Evaluation of Treatment Outcomes Using dNLR and GNRI in Combination Therapy With Atezolizumab and Bevacizumab for Hepatocellular Carcinoma

Evaluation of Treatment Outcomes Using dNLR and GNRI in Combination Therapy With Atezolizumab and Bevacizumab for Hepatocellular Carcinoma

ABSTRACT Aim This study aims to investigate the clinical utility of the derived neutrophil‐to‐lymphocyte ratio (dNLR) and the Geriatric Nutritional Risk Index (GNRI) in predicting treatment outcomes for patients with unresectable hepatocellular carcinoma (HCC) undergoing combination therapy with ate...

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Main Authors: Atsushi Naganuma, Satoru Kakizaki, Atsushi Hiraoka, Toshifumi Tada, Takeshi Hatanaka, Kazuya Kariyama, Joji Tani, Masanori Atsukawa, Koichi Takaguchi, Ei Itobayashi, Shinya Fukunishi, Kunihiko Tsuji, Toru Ishikawa, Kazuto Tajiri, Hidenori Toyoda, Chikara Ogawa, Hiroki Nishikawa, Takashi Nishimura, Kazuhito Kawata, Hisashi Kosaka, Masashi Hirooka, Yutaka Yata, Hideko Ohama, Hidekatsu Kuroda, Tomomitsu Matono, Tomoko Aoki, Yuki Kanayama, Kazunari Tanaka, Fujimasa Tada, Kazuhiro Nouso, Asahiro Morishita, Akemi Tsutsui, Takuya Nagano, Norio Itokawa, Tomomi Okubo, Taeang Arai, Michitaka Imai, Shinichiro Nakamura, Hirayuki Enomoto, Masaki Kaibori, Yoichi Hiasa, Masatoshi Kudo, Takashi Kumada
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Cancer Medicine
Subjects:
dNLR
GNRI
hepatocellular carcinoma
immune checkpoint inhibitor
prognosis
Online Access:https://doi.org/10.1002/cam4.70618
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Summary:ABSTRACT Aim This study aims to investigate the clinical utility of the derived neutrophil‐to‐lymphocyte ratio (dNLR) and the Geriatric Nutritional Risk Index (GNRI) in predicting treatment outcomes for patients with unresectable hepatocellular carcinoma (HCC) undergoing combination therapy with atezolizumab and bevacizumab (Atez/Bev). Methods A retrospective analysis was conducted on 310 patients. The dNLR, NLR, and GNRI were calculated, and their impact on progression‐free survival (PFS) and overall survival (OS) was assessed. The formula for calculating dNLR is: (neutrophil count ÷ [white blood cell count—neutrophil count]), which means it does not require lymphocyte count. Furthermore, GNRI‐dNLR and GNRI‐NLR scores were defined, and their prognostic values were also analyzed. Results The median PFS of this cohort was 7.2 months (95% CI: 5.9–8.5), and the median OS was 24.9 months (95% CI: 19.6–30.2). The dNLR, NLR, and GNRI were significant predictors of both PFS and OS. The dNLR showed a significant correlation with the NLR (Pearson correlation coefficient, p < 0.0001). Patients with high GNRI‐dNLR scores demonstrated significantly worse PFS and OS compared to those with low scores (p = 0.001, p < 0.001, respectively). Compared to stratification by GNRI alone, the GNRI‐dNLR or GNRI‐NLR provided better stratification for both PFS and OS. Conclusion The dNLR could be a valuable substitute for NLR as a prognostic marker in patients with unresectable HCC undergoing Atez/Bev therapy. It offers a feasible alternative for databases lacking lymphocyte count information, ensuring comprehensive patient stratification and outcome prediction. The GNRI‐NLR or GNRI‐dNLR score provided better stratification compared to GNRI alone.
ISSN:2045-7634

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