Assessment of the impact of delays to radiotherapy on prostate cancer mortality in localized prostate cancer.
Bibliographic record
Abstract
5100 Background: Resource constraints and patient preferences may lead to delays in the treatment of localized prostate cancer, but the implications of such delays remain unclear. We aimed to investigate the impact of time from diagnosis to treatment initiation (TTI, including neoadjuvant ADT) on prostate cancer-specific mortality (PCSM) in patients receiving radiotherapy for localized prostate cancer. Methods: Patients diagnosed with localized prostate cancer from 2004 to 2020 who received radiotherapy as part of their first course of treatment were identified from the SEER 17 database. Those who initially underwent active surveillance or surgery, as well as those whose TTI exceeded 24 months, were excluded. The remaining patients were divided into cohorts with prespecified TTI intervals of 0-3 months, 4-6 months, and >6 months. Covariates were age, race, county median income, county remoteness, diagnosis year, T stage, PSA, Gleason grade, and treatment modality (external beam radiotherapy, brachytherapy, or a combination). Missing covariates were imputed 50 times using multiple imputations with chained equations, after which propensity score weighting using Bayesian additive regression trees was performed for each imputed dataset. Pooled marginal Cox models, in accordance with Rubin's rules, were used to compare the PCSM of the three TTI cohorts. Additionally, a prespecified subgroup analysis based on NCCN risk classification was completed. Results: A total of 230,278 patients with a median follow-up of 7.8 years were eligible for analysis, of whom 168,432 (73.1%) had a TTI of 0-3 months, 46,738 (20.3%) had a TTI of 4-6 months, and 15,108 (6.6%) had a TTI of >6 months. After propensity score weighting, the maximal standardized mean difference across all covariates and imputations was less than 0.03. Weighted 10-year PCSMs were 5.9%, 5.6%, and 7.1% for patients with TTIs of 0-3 months, 4-6 months, and >6 months, respectively. The PCSM of patients with a TTI of 4-6 months did not differ from that of patients with a TTI of 0-3 months (HR 0.95, 95% CI 0.89-1.01; P=0.09). However, patients with a TTI of >6 months had a higher risk of PCSM than those with TTIs of 0-3 months (HR 1.22, 95% CI 1.09-1.36; P<0.001) or 4-6 months (HR 1.28, 95% CI 1.13-1.45; P<0.001). There was no significant interaction between TTI and NCCN risk group (P=0.49). Conclusions: A TTI exceeding 6 months was associated with an increased risk of prostate cancer mortality. These findings support the timely initiation of treatment for patients undergoing radiotherapy for localized prostate cancer. PCSM by NCCN risk subgroup. Subgroup 4-6 months vs. 0-3 monthsHR (95% CI) >6 months vs. 0-3 monthsHR (95% CI) >6 months vs. 4-6 monthsHR (95% CI) Overall 0.95 (0.89-1.01) 1.22 (1.09-1.36) 1.28 (1.13-1.45) Low risk 1.02 (0.89-1.17) 1.05 (0.86-1.29) 1.04 (0.83-1.30) Intermediate risk 0.94 (0.86-1.03) 1.19 (1.02-1.38) 1.27 (1.07-1.50) High risk 0.94 (0.85-1.03) 1.28 (1.06-1.54) 1.37 (1.11-1.68)
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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 | 0.003 | 0.008 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".