Denise Napoli

NEW YORK – All patients, regardless of skin color, need to be screened for skin cancer and receive sun protection education, according to Dr. Brooke A. Jackson.

"We have done a pretty good job of relaying the skin cancer awareness/risk message to fair skin types, but we still need to work on the message to darker skin types," noted Dr. Jackson. "This includes offering skin cancer screenings to all of our patients regardless of skin color, having a [high] level of suspicion for nonhealing lesions or changing lesions in darker skin types, and discussing skin cancer risks and sun protection with our patients who have darker skin."

Dr. Jackson and her colleagues surveyed 105 dark-skinned adult patients who presented to her private practice in Chicago for a variety of reasons.

Overall, 91 patients identified themselves as black, 9 as Hispanic, 4 as Asian, and 1 as Middle Eastern, noted Dr. Jackson, clinical assistant professor of dermatology at Northwestern University in Chicago.

Of the 105 patients, 9 had a Fitzpatrick skin type of III, 29 had type IV, 64 had type V, and 3 patients had type VI.

Patients read the descriptions for several types of lesions and were asked to identify whether a particular lesion was a risk factor for skin cancer, including "dark spot with irregular border," "new mole," "nonhealing wound," "bleeding lesion," and "shiny pink bump."

Dr. Jackson found that "regardless of ethnic origin or skin type, ‘dark spot with irregular borders’ followed by ‘new mole’ were the most frequent top two choices" selected as being high risk for skin cancer.

"Shiny pink bump" was the least selected choice for recognition of skin cancer and was not selected by any respondents with skin types III and VI, she reported.

Indeed, "15 respondents, most of whom were of African ethnicity and/or had skin type V, were unaware that skin of color was at risk for developing skin cancer," noted Dr. Jackson and her colleagues.

As for skin protective behaviors, 70 of the 91 black patients reported use of sunblock or sunscreen, and 47 used protective clothing. Twenty-nine black patients practiced sun avoidance. Ten of the black patients reported that they took no precaution at all with regard to sun exposure. Similarly, among the 64 Fitzpatrick skin type V patients, 13 reported practicing no sun protection.

Dr. Jackson stated that neither she nor her colleagues had any disclosures relevant to this presentation.

NEW YORK – All patients, regardless of skin color, need to be screened for skin cancer and receive sun protection education, according to Dr. Brooke A. Jackson.

"We have done a pretty good job of relaying the skin cancer awareness/risk message to fair skin types, but we still need to work on the message to darker skin types," noted Dr. Jackson. "This includes offering skin cancer screenings to all of our patients regardless of skin color, having a [high] level of suspicion for nonhealing lesions or changing lesions in darker skin types, and discussing skin cancer risks and sun protection with our patients who have darker skin."

Dr. Jackson and her colleagues surveyed 105 dark-skinned adult patients who presented to her private practice in Chicago for a variety of reasons.

Overall, 91 patients identified themselves as black, 9 as Hispanic, 4 as Asian, and 1 as Middle Eastern, noted Dr. Jackson, clinical assistant professor of dermatology at Northwestern University in Chicago.

Of the 105 patients, 9 had a Fitzpatrick skin type of III, 29 had type IV, 64 had type V, and 3 patients had type VI.

Patients read the descriptions for several types of lesions and were asked to identify whether a particular lesion was a risk factor for skin cancer, including "dark spot with irregular border," "new mole," "nonhealing wound," "bleeding lesion," and "shiny pink bump."

Dr. Jackson found that "regardless of ethnic origin or skin type, ‘dark spot with irregular borders’ followed by ‘new mole’ were the most frequent top two choices" selected as being high risk for skin cancer.

"Shiny pink bump" was the least selected choice for recognition of skin cancer and was not selected by any respondents with skin types III and VI, she reported.

Indeed, "15 respondents, most of whom were of African ethnicity and/or had skin type V, were unaware that skin of color was at risk for developing skin cancer," noted Dr. Jackson and her colleagues.

As for skin protective behaviors, 70 of the 91 black patients reported use of sunblock or sunscreen, and 47 used protective clothing. Twenty-nine black patients practiced sun avoidance. Ten of the black patients reported that they took no precaution at all with regard to sun exposure. Similarly, among the 64 Fitzpatrick skin type V patients, 13 reported practicing no sun protection.

Dr. Jackson stated that neither she nor her colleagues had any disclosures relevant to this presentation.

NEW YORK – All patients, regardless of skin color, need to be screened for skin cancer and receive sun protection education, according to Dr. Brooke A. Jackson.

"We have done a pretty good job of relaying the skin cancer awareness/risk message to fair skin types, but we still need to work on the message to darker skin types," noted Dr. Jackson. "This includes offering skin cancer screenings to all of our patients regardless of skin color, having a [high] level of suspicion for nonhealing lesions or changing lesions in darker skin types, and discussing skin cancer risks and sun protection with our patients who have darker skin."

Dr. Jackson and her colleagues surveyed 105 dark-skinned adult patients who presented to her private practice in Chicago for a variety of reasons.

Overall, 91 patients identified themselves as black, 9 as Hispanic, 4 as Asian, and 1 as Middle Eastern, noted Dr. Jackson, clinical assistant professor of dermatology at Northwestern University in Chicago.

Of the 105 patients, 9 had a Fitzpatrick skin type of III, 29 had type IV, 64 had type V, and 3 patients had type VI.

Patients read the descriptions for several types of lesions and were asked to identify whether a particular lesion was a risk factor for skin cancer, including "dark spot with irregular border," "new mole," "nonhealing wound," "bleeding lesion," and "shiny pink bump."

Dr. Jackson found that "regardless of ethnic origin or skin type, ‘dark spot with irregular borders’ followed by ‘new mole’ were the most frequent top two choices" selected as being high risk for skin cancer.

"Shiny pink bump" was the least selected choice for recognition of skin cancer and was not selected by any respondents with skin types III and VI, she reported.

Indeed, "15 respondents, most of whom were of African ethnicity and/or had skin type V, were unaware that skin of color was at risk for developing skin cancer," noted Dr. Jackson and her colleagues.

As for skin protective behaviors, 70 of the 91 black patients reported use of sunblock or sunscreen, and 47 used protective clothing. Twenty-nine black patients practiced sun avoidance. Ten of the black patients reported that they took no precaution at all with regard to sun exposure. Similarly, among the 64 Fitzpatrick skin type V patients, 13 reported practicing no sun protection.

Dr. Jackson stated that neither she nor her colleagues had any disclosures relevant to this presentation.

A panel of 10 serum biomarkers for lung cancer could offer more accurate interpretation of nodules detected on computed tomography, avoiding invasive biopsies and radiographic follow-up.

"CT-screening detection of an indeterminate pulmonary nodule, a nonspecific but frequent finding in high-risk subjects with a smoking history, creates a diagnostic dilemma," wrote investigator William L. Bigbee, Ph.D., and his colleagues in the April issue of the Journal of Thoracic Oncology.

"Although the biomarker model we described could not detect every lung cancer, it offers a significant clinical improvement over CT imaging alone.... Also, patients with nodules not identified as cancer by the model would continue to receive follow-up clinical monitoring and would be biopsied if the nodules grew in size, which is the current standard of care," the researchers said (J. Thorac. Oncol. 2012;7:698-708).

Dr. Bigbee of the University of Pittsburgh and his colleagues cite results of the National Lung Screening Trial (NLST), published in June 2011, which showed for the first time that low-dose CT screening of heavy smokers could reduce lung cancer mortality by 20%. But, as Dr. Bigbee et al. note in the current study, the "vast majority" of positive results in the NLST program turned out to be false after diagnostic evaluation. Moreover, smaller nodules are least likely to be malignant and least likely to be considered for biopsy or surgery.

For the current study, the researchers initially looked at a "training" set of 56 patients with non–small cell lung cancer in the University of Pittsburgh Cancer Institute Georgia Cooper Lung Research Registry. These cases were matched with 56 controls from the Pittsburgh Lung Screening Study (PLuSS), a volunteer cohort at high risk for lung cancer. All controls were known to be cancer free. The authors then analyzed serum samples from both groups for the presence of 70 potential cancer-associated biomarkers.

"Together, these biomarkers incorporate a wide range of host and tumor derived factors that allow a broad analysis of the lung cancer/host interaction, and includes a number of previously described epithelial cell cancer-associated serological markers," wrote the investigators. "The initial goal of this discovery study was to identify the most robust subset of these biomarkers to discriminate lung cancer and matched control samples."

Using a rule-learning algorithm, they whittled the field of potential biomarkers down to eight: prolactin, transthyretin, E-selectin, C-C motif, thrombospondin-1, chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor 1, and receptor tyrosine-protein kinase erbB-2.

"This rule model distinguished the lung cancer case samples from the control samples in the training set with a sensitivity of 92.9% and specificity of 87.5%," they reported.

Ultimately, two additional biomarkers were added to the panel – cytokeratin fragment 19-9 and serum amyloid A protein – and an additional set of cases and controls, 30 in each cohort, was assessed, in a blinded "verification" set.

In this set, the authors calculated an overall classification performance of 73.3% sensitivity and 93.3% specificity. Only 10 misclassifications occurred among 60 predictions made. Moreover, when looking at accuracy according to patient demographic factors, the researchers found that the 10-biomarker panel was equally good at distinguishing males and females as either cases or controls and that neither current smoking status nor airway obstruction skewed the results.

Nor did the presence of nodules visible on CT scan confound the biomarkers’ predictive value. "In fact, those PLuSS subjects with a suspicious nodule were more often correctly classified as controls than those with no nodule or a benign nodule," wrote the authors.

They add that all nodules found in controls remained clinically noncancerous at least 3 years after initial detection, with either resolution or no further growth on subsequent CT scans.

Finally, Dr. Bigbee assessed the model’s accuracy with early- vs. late-stage tumors.

"Among stage I/II lung tumors, the 10-biomarker panel misclassified 15% of stage I/II tumors in the verification set, compared to 50% of the stage III/IV tumors, suggesting the model performs well in discriminating early-stage lung cancer," he wrote. "With a specificity of 93.3%, the 10-biomarker model [balanced accuracy] was 89.2% in stage I/II disease."

The authors conceded that the biomarker panel presented here would not suffice for general population screening. However, in a clinical context, among high-risk patients, the model "may provide clinical utility in guiding interpretation of screening CT scans, even in tobacco-exposed persons with COPD or emphysema," they wrote.

"Formal validation in larger patient cohorts will be needed to confirm these initial findings."

The authors disclosed that funding for this study was supplied by grants from the National Cancer Institute. Dr. Bigbee stated that there were no personal disclosures.

A panel of 10 serum biomarkers for lung cancer could offer more accurate interpretation of nodules detected on computed tomography, avoiding invasive biopsies and radiographic follow-up.

"CT-screening detection of an indeterminate pulmonary nodule, a nonspecific but frequent finding in high-risk subjects with a smoking history, creates a diagnostic dilemma," wrote investigator William L. Bigbee, Ph.D., and his colleagues in the April issue of the Journal of Thoracic Oncology.

"Although the biomarker model we described could not detect every lung cancer, it offers a significant clinical improvement over CT imaging alone.... Also, patients with nodules not identified as cancer by the model would continue to receive follow-up clinical monitoring and would be biopsied if the nodules grew in size, which is the current standard of care," the researchers said (J. Thorac. Oncol. 2012;7:698-708).

