Comparing Health Insurance-ReimbursedFirst Line Lenvatinib and Self-paid Atezolizumab plus Bevacizumab in Patients with Unresectable Hepatocellular Carcinoma

Comparing Health Insurance-ReimbursedFirst Line Lenvatinib and Self-paid Atezolizumab plus Bevacizumab in Patients with Unresectable Hepatocellular Carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparing Health Insurance-ReimbursedFirst Line Lenvatinib and Self-paid Atezolizumab plus Bevacizumab in Patients with Unresectable Hepatocellular Carcinoma Yuan-Hung Kuo, Yen-Hao Chen, Ming-Chao Tsai, Sheng-Nan Lu, Tsung-Hui Hu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4522670/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background/Purpose: Atezolizumab plus bevacizumab (Ate/Bev) and lenvatinib (Len) are first-line therapies for unresectable hepatocellular carcinoma (uHCC). However, Ate/Bev's high cost limits its common use in real-life practice, while Len is usually covered by national health insurance (NHI). We conducted this study to compare their effectiveness and safety in real-world settings. Methods: We retrospectively evaluated 346 uHCC patients treated with first-line Ate/Bev (n=80) or Len (n=266) from December 2019 to December 2022, using 1:2 ratio propensity score matching (PSM) analyses. Results: Compared to the Len group, the Ate/Bev group exhibited higher incidences of Child-Pugh class B (14.1% vs. 5.7%, p=0.014), larger main tumors (58.8% vs. 40.2%, p=0.003), and more main portal vein invasion (25% vs. 12.8%, p=0.008). Treatment-related adverse events were notably lower in the Ate/Bev group (56.3% vs. 72.3%, p=0.007). After PSM, no significant differences were observed in the objective response rate (21.9% vs. 21.6%, p=0.983), progression-free survival (5.1 vs. 6 months, p=0.783), and overall survival (13.3 vs. 14.1 months, p=0.945) between the Ate/Bev (n=73) and Len (n=142) groups. Patients in the Ate/Bev group received more sequential post-treatments compared to the Len group (45.2% vs. 24.6%, p=0.009). Len-based therapies (n=28, 84.8%) and mono- or combined-immunotherapy (n=19, 54.3%) were the most frequently administered sequential therapies following Ate/Bev and Len, respectively. Conclusion: Patients with uHCC who received first-line self-paid Ate/Bev appeared to have lower liver function reserve and more advanced tumor characteristics compared to those who underwent NHI-reimbursed Len. However, the treatment outcomes and safety profiles were similar between these two groups. Atezolizumab plus Bevacizumab Lenvatinib National health insurance Propensity score matching analysis Unresectable hepatocellular carcinoma. Figures Figure 1 Figure 2 Figure 3 Introduction Unresectable hepatocellular carcinoma (HCC) represents a formidable challenge in clinical oncology, necessitating the exploration of diverse therapeutic strategies to improve patient outcomes. In recent years, the advent of immune checkpoint inhibitors (ICIs) and targeted therapies has transformed the treatment landscape for advanced HCC [ 1 ]. Atezolizumab, an immune checkpoint inhibitor targeting programmed death-ligand 1 (PD-L1), in combination with Bevacizumab, an anti-vascular endothelial growth factor (VEGF) monoclonal antibody, has demonstrated promising efficacy and safety in clinical trials [ 2 , 3 ]. The IMbrave150 trial, a landmark phase III study, established atezolizumab plus bevacizumab (Ate/Bev) as a new standard of care for unresectable HCC, showing a superior overall survival (OS) of 19.2 months compared to 13.4 months in patients receiving sorafenib (hazard ratio (HR): 0.66, p = 0.0009), the previous standard first-line therapy [ 2 ]. Lenvatinib (Len), a multitargeted tyrosine kinase inhibitor (TKI), has also emerged as a frontline treatment option for unresectable HCC [ 4 ]. The REFLECT trial demonstrated non-inferiority of Len compared to sorafenib in terms of OS (median 13.6 versus 12.3 months, respectively), with favorable objective response rates (ORR) and progression-free survival (PFS) [ 5 ]. Subsequent real-world studies have corroborated the efficacy and safety of Len in routine clinical practice, highlighting its role as a valuable therapeutic option for patients with advanced HCC [ 6 – 9 ]. However, the comparative effectiveness and safety of Ate/Bev versus Len in randomised controlled trial remains lack. Several real-world studies have evaluated the clinical outcomes of these two regimens in patients with unresectable HCC [ 10 – 12 ]. For instance, a single institute study from Taiwan indicated that there was no significant difference in ORR, PFS, and OS between the Len and Ate/Bev groups [ 10 ]. Similarly, a large real-life worldwide analysis also reported that Ate/Bev did not show a survival advantage over Len (HR: 0.97 (p = 0.739)). [ 11 ]. The study reported comparable OS but lower rates of treatment-related adverse events (TRAEs) with the immunotherapy combination compared to Len. However, another multicenter retrospective study from Japan investigated the real-world effectiveness of Ate/Bev versus Len in patients with unresectable HCC across multiple institutions [ 12 ]. The findings suggested Ate/Bev group showed better PFS (0.5-/1-/1.5-years: 56.6%/31.6%/non-estimable vs. 48.6%/20.4%/11.2%, p < 0.0001) and OS rates (0.5-/1-/1.5-years: 89.6%/67.2%/58.1% vs. 77.8%/66.2%/52.7%, p = 0.002) than the Len group. These varieties of survival analyses between Ate/Bev and Len might be due to different studied population. A recent meta-analysis enrolling 8 real-world studies indicated that the Ate/Bev group had significant longer PFS, compared with Len group but no significant difference in OS, ORR and disease control rate (DCR) among them [ 13 ]. Moreover, patients receiving Ate/Bev exhibited lower incidences of grade 3/4 AEs than those receiving Len. Through an in-depth analysis of these real-world comparisons and ongoing prospective trials, we aim to enhance our understanding of the relative effectiveness and safety profiles of Ate/Bev and Len, particularly within the distinct reimbursement framework of health insurance for these agents in Taiwan. Notably, Len has been reimbursed by Taiwan's National Health Insurance (NHI) since Jan 2020, while Ate/Bev has been covered since August 2023 [ 14 ]. Consequently, this study was undertaken to investigate the comparative efficacy and safety of Ate/Bev versus Len as first-line treatments for patients with unresectable HCC under different reimbursement statuses of National Health Insurance in real-world. Materials and Methods Patients We evaluated patients with unresectable HCC treated with Ate/Bev or Len between December 2019 and December 2022 in Kaohsiung Chang Gung Memorial Hospital. HCC diagnosis relied on computed tomography (CT) or magnetic resonance imaging (MRI) identifications or histological proofs. Clinical data, including patient demographics, tumor characteristics, treatment details, and outcomes, were collected from electronic medical records. Inclusion criteria comprised a diagnosis of unresectable HCC, aged 18 years or older, and receiving either Ate/Bev or Len as first-line systemic therapy. Patients with prior systemic therapy, inadequate follow-up data, or incomplete treatment records were excluded. Using Ate/Bev or Len was based on the decisions of clinicians and patient`s wishes. Patients who received Len could be reimbursed if they met the criteria of Taiwan NHI including Child-Pugh class A liver function reserve, tumor in Barcelona Clinical Liver Cancer (BCLC) stage C, or tumor in BCLC stage B with TACE refractory [ 14 ]. Concurrent use of Ate/Bev or Len with other treatments is permissible. The study protocol was approved by the Research Ethics Committee of Chang Gung Memorial Hospital (IRB No. 202001701A3). Assessment of Treatment Outcome Treatment response was assessed using radiologic imaging based on the Response Evaluation Criteria in Solid Tumors version 1.1. (RECIST 1.1) [ 15 ]. The ORR was defined as patients achieving complete response (CR) or partial response (PR), while the disease control rate (DCR) was defined as patients achieving CR, PR, or stable disease status (SD). Progression disease (PD) was identified as tumors demonstrating obvious progression during assessment. Assessment of adverse events Termination of Ate/Bev or Len depended upon the occurrence of any unacceptable or serious TRAEs, or upon clinical tumor progression. Following Ate/Bev or Len administration guidelines, dosage adjustments or temporary treatment pauses were implemented if a patient experienced any TRAE of grade 3 or higher severity, or if any unacceptable grade 2 TRAE occurred. TRAEs graded 3 or higher were deemed severe. In the event of a TRAE, dose reductions or temporary treatment pauses were maintained until the TRAE resolved to grade 1 or 2, in accordance with the manufacturer's guidelines. Statistical Analysis Continuous variables were presented as mean ± standard deviation or median with interquartile range, while categorical variables were presented as frequencies and percentages. Differences between groups were analyzed using Student's t-test, Mann-Whitney U test, chi-square test, or Fisher's exact test, as appropriate. Survival outcomes, including PFS and OS, were analyzed using Kaplan-Meier curves and Cox regression models. Propensity-score matching (PSM) analysis was performed using Age, Sex, Alpha-fetoprotein (AFP), Child-Pugh class, Viral etiology, Extrahepatic metastasis (EHM), Macrovascular invasion (MVI) and Maximal tumor size with a 1:2 ratio to reduce the real-life baseline difference between Ate/Bev and Len groups. All enrolled patients were followed up till Dec 2023. All statistical analyses were performed using SPSS 26 software (SPSS Inc., Chicago, IL, USA), and a p-value < 0.05 was considered statistically significant. Results The baseline clinical characteristics The flowchart of enrollment in this study is shown in supplementary Fig. 1. There were 430 patients with unresectable HCC who received Ate/Bev or Len between December 2019 and December 2022. Eighty-four patients were excluded due to receiving other systemic therapies before, having insufficient data, or being lost to follow-up. Therefore, a total of 346 patients including 80 (23.1%) with Ate/Bev and 266 (76.9%) with Len were further assigned to the Ate/Bev group (number, n = 73) and the Len group (n = 142) by using PSM analysis with a 1:2 ratio. Table 1 presents the baseline characteristics of all enrolled patients before and after PSM analysis. Before PSM, the Ate/Bev group were younger (61.6 vs 65.4 years, p = 0.012), showed more Child-Pugh class B (14.1 vs 5.7%, p = 0.014), larger main tumor (58.8 vs 40.2%, p = 0.003), more main portal vein invasion (Vp4) (25% vs. 12.8%, p = 0.008), more treatment termination (93.8 vs 83.8%, 0.024) and fewer concurrent treatments (20 vs 40.6%, p < 0.001) compared with the Len group. After the performance of PSM, the baseline characteristics of the two groups were balanced, except that the proportion of receiving concurrent treatment (21.9 vs 45.8%, p < 0.001) remained lower in the Ate/Bev than in the Len group. In the PSM cohort, the leading four concurrent treatments with Len were mono-immunotherapy as pembrolizumab or nivolumab, radiotherapy, TACE, and proton beam radiotherapy. In the Ate/Bev group, the mostly concurrent treatment was proton beam radiotherapy, followed by TACE and radiotherapy. Table 1 Baseline characteristics of patients receiving Ate/Bev or Len before and after PSM Before PSM After PSM Ate/Bev (n = 80) Len (n = 266) P-value Ate/Bev (n = 73) Len (n = 142) P-value Male sex, n (%) 61 (76.3) 201 (75.6) 0.9 55 (75.3) 103 (72.5) 0.659 Age(years) 61.6 ± 11.6 65.4 ± 11.4 0.012 63.2 ± 10.5 63.2 ± 11.4 0.987 Child-Pugh class A, n (%) 67 (85.9) 249 (94.3) 0.014 64 (87.7) 131 (92.3) 0.273 B, n (%) 11 (14.1) 15 (5.7) 9 (12.3) 11 (7.7) Viral etiology, n (%) 61 (76.3) 199 (74.8) 0.794 55 (75.3) 106 (74.6) 0.911 HBV infection, n(%) 51 (63.7) 137 (51.5) 45 (61.6) 78 (54.9) 0.346 HCV infection, n(%) 14 (17.9) 67 (25.2) 14 (19.2) 31 (21.8) 0.651 ALBI grade 1, n (%) 36 (46.2) 151 (57) 0.178 35 (48.6) 65 (45.8) 0.676 2, n (%) 38 (48.7) 107 (40.4) 33 (45.8) 72 (50.7) 3, n (%) 4 (5.1) 7 (2.6) 4 (5.6) 5 (3.5) BCLC stage, B, n (%) 10 (12.5) 53 (19.9) 0.131 10 (13.7) 17 (12) 0.717 C, n (%) 70 (87.5) 213 (80.1) 63 (86.3) 125 (88) EHM, n(%) 40 (50) 144 (45.9) 0.516 35 (47.9) 65 (45.8) 0.763 MVI, n(%) 44 (55) 117 (44) 0.083 41 (56.2) 74 (52.1) 0.573 Vp4, n(%) 20 (25) 34 (12.8) 0.008 18 (24.7) 24 (16.9) 0.174 Tumor size > 6cm, n(%) 47 (58.8) 107 (40.2) 0.003 43 (58.9) 76 (53.5) 0.578 BMI, kg/m 2 24.5 ± 3.2 24.7 ± 4 0.506 24.4 ± 3.2 24.3 ± 3.6 0.812 AST, IU/L 76.5 ± 48.6 63.6 ± 51.9 0.045 73.4 ± 47.6 73.7 ± 61.6 0.973 ALT, IU/L 51.9 ± 36 52.9 ± 63 0.864 52.6 ± 37.3 59.9 ± 81 0.17 AFP, ng/ml 8802 ± 20738 6753 ± 18331 0.428 7553 ± 21568 7281 ± 18006 0.441 AFP ≥ 400, n(%) 34 (43) 91 (34.2) 0.152 31 (42.5) 56 (39.4) 0.668 NLR 4.5 ± 2.9 3.8 ± 2.5 0.057 4.5 ± 3.0 3.9 ± 2.7 0.181 NLR > 3, N(%) 52 (65) 120 (52.9) 0.06 46 (63) 59 (50) 0.079 PLR 4.6 ± 3.5 3.9 ± 2.6 0.228 189.5 ± 119 169.9 ± 99 0.243 PLR > 230, N(%) 25 (45.5) 42 (38.9) 0.421 16 (21.9) 26 (22.2) 0.961 Concurrent treatment, n(%) 16 (20) 108 (40.6) 0.001 16 (21.9) 65 (45.8) 0.001 Pembrolizumab /Nivolumab 0 17 / 8 0 12 / 5 Radiotherapy 2 23 2 16 TACE 4 19 4 8 Proton bean radiotherapy 9 18 9 12 Post treatment, n(%) 43 (53.8) 107 (46.9) 0.294 40 (54.8) 54 (43.9) 0.14 Treatment stop, n(%) 75 (93.8) 223 (83.8) 0.024 68 (93.2) 120 (84.5) 0.07 Abbreviations: AFP, alpha-fetoprotein; ALBI grade, albumin-bilirubin grade; ALT, alanine aminotransferase; AST aspartate transaminase; Ate/Bev: Atezolizumab plus Bevacizumab; BCLC stage, Barcelona Clinic Liver Cancer stage; BMI, body mass index; EHM, extra-hepatic metastasis; Len, Lenvatinib; NLR, neutrophil lymphocyte ratio; PLR, platelet lymphocyte ratio; PSM, propensity score matching; TACE, trans-arterial chemoembolization; Vp4, main portal vein invasion or bilateral portal vein invasion. Treatment response of patients before and after PSM Treatment response was assessed via those patients who received following CT or MRI imaging (Table 2 ). Before PSM, the ORR was compatible between the Ate/Bev and Len group (20% vs 20.3%); however, patients in the Len group had a superior DCR (72 vs 55.7%, p = 0.004). After PSM, there were no statistically significant differences between the Ate/Bev and Len groups regarding CR, PR, SD, PD, DCR, and death. However, a trend was observed indicating a better DCR in the Len group. Table 2 Treatment response of patients receiving Ate/Bev or Len before and after PSM Before PSM After PSM Variables Ate/Bev (n = 80) Len (n = 266) P-value Ate/Bev (n = 73) Len (n = 142) P-value Treatment response evaluation, n(%) † 70 (82.1) 225 (89.3) 64 (87.7) 116 (81.7) Complete Response, n(%) 2 (2.9) 15 (6.7) 0.069 2 (3.1) 6 (5.2) 0.245 Partial Response, n(%) 12 (17.1) 31 (13.8) 12 (18.8) 19 (16.4) Stable Disease, n(%) 25 (35.7) 116 (51.6) 23 (35.9) 57 (49.1) Progression Disease, n(%) 31 (44.3) 63 (28) 27 (42.2) 34 (29.3) Objective Response Rate 20% 20.5% 0.923 21.9% 21.6% 0.983 Disease Control Rate‡ 55.7% 72% 0.004 57.8% 70.7% 0.062 Death, n(%) 44 (55) 122 (45.9) 0.152 41 (56.2) 70 (49.3) 0.34 Abbreviations: Ate/Bev: Atezolizumab plus Bevacizumab; Len, Lenvatinib; PSM, propensity score matching. †Treatment response based on those who received image evaluation including Computer tomography or Magnetic resonance image. Table 3 Treatment related adverse events of patients receiving Ate/Bev or Len before and after PSM Before PSM After PSM Ate/Bev (n = 80) Len (n = 266) Ate/Bev (n = 73) Len (n = 142) Variables Any, n (%) Grade ≥ 3, n (%) Any, n (%) Grade ≥ 3, n (%) Any, n (%) Grade ≥ 3, n (%) Any, n (%) Grade ≥ 3, n (%) Total TRAE 45 (56.3) 5 (6.3) 185 (72) 24 (9.6) 41 (56.2) 5 (7) 96 (71.1) 13 (9.1) Fatigue, n (%) 20 (25) 1 (1.3) 64 (25.6) 11 (4.4) 20 (28) 1 (1.4) 31 (21.7) 5 (3.5) HFSR, n (%) 0 0 59 (23.6) 5 (2) 0 0 32 (22.4) 3 (2.1) Diarrhea, n (%) 3 () 0 36 (14.4) 0 1 (1.4) 0 20 (14) 0 Hypertension, n (%) 1 () 0 26 (10.4) 1 (0.4) 1 (1.4) 0 9 (6.3) 0 Poor appetite, n (%) 15 (18.8) 0 26 (10.4) 1 (0.4) 8 (11.2) 0 7 (4.9) 0 Dysphonia, n (%) 0 0 14 (5.6) 0 0 0 8 (5.6) 0 Dermatitis, n (%) 9 (11.3) 0 13 (5.2) 0 8 (11.2) 0 6 (4.2) 0 Proteinuria, n (%) 1 (1.3) 0 11 (4.4) 0 1 (1.4) 0 5 (3.5) 0 Encephalopathy, n(%) 2 (2.5) 0 6 (2.4) 3 (1.2) 2 (2.8) 0 2 (1.4) 2 (1.4) Elevated bilirubin, n (%) 2 (2.5) 2 (2.5) 5 (2) 0 2 (2.8) 2 (2.8) 3 (2.1) 0 UGI bleeding, n(%) 3 (3.8) 1 (1.3) 3 (1.2) 2 (0.8) 2 (2.8) 1 (1.4) 3 (2.1) 2 (1.4) Hepatitis, n (%) 0 0 1 (0.4) 1 (0.4) 0 0 1 (0.7) 1 (0.7) Seizure, n(%) 1 (1.3) 1 (1.3) 0 0 1(1.4) 1(1.4) 0 0 Abbreviations: Ate/Bev: Atezolizumab plus Bevacizumab; HFSR, hand foot skin reaction; Len, Lenvatinib; PSM, propensity score matching; TRAE, treatment related adverse event; UGI bleeding, upper gastrointestinal bleeding. * The comparison of any TRAE between two groups was 0.008 (Before PSM) and 0.03(After PSM). Treatment Related Adverse Events before and after PSM Before (56.3 vs 72%, p = 0.008) and after PSM (56.2 vs 71.1%, p = 0.03), the Ate/Bev group both experienced a lower proportion of total TRAE than the Len group (Table 4 ). However, the occurrence rate of severer TRAE (≥ grade 3) between the two groups was similar. After PSM, the most reported TRAE in the Len group was hand-foot skin reaction, with a total of 32 patients (22.4%), followed by with fatigue with 31 patients (21.7%), and diarrhea with 20 patients (14%). In the Ate/Bev group, 56.2% of patients had incidence of total TRAE, where the incidence over 10% included 28% of patients with fatigue, 11.2% with dermatitis, and 11.2% with decreased appetite. Only 5 patients (7%) in the Ate/Bev group experienced severe TRAE needed to stop treatment. Table 4 Factors associated with Progression Free Survival in the PSM cohort Univariate analysis Multivariate analysis Variable Comparison H.R. 95% CI p-value H.R. 95% CI p-value Age, years Increase per year 0.994 0.98–1.009 0.446 Sex Female vs. Male 0.916 0.624–1.344 0.653 Child-Pugh class B vs A 1.495 0.805–2.799 0.203 Etiology Viral vs non viral 1.166 0.774–1.756 0.464 BCLC stage C vs B 1.701 0.977–2.961 0.061 EHM Yes vs No 0.855 0.611–1.196 0.360 MVI Yes vs No 1.623 1.159–2.277 0.005 1.637 1.168–2.294 0.004 Tumor size, cm > 6 vs ≦ 6 1.443 1.027–2.028 0.034 AFP, ng/ml > 400 vs ≦ 400 1.674 1.195–2.344 0.003 1.718 1.225–2.411 0.002 Concurrent treatment Yes vs No 0.649 0.461–0.914 0.013 0.6 0.425–0.847 0.004 Treatment option Ate/Bev vs Len 1.052 0.733–1.511 0.783 Abbreviations: AFP, alpha-fetoprotein; Ate/Bev: Atezolizumab plus Bevacizumab; BCLC stage, Barcelona Clinic Liver Cancer stage; EHM, extra-hepatic metastasis; Len, Lenvatinib; PSM, propensity score matching. PFS and its predicting factors Kaplan-Meier curves of PFS were 3.7 months in the Ate/Bev group and 6.8 months in the Len group, respectively (Fig. 1 A). Although the Len group seemed to have a better PFS, but the comparison was insignificant. After PSM, the Len group had a longer PFS than the Ate/Bev group (6 vs 5.1 months, p = 0.783), but there was no difference (Fig. 1 B). In Cox regression model of multivariate analyses, more microvascular invasion, higher AFP level, and fewer concurrent treatment were independent risk factors associated with PFS in the PSM cohort (Table 4 ). Different treatment agents using Ate/Bev or Len did not contribute to PFS, whether for univariate or multivariate analysis. OS and its predicting factors Comparing OS, the Ate/Bev group had a median of 10.4 months, while the Len group had 16.6 months, but there was no significant difference between the two groups (P = 0.158) (Fig. 1 (C)). After PSM, the OS in the Ate/Bev group was 13.3 months, compared to 14.1 months in the Len group, still showing a statistically insignificant (P = 0.945) (Fig. 1 (D)). In the multivariate analysis, after adjusting for other variables, non-viral etiology, higher AFP level, larger main tumor size, no concurrent treatment and no sequential post-treatment were associated with poor outcome in the PSM cohort (Table 5 ). Different treatment agents using Ate/Bev or Len did not contribute to OS, whether for univariate or multivariate analysis. Table 5 Factors associated with Overall Survival in the PSM cohort Univariate analysis Multivariate analysis Variable Comparison H.R. 95% CI p-value H.R. 95% CI p-value Age, years Increase per year 1.005 0.988–1.023 0.537 Sex Female vs. Male 0.859 0.561–1.314 0.483 Child-Pugh class B vs A 2.76 1.592–4.784 < 0.001 Etiology Viral vs non viral 0.58 0.386–0.869 0.008 0.448 0.295–0.681 6 vs ≦ 6 1.888 1.277–2.792 0.001 1.809 1.208–2.710 0.004 AFP, ng/ml > 400 vs ≦ 400 1.941 1.335–2.823 0.001 2.063 1.396–3.048 < 0.001 Concurrent treatment Yes vs No 0.411 0.269–0.629 < 0.001 0.362 0.235–0.557 < 0.001 Post treatment Yes vs No 0.43 0.293–0.631 < 0.001 0.437 0.297–0.644 < 0.001 Treatment option Ate/Bev vs Len 0.986 0.666–1.461 0.945 Abbreviations: AFP, alpha-fetoprotein; Ate/Bev: Atezolizumab plus Bevacizumab; BCLC stage, Barcelona Clinic Liver Cancer stage; EHM, extra-hepatic metastasis; Len, Lenvatinib; PSM, propensity score matching. Subgroup Analysis for PFS and OS after PSM After PSM, the subgroup analysis indicated that using Ate/Bev was equal to using Len associated with PFS in all subgroups before PSM (Supplementary Fig. 2) and after PSM (Fig. 2 ). Similarly, there were still no difference in all subgroups regarding the OS in using first line Ate/Bev or Len before PSM (Supplementary Fig. 3) and after PSM (Fig. 3 ). Although non-viral patients who preferred Len over Ate/Bev tended to experience better OS (HR: 0.50, 95% CI: 0.27–0.93, p = 0.028), this comparison became insignificant after PSM (HR: 0.55, 95% CI: 0.27–1.09, p = 0.087). Sequential treatments following Ate/Bev or Len after PSM After cessation of first line treatment, 40 patients (54.8%) in the Ate/Bev group and 54 (43.9%) in the Len group still afforded following therapies (Table 6 ). Concerning sequential systemic treatments, the Ate/Bev group had a higher proportion than the Len group (45.2 vs 24.6%, p = 0.009). A total of 30 patients (90.9%) received TKI after failure of Ate/Bev, 3 patients used sorafenib whereas 27 patients took Len-based therapies including 14 for Len, 9 for Len plus pembrolizumab, 3 for Len plus chemotherapy, and 2 for Len plus nivolumab. In the Len group, most patients decided chemotherapy or immunotherapy as the second line treatment. The most frequently used agent was chemotherapy for 13 patients, followed by Ate/Bev for 9, and nivolumab for 9. Table 6 Sequential treatments after failure of Ate/Bev or Len in the PSM cohort Variables Ate/Bev (n = 73) Len (n = 142) P-value Treatment Stop, n (%) 68 (93.2) 120 (84.5) 0.07 Post-treatment, n (%) 40 (54.8) 54 (43.9) 0.14 2nd-line systemic treatments, n (%) 33 (45.2) 35 (24.6) 0.009 Len 14 2 Len plus Pembrolizumab 9 0 Len plus Nivolumab 2 0 Len plus Chemotherapy 3 0 Chemotherapy 1 13 Ate/Bev 0 9 Nivolumab plus Ipilizumab 1 1 Nivolumab 0 9 Sorafenib 3 0 Thalidomide 0 1 Abbreviations: Ate/Bev: Atezolizumab plus Bevacizumab; Len, Lenvatinib; PSM, propensity score matching. Discussion Ate/Bev has been recommended as the first choice of treatment option for patients with advanced HCCs by current international guidelines based on the IMbrave 150 clinical trial [ 2 ], which demonstrated that Ate/Bev can achieve a benefit in OS (19.2 vs. 13.4 months; p < 0.001) and PFS (6.9 vs. 4.3 months; p < 0.001) compared to sorafenib. Len, another effective TKI, showed non-inferior treatment efficacy to sorafenib in the clinical trial [ 5 ], and even demonstrates better treatment outcomes and responses than sorafenib in real-life practices [ 16 – 18 ]. Although current HCC guidelines suggest Len should be considered as a first-line treatment if Ate/Bev is unsuitable or as a second-line treatment following Ate/Bev [ 19 , 20 ], there have been no head-to-head comparisons between these two agents. Some studies have attempted to clarify this issue in real-world settings; however, the results have been controversial. Even meta-analyses have not reached a consistent conclusion. Changez et al. showed that Ate/Bev provides a potential advantage in efficacy and better safety than Len in the treatment of unresectable HCC via ten cohorts including 6493 patients [ 21 ], whereas Lu et al. reported that the Len group had longer OS and PFS than the Ate/Bev group via seven eligible studies involving 4428 patients [ 22 ]. This suggests that Len might provide treatment benefits equal to those of Ate/Bev for patients with unresectable HCC. Additionally, the high price of Ate/Bev limits its common application in real-life practice, particularly in Taiwan where our NHI didn’t cover this agent before August 2023. Consequently, TKIs such as sorafenib or Len usually serve as the first-line treatment choice for patients with unresectable HCC in real-world practice. In Taiwan, Len has been reimbursed by the insurance since January 2020. The current study observes the treatment outcomes between Len and Ate/Bev in the era of different insurance coverage in Taiwan. Compared