使用创新的肝功能-营养-炎症-免疫（LFNII）评分构建并验证预测甲胎蛋白阴性肝细胞癌术后复发的新型列线图：一项双中心研究。
Construction and Validation of a Novel Nomogram Predicting Recurrence in Alpha-Fetoprotein-Negative Hepatocellular Carcinoma Post-Surgery Using an Innovative Liver Function-Nutrition-Inflammation-Immune (LFNII) Score: A Bicentric Investigation.
作者信息
Zhang Bo-Lun, Liu Jia, Diao Guanghao, Chang Jianping, Xue Junshuai, Huang Zhen, Zhao Hong, Yu Lingxiang, Cai Jianqiang
机构信息
Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Department of Hepatobiliary Surgery, the Fifth Medical Center of the PLA General Hospital, Beijing, People's Republic of China.
出版信息
J Hepatocell Carcinoma. 2024 Mar 6;11:489-508. doi: 10.2147/JHC.S451357. eCollection 2024.
PURPOSE
We developed a nomogram based on the liver function, nutrition, inflammation, and immunity (LFNII) score to predict recurrence-free survival (RFS) post-resection in patients with hepatocellular carcinoma (HCC) exhibiting alpha-fetoprotein (AFP) negativity (AFP ≤20 ng/mL).
PATIENTS AND METHODS
Clinical data of 661 patients diagnosed with alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) who underwent surgical resection at two medical centers between 2012 and 2021 were collected. A total of 462 and 199 patients served as the training and validation sets, respectively. Pre-operative blood markers were collected and analyzed for LFNII. The LFNII score was formulated using the least absolute shrinkage and selection operator Cox regression model. A nomogram model was developed using the training set to incorporate other relevant clinicopathological indicators and predict postoperative recurrence. Model discrimination was assessed using the receiver operating characteristic curve, calibration was evaluated using a calibration curve, and clinical applicability was assessed using clinical decision curve analysis. A comparison with liver cancer staging was performed using the nomogram model. Finally, a cohort study was conducted to validate our findings.
RESULTS
We derived the LFNII scores from nine indicators. Elevated LFNII scores correlated with unfavorable clinicopathological features. The LFNII score area under the curve revealed superior predictive efficacy at 1-, 2-, and 5-year RFS intervals, with values of 0.675, 0.658, and 0.633, respectively. Multivariate Cox analysis revealed that a high LFNII score independently increased RFS risk in patients with AFP-NHCC. The C-index of the LFNII-nomogram model was 0.686 (95% confidence interval [CI], 0.651-0.721). The nomogram model's clinical application value surpassed that of standard HCC staging systems.
CONCLUSION
The LFNII score-derived nomogram effectively predicted the RFS of patients with AFP-NHCC after curative resection.
目的
我们基于肝功能、营养、炎症和免疫（LFNII）评分开发了一种列线图，以预测甲胎蛋白（AFP）阴性（AFP≤20 ng/mL）的肝细胞癌（HCC）患者切除术后的无复发生存期（RFS）。
患者和方法
收集了2012年至2021年间在两个医疗中心接受手术切除的661例诊断为甲胎蛋白阴性肝细胞癌（AFP-NHCC）患者的临床数据。分别有462例和199例患者作为训练集和验证集。收集术前血液标志物并分析LFNII。使用最小绝对收缩和选择算子Cox回归模型制定LFNII评分。使用训练集开发列线图模型，纳入其他相关临床病理指标并预测术后复发。使用受试者工作特征曲线评估模型辨别力，使用校准曲线评估校准情况，使用临床决策曲线分析评估临床适用性。使用列线图模型与肝癌分期进行比较。最后，进行队列研究以验证我们的发现。
结果
我们从九个指标得出LFNII评分。升高的LFNII评分与不良临床病理特征相关。曲线下面积的LFNII评分在1年、2年和5年RFS间隔显示出卓越的预测效能，其值分别为0.675、0.658和0.633。多变量Cox分析显示，高LFNII评分独立增加AFP-NHCC患者的RFS风险。LFNII-列线图模型的C指数为0.686（95%置信区间[CI]，0.651-0.721）。列线图模型的临床应用价值超过标准HCC分期系统。
结论
基于LFNII评分的列线图有效预测了AFP-NHCC患者根治性切除术后的RFS。
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