Dr. Bigbee of the University of Pittsburgh and his colleagues cite results of the National Lung Screening Trial (NLST), published in June 2011, which showed for the first time that low-dose CT screening of heavy smokers could reduce lung cancer mortality by 20%. But, as Dr. Bigbee et al. note in the current study, the "vast majority" of positive results in the NLST program turned out to be false after diagnostic evaluation. Moreover, smaller nodules are least likely to be malignant and least likely to be considered for biopsy or surgery.

For the current study, the researchers initially looked at a "training" set of 56 patients with non–small cell lung cancer in the University of Pittsburgh Cancer Institute Georgia Cooper Lung Research Registry. These cases were matched with 56 controls from the Pittsburgh Lung Screening Study (PLuSS), a volunteer cohort at high risk for lung cancer. All controls were known to be cancer free. The authors then analyzed serum samples from both groups for the presence of 70 potential cancer-associated biomarkers.

"Together, these biomarkers incorporate a wide range of host and tumor derived factors that allow a broad analysis of the lung cancer/host interaction, and includes a number of previously described epithelial cell cancer-associated serological markers," wrote the investigators. "The initial goal of this discovery study was to identify the most robust subset of these biomarkers to discriminate lung cancer and matched control samples."

Using a rule-learning algorithm, they whittled the field of potential biomarkers down to eight: prolactin, transthyretin, E-selectin, C-C motif, thrombospondin-1, chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor 1, and receptor tyrosine-protein kinase erbB-2.

"This rule model distinguished the lung cancer case samples from the control samples in the training set with a sensitivity of 92.9% and specificity of 87.5%," they reported.

Ultimately, two additional biomarkers were added to the panel – cytokeratin fragment 19-9 and serum amyloid A protein – and an additional set of cases and controls, 30 in each cohort, was assessed, in a blinded "verification" set.

In this set, the authors calculated an overall classification performance of 73.3% sensitivity and 93.3% specificity. Only 10 misclassifications occurred among 60 predictions made. Moreover, when looking at accuracy according to patient demographic factors, the researchers found that the 10-biomarker panel was equally good at distinguishing males and females as either cases or controls and that neither current smoking status nor airway obstruction skewed the results.

Nor did the presence of nodules visible on CT scan confound the biomarkers’ predictive value. "In fact, those PLuSS subjects with a suspicious nodule were more often correctly classified as controls than those with no nodule or a benign nodule," wrote the authors.

They add that all nodules found in controls remained clinically noncancerous at least 3 years after initial detection, with either resolution or no further growth on subsequent CT scans.

Finally, Dr. Bigbee assessed the model’s accuracy with early- vs. late-stage tumors.

"Among stage I/II lung tumors, the 10-biomarker panel misclassified 15% of stage I/II tumors in the verification set, compared to 50% of the stage III/IV tumors, suggesting the model performs well in discriminating early-stage lung cancer," he wrote. "With a specificity of 93.3%, the 10-biomarker model [balanced accuracy] was 89.2% in stage I/II disease."

The authors conceded that the biomarker panel presented here would not suffice for general population screening. However, in a clinical context, among high-risk patients, the model "may provide clinical utility in guiding interpretation of screening CT scans, even in tobacco-exposed persons with COPD or emphysema," they wrote.

"Formal validation in larger patient cohorts will be needed to confirm these initial findings."

The authors disclosed that funding for this study was supplied by grants from the National Cancer Institute. Dr. Bigbee stated that there were no personal disclosures.

A panel of 10 serum biomarkers for lung cancer could offer more accurate interpretation of nodules detected on computed tomography, avoiding invasive biopsies and radiographic follow-up.

"CT-screening detection of an indeterminate pulmonary nodule, a nonspecific but frequent finding in high-risk subjects with a smoking history, creates a diagnostic dilemma," wrote investigator William L. Bigbee, Ph.D., and his colleagues in the April issue of the Journal of Thoracic Oncology.

"Although the biomarker model we described could not detect every lung cancer, it offers a significant clinical improvement over CT imaging alone.... Also, patients with nodules not identified as cancer by the model would continue to receive follow-up clinical monitoring and would be biopsied if the nodules grew in size, which is the current standard of care," the researchers said (J. Thorac. Oncol. 2012;7:698-708).

Dr. Bigbee of the University of Pittsburgh and his colleagues cite results of the National Lung Screening Trial (NLST), published in June 2011, which showed for the first time that low-dose CT screening of heavy smokers could reduce lung cancer mortality by 20%. But, as Dr. Bigbee et al. note in the current study, the "vast majority" of positive results in the NLST program turned out to be false after diagnostic evaluation. Moreover, smaller nodules are least likely to be malignant and least likely to be considered for biopsy or surgery.

For the current study, the researchers initially looked at a "training" set of 56 patients with non–small cell lung cancer in the University of Pittsburgh Cancer Institute Georgia Cooper Lung Research Registry. These cases were matched with 56 controls from the Pittsburgh Lung Screening Study (PLuSS), a volunteer cohort at high risk for lung cancer. All controls were known to be cancer free. The authors then analyzed serum samples from both groups for the presence of 70 potential cancer-associated biomarkers.

"Together, these biomarkers incorporate a wide range of host and tumor derived factors that allow a broad analysis of the lung cancer/host interaction, and includes a number of previously described epithelial cell cancer-associated serological markers," wrote the investigators. "The initial goal of this discovery study was to identify the most robust subset of these biomarkers to discriminate lung cancer and matched control samples."

Using a rule-learning algorithm, they whittled the field of potential biomarkers down to eight: prolactin, transthyretin, E-selectin, C-C motif, thrombospondin-1, chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor 1, and receptor tyrosine-protein kinase erbB-2.

"This rule model distinguished the lung cancer case samples from the control samples in the training set with a sensitivity of 92.9% and specificity of 87.5%," they reported.

Ultimately, two additional biomarkers were added to the panel – cytokeratin fragment 19-9 and serum amyloid A protein – and an additional set of cases and controls, 30 in each cohort, was assessed, in a blinded "verification" set.

In this set, the authors calculated an overall classification performance of 73.3% sensitivity and 93.3% specificity. Only 10 misclassifications occurred among 60 predictions made. Moreover, when looking at accuracy according to patient demographic factors, the researchers found that the 10-biomarker panel was equally good at distinguishing males and females as either cases or controls and that neither current smoking status nor airway obstruction skewed the results.

Nor did the presence of nodules visible on CT scan confound the biomarkers’ predictive value. "In fact, those PLuSS subjects with a suspicious nodule were more often correctly classified as controls than those with no nodule or a benign nodule," wrote the authors.

They add that all nodules found in controls remained clinically noncancerous at least 3 years after initial detection, with either resolution or no further growth on subsequent CT scans.

Finally, Dr. Bigbee assessed the model’s accuracy with early- vs. late-stage tumors.

"Among stage I/II lung tumors, the 10-biomarker panel misclassified 15% of stage I/II tumors in the verification set, compared to 50% of the stage III/IV tumors, suggesting the model performs well in discriminating early-stage lung cancer," he wrote. "With a specificity of 93.3%, the 10-biomarker model [balanced accuracy] was 89.2% in stage I/II disease."

The authors conceded that the biomarker panel presented here would not suffice for general population screening. However, in a clinical context, among high-risk patients, the model "may provide clinical utility in guiding interpretation of screening CT scans, even in tobacco-exposed persons with COPD or emphysema," they wrote.

"Formal validation in larger patient cohorts will be needed to confirm these initial findings."

The authors disclosed that funding for this study was supplied by grants from the National Cancer Institute. Dr. Bigbee stated that there were no personal disclosures.

A panel of 10 serum biomarkers for lung cancer could offer more accurate interpretation of nodules detected on computed tomography, avoiding invasive biopsies and radiographic follow-up.

"CT-screening detection of an indeterminate pulmonary nodule, a nonspecific but frequent finding in high-risk subjects with a smoking history, creates a diagnostic dilemma," wrote investigator William L. Bigbee, Ph.D., and his colleagues in the April issue of the Journal of Thoracic Oncology.

"Although the biomarker model we described could not detect every lung cancer, it offers a significant clinical improvement over CT imaging alone.... Also, patients with nodules not identified as cancer by the model would continue to receive follow-up clinical monitoring and would be biopsied if the nodules grew in size, which is the current standard of care," the researchers said (J. Thorac. Oncol. 2012;7:698-708).

Dr. Bigbee of the University of Pittsburgh and his colleagues cite results of the National Lung Screening Trial (NLST), published in June 2011, which showed for the first time that low-dose CT screening of heavy smokers could reduce lung cancer mortality by 20%. But, as Dr. Bigbee et al. note in the current study, the "vast majority" of positive results in the NLST program turned out to be false after diagnostic evaluation. Moreover, smaller nodules are least likely to be malignant and least likely to be considered for biopsy or surgery.

For the current study, the researchers initially looked at a "training" set of 56 patients with non–small cell lung cancer in the University of Pittsburgh Cancer Institute Georgia Cooper Lung Research Registry. These cases were matched with 56 controls from the Pittsburgh Lung Screening Study (PLuSS), a volunteer cohort at high risk for lung cancer. All controls were known to be cancer free. The authors then analyzed serum samples from both groups for the presence of 70 potential cancer-associated biomarkers.

"Together, these biomarkers incorporate a wide range of host and tumor derived factors that allow a broad analysis of the lung cancer/host interaction, and includes a number of previously described epithelial cell cancer-associated serological markers," wrote the investigators. "The initial goal of this discovery study was to identify the most robust subset of these biomarkers to discriminate lung cancer and matched control samples."

Using a rule-learning algorithm, they whittled the field of potential biomarkers down to eight: prolactin, transthyretin, E-selectin, C-C motif, thrombospondin-1, chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor 1, and receptor tyrosine-protein kinase erbB-2.

"This rule model distinguished the lung cancer case samples from the control samples in the training set with a sensitivity of 92.9% and specificity of 87.5%," they reported.

Ultimately, two additional biomarkers were added to the panel – cytokeratin fragment 19-9 and serum amyloid A protein – and an additional set of cases and controls, 30 in each cohort, was assessed, in a blinded "verification" set.

In this set, the authors calculated an overall classification performance of 73.3% sensitivity and 93.3% specificity. Only 10 misclassifications occurred among 60 predictions made. Moreover, when looking at accuracy according to patient demographic factors, the researchers found that the 10-biomarker panel was equally good at distinguishing males and females as either cases or controls and that neither current smoking status nor airway obstruction skewed the results.

Nor did the presence of nodules visible on CT scan confound the biomarkers’ predictive value. "In fact, those PLuSS subjects with a suspicious nodule were more often correctly classified as controls than those with no nodule or a benign nodule," wrote the authors.

They add that all nodules found in controls remained clinically noncancerous at least 3 years after initial detection, with either resolution or no further growth on subsequent CT scans.

Finally, Dr. Bigbee assessed the model’s accuracy with early- vs. late-stage tumors.

"Among stage I/II lung tumors, the 10-biomarker panel misclassified 15% of stage I/II tumors in the verification set, compared to 50% of the stage III/IV tumors, suggesting the model performs well in discriminating early-stage lung cancer," he wrote. "With a specificity of 93.3%, the 10-biomarker model [balanced accuracy] was 89.2% in stage I/II disease."

The authors conceded that the biomarker panel presented here would not suffice for general population screening. However, in a clinical context, among high-risk patients, the model "may provide clinical utility in guiding interpretation of screening CT scans, even in tobacco-exposed persons with COPD or emphysema," they wrote.

"Formal validation in larger patient cohorts will be needed to confirm these initial findings."

The authors disclosed that funding for this study was supplied by grants from the National Cancer Institute. Dr. Bigbee stated that there were no personal disclosures.

