Androgen Deprivation Therapy and the Risk of Dementia in Patients With Prostate Cancer
Bibliographic record
Abstract
Purpose Recent observational studies have associated the use of androgen deprivation therapy (ADT) with an increased risk of dementia and Alzheimer's disease, but these studies had limitations. The objective of this study was to determine whether the use of ADT is associated with an increased risk of dementia, including Alzheimer's disease, in patients with prostate cancer. Patients and Methods Using the United Kingdom's Clinical Practice Research Datalink, we assembled a cohort of 30,903 men newly diagnosed with nonmetastatic prostate cancer between April 1, 1988 and April 30, 2015, and observed them until April 30, 2016. Time-dependent Cox proportional hazards models were used to estimate adjusted hazard ratios with 95% CIs of dementia associated with the use of ADT compared with nonuse. ADT exposure was lagged by 1 year to account for delays associated with the diagnosis of dementia and to minimize reverse causality. Secondary analyses assessed whether the risk varied with cumulative duration of use and by ADT type. Results During a mean (standard deviation) follow-up of 4.3 (3.6) years, 799 patients were newly diagnosed with dementia (incidence, 6.0; 95% CI, 5.6 to 6.4) per 1,000 person-years. Compared with nonuse, ADT use was not associated with an increased risk of dementia (incidence, 7.4 v 4.4 per 1,000 person-years, respectively; adjusted hazard ratio, 1.02; 95% CI, 0.87 to 1.19). In secondary analyses, cumulative duration of use ( P for heterogeneity = .78) and no single type of ADT were associated with an increased risk of dementia. Conclusion In this population-based study, the use of ADT was not associated with an increased risk of dementia. Additional studies in different settings are needed to confirm these findings.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".