Association of chronic baseline prostate inflammation with lower tumor grade in men with prostate cancer on repeat biopsy.
Bibliographic record
Abstract
75 Background: We have previously shown that chronic baseline prostate inflammation in an otherwise benign biopsy was associated with lower risk of prostate cancer in repeat prostate biopsies and lower tumor volumes for those who are diagnosed with cancer. In the present study, we evaluated whether baseline acute or chronic prostate inflammation among men with initial negative biopsies for prostate cancer was associated with cancer grade at the 2-year repeat prostate biopsy. Methods: Retrospective analysis of 889 men 50-75 years-old with negative baseline prostate biopsy and positive 2-year repeat biopsy for prostate cancer in the REDUCE study. Acute and chronic prostate inflammation (coded as present or absent) and cancer grade were determined by central pathology. The association of inflammation in baseline biopsies with 2-year repeat biopsy cancer grade (low-grade: Gleason scores 2-6 vs. high-grade: Gleason scores 7-10) was evaluated with t test, chi-squared test and logistic regression controlling for age, race, body-mass index (BMI), digital rectal exam (DRE), prostate volume, baseline pre-study PSA and treatment (dutasteride or placebo). Results: Chronic, acute inflammation and both were detected in 533 (60%), 12 (1%) and 85 (10%) baseline biopsies, respectively. Presence of acute and chronic inflammations were significantly associated with each other (P < 0.001). Patients with chronic inflammation had significantly larger prostates (P < 0.001). Both types of inflammation were unrelated to race, BMI, PSA or DRE. At 2-year biopsy, a total of 621 (70%) tumors were low-grade and 268 (30%) tumors were high-grade. In both uni- and multivariable analyses, men with baseline chronic inflammation had significantly less high-grade tumors (univariable OR = 0.64, 95% CI = 0.47-0.87, P = 0.004; multivariable OR = 0.68, 95% CI = 0.50-0.93, P = 0.016) than those without baseline chronic inflammation. Baseline acute inflammation was not associated with tumor grade. Conclusions: Among men undergoing repeat prostate biopsy 2 years after a negative baseline biopsy who all had cancer on the follow-up biopsy, the presence baseline chronic inflammation was associated with lower prostate cancer grade.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".