A panel of 10 serum biomarkers for lung cancer could offer more accurate interpretation of nodules detected on computed tomography, avoiding invasive biopsies and radiographic follow-up.

"CT-screening detection of an indeterminate pulmonary nodule, a nonspecific but frequent finding in high-risk subjects with a smoking history, creates a diagnostic dilemma," wrote investigator William L. Bigbee, Ph.D., and his colleagues in the April issue of the Journal of Thoracic Oncology.

"Although the biomarker model we described could not detect every lung cancer, it offers a significant clinical improvement over CT imaging alone.... Also, patients with nodules not identified as cancer by the model would continue to receive follow-up clinical monitoring and would be biopsied if the nodules grew in size, which is the current standard of care," the researchers said (J. Thorac. Oncol. 2012;7:698-708).

Dr. Bigbee of the University of Pittsburgh and his colleagues cite results of the National Lung Screening Trial (NLST), published in June 2011, which showed for the first time that low-dose CT screening of heavy smokers could reduce lung cancer mortality by 20%. But, as Dr. Bigbee et al. note in the current study, the "vast majority" of positive results in the NLST program turned out to be false after diagnostic evaluation. Moreover, smaller nodules are least likely to be malignant and least likely to be considered for biopsy or surgery.

For the current study, the researchers initially looked at a "training" set of 56 patients with non–small cell lung cancer in the University of Pittsburgh Cancer Institute Georgia Cooper Lung Research Registry. These cases were matched with 56 controls from the Pittsburgh Lung Screening Study (PLuSS), a volunteer cohort at high risk for lung cancer. All controls were known to be cancer free. The authors then analyzed serum samples from both groups for the presence of 70 potential cancer-associated biomarkers.

"Together, these biomarkers incorporate a wide range of host and tumor derived factors that allow a broad analysis of the lung cancer/host interaction, and includes a number of previously described epithelial cell cancer-associated serological markers," wrote the investigators. "The initial goal of this discovery study was to identify the most robust subset of these biomarkers to discriminate lung cancer and matched control samples."

Using a rule-learning algorithm, they whittled the field of potential biomarkers down to eight: prolactin, transthyretin, E-selectin, C-C motif, thrombospondin-1, chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor 1, and receptor tyrosine-protein kinase erbB-2.

"This rule model distinguished the lung cancer case samples from the control samples in the training set with a sensitivity of 92.9% and specificity of 87.5%," they reported.

Ultimately, two additional biomarkers were added to the panel – cytokeratin fragment 19-9 and serum amyloid A protein – and an additional set of cases and controls, 30 in each cohort, was assessed, in a blinded "verification" set.

In this set, the authors calculated an overall classification performance of 73.3% sensitivity and 93.3% specificity. Only 10 misclassifications occurred among 60 predictions made. Moreover, when looking at accuracy according to patient demographic factors, the researchers found that the 10-biomarker panel was equally good at distinguishing males and females as either cases or controls and that neither current smoking status nor airway obstruction skewed the results.

Nor did the presence of nodules visible on CT scan confound the biomarkers’ predictive value. "In fact, those PLuSS subjects with a suspicious nodule were more often correctly classified as controls than those with no nodule or a benign nodule," wrote the authors.

They add that all nodules found in controls remained clinically noncancerous at least 3 years after initial detection, with either resolution or no further growth on subsequent CT scans.

Finally, Dr. Bigbee assessed the model’s accuracy with early- vs. late-stage tumors.

"Among stage I/II lung tumors, the 10-biomarker panel misclassified 15% of stage I/II tumors in the verification set, compared to 50% of the stage III/IV tumors, suggesting the model performs well in discriminating early-stage lung cancer," he wrote. "With a specificity of 93.3%, the 10-biomarker model [balanced accuracy] was 89.2% in stage I/II disease."

The authors conceded that the biomarker panel presented here would not suffice for general population screening. However, in a clinical context, among high-risk patients, the model "may provide clinical utility in guiding interpretation of screening CT scans, even in tobacco-exposed persons with COPD or emphysema," they wrote.

"Formal validation in larger patient cohorts will be needed to confirm these initial findings."

The authors disclosed that funding for this study was supplied by grants from the National Cancer Institute. Dr. Bigbee stated that there were no personal disclosures.

A panel of 10 serum biomarkers for lung cancer could offer more accurate interpretation of nodules detected on computed tomography, avoiding invasive biopsies and radiographic follow-up.

"CT-screening detection of an indeterminate pulmonary nodule, a nonspecific but frequent finding in high-risk subjects with a smoking history, creates a diagnostic dilemma," wrote investigator William L. Bigbee, Ph.D., and his colleagues in the April issue of the Journal of Thoracic Oncology.

"Although the biomarker model we described could not detect every lung cancer, it offers a significant clinical improvement over CT imaging alone.... Also, patients with nodules not identified as cancer by the model would continue to receive follow-up clinical monitoring and would be biopsied if the nodules grew in size, which is the current standard of care," the researchers said (J. Thorac. Oncol. 2012;7:698-708).

Dr. Bigbee of the University of Pittsburgh and his colleagues cite results of the National Lung Screening Trial (NLST), published in June 2011, which showed for the first time that low-dose CT screening of heavy smokers could reduce lung cancer mortality by 20%. But, as Dr. Bigbee et al. note in the current study, the "vast majority" of positive results in the NLST program turned out to be false after diagnostic evaluation. Moreover, smaller nodules are least likely to be malignant and least likely to be considered for biopsy or surgery.

For the current study, the researchers initially looked at a "training" set of 56 patients with non–small cell lung cancer in the University of Pittsburgh Cancer Institute Georgia Cooper Lung Research Registry. These cases were matched with 56 controls from the Pittsburgh Lung Screening Study (PLuSS), a volunteer cohort at high risk for lung cancer. All controls were known to be cancer free. The authors then analyzed serum samples from both groups for the presence of 70 potential cancer-associated biomarkers.

"Together, these biomarkers incorporate a wide range of host and tumor derived factors that allow a broad analysis of the lung cancer/host interaction, and includes a number of previously described epithelial cell cancer-associated serological markers," wrote the investigators. "The initial goal of this discovery study was to identify the most robust subset of these biomarkers to discriminate lung cancer and matched control samples."

Using a rule-learning algorithm, they whittled the field of potential biomarkers down to eight: prolactin, transthyretin, E-selectin, C-C motif, thrombospondin-1, chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor 1, and receptor tyrosine-protein kinase erbB-2.

"This rule model distinguished the lung cancer case samples from the control samples in the training set with a sensitivity of 92.9% and specificity of 87.5%," they reported.

Ultimately, two additional biomarkers were added to the panel – cytokeratin fragment 19-9 and serum amyloid A protein – and an additional set of cases and controls, 30 in each cohort, was assessed, in a blinded "verification" set.

In this set, the authors calculated an overall classification performance of 73.3% sensitivity and 93.3% specificity. Only 10 misclassifications occurred among 60 predictions made. Moreover, when looking at accuracy according to patient demographic factors, the researchers found that the 10-biomarker panel was equally good at distinguishing males and females as either cases or controls and that neither current smoking status nor airway obstruction skewed the results.

Nor did the presence of nodules visible on CT scan confound the biomarkers’ predictive value. "In fact, those PLuSS subjects with a suspicious nodule were more often correctly classified as controls than those with no nodule or a benign nodule," wrote the authors.

They add that all nodules found in controls remained clinically noncancerous at least 3 years after initial detection, with either resolution or no further growth on subsequent CT scans.

Finally, Dr. Bigbee assessed the model’s accuracy with early- vs. late-stage tumors.

"Among stage I/II lung tumors, the 10-biomarker panel misclassified 15% of stage I/II tumors in the verification set, compared to 50% of the stage III/IV tumors, suggesting the model performs well in discriminating early-stage lung cancer," he wrote. "With a specificity of 93.3%, the 10-biomarker model [balanced accuracy] was 89.2% in stage I/II disease."

The authors conceded that the biomarker panel presented here would not suffice for general population screening. However, in a clinical context, among high-risk patients, the model "may provide clinical utility in guiding interpretation of screening CT scans, even in tobacco-exposed persons with COPD or emphysema," they wrote.

"Formal validation in larger patient cohorts will be needed to confirm these initial findings."

The authors disclosed that funding for this study was supplied by grants from the National Cancer Institute. Dr. Bigbee stated that there were no personal disclosures.

NEW YORK – To successfully treat alopecia in darker-skinned patients, it is important to first get to the root of a patient’s hair care regimen, according to Dr. Amy McMichael.

For the past 18 years, Dr. McMichael of Wake Forest University in Winston-Salem, N.C., has run a hair disorders clinic. She said she often finds herself at odds with patients who can’t understand why their hair won’t grow.

"Of course, we know it’s growing; it’s just breaking off. They’re having issues with damaged hair," she said at the Skin of Color Seminar Series. Patients "want me to find some underlying vitamin disorder or disease, or something [in their diet] that they can ‘cut out,’ " she said.

Photos courtesy Valerie Callender M.D.

Instead, the key is to specifically ask patients about their hair care regimen. She also uses a "60-second comb test" to assess fragility, whereby she instructs patients to brush their hair over a white pillow for 60 seconds and then count the broken and full-bulb hairs that are seen on the pillow.

More often than not, she said she finds that the number of full telogen hairs do not differ between white and darker-skinned people, but that broken hairs (versus bulb hairs) are found significantly more often in women of African descent.

This standardized approach may help convince women that, indeed, breakage – and not some underlying condition – is at the root of their problem, and that changes in behavior could have big effects.

Traction alopecia is a major issue in this population – even among patients who say they don’t pull their hair – and is likely because of the African American custom of getting tight braids starting at a young age. "They tell me their hair braids were so tight, they couldn’t chew the next day," she said. "That is not normal."

Additionally, many skin of color patients use powerful, lye-based chemical relaxers. The damage inflicted by these products, combined with braids, increases the risk for alopecia.

She pointed to a 2008 study of 574 African school girls and 604 African women that showed that females who both relaxed and braided their hair had a 3.5 times greater risk for traction alopecia, compared with patients who did neither (J. Am. Acad. Dermatol. 2008;59:432-8).

Central centrifugal scarring alopecia is also associated with particular cultural practices. For example, Dr. McMichael cited a 2009 study that looked at 101 black women with the condition and found that there was a strong association between scarring alopecia and patients who reported using sewn-in hair weaves and braided styles with hair extensions (J. Am. Acad. Dermatol. 2009;60:574-8).

A second 2011 study by Dr. McMichael and her colleagues confirmed this, but also found associations with chemical relaxers in 44 surveyed patients (Cosmet. Dermatol. 2011;24:331-7).

She recommends that patients discontinue tight braids, sewn-in weaves, relaxers, and heat treatments. "A lot of women still go under hooded hair dryers," she said. She also advocates serial trimming of the hair every 6-8 weeks, as well as gentle hair conditioning with positively charged silicones and dimethicone coating agents.

"These work very nicely in this population," she said. She also recommends using foams as a vehicle for treatments when available. For patients with more severe issues, however, she has administered intralesional corticosteroids, and followed with an off-label use of topical minoxidil.

Additionally, "a lot of women do well with surgical hair restoration," she said, despite initial patient concerns about it being prohibitively expensive. "It might be much less expensive [than patients think] because they have a small area to treat."

Finally, Dr. McMichael said she refers patients with cicatricial alopecia to the Cicatricial Alopecia Research Foundation.

