Prognostic association between common laboratory tests and overall survival in men with <i>de novo</i> metastatic castration-sensitive prostate cancer: A population-based study.
Bibliographic record
Abstract
149 Background: Despite significant advancements in the treatment of metastatic prostate cancer, a validated prognostic tool for patients with de novo metastatic castration-sensitive prostate cancer (mCSPC) is still lacking. Using population-based data from Ontario, Canada, we sought to examine the prognostic association between common laboratory tests and survival for patients with mCSPC. Methods: A population-based cohort of men aged 66 years and older diagnosed with de novo metastatic prostate cancer between 2014-2019 were included. We assessed the association between laboratory tests at the time of cancer diagnosis and overall survival (OS). Utilizing a complete case analysis, we used Cox proportional hazards models to assess the association between these laboratory tests and OS while adjusting for patient and disease characteristics. Results: A total of 3,556 men with de novo mCSPC were included. On multivariable analysis, there were significant associations between OS and neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, albumin, hemoglobin, PSA decrease and PSA nadir <0.1 ng/mL (please see table). Conclusions: Commonly available laboratory tests provide important prognostic information for patients with newly diagnosed mCSPC given demonstrated associations to overall survival. Apart from PSA kinetics, none of these baseline tests were performed in more than 57% of patients indicating underutilization of these low-cost prognostic biomarkers. [Table: see text]
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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) | 0.001 | 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".