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

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

doi:10.1002/cam4.70618

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

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 KosakaMasashi 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

^*Corresponding author for this work

Internal Medicine （3）

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	e70618
Journal	Cancer Medicine
Volume	14
Issue number	2
DOIs	https://doi.org/10.1002/cam4.70618
State	Published - 2025/01

Keywords

dNLR
GNRI
hepatocellular carcinoma
immune checkpoint inhibitor
prognosis

ASJC Scopus subject areas

Oncology
Radiology Nuclear Medicine and imaging
Cancer Research

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/cam4.70618

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Naganuma, A., Kakizaki, S., Hiraoka, A., Tada, T., Hatanaka, T., Kariyama, K., Tani, J., Atsukawa, M., Takaguchi, K., Itobayashi, E., Fukunishi, S., Tsuji, K., Ishikawa, T., Tajiri, K., Toyoda, H., Ogawa, C., Nishikawa, H., Nishimura, T., Kawata, K., ... Kumada, T. (2025). Evaluation of Treatment Outcomes Using dNLR and GNRI in Combination Therapy With Atezolizumab and Bevacizumab for Hepatocellular Carcinoma. Cancer Medicine, 14(2), Article e70618. https://doi.org/10.1002/cam4.70618

@article{f9ffa1bdbcbf4d1c81bf93f507bf8c5a,

title = "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 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.",

keywords = "dNLR, GNRI, hepatocellular carcinoma, immune checkpoint inhibitor, prognosis",

author = "Atsushi Naganuma and Satoru Kakizaki and Atsushi Hiraoka and Toshifumi Tada and Takeshi Hatanaka and Kazuya Kariyama and Joji Tani and Masanori Atsukawa and Koichi Takaguchi and Ei Itobayashi and Shinya Fukunishi and Kunihiko Tsuji and Toru Ishikawa and Kazuto Tajiri and Hidenori Toyoda and Chikara Ogawa and Hiroki Nishikawa and Takashi Nishimura and Kazuhito Kawata and Hisashi Kosaka and Masashi Hirooka and Yutaka Yata and Hideko Ohama and Hidekatsu Kuroda and Tomomitsu Matono and Tomoko Aoki and Yuki Kanayama and Kazunari Tanaka and Fujimasa Tada and Kazuhiro Nouso and Asahiro Morishita and Akemi Tsutsui and Takuya Nagano and Norio Itokawa and Tomomi Okubo and Taeang Arai and Michitaka Imai and Shinichiro Nakamura and Hirayuki Enomoto and Masaki Kaibori and Yoichi Hiasa and Masatoshi Kudo and Takashi Kumada",

note = "Publisher Copyright: {\textcopyright} 2025 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.",

year = "2025",

month = jan,

doi = "10.1002/cam4.70618",

language = "英語",

volume = "14",

journal = "Cancer Medicine",

issn = "2045-7634",

publisher = "John Wiley and Sons Inc.",

number = "2",

}

Naganuma, A, Kakizaki, S, Hiraoka, A, Tada, T, Hatanaka, T, Kariyama, K, Tani, J, Atsukawa, M, Takaguchi, K, Itobayashi, E, Fukunishi, S, Tsuji, K, Ishikawa, T, Tajiri, K, Toyoda, H, Ogawa, C, Nishikawa, H, Nishimura, T, Kawata, K, Kosaka, H, Hirooka, M, Yata, Y, Ohama, H, Kuroda, H, Matono, T, Aoki, T, Kanayama, Y, Tanaka, K, Tada, F, Nouso, K, Morishita, A, Tsutsui, A, Nagano, T, Itokawa, N, Okubo, T, Arai, T, Imai, M, Nakamura, S, Enomoto, H, Kaibori, M, Hiasa, Y, Kudo, M & Kumada, T 2025, 'Evaluation of Treatment Outcomes Using dNLR and GNRI in Combination Therapy With Atezolizumab and Bevacizumab for Hepatocellular Carcinoma', Cancer Medicine, vol. 14, no. 2, e70618. https://doi.org/10.1002/cam4.70618

TY - JOUR

T1 - Evaluation of Treatment Outcomes Using dNLR and GNRI in Combination Therapy With Atezolizumab and Bevacizumab for Hepatocellular Carcinoma

AU - Naganuma, Atsushi

AU - Kakizaki, Satoru

AU - Hiraoka, Atsushi

AU - Tada, Toshifumi

AU - Hatanaka, Takeshi

AU - Kariyama, Kazuya

AU - Tani, Joji

AU - Atsukawa, Masanori

AU - Takaguchi, Koichi

AU - Itobayashi, Ei

AU - Fukunishi, Shinya

AU - Tsuji, Kunihiko

AU - Ishikawa, Toru

AU - Tajiri, Kazuto

AU - Toyoda, Hidenori

AU - Ogawa, Chikara

AU - Nishikawa, Hiroki

AU - Nishimura, Takashi

AU - Kawata, Kazuhito

AU - Kosaka, Hisashi

AU - Hirooka, Masashi

AU - Yata, Yutaka

AU - Ohama, Hideko

AU - Kuroda, Hidekatsu

AU - Matono, Tomomitsu

AU - Aoki, Tomoko

AU - Kanayama, Yuki

AU - Tanaka, Kazunari

AU - Tada, Fujimasa

AU - Nouso, Kazuhiro

AU - Morishita, Asahiro

AU - Tsutsui, Akemi

AU - Nagano, Takuya

AU - Itokawa, Norio

AU - Okubo, Tomomi

AU - Arai, Taeang

AU - Imai, Michitaka

AU - Nakamura, Shinichiro

AU - Enomoto, Hirayuki

AU - Kaibori, Masaki

AU - Hiasa, Yoichi

AU - Kudo, Masatoshi

AU - Kumada, Takashi

PY - 2025/1

Y1 - 2025/1

N2 - 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.

AB - 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.

KW - dNLR

KW - GNRI

KW - hepatocellular carcinoma

KW - immune checkpoint inhibitor

KW - prognosis

UR - http://www.scopus.com/inward/record.url?scp=85215961336&partnerID=8YFLogxK

U2 - 10.1002/cam4.70618

DO - 10.1002/cam4.70618

M3 - 学術論文

C2 - 39840727

AN - SCOPUS:85215961336

SN - 2045-7634

VL - 14

JO - Cancer Medicine

JF - Cancer Medicine

IS - 2

M1 - e70618

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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