Predicting recurrence of depression using lifelog data: an explanatory feasibility study with a panel VAR approach.

BACKGROUND: Although depression has a high rate of recurrence, no prior studies have established a method that could identify the warning signs of its recurrence. METHODS: We collected digital data consisting of individual activity records such as location or mobility information (lifelog data) from 89 patients who were on maintenance therapy for depression for a year, using a smartphone application and a wearable device. We assessed depression and its recurrence using both the Kessler Psychological Distress Scale (K6) and the Patient Health Questionnaire-9. RESULTS: A panel vector autoregressive analysis indicated that long sleep time was a important risk factor for the recurrence of depression. Long sleep predicted the recurrence of depression after 3 weeks. CONCLUSIONS: The panel vector autoregressive approach can identify the warning signs of depression recurrence; however, the convenient sampling of the present cohort may limit the scope towards drawing a generalised conclusion.

Predicting relapse in major depression after successful initial pharmacological treatment.

BACKGROUND: Identifying the predictors of relapse could help to develop more individualized treatment strategies for major depression. The study aim was to explore predictors of depression relapse after remission using data from our previous multicenter randomized practical trial of patients with major depression. METHODS: Our cohort comprised subjects with Patient Health Questionnaire (PHQ-9) scores less than 5 after antidepressant treatment for 9 weeks. Relapse was defined as a PHQ-9 score of 5 or more at week 25. We examined patient demographic and clinical characteristics at baseline (age, sex education, job status, marital status, onset age at first depressive episode, number of previous episodes, length of current episode, scores on the nine PHQ-9 criteria at week 0) and Frequency, Intensity, and Burden of Side Effects Rating Scale and PHQ-9 total scores at week 9 (residual symptoms) as potential predictors of depression relapse at week 25. RESULTS: Of 494 patients remitted at week 9, 71 (14.4%) experienced relapse at week 25. Logistic regression analysis showed that lower PHQ-9 depressive mood score at week 0, higher suicidal ideation score at week 0, and total PHQ-9 score at week 9, and greater severity of side effects at week 9 were significant predictors. On the other hand, when relapse was defined as a PHQ-9 score of 10 or more at week 25, there were no significant predictors. LIMITATIONS: There may be other important predictors that this study failed to identify and the findings obtained may be sensitive to the specific definition of relapse. CONCLUSIONS: Approximately one-seventh of subjects who remitted after 2 months of acute-phase treatment experienced depression relapse within 4 months of remission. Lower depressive mood and higher suicidal ideation upon development of the current depression episode, the presence of residual symptoms, and greater severity of side effects at remission may predict subsequent depression relapse.

Optimising first- and second-line treatment strategies for untreated major depressive disorder - the SUN☺D study: a pragmatic, multi-centre, assessor-blinded randomised controlled trial.

BACKGROUND: For patients starting treatment for depression, current guidelines recommend titrating the antidepressant dosage to the maximum of the licenced range if tolerated. When patients do not achieve remission within several weeks, recommendations include adding or switching to another antidepressant. However, the relative merits of these guideline strategies remain unestablished. METHODS: This multi-centre, open-label, assessor-blinded, pragmatic trial involved two steps. Step 1 used open-cluster randomisation, allocating clinics into those titrating sertraline up to 50 mg/day or 100 mg/day by week 3. Step 2 used central randomisation to allocate patients who did not remit after 3 weeks of treatment to continue sertraline, to add mirtazapine or to switch to mirtazapine. The primary outcome was depression severity measured with the Patient Health Questionnaire-9 (PHQ-9) (scores between 0 and 27; higher scores, greater depression) at week 9. We applied mixed-model repeated-measures analysis adjusted for key baseline covariates. RESULTS: Between December 2010 and March 2015, we recruited 2011 participants with hitherto untreated major depression at 48 clinics in Japan. In step 1, 970 participants were allocated to the 50 mg/day and 1041 to the 100 mg/day arms; 1927 (95.8%) provided primary outcomes. There was no statistically significant difference in the adjusted PHQ-9 score at week 9 between the 50 mg/day arm and the 100 mg/day arm (0.25 point, 95% confidence interval (CI), - 0.58 to 1.07, P = 0.55). Other outcomes proved similar in the two groups. In step 2, 1646 participants not remitted by week 3 were randomised to continue sertraline (n = 551), to add mirtazapine (n = 537) or to switch to mirtazapine (n = 558): 1613 (98.0%) provided primary outcomes. At week 9, adding mirtazapine achieved a reduction in PHQ-9 scores of 0.99 point (0.43 to 1.55, P = 0.0012); switching achieved a reduction of 1.01 points (0.46 to 1.56, P = 0.0012), both relative to continuing sertraline. Combination increased the percentage of remission by 12.4% (6.1 to 19.0%) and switching by 8.4% (2.5 to 14.8%). There were no differences in adverse effects. CONCLUSIONS: In patients with new onset depression, we found no advantage of titrating sertraline to 100 mg vs 50 mg. Patients unremitted by week 3 gained a small benefit in reduction of depressive symptoms at week 9 by switching sertraline to mirtazapine or by adding mirtazapine. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01109693 . Registered on 23 April 2010.