Nivolumab plus cabozantinib in metastatic renal cell carcinoma: real-world evidence from the international ARON-1 study
Bibliographic record
Abstract
Introduction: Four approved immune-based combinations for untreated metastatic renal carcinoma have demonstrated survival benefits. The ARON-1 study (NCT05287464) analyzed real-world data of patients with metastatic renal cell carcinoma receiving first-line immuno-oncology combinations. This sub-analysis is focused on the nivolumab plus cabozantinib effectiveness. Methods: We conducted a retrospective study across 52 centers in 17 countries, including patients with metastatic renal carcinoma treated with first-line nivolumab plus cabozantinib, regardless of histologic characteristics, performance status, or risk by IMDC prognostic model. Patients with incomplete medical data were excluded. The primary objective of this sub-analysis of the ARON-1 study was to evaluate the real-world effectiveness and safety. Results: A total of 333 patients were treated with nivolumab plus cabozantinib, clinical characteristics included ECOG performance status ≥2 20%, non-clear cell histology 16%, sarcomatoid de-differentiation 12%, and poor-risk by IMDC 28%. At a median follow-up of 15.9 months (95%CI 11.2-44.0), the median overall survival was not reached (40.0-NR), the probability of survival at 2 years was 75%, while median progression free survival was 33.7 months (95%CI 21.1-38.9). In the entire cohort, an objective response was observed in 58%, with 6% complete responses, and a median duration of response of 38.9 months (95%CI 33.7-NR). At multivariate analysis, adverse prognostic factors for overall survival included ECOG performance status ≥2, sarcomatoid de-differentiation, brain and bone metastases, and poor IMDC group. In the safety analysis, the incidence of grade 3 or higher toxicity was 37%, with hypertension and hand-foot syndrome being the most frequent adverse events. Conclusion: The findings in the present real-world study reaffirm the clinical benefits and safety of the nivolumab plus cabozantinib combination across all subgroups, including populations that are generally excluded from clinical trials for whom data is often missing. Poor performance status, sarcomatoid de-differentiation, bone or central nervous system metastases and IMDC poor risk group were confirmed as negative prognostic factors.
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".