Suppr超能文献

基于肝动脉灌注化疗的肝癌转化切除术后复发概率和无复发生存率预测的列线图:一项多中心回顾性研究。

Nomograms for predicting the recurrence probability and recurrence-free survival in patients with hepatocellular carcinoma after conversion hepatectomy based on hepatic arterial infusion chemotherapy: a multicenter, retrospective study.

机构信息

Department of Liver Surgery, Sun Yat-sen University Cancer Center.

State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine.

出版信息

Int J Surg. 2023 May 1;109(5):1299-1310. doi: 10.1097/JS9.0000000000000376.

Abstract

BACKGROUND

This study aimed to establish and validate nomograms to predict the probability of recurrence and recurrence-free survival (RFS) in patients with hepatocellular carcinoma (HCC) after conversion hepatectomy based on hepatic arterial infusion chemotherapy (HAIC).

METHODS

Nomograms were constructed using data from a retrospective study of 214 consecutive patients treated with HAIC-based conversion liver resection between January 2016 and July 2020. Nomograms predicting the probability of tumor recurrence and RFS were established based on predictors selected by multivariate regression analysis. Predictive accuracy and discriminative ability of the nomogram were examined. Bootstrap method was used for internal validation. External validation was performed using cohorts ( n =128) from three other centers.

RESULTS

Recurrence rates in the primary and external validation cohorts were 63.6 and 45.3%, respectively. Nomograms incorporating clinicopathological features of tumor recurrence and RFS were generated. Concordance index (C-index) scores of the nomograms for predicting recurrence probability and RFS were 0.822 (95% CI, 0.703-0.858) and 0.769 (95% CI, 0.731-0.814) in the primary cohort, and 0.802 (95% CI, 0.726-0.878) and 0.777 (95% CI, 0.719-0.835) in the external validation cohort, respectively. Calibration curves indicated good agreement between the nomograms and actual observations. Moreover, the nomograms outperformed the commonly used staging systems. Patients with low risk, stratified by the median nomogram scores had better RFS (low risk vs. high risk, 36.5 vs. 5.2 months, P <0.001). The external validation cohort supported these findings.

CONCLUSIONS

The presented nomograms showed favorable accuracy for predicting recurrence probability and RFS in HCC patients treated with HAIC-based conversion hepatectomy. Identifying risk factors and estimating tumor recurrence may help clinicians in the decision-making process regarding adjuvant therapies for patients with HCC, which eventually achieves better oncological outcomes.

摘要

背景

本研究旨在建立并验证基于肝动脉灌注化疗(HAIC)的转化肝切除术后肝癌(HCC)患者复发和无复发生存(RFS)概率的列线图。

方法

使用 2016 年 1 月至 2020 年 7 月期间接受基于 HAIC 的转化肝切除治疗的 214 例连续患者的回顾性研究数据,构建了预测肿瘤复发和 RFS 的列线图。基于多变量回归分析选择的预测因子建立预测肿瘤复发和 RFS 的列线图。检验列线图的预测准确性和区分能力。使用 bootstrap 方法进行内部验证。使用来自其他三个中心的 128 例队列进行外部验证。

结果

原发和外部验证队列的复发率分别为 63.6%和 45.3%。生成了包含肿瘤复发和 RFS 的临床病理特征的列线图。列线图预测复发概率和 RFS 的一致性指数(C 指数)评分分别为原发队列的 0.822(95%CI,0.703-0.858)和 0.769(95%CI,0.731-0.814),外部验证队列的 0.802(95%CI,0.726-0.878)和 0.777(95%CI,0.719-0.835)。校准曲线表明列线图与实际观察结果吻合良好。此外,列线图优于常用的分期系统。根据中位数列线图评分分层的低危患者具有更好的 RFS(低危 vs. 高危,36.5 与 5.2 个月,P<0.001)。外部验证队列支持这些发现。

结论

本研究提供的列线图在预测接受基于 HAIC 的转化肝切除治疗的 HCC 患者的复发概率和 RFS 方面具有较好的准确性。识别危险因素和估计肿瘤复发有助于临床医生在 HCC 患者辅助治疗决策中做出决策,最终实现更好的肿瘤学结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a18b/10389618/32a0869a54fe/js9-109-1299-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验