Prospective associations of depression with survival: a population-based cohort study in patients with newly diagnosed breast cancer
Bibliographic record
Abstract
Psychological factors may influence survival in breast cancer patients but results of previous research are inconclusive. This prospective population-based study tested whether depression predicts mortality in breast cancer patients. Routinely collected depression screening data were merged with electronically archived provincial cancer registry data and censored data from British Columbia Vital Statistics (extracted in December 2012). Cox proportional-hazards regression analyses were conducted to predict all-cause and breast cancer-specific mortality as a function of depression after controlling for biomedical confounders. Of 1,646 patients, 1,604 had breast cancer stages I-III and 42 had stage IV breast cancer. 176 (11.0 %) versus 28 (66.7 %) were deceased after a median follow-up of 76 months. In patients with curable breast cancer, depression predicted all-cause (HR = 1.54 (95 % CI 1.06-2.25); p = 0.024), but not breast cancer-specific mortality (HR = 1.51 (95 % CI 0.95-2.41); p = 0.084). No association was shown for metastatic disease. Stage-specific analyses demonstrated a 2-2.5-fold increase in breast cancer-specific and all-cause mortality in patients with stage I and II disease, but not in patients with stage III or IV breast cancer. In stage I breast cancer patients, age moderated effects of depression such that depressed younger patients diagnosed at age 45 (i.e., mean age -1SD) showed a ninefold (HR = 9.82 (95 % CI 2.26-42.68); p = 0.002) increase in all-cause mortality and depressed patients at 57 a 3.7-fold (HR = 3.69 (95 % CI 1.44-9.48); p = 0.007) increase, while no association was evident in older patients at age 69 (mean age +1SD). Depression is strongly associated with mortality in younger patients with early stage breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".