Geriatric nutritional risk index as a prognostic marker of first-line immune checkpoint inhibitor combination therapy in patients with renal cell carcinoma: a retrospective multi-center study.

Abstract

PURPOSE:

This study aimed to investigate the effectiveness of the Geriatric Nutritional Risk Index (GNRI) in predicting the efficacy of first-line immune checkpoint inhibitor (ICI) combination therapy for metastatic or unresectable renal cell carcinoma (RCC) and associated patient prognosis.

METHODS:

A retrospective study was conducted using data from 19 institutions. The GNRI was calculated using body mass index and serum albumin level, and patients were classified into two groups using the GNRI values, with 98 set as the cutoff point.

RESULTS:

In all, 119 patients with clear cell RCC who received first-line drug therapy with ICIs were analyzed. Patients with GNRI ≥ 98 had significantly better overall survival (OS) (p = 0.008) and cancer-specific survival (CSS) (p = 0.001) rates than those with GNRI < 98; however, progression-free survival (PFS) did not differ significantly. Inverse probability of treatment weighting analysis showed that low GNRI scores were significantly associated with poor OS (p = 0.004) and CSS (p = 0.015). Multivariate analysis showed that the Karnofsky performance status (KPS) score was a better predictor of prognosis (OS; HR 5.17, p < 0.001, CSS; HR 4.82, p = 0.003) than GNRI (OS; HR 0.36, p = 0.066, CSS; HR 0.35, p = 0.072). In a subgroup analysis of patients with a good KPS and GNRI ≥ 98 vs < 98, the 2-year OS rates were 91.4% vs 66.9% (p = 0.068), 2-year CSS rates were 91.4% vs 70.1% (p = 0.073), and PFS rates were 39.7% vs 21.4 (p = 0.27), respectively.

CONCLUSION:

The prognostic efficiency of GNRI was inferior to that of the KPS score at the initiation of the first-line ICI combination therapy for clear cell RCC.

• Authors: Shogo Watari, Satoshi Katayama, Hiromasa Shiraishi, Moto Tokunaga, Risa Kubota, Norihiro Kusumi, Takaharu Ichikawa, Tomoyasu Tsushima, Yasuyuki Kobayashi, Kensuke Bekku, Motoo Araki
• Journal: Discover oncology (Discov Oncol) Vol. 14 Issue 1 Pg. 204 (Nov 16 2023) ISSN: 2730-6011 [Electronic] United States
• PMID: 37968545 (Publication Type: Journal Article)
• Copyright: © 2023. The Author(s).