The Neutrophil-to-Lymphocyte Ratio as a Biomarker in Metastatic Castrate-Sensitive Prostate Cancer Patients Treated with Abiraterone Acetate
Bibliographic record
Abstract
Given its known prognostic role, we aimed to investigate the role of neutrophil–lymphocyte ratio (NLR) as a biomarker in metastatic castration-resistant prostate cancer (mCRPC) patients receiving ADT, either as monotherapy or in conjunction with abiraterone acetate (AA) and prednisone. This retrospective cohort study analyzed the LATITUDE study of men with high-risk mCSPC. Patients were assigned to receive either AA, prednisone, and androgen deprivation therapy (ADT) or placebo plus ADT. Using a previously established NLR threshold of 2.5, we evaluated if this could predict clinical response to abiraterone. At baseline, there were no significant differences in NLR values between the treatment groups. Of the known baseline prognostic factors, NLR was associated with albumin levels and Eastern Cooperative Oncology Group performance scores. Moreover, the number of bone metastases was higher in patients with NLR ≥ 2.5. On multivariable analysis, baseline NLR ≥ 2.5 did not predict overall survival, PSA progression-free, or metastasis-free survival. However, changes in PSA and NLR at six months indicated distinct survival patterns between the placebo and AA groups, suggesting the potential for their combined assessment as a prognostic tool. Baseline NLR was not an independent predictor factor for response to AA in the LATITUDE study, though NLR changes at 6 months may predict better survival beyond PSA values alone. Further research is required to better understand in which patients with advanced prostate cancer NLR changes may be a useful prognostic tool.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".