Systematic review and meta-analysis of collaborative care interventions for depression in patients with cancer
Bibliographic record
Abstract
BACKGROUND: Previous systematic reviews have found limited evidence for the effectiveness of pharmacological and psychological interventions for the management of depression in patients with cancer. This paper provides the first meta-analysis of newer collaborative care interventions, which may include both types of treatment, as well as integrated delivery and follow-up. Meta-analyses of pharmacological and psychological interventions are included as a comparison. METHODS: A search of MEDLINE, EMBASE, PsycINFO, and the Cochrane Library from July 2005 to January 2015 for randomized controlled trials of depression treatments for cancer patients diagnosed with a major depressive disorder, or who met a threshold on a validated depression rating scale was conducted. Meta-analyses were conducted using summary data. RESULTS: Key findings included eight reports of four collaborative care interventions, eight pharmacological, and nine psychological trials. A meta-analysis demonstrated that collaborative care interventions were significantly more effective than usual care (standardized mean difference = -0.49, p = 0.003), and depression reduction was maintained at 12 months. By comparison, short-term (up to 12 weeks), but not longer-term effectiveness was demonstrated for both pharmacological and psychological interventions. CONCLUSIONS: Collaborative care interventions have newly emerged as multidisciplinary care delivery models, which may result in more long-term depression remission. This review also updates previous findings of modest evidence for the effectiveness of both pharmacological and psychological interventions for threshold depression in cancer patients. Research designs focusing on combined treatments and delivery systems may best further the limited evidence-base for the management of depression in cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.087 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.040 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".