Comparative efficacy and safety of anti-PD-1/L1 antibody plus anti-VEGF antibody and anti-PD-1/L1 antibody plus VEGFR-targeted tyrosine kinase inhibitor as first-line therapy for unresectable hepatocellular carcinoma (uHCC): a systematic review and network meta- analysis

doi:10.21203/rs.3.rs-2961338/v1

Background

Anti-PD-1/L1 antibody + anti-VEGF antibody (A + A) and anti-PD-1/L1 antibody + VEGFR-targeted tyrosine kinase inhibitor (A + T) are both effective first-line therapies for uHCC. However, direct comparisons between them are not available. We conducted a network meta-analysis of them in terms of overall survival (OS), progression free survival (PFS), objective response rate (ORR) and incidence of treatment-related adverse events (TRAEs).

Methods

After a rigorous literature research, 6 phase III trials has been identified for the final analysis: IMbrave150, ORIENT-32, COSMIC-312, CARES-310, LEAP-002 and REFLECT. The experiments were classified into three groups: A + A, A + T and intermediate reference group. We derived hazard ratios (HR) with 95% confidence intervals (95%CI) for OS and PFS, odds ratio (OR) for ORR and relative risks (RR) for all grade and ≥ 3 TRAEs. With fixed effect models to estimate the indirect pooled HRs, ORs, RRs and 95%CI, a frequentist network meta-analysis was conducted using sorafenib as intermediate reference.

Results

With a P-score of 98%, A + A provided the greatest reduction in the risk of death, without significant difference from A + T (HR = 0.84, 95%CI: 0.66–1.06). Besides, A + T showed the greatest effect in prolonging PFS and improving ORR with 91% for P-score, but there are no statistical differences with A + A(HR = 1.06, 95%CI: 0.87–1.30, OR = 0.82, 95%CI: 0.47–1.46). A + A were significantly safer than A + T (RR = 0.91, 95%CI: 0.84–0.98) in all grade of TRAEs and ≥ 3 (RR = 0.91, 95%CI: 0.84–0.98).

Conclusions

A + A has the greatest probability of delivering the longest OS, while A + T is correlated with larger PFS benefit at the cost of a lower safety rate.

Hepatocellular carcinoma

Anti-PD-1/L1 antibody

Anti-VEGF antibody

Tyrosine kinase inhibitor

Network meta-analysis

According to data from GLOBOCAN 2020 database, liver cancer is a pronounced health burden worldwide, ranking sixth in incidence (4.7%) and third in mortality (8.3%) among all cancers[1]. Hepatocellular carcinoma (HCC) accounts for 75%-85% of primary liver cancer cases[2]. Due to difficulties in early diagnosis, most HCC patients are diagnosed at an advanced stage and miss opportunities for radical treatment such as surgery or radiofrequency ablation, which further shows the importance of systematic treatment[3].

According to the results from the SHARP[4] and Sorafenib Asia-Pacific trials[5], sorafenib was the only targeted therapy allowed for HCC patients from 2007 until 2018, which significantly prolonged patients' overall survival (OS). During that decade, many other compounds, including erlotinib, brivanib (HR = 1.06, 95.8% CI 0.93–1.22), sunitinib, linifanib and everolimus (HR = 1.05, 95% CI 0.86–1.27), were tested in the first-line treatment of HCC, but they did not show superiority (or at least noninferiority) to sorafenib[6]. In 2018, lenvatinib was found to be noninferior to sorafenib (HR = 0.92, 95% CI 0.79–1.06) and represented a long-awaited alternative option to sorafenib for the first-line systemic treatment of patients with unresectable HCC (uHCC)[7]. In recent years, researchers have conducted clinical trials of a variety of combination regimens and have mixed results. The results of IMbrave150 led to the largest change in the treatment landscape of uHCC, which showed that the combination of atezolizumab and bevacizumab was significantly superior to sorafenib with an improved median OS (HR = 0.58, 95% CI 0.42–0.79) and comparable rates of ≥ 3 grade adverse events (43% vs. 46%)[8]. The results of the ORIENT-32 were also positive for OS and PFS[9]. With the combination of camrelizumab and apatinib, CARES-310 (NCT03764293) observed the longest OS (22.1 months) among all phase III trials for uHCC in 2022. However, the LEAP-002 trial showed that pembrolizumab plus lenvatinib did not meet its dual primary endpoints of OS and PFS as a first-line treatment for patients with uHCC[10]. Similarly, treatment with atezolizumab with cabozantinib in COSMIC-312 significantly improved PFS compared to sorafenib (HR = 0.63, 95% CI 0.44–0.91), while it did not reach statistical significance for OS (HR = 0.90, 95% CI 0.69–1.18)[11].

Based on the above studies, immunotherapy combined with targeted therapy is a widely used first-line therapy for uHCC and can be roughly divided into two types: anti-programmed death 1/ligand-1 (anti-PD-1/L1) antibody combined with vascular endothelial growth factor antibody (VEGF-antibody) and anti-PD-1/L1 antibody combined with VEGFR-targeted tyrosine kinase inhibitor (VEGFR-TKI). The choice of anti-PD-1/L1 antibody + VEGF-antibody (A + A) or anti-PD-1/L1 antibody + VEGFR-TKI (A + T) for the first-line treatment of uHCC is a practical problem that is a challenge for clinicians. Due to the absence of head-to-head clinical trials, we conducted a network meta-analysis (NMA) to indirectly compare A + A and A + T.

