8 Nivolumab plus ipilimumab vs sunitinib for first-line treatment of advanced renal cell carcinoma: 8-year follow-up with analyses in favorable risk patients from the phase 3 CheckMate 214 trial
Bibliographic record
Abstract
Abstract Background First-line nivolumab plus ipilimumab (NIVO+IPI) has provided substantial long-term survival benefits over sunitinib (SUN) in patients with advanced renal cell carcinoma (aRCC) in CheckMate 214. With a median follow-up of 8 years, the longest follow-up to date for any phase 3 trial of immune checkpoint inhibitor combination therapy in patients with aRCC, we report survival, response per independent radiology review committee (IRRC), and safety in all randomized patients (intent-to-treat [ITT] population) and in patients with International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) favorable risk. Methods Patients with clear cell aRCC were randomized 1:1 to NIVO 3 mg/kg plus IPI 1 mg/kg Q3W×4 doses, followed by NIVO (3 mg/kg or 240 mg Q2W or 480 mg Q4W); or SUN 50 mg once daily for 4 weeks on, 2 weeks off. Key study endpoints included overall survival (OS), IRRC-assessed progression-free survival (PFS) and objective response rate (ORR) in intermediate/poor-risk (primary), ITT (secondary), and favorable-risk (exploratory) patients. Cancer-specific survival was evaluated in ITT patients by censoring all causes of death other than RCC. Post hoc exploratory analyses in patients with favorable risk were performed. Results With 8 years (99.1 months) median follow-up, OS with NIVO+IPI versus SUN remained superior in ITT patients (hazard ratio [HR], 0.72; Table). The HR for PFS with NIVO+IPI versus SUN was 0.88. ORR was higher with NIVO+IPI versus SUN (Table), with more complete responses (12% vs 3%) and a longer median duration of response (DOR) in the combination arm versus SUN. In patients with favorable risk, OS benefits were similar between arms (HR, 0.82; Table). The HR for PFS favored SUN (HR, 1.76). ORR was lower with NIVO+IPI versus SUN, yet more patients achieved complete responses (13% vs 6%, respectively) and median DOR was longer with NIVO+IPI. Median cancer-specific survival (95% CI) in ITT patients was 73.7 (62.8-91.2) months with NIVO+IPI versus 45.1 (37.8-53.3) months with SUN (HR, 0.69; 95% CI 0.59-0.82). In exploratory post hoc analyses of patients with favorable risk, 75/125 (60.0%) patients in the NIVO+IPI arm and 85/124 (68.5%) patients in the SUN arm died over 8 years of follow-up. Of these patients, 31 in the NIVO+IPI arm and 27 in the SUN arm died within 3 years of randomization; the primary reason for death was disease in either arm (71.0% and 85.2%, respectively). Furthermore, among 27 patients in the NIVO+IPI arm with favorable risk who died after disease progression within 3 years, 12 patients did not receive second-line systemic therapy. Beyond 3 years, only 2 of 43 patients who died after disease progression did not receive subsequent systemic therapy. Among all treated patients, incidence of any-grade and grade 3-4 treatment-related adverse events remained largely unchanged. No new drug-related deaths occurred in either arm since the previous database lock. Table Conclusions With a median follow-up up of 8 years, NIVO+IPI continues to demonstrate sustained survival and more durable response benefits versus SUN in the ITT population, including a further reduction in the risk of death with NIVO+IPI as measured by cancer-specific survival. Long-term exploratory data in patients with favorable risk have shown a steady improvement in the HR for OS, and a marked improvement in median DOR and complete response rates with NIVO+IPI versus SUN, thus contributing to the survival and response benefits reported in the ITT population. Furthermore, the disproportionate number of patients with favorable risk who died within 3 years of randomization after documented progression without receiving subsequent therapy may have affected the HR for OS in this patient population early on. NIVO+IPI offers the potential for positive long-term outcomes, regardless of IMDC risk, and with no emergence of new safety signals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".