to the Len group, patients who opted for self-paid Ate/Bev showed more locally advanced tumor patterns, larger tumor burdens, and poorer liver function at baseline. These are common contributing factors to a poor treatment prognosis. On the contrary, most patients in the Len group received Len under the reimbursed criteria of NHI, with good liver function and consistent tumor patterns. The Ate/Bev group had a comparable ORR (20% vs. 20.3%) but an inferior DCR (55.7% vs. 27%, p = 0.004) compared to the Len group. After PSM, there were no statistically significant differences between the Ate/Bev and Len groups regarding ORR, DCR, and death. Additionally, the PFS of the Ate/Bev group was shorter than that of the Len group, though the difference was not statistically significant (3.7 months vs. 6.8 months, p = 0.292). After PSM, the Len group still had a longer PFS than the Ate/Bev group (6 months vs. 5.1 months, p = 0.783), but the difference was not significant. Regarding OS, the Ate/Bev group also had poorer survival compared to the Len group, but the difference was not significant (10.4 months vs. 16.6 months, p = 0.158). After PSM, the OS of the two groups was more similar (13.3 months for the Ate/Bev group and 14.1 months for the Len group). We found that our patients who received self-paid Ate/Bev seemed to have poorer PFS and OS compared to the clinical trials and showed a worse trend in survival compared to patients who received reimbursed Len. This may be due to these patients having more advanced tumor patterns and poorer liver function than those enrolled in clinical trials. Additionally, the observation period from the beginning of Ate/Bev treatment to the first image evaluation was significantly shorter than in the clinical trials due to the high cost of this agent. Most patients received their first image evaluation after only two to three administrations, which might lead to an underestimate of PFS. Moreover, previous studies indicated that delayed immune treatment response sometimes occurs after image pseudo-progression in HCC treatment [ 23 , 24 ]. Insufficient drug exposure could result in a suboptimal treatment response and worse treatment outcomes. Recent meta-analysis has demonstrated that patients receiving Ate/Bev exhibited lower incidences of grade 3/4 adverse events compared to those receiving Len (p = 0.003) [ 13 ]. The present study also observed that the Ate/Bev group experienced a lower proportion of TRAEs than the Len group, both before (56.3% vs. 72%, p = 0.008) and after PSM (56.2% vs. 71.1%, p = 0.03). However, the occurrence rate of severe TRAEs (≥ grade 3) between the two groups was similar. Following PSM, the most frequently reported TRAE in the Len group was hand-foot skin reaction, affecting a total of 32 patients (22.4%), followed by fatigue in 31 patients (21.7%), and diarrhea in 20 patients (14%). In the Ate/Bev group, 56.2% of patients experienced total TRAEs, with incidences exceeding 10% including fatigue in 28% of patients, dermatitis in 11.2%, and decreased appetite in 11.2%. Only 5 patients (7%) in the Ate/Bev group experienced severe TRAEs necessitating treatment discontinuation. The current study also indicated that concurrent treatment was a significant contributing factor to treatment prognosis, both in univariate and multivariate analyses. In real-world practice, clinicians often combine locoregional therapies with systemic treatments to enhance treatment response [ 25 , 26 ]. Patients receiving concurrent treatment had superior PFS (9.3 vs. 3.4 months, p = 0.012) and OS (19.2 vs. 8.9 months, p < 0.001) compared to those who did not combine treatments. We observed that patients reimbursed for Len received more concurrent therapies than those self-paying for Ate/Bev (45.9% vs. 21.8%, p = 0.001). In the PSM cohort, the most common concurrent treatments with Len were mono-immunotherapy with pembrolizumab or nivolumab, radiotherapy, TACE, and proton beam radiotherapy. In the Ate/Bev group, the predominant concurrent treatment was proton beam radiotherapy, followed by TACE and radiotherapy. Len combined with pembrolizumab, a combination of TKI plus immunotherapy, had been a popular treatment option for patients with advanced HCC based on a phase Ib clinical trial [ 27 ]. Although this combination did not demonstrate superiority to Len monotherapy in phase III results [ 28 ], many patients still derived survival benefits from this combination in real-world practice. Yang et al. reported that Len plus PD-1 inhibitor treatment resulted in a longer OS of 17.8 months and a notable ORR of 19.6% and DCR of 73.5% in unresectable HCC patients [ 29 ]. The current study also observed that patients combining Len with pembrolizumab or nivolumab achieved excellent OS of 18.5 months. In multivariate analysis, post-treatment emerged as a significant factor in reducing mortality risk for patients receiving first-line Ate/Bev or Len. Patients who underwent post-treatment experienced significantly better OS compared to those who did not (17.2 vs. 6.6 months, p < 0.001). Following cessation of first-line treatment, 40 patients (54.8%) in the Ate/Bev group and 54 (43.9%) in the Len group continued to receive subsequent therapies. Regarding sequential systemic treatments, a higher proportion of patients in the Ate/Bev group received them compared to the Len group (45.2% vs. 24.6%, p = 0.009). Of the patients who failed Ate/Bev, 90.9% received TKI therapy, 3 patients received sorafenib, and 27 patients received Len-based therapies, including 14 for Len alone, 9 for Len plus pembrolizumab, 3 for Len plus chemotherapy, and 2 for Len plus nivolumab. In the Len group, most patients opted for chemotherapy or immunotherapy as second-line treatment. Chemotherapy was the most frequently chosen agent for 13 patients, followed by Ate/Bev for 9, and nivolumab for 9. It appears that the primary consideration in selecting sequential treatment was to explore a different mechanism from the failed first-line agent. Unlike previous studies, the current study found no association between the use of Ate/Bev or Len and PFS across all subgroups. Similarly, there were no differences observed in OS among all subgroups receiving first-line Ate/Bev or Len. Some studies have suggested that non-viral patients, particularly those with non-alcoholic fatty liver disease, might exhibit poorer treatment responses to Ate/Bev compared to viral patients [ 11 , 13 , 30 ]. Our study also observed that non-viral patients who preferred Len over Ate/Bev tended to experience better OS (HR: 0.50, 95% CI: 0.27–0.93, p = 0.028). However, this comparison became insignificant after PSM (HR: 0.55, 95% CI: 0.27–1.09, p = 0.087). A larger study cohort might be necessary to elucidate this issue further in clinical practice. The current study has several limitations. Firstly, the differential NHI-reimbursed status for Ate/Bev and Len introduces the risk of selection bias and confounding factors that could influence treatment outcomes. Although we utilized PSM to address these biases, residual confounding may still be present. Since both regimens have been reimbursed by the Taiwan NHI program since August 2023, further studies are needed to compare Ate/Bev and Len under more consistent baseline clinical characteristics. Secondly, the relatively small sample size and single-center nature of the study may restrict the generalizability of our findings to broader populations. Larger multicenter studies are necessary to validate our results and provide more robust evidence. Thirdly, the absence of long-term follow-up data may obscure the impact of treatment on survival outcomes beyond the study period. Future studies with extended follow-up durations are required to evaluate the durability of treatment responses and long-term survival benefits. Conclusion In summary, our study offers valuable insights into the comparative effectiveness of Health Insurance-Guided First-Line Len and self-paid Ate/Bev in patients with unresectable HCC. Despite initial differences in baseline characteristics, both treatment regimens demonstrated comparable treatment responses and survival outcomes. These findings highlight the significance of individualized treatment decisions tailored to patient-specific factors. Further research is warranted to optimize first-line treatment strategies for Len or Ate/Bev under consistent reimbursement criteria from the NHI. Abbreviations AFP, alpha-fetoprotein; ALBI grade, albumin-bilirubin grade; ALT, alanine aminotransferase; AST, aspartate transaminase; Ate/Bev, atezolizumab plus bevacizumab; BCLC stage, Barcelona clinic liver cancer stage; CR, complete response; DCR, disease control rate; EHM, extra-hepatic metastasis; HCC, hepatocellular carcinoma; Len, lenvatinib; MVI, microvascular invasion; NHI, national health insurance; ORR, objective response rates; OS, overall survival; PD, progression disease; PD-L1, anti-programmed death-ligand 1; PFS, progression-free survival; PSM, propensity score matching; PR, partial response; RFA, radio-frequency ablation; SD, stable disease; TACE, Trans-Arterial Chemoembolization; TKI, tyrosine kinase inhibitor; TRAEs, treatment-related adverse events; uHCC, unresectable hepatocellular carcinoma; VEGF, vascular endothelial growth factor. Declarations Acknowledgements The authors would like to thank Miss Nien-Tzu Hsu and the biostatistics center of Kaohsiung Chang Gung Memorial Hospital for excellent statistics works. Funding: This study was funded from Chang Gung Memorial Hospital (CMRPG8L0291) to Prof. Yuan-Hung Kuo. Conflict of interest: Yuan-Hung Kuo, Wei-Chen Tai, Yen-Hao Chen, Ming-Chao Tsai, Sheng-Nan Lu, Tsung-Hui Hu, Chao-Hung Hung, Chien-Hung Chen, and Jing-Houng Wang declare that they have no conflict of interest. Ethics approval: All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (Chang Gung Memorial Hospital (IRB No. 202001701A3) and with the Helsinki Declaration of 1975, as revised in 2008. Informed consent was obtained from all patients for being included in the study. Informed Consent Statement: The Institutional Review Board of Chang Gung Medical Foundation waived the requirement of written informed consent. Consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and material (data transparency): Not applicable. Code availability (software application or custom code): Not applicable. Clinical Trials Registration: Not applicable. Author Contributions: Conceptualization and study design: Yuan-Hung Kuo and Jing-Houng Wang; Analysis and interpretation of the data: Yuan-Hung Kuo; Writing original draft: Yuan-Hung Kuo; Data acquisition: Yuan-Hung Kuo, Wei-Chen Tai; Yen-Hao Chen, Ming-Chao Tsai, Sheng-Nan Lu, Tsung-Hui Hu, Chao-Hung Hung, Chien-Hung Chen; Jing-Houng Wang, Supervision: Jing-Houng Wang. All authors read and approved the final manuscript. References Cappuyns S, Corbett V, Yarchoan M, Finn RS, Llovet JM. Critical Appraisal of Guideline Recommendations on Systemic Therapies for Advanced Hepatocellular Carcinoma. Rev JAMA Oncol. 2024;10(3):395–404. Finn RS, Qin S, Ikeda M, et al. Atezolizumab plus bevacizumab in unresectable hepatocellular carcinoma. N Engl J Med. 2020;382(20):1894–905. Cheng AL, Qin S, Ikeda M, et al. Updated efficacy and safety data from IMbrave150: Atezolizumab plus bevacizumab vs. sorafenib for unresectable hepatocellular carcinoma. J Hepatol. 2022;76(4):862–73. Cappuyns S, Corbett V, Yarchoan M, Finn RS, Llovet JM. Critical Appraisal of Guideline Recommendations on Systemic Therapies for Advanced Hepatocellular Carcinoma: A Review. JAMA Oncol. 2024;10(3):395–404. Kudo M, Finn RS, Qin S, et al. Lenvatinib versus sorafenib in first-line treatment of patients with unresectable hepatocellular carcinoma: a randomised phase 3 non-inferiority trial. Lancet. 2018;391(10126):1163–73. Kuo YH, Lu SN, Chen YY, et al. Real-World Lenvatinib Versus Sorafenib in Patients With Advanced Hepatocellular Carcinoma: A Propensity Score Matching Analysis. Front Oncol. 2021;11:737767. Hsiao YW, Sou FM, Wang JH, et al. Well-controlled viremia reduces the progression of hepatocellular carcinoma in chronic viral hepatitis patients treated with lenvatinib. Kaohsiung J Med Sci. 2023;39(12):1233–42. Kudo M, Finn RS, Qin S, et al. Overall survival and objective response in advanced unresectable hepatocellular carcinoma: A subanalysis of the REFLECT study. J Hepatol. 2023;78(1):133–41. Casadei-Gardini A, Rimini M, Kudo M, et al. Real Life Study of Lenvatinib Therapy for Hepatocellular Carcinoma: RELEVANT Study. Liver Cancer. 