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Toward an online cognitive and emotional battery to predict treatment remission in depression
PURPOSE: To evaluate the performance of a cognitive and emotional test battery in a representative sample of depressed outpatients to inform likelihood of remission over 8 weeks of treatment with each of three common antidepressant medications. PATIENTS AND METHODS: Outpatients 18–65 years old with...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4348126/ https://www.ncbi.nlm.nih.gov/pubmed/25750532 http://dx.doi.org/10.2147/NDT.S75975 |
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author | Gordon, Evian Rush, A John Palmer, Donna M Braund, Taylor A Rekshan, William |
author_facet | Gordon, Evian Rush, A John Palmer, Donna M Braund, Taylor A Rekshan, William |
author_sort | Gordon, Evian |
collection | PubMed |
description | PURPOSE: To evaluate the performance of a cognitive and emotional test battery in a representative sample of depressed outpatients to inform likelihood of remission over 8 weeks of treatment with each of three common antidepressant medications. PATIENTS AND METHODS: Outpatients 18–65 years old with nonpsychotic major depressive disorder (17 sites) were randomized to escitalopram, sertraline or venlafaxine-XR (extended release). Participants scored ≥12 on the baseline 16-item Quick Inventory of Depressive Symptomatology – Self-Report and completed 8 weeks of treatment. The baseline test battery measured cognitive and emotional status. Exploratory multivariate logistic regression models predicting remission (16-item Quick Inventory of Depressive Symptomatology – Self-Report score ≤5 at 8 weeks) were developed independently for each medication in subgroups stratified by age, sex, or cognitive and emotional test performance. The model with the highest cross-validated accuracy determined the participant proportion in each arm for whom remission could be predicted with an accuracy ≥10% above chance. The proportion for whom a prediction could be made with very high certainty (positive predictive value and negative predictive value exceeding 80%) was calculated by incrementally increasing test battery thresholds to predict remission/non-remission. RESULTS: The test battery, individually developed for each medication, improved identification of remitting and non-remitting participants by ≥10% beyond chance for 243 of 467 participants. The overall remission rates were escitalopram: 40.8%, sertraline: 30.3%, and venlafaxine-XR: 31.1%. Within this subset for whom prediction exceeded chance, test battery thresholds established a negative predictive value of ≥80%, which identified 40.9% of participants not remitting on escitalopram, 77.1% of participants not remitting on sertraline, and 38.7% of participants not remitting on venlafaxine-XR (all including 20% false negatives). CONCLUSION: The test battery identified about 50% of each medication group as being ≥10% more or less likely to remit than by chance, and identified about 38% of individuals who did not remit with ≥80% certainty. Clinicians might choose to avoid this specific medication in these particular patients. |
format | Online Article Text |
id | pubmed-4348126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-43481262015-03-06 Toward an online cognitive and emotional battery to predict treatment remission in depression Gordon, Evian Rush, A John Palmer, Donna M Braund, Taylor A Rekshan, William Neuropsychiatr Dis Treat Original Research PURPOSE: To evaluate the performance of a cognitive and emotional test battery in a representative sample of depressed outpatients to inform likelihood of remission over 8 weeks of treatment with each of three common antidepressant medications. PATIENTS AND METHODS: Outpatients 18–65 years old with nonpsychotic major depressive disorder (17 sites) were randomized to escitalopram, sertraline or venlafaxine-XR (extended release). Participants scored ≥12 on the baseline 16-item Quick Inventory of Depressive Symptomatology – Self-Report and completed 8 weeks of treatment. The baseline test battery measured cognitive and emotional status. Exploratory multivariate logistic regression models predicting remission (16-item Quick Inventory of Depressive Symptomatology – Self-Report score ≤5 at 8 weeks) were developed independently for each medication in subgroups stratified by age, sex, or cognitive and emotional test performance. The model with the highest cross-validated accuracy determined the participant proportion in each arm for whom remission could be predicted with an accuracy ≥10% above chance. The proportion for whom a prediction could be made with very high certainty (positive predictive value and negative predictive value exceeding 80%) was calculated by incrementally increasing test battery thresholds to predict remission/non-remission. RESULTS: The test battery, individually developed for each medication, improved identification of remitting and non-remitting participants by ≥10% beyond chance for 243 of 467 participants. The overall remission rates were escitalopram: 40.8%, sertraline: 30.3%, and venlafaxine-XR: 31.1%. Within this subset for whom prediction exceeded chance, test battery thresholds established a negative predictive value of ≥80%, which identified 40.9% of participants not remitting on escitalopram, 77.1% of participants not remitting on sertraline, and 38.7% of participants not remitting on venlafaxine-XR (all including 20% false negatives). CONCLUSION: The test battery identified about 50% of each medication group as being ≥10% more or less likely to remit than by chance, and identified about 38% of individuals who did not remit with ≥80% certainty. Clinicians might choose to avoid this specific medication in these particular patients. Dove Medical Press 2015-02-26 /pmc/articles/PMC4348126/ /pubmed/25750532 http://dx.doi.org/10.2147/NDT.S75975 Text en © 2015 Gordon et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Gordon, Evian Rush, A John Palmer, Donna M Braund, Taylor A Rekshan, William Toward an online cognitive and emotional battery to predict treatment remission in depression |
title | Toward an online cognitive and emotional battery to predict treatment remission in depression |
title_full | Toward an online cognitive and emotional battery to predict treatment remission in depression |
title_fullStr | Toward an online cognitive and emotional battery to predict treatment remission in depression |
title_full_unstemmed | Toward an online cognitive and emotional battery to predict treatment remission in depression |
title_short | Toward an online cognitive and emotional battery to predict treatment remission in depression |
title_sort | toward an online cognitive and emotional battery to predict treatment remission in depression |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4348126/ https://www.ncbi.nlm.nih.gov/pubmed/25750532 http://dx.doi.org/10.2147/NDT.S75975 |
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