2.1. Search strategy and selection criteria

We conducted a network meta-analysis to indirectly compare two different combination therapies, anti-PD-1/L1 antibody plus VEGF-antibody and anti-PD-1/L1 antibody plus VEGFR-TKI. We specified that the interventions in the trial included any anti-PD-1/L1 antibody combined with any kind of VEGF antibody or combined with any kind of VEGFR-TKI. Additionally, to satisfy the establishment of indirect comparison, we also included the study of lenvatinib as the experimental group. The control group can be any immunotherapy or targeted therapy, excluding any local treatment such as hepatic arterial infusion chemotherapy or radiotherapy. The trial must be a phase III randomized controlled trial. In addition, each trial should measure overall survival (OS) as the primary outcome and report data on progression-free survival (PFS), objective response rate (ORR), and treatment-related adverse events (TRAEs). All participants in the study were patients with unresectable or locally advanced HCC who had not undergone systemic therapy before and had no other coexisting cancers. The PubMed, MEDLINE, Embase and Cochrane Library databases were searched from the time of U.S. approval of sorafenib for the treatment of uHCC (2007) to November 6th, 2022, without any language requirements. In addition, conference proceedings of meetings published in several major scientific societies were also manually searched up to November 6th, 2022, including the American Society of Clinical Oncology (ASCO), European Society of Medical Oncology (ESMO), European Association for the Study of the Liver (EASL) and American Association for the Study of Liver Diseases (AASLD). Full search strategies are provided in Table 1. Two independent researchers screened the records according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria and eliminated articles that did not meet the inclusion requirements by reading the title, abstract and full text of the article. When disputes arose between two independent researchers, a third researcher was consulted. The research protocol was registered in PROSPERO (registration code CRD42022375512).

2.2. Data analysis

Table 2 clearly shows the relevant data extracted from the included studies. OS, PFS and ORR were the indicators of the efficacy of the treatment, while the incidence of all grade TRAEs and ≥ 3 TRAEs were used to assess the safety of the treatment. We used hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) to measure the therapy efficacy, including whether it can prolong OS and PFS effectively and whether it can reduce or stabilize the tumour dimension. Relative risks (RRs) and 95% CIs were used to perform the analysis for the risk of TRAEs. For the analysis, we drew forest plots to directly show the comparison results. Moreover, we also calculated the P scores of each treatment, which represents the probability that different treatments are expected to be the best, as a kind of evidence of indirect comparison. For OS, the primary endpoint in our study, we performed a subgroup analysis and reported details in Table 5. The net-meta package in R and STATA was used in this analysis. According to the Cochrane risk of bias assessment tool, there are 7 areas, including selection bias, performance bias, detection bias, attrition bias, reporting bias and other bias, with a judgement of "low risk", "unknown risk" and "high risk" in each project. Detailed information on the risk of bias assessment is provided in Supplementary Fig. 1.

3.1 Screening results and basic characteristics of the included studies

As reported in Fig. 1, 3,277 records were obtained through database search, and 2 were obtained through manually searching conference presentations, of which 215 underwent full-text reading. A total of 209 studies were removed, and 6 were included in the NMA: IMbrave150[12], ORIENT-32[9], COSMIC-312[11], LEAP-002, CARES-310 and REFLECT[7]. IMbrave150 and ORIENT-32 tested A + A and sorafenib, CARES-310 tested A + T and sorafenib, LEAP-002 tested A + T and lenvatinib plus placebo, and REFLECT tested lenvatinib and sorafenib. COSMIC-312 included three arms of treatment; however, since one arm (sorafenib) was available for comparison, only atezolizumab plus cabozantinib was considered in the NMA. There is a network plot of the included studies (Fig. 2).

Overall, 4,012 patients were included in the analysis; among them, 716 patients were treated with A + A, 1,099 patients were treated with A + T, 877 patients were treated with lenvatinib, and 1,320 patients were treated with sorafenib. Sorafenib was the control arm of all the trials, except for the LEAP-002 studies, which investigated the A + T agonist lenvatinib.

In Table 1, we report the characteristics of the studies and participants included in the NMA, and the baseline characteristics of the patient populations are in part due to imbalances in the research. Except for LEAP-002, a double-blind randomized controlled trial, the other trials were open-label randomized controlled trials. Regarding the reporting time for trials, the median follow-up time for the experimental arm of ORIENT-32 (10.0 months) was shorter than that for the other trials: IMbrave150 (17.6 months), COSMIC-312 (15.8 months), LEAP-002 (32.1 months), CARES-310 (14.5 months) and REFLECT (17.6 months). In addition, patients in ORIENT-32 (I: 53 years; C: 54 years) and CARES-310 (I: 58 years; C: 56 years) were younger than those in other trials. There is a huge difference in the patients’ regions. All patients in ORIENT-32 come from Asia, but nationalities varied among the IMbrave150 (I: 40%; C: 41%), COSMIC-312 (I: 28%; C: 29%), LEAP-002 (I: 31%; C: 31%), CARES-310 (I: 83%; C: 83%) and REFLECT (I: 67%; C: 67%) trials. Moreover, we found that the region of the patient was closely related to the proportion of HBV infection; the more patients from Asia, the higher the probability of HBV infection. Almost all patients were Child push score A, except ORIENT-32 (I: 96%; C: 95%), which was due to the inclusion criteria. In each study, a small proportion of patients had macrovascular invasion (MVI), extrahepatic spread (EHS) or both. Only IMbrave150 reported patients’ PD-L1 status. We believe that age, region, aetiology, MVI and EHS are all known as prognostic factors, which may be used as the direction of subgroup discussion.

3.2 Risk of bias assessment

The Cochrane Collaboration's tool suggested that the risk of bias was generally low across all studies. In allocation concealment, blinding of outcome assessment and selective reporting, all studies showed low risk. Due to inadequate information in conference presentations, Leap-002 and CARES-310 showed unclear bias in random sequence generation, incomplete outcome data and other bias, respectively. However, all but LEAP-002 were open label, which made blinding of participants and personnel (performance bias) the greatest concern for the included studies.

3.3 Results of the outcome measures

Under our screening, the outcomes of the included studies were complete, including OS, PFS, ORR and TRAEs (Table 2). We chose RECIST 1.1 as the reference method for PFS and ORR to allow for reproducible comparison across trials.

