Protocol for a Systematic Review: Camrelizumab plus Apatinib in Solid Tumors

Protocol for a Systematic Review: Camrelizumab plus Apatinib in Solid Tumors | 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 Protocol for a Systematic Review: Camrelizumab plus Apatinib in Solid Tumors Mahmoud Rashad Kamal, Maria Dulce Estêvão, Chun Hoong Wong, Maria Azizian, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6063875/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: Solid tumors represent a significant global health burden, with limited treatment options for advanced or metastatic stages. The combination of camrelizumab, a programmed cell death protein-1 (PD-1) inhibitor, and apatinib, a vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitor, has shown promise in preclinical and early-phase clinical studies. However, the efficacy and safety of this combination therapy remain unclear. This systematic review aims to synthesize the available evidence on the use of camrelizumab plus apatinib in solid tumors to inform clinical practice and guide future research. Methods: A comprehensive search of electronic databases, including PubMed, Scopus, Web of Science, and ClinicalTrials.gov, will be conducted from January 2018 to the present. Randomized controlled trials, non-randomized controlled trials, cohort studies, and single-arm trials evaluating camrelizumab plus apatinib in patients with advanced or metastatic solid tumors will be included. The primary outcomes will include the objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). The secondary outcomes will focus on the incidence and severity of adverse events (AEs). Two reviewers will independently screen studies, extract data, and assess the risk of bias using standardized tools. Data will be synthesized narratively and, if appropriate, through meta-analysis. Discussion: This systematic review will provide a comprehensive evaluation of the efficacy and safety of camrelizumab plus apatinib in solid tumors. The findings will inform clinical decision-making, highlight gaps in the current evidence, and guide the design of future studies. By synthesizing the available data, this review aims to contribute to the development of more effective treatment strategies for patients with advanced or metastatic solid tumors. Camrelizumab Apatinib Combination Therapy Immune Checkpoint Inhibitors Anti-Angiogenic Therapy Introduction Cancer encompasses a diverse range of diseases, broadly classified into solid tumors and hematologic malignancies. Solid tumors arise from abnormal cell growth in specific organs or tissues, forming discrete masses. Solid tumors represent a significant global health challenge, and approximately 80% of all tumor types are derived from a subset of solid organs, including the breast, prostate, lung, colon, and ovary [ 1 ]. Solid cancers originate mainly from epithelia, develop as distinct lesions capable of invading surrounding structures and metastasizing to distant sites. These tumors account for more than 85% of all cancer cases worldwide and are a leading cause of cancer-related morbidity and mortality [ 1 ]. In 2022, an estimated 20.0 million new cancer cases were diagnosed globally, with solid tumors such as lung, breast, colorectal, and prostate cancers being the most prevalent [ 2 ]. The clinical management of solid tumors is complex, particularly in advanced or metastatic stages, where treatment options are often limited, and the prognosis remains poor. Traditional therapies, including surgery, chemotherapy, and radiation, have been the cornerstone of cancer treatment for decades. However, these approaches are often associated with significant toxicity, limited efficacy in advanced disease, and the development of treatment resistance [ 1 ]. For example, in hepatocellular carcinoma (HCC), systemic therapies such as sorafenib and lenvatinib have shown modest improvements in overall survival, underscoring the need for more effective treatments [ 3 ]. In recent years, targeted therapies and immunotherapy have transformed the landscape of cancer treatment. Immune checkpoint inhibitors (ICIs), such as programmed cell death protein-1 (PD-1) inhibitors, have demonstrated remarkable efficacy in a variety of solid tumors by enhancing the body's immune response against cancer cells [ 4 ]. Camrelizumab, a humanized PD-1 inhibitor, has shown promising activity in cancers such as hepatocellular carcinoma (HCC), esophageal squamous cell carcinoma (ESCC), and non-small cell lung cancer (NSCLC) [5, 6 ]. Similarly, antiangiogenic agents such as apatinib, which target vascular endothelial growth factor receptor-2 (VEGFR-2), effectively inhibit tumor angiogenesis and growth, particularly in gastric cancer and hepatocellular carcinoma (HCC) [7, 8 ]. The combination of camrelizumab and apatinib represents a novel therapeutic strategy that leverages the synergistic effects of immune modulation and angiogenesis inhibition. Preclinical studies suggest that antiangiogenic agents can increase the efficacy of ICIs by normalizing the tumor vasculature, promoting immune cell