly 20% in women 50 years or older with intact ovaries.

Family history also appeared to play an important role.

Among the whole cohort, the risk of contralateral breast cancer increased by a third with every first-degree relative diagnosed with breast cancer under age 50. “This was particularly evident in BRCA1 carriers and early-onset breast cancer,” said Dr. Metcalfe. Risk was increased by roughly 40% in each of these groups.

For women younger than 50 years at diagnosis who still have intact ovaries, the risk of developing contralateral breast cancer at 15 years was 58%. With the addition of two or more first-degree relatives diagnosed with breast cancer under the age 50, the 15-year risk rose to 68%.

The authors reported that they have no relevant financial relationships.non in the prone position (wh

NATIONAL HARBOR, MD. – Oophorectomy cut the risk of contralateral breast cancer by almost half in women with a family history of BRCA mutations, according to results of a retrospective study of more than 800 women. The benefit was even greater in women diagnosed with breast cancer before age 50.

“Oophorectomy was the most significant predictor of the development of contralateral breast cancer in this group of women,” investigator Kelly A. Metcalfe, Ph.D., said.

Removing ovaries reduced the risk of contralateral breast cancer by 47% in the entire cohort (relative risk 0.53, P = .007), she reported. Women younger than age 50 had a 55% reduction (RR 0.45, P = .002), but oophorectomy had no effect on risk of contralateral breast cancer in women 50 and older.

The multicenter cohort study followed women from the date of breast cancer diagnosis until contralateral breast cancer was diagnosed, contralateral mastectomy was performed, death, or date of last follow-up.

Women were included if they were part of a family with known BRCA1 or BRCA2 mutations, had stage I or II breast cancer, were 65 years or younger at the time of diagnosis, were diagnosed in 1975 or later, and had no previous cancer diagnosis. Investigators included living and deceased patients to avoid survivorship bias.

All told, 60% of the women had records of oophorectomy. The researchers reviewed 1,866 cases of breast cancer in 615 families. A total of 846 patients – 79% living – were eligible, gave consent, and had medical charts available for review.

The mean year of birth was 1950, and the mean age at diagnosis was 42 years. The women were followed for an average of 11.5 years. Nearly two-thirds (62%) had BRCA1 mutations, and 88% had undergone genetic testing. Among 177 women who died, breast cancer was the cause of death for 83%.

In the full study cohort, 18% were diagnosed with contralateral breast cancer with a mean time between the two diagnoses of 5.7 years. At 5 years, all women in the cohort had a 13% risk of developing contralateral disease, which rose to 34% at 15 years.

“Age was a very important predictor for these women. Women who were diagnosed with young-onset breast cancer (under the age of 50) had a significantly higher risk of developing contralateral breast cancer within the first 15 years,” said Dr. Metcalfe of the nursing faculty at the University of Toronto. For younger women, the risk was 38% at 15 years, compared with 18% in women 50 and older.

At 15 years post diagnosis, a woman younger than 50 years who had not had an oophorectomy had a roughly 60% risk of developing contralateral breast cancer. The risk was roughly 20% in women 50 years or older with intact ovaries.

Family history also appeared to play an important role.

Among the whole cohort, the risk of contralateral breast cancer increased by a third with every first-degree relative diagnosed with breast cancer under age 50. “This was particularly evident in BRCA1 carriers and early-onset breast cancer,” said Dr. Metcalfe. Risk was increased by roughly 40% in each of these groups.

For women younger than 50 years at diagnosis who still have intact ovaries, the risk of developing contralateral breast cancer at 15 years was 58%. With the addition of two or more first-degree relatives diagnosed with breast cancer under the age 50, the 15-year risk rose to 68%.

The authors reported that they have no relevant financial relationships.non in the prone position (wh

The Food and Drug Administration is asking health care professionals to report any confirmed cases of anaplastic large cell lymphoma (ALCL) in women with silicone gel- or saline-filled breast implants, citing concerns about a possible association.

The agency's announcement during a teleconference is based on a review of scientific literature published between 1997 and 2010, along with information from other international regulators, scientists, and breast implant manufacturers.

