Abstract Background Non-clear cell renal cell carcinoma (nccRCC) represents 25% of subtypes of kidney cancer and portends a poor prognosis PMID: 37823185. Given their rarity, clinical trial data to guide systemic therapy for metastatic disease are limited, and they are often treated similarly to clear cell RCC. Herein, we sought to assess treatment patterns and attrition rates of patients with metastatic nccRCC in a real-world nationwide database. Methods We utilized the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database. Eligibility: patients diagnosed with metastatic nccRCC (chromophobe, papillary, not otherwise specified NOS). Patients treated on clinical trials or with non-recommended chemotherapy regimens were excluded. Treatment patterns by line (L) of therapy and attrition rates by nccRCC subtype were collected. Results Of 13 909 patients diagnosed with metastatic RCC from 1/1/2011 to 10/16/2024, 2607 patients had metastatic nccRCC, received eligible 1 L therapy, and were included in our analysis (chromophobe 166 6.4%; papillary 740 28.4%; NOS 1701 65.2%). Treatment patterns and attrition rates by histological subtype are summarized in Table. Of 166 patients with chromophobe RCC, 57.2% received 2 L and 34.3% of patients received 3 L. Tyrosine kinase inhibitors (TKIs) were the most common treatment in 1 L (50%) and 2 L (38.9%), while both TKI and single-agent PD-1 inhibitors (PD-1i) were used similarly in 3 L (26.3%, each). Of 740 patients with papillary RCC who received 1 L, 59.7% received 2 L and 28.9% received 3 L. TKIs were the most common treatment in 1 L (48.4%), 2 L (36.7%), and 3 L (34.6%). Of 1701 patients with NOS, 41.3% received 2 L, and 17.6% received 3 L. TKIs again were the most common treatment in 1 L (48.7%), 2 L (34.7%), and 3 L (41.5%). Conclusions In one of the largest real-world studies evaluating treatment patterns and attrition rates in patients with metastatic nccRCC, TKI was the most commonly used treatment across chromophobe, papillary, and NOS subtypes. These data could help guide clinical trial design.
Özay et al. (Wed,) studied this question.