Second-line outcomes in metastatic renal cell carcinoma: The role of International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) prognostic factors after first-line immunotherapy.
Bibliographic record
Abstract
4548 Background: IMDC prognostic factors are well established in metastatic renal cell carcinoma (mRCC) with both VEGFR inhibitor and immunotherapy-based first-line therapies. However, the role of these prognostic factors for the second-line setting is less established in the contemporary era. Methods: We performed a retrospective analysis of patients with mRCC who received first-line therapy (1L) with dual immunotherapy (IPI-NIVO) or combination immunotherapy-VEGFR (IOVE) based regimens and then received second-line therapy (2L). 2L IMDC risk factors were assessed at the time of 2L therapy initiation and were composed of Karnofsky Performance Status < 80%, time from diagnosis to 2L therapy start < 1 year, hemoglobin < lower limit of normal, neutrophils > upper limit of normal (ULN), platelets > ULN, corrected calcium > ULN. 2L IMDC risk groups were favorable (0 risk factors), intermediate (1-2 risk factors), or poor risk (3+ risk factors). Baseline characteristics, objective response rates (ORR), treatment duration (TD), and overall survival (OS) were collected and compared by log-rank test. Results: A total of 781 patients were identified of whom 66% received IPI-NIVO and 34% received IOVE in the 1L setting. 2L IMDC risk groups and changes from 1L IMDC risk are presented in Table. Amongst all patients who received 2L therapies, 10.6% had favorable risk, 57.8% had intermediate risk, and 31.6% had poor risk disease. Nephrectomy status varied significantly across groups with 99% of favourable risk, 65% of intermediate risk, and 42% of poor risk patients having undergone nephrectomy (p<0.0001). Overall, 66.3% of patients retained their 1L risk group, while 12.6% were in a more favorable risk group and 21.1% a less favorable risk group. Type of 1L therapy (IPI-NIVO vs IOVE) did not predict change in 2L IMDC risk group (p=0.931). 2L therapies were heterogeneous with 38.9% receiving cabozantinib, 22.3% sunitinib, 8.7% pazopanib, 12.7% an IO-based regimen (IO monotherapy, IOIO, IOVE), and 17.4% other therapies. 2L ORR, TD, and OS varied significantly by 2L IMDC risk group (Table). Conclusions: In a real-world setting amongst patients receiving 1L IO-based regimens, IMDC risk factors remain prognostic in the 2L setting. These new benchmarks may be used for patient counselling and clinical trial design in 2L. Baseline characteristics and outcomes by 2L IMDC risk group. 2L FavorableN = 83 2L IntermediateN = 451 2L PoorN = 240 P-value 1L IPI-NIVO/IOVE 35/48 306/145 197/50 1L Favorable, N (%) 50 (50) 45 (45) 5 (5) 1L Intermediate, N (%) 21 (5.2) 284 (70.6) 97 (24.1) 1L Poor, N (%) 2 (1) 65 (33.3) 128 (65.6) 2L ORR, N (%) 26 (38.2) 114 (32.0) 40 (22.9) <0.0001 2L TD, Mo (95%CI) 9.8 (8.1-18.5) 9.1 (8.1-10.0) 4.2 (3.2-5.4) <0.0001 2L OS, Mo (95%CI) 41.0 (35.7-NR) 25.9 (20.5-32.1) 9.4 (7.1-10.8) <0.0001
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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 | 0.003 |
| 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) | 0.001 | 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".