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Preoperative Prediction for Early Recurrence Can Be as Accurate as Postoperative Assessment in Single Hepatocellular Carcinoma Patients.

ABSTRACT: OBJECTIVE:To evaluate the performance of predicting early recurrence using preoperative factors only in comparison with using both pre-/postoperative factors. MATERIALS AND METHODS:We retrospectively reviewed 549 patients who had undergone curative resection for single hepatcellular carcinoma (HCC) within Milan criteria. Multivariable analysis was performed to identify pre-/postoperative high-risk factors of early recurrence after hepatic resection for HCC. Two prediction models for early HCC recurrence determined by stepwise variable selection methods based on Akaike information criterion were built, either based on preoperative factors alone or both pre-/postoperative factors. Area under the curve (AUC) for each receiver operating characteristic curve of the two models was calculated, and the two curves were compared for non-inferiority testing. The predictive models of early HCC recurrence were internally validated by bootstrap resampling method. RESULTS:Multivariable analysis on preoperative factors alone identified aspartate aminotransferase/platelet ratio index (OR, 1.632; 95% CI, 1.056-2.522; p = 0.027), tumor size (OR, 1.025; 95% CI, 0.002-1.049; p = 0.031), arterial rim enhancement of the tumor (OR, 2.350; 95% CI, 1.297-4.260; p = 0.005), and presence of nonhypervascular hepatobiliary hypointense nodules (OR, 1.983; 95% CI, 1.049-3.750; p = 0.035) on gadoxetic acid-enhanced magnetic resonance imaging as significant factors. After adding postoperative histopathologic factors, presence of microvascular invasion (OR, 1.868; 95% CI, 1.155-3.022; p = 0.011) became an additional significant factor, while tumor size became insignificant (p = 0.119). Comparison of the AUCs of the two models showed that the prediction model built on preoperative factors alone was not inferior to that including both pre-/postoperative factors {AUC for preoperative factors only, 0.673 (95% confidence interval [CI], 0.623-0.723) vs. AUC after adding postoperative factors, 0.691 (95% CI, 0.639-0.744); p = 0.0013}. Bootstrap resampling method showed that both the models were valid. CONCLUSION:Risk stratification solely based on preoperative imaging and laboratory factors was not inferior to that based on postoperative histopathologic risk factors in predicting early recurrence after curative resection in within Milan criteria single HCC patients.

SUBMITTER: Cha DI

PROVIDER: S-EPMC7082657 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Preoperative Prediction for Early Recurrence Can Be as Accurate as Postoperative Assessment in Single Hepatocellular Carcinoma Patients.

Cha Dong Ik DI Jang Kyung Mi KM Kim Seong Hyun SH Kim Young Kon YK Kim Honsoul H Ahn Soo Hyun SH

Korean journal of radiology 20200401 4

<h4>Objective</h4>To evaluate the performance of predicting early recurrence using preoperative factors only in comparison with using both pre-/postoperative factors.<h4>Materials and methods</h4>We retrospectively reviewed 549 patients who had undergone curative resection for single hepatcellular carcinoma (HCC) within Milan criteria. Multivariable analysis was performed to identify pre-/postoperative high-risk factors of early recurrence after hepatic resection for HCC. Two prediction models f ...[more]

PMID: 32193888

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Project description:MethodsBetween December 2017 and December 2018, 153 HCC patients (134 males and 19 females; mean age, 56.0 ± 10.2 years; range, 28-78 years) treated with radical therapy were enrolled in our retrospective study and were divided into a training cohort (n = 107) and a validation cohort (n = 46). All patients underwent preoperative CTC tests and CEUS examinations before treatment. The ultrasomics signature was extracted and built from CEUS images. Univariate and multivariate logistic regression analyses were used to identify the significant variables related to ER, which were then combined to build a predictive nomogram. The performance of the nomogram was evaluated by its discrimination, calibration and clinical utility. The predictive model was further evaluated in the internal validation cohort.ResultsHBV DNA, serum AFP level, CTC status, tumour size and ultrasomics score were identified as independent predictors associated with ER (all p < 0.05). Multivariable logistic regression analysis showed that the CTC status (OR = 7.02 [95% CI, 2.07 to 28.38], p = 0.003) and ultrasomics score (OR = 148.65 [95% CI, 25.49 to 1741.72], p < 0.001) were independent risk factors for ER. The nomogram based on ultrasomics score, CTC status, serum AFP level and tumour size exhibited C-indexes of 0.933 (95% CI, 0.878 to 0.988) and 0.910 (95% CI, 0.765 to 1.055) in the training and validation cohorts, respectively, fitting well in calibration curves. Decision curve analysis further confirmed the clinical usefulness of the nomogram.ConclusionThe nomogram incorporating CTC, ultrasomics features and independent clinical risk factors achieved satisfactory preoperative prediction of ER in HCC patients after radical treatment.Advances in knowledge1. CTC status and ultrasomics score were identified as independent predictors associated with ER of HCC after radical treatment. 2. The nomogram constructed by ultrasomics score generated by 17 ultrasomics features, combined with CTCs and independent clinical risk factors such as AFP and tumour size. 3. The nomogram exhibited satisfactory discriminative power, and could be clinically useful in the preoperative prediction of ER after radical treatment in HCC patients.

Project description:Background and aimsThe incidence of non-B, non-C hepatocellular carcinoma (NBNC-HCC) is increasing. Like in hepatitis B virus (HBC)/HCV-associated HCC, treatment of NBNC-HCC after resection is challenging due to its high recurrence rate. However, few studies on the recurrence of NBNC-HCC have been published in the past decades. Hence, we aimed to investigate the risk factors for recurrence of NBNC-HCC and construct pre- and postoperative prognostic models for predicting recurrence in these patients who underwent curative resection.MethodsWe retrospectively analyzed 608 patients who underwent liver resection for NBNC-HCC. A multivariate Cox proportional hazard regression analysis was conducted to identify the independent risk factors of recurrence, based on which the prediction nomogram models were constructed and validated. The predictive performance of the models was assessed using the concordance index, time-dependent receiver operating characteristic curve, prediction error cure, and calibration curve. To facilitate clinical use, we stratified the patients into three distinct risk groups based on the score of the models. The cutoff scores of the models were determined by a survival tree analysis.ResultsMultivariable analysis identified neutrophil-to-lymphocyte ratio, alpha fetoprotein, tumor number, and tumor diameter as independent preoperative risk factors for recurrence. In addition to these variables, microvascular invasion was an independent postoperative risk factor for recurrence. The pre- and postoperative nomograms were constructed based on these variables. The C-index of the pre- and postoperative nomograms was 0.689 and 0.702 in the training cohort, 0.682 and 0.688 in the validation cohort, respectively, which were both higher than those of the conventional Barcelona Clinic Liver Cancer (BCLC) and 8th edition of the American Joint Committee on Cancer (AJCC8th) staging systems. In addition, the pre- and postoperative nomograms could also re-stratify patients with BCLC stage 0/A or AJCC8th stage IA/IB/II into distinct risk groups.ConclusionsWe constructed pre- and postoperative prognostic models for predicting recurrence in patients with NBNC-HCC who underwent curative resection. They can play a supplementary role to the traditional staging system.

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Preoperative Prediction for Early Recurrence Can Be as Accurate as Postoperative Assessment in Single Hepatocellular Carcinoma Patients.

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Preoperative Prediction for Early Recurrence Can Be as Accurate as Postoperative Assessment in Single Hepatocellular Carcinoma Patients.

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