Abstract
BACKGROUND: Major depressive disorder (MDD) has a highly recurrent nature. After successful treatment, it is important to identify individuals who are at risk of an unfavorable long-term course. Despite extensive research, there is no consensus yet on the clinically relevant predictors of long-term outcome in MDD, and no prediction models are implemented in clinical practice. The aim of this study was to create a prognostic index (PI) to estimate long-term depression severity after successful and high quality acute treatment for MDD.
METHODS: Data come from responders to cognitive therapy (CT) and interpersonal psychotherapy (IPT) in a randomized clinical trial (n = 85; CT = 45, IPT = 40). Primary outcome was depression severity, assessed with the Beck Depression Inventory II, measured throughout a 17-month follow-up phase. We examined 29 variables as potential predictors, using a model-based recursive partitioning method and bootstrap resampling in conjunction with backwards elimination. The selected predictors were combined into a PI. Individual PI scores were estimated using a cross-validation approach.
RESULTS: A total of three post-treatment predictors were identified: depression severity, hopelessness, and self-esteem. Cross-validated PI scores evidenced a strong correlation (r = 0.60) with follow-up depression severity.
CONCLUSION: Long-term predictions of MDD are multifactorial, involving a combination of variables that each has a small prognostic effect. If replicated and validated, the PI can be implemented to predict follow-up depression severity for each individual after acute treatment response, and to personalize long-term treatment strategies.
| Original language | English |
|---|---|
| Pages (from-to) | 252-261 |
| Number of pages | 10 |
| Journal | Depression and Anxiety |
| Volume | 36 |
| Issue number | 3 |
| Early online date | 5 Dec 2018 |
| DOIs | |
| Publication status | Published - Mar 2019 |
Keywords
- Clinical trials
- cognitive therapy
- depresseion
- empirical supported treatments
- interpersonal psychotherapy
Cite this
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A prognostic index for long-term outcome after successful acute phase cognitive therapy and interpersonal psychotherapy for major depressive disorder. / van Bronswijk, Suzanne C; Lemmens, Lotte H J M; Keefe, John R; Huibers, Marcus J H; DeRubeis, Robert J; Peeters, Frenk P M L.
In: Depression and Anxiety, Vol. 36, No. 3, 03.2019, p. 252-261.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A prognostic index for long-term outcome after successful acute phase cognitive therapy and interpersonal psychotherapy for major depressive disorder
AU - van Bronswijk, Suzanne C
AU - Lemmens, Lotte H J M
AU - Keefe, John R
AU - Huibers, Marcus J H
AU - DeRubeis, Robert J
AU - Peeters, Frenk P M L
N1 - © 2018 The Authors. Depression and Anxiety published by Wiley Periodicals, Inc.
PY - 2019/3
Y1 - 2019/3
N2 - BACKGROUND: Major depressive disorder (MDD) has a highly recurrent nature. After successful treatment, it is important to identify individuals who are at risk of an unfavorable long-term course. Despite extensive research, there is no consensus yet on the clinically relevant predictors of long-term outcome in MDD, and no prediction models are implemented in clinical practice. The aim of this study was to create a prognostic index (PI) to estimate long-term depression severity after successful and high quality acute treatment for MDD.METHODS: Data come from responders to cognitive therapy (CT) and interpersonal psychotherapy (IPT) in a randomized clinical trial (n = 85; CT = 45, IPT = 40). Primary outcome was depression severity, assessed with the Beck Depression Inventory II, measured throughout a 17-month follow-up phase. We examined 29 variables as potential predictors, using a model-based recursive partitioning method and bootstrap resampling in conjunction with backwards elimination. The selected predictors were combined into a PI. Individual PI scores were estimated using a cross-validation approach.RESULTS: A total of three post-treatment predictors were identified: depression severity, hopelessness, and self-esteem. Cross-validated PI scores evidenced a strong correlation (r = 0.60) with follow-up depression severity.CONCLUSION: Long-term predictions of MDD are multifactorial, involving a combination of variables that each has a small prognostic effect. If replicated and validated, the PI can be implemented to predict follow-up depression severity for each individual after acute treatment response, and to personalize long-term treatment strategies.
AB - BACKGROUND: Major depressive disorder (MDD) has a highly recurrent nature. After successful treatment, it is important to identify individuals who are at risk of an unfavorable long-term course. Despite extensive research, there is no consensus yet on the clinically relevant predictors of long-term outcome in MDD, and no prediction models are implemented in clinical practice. The aim of this study was to create a prognostic index (PI) to estimate long-term depression severity after successful and high quality acute treatment for MDD.METHODS: Data come from responders to cognitive therapy (CT) and interpersonal psychotherapy (IPT) in a randomized clinical trial (n = 85; CT = 45, IPT = 40). Primary outcome was depression severity, assessed with the Beck Depression Inventory II, measured throughout a 17-month follow-up phase. We examined 29 variables as potential predictors, using a model-based recursive partitioning method and bootstrap resampling in conjunction with backwards elimination. The selected predictors were combined into a PI. Individual PI scores were estimated using a cross-validation approach.RESULTS: A total of three post-treatment predictors were identified: depression severity, hopelessness, and self-esteem. Cross-validated PI scores evidenced a strong correlation (r = 0.60) with follow-up depression severity.CONCLUSION: Long-term predictions of MDD are multifactorial, involving a combination of variables that each has a small prognostic effect. If replicated and validated, the PI can be implemented to predict follow-up depression severity for each individual after acute treatment response, and to personalize long-term treatment strategies.
KW - Clinical trials
KW - cognitive therapy
KW - depresseion
KW - empirical supported treatments
KW - interpersonal psychotherapy
U2 - 10.1002/da.22868
DO - 10.1002/da.22868
M3 - Article
C2 - 30516871
VL - 36
SP - 252
EP - 261
JO - Depression and Anxiety
JF - Depression and Anxiety
SN - 1091-4269
IS - 3
ER -