Predicting future risk of depressive episode in adolescents: The Chicago adolescent depression risk assessment (CADRA)
Benjamin W. Van Voorhees, David Paunesku, Jackie Gollan, Sachiko Kuwabara, Mark Reinecke, Anirban Basu
PURPOSE: A risk prediction index, similar to those used for other disorders, such as cardiovascular disease, would facilitate depression prevention by identifying those who would benefit most from preventative measures in primary care settings. METHODS: The National Longitudinal Study of Adolescent Health enrolled a representative sample of US adolescents and included a baseline survey in 1995 and a 1-year follow-up survey in 1996 (n = 4,791). We used baseline risk factors (social and cognitive vulnerability and mood) to predict onset of a depressive episode at 1-year follow-up (eg, future risk of episode) and used boosted classification and regression trees to develop a prediction index, The Chicago Adolescent Depression Risk Assessment, suitable for a personal computer or hand-held device. True and false positives and negatives were determined based on concordance and discordance, respectively, between the prediction-category-based index and actual classification-category- based 1-year follow-up outcome. We evaluated the performance of the index for the entire sample and with several depressive episode outcomes using the standard Center for Epidemiologic Studies Depression (CES-D) scale cutoffs. RESULTS: The optimal prediction model (including depressed mood and social vulnerability) was a 20-item model with an area under the receiver operating characteristics curve of 0.80 (95% CI, 0.714-0.870), a sensitivity of 75%, and a specificity of 76.5%. For depressive episode, the positive predictive values in the highest risk group (level 4) was from 13.75% for a depressive episode to 63.57% for CES-D score of greater than 16 (mild to moderate depressed mood or above) at follow-up. Conversely, the negative predictive value of being in the lowest 2 levels (0 or 1) was 99.38% for a depressive episode and 89.19% for a CES-D score of greater than 16. CONCLUSIONS: Our model predicts a depressive episode and other depressive outcomes at 1-year follow-up. Positive and negative predictive values could enable primary care physicians and families to intervene on adolescents at highest risk.
Annals of family medicine
https://doi.org/10.1370/afm.887
Depressive disorder
10.1370/afm.887
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Risk Assessment Medicine & Life Sciences 100%
Depression Medicine & Life Sciences 78%
Epidemiologic Studies Medicine & Life Sciences 60%
National Longitudinal Study of Adolescent Health Medicine & Life Sciences 37%
Microcomputers Medicine & Life Sciences 28%
Primary Care Physicians Medicine & Life Sciences 25%
ROC Curve Medicine & Life Sciences 20%
Van Voorhees, B. W., Paunesku, D., Gollan, J., Kuwabara, S., Reinecke, M., & Basu, A. (2008). Predicting future risk of depressive episode in adolescents: The Chicago adolescent depression risk assessment (CADRA). Annals of family medicine, 6(6), 503-511. https://doi.org/10.1370/afm.887
Van Voorhees, Benjamin W. ; Paunesku, David ; Gollan, Jackie ; Kuwabara, Sachiko ; Reinecke, Mark ; Basu, Anirban. / Predicting future risk of depressive episode in adolescents : The Chicago adolescent depression risk assessment (CADRA). In: Annals of family medicine. 2008 ; Vol. 6, No. 6. pp. 503-511.
@article{9dc31dde31d2473b96db89f0d0cd071d,
title = "Predicting future risk of depressive episode in adolescents: The Chicago adolescent depression risk assessment (CADRA)",
abstract = "PURPOSE: A risk prediction index, similar to those used for other disorders, such as cardiovascular disease, would facilitate depression prevention by identifying those who would benefit most from preventative measures in primary care settings. METHODS: The National Longitudinal Study of Adolescent Health enrolled a representative sample of US adolescents and included a baseline survey in 1995 and a 1-year follow-up survey in 1996 (n = 4,791). We used baseline risk factors (social and cognitive vulnerability and mood) to predict onset of a depressive episode at 1-year follow-up (eg, future risk of episode) and used boosted classification and regression trees to develop a prediction index, The Chicago Adolescent Depression Risk Assessment, suitable for a personal computer or hand-held device. True and false positives and negatives were determined based on concordance and discordance, respectively, between the prediction-category-based index and actual classification-category- based 1-year follow-up outcome. We evaluated the performance of the index for the entire sample and with several depressive episode outcomes using the standard Center for Epidemiologic Studies Depression (CES-D) scale cutoffs. RESULTS: The optimal prediction model (including depressed mood and social vulnerability) was a 20-item model with an area under the receiver operating characteristics curve of 0.80 (95% CI, 0.714-0.870), a sensitivity of 75%, and a specificity of 76.5%. For depressive episode, the positive predictive values in the highest risk group (level 4) was from 13.75% for a depressive episode to 63.57% for CES-D score of greater than 16 (mild to moderate depressed mood or above) at follow-up. Conversely, the negative predictive value of being in the lowest 2 levels (0 or 1) was 99.38% for a depressive episode and 89.19% for a CES-D score of greater than 16. CONCLUSIONS: Our model predicts a depressive episode and other depressive outcomes at 1-year follow-up. Positive and negative predictive values could enable primary care physicians and families to intervene on adolescents at highest risk.",
keywords = "Behavioral medicine, Depression, Depressive disorder, Primary health care, Risk assessment",
author = "{Van Voorhees}, {Benjamin W.} and David Paunesku and Jackie Gollan and Sachiko Kuwabara and Mark Reinecke and Anirban Basu",
doi = "10.1370/afm.887",
journal = "Annals of Family Medicine",
publisher = "Annals of Family Medicine, Inc",
Van Voorhees, BW, Paunesku, D, Gollan, J, Kuwabara, S, Reinecke, M & Basu, A 2008, 'Predicting future risk of depressive episode in adolescents: The Chicago adolescent depression risk assessment (CADRA)', Annals of family medicine, vol. 6, no. 6, pp. 503-511. https://doi.org/10.1370/afm.887
Predicting future risk of depressive episode in adolescents : The Chicago adolescent depression risk assessment (CADRA). / Van Voorhees, Benjamin W.; Paunesku, David; Gollan, Jackie; Kuwabara, Sachiko; Reinecke, Mark; Basu, Anirban.
