First-, second-, third-line therapy for metastatic renal cell carcinoma (mRCC): Benchmarks for trials design from the International mRCC Database Consortium (IMDC).
Bibliographic record
Abstract
4586 Background: Limited data exists on outcomes for mRCC patients treated with multiple lines of therapy. Benchmarks for survival are required for patient counseling and clinical trial design. Methods: Outcomes of mRCC patients from the IMDC treated with 1, 2, or 3+ lines of targeted therapy (TT) were compared and adjusted by proportional hazards regression. Overall survival (OS) and progression-free survival (PFS) benchmarks were calculated using different population inclusion criteria. OS and PFS are calculated from the line of therapy under consideration unless otherwise specified. Results: 2,705 patients were treated with TT of which 1,533 (57%) received only 1st-line TT, 734 (27%) received 2 lines of TT, and 438 (16%) received 3+ lines of TT. The median OS of patients that received 1, 2 or 3+ lines of TT starting from initial TT was 14.9, 21.0, and 39.2 months, respectively (p<0.0001). On multivariable analysis adjusting for baseline Heng prognostic factors, the use of 2nd-line and 3rd-line therapy were each independently associated with better OS (HR=0.738 and 0.626, respectively, both p<0.0001). Survival benchmarks derived from patients in the IMDC using selected inclusion criteria as seen in contemporary mRCC clinical trials are shown below. Conclusions: Patients that are able to receive more lines of TT live longer. Survival benchmarks provide context and perspective when interpreting and designing new clinical trials. [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 | 0.146 | 0.209 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".