2022;11(6):527–39. Su CW, Teng W, Lin PT, et al. Similar efficacy and safety between lenvatinib versus atezolizumab plus bevacizumab as the first-line treatment for unresectable hepatocellular carcinoma. Cancer Med. 2023;12(6):7077–89. Casadei-Gardini A, Rimini M, Tada T, et al. Atezolizumab plus bevacizumab versus lenvatinib for unresectable hepatocellular carcinoma: a large real-life worldwide population. Eur J Cancer. 2023;180:9–20. Hiraoka A, Kumada T, Tada T, et al. Does first-line treatment have prognostic impact for unresectable HCC? Atezolizumab plus bevacizumab versus lenvatinib. Real-life Practice Experts for HCC (RELPEC) Study Group and HCC 48 Group (hepatocellular carcinoma experts from 48 clinics in Japan). Cancer Med. 2023;12(1):325–34. Liu J, Yang L, Wei S, Li J, Yi PJ. Efficacy and safety of atezolizumab plus bevacizumab versus lenvatinib for unresectable hepatocellular carcinoma: a systematic review and meta-analysis. Cancer Res Clin Oncol. 2023;149(17):16191–201. The Reimbursement Criteria of Hepatocellular Carcinoma Treatment. Ministry of Health and Welfare, ROC: The National Health Insurance Administration. May 2024 update. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228–47. Ding X, Sun W, Li W, et al. Transarterial chemoembolization plus lenvatinib versus transarterial chemoembolization plus sorafenib as first-line treatment for hepatocellular carcinoma with portal vein tumor thrombus: A prospective randomized study. Cancer. 2021;127(20):3782–93. Lee SW, Yang SS, Lien HC, Peng YC, Ko CW, Lee TY. Efficacy of Lenvatinib and Sorafenib in the Real-World First-Line Treatment of Advanced-Stage Hepatocellular Carcinoma in a Taiwanese Population. J Clin Med. 2022;11(5):1444. Park MK, Lee YB, Moon H, et al. Effectiveness of Lenvatinib Versus Sorafenib for Unresectable Hepatocellular Carcinoma in Patients with Hepatic Decompensation. Dig Dis Sci. 2022;67(10):4939–49. Cho Y, Kim BH, Park JW. Overview of Asian clinical practice guidelines for the management of hepatocellular carcinoma: An Asian perspective comparison. Clin Mol Hepatol. 2023;29(2):252–62. Reig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. J Hepatol. 2022;76(3):681–93. Changez MIK, Khan M, Uzair M, et al. Efficacy of Atezolizumab Plus Bevacizumab Versus Lenvatinib in Patients with Unresectable Hepatocellular Carcinoma: a Meta-analysis. J Gastrointest Cancer. 2024;55(1):467–81. Lu J, Lin X, Teng H, Zheng Y. Atezolizumab Plus Bevacizumab Versus Lenvatinib for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. J Clin Pharmacol. 2024;64(6):643–51. Odagiri N, Tamori A, Kotani K, et al. A case of hepatocellular carcinoma with pseudoprogression followed by complete response to atezolizumab plus bevacizumab. Clin J Gastroenterol. 2023;16(3):392–6. Otake S, Ota Y, Aso K, et al. Contrast-enhanced Ultrasonography Features for Diagnosing Pseudoprogression of Hepatocellular Carcinoma with Immunotherapy: A Case Report of the Response after Pseudoprogression. Intern Med. 2024;63(8):1093–7. Zhao C, Xiang Z, Li M, et al. Transarterial Chemoembolization Combined with Atezolizumab Plus Bevacizumab or Lenvatinib for Unresectable Hepatocellular Carcinoma: A Propensity Score Matched Study. J Hepatocell Carcinoma. 2023;10:1195–206. Su CW, Teng W, Shen EY, et al. Concurrent Atezolizumab Plus Bevacizumab and High-Dose External Beam Radiotherapy for Highly Advanced Hepatocellular Carcinoma. Oncologist. 2024 Mar;26:oyae048. Finn RS, Ikeda M, Zhu AX, et al. Phase Ib Study of Lenvatinib Plus Pembrolizumab in Patients With Unresectable Hepatocellular Carcinoma. J Clin Oncol. 2020;38(26):2960–70. Llovet JM, Kudo M, Merle P, et al. Lenvatinib plus pembrolizumab versus lenvatinib plus placebo for advanced hepatocellular carcinoma (LEAP-002): a randomised, double-blind, phase 3 trial. Lancet Oncol. 2023;24(12):1399–410. Yang X, Chen B, Wang Y, et al. Real-world efficacy and prognostic factors of lenvatinib plus PD-1 inhibitors in 378 unresectable hepatocellular carcinoma patients. Hepatol Int. 2023;17(3):709–19. Rimini M, Rimassa L, Ueshima K, et al. Atezolizumab plus bevacizumab versus lenvatinib or sorafenib in non-viral unresectable hepatocellular carcinoma: an international propensity score matching analysis. ESMO Open. 2022;7(6):100591. Supplementary Files SupplementaryFig1.tiff Supplementary Figure 1. Flow chart of the study population. SupplementaryFig2.tiff Supplementary Figure 2. Forest plots of Progression-Free Survival in the subgroups of the Ate/Bev and Len groups before propensity score matching SupplementaryFig3.tiff Supplementary Figure 3. Forest plots of Overall Survival in the subgroups of the Ate/Bev and Len groups before propensity score matching Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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15:04:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4522670/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4522670/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59215591,"identity":"3dd1092c-c85f-433b-86a1-49ffef8a53c3","added_by":"auto","created_at":"2024-06-27 18:59:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1176853,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curves for (A) Progression-free survival (PFS) of the Ate/Bev and Len groups (B) PFS of the Ate/Bev and Len groups after propensity score matching (PSM) (C) Overall survival (OS) of the Ate/Bev and Len groups (D) OS of the Ate/Bev and Len groups after PSM.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4522670/v1/cd7b8aec7ffeb7ffb2f32d65.png"},{"id":59215594,"identity":"b30f2113-ae82-47c3-9c7a-395f5a6e2c16","added_by":"auto","created_at":"2024-06-27 18:59:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1547592,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of Progression-Free Survival in the subgroups of the Ate/Bev and Len groups after propensity score matching\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4522670/v1/55c1ca0cc6046905a0d8391d.png"},{"id":59215593,"identity":"bcfb4f85-e8af-4303-a29d-594a6b170fff","added_by":"auto","created_at":"2024-06-27 18:59:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1658826,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of Overall Survival in the subgroups of the Ate/Bev and Len groups after propensity score matching\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4522670/v1/db571d5f3a53614f3dc3c9e2.png"},{"id":59217504,"identity":"72864d67-1557-47ce-a94a-7126a944fe83","added_by":"auto","created_at":"2024-06-27 19:23:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5056354,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4522670/v1/60ea16f4-fe3d-45c0-aea0-4ba557b7f8e9.pdf"},{"id":59215592,"identity":"9af086bb-d712-4a3b-9802-4f8ea7f510dc","added_by":"auto","created_at":"2024-06-27 18:59:14","extension":"tiff","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1169862,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1.\u003c/strong\u003e Flow chart of the study population.\u003c/p\u003e","description":"","filename":"SupplementaryFig1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-4522670/v1/90b143dd5986d4b2043641ae.tiff"},{"id":59215596,"identity":"b9a23c63-905b-48be-a458-4a84a7fe5983","added_by":"auto","created_at":"2024-06-27 18:59:15","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3125588,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 2. \u003c/strong\u003eForest plots of Progression-Free Survival in the subgroups of the Ate/Bev and Len groups before propensity score matching\u003c/p\u003e","description":"","filename":"SupplementaryFig2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-4522670/v1/3ce90995b30491253c0c638f.tiff"},{"id":59215597,"identity":"fd45bfe8-3357-4421-af4b-6acff6f71d4d","added_by":"auto","created_at":"2024-06-27 18:59:15","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3267194,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 3.\u003c/strong\u003e Forest plots of Overall Survival in the subgroups of the Ate/Bev and Len groups before propensity score matching\u003c/p\u003e","description":"","filename":"SupplementaryFig3.tiff","url":"https://assets-eu.researchsquare.com/files/rs-4522670/v1/007e79ead07bd2bc2a4bc7ed.tiff"}],"financialInterests":"","formattedTitle":"Comparing Health Insurance-ReimbursedFirst Line Lenvatinib and Self-paid Atezolizumab plus Bevacizumab in Patients with Unresectable Hepatocellular Carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUnresectable hepatocellular carcinoma (HCC) represents a formidable challenge in clinical oncology, necessitating the exploration of diverse therapeutic strategies to improve patient outcomes. In recent years, the advent of immune checkpoint inhibitors (ICIs) and targeted therapies has transformed the treatment landscape for advanced HCC [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Atezolizumab, an immune checkpoint inhibitor targeting programmed death-ligand 1 (PD-L1), in combination with Bevacizumab, an anti-vascular endothelial growth factor (VEGF) monoclonal antibody, has demonstrated promising efficacy and safety in clinical trials [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The IMbrave150 trial, a landmark phase III study, established atezolizumab plus bevacizumab (Ate/Bev) as a new standard of care for unresectable HCC, showing a superior overall survival (OS) of 19.2 months compared to 13.4 months in patients receiving sorafenib (hazard ratio (HR): 0.66, p\u0026thinsp;=\u0026thinsp;0.0009), the previous standard first-line therapy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Lenvatinib (Len), a multitargeted tyrosine kinase inhibitor (TKI), has also emerged as a frontline treatment option for unresectable HCC [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The REFLECT trial demonstrated non-inferiority of Len compared to sorafenib in terms of OS (median 13.6 versus 12.3 months, respectively), with favorable objective response rates (ORR) and progression-free survival (PFS) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Subsequent real-world studies have corroborated the efficacy and safety of Len in routine clinical practice, highlighting its role as a valuable therapeutic option for patients with advanced HCC [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the comparative effectiveness and safety of Ate/Bev versus Len in randomised controlled trial remains lack. Several real-world studies have evaluated the clinical outcomes of these two regimens in patients with unresectable HCC [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. For instance, a single institute study from Taiwan indicated that there was no significant difference in ORR, PFS, and OS between the Len and Ate/Bev groups [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Similarly, a large real-life worldwide analysis also reported that Ate/Bev did not show a survival advantage over Len (HR: 0.97 (p\u0026thinsp;=\u0026thinsp;0.739)). [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The study reported comparable OS but lower rates of treatment-related adverse events (TRAEs) with the immunotherapy combination compared to Len.\u003c/p\u003e \u003cp\u003eHowever, another multicenter retrospective study from Japan investigated the real-world effectiveness of Ate/Bev versus Len in patients with unresectable HCC across multiple institutions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The findings suggested Ate/Bev group showed better PFS (0.5-/1-/1.5-years: 56.6%/31.6%/non-estimable vs. 48.6%/20.4%/11.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and OS rates (0.5-/1-/1.5-years: 89.6%/67.2%/58.1% vs. 77.8%/66.2%/52.7%, p\u0026thinsp;=\u0026thinsp;0.002) than the Len group. These varieties of survival analyses between Ate/Bev and Len might be due to different studied population. A recent meta-analysis enrolling 8 real-world studies indicated that the Ate/Bev group had significant longer PFS, compared with Len group but no significant difference in OS, ORR and disease control rate (DCR) among them [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Moreover, patients receiving Ate/Bev exhibited lower incidences of grade 3/4 AEs than those receiving Len.