“ALCL is rare and has occurred in a very small number of women when compared to the millions who have breast implants,” said Dr. William Maisel, chief scientist and deputy director for science in FDA's Center for Devices and Radiological Health. The literature review identified 34 unique cases of this rare cancer in women with both saline and silicone breast implants. There have been roughly 60 cases of ALCL in women with breast implants worldwide, according to the FDA. It's estimated that 5–10 million women have breast implants worldwide.

“Data reviewed by the FDA suggest that patients with breast implants may have a very small but significant risk of ALCL in the scar capsule adjacent to the implant,” the agency noted in a press release. Most of the cases reviewed by the agency were diagnosed when patients sought treatment for implant-related symptoms such as pain, lumps, swelling, or asymmetry.

The FDA recommends that health care professionals consider the possibility of ALCL if a patient has late onset, persistent fluid around the implant (peri-implant seroma). When implant seroma is found, fresh seroma fluid should be sent for pathology tests to rule out ALCL. Patient information about breast implants and ALCL can be found in the FDA's Consumer Updates

Health care providers should discuss the risks and benefits with women who are considering breast implant surgery. The FDA published its literature review in a document posted on its Web site titled “Anaplastic Large Cell Lymphoma (ALCL) in Women With Breast Implants: Preliminary FDA Findings and Analyses.”

The FDA also plans to provide an update on its review of silicone gel–filled breast implants in the spring of 2011.

Health care professionals should report all confirmed cases of ALCL in women with breast implants to Medwatch, the FDA's safety information and adverse event reporting program, either online at www.fda.gov/Safety/MedWatch/default.htm

The FDA also provides general information about breast implants to share with patients.

The Food and Drug Administration is asking health care professionals to report any confirmed cases of anaplastic large cell lymphoma (ALCL) in women with silicone gel- or saline-filled breast implants, citing concerns about a possible association.

The agency's announcement during a teleconference is based on a review of scientific literature published between 1997 and 2010, along with information from other international regulators, scientists, and breast implant manufacturers.

“ALCL is rare and has occurred in a very small number of women when compared to the millions who have breast implants,” said Dr. William Maisel, chief scientist and deputy director for science in FDA's Center for Devices and Radiological Health. The literature review identified 34 unique cases of this rare cancer in women with both saline and silicone breast implants. There have been roughly 60 cases of ALCL in women with breast implants worldwide, according to the FDA. It's estimated that 5–10 million women have breast implants worldwide.

“Data reviewed by the FDA suggest that patients with breast implants may have a very small but significant risk of ALCL in the scar capsule adjacent to the implant,” the agency noted in a press release. Most of the cases reviewed by the agency were diagnosed when patients sought treatment for implant-related symptoms such as pain, lumps, swelling, or asymmetry.

The FDA recommends that health care professionals consider the possibility of ALCL if a patient has late onset, persistent fluid around the implant (peri-implant seroma). When implant seroma is found, fresh seroma fluid should be sent for pathology tests to rule out ALCL. Patient information about breast implants and ALCL can be found in the FDA's Consumer Updates

Health care providers should discuss the risks and benefits with women who are considering breast implant surgery. The FDA published its literature review in a document posted on its Web site titled “Anaplastic Large Cell Lymphoma (ALCL) in Women With Breast Implants: Preliminary FDA Findings and Analyses.”

The FDA also plans to provide an update on its review of silicone gel–filled breast implants in the spring of 2011.

Health care professionals should report all confirmed cases of ALCL in women with breast implants to Medwatch, the FDA's safety information and adverse event reporting program, either online at www.fda.gov/Safety/MedWatch/default.htm

The FDA also provides general information about breast implants to share with patients.

The Food and Drug Administration is asking health care professionals to report any confirmed cases of anaplastic large cell lymphoma (ALCL) in women with silicone gel- or saline-filled breast implants, citing concerns about a possible association.

The agency's announcement during a teleconference is based on a review of scientific literature published between 1997 and 2010, along with information from other international regulators, scientists, and breast implant manufacturers.

“ALCL is rare and has occurred in a very small number of women when compared to the millions who have breast implants,” said Dr. William Maisel, chief scientist and deputy director for science in FDA's Center for Devices and Radiological Health. The literature review identified 34 unique cases of this rare cancer in women with both saline and silicone breast implants. There have been roughly 60 cases of ALCL in women with breast implants worldwide, according to the FDA. It's estimated that 5–10 million women have breast implants worldwide.