Dr. McMichael stated that she has been an investigator for Abbott, Allergan, Intendis (now Bayer HealthCare), and Procter and Gamble. She also disclosed serving as a consultant for Allergan, Galderma, Guthy-Ranker, Johnson and Johnson, Procter and Gamble, and Stiefel.

NEW YORK – To successfully treat alopecia in darker-skinned patients, it is important to first get to the root of a patient’s hair care regimen, according to Dr. Amy McMichael.

For the past 18 years, Dr. McMichael of Wake Forest University in Winston-Salem, N.C., has run a hair disorders clinic. She said she often finds herself at odds with patients who can’t understand why their hair won’t grow.

"Of course, we know it’s growing; it’s just breaking off. They’re having issues with damaged hair," she said at the Skin of Color Seminar Series. Patients "want me to find some underlying vitamin disorder or disease, or something [in their diet] that they can ‘cut out,’ " she said.

Photos courtesy Valerie Callender M.D.

Instead, the key is to specifically ask patients about their hair care regimen. She also uses a "60-second comb test" to assess fragility, whereby she instructs patients to brush their hair over a white pillow for 60 seconds and then count the broken and full-bulb hairs that are seen on the pillow.

More often than not, she said she finds that the number of full telogen hairs do not differ between white and darker-skinned people, but that broken hairs (versus bulb hairs) are found significantly more often in women of African descent.

This standardized approach may help convince women that, indeed, breakage – and not some underlying condition – is at the root of their problem, and that changes in behavior could have big effects.

Traction alopecia is a major issue in this population – even among patients who say they don’t pull their hair – and is likely because of the African American custom of getting tight braids starting at a young age. "They tell me their hair braids were so tight, they couldn’t chew the next day," she said. "That is not normal."

Additionally, many skin of color patients use powerful, lye-based chemical relaxers. The damage inflicted by these products, combined with braids, increases the risk for alopecia.

She pointed to a 2008 study of 574 African school girls and 604 African women that showed that females who both relaxed and braided their hair had a 3.5 times greater risk for traction alopecia, compared with patients who did neither (J. Am. Acad. Dermatol. 2008;59:432-8).

Central centrifugal scarring alopecia is also associated with particular cultural practices. For example, Dr. McMichael cited a 2009 study that looked at 101 black women with the condition and found that there was a strong association between scarring alopecia and patients who reported using sewn-in hair weaves and braided styles with hair extensions (J. Am. Acad. Dermatol. 2009;60:574-8).

A second 2011 study by Dr. McMichael and her colleagues confirmed this, but also found associations with chemical relaxers in 44 surveyed patients (Cosmet. Dermatol. 2011;24:331-7).

She recommends that patients discontinue tight braids, sewn-in weaves, relaxers, and heat treatments. "A lot of women still go under hooded hair dryers," she said. She also advocates serial trimming of the hair every 6-8 weeks, as well as gentle hair conditioning with positively charged silicones and dimethicone coating agents.

"These work very nicely in this population," she said. She also recommends using foams as a vehicle for treatments when available. For patients with more severe issues, however, she has administered intralesional corticosteroids, and followed with an off-label use of topical minoxidil.

Additionally, "a lot of women do well with surgical hair restoration," she said, despite initial patient concerns about it being prohibitively expensive. "It might be much less expensive [than patients think] because they have a small area to treat."

Finally, Dr. McMichael said she refers patients with cicatricial alopecia to the Cicatricial Alopecia Research Foundation.

Dr. McMichael stated that she has been an investigator for Abbott, Allergan, Intendis (now Bayer HealthCare), and Procter and Gamble. She also disclosed serving as a consultant for Allergan, Galderma, Guthy-Ranker, Johnson and Johnson, Procter and Gamble, and Stiefel.

NEW YORK – To successfully treat alopecia in darker-skinned patients, it is important to first get to the root of a patient’s hair care regimen, according to Dr. Amy McMichael.

For the past 18 years, Dr. McMichael of Wake Forest University in Winston-Salem, N.C., has run a hair disorders clinic. She said she often finds herself at odds with patients who can’t understand why their hair won’t grow.

"Of course, we know it’s growing; it’s just breaking off. They’re having issues with damaged hair," she said at the Skin of Color Seminar Series. Patients "want me to find some underlying vitamin disorder or disease, or something [in their diet] that they can ‘cut out,’ " she said.

Photos courtesy Valerie Callender M.D.

Instead, the key is to specifically ask patients about their hair care regimen. She also uses a "60-second comb test" to assess fragility, whereby she instructs patients to brush their hair over a white pillow for 60 seconds and then count the broken and full-bulb hairs that are seen on the pillow.

More often than not, she said she finds that the number of full telogen hairs do not differ between white and darker-skinned people, but that broken hairs (versus bulb hairs) are found significantly more often in women of African descent.

This standardized approach may help convince women that, indeed, breakage – and not some underlying condition – is at the root of their problem, and that changes in behavior could have big effects.

Traction alopecia is a major issue in this population – even among patients who say they don’t pull their hair – and is likely because of the African American custom of getting tight braids starting at a young age. "They tell me their hair braids were so tight, they couldn’t chew the next day," she said. "That is not normal."

Additionally, many skin of color patients use powerful, lye-based chemical relaxers. The damage inflicted by these products, combined with braids, increases the risk for alopecia.

She pointed to a 2008 study of 574 African school girls and 604 African women that showed that females who both relaxed and braided their hair had a 3.5 times greater risk for traction alopecia, compared with patients who did neither (J. Am. Acad. Dermatol. 2008;59:432-8).

Central centrifugal scarring alopecia is also associated with particular cultural practices. For example, Dr. McMichael cited a 2009 study that looked at 101 black women with the condition and found that there was a strong association between scarring alopecia and patients who reported using sewn-in hair weaves and braided styles with hair extensions (J. Am. Acad. Dermatol. 2009;60:574-8).

A second 2011 study by Dr. McMichael and her colleagues confirmed this, but also found associations with chemical relaxers in 44 surveyed patients (Cosmet. Dermatol. 2011;24:331-7).

She recommends that patients discontinue tight braids, sewn-in weaves, relaxers, and heat treatments. "A lot of women still go under hooded hair dryers," she said. She also advocates serial trimming of the hair every 6-8 weeks, as well as gentle hair conditioning with positively charged silicones and dimethicone coating agents.

"These work very nicely in this population," she said. She also recommends using foams as a vehicle for treatments when available. For patients with more severe issues, however, she has administered intralesional corticosteroids, and followed with an off-label use of topical minoxidil.

Additionally, "a lot of women do well with surgical hair restoration," she said, despite initial patient concerns about it being prohibitively expensive. "It might be much less expensive [than patients think] because they have a small area to treat."

Finally, Dr. McMichael said she refers patients with cicatricial alopecia to the Cicatricial Alopecia Research Foundation.

Dr. McMichael stated that she has been an investigator for Abbott, Allergan, Intendis (now Bayer HealthCare), and Procter and Gamble. She also disclosed serving as a consultant for Allergan, Galderma, Guthy-Ranker, Johnson and Johnson, Procter and Gamble, and Stiefel.

Unprimed, higher dysfunctional attitude scale scores in a group of depressive cognitive therapy responders predicted depression relapse and recurrence.

On the other hand, primed negative mood was not associated with cognitive reactivity or dysfunctional attitudes in responders.

The findings "challenge the idea that it is necessary to prime mood in order to maximize dysfunctional attitudes’ prediction of depressive relapse and/or recurrence," reported Robin B. Jarrett, Ph.D., and her associates. The report is in the May issue of Behaviour Research and Therapy.

Dr. Jarrett of the University of Texas Southwestern Medical Center, Dallas, and her colleagues looked at 207 patients aged 18-70 years with DSM-IV nonpsychotic, recurrent major depressive disorder.

All patients had previously responded to either 16 or 20 sessions of acute phase cognitive therapy but were considered to be at higher risk based on a Hamilton Rating Scale for Depression (HRSD₁₇) score greater than or equal to 7 over the previous seven acute phase evaluations (Behav. Res. Ther. 2012:50;280-6).

Upon completion of the acute phase of cognitive therapy, patients performed the Visual Analogue Scale (VAS) and the Dysfunctional Attitudes Scale (DAS) and then underwent a mood induction procedure. Overall, 80% of patients were successfully primed to have a worsened mood, while the remaining 20% reported unchanged or improved moods after priming.

Following the mood priming, patients completed a second VAS and an alternate DAS form.

The authors found, to their surprise, that there was no significant change in patients’ mean DAS scores pre- and post mood induction.

"Because we did not observe the hypothesized negative cognitive reactivity, we examined the extent to which ... unprimed DAS scores at the end of acute phase therapy predicted relapse and/or recurrence," wrote the authors.

In this case, the DAS scores did not predict relapse or recurrence in the initial 8 months of postacute, continuation therapy.

"However, these unprimed DAS scores following acute phase cognitive therapy were predictive of relapse and/or recurrence across both the first year (20 months postrandomization) and second year of follow-up (i.e., full 32 months postrandomization)," they found.

Indeed, after the researchers controlled for posttreatment depression severity, patients with higher DAS score were at greater risk of relapse/recurrence over 20 months (hazard ratio = 1.01) and 32 months post randomization (HR also 1.01) after completion of the acute phase of cognitive therapy, compared with patients with a 1-unit-lower DAS score.

That translated to a 1.33-fold greater risk for patients with DAS scores equal to one standard deviation (30.2) higher over 20 months, and a similar figure (HR = 1.32) over 32 months – "a large, clinically relevant difference" in relapse vulnerability.

"The fact that cognitive reactivity was not evident in the current study suggests that the cognitive therapy responders may have been activating a behavior or a yet to be identified skill, perhaps learned in cognitive therapy, that prevented an increase in dysfunctional thoughts even in the presence of a negative affect shift," postulated the researchers.

"Future research may examine the change in cognitive reactivity (both positive and negative) throughout the course of illness before, during, and following different modalities of treatment," they wrote.

Several study authors disclosed ties with multiple pharmaceutical companies. The study was supported by Eli Lilly and Company.

Unprimed, higher dysfunctional attitude scale scores in a group of depressive cognitive therapy responders predicted depression relapse and recurrence.

On the other hand, primed negative mood was not associated with cognitive reactivity or dysfunctional attitudes in responders.

The findings "challenge the idea that it is necessary to prime mood in order to maximize dysfunctional attitudes’ prediction of depressive relapse and/or recurrence," reported Robin B. Jarrett, Ph.D., and her associates. The report is in the May issue of Behaviour Research and Therapy.

Dr. Jarrett of the University of Texas Southwestern Medical Center, Dallas, and her colleagues looked at 207 patients aged 18-70 years with DSM-IV nonpsychotic, recurrent major depressive disorder.

All patients had previously responded to either 16 or 20 sessions of acute phase cognitive therapy but were considered to be at higher risk based on a Hamilton Rating Scale for Depression (HRSD₁₇) score greater than or equal to 7 over the previous seven acute phase evaluations (Behav. Res. Ther. 2012:50;280-6).

Upon completion of the acute phase of cognitive therapy, patients performed the Visual Analogue Scale (VAS) and the Dysfunctional Attitudes Scale (DAS) and then underwent a mood induction procedure. Overall, 80% of patients were successfully primed to have a worsened mood, while the remaining 20% reported unchanged or improved moods after priming.

Following the mood priming, patients completed a second VAS and an alternate DAS form.

The authors found, to their surprise, that there was no significant change in patients’ mean DAS scores pre- and post mood induction.

"Because we did not observe the hypothesized negative cognitive reactivity, we examined the extent to which ... unprimed DAS scores at the end of acute phase therapy predicted relapse and/or recurrence," wrote the authors.

