Open AccessPrognostic value of prognostic nutritional index and its variations in advanced non‐small‐cell lung cancer patients treated with anlotinib monotherapy
Author(s) -
Chen Tian,
Liang Gaofeng,
Xiang Zhenfei,
He Jinxian,
Xu Xiaoyu,
Tang Mengqiu
Publication year - 2022
Publication title -
journal of clinical laboratory analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 50
eISSN - 1098-2825
pISSN - 0887-8013
DOI - 10.1002/jcla.24300
Subject(s) - medicine , oncology , multivariate analysis , lung cancer , proportional hazards model , univariate analysis , overall survival , univariate , multivariate statistics , statistics , mathematics
Background Anlotinib is a third‐line or further therapy for advanced non‐small‐cell lung cancer (NSCLC). However, the lack of simple biomarkers to predict the curative effect of anlotinib creates significant unmet needs in exploring the markers. This study aimed to explore the relationship between the prognostic nutritional index (PNI) and its variations and efficacy of anlotinib. Methods Data for patients with advanced NSCLC who received anlotinib were collected at Ningbo Medical Center Lihuili Hospital. The data included the values of pretreatment PNI (pre‐PNI), posttreatment PNI (post‐PNI), and ΔPNI (post‐PNI minus the pre‐PNI). The Kaplan–Meier method was used to generate survival curves, whereas univariate and multivariate Cox regression analyses were used to analyze survival predictors. Results A high disease control rate was associated with a high pre‐PNI ( p = 0.007), high post‐PNI ( p = 0.000), and high ΔPNI ( p = 0.006). Univariable analysis revealed that pre‐PNI ≤41.80, post‐PNI ≤42.48, and ΔPNI ≤0.20 were significant risk factors for poor survival. According to the multivariate analysis, progression‐free survival (PFS) in patients with post‐PNI ≤42.48 was significantly shorter than in patients with higher values (median PFS: 1.5 months vs. 4.0 months, p = 0.010). Conclusions Pre‐PNI, ΔPNI, and post‐PNI were found to be predictive factors for response in advanced NSCLC patients treated with anlotinib as a third‐line or further treatment. Only post‐PNI was a reliable predictor of PFS. Therefore, PNI and its variations, particularly post‐PNI, are affordable and accessible predictors of NSCLC patients treated with anlotinib in clinical work.