Background Residual symptoms are detrimental to prognosis in major depressive disorder (MDD);
however, little is known about the contribution of each residual symptom in predicting …

… Predicting relapse during maintenance treatment for depression is challenging. The … in this
study since the STAR*D trial did not assess treatment adherence. Finally, the STAR*D trial did …

… compared the STAR*D protocol’s step-by-step predictions of … While the purpose of these
predictions’ was to estimate the … though, STAR*D investigators reported an overall relapse rate …

… failed citalopram treatment were reanalyzed to examine the … It is concluded that initial severity
is a predictor of the time to … with worse outcomes, such as relapse 1 and so represent a key …

… baseline and biweekly ratings 8 to 2 weeks before relapse, using the linear mixed model. …
before relapse may be a useful marker for earlier interventions to possibly avert relapse. …

… further mediumsized trial, we recommend the reanalysis of concatenated raw data from previous
trials … of major depressive disorder with citalopram and risk of relapse: a STAR*D report. …

… In the patients who responded to the index ECT course, we used stepwise logistic regression
to predict relapse versus no relapse, using the scores on the 10 individual MADRS items (…

… Prediction of an individual's imminent depressive relapse could lead to just-in-time interventions
to prevent relapse, … down (CSD), have been proposed as a means of predicting relapse. …

… Concordance statistic was calculated to determine the accuracy of the best fit multivariable
models in predicting relapse. Finally, interaction terms were tested for each significant …

… The STAR*D subanalysis showed that the three most common residual symptoms in the …
to relapse and facilitating an effort to find adequate treatment at the earliest opportunity. …