In this case, the DAS scores did not predict relapse or recurrence in the initial 8 months of postacute, continuation therapy.

"However, these unprimed DAS scores following acute phase cognitive therapy were predictive of relapse and/or recurrence across both the first year (20 months postrandomization) and second year of follow-up (i.e., full 32 months postrandomization)," they found.

Indeed, after the researchers controlled for posttreatment depression severity, patients with higher DAS score were at greater risk of relapse/recurrence over 20 months (hazard ratio = 1.01) and 32 months post randomization (HR also 1.01) after completion of the acute phase of cognitive therapy, compared with patients with a 1-unit-lower DAS score.

That translated to a 1.33-fold greater risk for patients with DAS scores equal to one standard deviation (30.2) higher over 20 months, and a similar figure (HR = 1.32) over 32 months – "a large, clinically relevant difference" in relapse vulnerability.

"The fact that cognitive reactivity was not evident in the current study suggests that the cognitive therapy responders may have been activating a behavior or a yet to be identified skill, perhaps learned in cognitive therapy, that prevented an increase in dysfunctional thoughts even in the presence of a negative affect shift," postulated the researchers.

"Future research may examine the change in cognitive reactivity (both positive and negative) throughout the course of illness before, during, and following different modalities of treatment," they wrote.

Several study authors disclosed ties with multiple pharmaceutical companies. The study was supported by Eli Lilly and Company.

Unprimed, higher dysfunctional attitude scale scores in a group of depressive cognitive therapy responders predicted depression relapse and recurrence.

On the other hand, primed negative mood was not associated with cognitive reactivity or dysfunctional attitudes in responders.

The findings "challenge the idea that it is necessary to prime mood in order to maximize dysfunctional attitudes’ prediction of depressive relapse and/or recurrence," reported Robin B. Jarrett, Ph.D., and her associates. The report is in the May issue of Behaviour Research and Therapy.

Dr. Jarrett of the University of Texas Southwestern Medical Center, Dallas, and her colleagues looked at 207 patients aged 18-70 years with DSM-IV nonpsychotic, recurrent major depressive disorder.

All patients had previously responded to either 16 or 20 sessions of acute phase cognitive therapy but were considered to be at higher risk based on a Hamilton Rating Scale for Depression (HRSD₁₇) score greater than or equal to 7 over the previous seven acute phase evaluations (Behav. Res. Ther. 2012:50;280-6).

Upon completion of the acute phase of cognitive therapy, patients performed the Visual Analogue Scale (VAS) and the Dysfunctional Attitudes Scale (DAS) and then underwent a mood induction procedure. Overall, 80% of patients were successfully primed to have a worsened mood, while the remaining 20% reported unchanged or improved moods after priming.

Following the mood priming, patients completed a second VAS and an alternate DAS form.

The authors found, to their surprise, that there was no significant change in patients’ mean DAS scores pre- and post mood induction.

"Because we did not observe the hypothesized negative cognitive reactivity, we examined the extent to which ... unprimed DAS scores at the end of acute phase therapy predicted relapse and/or recurrence," wrote the authors.

In this case, the DAS scores did not predict relapse or recurrence in the initial 8 months of postacute, continuation therapy.

"However, these unprimed DAS scores following acute phase cognitive therapy were predictive of relapse and/or recurrence across both the first year (20 months postrandomization) and second year of follow-up (i.e., full 32 months postrandomization)," they found.

Indeed, after the researchers controlled for posttreatment depression severity, patients with higher DAS score were at greater risk of relapse/recurrence over 20 months (hazard ratio = 1.01) and 32 months post randomization (HR also 1.01) after completion of the acute phase of cognitive therapy, compared with patients with a 1-unit-lower DAS score.

That translated to a 1.33-fold greater risk for patients with DAS scores equal to one standard deviation (30.2) higher over 20 months, and a similar figure (HR = 1.32) over 32 months – "a large, clinically relevant difference" in relapse vulnerability.

"The fact that cognitive reactivity was not evident in the current study suggests that the cognitive therapy responders may have been activating a behavior or a yet to be identified skill, perhaps learned in cognitive therapy, that prevented an increase in dysfunctional thoughts even in the presence of a negative affect shift," postulated the researchers.

"Future research may examine the change in cognitive reactivity (both positive and negative) throughout the course of illness before, during, and following different modalities of treatment," they wrote.

Several study authors disclosed ties with multiple pharmaceutical companies. The study was supported by Eli Lilly and Company.

Current heavy smokers have a more than threefold increased risk for major depression, compared to former heavy smokers.

And while the link between smoking and depression is well documented, the finding adds another twist to the debate between so-called "shared-vulnerability" and causal hypotheses about smoking and depression.

Photo: kutay tanir/iStockphoto.com

"Under the shared-vulnerability hypothesis, ever-heavy smokers may be expected to have similar elevated risk for major depressive episode irrespective of their smoking status during follow-up," wrote Salma Khaled, Ph.D., in the April issue of the Journal of Psychiatric Research.

"Our results point to the contrary."

Dr. Khaled, who was at the Mental Health Center for Research and Teaching, Canada in Toronto at the time of this research, and colleagues looked at a total of 3,824 adults from the Canadian National Population Health Survey. Participants in the survey completed a baseline interview between 1994 and 1995 and were prospectively followed since then, with new interviews conducted every second year through 2006-2007.

To be included in the study, subjects had to have maintained their smoking status as current, former, and never smokers throughout the survey follow-up duration. "Heavy" smokers were defined as those subjects who smoked 20 or more cigarettes per day (J. Psychiatr. Res. 2012;46:436-43).

"Ever-heavy smokers (current and former) may share similar genetic, behavioral, and environmental vulnerabilities, at least for heavy smoking initiation," according to Dr. Khaled, who is now at the University of Calgary (Alta.), and her associates.

If these factors were wholly to blame for depression – as dictated by the shared vulnerability hypothesis – then we would expect former-heavy smokers and current smokers would have an equal likelihood of having a major depressive episode (MDE), she reasoned.

"However, if the persistence of the exposure (current as opposed to former) had the dominant effect on the risk for MDE, then current-heavy smokers would be expected to have higher risks of MDE relative to former-heavy smokers."

Overall, the 12-year risk of MDE for the entire sample was 13.2% (95% confidence interval, 11.8-14.6), the authors found.

Stratified by smoking status, the risk of MDE among current-heavy smokers was 26.7%; among former-heavy smokers it was 7.1%, and among those who never smoked it was 12.2%.

That amounted to a significant hazard ratio of 3.1 for current heavy smokers, compared with former smokers, even after adjustment for age, sex, and stress (P less than .001).

Moreover, the hazard ratios for MDE among former-heavy smokers, compared with current smokers, decreased incrementally according to time passed since smoking cessation, from 0.5 for those who quit for between 1 and 5 years ago (P less than .05) to a hazard ratio of 0.2 among those who quit smoking greater than 21 years ago (P less than .001).

"Our findings are consistent with the view that the heavy-smoking-to-major depression pathway is causal in nature, rather than mainly due to confounding by shared vulnerability factors," noted Dr. Khaled and her associates.

Nevertheless, she acknowledged that "shared vulnerability factors including genetic vulnerability in the context of smoking and depression may not be limited to smoking initiation and heavy smoking onset, but may also influence the ability to quit smoking and maintain smoking cessation."

The authors declared no conflicts of interest in relation to this study, which they said was supported by the Canadian Institutes of Health Research.

Current heavy smokers have a more than threefold increased risk for major depression, compared to former heavy smokers.

And while the link between smoking and depression is well documented, the finding adds another twist to the debate between so-called "shared-vulnerability" and causal hypotheses about smoking and depression.

Photo: kutay tanir/iStockphoto.com

"Under the shared-vulnerability hypothesis, ever-heavy smokers may be expected to have similar elevated risk for major depressive episode irrespective of their smoking status during follow-up," wrote Salma Khaled, Ph.D., in the April issue of the Journal of Psychiatric Research.

"Our results point to the contrary."

Dr. Khaled, who was at the Mental Health Center for Research and Teaching, Canada in Toronto at the time of this research, and colleagues looked at a total of 3,824 adults from the Canadian National Population Health Survey. Participants in the survey completed a baseline interview between 1994 and 1995 and were prospectively followed since then, with new interviews conducted every second year through 2006-2007.

To be included in the study, subjects had to have maintained their smoking status as current, former, and never smokers throughout the survey follow-up duration. "Heavy" smokers were defined as those subjects who smoked 20 or more cigarettes per day (J. Psychiatr. Res. 2012;46:436-43).

"Ever-heavy smokers (current and former) may share similar genetic, behavioral, and environmental vulnerabilities, at least for heavy smoking initiation," according to Dr. Khaled, who is now at the University of Calgary (Alta.), and her associates.

If these factors were wholly to blame for depression – as dictated by the shared vulnerability hypothesis – then we would expect former-heavy smokers and current smokers would have an equal likelihood of having a major depressive episode (MDE), she reasoned.

"However, if the persistence of the exposure (current as opposed to former) had the dominant effect on the risk for MDE, then current-heavy smokers would be expected to have higher risks of MDE relative to former-heavy smokers."

Overall, the 12-year risk of MDE for the entire sample was 13.2% (95% confidence interval, 11.8-14.6), the authors found.

Stratified by smoking status, the risk of MDE among current-heavy smokers was 26.7%; among former-heavy smokers it was 7.1%, and among those who never smoked it was 12.2%.

That amounted to a significant hazard ratio of 3.1 for current heavy smokers, compared with former smokers, even after adjustment for age, sex, and stress (P less than .001).

Moreover, the hazard ratios for MDE among former-heavy smokers, compared with current smokers, decreased incrementally according to time passed since smoking cessation, from 0.5 for those who quit for between 1 and 5 years ago (P less than .05) to a hazard ratio of 0.2 among those who quit smoking greater than 21 years ago (P less than .001).

"Our findings are consistent with the view that the heavy-smoking-to-major depression pathway is causal in nature, rather than mainly due to confounding by shared vulnerability factors," noted Dr. Khaled and her associates.

Nevertheless, she acknowledged that "shared vulnerability factors including genetic vulnerability in the context of smoking and depression may not be limited to smoking initiation and heavy smoking onset, but may also influence the ability to quit smoking and maintain smoking cessation."

The authors declared no conflicts of interest in relation to this study, which they said was supported by the Canadian Institutes of Health Research.

Current heavy smokers have a more than threefold increased risk for major depression, compared to former heavy smokers.

And while the link between smoking and depression is well documented, the finding adds another twist to the debate between so-called "shared-vulnerability" and causal hypotheses about smoking and depression.

Photo: kutay tanir/iStockphoto.com

"Under the shared-vulnerability hypothesis, ever-heavy smokers may be expected to have similar elevated risk for major depressive episode irrespective of their smoking status during follow-up," wrote Salma Khaled, Ph.D., in the April issue of the Journal of Psychiatric Research.

"Our results point to the contrary."

Dr. Khaled, who was at the Mental Health Center for Research and Teaching, Canada in Toronto at the time of this research, and colleagues looked at a total of 3,824 adults from the Canadian National Population Health Survey. Participants in the survey completed a baseline interview between 1994 and 1995 and were prospectively followed since then, with new interviews conducted every second year through 2006-2007.

To be included in the study, subjects had to have maintained their smoking status as current, former, and never smokers throughout the survey follow-up duration. "Heavy" smokers were defined as those subjects who smoked 20 or more cigarettes per day (J. Psychiatr. Res. 2012;46:436-43).

