The importance of the season of biopsy on the Gleason score on biopsy: does exposure to sunshine have an influence?
Bibliographic record
Abstract
The circadian clock is strongly influenced by the sun exposure and prostate cancer has been shown to be inversely proportional to it. We investigated whether PCa aggressiveness in Montreal, Quebec, Canada, differs over the months during or following potentially longer exposure to sunlight. We analyzed 3447 patients treated between January 1995 and December 2023 with primary radiotherapy for localized PCa. We investigated whether the month when diagnostic biopsy was performed was associated with a more frequent diagnosis of a primary Gleason score (pGS) of 4 or 5. We grouped the months of biopsy into the four quarters (Q1-4) of the year. Multivariable logistic regression was used to predict a pGS of 4 or 5, adjusted for age and year of biopsy. There were significantly fewer biopsies ( P = 0.027) with pGS 4 or 5 in the last 3 months of the year (Q4; 19.0%) than those in Q1-3 (22.9%). Age, prostate-specific antigen (PSA) level, and the number of positive biopsies were not significantly different between Q4 versus Q1-3. In multivariate logistic regression analysis, a biopsy in Q4 was significantly predictive of a lower risk of pGS 4 or 5 (odds ratio [OR]: 0.77, 95% confidence interval [CI]: 0.63-0.93, P = 0.007), as was older age (P < 0.001), but not the year of biopsy ( P = 0.76). In conclusion, patients biopsied during Q4 had a 23% lower risk of a pGS 4 or 5 on diagnostic biopsy than those biopsied during the previous 9 months. Our results are not a proof of causality.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".