3.3.1 Results of overall survival

OS was not only the primary or coprimary outcome for all 6 trials but was also the primary endpoint of this NMA. The fixed effects model (I² = 26.6%) suggested that A + A and A + T were not significantly different (HR = 0.84, 95% CI: 0.66–1.06, Fig. 3). However, according to the P scores, which ranked all therapies for their probability of being the most effective in prolonging survival time, A + A (98%) showed better performance than A + T (69%) (Table 3).

To find the source of heterogeneity and provide a direction for further research, we conducted a subgroup analysis on seven terms. A + A showed better results in prolonging OS with higher P scores overall, and it was similar in four subgroups, including region, aetiology, ECOG frequency score, and BCLC grade. However, A + T had a greater probability of prolonged survival time for patients with MVI or EHS (MVI: 84%, EHS: 86%). More details are shown in Table 4.

3.3.2 Results of progression-free survival

A fixed effects model (I² = 0%) was used to analyse PFS. According to P scores for PFS (Table 3), the combination of A + T (91%) is more likely to be the most effective treatment in reducing the risk of progression than A + A (69%). However, there was no significant difference between A + A and A + T (HR = 1.06, 95% CI: 0.87–1.30, Fig. 3).

3.3.3 Results of objective response rate

In consideration of indirect and direct comparisons of ORR (Table 3), A + T reported a 91% probability of being the most effective therapy for objective responses, which was evaluated by a blinded independent radiology committee, followed by A + A (69%). Unfortunately, as with OS and PFS, there was no significant difference between A + A and A + T (OR = 0.82, 95% CI: 0.47–1.46, Fig. 3).

3.3.4 Safety results

We compared the incidence of all grade TRAEs and ≥ 3 TRAEs between the two groups. TRAEs were graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events version 4 (IMbrave150, REFLECT) and 5 (COSMIC-312, ORIENT-32). However, the criteria are not clear in LEAP-002 and CARES-310. Information about the TRAEs of each treatment arm is reported in Table 5. A + A was found to be significantly safer than A + T both for all grade TRAEs and ≥ 3 grade TRAEs (RR = 0.91, 95% CI: 0.84–0.98; RR = 0.64, 95% CI: 0.51–0.79, Fig. 4).

To our knowledge, this is the first NMA to evaluate the clinical efficacy and safety of combining two combination regimens in patients with unresectable or locally advanced hepatocellular carcinoma as the first-line treatment[13, 14]. The VEGF antibodies included in our study were bevacizumab and ramucirumab, which target VEGF-A and VEGFR-2, respectively, and act by inhibiting the biological activity of human VEGF. However, TKIs participating in this NMA include sorafenib, lenvatinib and apatinib, whose targets include FGFR, PDGFR, KIT and the main target VEGFR. Although few studies were included in this study, the six included studies were all high-quality randomized controlled studies with a low risk of bias and similar baseline levels of patients. Sensitivity analysis assessed the robustness of the results and was broadly consistent with the main findings.

This study showed a certain tendency: anti-PD-1/L1 antibody combined with VEGF-antibody is the most effective therapeutic strategy in reducing the risk of death, while anti-PD-1/L1 antibody combined with VEGFR-TKI is more likely to bring longer PFS and higher ORR in patients at the cost of lower safety rate.

OS, as the primary endpoint of this NMA, provided the most objective clinical assessment of efficacy for indirect comparison. Unlike the ORR, it is not subject to differences in endpoint definition and does not suffer from the uncertainty of assessment across studies. The results showed that there was no significant difference in OS between the two groups, which was similar to the results of a recent retrospective study[15]. In our subgroup analysis, the clinical efficacy results were generally consistent with the primary results of patient analyses based on geographic region, ECOG score, and BCLC grade. Most notably, A + T was shown to have a significant advantage in patients with HCV, consistent with the results of a clinical study (mOS: 21 vs. 13 months, p = 0.043)[16]. There is no denying that the basic profile of the trial patients may also lead to erratic results. For example, ORIENT-32 only recruited patients in China, and the HBV infection rate was as high as 94%, while other trials recruited patients from different regions and had low HBV infection rates. Moreover, A + T shows a better ability to address MVI and EHS. Compared with those without MVI, HCC with MVI is usually characterized by worsening liver function, vulnerability to blood metastasis, a higher incidence of complications associated with portal hypertension and intolerance to treatment[17]. Patients with EHS usually have a poor prognosis, but the specific situation is closely related to the site of distant metastasis. Peritoneal metastasis and bile duct involvement in HCC patients treated with ICIs may indicate significantly poor OS but have no significant impact on the prognosis of ORR[18]. In a prospective trial using lenvatinib plus pembrolizumab, EHS was not an independent risk factor for OS, which may be related to front-line therapy in some patients[19]. Thus, we do not deny that the inadequacy of the included studies has contributed to the error in the results, so more high-quality trials should be promoted.

Different from the results of OS, A + T has a better effect in prolonging patients' PFS and reducing the size of solid tumours. The results are reproducible and have been demonstrated not only in vitro[20, 21], but also in clinical studies. A pilot study involving 10 HCC patients with vascular infiltration showed that after treatment with anti-PD-1 antibody combined with VEGFR-TKI, 7 patients achieved PR, 3 patients achieved CR, and all 10 patients underwent surgery with a recurrence-free survival rate of 75% within 12 months[22]. Another study also indicated that this conversion therapy strategy can be effective and safe for hepatectomy after careful preparation and patient evaluation[23]. At the same time, A + T combination treatment of renal cell carcinoma and non-small cell lung cancer also has an excellent tumour reduction effect with a high ORR[24, 25].

