30 August 2019 : Clinical Research
Conditional Survival in Patients with Advanced Renal Cell Carcinoma Treated with Nivolumab
Ning Shao12BCDE, Fangning Wan12BE, Yao Zhu12ADF, Dingwei Ye12AF*DOI: 10.12659/MSM.916984
Med Sci Monit 2019; 25:6518-6522
Abstract
BACKGROUND: Nivolumab is approved for the treatment of advanced renal cell carcinoma (RCC). However, traditional overall survival (OS) or progression-free survival (PFS) do not reflect patient prognosis after initial management. Therefore, this study aimed to evaluate conditional overall survival (COS) and conditional progression-free survival (CPFS) in patients with advanced RCC treated with nivolumab.
MATERIAL AND METHODS: There were 847 patients with advanced RCC treated with first-line nivolumab plus ipilimumab (n=425) and sunitinib (n=422), and 821 patients were treated with second-line nivolumab (n=410) and everolimus (n=411). Primary endpoints were COS and CPFS. Individual patient data of PFS and OS were digitally reconstructed from two large randomized controlled trials (CheckMate 025 and CheckMate 214).
RESULTS: In first-line treatment, compared with sunitinib, improvement of one-year CPFS for the nivolumab plus ipilimumab group after living for 0.5 and 0.75 years were 14% (from 53.0% to 67.0%) and 16% (from 57.0% to 73.0%) higher than the one-year PFS of 6.5% (from 42.9% to 49.4%), with similar results for one-year COS following first-line treatment. For second-line treatment, compared with everolimus, the improvement of one-year CPFS for the nivolumab group after living for 0.5 and 0.75 years were 19% (from 25.0% to 44.0%) and 19% (from 27.0% to 46.0%) and significantly higher than the one-year PFS of 4.5% (from 18.5% to 23.0%).
CONCLUSIONS: Survival benefit for patients with advanced RCC from nivolumab (plus ipilimumab) compared with sunitinib was more evident from conditional survival (CS) analysis of first-line treatment.
Keywords: Carcinoma, Renal Cell, Immunotherapy, Survival, Kidney Neoplasms, Nivolumab, Progression-Free Survival
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01 November 2024 : Editorial
Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and PrognosisDOI: 10.12659/MSM.947038
Med Sci Monit 2024; 30:e947038
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