Prognostic significance of absolute lymphocyte count in patients with metastatic renal cell carcinoma receiving first-line combination immunotherapies: results from the International Metastatic Renal Cell Carcinoma Database Consortium
Bibliographic record
Abstract
BACKGROUND: Lymphocytes are closely linked to mechanisms of action of immuno-oncology (IO) agents. We aimed to assess the prognostic significance of absolute lymphocyte count (ALC) in patients with metastatic renal cell carcinoma (mRCC). PATIENTS AND METHODS: Using the International mRCC Database Consortium (IMDC), patients receiving first-line IO-based combination therapy were analysed. Baseline patient characteristics, objective response rates (ORRs), time to next treatment (TTNT), and overall survival (OS) were compared. RESULTS: Of 966 patients included, 195 (20%) had lymphopenia at baseline, and they had a lower ORR (37% versus 45%; P < 0.001), shorter TTNT (10.1 months versus 24.3 months; P < 0.001), and shorter OS (30.4 months versus 48.2 months; P < 0.001). Among 125 patients with lymphopenia at baseline, 52 (42%) experienced ALC recovery at 3 months, and they had longer OS (not reached versus 30.4 months; P = 0.012). On multivariable analysis for OS, lymphopenia was an independent adverse prognostic factor (hazard ratio 1.68; P < 0.001). Incorporation of lymphopenia into the IMDC criteria improved OS prediction accuracy (C-index from 0.688 to 0.707). CONCLUSIONS: Lymphopenia was observed in one-fifth of treatment-naive patients with mRCC and may serve as an indicator of unfavourable oncologic outcomes in the contemporary IO era.
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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 | 0.004 |
| 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 | 0.001 | 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".