A + T showed higher toxicity with significantly higher incidences of all grade TRAEs and ≥ 3 TRAEs than A + A. As an important organ of drug metabolism, the liver is one of the most susceptible organs to cancer immunotherapy, and the liver damage caused by immunotherapy is often referred to as immune-mediated hepatitis (IMH) and often can be diagnosed by the increase in abnormally elevated serum liver enzymes[26]. Table 5 shows that the rate of abnormal elevation of serum liver enzymes in patients in the A + T group was higher than that in the A + A group. It can also be reflected that A + T can effectively improve the effect of immunotherapy. T cells may be overactive, which may lead to the destruction of immune tolerance in the liver, making it susceptible to acute inflammation and hepatitis[27, 28]. To control IMH, the guidelines recommend a detailed examination of the patient's liver condition prior to use of the drug, cessation of immunotherapy as soon as IMH occurs, and the use of corticosteroids as treatment agents[29–31].In the A + A group, the most common TRAEs were hypertension and proteinuria, which were closely related to the nephrotoxicity caused by VEGF antibodies[32, 33]. For the sake of patient safety, if patients suffer from complications such as diabetes or kidney disease, comprehensive renal function evaluation should be performed before A + A therapy, and patients’ hypertension must be well controlled[33].

This NMA also has limitations that need further consideration and exploration. First, the more complete the data presented in the report, the more robust the indirect comparisons, especially in the subgroup analysis. However, among the included trials, the data of two trials were obtained from the conference presentation, and the data were incomplete and possibly incorrect, which would eventually lead to the deviation of the estimation of the relative effect. In addition, the median follow-up time of each trial was different, which may have affected the final evaluation. In addition, the open-label nature of the trial was not an issue for survival endpoints OS but may have influenced other endpoints, such as ORR and TRAEs. Hence, more quality prospective studies are needed to better evaluate the optimal treatment. Second, a meta-analysis found that the Child‒Pugh score was subjective to a certain extent, and the ALBI score could better stratify patients[34]. Therefore, how to conduct more accurate stratification and precise treatment for patients before the implementation of treatment may be a major direction of our future research. Third, the results from a study in a mouse model of advanced HCC suggest that the use of high doses of sorafenib blocks VEGF signalling, leading to increased hypoxia and stromal cell derived Factor 1-mediated immunosuppressive cell recruitment and leading to drug resistance or reduced efficacy[35]. Therefore, determining the best dose or combination of drugs is also an area for further exploration. Last, because combination therapy may affect the pattern of tumour recurrence, we also focused on the effect of subsequent therapy. A recent study showed that discontinuation of atezolizumab plus bevacizumab in the absence of other therapeutic adjustments was associated with poor outcomes, including shorter OS and more AEs[36]. However, only 3 included studies described it, and TKIs played a major role (Leap-002: 34.9%, COSMIC-312: 14%, and CARES-310: 29.8%), which could not be compared. Thus, the search for the best follow-up regimen or drug use sequence will become an important challenge in the management of hepatocellular carcinoma.

Authors' contribution

JEY contributed to the design and conception of the study. YWZ and BBL carried out the collection and assembly of data. YWZ and YXZ performed the data analysis and interpretation. YWZ wrote the manuscript, JJL revised the manuscript, and then JEY gave the final approval of the manuscript.

Funding

The study was supported by grants from Natural Science Fund of Zhejiang Province (LTGY23H160010), Medical and Health Science and Technology Program of Zhejiang Province (2021KY087) and Natural Science Fund of Zhejiang Province - Exploration project (LQ20H160005).

Conflicts of interest statement

We declare that we have no financial or personal relationships with other people or organisations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Data availability

All data generated or analysed during this study are included in this published article and its Supplementary Information files.

Conflicts of interest statement: The authors declare that they have no competing interests.

Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49. https://doi.org/10.3322/caac.21660.
Singal AG, Lampertico P, Nahon P. Epidemiology and surveillance for hepatocellular carcinoma: New trends. J Hepatol. 2020;72(2):250-61. https://doi.org/10.1016/j.jhep.2019.08.025.
Ferlay J, Colombet M, Soerjomataram I, et al. Cancer statistics for the year 2020: An overview. Int J Cancer. 2021. https://doi.org/10.1002/ijc.33588.
Llovet JM, Ricci S, Mazzaferro V, et al. Sorafenib in advanced hepatocellular carcinoma. N Engl J Med. 2008;359(4):378-90. https://doi.org/10.1056/NEJMoa0708857.
Cheng AL, Kang YK, Chen Z, et al. Efficacy and safety of sorafenib in patients in the Asia-Pacific region with advanced hepatocellular carcinoma: a phase III randomised, double-blind, placebo-controlled trial. Lancet Oncol. 2009;10(1):25-34. https://doi.org/10.1016/S1470-2045(08)70285-7.
Roderburg C, Ozdirik B, Wree A, Demir M, Tacke F. Systemic treatment of hepatocellular carcinoma: from sorafenib to combination therapies. Hepat Oncol. 2020;7(2):HEP20. https://doi.org/10.2217/hep-2020-0004.
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. https://doi.org/10.1016/S0140-6736(18)30207-1.
Galle PR, Finn RS, Qin S, et al. Patient-reported outcomes with atezolizumab plus bevacizumab versus sorafenib in patients with unresectable hepatocellular carcinoma (IMbrave150): an open-label, randomised, phase 3 trial. Lancet Oncol. 2021;22(7):991-1001. https://doi.org/10.1016/S1470-2045(21)00151-0.
Ren Z, Xu J, Bai Y, et al. Sintilimab plus a bevacizumab biosimilar (IBI305) versus sorafenib in unresectable hepatocellular carcinoma (ORIENT-32): a randomised, open-label, phase 2-3 study. Lancet Oncol. 2021;22(7):977-90. https://doi.org/10.1016/S1470-2045(21)00252-7.
Finn RS, Kudo M, Merle P, et al. Primary results from the phase III LEAP-002 study: Lenvatinib plus pembrolizumab versus lenvatinib as first-line (1L) therapy for advanced hepatocellular carcinoma (aHCC). Annals of Oncology. 2022;33(7):S1401-S. https://doi.org/10.1016/j.annonc.2022.08.031.
Kelley RK, Rimassa L, Cheng AL, et al. Cabozantinib plus atezolizumab versus sorafenib for advanced hepatocellular carcinoma (COSMIC-312): a multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 2022;23(8):995-1008. https://doi.org/10.1016/S1470-2045(22)00326-6.
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. https://doi.org/10.1016/j.jhep.2021.11.030.
Liu K, Zhu Y, Zhu H. Immunotherapy or targeted therapy as the first-line strategies for unresectable hepatocellular carcinoma: A network meta-analysis and cost-effectiveness analysis. Front Immunol. 2022;13:1103055. https://doi.org/10.3389/fimmu.2022.1103055.
Rizzo A, Ricci AD, Fanizzi A, et al. Immune-Based Combinations versus Sorafenib as First-Line Treatment for Advanced Hepatocellular Carcinoma: A Meta-Analysis. Curr Oncol. 2023;30(1):749-57. https://doi.org/10.3390/curroncol30010057.
Zeng H, Xu Q, Wang J, et al. The effect of anti-PD-1/PD-L1 antibodies combined with VEGF receptor tyrosine kinase inhibitors versus bevacizumab in unresectable hepatocellular carcinoma. Front Immunol. 2023;14:1073133. https://doi.org/10.3389/fimmu.2023.1073133.
Lei J, Yang S, Chen B, et al. Efficacy and Safety of Tyrosine Kinase Inhibitors Alone or Combination with Programmed Death-1 Inhibitors in Treating of Hepatitis C-Related Hepatocellular Carcinoma. J Hepatocell Carcinoma. 2023;10:357-67. https://doi.org/10.2147/JHC.S392347.
Tao ZW, Cheng BQ, Zhou T, Gao YJ. Management of hepatocellular carcinoma patients with portal vein tumor thrombosis: A narrative review. Hepatobiliary Pancreat Dis Int. 2022;21(2):134-44. https://doi.org/10.1016/j.hbpd.2021.12.004.
Yao J, Zhu X, Wu Z, et al. Efficacy and safety of PD-1 inhibitor combined with antiangiogenic therapy for unresectable hepatocellular carcinoma: A multicenter retrospective study. Cancer Med. 2022;11(19):3612-22. https://doi.org/10.1002/cam4.4747.
Wu CJ, Lee PC, Hung YW, et al. Lenvatinib plus pembrolizumab for systemic therapy-naive and -experienced unresectable hepatocellular carcinoma. Cancer Immunol Immunother. 2022;71(11):2631-43. https://doi.org/10.1007/s00262-022-03185-6.
Shigeta K, Datta M, Hato T, et al. Dual Programmed Death Receptor-1 and Vascular Endothelial Growth Factor Receptor-2 Blockade Promotes Vascular Normalization and Enhances Antitumor Immune Responses in Hepatocellular Carcinoma. Hepatology. 2020;71(4):1247-61. https://doi.org/10.1002/hep.30889.
Fukumura D, Kloepper J, Amoozgar Z, Duda DG, Jain RK. Enhancing cancer immunotherapy using antiangiogenics: opportunities and challenges. Nat Rev Clin Oncol. 2018;15(5):325-40. https://doi.org/10.1038/nrclinonc.2018.29.
Zhang W, Hu B, Han J, et al. Surgery After Conversion Therapy With PD-1 Inhibitors Plus Tyrosine Kinase Inhibitors Are Effective and Safe for Advanced Hepatocellular Carcinoma: A Pilot Study of Ten Patients. Front Oncol. 2021;11:747950. https://doi.org/10.3389/fonc.2021.747950.
Zhu XD, Huang C, Shen YH, et al. Downstaging and Resection of Initially Unresectable Hepatocellular Carcinoma with Tyrosine Kinase Inhibitor and Anti-PD-1 Antibody Combinations. Liver Cancer. 2021;10(4):320-9. https://doi.org/10.1159/000514313.
Iinuma K, Yamada T, Kameyama K, et al. The Efficacy and Safety of Immune Checkpoint Inhibitor and Tyrosine Kinase Inhibitor Combination Therapy for Advanced or Metastatic Renal Cell Carcinoma: A Multicenter Retrospective Real-World Cohort Study. Cancers (Basel). 2023;15(3). https://doi.org/10.3390/cancers15030947.
Yu L, Xu J, Qiao R, et al. Efficacy and safety of anlotinib combined with PD-1/PD-L1 inhibitors as second-line and subsequent therapy in advanced small-cell lung cancer. Cancer Med. 2022. https://doi.org/10.1002/cam4.5360.
Liu Z, Zhu Y, Xie H, Zou Z. Immune-mediated hepatitis induced by immune checkpoint inhibitors: Current updates and future perspectives. Front Pharmacol. 2022;13:1077468. https://doi.org/10.3389/fphar.2022.1077468.
Gudd CLC, Possamai LA. The Role of Myeloid Cells in Hepatotoxicity Related to Cancer Immunotherapy. Cancers (Basel). 2022;14(8). https://doi.org/10.3390/cancers14081913.
Gudd CLC, Au L, Triantafyllou E, et al. Activation and transcriptional profile of monocytes and CD8(+) T cells are altered in checkpoint inhibitor-related hepatitis. J Hepatol. 2021;75(1):177-89. https://doi.org/10.1016/j.jhep.2021.02.008.
Brahmer JR, Abu-Sbeih H, Ascierto PA, et al. Society for Immunotherapy of Cancer (SITC) clinical practice guideline on immune checkpoint inhibitor-related adverse events. J Immunother Cancer. 2021;9(6). https://doi.org/10.1136/jitc-2021-002435.
Schneider BJ, Naidoo J, Santomasso BD, et al. Management of Immune-Related Adverse Events in Patients Treated With Immune Checkpoint Inhibitor Therapy: ASCO Guideline Update. J Clin Oncol. 2021;39(36):4073-126. https://doi.org/10.1200/JCO.21.01440.
De Martin E, Michot JM, Rosmorduc O, Guettier C, Samuel D. Liver toxicity as a limiting factor to the increasing use of immune checkpoint inhibitors. JHEP Rep. 2020;2(6):100170. https://doi.org/10.1016/j.jhepr.2020.100170.
Zhao D, Long X, Fan H, Wang J. Effects of hepatic or renal impairment on the pharmacokinetics of immune checkpoint inhibitors. Am J Cancer Res. 2022;12(11):4892-903.
Estrada CC, Maldonado A, Mallipattu SK. Therapeutic Inhibition of VEGF Signaling and Associated Nephrotoxicities. J Am Soc Nephrol. 2019;30(2):187-200. https://doi.org/10.1681/ASN.2018080853.
Tian BW, Yan LJ, Ding ZN, et al. Evaluating liver function and the impact of immune checkpoint inhibitors in the prognosis of hepatocellular carcinoma patients: A systemic review and meta-analysis. Int Immunopharmacol. 2023;114:109519. https://doi.org/10.1016/j.intimp.2022.109519.
Chen Y, Ramjiawan RR, Reiberger T, et al. CXCR4 inhibition in tumor microenvironment facilitates anti-programmed death receptor-1 immunotherapy in sorafenib-treated hepatocellular carcinoma in mice. Hepatology. 2015;61(5):1591-602. https://doi.org/10.1002/hep.27665.
Tokunaga T, Tateyama M, Kondo Y, et al. Therapeutic Modifications without Discontinuation of Atezolizumab Plus Bevacizumab Therapy Are Associated with Favorable Overall Survival and Time to Progression in Patients with Unresectable Hepatocellular Carcinoma. Cancers (Basel). 2023;15(5). https://doi.org/10.3390/cancers15051568.