\u003c/p\u003e \u003cp\u003eThrough an in-depth analysis of these real-world comparisons and ongoing prospective trials, we aim to enhance our understanding of the relative effectiveness and safety profiles of Ate/Bev and Len, particularly within the distinct reimbursement framework of health insurance for these agents in Taiwan. Notably, Len has been reimbursed by Taiwan's National Health Insurance (NHI) since Jan 2020, while Ate/Bev has been covered since August 2023 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Consequently, this study was undertaken to investigate the comparative efficacy and safety of Ate/Bev versus Len as first-line treatments for patients with unresectable HCC under different reimbursement statuses of National Health Insurance in real-world. \u003c/p\u003e"},{"header":"Materials and Methods","content":"\n\u003ch3\u003ePatients\u003c/h3\u003e\n\u003cp\u003eWe evaluated patients with unresectable HCC treated with Ate/Bev or Len between December 2019 and December 2022 in Kaohsiung Chang Gung Memorial Hospital. HCC diagnosis relied on computed tomography (CT) or magnetic resonance imaging (MRI) identifications or histological proofs. Clinical data, including patient demographics, tumor characteristics, treatment details, and outcomes, were collected from electronic medical records. Inclusion criteria comprised a diagnosis of unresectable HCC, aged 18 years or older, and receiving either Ate/Bev or Len as first-line systemic therapy. Patients with prior systemic therapy, inadequate follow-up data, or incomplete treatment records were excluded. Using Ate/Bev or Len was based on the decisions of clinicians and patient`s wishes. Patients who received Len could be reimbursed if they met the criteria of Taiwan NHI including Child-Pugh class A liver function reserve, tumor in Barcelona Clinical Liver Cancer (BCLC) stage C, or tumor in BCLC stage B with TACE refractory [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Concurrent use of Ate/Bev or Len with other treatments is permissible. The study protocol was approved by the Research Ethics Committee of Chang Gung Memorial Hospital (IRB No. 202001701A3).\u003c/p\u003e\n\u003ch3\u003eAssessment of Treatment Outcome\u003c/h3\u003e\n\u003cp\u003eTreatment response was assessed using radiologic imaging based on the Response Evaluation Criteria in Solid Tumors version 1.1. (RECIST 1.1) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The ORR was defined as patients achieving complete response (CR) or partial response (PR), while the disease control rate (DCR) was defined as patients achieving CR, PR, or stable disease status (SD). Progression disease (PD) was identified as tumors demonstrating obvious progression during assessment.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of adverse events\u003c/h2\u003e \u003cp\u003eTermination of Ate/Bev or Len depended upon the occurrence of any unacceptable or serious TRAEs, or upon clinical tumor progression. Following Ate/Bev or Len administration guidelines, dosage adjustments or temporary treatment pauses were implemented if a patient experienced any TRAE of grade 3 or higher severity, or if any unacceptable grade 2 TRAE occurred. TRAEs graded 3 or higher were deemed severe. In the event of a TRAE, dose reductions or temporary treatment pauses were maintained until the TRAE resolved to grade 1 or 2, in accordance with the manufacturer's guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median with interquartile range, while categorical variables were presented as frequencies and percentages. Differences between groups were analyzed using Student's t-test, Mann-Whitney U test, chi-square test, or Fisher's exact test, as appropriate. Survival outcomes, including PFS and OS, were analyzed using Kaplan-Meier curves and Cox regression models. Propensity-score matching (PSM) analysis was performed using Age, Sex, Alpha-fetoprotein (AFP), Child-Pugh class, Viral etiology, Extrahepatic metastasis (EHM), Macrovascular invasion (MVI) and Maximal tumor size with a 1:2 ratio to reduce the real-life baseline difference between Ate/Bev and Len groups. All enrolled patients were followed up till Dec 2023. All statistical analyses were performed using SPSS 26 software (SPSS Inc., Chicago, IL, USA), and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. \u003c/p\u003e \u003c/div\u003e\n"},{"header":"Results","content":"\u003ch3\u003eThe baseline clinical characteristics\u003c/h3\u003e\n\u003cp\u003eThe flowchart of enrollment in this study is shown in supplementary Fig.\u0026nbsp;1. There were 430 patients with unresectable HCC who received Ate/Bev or Len between December 2019 and December 2022. Eighty-four patients were excluded due to receiving other systemic therapies before, having insufficient data, or being lost to follow-up. Therefore, a total of 346 patients including 80 (23.1%) with Ate/Bev and 266 (76.9%) with Len were further assigned to the Ate/Bev group (number, n\u0026thinsp;=\u0026thinsp;73) and the Len group (n\u0026thinsp;=\u0026thinsp;142) by using PSM analysis with a 1:2 ratio. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the baseline characteristics of all enrolled patients before and after PSM analysis. Before PSM, the Ate/Bev group were younger (61.6 vs 65.4 years, p\u0026thinsp;=\u0026thinsp;0.012), showed more Child-Pugh class B (14.1 vs 5.7%, p\u0026thinsp;=\u0026thinsp;0.014), larger main tumor (58.8 vs 40.2%, p\u0026thinsp;=\u0026thinsp;0.003), more main portal vein invasion (Vp4) (25% vs. 12.8%, p\u0026thinsp;=\u0026thinsp;0.008), more treatment termination (93.8 vs 83.8%, 0.024) and fewer concurrent treatments (20 vs 40.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with the Len group. After the performance of PSM, the baseline characteristics of the two groups were balanced, except that the proportion of receiving concurrent treatment (21.9 vs 45.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) remained lower in the Ate/Bev than in the Len group. In the PSM cohort, the leading four concurrent treatments with Len were mono-immunotherapy as pembrolizumab or nivolumab, radiotherapy, TACE, and proton beam radiotherapy. In the Ate/Bev group, the mostly concurrent treatment was proton beam radiotherapy, followed by TACE and radiotherapy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of patients receiving Ate/Bev or Len before and after PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAfter PSM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAte/Bev (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLen (n\u0026thinsp;=\u0026thinsp;266)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAte/Bev (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLen (n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (76.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e201 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55 (75.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e103 (72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild-Pugh class\u003c/p\u003e \u003cp\u003eA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (85.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e249 (94.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64 (87.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e131 (92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eViral etiology, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (76.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199 (74.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55 (75.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e106 (74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBV infection, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (63.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137 (51.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45 (61.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCV infection, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALBI grade 1, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151 (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65 (45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (48.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33 (45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72 (50.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBCLC stage, B, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213 (80.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63 (86.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e125 (88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEHM, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35 (47.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65 (45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMVI, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41 (56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74 (52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVp4, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size\u0026thinsp;\u0026gt;\u0026thinsp;6cm, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (40.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (58.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76 (53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST, IU/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.5\u0026thinsp;\u0026plusmn;\u0026thinsp;48.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.6\u0026thinsp;\u0026plusmn;\u0026thinsp;51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.4\u0026thinsp;\u0026plusmn;\u0026thinsp;47.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.7\u0026thinsp;\u0026plusmn;\u0026thinsp;61.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, IU/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.9\u0026thinsp;\u0026plusmn;\u0026thinsp;36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.9\u0026thinsp;\u0026plusmn;\u0026thinsp;63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.6\u0026thinsp;\u0026plusmn;\u0026thinsp;37.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.9\u0026thinsp;\u0026plusmn;\u0026thinsp;81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFP, ng/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8802\u0026thinsp;\u0026plusmn;\u0026thinsp;20738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6753\u0026thinsp;\u0026plusmn;\u0026thinsp;18331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7553\u0026thinsp;\u0026plusmn;\u0026thinsp;21568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7281\u0026thinsp;\u0026plusmn;\u0026thinsp;18006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFP\u0026thinsp;\u0026ge;\u0026thinsp;400, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56 (39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u0026thinsp;\u0026gt;\u0026thinsp;3, N(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46 (63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189.5\u0026thinsp;\u0026plusmn;\u0026thinsp;119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e169.9\u0026thinsp;\u0026plusmn;\u0026thinsp;99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u0026thinsp;\u0026gt;\u0026thinsp;230, N(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcurrent treatment, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65 (45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePembrolizumab /Nivolumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 / 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 / 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTACE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProton bean radiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost treatment, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment stop, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e223 (83.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (93.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e120 (84.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: AFP, alpha-fetoprotein; ALBI grade, albumin-bilirubin grade; ALT, alanine aminotransferase; AST aspartate transaminase; Ate/Bev: Atezolizumab plus Bevacizumab; BCLC stage, Barcelona Clinic Liver Cancer stage; BMI, body mass index; EHM, extra-hepatic metastasis; Len, Lenvatinib; NLR, neutrophil lymphocyte ratio; PLR, platelet lymphocyte ratio; PSM, propensity score matching; TACE, trans-arterial chemoembolization; Vp4, main portal vein invasion or bilateral portal vein invasion.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eTreatment response of patients before and after PSM\u003c/h3\u003e\n\u003cp\u003eTreatment response was assessed via those patients who received following CT or MRI imaging (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Before PSM, the ORR was compatible between the Ate/Bev and Len group (20% vs 20.3%); however, patients in the Len group had a superior DCR (72 vs 55.7%, p\u0026thinsp;=\u0026thinsp;0.004). After PSM, there were no statistically significant differences between the Ate/Bev and Len groups regarding CR, PR, SD, PD, DCR, and death. However, a trend was observed indicating a better DCR in the Len group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment response of patients receiving Ate/Bev or Len before and after PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAfter PSM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAte/Bev\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;266)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAte/Bev\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment response evaluation, n(%) \u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (82.