Outcomes for International Metastatic Renal Cell Carcinoma Database Consortium Prognostic Groups in Contemporary First-line Combination Therapies for Metastatic Renal Cell Carcinoma
Bibliographic record
Abstract
BACKGROUND: The combination of immuno-oncology (IO) agents ipilimumab and nivolumab (IPI-NIVO) and vascular endothelial growth factor targeted therapies (VEGF-TT) combined with IO (IO-VEGF) are current standard of care first-line treatments for metastatic renal cell carcinoma (mRCC). OBJECTIVE: To establish real-world clinical benchmarks for IO combination therapies based on the International mRCC Database Consortium (IMDC) criteria. DESIGN, SETTING, AND PARTICIPANTS: Patients with mRCC who received first-line IPI-NIVO, IO-VEGF, or VEGF-TT from 2002 to 2021 were identified using the IMDC database and stratified according to IMDC risk groups. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Overall survival (OS), time to next treatment (TTNT), and treatment duration (TD) were calculated using the Kaplan-Meier method and compared between IMDC risk groups within each treatment cohort by the log-rank test. The overall response rate (ORR) was calculated by physician assessment of the best overall response. The primary outcome was OS at 18 mo. RESULTS AND LIMITATIONS: In total, 728 patients received IPI-NIVO, 282 IO-VEGF, and 7163 VEGF-TT. The median follow-up times for patients remaining alive were 14.3 mo for IPI-NIVO, 14.9 mo IO-VEGF, and 34.4 mo for VEGF-TT. OS at 18 mo for favorable, intermediate, and poor risk was, respectively, 90%, 78%, and 50% for those receiving IPI-NIVO; 93%, 83%, and 74% for IO-VEGF; and 84%, 64%, and 28% for VEGF-TT. ORRs in favorable-, intermediate-, and poor-risk groups were 41.3%, 40.6%, and 33.0% for those receiving IPI-NIVO; 60.3%, 56.8%, and 40.9% for IO-VEGF; and 39.3%, 33.5%, and 20.9% for VEGF-TT, respectively. The IMDC model stratified patients into statistically distinct risk groups for the three endpoints of OS, TTNT, and TD within each treatment cohort. Limitations of this study were the retrospective design and short follow-up. CONCLUSIONS: This study demonstrated that the IMDC model continues to risk stratify patients with mRCC treated with contemporary first-line IO combination therapies and provided real-world survival benchmarks. PATIENT SUMMARY: The International Metastatic Renal Cell Carcinoma Database Consortium model continues to stratify patients with metastatic renal cell carcinoma receiving modern combination treatments in the real-world setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".