Table 1 Characteristics of studies and participants included in the all-trials evidence network

Group	Anti-PD-1/L1 antibody + VEGF-inhibitor		Anti PD-1/L1 antibody + VEGFR-TKI						Monotherapy
Trial, Author et al (Year)	IMbrave150, Finn et al (2022)	ORIENT-32, Zheng et al (2021)	COSMIC-312, Robin et al (2022)				CARES-310, Shu et al (2022)	LEAP-002, Richard et al (2022)	REFLECT, Masatoshi et al(2018)
Network Intervention (n)	Atezolizumab + Bevacizumab (336)	Sintilimab + Bevacizumab biosimilar (380)	PITT	Atezolizumab + Cabozantinib (250)	ITT	Atezolizumab + Cabozantinib (432)	Camrelizumab + Rivoceranib (272)	Lenvatinib + Pembrolizumab (395)	Lenvatinib (478)
Network Comparator (n)	Sorafenib (165)	Sorafenib (191)	PITT	Sorafenib (122)	ITT	Sorafenib (217)	Sorafenib (271)	Lenvatinib + placebo (399)	Sorafenib (476)
Design	Open-label randomized, controlled trial	Open-label randomized, controlled trial	Open-label randomized, controlled trial				Open label randmized, controlled trial	Double-blind randmized, controlled trial	Open-label randomized, controlled trial
Age, mean or median (y)	I: 64; C: 66	I: 53; C: 54	I: 65; C: 64		I: 64; C: 64		I: 58; C:56	I: 66; C: 66	I: 63; C: 62
Age ≥ 65 years (%)	I: 48; C: 55	NA	NA		NA		NA	I: 53; C: 54	I: 44; C: 41
Sex, male (%)	I: 82; C: 83	I: 88; C: 90	I: 86; C: 88		I: 83; C: 86		I: 84; C: 85	I: 80; C: 82	I: 85; C: 84
Follow-up, median (months)	I: 17.6; C: 10.4	I: 10.0; C: 10.0	15.8		13.3		14.5	32.1	I: 17.6; C: 10.4
Region, Asia (%)	I: 56; C: 58	I: 100; C: 100	I: 27; C: 30		I: 29; C: 33		NA	NA	I: 56; C: 58
ECOG PS, 0 (%)	I: 62; C: 62	I: 48; C: 48	I: 65; C: 61		I: 64; C: 66		I: 44; C: 43	I: 68; C: 68	I: 64; C: 63
ECOG PS, 1 (%)	I: 38; C: 38	I: 52; C: 52	I: 35; C: 28		I: 36; C: 34		I: 56; C: 57	I: 32; C: 32	I: 36; C: 37
Etiology, HBV (%)	I: 49; C: 46	I: 94; C: 94	I: 30; C: 29		I: 29; C: 30		I: 77; C: 73	I: 49; C: 49	I: 53; C: 48
Etiology, HCV (%)	I: 21; C: 22	I: 2; C: 4	I: 28; C: 28		I: 32; C: 31		I: 8; C: 11	I: 33; C: 22	I: 19; C: 26
Etiology, non-viral (%)	I: 30; C: 32	NA	I: 42; C: 43		I: 39; C: 40		I: 15; C: 17	I: 63; C: 59	NA
AFP ≥ 400 µg/L (%)	I: 38; C: 37	I: 43; C:42	I: 34; C: 30		I: 38; C: 30		I: 35; C: 37	I: 30; C: 33	NA
Child Pugh, A (%)	I: 99; C: 100	I: 96; C: 95	I: 100; C: 100		I: 100; C: 100		I: 100; C: 100	I: 99.5; C: 99.5	I: 99; C: 99
MVI (%)	I: 38; C: 43	I: 28; C: 26	I: 34; C: 31		I: 31; C: 28		I: 15; C: 19	I: 18; C: 16	I: 23; C: 19
EHS (%)	I: 63; C: 56	I: 73; C: 75	I: 54; C: 57		I: 54; C: 56		I: 64; C: 66	I: 63; C: 61	I: 61; C: 62
BCLC, B (%)	I: 15; C: 15	I: 15; C: 14	I: 33; C: 34		I: 32; C: 33		I: 14; C: 15	I: 22; C: 24	I: 22; C: 19
BCLC, C (%)	I: 82 C: 81	I: 85; C: 86	I: 67; C: 66		I: 68; C: 67		I: 86; C: 85	I: 79; C: 76	I: 78 C: 81
PD-L1 ≥ 1 (%)	I: 64; C: 57	NA	NA		NA		NA	NA	NA
Prior local therapy (%)	I: 50; C: 52	I: 81; C: 85	I: 65; C: 64		I: 38; C: 39		I: 59; C: 55	I: 49; C: 51	NA

