Decrease in Depression Symptoms Is Associated With Longer Survival in Patients With Metastatic Breast Cancer: A Secondary Analysis
Bibliographic record
Abstract
PURPOSE: Numerous studies have examined the comorbidity of depression with cancer, and some have indicated that depression may be associated with cancer progression or survival. However, few studies have assessed whether changes in depression symptoms are associated with survival. METHODS: In a secondary analysis of a randomized trial of supportive-expressive group therapy, 125 women with metastatic breast cancer (MBC) completed a depression symptom measure (Center for Epidemiologic Studies-Depression Scale [CES-D]) at baseline and were randomly assigned to a treatment group or to a control group that received educational materials. At baseline and three follow-up points, 101 of 125 women completed a depression symptom measure. We used these data in a Cox proportional hazards analysis to examine whether decreasing depression symptoms over the first year of the study (the length of the intervention) would be associated with longer survival. RESULTS: Median survival time was 53.6 months for women with decreasing CES-D scores over 1 year and 25.1 months for women with increasing CES-D scores. There was a significant effect of change in CES-D over the first year on survival out to 14 years (P = .007) but no significant interaction between treatment condition and CES-D change on survival. Neither demographic nor medical variables explained this association. CONCLUSION: Decreasing depression symptoms over the first year were associated with longer subsequent survival for women with MBC in this sample. Further research is necessary to confirm this hypothesis in other samples, and causation cannot be assumed based on this analysis.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".