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Who will benefit from antidepressants in the acute treatment of bipolar depression? A reanalysis of the STEP-BD study by Sachs et al. 2007, using Q-learning.

Wu F, Laber EB, Lipkovich IA, Severus E - Int J Bipolar Disord (2015)

Bottom Line: There is substantial uncertainty regarding the efficacy of antidepressants in the treatment of bipolar disorders.Using data from the acute depression randomized care (RAD) pathway of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we estimate an optimal dynamic treatment regime via Q-learning.The estimated optimal treatment regime presents some evidence that patients in the RAD pathway of STEP-BD who experienced a (hypo)manic episode before the depressive episode may do better to forgo adding an antidepressant to a mandatory mood stabilizer.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, 27695 USA.

ABSTRACT

Background: There is substantial uncertainty regarding the efficacy of antidepressants in the treatment of bipolar disorders.

Methods: Traditional randomized controlled trials and statistical methods are not designed to discover if, when, and to whom an intervention should be applied; thus, other methodological approaches are needed that allow for the practice of personalized, evidence-based medicine with patients with bipolar depression.

Results: Dynamic treatment regimes operationalize clinical decision-making as a sequence of decision rules, one per stage of clinical intervention, that map patient information to a recommended treatment. Using data from the acute depression randomized care (RAD) pathway of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we estimate an optimal dynamic treatment regime via Q-learning.

Conclusions: The estimated optimal treatment regime presents some evidence that patients in the RAD pathway of STEP-BD who experienced a (hypo)manic episode before the depressive episode may do better to forgo adding an antidepressant to a mandatory mood stabilizer.

No MeSH data available.


Related in: MedlinePlus

Estimated optimal second-stage decision rule. As anticipated by the estimated second-stage Q-function, SUMM1 (scale score for mood elevation) and SIDE3 (sedation side effect) are used to dictate treatment.
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Fig4: Estimated optimal second-stage decision rule. As anticipated by the estimated second-stage Q-function, SUMM1 (scale score for mood elevation) and SIDE3 (sedation side effect) are used to dictate treatment.

Mentions: We use a version of stepwise variable selection to optimize the Bayesian information criteria (BIC); a complete description of this procedure is given in the Appendix section. The variables included in the model for the second-stage Q-function are SIDE3, SUMD1, and SUMM1. The variables included in the model for the first-stage Q-function are AGE, PRONSET, SUMD0, and SUMM0. Thus, the second-stage Q-functions has the form , where and A2 is indicator variable for stage 2 treatment coded so that A2=1 denotes high-dose Bupropion and A2=0 denotes high-dose Paroxetine. The estimated coefficients along with 90% bootstrap confidence intervals are shown in Table 2. The table shows that the main effect of A2 and interaction between second A2 and SUMM1 is significant at the 90% level. The estimated optimal decision rule is shown in Figure 4. As anticipated by estimated second-stage Q-function, SUMM1 (mood severity) and SIDE3 (sedation side effect) dictate treatment selection; subjects with sedation side effects and low mood severity are recommended to Bupropion, and all others are recommended to Paroxetine.Figure 4


Who will benefit from antidepressants in the acute treatment of bipolar depression? A reanalysis of the STEP-BD study by Sachs et al. 2007, using Q-learning.

Wu F, Laber EB, Lipkovich IA, Severus E - Int J Bipolar Disord (2015)

Estimated optimal second-stage decision rule. As anticipated by the estimated second-stage Q-function, SUMM1 (scale score for mood elevation) and SIDE3 (sedation side effect) are used to dictate treatment.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383759&req=5

Fig4: Estimated optimal second-stage decision rule. As anticipated by the estimated second-stage Q-function, SUMM1 (scale score for mood elevation) and SIDE3 (sedation side effect) are used to dictate treatment.
Mentions: We use a version of stepwise variable selection to optimize the Bayesian information criteria (BIC); a complete description of this procedure is given in the Appendix section. The variables included in the model for the second-stage Q-function are SIDE3, SUMD1, and SUMM1. The variables included in the model for the first-stage Q-function are AGE, PRONSET, SUMD0, and SUMM0. Thus, the second-stage Q-functions has the form , where and A2 is indicator variable for stage 2 treatment coded so that A2=1 denotes high-dose Bupropion and A2=0 denotes high-dose Paroxetine. The estimated coefficients along with 90% bootstrap confidence intervals are shown in Table 2. The table shows that the main effect of A2 and interaction between second A2 and SUMM1 is significant at the 90% level. The estimated optimal decision rule is shown in Figure 4. As anticipated by estimated second-stage Q-function, SUMM1 (mood severity) and SIDE3 (sedation side effect) dictate treatment selection; subjects with sedation side effects and low mood severity are recommended to Bupropion, and all others are recommended to Paroxetine.Figure 4

Bottom Line: There is substantial uncertainty regarding the efficacy of antidepressants in the treatment of bipolar disorders.Using data from the acute depression randomized care (RAD) pathway of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we estimate an optimal dynamic treatment regime via Q-learning.The estimated optimal treatment regime presents some evidence that patients in the RAD pathway of STEP-BD who experienced a (hypo)manic episode before the depressive episode may do better to forgo adding an antidepressant to a mandatory mood stabilizer.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, 27695 USA.

ABSTRACT

Background: There is substantial uncertainty regarding the efficacy of antidepressants in the treatment of bipolar disorders.

Methods: Traditional randomized controlled trials and statistical methods are not designed to discover if, when, and to whom an intervention should be applied; thus, other methodological approaches are needed that allow for the practice of personalized, evidence-based medicine with patients with bipolar depression.

Results: Dynamic treatment regimes operationalize clinical decision-making as a sequence of decision rules, one per stage of clinical intervention, that map patient information to a recommended treatment. Using data from the acute depression randomized care (RAD) pathway of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we estimate an optimal dynamic treatment regime via Q-learning.

Conclusions: The estimated optimal treatment regime presents some evidence that patients in the RAD pathway of STEP-BD who experienced a (hypo)manic episode before the depressive episode may do better to forgo adding an antidepressant to a mandatory mood stabilizer.

No MeSH data available.


Related in: MedlinePlus