infiltration, and reducing the levels of immunosuppressive factors within the tumor microenvironment [ 9 ]. Early-phase clinical trials have reported encouraging results for this combination, with improved response rates and survival outcomes in patients with advanced solid tumors [ 10 ]. However, the evidence remains fragmented, and a comprehensive synthesis of the available data is needed to evaluate the efficacy and safety of this combination therapy. This systematic review aims to address this gap by synthesizing the existing evidence on the use of camrelizumab plus apatinib in solid tumors. By evaluating outcomes such as the objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and adverse events (AEs), this review provides critical insights into the potential benefits and risks of this combination therapy. These findings will inform clinical practice, guide future research, and contribute to ongoing efforts to improve outcomes for patients with solid tumors. OBJECTIVES To assess the efficacy and safety of camrelizumab (a PD-1 inhibitor) plus apatinib in patients with solid cancer. Methods Criteria for considering studies for this review Types of studies Randomized controlled trials (RCTs), non-randomized controlled trials, cohort studies, and single-arm trials will be included. Types of participants Patients with advanced or metastatic solid tumors with no population restrictions (age, sex, race/ethnicity, geographic origin, or others). Types of interventions Combination therapy using camrelizumab (an anti-PD-1 monoclonal antibody) and apatinib (a VEGFR-2 inhibitor). Comparator Standard therapies (e.g., radiation, chemotherapy, monotherapy with ICIs or antiangiogenic agents, placebo) or other treatments. Types of outcome measures Primary outcomes Progression-free survival (PFS): Time from enrollment to the first documented progression of disease or death. Objective response rate (ORR): Proportion of patients who achieve a complete or partial response according to the RECIST criteria. Secondary outcomes Overall survival (OS): Time from enrollment to death from any cause Adverse events (AEs) and serious adverse events (SAEs) will be reported. The severity of AEs will be assessed according to the National Cancer Institute-Common Terminology Criteria for Adverse Events (NCI‐CTCAE, 2010), if available. If severity grading is not provided, adverse event data will still be included, and the grading system used will be noted where applicable. Exclusion Criteria The following will be excluded: Animal studies, in vitro experiments, and basic research. Conference abstracts, reviews, commentaries, and case reports. Studies with aggregate reporting of results from multiple populations or disease cohorts. Duplicate publications. Literature from which valid outcome data cannot be extracted. Search methods for the identification of studies We will search the following databases from 2018 to the present, as the combination of camrelizumab and apatinib was not available (even in clinical trials) before 2018: PubMed Web of Science Scopus ClinicalTrials.gov (only completed trials will be included) Data collection and analysis Selection of studies The study selection process will follow the PRISMA 2020 diagram [ 11 ]. First, studies will be imported into Covidence, which facilitates the selection process for the reviewers. The screening process will include screening the titles and abstracts and reviewing the full texts of the eligible articles. Two independent reviewers (CH, MDE) will systematically perform the selection process. The selected articles will be divided into three categories: included, excluded, and uncertain. Any disagreements among reviewers will be resolved through discussion or by consulting a third reviewer (MR). Data extraction and management Two independent reviewers (MA, MM) will collect information from the included studies. This process will be conducted by using a standardized data extraction template. The following information will be extracted: Reference details (authors, year of publication, title, country, DOI, funding source); Study characteristics (study design and objectives, sample size, locations, follow-up duration); Population characteristics (age, sex, race/ethnicity, type of cancer, previous treatments); Interventions (intervention group, intervention dose, control group, treatment duration); Outcomes (primary and secondary outcomes, including PFS, ORR, OS, and the number of SAEs; numerical outcomes will include the exact figures and units). Assessment of risk of bias in included studies The risk of bias in the included studies will be assessed independently by two reviewers (MM, MR) via standardized tools appropriate for the study designs, as presented below. Discrepancies will be resolved through discussion or, if necessary, by consulting a third reviewer (MA). 