Association of patient and physician characteristics with androgen‐deprivation‐therapy intensification in patients with de novo hormone‐sensitive metastatic prostate cancer: A population‐based study
Bibliographic record
Abstract
INTRODUCTION: Treatment intensification with androgen receptor signaling inhibitors and/or chemotherapy is guideline recommended for patients with de novo metastatic hormone-sensitive prostate cancer (mHSPC). However, most patients only receive androgen deprivation therapy monotherapy. The aim was to identify physician-, patient-, and tumor-related factors associated with the receipt of treatment intensification. METHODS: A population-based cohort study was conducted in Ontario, Canada, which included men ≥66 years newly diagnosed with de novo mHSPC between January 2014 and December 2022. Hierarchical regression modeling was used to examine the association of physician, patient, and tumor characteristics with the receipt of treatment intensification, defined as the initiation of an androgen receptor signaling inhibitor, docetaxel, or both within six months of diagnosis. Darlington's method was used to assess predictor importance via standardized regression coefficients (SRC). RESULTS: Among 6099 eligible older men newly diagnosed with de novo mHSPC, 1475 (24.2%) received treatment intensification. In multivariable modeling, patients initiated on androgen deprivation therapy by radiation oncologists were less likely to receive treatment intensification (odds ratio [OR]. 0.48; 95% CI, 0.37-0.61; p < .01; SRC: 19.46; p < .01) whereas those by medical oncologists were more likely to receive treatment intensification (OR, 1.64; 95% CI, 1.21-2.22; p < .01; SRC: 9.56; p < .01), each compared to urologists. Older patients were significantly less likely to receive treatment intensification (OR 0.94 per year over age 66; 95% CI, 0.93-0.95; p < .01; SRC: -36.21; p < .01). CONCLUSION: Patient and physician characteristics significantly influence variation in the use of treatment intensification for de novo mHSPC. These findings inform targeted interventions and policies to enhance the delivery of life-prolonging mHSPC care.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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".