Prognostic Role of Pre-Treatment Body Composition Parameters in Patients Undergoing First-Line Immunotherapy for Metastatic Renal Cell Carcinoma

Abstract

Purpose: We investigated the relationship between body mass index (BMI), radiological body composition, and survival outcomes in patients with metastatic renal cell carcinoma (mRCC) underwent first-line immune checkpoint inhibitor (ICI)-based therapy.

Methods: Analyzing data from 102 patients treated between November 2019 and March 2023, pre-treatment computed tomography (CT) scans assessed fat and muscle areas. BMI and body composition indices were examined, including skeletal muscle index, subcutaneous fat index (SFI), visceral fat index, and total fat index. Kaplan-Meier curves and Log rank tests compared progression-free survival (PFS) and overall survival (OS), while multivariable Cox proportional regression analysis was performed to identify the variables significantly associated with survival outcomes.

Results: 54 patients (52.9%) experienced disease progression, and 26 (25.5%) died during a median follow-up of 17.4 months. High SFI was significantly associated with improved OS (p = 0.018) but not PFS (p = 0.090). Multivariable analysis confirmed the positive impact of high SFI on OS (adjusted HR: 0.37, p = 0.029) and suggested a trend towards improved PFS (adjusted HR: 0.61, p = 0.088). Notably, in the ipilimumab + nivolumab subgroup, high SFI significantly correlated with both PFS and OS (p = 0.047 and p = 0.012, respectively).

Conclusion: High SFI predicts favorable OS in patients with mRCC receiving first-line ICI-based therapy, especially patients treated with ipilimumab + nivolumab displayed a significant association between high SFI and favorable PFS and OS.

Keywords: body composition; immunotherapy; prognosis; renal cell carcinoma.

Figure 1

Semiautomatic quantification of body composition in a 58-year-old male with metastatic renal cell carcinoma. To enhance the visibility of muscle boundaries, computed tomography (CT) image intensity was linearly transformed into a range of 0 to +100 Hounsfield Units (HU) (A). Following semiautomatic manipulation (B), the active contour method is used to detect the boundary between muscles and inner tissues by minimizing a cost function, thereby segmenting CT images into inner and outer regions (C). Subsequently, pixels corresponding to fat and muscle are identified using predefined cut-off values of −300 to −50 HU and −29 to +150 HU, respectively. Regions of muscle, subcutaneous fat, and visceral fat are displayed as color-coded in green, red, and blue, respectively (D). The cross-sectional areas of muscle, subcutaneous fat, and visceral fat are quantified at 140.18 cm², 94.95 cm², and 186.46 cm², respectively. CT, computed tomography; HU, Hounsfield unit.

Figure 2

Kaplan–Meier analysis of overall survival and progression-free survival according to high and low subcutaneous fat indexes (SFI).

Figure 3

Kaplan–Meier analysis of overall survival and progression-free survival according to high and low subcutaneous fat indexes (SFI) in the ipilimumab + nivolumab subgroup and immune checkpoint inhibitors with tyrosine kinase inhibitor (ICI with TKI) subgroup.