Real world evidence comparison of first-line (1L) immune-oncology(IO)/tyrosine kinase inhibitor (TKI) vs. IO/IO combination therapy in renal cell carcinoma (RCC)

We performed a retrospective cohort study comparing IO/IO vs IO/TKI therapy for pts with metastatic RCC. We used the Atropos health platform, which is a commercial platform and queried ASCO CancerLinq data for this study. We identified pts with kidney cancer who received IO/IO or IO/TKI combinations between 2019 and 2023. For our primary analysis, we included only pts with ICD10 code consistent with clear cell [cc]RCC, but also did a secondary analysis including all pts with kidney cancer. The IO/TKI pts received either avelumab/axitinib, pembrolizumab/axitinib, nivolumab/cabozantinib, pembrolizumab/lenvatinib, or atezolizumab/cabozantinib within two weeks of each other. The IO/IO pts were identified as pts receiving ipilimumab and nivolumab within 2 weeks of each other without interceding TKI. We conducted a survival analysis of time to death using Cox proportional hazards regression to compare the two groups. The analysis was performed under three different confounder adjustment scenarios: without adjustment, with basic matching on sex and age, and with high dimensional propensity score (hdPS) using inverse probability of treatment weighting.

A total of 584 pts (286 IO/IO and 296 IO/TKI) with kidney cancer and 146 with ccRCC (75 IO/IO and 71 IO/TKI) were included. Mean age was 63-65 years and 30-35% female sex across groups. Table shows the restricted mean survival time (RMST) and HR for the Cox models. In the ccRCC cohort, 20 pts with IO/IO and 7 with IO/TKI died with RMST of 947 and 1071 days, respectively (hdPS HR 0.35, p=0.03). In the RCC cohort, 76 pts with IO/IO vs 49 with IO/TKI died with RMST 1126 vs 1017 (hdPS HR 0.61, p=0.04).

In this exploratory, hypothesis-generating analysis of CancerLinq data, pts treated with IO/TKI had longer OS vs those treated with IO/IO. Limitations include the retrospective nature of the study, low power, lack of randomization, and potential unmeasured confounding factors (e.g., confounding by indication). Further investigation and prospective validation are needed to confirm these findings.