基于mALBI分级的风险模型预测阿特唑单抗加贝伐单抗作为一线治疗的肝癌患者预后的可靠性能:13种风险模型的比较分析

IF 3.7 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY
Takeshi Hatanaka, Satoru Kakizaki, Atsushi Hiraoka, Toshifumi Tada, Masashi Hirooka, 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, Atsushi Naganuma, Yutaka Yata, Hideko Ohama, Hidekatsu Kuroda, Tomomitsu Matono, Kazunari Tanaka, Fujimasa Tada, Kazuhiro Nouso, Asahiro Morishita, Akemi Tsutsui, Takuya Nagano, Norio Itokawa, Tomomi Okubo, Taeang Arai, Michitaka Imai, Yohei Koizumi, Shinichiro Nakamura, Masaki Kaibori, Hiroko Iijima, Yoichi Hiasa, Takashi Kumada, the Real-life Practice Experts for HCC (RELPEC) Study Group, and HCC 48 Group (hepatocellular carcinoma experts from 48 clinics in Japan)
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引用次数: 0

摘要

目的:本研究旨在比较接受阿特唑单抗和贝伐单抗(Atez/Bev)作为一线治疗的肝细胞癌(HCC)患者的预后风险模型。方法:在这项回顾性多中心研究的449例患者中,我们使用曲线下面积(AUC)、净重分类改善(NRI)和相对综合区分改善(IDI)分析比较13种风险模型对12个月和18个月生存状态的预后表现。我们还构建了一个校准图来评估每个模型的适应度。结果:在12个月生存状态分析中,所有风险模型的AUC值均未高于改良白蛋白-胆红素(mALBI)分级。在NRI分析中,与mALBI分级相比,只有AFP、BCLC分期、mALBI和DCP评估(IMABALI-De评分)的免疫治疗表现出具有统计学意义的改善(p = 0.009)。改良的白蛋白胆红素分级(mALF)评分和预后营养指数(PNI)与mALBI分级相比没有显著差异(p分别= 0.3和0.2),但其余风险模型不如mALBI分级。在相对IDI分析中,与mALBI等级相比,没有任何风险模型显示出显着改善。PNI的校准图不令人满意。18个月生存状态的结果与12个月生存状态的结果一致。时间相关的ROC分析表明,mALBI等级和基于mALBI的模型随时间的推移表现一致。结论:mALBI分级以及IMABALI-De和mALF评分(两者都是基于mALBI分级的风险模型)在预测HCC患者预后方面表现可靠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reliable Performance of mALBI Grade-Based Risk Models for Predicting the Prognosis of Patients With Hepatocellular Carcinoma Receiving Atezolizumab Plus Bevacizumab as First-Line Treatment: Comparative Analysis of 13 Risk Models

Aim

This study aimed to compare the prognostic performance of the risk models for patients with hepatocellular carcinoma (HCC) receiving atezolizumab and bevacizumab (Atez/Bev) as first-line treatment.

Methods

Among 449 patients included in this retrospective multicenter study, we compared the prognostic performance of 13 risk models for the 12-month and 18-month survival status using area under the curve (AUC), net reclassification improvement (NRI), and relative integrated discrimination improvement (IDI) analysis. We also constructed a calibration plot to assess the fitness of each model.

Results

Regarding the analysis of the 12-month survival status, none of the risk models demonstrated AUC values higher than the modified albumin-bilirubin (mALBI) grade. In the NRI analysis, only the IMmunotherapy with AFP, BCLC staging, mALBI, and DCP evaluation (IMABALI-De score) exhibited a statistically significant improvement compared with the mALBI grade (p = 0.009). While the modified albumin-bilirubin grade (mALF) score and prognostic nutritional index (PNI) did not exhibit significant differences compared to the mALBI grade (p = 0.3 and 0.2, respectively), the remaining risk models were inferior to the mALBI grade. In the relative IDI analysis, none of the risk models showed a significant improvement compared with the mALBI grade. The calibration plot of the PNI was unsatisfactory. The results for the 18-month survival status were consistent with those for the 12-month survival status. A time-dependent ROC analysis demonstrated that both the mALBI grade and the mALBI-based model showed consistent performance over time.

Conclusions

The mALBI grade, as well as the IMABALI-De and mALF scores (both of which are risk models based on mALBI grade), exhibited reliable performance in predicting the prognosis of patients with HCC.

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来源期刊
CiteScore
7.90
自引率
2.40%
发文量
326
审稿时长
2.3 months
期刊介绍: Journal of Gastroenterology and Hepatology is produced 12 times per year and publishes peer-reviewed original papers, reviews and editorials concerned with clinical practice and research in the fields of hepatology, gastroenterology and endoscopy. Papers cover the medical, radiological, pathological, biochemical, physiological and historical aspects of the subject areas. All submitted papers are reviewed by at least two referees expert in the field of the submitted paper.
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