“Data reviewed by the FDA suggest that patients with breast implants may have a very small but significant risk of ALCL in the scar capsule adjacent to the implant,” the agency noted in a press release. Most of the cases reviewed by the agency were diagnosed when patients sought treatment for implant-related symptoms such as pain, lumps, swelling, or asymmetry.

The FDA recommends that health care professionals consider the possibility of ALCL if a patient has late onset, persistent fluid around the implant (peri-implant seroma). When implant seroma is found, fresh seroma fluid should be sent for pathology tests to rule out ALCL. Patient information about breast implants and ALCL can be found in the FDA's Consumer Updates

Health care providers should discuss the risks and benefits with women who are considering breast implant surgery. The FDA published its literature review in a document posted on its Web site titled “Anaplastic Large Cell Lymphoma (ALCL) in Women With Breast Implants: Preliminary FDA Findings and Analyses.”

The FDA also plans to provide an update on its review of silicone gel–filled breast implants in the spring of 2011.

Health care professionals should report all confirmed cases of ALCL in women with breast implants to Medwatch, the FDA's safety information and adverse event reporting program, either online at www.fda.gov/Safety/MedWatch/default.htm

The FDA also provides general information about breast implants to share with patients.

Breastfeeding appears to have a protective effect against later obesity for children born to mothers with diabetes during pregnancy, based on the analysis of data from a retrospective cohort study published online Feb. 25 in Diabetes Care.

The findings could help to prevent childhood obesity in children born to mothers with diabetes during pregnancy. Research has shown that these children have a greater prevalence of obesity in childhood, Tessa L. Crume, Ph.D., of the Colorado School of Public Health at the University of Colorado in Denver and her coinvestigators noted (Diabetes Care 2011;34:641-5).

Both children exposed to diabetes in utero and those unexposed but who had adequate breastfeeding had significantly lower body mass index (BMI), waist circumference, subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) at ages 6-13 years than did those with less breastfeeding.

©Lev Olkha/iStockphoto.com

"Our study provides novel evidence that the effect of exposure to diabetes in utero on childhood adiposity parameters is substantially attenuated by breastfeeding, such that the obesity outcomes in exposed youth who were adequately breastfed were similar to those of unexposed youth. Our data suggest that breastfeeding promotion may be an effective strategy for reducing the increased risk of childhood obesity in the offspring of mothers with diabetes during pregnancy," wrote Dr. Crume and her colleagues.

The researchers used data from a retrospective cohort study entitled Exploring Perinatal Outcomes Among Children (EPOCH). Participants were aged 6-13 years. In addition, they were multiethnic offspring of singleton pregnancies born at a single hospital in Denver between 1992 and 2002. The mothers were members of the Kaiser Permanente of Colorado Health Plan and were still members and living in Colorado over the study period (2006-2009).

The study included 89 youths, who were exposed to diabetes in utero. The researchers also identified a random sample of 397 children who were not exposed to diabetes in utero. Children and their biological mothers were invited for a research visit between January 2006 and October 2009.

Physician-diagnosed maternal diabetes status was ascertained from the Kaiser Permanente Colorado perinatal database – an electronic database linking neonatal and perinatal medical records. Gestational diabetes mellitus was coded as present if diagnosed through the standard Kaiser screening protocol and absent if screening was negative. All pregnant women were offered screening at 24-28 weeks.

Exposure to diabetes in utero was defined as the presence of preexistent diabetes or gestational diabetes diagnosed during the index pregnancy. Birth weight, gestational age, and maternal prepregnancy weight also were obtained from the database.

Mothers were asked about breast- and formula-feeding, timing, and the introduction of other solid foods and beverages. Mixed feeding was commonly reported, so a measure of breast milk-months was developed that incorporated duration and exclusivity. For exclusively breastfed infants, duration was equal to the age of the child (months) when breastfeeding was stopped. Breastfeeding exclusivity was quantified using weights from 0 to 1, with exclusive breastfeeding having a weight of 1 and exclusive formula-feeding having a weight of 0. For infants who were ever fed formula, mothers classified their infant feeding as formula only (0), more formula than breast milk (0.25), equal breast milk and formula (0.50), or more breast milk than formula (0.75).

