Characterizing the outcomes of metastatic papillary renal cell carcinoma
Bibliographic record
Abstract
Outcomes of metastatic papillary renal cell carcinoma (pRCC) patients are poorly characterized in the era of targeted therapy. A total of 5474 patients with metastatic renal cell carcinoma (mRCC) in the International mRCC Database Consortium (IMDC) were retrospectively analyzed. Outcomes were compared between clear cell (ccRCC; n = 5008) and papillary patients (n = 466), and recorded type I and type II papillary patients (n = 30 and n = 165, respectively). Overall survival (OS), progression-free survival (PFS), and overall response rate (ORR) favored ccRCC over pRCC. OS was 8 months longer in ccRCC patients and the hazard ratio of death was 0.71 for ccRCC patients. No differences in PFS or ORR were detected between type I and II PRCC in this limited dataset. The median OS for type I pRCC was 20.0 months while the median OS for type II was 12.6 months (P = 0.096). The IMDC prognostic model was able to stratify pRCC patients into favorable risk (OS = 34.1 months), intermediate risk (OS = 17.0 months), and poor-risk groups (OS = 6.0 months). pRCC patient outcomes were inferior to ccRCC, even after controlling for IMDC prognostic factors. The IMDC prognostic model was able to effectively stratify pRCC patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".