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225 (89.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64 (87.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e116 (81.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete Response, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartial Response, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStable Disease, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57 (49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgression Disease, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (44.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (42.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObjective Response Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease Control Rate\u0026Dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41 (56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: Ate/Bev: Atezolizumab plus Bevacizumab; Len, Lenvatinib; PSM, propensity score matching.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u0026dagger;Treatment response based on those who received image evaluation including Computer tomography or Magnetic resonance image.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment related adverse events of patients receiving Ate/Bev or Len before and after PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eAfter PSM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAte/Bev (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eLen (n\u0026thinsp;=\u0026thinsp;266)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAte/Bev (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eLen (n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAny,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrade\u0026thinsp;\u0026ge;\u0026thinsp;3,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAny,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGrade\u0026thinsp;\u0026ge;\u0026thinsp;3, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAny,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGrade\u0026thinsp;\u0026ge;\u0026thinsp;3,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAny,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eGrade\u0026thinsp;\u0026ge;\u0026thinsp;3, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal TRAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e185 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41 (56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5 (3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHFSR, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59 (23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiarrhea, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 ()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 ()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor appetite, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDysphonia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDermatitis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProteinuria, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEncephalopathy, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated bilirubin, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUGI bleeding, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeizure, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1(1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAbbreviations: Ate/Bev: Atezolizumab plus Bevacizumab; HFSR, hand foot skin reaction; Len, Lenvatinib; PSM, propensity score matching; TRAE, treatment related adverse event; UGI bleeding, upper gastrointestinal bleeding.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e* The comparison of any TRAE between two groups was 0.008 (Before PSM) and 0.03(After PSM).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTreatment Related Adverse Events before and after PSM\u003c/h2\u003e \u003cp\u003eBefore (56.3 vs 72%, p\u0026thinsp;=\u0026thinsp;0.008) and after PSM (56.2 vs 71.1%, p\u0026thinsp;=\u0026thinsp;0.03), the Ate/Bev group both experienced a lower proportion of total TRAE than the Len group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However, the occurrence rate of severer TRAE (\u0026ge;\u0026thinsp;grade 3) between the two groups was similar. After PSM, the most reported TRAE in the Len group was hand-foot skin reaction, with a total of 32 patients (22.4%), followed by with fatigue with 31 patients (21.7%), and diarrhea with 20 patients (14%). In the Ate/Bev group, 56.2% of patients had incidence of total TRAE, where the incidence over 10% included 28% of patients with fatigue, 11.2% with dermatitis, and 11.2% with decreased appetite. Only 5 patients (7%) in the Ate/Bev group experienced severe TRAE needed to stop treatment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with Progression Free Survival in the PSM cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH.R.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eH.R.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncrease per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u0026ndash;1.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale vs. Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.624\u0026ndash;1.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild-Pugh class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB vs A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.805\u0026ndash;2.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEtiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eViral vs non viral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.774\u0026ndash;1.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBCLC stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC vs B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.977\u0026ndash;2.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEHM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.611\u0026ndash;1.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMVI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.159\u0026ndash;2.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.168\u0026ndash;2.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6 vs\u0026thinsp;≦\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.027\u0026ndash;2.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFP, ng/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;400 vs\u0026thinsp;≦\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.195\u0026ndash;2.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.225\u0026ndash;2.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcurrent treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.461\u0026ndash;0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.425\u0026ndash;0.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment option\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAte/Bev vs Len\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.733\u0026ndash;1.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eAbbreviations: AFP, alpha-fetoprotein; Ate/Bev: Atezolizumab plus Bevacizumab; BCLC stage, Barcelona Clinic Liver Cancer stage; EHM, extra-hepatic metastasis; Len, Lenvatinib; PSM, propensity score matching.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePFS and its predicting factors\u003c/h2\u003e \u003cp\u003eKaplan-Meier curves of PFS were 3.7 months in the Ate/Bev group and 6.8 months in the Len group, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Although the Len group seemed to have a better PFS, but the comparison was insignificant. After PSM, the Len group had a longer PFS than the Ate/Bev group (6 vs 5.1 months, p\u0026thinsp;=\u0026thinsp;0.783), but there was no difference (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In Cox regression model of multivariate analyses, more microvascular invasion, higher AFP level, and fewer concurrent treatment were independent risk factors associated with PFS in the PSM cohort (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Different treatment agents using Ate/Bev or Len did not contribute to PFS, whether for univariate or multivariate analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eOS and its predicting factors\u003c/h2\u003e \u003cp\u003eComparing OS, the Ate/Bev group had a median of 10.4 months, while the Len group had 16.6 months, but there was no significant difference between the two groups (P\u0026thinsp;=\u0026thinsp;0.158) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(C)). After PSM, the OS in the Ate/Bev group was 13.3 months, compared to 14.1 months in the Len group, still showing a statistically insignificant (P\u0026thinsp;=\u0026thinsp;0.945) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(D)). In the multivariate analysis, after adjusting for other variables, non-viral etiology, higher AFP level, larger main tumor size, no concurrent treatment and no sequential post-treatment were associated with poor outcome in the PSM cohort (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Different treatment agents using Ate/Bev or Len did not contribute to OS, whether for univariate or multivariate analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with Overall Survival in the PSM cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH.R.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eH.R.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncrease per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.988\u0026ndash;1.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale vs. Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.561\u0026ndash;1.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild-Pugh class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB vs A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.592\u0026ndash;4.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEtiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eViral vs non viral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.386\u0026ndash;0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.295\u0026ndash;0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBCLC stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC vs B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.743\u0026ndash;2.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEHM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.742\u0026ndash;1.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMVI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.989\u0026ndash;2.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6 vs\u0026thinsp;≦\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.277\u0026ndash;2.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.208\u0026ndash;2.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFP, ng/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;400 vs\u0026thinsp;≦\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.335\u0026ndash;2.823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.396\u0026ndash;3.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcurrent treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.269\u0026ndash;0.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.235\u0026ndash;0.557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.293\u0026ndash;0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.297\u0026ndash;0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment option\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAte/Bev vs Len\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.666\u0026ndash;1.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eAbbreviations: AFP, alpha-fetoprotein; Ate/Bev: Atezolizumab plus Bevacizumab; BCLC stage, Barcelona Clinic Liver Cancer stage; EHM, extra-hepatic metastasis; Len, Lenvatinib; PSM, propensity score matching.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup Analysis for PFS and OS after PSM\u003c/h2\u003e \u003cp\u003eAfter PSM, the subgroup analysis indicated that using Ate/Bev was equal to using Len associated with PFS in all subgroups before PSM (Supplementary Fig.