Asia is exluded Japan. ITT=intention-to-treat; PITT= progression-free survival ITT. MVI=Macrovascular invasion; EHS=Extrahepatic metastasis.

Table 2 Outcomes of studies included in the network Meta-analysis

Trial Author et al (Year)	Treatments	Median OS, months (95% CI)	HR (95% CI)	Median PFS, months (95% CI)	HR (95% CI)	ORR% (95% CI)^※
IMbrave150 Finn et al (2022)	Atezolizumab + Bevacizumab	19.2 (17.0-23.7)	0.66 (0.52-0.85)	6.9 (5.7-8.6)	0.65 (0.53-0.81)	30 (25-35)
	Sorafenib
ORIENT-32 Zheng et al (2021)	Sintilimab + Bevacizumab biosimilar	13.4 (11.4-16.9)	0.57 (0.43–0.75)	4.3 (4.0-5.6)	0.56 (0.46–0.70)	11 (7-17)
	Sorafenib
COSMIC-312 Robin et al (2022)	Atezolizumab + Cabozantinib	NR	0.90 (96% CI 0.69–1.18)	4.6(4.1–5.7)	0.63 (99% CI 0.44–0.91)	21 (17–25)
	Sorafenib
CARES-310 Shu et al (2022)	Camrelizumab + Rivoceranib	10.4 (8.5-NR)	0.62 (0.49-0.80)	2.8 (2.7–3.2)	0.52 ( 0.41-0.65)	4 (2–8)
	Sorafenib
LEAP-002 Richard et al (2022)	Lenvatinib + Pembrolizumab	15.4 (96% CI 13.7–17.7)§	0.84 (0.71-1.00)	6.8 (99% CI 5.6–8.3)＊	0.87 (0.73-1.02)	11 (8.1-14.2)^в
	Lenvatinib + placebo
REFLECT Masatoshi et al (2018)	Lenvatinib	15.5 (96% CI 12.1–NE)§	0.92 (0.79-1.06)	4.2 (99% CI 2.8–7.0)＊	0.66 (0.57-0.77)	4 (1.6-7.1)^в
	Sorafenib

^§: ITT, ^＊: PITT; ^※:IMbrave150 were investigator assessed, others were BIRC；^в:according to ITT population.

Table 3 Ranking of the available treatment according to their probability of being the best

Overall survival		Progression-free survival		Objective response rate
Treatment	P-score	Treatment	P-score	Treatment	P-score
A+A	97.57%	A+T	90.16%	A+T	91.47%
A+T	68.97%	A+A	69.31%	A+A	69.17%
LEN	31.75%	LEN	40.53%	LEN	39.36%
SOR	1.71%	SOR	00.00%	SOR	00.00%

Probability (P-score) for each treatment to be the best in terms of overall survival, progression-free survival and objective response rate.

Table 4 Subgroup analysis of overall survival

subgroup analysis

Region

AFP

MVI

EHS

Etiology

ECOG

BCLC

Asia

Other

< 400

> 400

(+)

(-)

(+)

(-)

HBV

HCV

PS=0

PS=1

B

C

Included trials

1；3；4；5；6

1；2；4；5

1；2；3；4；5；6

1；3；4；5；6

1；2；4；5；6

A+A

vs.

A+T

0.92 (0.59,1.43)

0.84 (0.27,2.61)

1.03 (0.67,1.58)

1.07 (0.68,1.66)

1.13 (0.60,2.11)

0.89 (0.62,1.30)

1.04 (0.72,1.51)

0.87 (0.50,1.52)

0.93 (0.69,1.25)

0.49 (0.26,0.91)

0.94 (0.67,1.33)

0.47 (0.17,1.35)

0.92 (0.70,1.20)

Ranking

P-score(%)

A+A 85.49

A+A

75.93

A+T 74.37

A+T

86.74

A+T

84.40

A+T 87.68

A+T 85.99

A+A 78.43

A+A 89.33

A+A

99.43

A+A 85.85

A+A 96.28

A+A 91.22

A+T 78.06

A+T

67.95

A+A

66.21

A+A

75.98

A+A

66.73

A+A 74.67

A+A 74.57

A+T 55.93

A+T 77.03

A+T

51.02

A+T 78.09

A+T 50.58

A+T

75.25

LEN 35.22

SOR

42.08

LEN 58.40

LEN 23.80

LEN 42.10

LEN 34.51

LEN 38.14

LEN 47.35

LEN 32.99

LEN 30.25

LEN 34.26

LEN 32.11

LEN 32.03

SOR 1.23

LEN

14.03

SOR 1.02

SOR 13.48

SOR 6.76

SOR 3.14

SOR 1.30

SOR 18.29

SOR

0.65

SOR 19.30

SOR 1.80

SOR 21.03

SOR 1.50

Trials: 1-IMbrave150, 2-ORIENT32, 3-COSMIC312, 4-CARES310, 5-LEAP002, 6-REFLECT

Table 5 Descriptive incidence of treatments related adverse events according to NCTCA