"Ever-heavy smokers (current and former) may share similar genetic, behavioral, and environmental vulnerabilities, at least for heavy smoking initiation," according to Dr. Khaled, who is now at the University of Calgary (Alta.), and her associates.

If these factors were wholly to blame for depression – as dictated by the shared vulnerability hypothesis – then we would expect former-heavy smokers and current smokers would have an equal likelihood of having a major depressive episode (MDE), she reasoned.

"However, if the persistence of the exposure (current as opposed to former) had the dominant effect on the risk for MDE, then current-heavy smokers would be expected to have higher risks of MDE relative to former-heavy smokers."

Overall, the 12-year risk of MDE for the entire sample was 13.2% (95% confidence interval, 11.8-14.6), the authors found.

Stratified by smoking status, the risk of MDE among current-heavy smokers was 26.7%; among former-heavy smokers it was 7.1%, and among those who never smoked it was 12.2%.

That amounted to a significant hazard ratio of 3.1 for current heavy smokers, compared with former smokers, even after adjustment for age, sex, and stress (P less than .001).

Moreover, the hazard ratios for MDE among former-heavy smokers, compared with current smokers, decreased incrementally according to time passed since smoking cessation, from 0.5 for those who quit for between 1 and 5 years ago (P less than .05) to a hazard ratio of 0.2 among those who quit smoking greater than 21 years ago (P less than .001).

"Our findings are consistent with the view that the heavy-smoking-to-major depression pathway is causal in nature, rather than mainly due to confounding by shared vulnerability factors," noted Dr. Khaled and her associates.

Nevertheless, she acknowledged that "shared vulnerability factors including genetic vulnerability in the context of smoking and depression may not be limited to smoking initiation and heavy smoking onset, but may also influence the ability to quit smoking and maintain smoking cessation."

The authors declared no conflicts of interest in relation to this study, which they said was supported by the Canadian Institutes of Health Research.

Depression occurring before 40 years of age is associated with a longer duration of symptoms, more childhood trauma, and increased suicidal thoughts, compared with depression that begins later in life.

Indeed, "When performing diagnostics it is important to take into account that some symptoms may not occur as much at a higher age of depression onset, [although] a diagnosis may be present," wrote Dr. Nicole C.M. Korten and her colleagues in the May issue of the Journal of Affective Disorders.

"Additionally, the more personal vulnerability and chronic character of early onset depression are important factors to keep in mind for prevention and treatment strategies," they added (J. Affect. Disord. 2012;138:259-67).

Dr. Korten, of the VU University Medical Center, in Amsterdam, looked at data from the baseline assessment of 1,104 subjects enrolled in the Netherlands Study of Depression and Anxiety, an 8-year longitudinal cohort study, according to the authors.

All subjects had to have a current (within 6 months of the assessment) DSM-IV diagnosis of major depressive disorder, as well as information about the age of onset.

Symptoms of depression were assessed using the Composite International Diagnostic Interview (CIDI), with three general depressive symptoms on the DSM-IV split up into more specific descriptors: "appetite/weight change" was broken into increased vs. decreased appetite/weight; "sleep problems" was changed to insomnia vs. hypersomnia; and "psychomotor change" became retardation vs. agitation.

An assessed "duration of symptoms," in months, referred to the 4 years preceding the baseline assessment.

The overall mean age of the sample was 40.8 years; slightly less than one-third were male (32.3%).

The authors found, using a continuous age of onset indicator ranging from 4 to 64 years and adjusting for socio-demographic factors, late onset depression was associated with less sadness (P less than .001), less weight gain and fewer increases in appetite (P = .008), more weight loss and a suppressed appetite (P less than .007), fewer feelings of worthlessness (P = .01), less diminished concentration (P = .04), and fewer thoughts of death (P less than .001).

An older age of onset also was tied to a shorter duration of symptoms (P less than .001), not committing a serious suicide attempt (P less than .001), and a lower severity of depression (P = .005).

Finally, regarding the presence of comorbidities, a higher age of onset was less often associated with generalized anxiety disorder (P = .02), social phobia (P = .02), and dysthymia (P = .001).

Next, the authors analyzed early vs. late onset depression characteristics using a dichotomous model, with 40 years as the cutoff.

In this set, 80.2% of subjects were classified as having early onset disease, with a mean age of onset of 22.2 years. The remaining late onset subjects had a mean age of onset of 46.8 years.

Looking at demographic data, "As expected, [late onset depression] was associated with a higher age (odds ratio, 1.16; 95% confidence interval, 1.13-1.18), but [late onset depression] also was associated with [fewer] years of education (OR, 0.91; 95% CI, 0.86-0.96) and being male (OR, 1.67; 95% CI, 1.16-2.39)," the researchers wrote.

Characterizing according to symptomatology, the researchers found that feelings of sadness (OR, 0.41; 95% CI, 0.19-0.86) were less often observed in late onset disease.

"The psychosocial factors [like] childhood events (OR, 0.77; 95% CI, 0.68-0.88), family history (OR, 0.60; 95% CI, 0.38-0.95), and neuroticism (OR, 0.94; 95% CI, 0.91-0.97) were less often observed in late onset depression," added the researchers, "in line with the continuous age of onset analysis."

The authors stated that one major limitation of this study was the potential for recall bias among patients, since onset was assessed retrospectively.

They pointed out, however, that other studies reported high test-retest reliability of self-reported age of onset of major depression, and added that "although the exact onset point may sometimes be uncertain, participants can likely recall whether symptoms started earlier or later in life."

In conclusion, wrote Dr. Korten, the "subtle but consistent differences" observed in the current study confirm that "early onset depression might be a more chronic form of depression with probably a worse course."

She cautioned that the findings must be confirmed in further longitudinal analysis.

The authors stated that they had no conflicts of interest and disclosed no commercial funding.

Depression occurring before 40 years of age is associated with a longer duration of symptoms, more childhood trauma, and increased suicidal thoughts, compared with depression that begins later in life.

Indeed, "When performing diagnostics it is important to take into account that some symptoms may not occur as much at a higher age of depression onset, [although] a diagnosis may be present," wrote Dr. Nicole C.M. Korten and her colleagues in the May issue of the Journal of Affective Disorders.

"Additionally, the more personal vulnerability and chronic character of early onset depression are important factors to keep in mind for prevention and treatment strategies," they added (J. Affect. Disord. 2012;138:259-67).

Dr. Korten, of the VU University Medical Center, in Amsterdam, looked at data from the baseline assessment of 1,104 subjects enrolled in the Netherlands Study of Depression and Anxiety, an 8-year longitudinal cohort study, according to the authors.

All subjects had to have a current (within 6 months of the assessment) DSM-IV diagnosis of major depressive disorder, as well as information about the age of onset.

Symptoms of depression were assessed using the Composite International Diagnostic Interview (CIDI), with three general depressive symptoms on the DSM-IV split up into more specific descriptors: "appetite/weight change" was broken into increased vs. decreased appetite/weight; "sleep problems" was changed to insomnia vs. hypersomnia; and "psychomotor change" became retardation vs. agitation.

An assessed "duration of symptoms," in months, referred to the 4 years preceding the baseline assessment.

The overall mean age of the sample was 40.8 years; slightly less than one-third were male (32.3%).

The authors found, using a continuous age of onset indicator ranging from 4 to 64 years and adjusting for socio-demographic factors, late onset depression was associated with less sadness (P less than .001), less weight gain and fewer increases in appetite (P = .008), more weight loss and a suppressed appetite (P less than .007), fewer feelings of worthlessness (P = .01), less diminished concentration (P = .04), and fewer thoughts of death (P less than .001).

An older age of onset also was tied to a shorter duration of symptoms (P less than .001), not committing a serious suicide attempt (P less than .001), and a lower severity of depression (P = .005).

Finally, regarding the presence of comorbidities, a higher age of onset was less often associated with generalized anxiety disorder (P = .02), social phobia (P = .02), and dysthymia (P = .001).

Next, the authors analyzed early vs. late onset depression characteristics using a dichotomous model, with 40 years as the cutoff.

In this set, 80.2% of subjects were classified as having early onset disease, with a mean age of onset of 22.2 years. The remaining late onset subjects had a mean age of onset of 46.8 years.

Looking at demographic data, "As expected, [late onset depression] was associated with a higher age (odds ratio, 1.16; 95% confidence interval, 1.13-1.18), but [late onset depression] also was associated with [fewer] years of education (OR, 0.91; 95% CI, 0.86-0.96) and being male (OR, 1.67; 95% CI, 1.16-2.39)," the researchers wrote.

Characterizing according to symptomatology, the researchers found that feelings of sadness (OR, 0.41; 95% CI, 0.19-0.86) were less often observed in late onset disease.

"The psychosocial factors [like] childhood events (OR, 0.77; 95% CI, 0.68-0.88), family history (OR, 0.60; 95% CI, 0.38-0.95), and neuroticism (OR, 0.94; 95% CI, 0.91-0.97) were less often observed in late onset depression," added the researchers, "in line with the continuous age of onset analysis."

The authors stated that one major limitation of this study was the potential for recall bias among patients, since onset was assessed retrospectively.

They pointed out, however, that other studies reported high test-retest reliability of self-reported age of onset of major depression, and added that "although the exact onset point may sometimes be uncertain, participants can likely recall whether symptoms started earlier or later in life."

In conclusion, wrote Dr. Korten, the "subtle but consistent differences" observed in the current study confirm that "early onset depression might be a more chronic form of depression with probably a worse course."

She cautioned that the findings must be confirmed in further longitudinal analysis.

The authors stated that they had no conflicts of interest and disclosed no commercial funding.

Depression occurring before 40 years of age is associated with a longer duration of symptoms, more childhood trauma, and increased suicidal thoughts, compared with depression that begins later in life.

Indeed, "When performing diagnostics it is important to take into account that some symptoms may not occur as much at a higher age of depression onset, [although] a diagnosis may be present," wrote Dr. Nicole C.M. Korten and her colleagues in the May issue of the Journal of Affective Disorders.

"Additionally, the more personal vulnerability and chronic character of early onset depression are important factors to keep in mind for prevention and treatment strategies," they added (J. Affect. Disord. 2012;138:259-67).

Dr. Korten, of the VU University Medical Center, in Amsterdam, looked at data from the baseline assessment of 1,104 subjects enrolled in the Netherlands Study of Depression and Anxiety, an 8-year longitudinal cohort study, according to the authors.

All subjects had to have a current (within 6 months of the assessment) DSM-IV diagnosis of major depressive disorder, as well as information about the age of onset.

Symptoms of depression were assessed using the Composite International Diagnostic Interview (CIDI), with three general depressive symptoms on the DSM-IV split up into more specific descriptors: "appetite/weight change" was broken into increased vs. decreased appetite/weight; "sleep problems" was changed to insomnia vs. hypersomnia; and "psychomotor change" became retardation vs. agitation.

An assessed "duration of symptoms," in months, referred to the 4 years preceding the baseline assessment.

The overall mean age of the sample was 40.8 years; slightly less than one-third were male (32.3%).

The authors found, using a continuous age of onset indicator ranging from 4 to 64 years and adjusting for socio-demographic factors, late onset depression was associated with less sadness (P less than .001), less weight gain and fewer increases in appetite (P = .008), more weight loss and a suppressed appetite (P less than .007), fewer feelings of worthlessness (P = .01), less diminished concentration (P = .04), and fewer thoughts of death (P less than .001).

An older age of onset also was tied to a shorter duration of symptoms (P less than .001), not committing a serious suicide attempt (P less than .001), and a lower severity of depression (P = .005).

