Predictive Value of Geriatric Nutritional Risk Index in Patients with Colorectal Cancer: A Meta-Analysis

Abstract

Geriatric Nutritional Risk Index (GNRI) has been used as a predictor of adverse prognosis in patients with colorectal cancer (CRC). This meta-analysis sought to evaluate the prognostic role of GNRI in CRC patients. Two authors comprehensively searched the studies indexed in PubMed and Embase databases until March 15, 2022. Only observational studies evaluating the association between GNRI and adverse outcomes in patients with CRC were eligible. The prognostic value of GNRI was expressed by pooling the adjusted hazard ratio (HR) with 95% confidence intervals (CI) for the low vs. high GNRI group. Eight retrospective studies enrolling 3239 CRC patients were included. When comparing the low with the high GNRI group, the pooled HR was 2.40 (95% CI 1.71–3.39) for overall survival, 1.63 (95% CI 1.35–1.96) for disease-free survival, and 1.85 (95% CI 1.21–1.83) for ≥ 2 Clavien-Dindo Grade postoperative complications, respectively. Moreover, malnutrition defined by the cutoff GNRI at 98 was associated with a reduced overall survival (HR 1.66; 95% CI 1.37–2.02). Low GNRI score may be a promising predictor of postoperative complications and long-term poor survival in Asian patients with CRC. Malnutrition defined by the GNRI can be applied to improve risk stratification of CRC.

Authors’ Contributions

Study conception/design and interpretation of data: DD Gong and Y Fan; Literature search, data extraction, quality assessment, statistical analysis: J Xu and YM Sun; Writing the manuscript: J Xu; Revising the manuscript: Y Fan. All authors read and approved the final manuscript.

Disclosure Statement

All authors declare that there is no conflict of interest.

Data Availability Statement

The available data and materials section refers to the raw data used in this study are included in manuscript.

Additional information

Funding

This work is supported by 1) Suqian Science and Technology Support Project Fund (K202014); 2) Jiangsu 333 Talent Fund (BRA2020016); and 3) Zhenjiang Key Research and Development Fund (SH2021038).