The breast milk-months measure incorporated duration and exclusivity to estimate an overall breast milk dose equivalent in months. Based on a formula that included breastfeeding exclusivity and duration, breastfeeding status was categorized as low (less than 6 breast milk-months) and adequate (at least 6 breast milk-months).

The subscapular-to-triceps skinfold ratio (STR) was calculated to assess regional differences in subcutaneous fat distribution. In addition, an MRI of the abdominal region was used to quantify VAT and SAT.

The mean age was 9.6 years for exposed youth and 10.6 years for unexposed youth at the study visit – a difference that was significant. Exposed youth were significantly more likely to be non-Hispanic white or Hispanic, and a larger proportion of exposed youth self-reported a Tanner stage less than 2 (prepubertal). Mothers with diabetes during pregnancy were significantly older on average than mothers whose pregnancies were not complicated by diabetes. Exposed and unexposed offspring were not significantly different in terms of intrauterine growth, socioeconomic factors or infant feeding practices.

Among adolescents with low breastfeeding status, exposure to diabetes in utero was associated with a 1.7 kg/m2 greater BMI (significant); a 5.8 cm greater waist circumference (significant); a 6.1 cm2 higher VAT; a 44.6 cm2 greater SAT (significant); and a 0.11 higher STR (significant). The association between exposure to diabetes in utero and the adiposity parameters was substantially reduced and not significant for adolescents with adequate breastfeeding in infancy with a 0.7 kg/m2 lower BMI (significant); a 2.7 cm greater waist circumference; a 2.1 cm2 greater VAT; a 23.4 cm2 greater SAT; and a 0.05 greater STR among exposed versus unexposed children.

Importantly, all measures of adiposity were influenced, including the more sensitive VAT and SAT, the investigators noted. Although the mechanisms that trigger adipose tissue deposition in specific locations at different periods of fetal development or in childhood remain unclear, the identification of strategies to alter the long-term development of fat deposition/accumulation is necessary to minimize the significant increased morbidity risk associated with childhood obesity. "Fetal life and early infancy both represent critical periods when obesity begins and may be effectively minimized by targeted prevention strategies," they said.

Further work is needed to confirm this finding in larger populations though, and to determine if the reductions in adiposity continue into adulthood.

Dr. Crume and her associates reported that they have no relevant financial relationships.

Breastfeeding appears to have a protective effect against later obesity for children born to mothers with diabetes during pregnancy, based on the analysis of data from a retrospective cohort study published online Feb. 25 in Diabetes Care.

The findings could help to prevent childhood obesity in children born to mothers with diabetes during pregnancy. Research has shown that these children have a greater prevalence of obesity in childhood, Tessa L. Crume, Ph.D., of the Colorado School of Public Health at the University of Colorado in Denver and her coinvestigators noted (Diabetes Care 2011;34:641-5).

Both children exposed to diabetes in utero and those unexposed but who had adequate breastfeeding had significantly lower body mass index (BMI), waist circumference, subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) at ages 6-13 years than did those with less breastfeeding.

©Lev Olkha/iStockphoto.com

"Our study provides novel evidence that the effect of exposure to diabetes in utero on childhood adiposity parameters is substantially attenuated by breastfeeding, such that the obesity outcomes in exposed youth who were adequately breastfed were similar to those of unexposed youth. Our data suggest that breastfeeding promotion may be an effective strategy for reducing the increased risk of childhood obesity in the offspring of mothers with diabetes during pregnancy," wrote Dr. Crume and her colleagues.

The researchers used data from a retrospective cohort study entitled Exploring Perinatal Outcomes Among Children (EPOCH). Participants were aged 6-13 years. In addition, they were multiethnic offspring of singleton pregnancies born at a single hospital in Denver between 1992 and 2002. The mothers were members of the Kaiser Permanente of Colorado Health Plan and were still members and living in Colorado over the study period (2006-2009).

The study included 89 youths, who were exposed to diabetes in utero. The researchers also identified a random sample of 397 children who were not exposed to diabetes in utero. Children and their biological mothers were invited for a research visit between January 2006 and October 2009.

Physician-diagnosed maternal diabetes status was ascertained from the Kaiser Permanente Colorado perinatal database – an electronic database linking neonatal and perinatal medical records. Gestational diabetes mellitus was coded as present if diagnosed through the standard Kaiser screening protocol and absent if screening was negative. All pregnant women were offered screening at 24-28 weeks.

