CABOSEQ 3—Comparison of Cabozantinib versus Sunitinib Following First-Line Nivolumab- Ipilimumab for Metastatic Renal Cell Carcinoma: A Target Trial Emulation Using Real-World Data from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC)
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: While the benefit of cabozantinib in metastatic renal cell carcinoma (mRCC) is well established post-tyrosine kinase inhibitor therapy, its comparative effectiveness versus sunitinib after first-line (1L) nivolumab-ipilimumab is uncertain. METHODS: A target trial emulation was designed using data from the IMDC to estimate the effect of second-line (2L) cabozantinib versus sunitinib within 18 months of discontinuing 1L nivolumab-ipilimumab on overall survival (OS). Patients diagnosed after January 1, 2017 were followed from initiation of 2L until death or last known contact. Inverse-probability of treatment weighting was used to adjust for hemoglobin, calcium, platelets, and neutrophils at 2L, Karnofsky performance score (KPS) at 2L, time from diagnosis to initiation of 2L, and response to 1L nivolumab-ipilimumab. Treatments were compared using adjusted Kaplan-Meier curves and adjusted hazard ratios (HR) from a Cox regression model. Missing data were addressed with multiple imputation by chained equations. E-values were used to assess the likelihood findings could be explained by residual confounding. KEY FINDINGS AND LIMITATIONS: A total of 120 and 121 patients who received cabozantinib or sunitinib after 1L nivolumab-ipilimumab were included. The proportion with a KPS < 80% at 2L (21% vs. 46% P = .001) and the overall response rate to first line therapy (12.7% vs. 17.9% P = .002) differed significantly between cabozantinib and sunitinib. The objective response was 27% for cabozantinib versus 20% for sunitinib with a median time to treatment failure of 8.5 (95% CI: 6.9-12.9) and 4.5 (95% CI: 3.7-5.8) months. Median OS was 21.4 (95% CI: 17.9-NA) months from initiation of cabozantinib and 10.1 (95% CI: 7.6-17.7) months for sunitinib (Adjusted HR 0.44 (95% CI: 0.22-0.86)). The E-value was 2.92, suggesting a low likelihood of findings being due to residual confounding alone. CONCLUSIONS: These data provide real-world evidence supporting cabozantinib as a second-line treatment option in mRCC following 1L nivolumab-ipilimumab.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".