Finally, regarding the presence of comorbidities, a higher age of onset was less often associated with generalized anxiety disorder (P = .02), social phobia (P = .02), and dysthymia (P = .001).

Next, the authors analyzed early vs. late onset depression characteristics using a dichotomous model, with 40 years as the cutoff.

In this set, 80.2% of subjects were classified as having early onset disease, with a mean age of onset of 22.2 years. The remaining late onset subjects had a mean age of onset of 46.8 years.

Looking at demographic data, "As expected, [late onset depression] was associated with a higher age (odds ratio, 1.16; 95% confidence interval, 1.13-1.18), but [late onset depression] also was associated with [fewer] years of education (OR, 0.91; 95% CI, 0.86-0.96) and being male (OR, 1.67; 95% CI, 1.16-2.39)," the researchers wrote.

Characterizing according to symptomatology, the researchers found that feelings of sadness (OR, 0.41; 95% CI, 0.19-0.86) were less often observed in late onset disease.

"The psychosocial factors [like] childhood events (OR, 0.77; 95% CI, 0.68-0.88), family history (OR, 0.60; 95% CI, 0.38-0.95), and neuroticism (OR, 0.94; 95% CI, 0.91-0.97) were less often observed in late onset depression," added the researchers, "in line with the continuous age of onset analysis."

The authors stated that one major limitation of this study was the potential for recall bias among patients, since onset was assessed retrospectively.

They pointed out, however, that other studies reported high test-retest reliability of self-reported age of onset of major depression, and added that "although the exact onset point may sometimes be uncertain, participants can likely recall whether symptoms started earlier or later in life."

In conclusion, wrote Dr. Korten, the "subtle but consistent differences" observed in the current study confirm that "early onset depression might be a more chronic form of depression with probably a worse course."

She cautioned that the findings must be confirmed in further longitudinal analysis.

The authors stated that they had no conflicts of interest and disclosed no commercial funding.

Women with depression engage in fewer healthy dieting behaviors such as eating fruits and vegetables, and more unhealthy dieting behaviors such as skipping meals, than do women who are not depressed.

The finding "suggests that a ‘healthy state of mind’ may be a precursor to the adoption of adaptive efforts to lose weight," whereas unhealthy strategies "may represent a form of self-punishment due to disgust with their weight status or themselves in general," according to Meghan M. Gillen, Ph.D., and her colleagues. The report was published in the April issue of Eating Behaviors.

Dr. Gillen, of Pennsylvania State University, Abington, looked at 198 adults in the region of her institution (51% female, mean age 24.8 years) who had volunteered for a larger study about romantic relationships and health. Three-quarters of the participants identified themselves as white (Eat. Behav. 2012;13;88-93).

The average body mass index for women in this sample was 23.93 (range: 17.45-47.71), and the average BMI for men was 27.45 (range: 18.79-49.66).

Overall, 40% of men were overweight, while 25% were obese, in line with national statistics; among women, 22% were overweight, and 8% were obese, a "relatively thin" sample, compared with national figures.

The participants were asked to fill out a questionnaire that dealt with health behaviors and attitudes. The study lasted about 1.5 hours, and each participant received about $25 as payment, except for 14% of the sample who opted to receive credit toward a psychology class instead.

Depression was measured using the Center for Epidemiological Studies Scale for Depression (CES-D), and the 24-item Weight Control Behavior Scale was used to assess weight loss behaviors, with 3 items removed (diet centers with food, weight loss groups, and other) "because it is not clear whether they constitute healthy or unhealthy dieting behaviors."

"In the current study, subscales include healthy dieting behavior (12 items; for example, ‘eat more fruit and vegetables’) and unhealthy dieting behavior (9 items; for example, ‘skip meals’)," Dr. Gillen wrote.

In each case, participants indicated how often they used that strategy to lose weight in the past year, with a score of 0 meaning never, a score of 1 meaning "sometimes," and a score of 2 being "always."

A sum of items on each subscale was used by the investigators to assign an overall "healthy dieting behavior" and "unhealthy dieting behavior" score.

The authors found that even after controlling for BMI and depression, women reported using more healthy as well as unhealthy dieting tactics than men, and both men and women with higher BMIs were more likely to engage in both types of dieting behaviors.

When the authors assessed the effect of depression on the types of dieting behaviors, they determined that, among women, depression was negatively related to healthy dieting behaviors (significance test of the simple slope t(192) = –2.59) and positively related to unhealthy dieting behaviors (t[192] = 3.61), with P less than .01 for both.

Among men, depression had no effect on either healthy (t[192] = 0.63, P = .52) or unhealthy (t[192] = 1.93 P = .06) behaviors.

"These findings suggest that Stice and Bearman’s (2001) model, which predicts an association between weight management strategies and depression in female adolescents (but not their male counterparts), may be extended to adults," the authors wrote.

Moreover, "an extension of the gender additive model may be that depression tends to lead to increasingly maladaptive dieting behaviors as women become both more desperate to lose weight and more psychologically unfit to make healthy choices," Dr. Gillen added.

"Ultimately, maladaptive dieting behaviors may be associated not only with depression but with eating disorders as well, which suggests the need for health care professionals to reduce women’s unhealthy dieting behaviors before they become more complex long-term mental health problems."

A coinvestigator was supported by an award from Rutgers University. The authors wrote that they had no conflicts of interest to disclose.

Women with depression engage in fewer healthy dieting behaviors such as eating fruits and vegetables, and more unhealthy dieting behaviors such as skipping meals, than do women who are not depressed.

The finding "suggests that a ‘healthy state of mind’ may be a precursor to the adoption of adaptive efforts to lose weight," whereas unhealthy strategies "may represent a form of self-punishment due to disgust with their weight status or themselves in general," according to Meghan M. Gillen, Ph.D., and her colleagues. The report was published in the April issue of Eating Behaviors.

Dr. Gillen, of Pennsylvania State University, Abington, looked at 198 adults in the region of her institution (51% female, mean age 24.8 years) who had volunteered for a larger study about romantic relationships and health. Three-quarters of the participants identified themselves as white (Eat. Behav. 2012;13;88-93).

The average body mass index for women in this sample was 23.93 (range: 17.45-47.71), and the average BMI for men was 27.45 (range: 18.79-49.66).

Overall, 40% of men were overweight, while 25% were obese, in line with national statistics; among women, 22% were overweight, and 8% were obese, a "relatively thin" sample, compared with national figures.

The participants were asked to fill out a questionnaire that dealt with health behaviors and attitudes. The study lasted about 1.5 hours, and each participant received about $25 as payment, except for 14% of the sample who opted to receive credit toward a psychology class instead.

Depression was measured using the Center for Epidemiological Studies Scale for Depression (CES-D), and the 24-item Weight Control Behavior Scale was used to assess weight loss behaviors, with 3 items removed (diet centers with food, weight loss groups, and other) "because it is not clear whether they constitute healthy or unhealthy dieting behaviors."

"In the current study, subscales include healthy dieting behavior (12 items; for example, ‘eat more fruit and vegetables’) and unhealthy dieting behavior (9 items; for example, ‘skip meals’)," Dr. Gillen wrote.

In each case, participants indicated how often they used that strategy to lose weight in the past year, with a score of 0 meaning never, a score of 1 meaning "sometimes," and a score of 2 being "always."

A sum of items on each subscale was used by the investigators to assign an overall "healthy dieting behavior" and "unhealthy dieting behavior" score.

The authors found that even after controlling for BMI and depression, women reported using more healthy as well as unhealthy dieting tactics than men, and both men and women with higher BMIs were more likely to engage in both types of dieting behaviors.

When the authors assessed the effect of depression on the types of dieting behaviors, they determined that, among women, depression was negatively related to healthy dieting behaviors (significance test of the simple slope t(192) = –2.59) and positively related to unhealthy dieting behaviors (t[192] = 3.61), with P less than .01 for both.

Among men, depression had no effect on either healthy (t[192] = 0.63, P = .52) or unhealthy (t[192] = 1.93 P = .06) behaviors.

"These findings suggest that Stice and Bearman’s (2001) model, which predicts an association between weight management strategies and depression in female adolescents (but not their male counterparts), may be extended to adults," the authors wrote.

Moreover, "an extension of the gender additive model may be that depression tends to lead to increasingly maladaptive dieting behaviors as women become both more desperate to lose weight and more psychologically unfit to make healthy choices," Dr. Gillen added.

"Ultimately, maladaptive dieting behaviors may be associated not only with depression but with eating disorders as well, which suggests the need for health care professionals to reduce women’s unhealthy dieting behaviors before they become more complex long-term mental health problems."

A coinvestigator was supported by an award from Rutgers University. The authors wrote that they had no conflicts of interest to disclose.

Women with depression engage in fewer healthy dieting behaviors such as eating fruits and vegetables, and more unhealthy dieting behaviors such as skipping meals, than do women who are not depressed.

The finding "suggests that a ‘healthy state of mind’ may be a precursor to the adoption of adaptive efforts to lose weight," whereas unhealthy strategies "may represent a form of self-punishment due to disgust with their weight status or themselves in general," according to Meghan M. Gillen, Ph.D., and her colleagues. The report was published in the April issue of Eating Behaviors.

Dr. Gillen, of Pennsylvania State University, Abington, looked at 198 adults in the region of her institution (51% female, mean age 24.8 years) who had volunteered for a larger study about romantic relationships and health. Three-quarters of the participants identified themselves as white (Eat. Behav. 2012;13;88-93).

The average body mass index for women in this sample was 23.93 (range: 17.45-47.71), and the average BMI for men was 27.45 (range: 18.79-49.66).

Overall, 40% of men were overweight, while 25% were obese, in line with national statistics; among women, 22% were overweight, and 8% were obese, a "relatively thin" sample, compared with national figures.

The participants were asked to fill out a questionnaire that dealt with health behaviors and attitudes. The study lasted about 1.5 hours, and each participant received about $25 as payment, except for 14% of the sample who opted to receive credit toward a psychology class instead.

Depression was measured using the Center for Epidemiological Studies Scale for Depression (CES-D), and the 24-item Weight Control Behavior Scale was used to assess weight loss behaviors, with 3 items removed (diet centers with food, weight loss groups, and other) "because it is not clear whether they constitute healthy or unhealthy dieting behaviors."

"In the current study, subscales include healthy dieting behavior (12 items; for example, ‘eat more fruit and vegetables’) and unhealthy dieting behavior (9 items; for example, ‘skip meals’)," Dr. Gillen wrote.

In each case, participants indicated how often they used that strategy to lose weight in the past year, with a score of 0 meaning never, a score of 1 meaning "sometimes," and a score of 2 being "always."

A sum of items on each subscale was used by the investigators to assign an overall "healthy dieting behavior" and "unhealthy dieting behavior" score.

The authors found that even after controlling for BMI and depression, women reported using more healthy as well as unhealthy dieting tactics than men, and both men and women with higher BMIs were more likely to engage in both types of dieting behaviors.

When the authors assessed the effect of depression on the types of dieting behaviors, they determined that, among women, depression was negatively related to healthy dieting behaviors (significance test of the simple slope t(192) = –2.59) and positively related to unhealthy dieting behaviors (t[192] = 3.61), with P less than .01 for both.

Among men, depression had no effect on either healthy (t[192] = 0.63, P = .52) or unhealthy (t[192] = 1.93 P = .06) behaviors.

"These findings suggest that Stice and Bearman’s (2001) model, which predicts an association between weight management strategies and depression in female adolescents (but not their male counterparts), may be extended to adults," the authors wrote.

