Impact of androgen deprivation therapy on depressive symptoms in men with nonmetastatic prostate cancer
Bibliographic record
Abstract
BACKGROUND: Up to 50% of prostate cancer (PC) patients receive androgen deprivation therapy (ADT), often for several years. Although depression has been reported after a diagnosis of PC, whether ADT leads to or worsens depression is not clear. METHODS: Three groups were assembled: ADT users (men initiating continuous ADT), PC controls (PC patients who were not on ADT), and healthy controls. All 3 cohorts were matched on age, education, and physical function, and none had metastases. Depression was measured at study entry and again at 3, 6, and 12 months using the 15-item Geriatric Depression Scale (GDS). Our primary outcomes were worsening depressive symptoms and incident depression (defined as a GDS score ≥5), analyzed using adjusted linear regression and logistic regression, respectively. RESULTS: Of the 257 participants (mean age, 69.1 years), baseline characteristics including GDS score and prior depression were similar across cohorts. In adjusted analyses of initially nondepressed patients, ADT use was not a significant predictor of change in GDS score at 3 months (P = .42), 6 months (P = .25), or 12 months (P = 0.19). Among ADT users, 8%-9% of participants developed incident depression compared with 0%-4% among PC controls and 4%-6% among healthy controls over 3-12 months (P>.05 at all time points). In a separate analysis of patients with depression at baseline, there was no effect of ADT on depressive symptoms at 3, 6, or 12 months (P = .11, .74, and .12, respectively). CONCLUSION: Twelve months of ADT use were not associated with worsening depressive symptoms among nondepressed or depressed patients with nonmetastatic PC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".