Systemic Inflammatory Markers Are Predictive of the Response to Brachytherapy in the Prostate
Bibliographic record
Abstract
We analyzed the influence of the neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) on the biochemical recurrence (BCR) in low-intermediate risk prostate cancer (PCa). A total of 604 patients treated with exclusive brachytherapy for low- and intermediate-risk cancers were included in this study. No patient received either androgen deprivation or brachytherapy as a boost. BCR was defined according to the Phoenix definition (nadir prostatic specific antigen (PSA) +2). The median follow-up was 60 months (IQR 44–48 months). An NLR > 3 was more frequent in statin users (p = 0.025), but not in diabetics (p = 0.079). In univariate analysis (UVA) and multivariate analysis (MVA), a NLR > 3 (MVA p = 0.03), as well as Cancer of the Prostate Risk Assessment (CAPRA) low- vs. intermediate-risk (MVA p = 0.04), were predictive of BCR. When combining the NLR score with the CAPRA risk group, CAPRA intermediate risk patients with an NLR ≤ 3 (n = 157) had the worst (p = 0.0276) BCR rates, with a 5-year recurrence-free survival (p = 0.004, Bonferroni correction for six comparisons p = 0.024). We were able to identify a subgroup of PCa patients with CAPRA intermediate-risk and an NLR ≤ 3 who had worse BCR. This is in contrast to most other cancers, which have a worse prognosis when the NLR is high.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".