Time from biopsy to radical prostatectomy by race in an equal‐access healthcare system: Results from the SEARCH cohort
Bibliographic record
Abstract
BACKGROUND: We previously showed that within an equal-access health system, race was not associated with the time between prostate cancer (PC) diagnosis and radical prostatectomy (RP). However, in the more recent time-period of the study (2003-2007), Black men had significantly longer times to RP. We sought to revisit the question in a larger study population with more contemporary patients. We hypothesized that time from diagnosis to treatment would not differ by race, even after accounting for active surveillance (AS) and the exclusion of men at very low to low risk of PC progression. METHODS: We analyzed data from 5885 men undergoing RP from 1988 to 2017 at eight Veterans Affairs Hospitals from SEARCH. Multiple linear regression was used to compare time from biopsy to RP and to examine the risk of delays (>90 and >180 days) between races. In sensitivity analyses we excluded men deemed to have initially chosen AS based on having >365 days from biopsy to RP and men at very low to low PC risk for progression according to National Comprehensive Cancer Network Clinical Practice Guidelines. RESULTS: At biopsy, Black men (n = 1959) were younger, had lower body mass index, and higher prostate specific antigen levels, (all p < 0.02), compared to White men (n = 3926). Time from biopsy to RP was longer in Black men (mean days: 98 vs. 92; adjusted ratio of mean number of days, 1.07 [95% confidence interval: 1.03-1.11], p < 0.001); however, there were no differences in delays >90 or >180 days after adjusting for confounders (all p ≥ 0.286). Results were similar following the exclusion of men potentially under on AS and at very low and low risk. CONCLUSIONS: In an equal-access healthcare system, we did not find evidence of clinically relevant differences in time from biopsy to RP in Black versus White men.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".