A nomogram integrating hepatic reserve and tumor characteristics for hepatocellular carcinoma following curative liver resection
Introduction
Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third leading cause of cancer deaths worldwide [1]. Hepatic resection remains the best therapeutic option for potential curative outcomes, although less than a third of HCC cases are suitable for it at the time of diagnosis [2]. Unlike other solid tumors, the prognosis and treatment options for patients with HCC depend not only on the tumor stage but also on residual liver function [3, 4]. In an attempt to stratify expected survival outcomes for HCC patients treated by partial hepatectomy, several staging systems have been developed, including the Cancer of the Liver Italian Program (CLIP) staging system [5], the Barcelona Clinic Liver Cancer (BCLC) staging system [6], Okuda staging system [7], and the seventh edition of the Tumor Node Metastasis (TNM 7th) system [8]. Unfortunately, their criteria vary greatly, and no single system has consistently emerged as the optimal predictor of postoperative survival [9], including the BCLC or CLIP systems.
The albumin-bilirubin (ALBI) scoring model for evaluation of hepatic reserve in patients with HCC was reported, recently [10]. The ALBI grade offers a simple, evidence-based, objective, and discriminatory method of assessing hepatic reserve in HCC that has been extensively tested in an international setting, including patients treated with transarterial chemo-embolisation [11] and sorafenib [3, 12]. The ALBI score not only provides superior prognostic information to Child-Pugh (CP) class in patients with HCC but also obviates the need to assess subjective parameters such as ascites and hepatic encephalopathy [13, 14]. Modification of the BCLC system and CLIP score with the incorporation of the ALBI grade retains and, might have improved prognosis prediction for advanced HCC [[15], [16], [17], [18]]. However, BCLC and CLIP systems are excessively complex, which are clearly impractical in a busy clinical practice.
Nomograms are graphical depictions of predictive statistical models for individual patients, and have been developed for various diseases, which have consistently shown better performance characteristics than other options [19, 20]. Moreover, nomograms provide a user-friendly interface, which does not require computer software for interpretation/prediction [21]. In addition, the use of nomograms has a demonstrated advantage over the traditional staging systems used to predict patient outcomes for many diseases [22]. The nomograms have been proposed as an alternative method or even as a new standard to guide treatment allocation for critical diseases [23].
Section snippets
Study design and participants
We enrolled patients treated with liver resection for HCC from the First Affiliated Hospital of Wenzhou Medical University between Jan 1, 2007, and Dec 31, 2015, retrospectively. Patients who met the following criteria were excluded: liver transplantation; preoperative anticancer therapy or intraoperative radiofrequency ablation; other simultaneous malignancies; cardiopulmonary, renal or cerebral dysfunction before liver resection. Patients undergoing repeat or noncurative resections were also
Patient characteristics
After exclusion of those who did not meet the inclusion criteria, 709 consecutive patients with HCC were finally included. The baseline characteristics of the patients in the training cohort were listed in Table 1. Supplementary Table 1 summarized the baseline characteristics of 1022 patients with HCC following curative liver resection in the validation cohort (Japan cohort = 615; Hong Kong cohort = 407).
Prognostic factors
Mortality was 16.9% at 1 y, 32.9% at 3 y and 40.6% at 5 y follow-up. Univariate analysis
Discussion
Nomograms provide user-friendly, accurate and reproducible predictions for patients without requiring computer software for interpretation/prediction, thereby allowing clinicians to standardize clinical decision-making. In current study, we developed and validated a prognostic nomogram integrating the ALBI grade and tumor characteristics, which had a high accuracy for predicting OS of patients with HCC following curative liver resection. The prognostic value of the nomogram was superior to
Acknowledgements
This work was supported by grants from Natural Science Foundation of Zhejiang Province (LY16H160047), Provinces and Ministries Co-Contribution of Zhejiang, China (No. wkj-zj-1706), Project of New Century 551 Talent Nurturing in Wenzhou, the Natural Science Foundation of China (81501823), Zhejiang Provincial Natural Science Foundation of China (LY18H160049 and LY17H200005), The medical scientific research of Zhejiang Province, Wenzhou municipal Science and Technology Bureau (Y20160077 and
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