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准确预测肝癌根治性手术后微血管侵犯的发生及对患者的有效预后评估。

Accurate prediction of microvascular invasion occurrence and effective prognostic estimation for patients with hepatocellular carcinoma after radical surgical treatment.

机构信息

Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.

Department of Hepatopancreatobiliary Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.

出版信息

World J Surg Oncol. 2022 Sep 30;20(1):328. doi: 10.1186/s12957-022-02792-y.

DOI:10.1186/s12957-022-02792-y
PMID:36180867
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9523961/
Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) is the third most common cause of cancer death worldwide, with an overall 5-year survival rate of less than 18%, which may be related to tumor microvascular invasion (MVI). This study aimed to compare the clinical prognosis of HCC patients with or without MVI after radical surgical treatment, and further analyze the preoperative risk factors related to MVI to promote the development of a new treatment strategy for HCC.

METHODS

According to the postoperative pathological diagnosis of MVI, 160 study patients undergoing radical hepatectomy were divided into an MVI-negative group (n = 68) and an MVI-positive group (n = 92). The clinical outcomes and prognosis were compared between the two groups, and then the parameters were analyzed by multivariate logistic regression to construct an MVI prediction model. Then, the practicability and validity of the model were evaluated, and the clinical prognosis of different MVI risk groups was subsequently compared.

RESULT

There were no significant differences between the MVI-negative and MVI-positive groups in clinical baseline, hematological, or imaging data. Additionally, the clinical outcome comparison between the two groups presented no significant differences except for the pathological grading (P = 0.002) and survival and recurrence rates after surgery (P < 0.001). The MVI prediction model, based on preoperative AFP, tumor diameter, and TNM stage, presented superior predictive efficacy (AUC = 0.7997) and good practicability (high H-L goodness of fit, P = 0.231). Compared with the MVI high-risk group, the patients in the MVI low-risk group had a higher survival rate (P = 0.002) and a lower recurrence rate (P = 0.004).

CONCLUSION

MVI is an independent risk factor for a poor prognosis after radical resection of HCC. The MVI prediction model, consisting of AFP, tumor diameter, and TNM stage, exhibits superior predictive efficacy and strong clinical practicability for MVI prediction and prognostication, which provides a new therapeutic strategy for the standardized treatment of HCC patients.

摘要

背景

肝细胞癌(HCC)是全球第三大常见癌症死亡原因,整体 5 年生存率不足 18%,这可能与肿瘤微血管侵犯(MVI)有关。本研究旨在比较根治性手术后伴有和不伴有 MVI 的 HCC 患者的临床预后,并进一步分析与 MVI 相关的术前危险因素,以促进 HCC 新治疗策略的发展。

方法

根据术后 MVI 的病理诊断,将 160 例接受根治性肝切除术的研究患者分为 MVI 阴性组(n=68)和 MVI 阳性组(n=92)。比较两组的临床结局和预后,然后通过多变量逻辑回归分析参数,构建 MVI 预测模型。然后评估模型的实用性和有效性,随后比较不同 MVI 风险组的临床预后。

结果

MVI 阴性组和 MVI 阳性组在临床基线、血液学或影像学数据方面无显著差异。此外,两组之间的临床结果比较除病理分级(P=0.002)和术后生存率和复发率外(P<0.001),无显著差异。基于术前 AFP、肿瘤直径和 TNM 分期的 MVI 预测模型具有较高的预测效能(AUC=0.7997)和良好的实用性(高 H-L 拟合优度,P=0.231)。与 MVI 高风险组相比,MVI 低风险组患者的生存率更高(P=0.002),复发率更低(P=0.004)。

结论

MVI 是 HCC 根治性切除术后预后不良的独立危险因素。由 AFP、肿瘤直径和 TNM 分期组成的 MVI 预测模型在预测和预后 MVI 方面具有较高的预测效能和较强的临床实用性,为 HCC 患者的规范化治疗提供了新的治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/dc01cf84c152/12957_2022_2792_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/fc5b830a6e25/12957_2022_2792_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/5e4a84dfada9/12957_2022_2792_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/33e4f23cc56d/12957_2022_2792_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/61b9d32939d0/12957_2022_2792_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/dc01cf84c152/12957_2022_2792_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/fc5b830a6e25/12957_2022_2792_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/5e4a84dfada9/12957_2022_2792_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/33e4f23cc56d/12957_2022_2792_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/61b9d32939d0/12957_2022_2792_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72de/9523961/dc01cf84c152/12957_2022_2792_Fig5_HTML.jpg

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