Management of Depression in Patients With Cancer: A Clinical Practice Guideline
Bibliographic record
Abstract
PURPOSE: This report updates the Cancer Care Ontario Program in Evidence-Based Care guideline for the management of depression in adult patients with cancer. This guideline covers pharmacologic, psychological, and collaborative care interventions, with a focus on integrating practical management tools to assist clinicians in delivering appropriate treatments for depression in patients with cancer. METHODS: Recommendations were developed by synthesizing information from extant guidelines and reviews and searching for randomized controlled trials from the date of database inception (1964 for MEDLINE and 1974 for EMBASE) to January 2015. Quality assessment of guidelines and systematic reviews were conducted by using the Appraisal of Guidelines for Research and Evaluation II (AGREE II), Assessment of Multiple Systematic Reviews (AMSTAR), and Cochrane Risk of Bias tools. Final recommendations were developed through a standardized Program in Evidence-Based Care multidisciplinary expert and knowledge user review process. RESULTS: Two high-quality relevant clinical practice guidelines, eight pharmacologic trials, nine psychological trials, and eight collaborative care intervention trials composed the evidence base upon which the recommendations were developed. Eight specific recommendations were made to establish a standard of care for the management of depression in patients with cancer. The recommendations and practical management tools were reviewed as being well organized and helpful, although systemic barriers to implementation were identified. CONCLUSION: This updated guideline supports the previous general recommendation that patients with cancer who have depression may benefit from psychological and/or pharmacologic interventions, without evidence for the superiority of any specific treatment over another. New recommendations for a collaborative care model that incorporates a stepped care approach suggest that multidisciplinary mental health care restructuring may be required for optimal management of depression.
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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 | 0.019 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".