Moreover, "an extension of the gender additive model may be that depression tends to lead to increasingly maladaptive dieting behaviors as women become both more desperate to lose weight and more psychologically unfit to make healthy choices," Dr. Gillen added.

"Ultimately, maladaptive dieting behaviors may be associated not only with depression but with eating disorders as well, which suggests the need for health care professionals to reduce women’s unhealthy dieting behaviors before they become more complex long-term mental health problems."

A coinvestigator was supported by an award from Rutgers University. The authors wrote that they had no conflicts of interest to disclose.

Young adults who drop out of psychosis treatment programs are more likely to have lower baseline negative symptom scores, a shorter duration of untreated psychosis, and a lack of an involved family member.

"With the increased attention to early intervention, understanding predictors of disengagement may have important implications for the development of specialty programs for this young population," wrote Jacqueline Stowkowy in the April issue of Schizophrenia Research.

Indeed, "in the design of services or programs for first-episode psychosis patients, it may be useful from the beginning to determine strategies that may prevent disengagement," for example, family outreach (Schiz. Res. 2012;136:7-12).

Ms. Stowkowy of the University of Calgary (Alta.) and her colleagues studied 266 patients admitted to the 36-month Calgary Early Psychosis Treatment Service, "a well-established comprehensive program for individuals who are experiencing their first episode of psychosis."

According to the authors, the service involves psychiatric and case management, a range of group programs, individual therapy, and family intervention.

The majority of patients were white males, with a mean age of 24.5 years. In addition, most of the participants were single (60%), lived at home (77.1%), and had completed the 12th grade (60%).

"Disengagement" from the program was defined as dropping out after fewer than 30 months, since the final 6 months were given to discharge planning. Individuals were considered to be dropouts when they did not return calls, could not be reached, or would not attend meetings for 3 months.

Overall, Ms. Stowkowy and her colleagues found a dropout rate of 31% for the program, "a number broadly consistent with previous research."

The authors then compared dropouts with patients who stuck with the program until reaching the 3-year anniversary of their admission. They found that the patients who left had lower negative symptom scale scores at baseline, compared with patients who stayed with the program (hazard ratio = 0.946; 95% confidence interval, 0.909-0.985).

Dropouts also had a shorter duration of untreated psychosis, compared with their counterparts (HR = 0.997; 95% CI, 0.994-0.999).

However, the most important overall predictor was not having a family member involved in the program, the researchers found (HR = 0.310; 95% CI, 0.196-0.490). "The two groups did not differ demographically on sex, marital status, living arrangements, or age," wrote the researchers.

Nor did they differ on many other scales, including the presence of positive symptoms, general psychopathology scores, insight, Calgary Depression Scale for Schizophrenia ratings, Global Assessment of Functioning scores, premorbid functioning scale scores, Quality of Life Scale scores, alcohol use, drug use, or cognition.

The researchers then divided the dropouts into four groups: those who dropped out prior to the 6-month assessment, those who remained in treatment for 6-17 months, those who held on for 18-29 months, and those who were still in treatment after 30 months.

In this model, using a one-way analysis of variance, "baseline cannabis and other drug use significantly differentiated those who dropped out of treatment within the first 6 months from both those who remained in treatment or did not leave before 6 months," the authors said.

The authors offered several possible explanations for their findings.

In the case of disengagement associated with fewer negative psychotic symptoms, "young, first-episode individuals whose positive symptoms have resolved and who have lower levels of negative symptoms may think that they are well enough to no longer need treatment," Ms. Stowkowy said.

And in relation to the finding that a shorter duration of untreated psychosis was predictive of dropout, she wrote, "it may be that those who sought treatment earlier were quickest to leave should there be a remission of symptoms."

However, the findings on associated drug use and family involvement offer the most utility in tailoring programs that minimize dropout rates.

"Those who enter with a substance problem need to be considered at entry as potential dropouts, and every effort should be made to engage them in the treatment," the investigators said.

"Another group to identify for specific interventions is those whose families are not engaged in treatment either due to their own or their family’s choice. Efforts to engage the family may serve to maintain the young person longer in the treatment," including active outreach to families who do not attend therapy with the patient.

Two authors disclosed personal funding from noncommercial sources, including the National Institute of Mental Health and the Alberta Heritage Foundation for Medical Research. The study also was supported partly by Eli Lilly.

Young adults who drop out of psychosis treatment programs are more likely to have lower baseline negative symptom scores, a shorter duration of untreated psychosis, and a lack of an involved family member.

"With the increased attention to early intervention, understanding predictors of disengagement may have important implications for the development of specialty programs for this young population," wrote Jacqueline Stowkowy in the April issue of Schizophrenia Research.

Indeed, "in the design of services or programs for first-episode psychosis patients, it may be useful from the beginning to determine strategies that may prevent disengagement," for example, family outreach (Schiz. Res. 2012;136:7-12).

Ms. Stowkowy of the University of Calgary (Alta.) and her colleagues studied 266 patients admitted to the 36-month Calgary Early Psychosis Treatment Service, "a well-established comprehensive program for individuals who are experiencing their first episode of psychosis."

According to the authors, the service involves psychiatric and case management, a range of group programs, individual therapy, and family intervention.

The majority of patients were white males, with a mean age of 24.5 years. In addition, most of the participants were single (60%), lived at home (77.1%), and had completed the 12th grade (60%).

"Disengagement" from the program was defined as dropping out after fewer than 30 months, since the final 6 months were given to discharge planning. Individuals were considered to be dropouts when they did not return calls, could not be reached, or would not attend meetings for 3 months.

Overall, Ms. Stowkowy and her colleagues found a dropout rate of 31% for the program, "a number broadly consistent with previous research."

The authors then compared dropouts with patients who stuck with the program until reaching the 3-year anniversary of their admission. They found that the patients who left had lower negative symptom scale scores at baseline, compared with patients who stayed with the program (hazard ratio = 0.946; 95% confidence interval, 0.909-0.985).

Dropouts also had a shorter duration of untreated psychosis, compared with their counterparts (HR = 0.997; 95% CI, 0.994-0.999).

However, the most important overall predictor was not having a family member involved in the program, the researchers found (HR = 0.310; 95% CI, 0.196-0.490). "The two groups did not differ demographically on sex, marital status, living arrangements, or age," wrote the researchers.

Nor did they differ on many other scales, including the presence of positive symptoms, general psychopathology scores, insight, Calgary Depression Scale for Schizophrenia ratings, Global Assessment of Functioning scores, premorbid functioning scale scores, Quality of Life Scale scores, alcohol use, drug use, or cognition.

The researchers then divided the dropouts into four groups: those who dropped out prior to the 6-month assessment, those who remained in treatment for 6-17 months, those who held on for 18-29 months, and those who were still in treatment after 30 months.

In this model, using a one-way analysis of variance, "baseline cannabis and other drug use significantly differentiated those who dropped out of treatment within the first 6 months from both those who remained in treatment or did not leave before 6 months," the authors said.

The authors offered several possible explanations for their findings.

In the case of disengagement associated with fewer negative psychotic symptoms, "young, first-episode individuals whose positive symptoms have resolved and who have lower levels of negative symptoms may think that they are well enough to no longer need treatment," Ms. Stowkowy said.

And in relation to the finding that a shorter duration of untreated psychosis was predictive of dropout, she wrote, "it may be that those who sought treatment earlier were quickest to leave should there be a remission of symptoms."

However, the findings on associated drug use and family involvement offer the most utility in tailoring programs that minimize dropout rates.

"Those who enter with a substance problem need to be considered at entry as potential dropouts, and every effort should be made to engage them in the treatment," the investigators said.

"Another group to identify for specific interventions is those whose families are not engaged in treatment either due to their own or their family’s choice. Efforts to engage the family may serve to maintain the young person longer in the treatment," including active outreach to families who do not attend therapy with the patient.

Two authors disclosed personal funding from noncommercial sources, including the National Institute of Mental Health and the Alberta Heritage Foundation for Medical Research. The study also was supported partly by Eli Lilly.

Young adults who drop out of psychosis treatment programs are more likely to have lower baseline negative symptom scores, a shorter duration of untreated psychosis, and a lack of an involved family member.

"With the increased attention to early intervention, understanding predictors of disengagement may have important implications for the development of specialty programs for this young population," wrote Jacqueline Stowkowy in the April issue of Schizophrenia Research.

Indeed, "in the design of services or programs for first-episode psychosis patients, it may be useful from the beginning to determine strategies that may prevent disengagement," for example, family outreach (Schiz. Res. 2012;136:7-12).

Ms. Stowkowy of the University of Calgary (Alta.) and her colleagues studied 266 patients admitted to the 36-month Calgary Early Psychosis Treatment Service, "a well-established comprehensive program for individuals who are experiencing their first episode of psychosis."

According to the authors, the service involves psychiatric and case management, a range of group programs, individual therapy, and family intervention.

The majority of patients were white males, with a mean age of 24.5 years. In addition, most of the participants were single (60%), lived at home (77.1%), and had completed the 12th grade (60%).

"Disengagement" from the program was defined as dropping out after fewer than 30 months, since the final 6 months were given to discharge planning. Individuals were considered to be dropouts when they did not return calls, could not be reached, or would not attend meetings for 3 months.

Overall, Ms. Stowkowy and her colleagues found a dropout rate of 31% for the program, "a number broadly consistent with previous research."

The authors then compared dropouts with patients who stuck with the program until reaching the 3-year anniversary of their admission. They found that the patients who left had lower negative symptom scale scores at baseline, compared with patients who stayed with the program (hazard ratio = 0.946; 95% confidence interval, 0.909-0.985).

Dropouts also had a shorter duration of untreated psychosis, compared with their counterparts (HR = 0.997; 95% CI, 0.994-0.999).

However, the most important overall predictor was not having a family member involved in the program, the researchers found (HR = 0.310; 95% CI, 0.196-0.490). "The two groups did not differ demographically on sex, marital status, living arrangements, or age," wrote the researchers.

Nor did they differ on many other scales, including the presence of positive symptoms, general psychopathology scores, insight, Calgary Depression Scale for Schizophrenia ratings, Global Assessment of Functioning scores, premorbid functioning scale scores, Quality of Life Scale scores, alcohol use, drug use, or cognition.

The researchers then divided the dropouts into four groups: those who dropped out prior to the 6-month assessment, those who remained in treatment for 6-17 months, those who held on for 18-29 months, and those who were still in treatment after 30 months.

In this model, using a one-way analysis of variance, "baseline cannabis and other drug use significantly differentiated those who dropped out of treatment within the first 6 months from both those who remained in treatment or did not leave before 6 months," the authors said.

The authors offered several possible explanations for their findings.

In the case of disengagement associated with fewer negative psychotic symptoms, "young, first-episode individuals whose positive symptoms have resolved and who have lower levels of negative symptoms may think that they are well enough to no longer need treatment," Ms. Stowkowy said.

And in relation to the finding that a shorter duration of untreated psychosis was predictive of dropout, she wrote, "it may be that those who sought treatment earlier were quickest to leave should there be a remission of symptoms."

However, the findings on associated drug use and family involvement offer the most utility in tailoring programs that minimize dropout rates.

"Those who enter with a substance problem need to be considered at entry as potential dropouts, and every effort should be made to engage them in the treatment," the investigators said.

"Another group to identify for specific interventions is those whose families are not engaged in treatment either due to their own or their family’s choice. Efforts to engage the family may serve to maintain the young person longer in the treatment," including active outreach to families who do not attend therapy with the patient.

Two authors disclosed personal funding from noncommercial sources, including the National Institute of Mental Health and the Alberta Heritage Foundation for Medical Research. The study also was supported partly by Eli Lilly.