Abstract
BackgroundThere is no study accessible now assessing the prognostic aspect of radiomics for anti-PD-1 therapy for patients with HCC.AimThe aim of this study was to develop and validate a radiomics nomogram by incorporating the pretreatment contrast-enhanced Computed tomography (CT) images and clinical risk factors to estimate the anti-PD-1 treatment efficacy in Hepatocellular Carcinoma (HCC) patients.MethodsA total of 58 patients with advanced HCC who were refractory to the standard first-line of therapy, and received PD-1 inhibitor treatment with Toripalimab, Camrelizumab, or Sintilimab from 1st January 2019 to 31 July 2020 were enrolled and divided into two sets randomly: training set (n = 40) and validation set (n = 18). Radiomics features were extracted from non-enhanced and contrast-enhanced CT scans and selected by using the least absolute shrinkage and selection operator (LASSO) method. Finally, a radiomics nomogram was developed based on by univariate and multivariate logistic regression analysis. The performance of the nomogram was evaluated by discrimination, calibration, and clinical utility.ResultsEight radiomics features from the whole tumor and peritumoral regions were selected and comprised of the Fusion Radiomics score. Together with two clinical factors (tumor embolus and ALBI grade), a radiomics nomogram was developed with an area under the curve (AUC) of 0.894 (95% CI, 0.797–0.991) and 0.883 (95% CI, 0.716–0.998) in the training and validation cohort, respectively. The calibration curve and decision curve analysis (DCA) confirmed that nomogram had good consistency and clinical usefulness.ConclusionsThis study has developed and validated a radiomics nomogram by incorporating the pretreatment CECT images and clinical factors to predict the anti-PD-1 treatment efficacy in patients with advanced HCC.
Highlights
Hepatocellular carcinoma (HCC) is the fourth most common cancer and the second leading causes of cancerrelated mortality worldwide [1, 2]
The inclusion criteria were listed as follows: 1. patients who were aged ≥18 with HCC diagnosed by two imaging modalities, or biopsy; 2. were refractory to the standard first-line of therapy; 3. were in stage C according to the Barcelona Clinic Liver Cancer (BCLC) staging system; or in stage B who could not tolerate further surgery or ablation; 4. with Child-Pugh A or B liver function; 5
There are currently no reliable predictive biomarker to aid in the precision of programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) therapy and excavating a curative effect predictor as useful tool for progressive disease (PD)-1/PD-L1 application in HCC patients is urgently needed in the era of precision medicine
Summary
Hepatocellular carcinoma (HCC) is the fourth most common cancer and the second leading causes of cancerrelated mortality worldwide [1, 2]. Late diagnosis, limited treatment options and lack of predictors of anti-tumor efficacy greatly account for the poor prognosis of HCC [3,4,5]. According to the limited researches [18,19,20,21], tumor mutational burden (TMB) and PD-L1 expression are the most extensively studied predictive markers for the efficacy of PD-1/PD-L1 treatment. The percentage of patients with high TMB was low in HCC, and its value as a predictive marker for PD-1 therapy is not reported in the CheckMate-040 and KEYNOTE-224 study [13, 14]. Identifying robust predictors as useful tools to predict response to PD-1/PD-L1 treatment in HCC patients is urgently needed in the era of precision medicine. There is no study accessible assessing the prognostic aspect of radiomics for anti-PD-1 therapy for patients with HCC
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