\u0026nbsp;2) and after PSM (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Similarly, there were still no difference in all subgroups regarding the OS in using first line Ate/Bev or Len before PSM (Supplementary Fig.\u0026nbsp;3) and after PSM (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Although non-viral patients who preferred Len over Ate/Bev tended to experience better OS (HR: 0.50, 95% CI: 0.27\u0026ndash;0.93, p\u0026thinsp;=\u0026thinsp;0.028), this comparison became insignificant after PSM (HR: 0.55, 95% CI: 0.27\u0026ndash;1.09, p\u0026thinsp;=\u0026thinsp;0.087).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSequential treatments following Ate/Bev or Len after PSM\u003c/h2\u003e \u003cp\u003eAfter cessation of first line treatment, 40 patients (54.8%) in the Ate/Bev group and 54 (43.9%) in the Len group still afforded following therapies (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Concerning sequential systemic treatments, the Ate/Bev group had a higher proportion than the Len group (45.2 vs 24.6%, p\u0026thinsp;=\u0026thinsp;0.009). A total of 30 patients (90.9%) received TKI after failure of Ate/Bev, 3 patients used sorafenib whereas 27 patients took Len-based therapies including 14 for Len, 9 for Len plus pembrolizumab, 3 for Len plus chemotherapy, and 2 for Len plus nivolumab. In the Len group, most patients decided chemotherapy or immunotherapy as the second line treatment. The most frequently used agent was chemotherapy for 13 patients, followed by Ate/Bev for 9, and nivolumab for 9. \u003c/p\u003e \n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSequential treatments after failure of Ate/Bev or Len in the PSM cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAte/Bev (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLen (n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment Stop, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (93.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (84.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-treatment, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd-line systemic treatments, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLen plus Pembrolizumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLen plus Nivolumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLen plus Chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAte/Bev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNivolumab plus Ipilizumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNivolumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSorafenib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThalidomide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: Ate/Bev: Atezolizumab plus Bevacizumab; Len, Lenvatinib; PSM, propensity score matching.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":" \u003cp\u003eAte/Bev has been recommended as the first choice of treatment option for patients with advanced HCCs by current international guidelines based on the IMbrave 150 clinical trial [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], which demonstrated that Ate/Bev can achieve a benefit in OS (19.2 vs. 13.4 months; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and PFS (6.9 vs. 4.3 months; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to sorafenib. Len, another effective TKI, showed non-inferior treatment efficacy to sorafenib in the clinical trial [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and even demonstrates better treatment outcomes and responses than sorafenib in real-life practices [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Although current HCC guidelines suggest Len should be considered as a first-line treatment if Ate/Bev is unsuitable or as a second-line treatment following Ate/Bev [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], there have been no head-to-head comparisons between these two agents. Some studies have attempted to clarify this issue in real-world settings; however, the results have been controversial. Even meta-analyses have not reached a consistent conclusion. Changez et al. showed that Ate/Bev provides a potential advantage in efficacy and better safety than Len in the treatment of unresectable HCC via ten cohorts including 6493 patients [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], whereas Lu et al. reported that the Len group had longer OS and PFS than the Ate/Bev group via seven eligible studies involving 4428 patients [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This suggests that Len might provide treatment benefits equal to those of Ate/Bev for patients with unresectable HCC.\u003c/p\u003e \u003cp\u003eAdditionally, the high price of Ate/Bev limits its common application in real-life practice, particularly in Taiwan where our NHI didn\u0026rsquo;t cover this agent before August 2023. Consequently, TKIs such as sorafenib or Len usually serve as the first-line treatment choice for patients with unresectable HCC in real-world practice. In Taiwan, Len has been reimbursed by the insurance since January 2020. The current study observes the treatment outcomes between Len and Ate/Bev in the era of different insurance coverage in Taiwan. Compared to the Len group, patients who opted for self-paid Ate/Bev showed more locally advanced tumor patterns, larger tumor burdens, and poorer liver function at baseline. These are common contributing factors to a poor treatment prognosis. On the contrary, most patients in the Len group received Len under the reimbursed criteria of NHI, with good liver function and consistent tumor patterns.\u003c/p\u003e \u003cp\u003eThe Ate/Bev group had a comparable ORR (20% vs. 20.3%) but an inferior DCR (55.7% vs. 27%, p\u0026thinsp;=\u0026thinsp;0.004) compared to the Len group. After PSM, there were no statistically significant differences between the Ate/Bev and Len groups regarding ORR, DCR, and death. Additionally, the PFS of the Ate/Bev group was shorter than that of the Len group, though the difference was not statistically significant (3.7 months vs. 6.8 months, p\u0026thinsp;=\u0026thinsp;0.292). After PSM, the Len group still had a longer PFS than the Ate/Bev group (6 months vs. 5.1 months, p\u0026thinsp;=\u0026thinsp;0.783), but the difference was not significant. Regarding OS, the Ate/Bev group also had poorer survival compared to the Len group, but the difference was not significant (10.4 months vs. 16.6 months, p\u0026thinsp;=\u0026thinsp;0.158). After PSM, the OS of the two groups was more similar (13.3 months for the Ate/Bev group and 14.1 months for the Len group).\u003c/p\u003e \u003cp\u003eWe found that our patients who received self-paid Ate/Bev seemed to have poorer PFS and OS compared to the clinical trials and showed a worse trend in survival compared to patients who received reimbursed Len. This may be due to these patients having more advanced tumor patterns and poorer liver function than those enrolled in clinical trials. Additionally, the observation period from the beginning of Ate/Bev treatment to the first image evaluation was significantly shorter than in the clinical trials due to the high cost of this agent. Most patients received their first image evaluation after only two to three administrations, which might lead to an underestimate of PFS. Moreover, previous studies indicated that delayed immune treatment response sometimes occurs after image pseudo-progression in HCC treatment [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Insufficient drug exposure could result in a suboptimal treatment response and worse treatment outcomes.\u003c/p\u003e \u003cp\u003eRecent meta-analysis has demonstrated that patients receiving Ate/Bev exhibited lower incidences of grade 3/4 adverse events compared to those receiving Len (p\u0026thinsp;=\u0026thinsp;0.003) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The present study also observed that the Ate/Bev group experienced a lower proportion of TRAEs than the Len group, both before (56.3% vs. 72%, p\u0026thinsp;=\u0026thinsp;0.008) and after PSM (56.2% vs. 71.1%, p\u0026thinsp;=\u0026thinsp;0.03). However, the occurrence rate of severe TRAEs (\u0026ge;\u0026thinsp;grade 3) between the two groups was similar. Following PSM, the most frequently reported TRAE in the Len group was hand-foot skin reaction, affecting a total of 32 patients (22.4%), followed by fatigue in 31 patients (21.7%), and diarrhea in 20 patients (14%). In the Ate/Bev group, 56.2% of patients experienced total TRAEs, with incidences exceeding 10% including fatigue in 28% of patients, dermatitis in 11.2%, and decreased appetite in 11.2%. Only 5 patients (7%) in the Ate/Bev group experienced severe TRAEs necessitating treatment discontinuation.\u003c/p\u003e \u003cp\u003eThe current study also indicated that concurrent treatment was a significant contributing factor to treatment prognosis, both in univariate and multivariate analyses. In real-world practice, clinicians often combine locoregional therapies with systemic treatments to enhance treatment response [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Patients receiving concurrent treatment had superior PFS (9.3 vs. 3.4 months, p\u0026thinsp;=\u0026thinsp;0.012) and OS (19.2 vs. 8.9 months, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those who did not combine treatments. We observed that patients reimbursed for Len received more concurrent therapies than those self-paying for Ate/Bev (45.9% vs. 21.8%, p\u0026thinsp;=\u0026thinsp;0.001). In the PSM cohort, the most common concurrent treatments with Len were mono-immunotherapy with pembrolizumab or nivolumab, radiotherapy, TACE, and proton beam radiotherapy. In the Ate/Bev group, the predominant concurrent treatment was proton beam radiotherapy, followed by TACE and radiotherapy.\u003c/p\u003e \u003cp\u003eLen combined with pembrolizumab, a combination of TKI plus immunotherapy, had been a popular treatment option for patients with advanced HCC based on a phase Ib clinical trial [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Although this combination did not demonstrate superiority to Len monotherapy in phase III results [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], many patients still derived survival benefits from this combination in real-world practice. Yang et al. reported that Len plus PD-1 inhibitor treatment resulted in a longer OS of 17.8 months and a notable ORR of 19.6% and DCR of 73.5% in unresectable HCC patients [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The current study also observed that patients combining Len with pembrolizumab or nivolumab achieved excellent OS of 18.5 months.\u003c/p\u003e \u003cp\u003eIn multivariate analysis, post-treatment emerged as a significant factor in reducing mortality risk for patients receiving first-line Ate/Bev or Len. Patients who underwent post-treatment experienced significantly better OS compared to those who did not (17.2 vs. 6.6 months, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Following cessation of first-line treatment, 40 patients (54.8%) in the Ate/Bev group and 54 (43.9%) in the Len group continued to receive subsequent therapies. Regarding sequential systemic treatments, a higher proportion of patients in the Ate/Bev group received them compared to the Len group (45.2% vs. 24.6%, p\u0026thinsp;=\u0026thinsp;0.009). Of the patients who failed Ate/Bev, 90.9% received TKI therapy, 3 patients received sorafenib, and 27 patients received Len-based therapies, including 14 for Len alone, 9 for Len plus pembrolizumab, 3 for Len plus chemotherapy, and 2 for Len plus nivolumab. In the Len group, most patients opted for chemotherapy or immunotherapy as second-line treatment. Chemotherapy was the most frequently chosen agent for 13 patients, followed by Ate/Bev for 9, and nivolumab for 9. It appears that the primary consideration in selecting sequential treatment was to explore a different mechanism from the failed first-line agent.\u003c/p\u003e \u003cp\u003eUnlike previous studies, the current study found no association between the use of Ate/Bev or Len and PFS across all subgroups. Similarly, there were no differences observed in OS among all subgroups receiving first-line Ate/Bev or Len. Some studies have suggested that non-viral patients, particularly those with non-alcoholic fatty liver disease, might exhibit poorer treatment responses to Ate/Bev compared to viral patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our study also observed that non-viral patients who preferred Len over Ate/Bev tended to experience better OS (HR: 0.50, 95% CI: 0.27\u0026ndash;0.93, p\u0026thinsp;=\u0026thinsp;0.028). However, this comparison became insignificant after PSM (HR: 0.55, 95% CI: 0.27\u0026ndash;1.09, p\u0026thinsp;=\u0026thinsp;0.087). A larger study cohort might be necessary to elucidate this issue further in clinical practice.