Exposure to diabetes in utero was defined as the presence of preexistent diabetes or gestational diabetes diagnosed during the index pregnancy. Birth weight, gestational age, and maternal prepregnancy weight also were obtained from the database.

Mothers were asked about breast- and formula-feeding, timing, and the introduction of other solid foods and beverages. Mixed feeding was commonly reported, so a measure of breast milk-months was developed that incorporated duration and exclusivity. For exclusively breastfed infants, duration was equal to the age of the child (months) when breastfeeding was stopped. Breastfeeding exclusivity was quantified using weights from 0 to 1, with exclusive breastfeeding having a weight of 1 and exclusive formula-feeding having a weight of 0. For infants who were ever fed formula, mothers classified their infant feeding as formula only (0), more formula than breast milk (0.25), equal breast milk and formula (0.50), or more breast milk than formula (0.75).

The breast milk-months measure incorporated duration and exclusivity to estimate an overall breast milk dose equivalent in months. Based on a formula that included breastfeeding exclusivity and duration, breastfeeding status was categorized as low (less than 6 breast milk-months) and adequate (at least 6 breast milk-months).

The subscapular-to-triceps skinfold ratio (STR) was calculated to assess regional differences in subcutaneous fat distribution. In addition, an MRI of the abdominal region was used to quantify VAT and SAT.

The mean age was 9.6 years for exposed youth and 10.6 years for unexposed youth at the study visit – a difference that was significant. Exposed youth were significantly more likely to be non-Hispanic white or Hispanic, and a larger proportion of exposed youth self-reported a Tanner stage less than 2 (prepubertal). Mothers with diabetes during pregnancy were significantly older on average than mothers whose pregnancies were not complicated by diabetes. Exposed and unexposed offspring were not significantly different in terms of intrauterine growth, socioeconomic factors or infant feeding practices.

Among adolescents with low breastfeeding status, exposure to diabetes in utero was associated with a 1.7 kg/m2 greater BMI (significant); a 5.8 cm greater waist circumference (significant); a 6.1 cm2 higher VAT; a 44.6 cm2 greater SAT (significant); and a 0.11 higher STR (significant). The association between exposure to diabetes in utero and the adiposity parameters was substantially reduced and not significant for adolescents with adequate breastfeeding in infancy with a 0.7 kg/m2 lower BMI (significant); a 2.7 cm greater waist circumference; a 2.1 cm2 greater VAT; a 23.4 cm2 greater SAT; and a 0.05 greater STR among exposed versus unexposed children.

Importantly, all measures of adiposity were influenced, including the more sensitive VAT and SAT, the investigators noted. Although the mechanisms that trigger adipose tissue deposition in specific locations at different periods of fetal development or in childhood remain unclear, the identification of strategies to alter the long-term development of fat deposition/accumulation is necessary to minimize the significant increased morbidity risk associated with childhood obesity. "Fetal life and early infancy both represent critical periods when obesity begins and may be effectively minimized by targeted prevention strategies," they said.

Further work is needed to confirm this finding in larger populations though, and to determine if the reductions in adiposity continue into adulthood.

Dr. Crume and her associates reported that they have no relevant financial relationships.

Breastfeeding appears to have a protective effect against later obesity for children born to mothers with diabetes during pregnancy, based on the analysis of data from a retrospective cohort study published online Feb. 25 in Diabetes Care.

The findings could help to prevent childhood obesity in children born to mothers with diabetes during pregnancy. Research has shown that these children have a greater prevalence of obesity in childhood, Tessa L. Crume, Ph.D., of the Colorado School of Public Health at the University of Colorado in Denver and her coinvestigators noted (Diabetes Care 2011;34:641-5).

Both children exposed to diabetes in utero and those unexposed but who had adequate breastfeeding had significantly lower body mass index (BMI), waist circumference, subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) at ages 6-13 years than did those with less breastfeeding.

©Lev Olkha/iStockphoto.com

"Our study provides novel evidence that the effect of exposure to diabetes in utero on childhood adiposity parameters is substantially attenuated by breastfeeding, such that the obesity outcomes in exposed youth who were adequately breastfed were similar to those of unexposed youth. Our data suggest that breastfeeding promotion may be an effective strategy for reducing the increased risk of childhood obesity in the offspring of mothers with diabetes during pregnancy," wrote Dr. Crume and her colleagues.

