Clinical Outcomes Associated with Monotherapy and Combination Therapy of Immune Checkpoint Inhibitors as First-Line Treatment for Advanced Hepatocellular Carcinoma in Real-World Practice: A Systematic Literature Review and Meta-Analysis

Zou, Huimin; Lei, Qing; Yan, Xin; Lai, Yunfeng; Ung, Carolina Oi Lam; Hu, Hao

doi:10.3390/cancers15010260

Cited by 3 publications

(1 citation statement)

References 75 publications

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“…HCC progress rapidly, and most patients are diagnosed in an advanced stage. Although the emerging systemic therapies such as immune checkpoint inhibitors (ICIs)-based therapies have significantly improved the clinical outcomes in advanced HCC, the medical utilisation, productivity loss, and long and poor prognosis owing to the disease have brought a substantial economic burden to HCC patients and payers [6][7][8]. The costs of HCC are forecasted to exceed US$500 million and JPY 607.2 billion annually in the United States (US) and Japan [9,10].…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of disease modelling for health economic evaluations of systemic therapies in advanced hepatocellular carcinoma

Zou,

Xue,

Chen

et al. 2023

PLoS ONE

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Background The objective of this study was to systematically analyse methodological and structural assumptions utilised in model-based health economic evaluations of systemic advanced hepatocellular carcinoma (HCC) therapies, discuss the existing challenges, and develop methodological recommendations for future models in advanced HCC. Methods We performed literature searches using five databases (Embase, PubMed, Web of Science, Econlit, and CNKI) up to December 4, 2022. Technology appraisals from Canada, England, Australia, and the United States were also considered. Model-based full economic evaluations of systemic advanced HCC therapies in English or Chinese met the eligibility criteria. The reporting quality was assessed by using the Consolidated Health Economic Evaluation Reporting Standards 2022 checklist. Results Of 12,863 records retrieved, 55 were eligible for inclusion. Markov model (n = 29, 53%) and partitioned survival model (n = 27, 49%) were the most commonly used modelling techniques. Most studies were based on health-state-driven structure (n = 51, 93%), followed by treatment-line-driven structure (n = 2, 4%) and combination structure (n = 1, 2%). Only three studies (5%) adopted external real-world data to extrapolate the overall survival or calibrate the extrapolation. Few studies reported the assumptions of transition probabilities. Utility modelling approaches were state-based (n = 51, 93%) and time-to-death (n = 1, 2%). Only 13 studies (24%) reported five types of model validation. Economic evaluation results of specific treatment strategies varied among studies. Conclusions Disease modelling for health economic evaluations of systemic therapies in advanced HCC has adopted various modelling approaches and assumptions, leading to marked uncertainties in results. By proposing methodological recommendations, we suggest that future model-based studies for health economic evaluation of HCC therapies should follow good modelling practice guidelines and improve modelling methods to generate reliable health and economic evidence.

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Section: Introductionmentioning

confidence: 99%

Comparative analysis of disease modelling for health economic evaluations of systemic therapies in advanced hepatocellular carcinoma

Zou,

Xue,

Chen

et al. 2023

PLoS ONE

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Real-world treatment patterns and outcomes for patients with advanced hepatocellular carcinoma initially treated with PD-1 inhibitors

Zou,

Ge,

Chen

et al. 2024

International Immunopharmacology

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Radiomics models based on multisequence MRI for predicting PD-1/PD-L1 expression in hepatocellular carcinoma

Gong,

Liu,

Tao

et al. 2023

Sci Rep

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The purpose of this study was to explore the effectiveness of radiomics based on multisequence MRI in predicting the expression of PD-1/PD-L1 in hepatocellular carcinoma (HCC). One hundred and eight patients with HCC who underwent contrast-enhanced MRI 2 weeks before surgical resection were enrolled in this retrospective study. Corresponding paraffin sections were collected for immunohistochemistry to detect the expression of PD-1 and PD-L1. All patients were randomly divided into a training cohort and a validation cohort at a ratio of 7:3. Univariate and multivariate analyses were used to select potential clinical characteristics related to PD-1 and PD-L1 expression. Radiomics features were extracted from the axial fat-suppression T2-weighted imaging (FS-T2WI) images and the arterial phase and portal venous phase images from the axial dynamic contrast-enhanced MRI, and the corresponding feature sets were generated. The least absolute shrinkage and selection operator (LASSO) was used to select the optimal radiomics features for analysis. Logistic regression analysis was performed to construct single-sequence and multisequence radiomics and radiomic-clinical models. The predictive performance was judged by the area under the receiver operating characteristic curve (AUC) in the training and validation cohorts. In the whole cohort, PD-1 expression was positive in 43 patients, and PD-L1 expression was positive in 34 patients. The presence of satellite nodules served as an independent predictor of PD-L1 expression. The AUC values of the FS-T2WI, arterial phase, portal venous phase and multisequence models in predicting the expression of PD-1 were 0.696, 0.843, 0.863, and 0.946 in the training group and 0.669, 0.792, 0.800 and 0.815 in the validation group, respectively. The AUC values of the FS-T2WI, arterial phase, portal venous phase, multisequence and radiomic-clinical models in predicting PD-L1 expression were 0.731, 0.800, 0.800, 0.831 and 0.898 in the training group and 0.621, 0.743, 0.771, 0.810 and 0.779 in the validation group, respectively. The combined models showed better predictive performance. The results of this study suggest that a radiomics model based on multisequence MRI has the potential to predict the preoperative expression of PD-1 and PD-L1 in HCC, which could become an imaging biomarker for immune checkpoint inhibitor (ICI)-based treatment.

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Clinical Outcomes Associated with Monotherapy and Combination Therapy of Immune Checkpoint Inhibitors as First-Line Treatment for Advanced Hepatocellular Carcinoma in Real-World Practice: A Systematic Literature Review and Meta-Analysis

Cited by 3 publications

References 75 publications

Comparative analysis of disease modelling for health economic evaluations of systemic therapies in advanced hepatocellular carcinoma

Comparative analysis of disease modelling for health economic evaluations of systemic therapies in advanced hepatocellular carcinoma

Real-world treatment patterns and outcomes for patients with advanced hepatocellular carcinoma initially treated with PD-1 inhibitors

Radiomics models based on multisequence MRI for predicting PD-1/PD-L1 expression in hepatocellular carcinoma

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