Trial, Author et al (Year)	IMbrave150, Finn et al (2022)		ORIENT-32, Zheng et al (2021)		COSMIC-312, Robin et al (2022)		CARES-310, Shu et al (2022)		LEAP-002, Richard et al (2022)		REFLECT, Masatoshi et al (2018)
Treatment (n)	Atezolizumab + Bevacizumab (329)	Sorafenib (156)	Sintilimab + Bevacizumab biosimilar (380)	Sorafenib (185)	Atezolizumab + Cabozantinib (429)	Sorafenib (207)	Camrelizumab + Rivoceranib (272)	Sorafenib (269)	Lenvatinib + Pembrolizumab (395)	Lenvatinib + placebo (395)	Lenvatinib (476)	Sorafenib (475)
TRAEs (all Grade)	284 (86%)	148 (95%)	337 (89%)	173 (94%)	399 (93%)	186 (90%)	265 (97%)	249 (93%)	381 (97%)	378 (96%)	447 (94%)	452 (95%)
TRAEs (≥ 3 Grade)	149 (45%)	73 (47%)	131 (34%)	68 (37%)	236 (55%)	68 (33%)	220 (81%)	141 (52%)	247 (63%)	227 (57%)	270 (57%)	231 (49%)
Proteinuria (all Grade)	95 (29%)	8 (5%)	154 (41%)	27 (15%)	28 (7%)	12 (6%)	134 (49%)	72 (27%)	121 (31%)	138 (35%)	NA	NA
Proteinuria (≥ 3 Grade)	3 (4%)	1 (<1%)	18 (5%)	2 (1%)	7 (2%)	0	16 (6%)	5 (2%)	NA	NA	NA	NA
AST increased (all Grade)	54 (16%)	12 (8%)	81 (21%)	42 (23%)	92 (21%)	17 (8%)	147 (54%)	99 (37%)	87 (22%)	61 (15%)	NA	NA
AST increased (≥ 3 Grade)	17 (5%)	5 (3%)	4 (1%)	5 (3%)	28 (7%)	5 (2%)	45 (17%)	14 (5%)	NA	NA	NA	NA
Platelet count decreased (all Grade)	34 (10%)	15 (10%)	99 (26%)	40 (22%)	46 (11%)	13 (6%)	126 (46%)	89 (33%)	83 (21%)	83 (21%)	87 (18%)	58 (12%)
Platelet count decreased (≥ 3 Grade)	9 (3%)	1 (<1%)	22 (6%)	2 (1%)	8 (2%)	2 (1%)	32 (12%)	4 (2%)	NA	NA	26 (5%)	16 (3%)
Hypertension (all Grade)	93 (28%)	31 (20%)	108 (28%)	27 (15%)	82 (19%)	32 (15%)	189 (70%)	116 (43%)	171 (43%)	185 (47%)	201 (42%)	144 (30%)
Hypertension (≥ 3 Grade)	39 (12%)	14 (9%)	48 (13%)	9 (5%)	30 (7%)	13 (6%)	102 (38%)	40 (15%)	NA	NA	111 (23%)	68 (14%)
ALT increased (all Grade)	40 (12%)	4 (3%)	63 (17%)	35 (19%)	96 (22%)	12 (6%)	127 (47%)	80 (30%)	76 (19%)	59 (5%)	NA	NA
ALT increased (≥ 3 Grade)	8 (2%)	0	4 (1%)	2 (1%)	27 (6%)	4 (2%)	35 (13%)	8 (3%)	NA	NA	NA	NA
Hypothyroidism (all Grade)	33 (10%)	2 (1%)	47 (12%)	11 (6%)	83 (19%)	4 (2%)	58 (21%)	16 (6%)	158 (40%)	141 (36%)	78 (16%)	8 (2%)
Hypothyroidism (≥ 3 Grade)	0	0	0	0	0	0	0	0	NA	NA	0	0
Diarrhoea (all Grade)	36 (11%)	68 (44%)	24 (6%)	63 (34%)	181 (42%)	87 (42%)	83 (31%)	105 (39%)	159 (40%)	134 (34%)	184 (39%)	220 (46%)
Diarrhoea (≥ 3 Grade)	3 (1%)	6 (4%)	2 (<1%)	3 (2%)	15 (3%)	2 (1%)	6 (2%)	14 (5%)	NA	NA	20 (4%)	20 (4%)
PPE syndrome (all Grade)	5 (2%)	75 (48%)	1 (<1%)	102 (55%)	181 (42%)	92 (44%)	102 (38%)	163 (61%)	131 (33%)	121 (31%)	128 (27%)	249 (52%)
PPE syndrome (≥ 3 Grade)	0	13 (8%)	0	22 (12%)	34 (8%)	17 (8%)	33 (12%)	41 (15%)	NA	NA	14 (3%)	54 (11%)

AST=aspartate aminotransferase; ALT=alanine aminotransferase; PPE=palmar-plantar erythrodysaesthesia. NA= unavailable.

No competing interests reported.

Supplementarymaterial.docx

Comparative efficacy and safety of anti-PD-1/L1 antibody plus anti-VEGF antibody and anti-PD-1/L1 antibody plus VEGFR-targeted tyrosine kinase inhibitor as first-line therapy for unresectable hepatocellular carcinoma (uHCC): a systematic review and network meta- analysis

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

1. Introduction

2. Methods

2.1. Search strategy and selection criteria

2.2. Data analysis

3. Results

3.1 Screening results and basic characteristics of the included studies

3.2 Risk of bias assessment

3.3 Results of the outcome measures

3.3.1 Results of overall survival

3.3.2 Results of progression-free survival

3.3.3 Results of objective response rate

3.3.4 Safety results

4. Discussion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1