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      Hepatic arterial infusion chemotherapy combined with anti-PD-1/PD-L1 immunotherapy and molecularly targeted agents for advanced hepatocellular carcinoma: a real world study

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          Abstract

          Background

          Molecular targeted therapy combined with immunotherapy significantly improves the prognosis of patients with advanced liver cancer. Additionally, hepatic arterial infusion chemotherapy (HAIC) can improve the prognosis of patients with advanced liver cancer. This real-world study aimed to evaluate the clinical efficacy and safety of HAIC combined with molecular targeted therapy and immunotherapy in the treatment of primary unresectable hepatocellular carcinoma (uHCC).

          Methods

          A total of 135 patients with uHCC were enrolled in this study. Progression-free survival (PFS) was the primary endpoint. The efficacy of the combination therapy was assessed based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) guidelines. Overall survival (OS), adverse events (AEs) and surgical conversion rate were the secondary endpoints. Univariate and multivariate Cox regression analyses were performed to examine independent prognostic factors. For sensitivity analysis, inverse probability weighting (IPW) was used to balance the influence of the tested confounding factors between groups to verify the robustness of conversion surgery for survival benefits. The E-values were estimated to assess robustness to unmeasured confounders.

          Results

          The median number of therapies was three. Approximately 60% of the patients had portal vein tumour thrombosis (PVTT). The most common targeted drugs were lenvatinib and bevacizumab, whereas the most common immunotherapy drug was sintilimab. The overall objective response rate (ORR) was 54.1%, and the disease control rate (DCR) was 94.6%. A total of 97 (72%) patients experienced AEs of grades 3–4. Fatigue, pain and fever were the most common symptoms of grade 3-4 AEs. The median PFS was 28 months and 7 months in the successful and unsuccessful conversion groups, respectively. The median OS was 30 months and 15 months in the successful and unsuccessful conversion groups, respectively. Successful conversion surgery, sex, hapatic vein invasion, BCLC stage, baseline tumour size, AFP levels and maximum therapeutic response were independent prognostic factors for PFS. Successful conversion surgery, number of interventions, hapatic vein invasion and total bilirubin levels were independent prognostic factors for OS. After IPTW, no standardised differences exceeding 0.1 were found. IPW-adjusted Kaplan–Meier curves showed that successful conversion surgery was an independent prognostic factor for both PFS and OS. The E-values of successful conversion surgery were 7.57 and 6.53 for OS and PFS, respectively, which indicated a relatively robust impact of successful conversion surgery on the prognosis of patients.

          Conclusion

          Patients with primary uHCC undergoing HAIC combined with immunotherapy and molecular targeted therapy have a higher tumour regression rate and the side effects are manageable. Patients undergoing surgery after combination therapy have survival benefits.

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          Most cited references37

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            The combination of atezolizumab and bevacizumab showed encouraging antitumor activity and safety in a phase 1b trial involving patients with unresectable hepatocellular carcinoma.
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              An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

              The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                26 April 2023
                2023
                : 14
                : 1127349
                Affiliations
                [1] 1 Department of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer , Tianjin, China
                [2] 2 Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital , Tianjin, China
                [3] 3 Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital , Tianjin, China
                [4] 4 Department of Hepatobiliary, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer , Tianjin, China
                Author notes

                Edited by: Chenyu Sun, AMITA Health, United States

                Reviewed by: Feiling Feng, Eastern Hepatobiliary Surgery Hospital, China; Xinwei Han, Zhengzhou University, China

                *Correspondence: Wenge Xing, xingwenge@ 123456tjmuch.com ; Haipeng Yu, jieruke@ 123456163.com

                †These authors have contributed equally to this work and share first authorship

                This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2023.1127349
                10169627
                37180098
                e293a7cc-bfd5-4966-bbe2-7d5c8199b62a
                Copyright © 2023 Zhang, Zhang, Liu, Gao, Si, Zou, Guo, Yang, Li, Liu, Mu, Li, Yu and Xing

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 19 December 2022
                : 31 March 2023
                Page count
                Figures: 7, Tables: 1, Equations: 0, References: 38, Pages: 11, Words: 3868
                Funding
                This work was supported by the 2020 pilotage elite special scientific research fund, Grant No.XM2020031029501, China Health Promotion Foundation (No: XM-2018-011-0006-01), Beijing Health Prevention and Therapy Association (No: IZ 2021-1001).
                Categories
                Immunology
                Original Research

                Immunology
                hepatic arterial infusion chemotherapy,molecularly targeted agents,advanced hepatocellular carcinoma,conversion surgery,survival benefit,anti-pd-1/pd-l1 immunotherapy

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