The researchers used data from a retrospective cohort study entitled Exploring Perinatal Outcomes Among Children (EPOCH). Participants were aged 6-13 years. In addition, they were multiethnic offspring of singleton pregnancies born at a single hospital in Denver between 1992 and 2002. The mothers were members of the Kaiser Permanente of Colorado Health Plan and were still members and living in Colorado over the study period (2006-2009).

The study included 89 youths, who were exposed to diabetes in utero. The researchers also identified a random sample of 397 children who were not exposed to diabetes in utero. Children and their biological mothers were invited for a research visit between January 2006 and October 2009.

Physician-diagnosed maternal diabetes status was ascertained from the Kaiser Permanente Colorado perinatal database – an electronic database linking neonatal and perinatal medical records. Gestational diabetes mellitus was coded as present if diagnosed through the standard Kaiser screening protocol and absent if screening was negative. All pregnant women were offered screening at 24-28 weeks.

Exposure to diabetes in utero was defined as the presence of preexistent diabetes or gestational diabetes diagnosed during the index pregnancy. Birth weight, gestational age, and maternal prepregnancy weight also were obtained from the database.

Mothers were asked about breast- and formula-feeding, timing, and the introduction of other solid foods and beverages. Mixed feeding was commonly reported, so a measure of breast milk-months was developed that incorporated duration and exclusivity. For exclusively breastfed infants, duration was equal to the age of the child (months) when breastfeeding was stopped. Breastfeeding exclusivity was quantified using weights from 0 to 1, with exclusive breastfeeding having a weight of 1 and exclusive formula-feeding having a weight of 0. For infants who were ever fed formula, mothers classified their infant feeding as formula only (0), more formula than breast milk (0.25), equal breast milk and formula (0.50), or more breast milk than formula (0.75).

The breast milk-months measure incorporated duration and exclusivity to estimate an overall breast milk dose equivalent in months. Based on a formula that included breastfeeding exclusivity and duration, breastfeeding status was categorized as low (less than 6 breast milk-months) and adequate (at least 6 breast milk-months).

The subscapular-to-triceps skinfold ratio (STR) was calculated to assess regional differences in subcutaneous fat distribution. In addition, an MRI of the abdominal region was used to quantify VAT and SAT.

The mean age was 9.6 years for exposed youth and 10.6 years for unexposed youth at the study visit – a difference that was significant. Exposed youth were significantly more likely to be non-Hispanic white or Hispanic, and a larger proportion of exposed youth self-reported a Tanner stage less than 2 (prepubertal). Mothers with diabetes during pregnancy were significantly older on average than mothers whose pregnancies were not complicated by diabetes. Exposed and unexposed offspring were not significantly different in terms of intrauterine growth, socioeconomic factors or infant feeding practices.

Among adolescents with low breastfeeding status, exposure to diabetes in utero was associated with a 1.7 kg/m2 greater BMI (significant); a 5.8 cm greater waist circumference (significant); a 6.1 cm2 higher VAT; a 44.6 cm2 greater SAT (significant); and a 0.11 higher STR (significant). The association between exposure to diabetes in utero and the adiposity parameters was substantially reduced and not significant for adolescents with adequate breastfeeding in infancy with a 0.7 kg/m2 lower BMI (significant); a 2.7 cm greater waist circumference; a 2.1 cm2 greater VAT; a 23.4 cm2 greater SAT; and a 0.05 greater STR among exposed versus unexposed children.

Importantly, all measures of adiposity were influenced, including the more sensitive VAT and SAT, the investigators noted. Although the mechanisms that trigger adipose tissue deposition in specific locations at different periods of fetal development or in childhood remain unclear, the identification of strategies to alter the long-term development of fat deposition/accumulation is necessary to minimize the significant increased morbidity risk associated with childhood obesity. "Fetal life and early infancy both represent critical periods when obesity begins and may be effectively minimized by targeted prevention strategies," they said.

Further work is needed to confirm this finding in larger populations though, and to determine if the reductions in adiposity continue into adulthood.

Dr. Crume and her associates reported that they have no relevant financial relationships.