In: Annals of family medicine, Vol. 6, No. 6, 2008, p. 503-511.
T1 - Predicting future risk of depressive episode in adolescents
T2 - The Chicago adolescent depression risk assessment (CADRA)
AU - Van Voorhees, Benjamin W.
AU - Paunesku, David
AU - Gollan, Jackie
AU - Kuwabara, Sachiko
AU - Reinecke, Mark
AU - Basu, Anirban
N2 - PURPOSE: A risk prediction index, similar to those used for other disorders, such as cardiovascular disease, would facilitate depression prevention by identifying those who would benefit most from preventative measures in primary care settings. METHODS: The National Longitudinal Study of Adolescent Health enrolled a representative sample of US adolescents and included a baseline survey in 1995 and a 1-year follow-up survey in 1996 (n = 4,791). We used baseline risk factors (social and cognitive vulnerability and mood) to predict onset of a depressive episode at 1-year follow-up (eg, future risk of episode) and used boosted classification and regression trees to develop a prediction index, The Chicago Adolescent Depression Risk Assessment, suitable for a personal computer or hand-held device. True and false positives and negatives were determined based on concordance and discordance, respectively, between the prediction-category-based index and actual classification-category- based 1-year follow-up outcome. We evaluated the performance of the index for the entire sample and with several depressive episode outcomes using the standard Center for Epidemiologic Studies Depression (CES-D) scale cutoffs. RESULTS: The optimal prediction model (including depressed mood and social vulnerability) was a 20-item model with an area under the receiver operating characteristics curve of 0.80 (95% CI, 0.714-0.870), a sensitivity of 75%, and a specificity of 76.5%. For depressive episode, the positive predictive values in the highest risk group (level 4) was from 13.75% for a depressive episode to 63.57% for CES-D score of greater than 16 (mild to moderate depressed mood or above) at follow-up. Conversely, the negative predictive value of being in the lowest 2 levels (0 or 1) was 99.38% for a depressive episode and 89.19% for a CES-D score of greater than 16. CONCLUSIONS: Our model predicts a depressive episode and other depressive outcomes at 1-year follow-up. Positive and negative predictive values could enable primary care physicians and families to intervene on adolescents at highest risk.
AB - PURPOSE: A risk prediction index, similar to those used for other disorders, such as cardiovascular disease, would facilitate depression prevention by identifying those who would benefit most from preventative measures in primary care settings. METHODS: The National Longitudinal Study of Adolescent Health enrolled a representative sample of US adolescents and included a baseline survey in 1995 and a 1-year follow-up survey in 1996 (n = 4,791). We used baseline risk factors (social and cognitive vulnerability and mood) to predict onset of a depressive episode at 1-year follow-up (eg, future risk of episode) and used boosted classification and regression trees to develop a prediction index, The Chicago Adolescent Depression Risk Assessment, suitable for a personal computer or hand-held device. True and false positives and negatives were determined based on concordance and discordance, respectively, between the prediction-category-based index and actual classification-category- based 1-year follow-up outcome. We evaluated the performance of the index for the entire sample and with several depressive episode outcomes using the standard Center for Epidemiologic Studies Depression (CES-D) scale cutoffs. RESULTS: The optimal prediction model (including depressed mood and social vulnerability) was a 20-item model with an area under the receiver operating characteristics curve of 0.80 (95% CI, 0.714-0.870), a sensitivity of 75%, and a specificity of 76.5%. For depressive episode, the positive predictive values in the highest risk group (level 4) was from 13.75% for a depressive episode to 63.57% for CES-D score of greater than 16 (mild to moderate depressed mood or above) at follow-up. Conversely, the negative predictive value of being in the lowest 2 levels (0 or 1) was 99.38% for a depressive episode and 89.19% for a CES-D score of greater than 16. CONCLUSIONS: Our model predicts a depressive episode and other depressive outcomes at 1-year follow-up. Positive and negative predictive values could enable primary care physicians and families to intervene on adolescents at highest risk.
KW - Behavioral medicine
KW - Depression
KW - Depressive disorder
KW - Primary health care
KW - Risk assessment
U2 - 10.1370/afm.887
DO - 10.1370/afm.887
JO - Annals of Family Medicine
JF - Annals of Family Medicine
Van Voorhees BW, Paunesku D, Gollan J, Kuwabara S, Reinecke M, Basu A. Predicting future risk of depressive episode in adolescents: The Chicago adolescent depression risk assessment (CADRA). Annals of family medicine. 2008;6(6):503-511. https://doi.org/10.1370/afm.887