\u003c/p\u003e \u003cp\u003eThe current study has several limitations. Firstly, the differential NHI-reimbursed status for Ate/Bev and Len introduces the risk of selection bias and confounding factors that could influence treatment outcomes. Although we utilized PSM to address these biases, residual confounding may still be present. Since both regimens have been reimbursed by the Taiwan NHI program since August 2023, further studies are needed to compare Ate/Bev and Len under more consistent baseline clinical characteristics. Secondly, the relatively small sample size and single-center nature of the study may restrict the generalizability of our findings to broader populations. Larger multicenter studies are necessary to validate our results and provide more robust evidence. Thirdly, the absence of long-term follow-up data may obscure the impact of treatment on survival outcomes beyond the study period. Future studies with extended follow-up durations are required to evaluate the durability of treatment responses and long-term survival benefits. \u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003e In summary, our study offers valuable insights into the comparative effectiveness of Health Insurance-Guided First-Line Len and self-paid Ate/Bev in patients with unresectable HCC. Despite initial differences in baseline characteristics, both treatment regimens demonstrated comparable treatment responses and survival outcomes. These findings highlight the significance of individualized treatment decisions tailored to patient-specific factors. Further research is warranted to optimize first-line treatment strategies for Len or Ate/Bev under consistent reimbursement criteria from the NHI.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAFP, alpha-fetoprotein; ALBI grade, albumin-bilirubin grade; ALT, alanine aminotransferase; AST, aspartate transaminase; Ate/Bev, atezolizumab plus bevacizumab; BCLC stage, Barcelona clinic liver cancer stage; CR, complete response; DCR, disease control rate; EHM, extra-hepatic metastasis; HCC, hepatocellular carcinoma; Len, lenvatinib; MVI, microvascular invasion; NHI, national health insurance; ORR, objective response rates; OS, overall survival; PD, progression disease; PD-L1, anti-programmed death-ligand 1; PFS, progression-free survival; PSM, propensity score matching; PR, partial response; RFA, radio-frequency ablation; SD, stable disease; TACE, Trans-Arterial Chemoembolization; TKI, tyrosine kinase inhibitor; TRAEs, treatment-related adverse events; uHCC, unresectable hepatocellular carcinoma; VEGF, vascular endothelial growth factor.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Miss Nien-Tzu Hsu and the biostatistics center of Kaohsiung Chang Gung Memorial Hospital for excellent statistics works.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was funded from Chang Gung Memorial Hospital (CMRPG8L0291) to Prof. Yuan-Hung Kuo.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest: \u003c/strong\u003eYuan-Hung Kuo, Wei-Chen Tai, Yen-Hao Chen, Ming-Chao Tsai, Sheng-Nan Lu, Tsung-Hui Hu, Chao-Hung Hung, Chien-Hung Chen, and Jing-Houng Wang declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval: \u003c/strong\u003eAll procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (Chang Gung Memorial Hospital (IRB No. 202001701A3) and with the Helsinki Declaration of 1975, as revised in 2008. Informed consent was obtained from all patients for being included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement: \u003c/strong\u003eThe Institutional Review Board of Chang Gung Medical Foundation waived the requirement of written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate: \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material (data transparency): \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability (software application or custom code): \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trials Registration: \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions: \u003c/strong\u003eConceptualization and study design: Yuan-Hung Kuo and Jing-Houng Wang; Analysis and interpretation of the data: Yuan-Hung Kuo; Writing original draft: Yuan-Hung Kuo; Data acquisition: Yuan-Hung Kuo, Wei-Chen Tai; Yen-Hao Chen, Ming-Chao Tsai, Sheng-Nan Lu, Tsung-Hui Hu, Chao-Hung Hung, Chien-Hung Chen; Jing-Houng Wang, Supervision: Jing-Houng Wang. \u003cem\u003eAll authors read and approved the final manuscript.\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCappuyns S, Corbett V, Yarchoan M, Finn RS, Llovet JM. 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Eur J Cancer. 2023;180:9\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiraoka A, Kumada T, Tada T, et al. Does first-line treatment have prognostic impact for unresectable HCC? Atezolizumab plus bevacizumab versus lenvatinib. Real-life Practice Experts for HCC (RELPEC) Study Group and HCC 48 Group (hepatocellular carcinoma experts from 48 clinics in Japan). Cancer Med. 2023;12(1):325\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, Yang L, Wei S, Li J, Yi PJ. Efficacy and safety of atezolizumab plus bevacizumab versus lenvatinib for unresectable hepatocellular carcinoma: a systematic review and meta-analysis. Cancer Res Clin Oncol. 2023;149(17):16191\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe Reimbursement Criteria of Hepatocellular Carcinoma Treatment. Ministry of Health and Welfare, ROC: The National Health Insurance Administration. May 2024 update.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDing X, Sun W, Li W, et al. Transarterial chemoembolization plus lenvatinib versus transarterial chemoembolization plus sorafenib as first-line treatment for hepatocellular carcinoma with portal vein tumor thrombus: A prospective randomized study. Cancer. 2021;127(20):3782\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SW, Yang SS, Lien HC, Peng YC, Ko CW, Lee TY. Efficacy of Lenvatinib and Sorafenib in the Real-World First-Line Treatment of Advanced-Stage Hepatocellular Carcinoma in a Taiwanese Population. J Clin Med. 2022;11(5):1444.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark MK, Lee YB, Moon H, et al. Effectiveness of Lenvatinib Versus Sorafenib for Unresectable Hepatocellular Carcinoma in Patients with Hepatic Decompensation. Dig Dis Sci. 2022;67(10):4939\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCho Y, Kim BH, Park JW. Overview of Asian clinical practice guidelines for the management of hepatocellular carcinoma: An Asian perspective comparison. Clin Mol Hepatol. 2023;29(2):252\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. J Hepatol. 2022;76(3):681\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChangez MIK, Khan M, Uzair M, et al. Efficacy of Atezolizumab Plus Bevacizumab Versus Lenvatinib in Patients with Unresectable Hepatocellular Carcinoma: a Meta-analysis. J Gastrointest Cancer. 2024;55(1):467\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu J, Lin X, Teng H, Zheng Y. Atezolizumab Plus Bevacizumab Versus Lenvatinib for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. J Clin Pharmacol. 2024;64(6):643\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOdagiri N, Tamori A, Kotani K, et al. A case of hepatocellular carcinoma with pseudoprogression followed by complete response to atezolizumab plus bevacizumab. Clin J Gastroenterol. 2023;16(3):392\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOtake S, Ota Y, Aso K, et al. Contrast-enhanced Ultrasonography Features for Diagnosing Pseudoprogression of Hepatocellular Carcinoma with Immunotherapy: A Case Report of the Response after Pseudoprogression. Intern Med. 2024;63(8):1093\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao C, Xiang Z, Li M, et al. Transarterial Chemoembolization Combined with Atezolizumab Plus Bevacizumab or Lenvatinib for Unresectable Hepatocellular Carcinoma: A Propensity Score Matched Study. J Hepatocell Carcinoma. 2023;10:1195\u0026ndash;206.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu CW, Teng W, Shen EY, et al. Concurrent Atezolizumab Plus Bevacizumab and High-Dose External Beam Radiotherapy for Highly Advanced Hepatocellular Carcinoma. Oncologist. 2024 Mar;26:oyae048.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFinn RS, Ikeda M, Zhu AX, et al. Phase Ib Study of Lenvatinib Plus Pembrolizumab in Patients With Unresectable Hepatocellular Carcinoma. J Clin Oncol. 2020;38(26):2960\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLlovet JM, Kudo M, Merle P, et al. Lenvatinib plus pembrolizumab versus lenvatinib plus placebo for advanced hepatocellular carcinoma (LEAP-002): a randomised, double-blind, phase 3 trial. Lancet Oncol. 2023;24(12):1399\u0026ndash;410.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang X, Chen B, Wang Y, et al. Real-world efficacy and prognostic factors of lenvatinib plus PD-1 inhibitors in 378 unresectable hepatocellular carcinoma patients. Hepatol Int. 2023;17(3):709\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRimini M, Rimassa L, Ueshima K, et al. Atezolizumab plus bevacizumab versus lenvatinib or sorafenib in non-viral unresectable hepatocellular carcinoma: an international propensity score matching analysis. ESMO Open. 2022;7(6):100591.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Atezolizumab plus Bevacizumab, Lenvatinib, National health insurance, Propensity score matching analysis, Unresectable hepatocellular carcinoma.","lastPublishedDoi":"10.21203/rs.3.rs-4522670/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4522670/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Purpose:\u003c/strong\u003e Atezolizumab plus bevacizumab (Ate/Bev) and lenvatinib (Len) are first-line therapies for unresectable hepatocellular carcinoma (uHCC). However, Ate/Bev's high cost limits its common use in real-life practice, while Len is usually covered by national health insurance (NHI). We conducted this study to compare their effectiveness and safety in real-world settings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We retrospectively evaluated 346 uHCC patients treated with first-line Ate/Bev (n=80) or Len (n=266) from December 2019 to December 2022, using 1:2 ratio propensity score matching (PSM) analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Compared to the Len group, the Ate/Bev group exhibited higher incidences of Child-Pugh class B (14.1% vs. 5.7%, p=0.014), larger main tumors (58.8% vs. 40.2%, p=0.003), and more main portal vein invasion (25% vs. 12.8%, p=0.008). Treatment-related adverse events were notably lower in the Ate/Bev group (56.3% vs. 72.3%, p=0.007). After PSM, no significant differences were observed in the objective response rate (21.9% vs. 21.6%, p=0.983), progression-free survival (5.1 vs. 6 months, p=0.783), and overall survival (13.3 vs. 14.1 months, p=0.945) between the Ate/Bev (n=73) and Len (n=142) groups. Patients in the Ate/Bev group received more sequential post-treatments compared to the Len group (45.2% vs. 24.6%, p=0.009). Len-based therapies (n=28, 84.8%) and mono- or combined-immunotherapy (n=19, 54.3%) were the most frequently administered sequential therapies following Ate/Bev and Len, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Patients with uHCC who received first-line self-paid Ate/Bev appeared to have lower liver function reserve and more advanced tumor characteristics compared to those who underwent NHI-reimbursed Len. However, the treatment outcomes and safety profiles were similar between these two groups.\u003c/p\u003e","manuscriptTitle":"Comparing Health Insurance-ReimbursedFirst Line Lenvatinib and Self-paid Atezolizumab plus Bevacizumab in Patients with Unresectable Hepatocellular Carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-27 18:59:10","doi":"10.21203/rs.3.rs-4522670/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60353aba-bf32-4f6f-b4d4-cfb9329c648b","owner":[],"postedDate":"June 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-27T18:59:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-27 18:59:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4522670","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4522670","identity":"rs-4522670","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}