1. Tools for Risk of Bias Assessment Randomized Controlled Trials (RCTs) : The Cochrane Risk of Bias Tool (RoB 2) will be used to assess the following domains: Randomization process. Deviations from intended interventions. Missing outcome data. Measurement of the outcome. Selection of the reported result. Each domain will be judged as "low risk," "some concerns," or "high risk" of bias. Non-Randomized Studies : The Risk of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool will be used to assess the following domains: Bias due to confounding factors. Bias on the selection of participants. Bias in the classification of interventions. Bias due to deviations from intended interventions. Bias due to missing data. Bias in the measurement of outcomes. Bias in the selection of the reported result. Each domain will be judged as "low risk," "moderate risk," "serious risk," or "critical risk" of bias. Single-Arm Trials : The NIH Quality Assessment Tool for Before-After (Pre-Post) Studies with No Control Group will be used to assess methodological quality. The key domains include the following: Clear study question. Appropriate eligibility criteria. Consistent and reliable outcome measures. Appropriate statistical analysis. Minimization of bias. Each domain will be judged as "yes," "no," or "not applicable." 2. Process for Risk of Bias Assessment Pilot testing : A pilot test will be conducted on a sample of studies to ensure consistency between reviewers. Independent assessment : Two reviewers independently assess the risk of bias for each study. Resolution of Discrepancies : Disagreements will be resolved through discussion or by consulting a third reviewer. Summary of Findings : The risk of bias assessments will be summarized in a table and incorporated into the results and discussion sections of the review. 3. Reporting The risk of bias assessments will be presented as follows: Risk of Bias Tables: Summarizing judgments for each domain. Risk of Bias Graphs: Visualizing the overall risk of bias across studies. Sensitivity Analysis: If applicable, studies with a high risk of bias will be excluded to assess their impact on the results. Measures of treatment effect Descriptive statistics will be conducted to describe the characteristics of all eligible studies. Meta-analysis will be performed if enough studies are obtained. For dichotomous outcomes, including the ORR and adverse events, risk ratios (RRs) with 95% confidence intervals (CIs) will be calculated. For time-to-event outcomes, including PFS and OS, HRs with 95% CIs will be computed. Statistical significance will be considered at a p-value of less than 0.05. Dealing with missing data For studies with missing outcome data, the extent and reasons for missing data will be assessed. A complete case analysis will be performed as the primary analysis. Missing data will be imputed by multiple imputations under the missing-at-random assumption. Sensitivity analyses will be applied to the articles with more than 25% missing data. Assessment of heterogeneity Statistical heterogeneity among studies will be assessed via the Cochran’s Q statistic p-value and the I² statistic. An I² value greater than 50% or a Cochran’s Q test p-value < 0.10 will be considered substantial heterogeneity. Data synthesis Meta-analysis We will use a random-effect model for the meta-analysis unless we can assume that all studies estimate the same intervention effect. If homogeneity is assumed, we will use a fixed-effect model. However, we will interpret random-effects meta-analyses with caution due to the potential for small study effects and refer to Chap. 10 of the Cochrane Handbook for Systematic Reviews of Interventions for further guidance[ 12 ]. We will perform meta-analyses via Review Manager Web [ 13 ], following the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions [ 14 ]. Subgroup analysis and investigation of heterogeneity If applicable, subgroup analysis will be conducted to evaluate the effects of predefined characteristics on the outcomes. A subgroup will be applied if any specific factors contribute to heterogeneity. The subgroup analysis will be performed considering the type of cancer, patient characteristics, and location. Summary of findings and assessment of the certainty of the evidence A summary of the findings table will be created for primary and secondary outcomes. The quality of the evidence will be independently assessed by two reviewers using the GRADE Quality Assessment Checklist (Grading of Recommendations, Assessment, Development, and Evaluation) [ 15 ]. The certainty of the evidence will be categorized into high, moderate, low, and very low level, based on criteria including risk of bias, consistency of findings, precision, directness, and publication bias. References Najafi M, Majidpoor J, Toolee H, Mortezaee K. The current knowledge concerning solid cancer and therapy. J Biochem Mol Toxicol. Nov. 2021;35(11):e22900. 10.1002/JBT.22900 . Bray Bsc F, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. May 2024;74(3):229–63. 10.3322/CAAC.21834 . Vogel A, Saborowski A. Current strategies for the treatment of intermediate and advanced hepatocellular carcinoma. Cancer Treat Rev. Jan. 2020;82:101946. 10.1016/J.CTRV.2019.101946 . Kyi C, Postow MA. Immune Checkpoint Inhibitor Combinations in Solid Tumors: Opportunities and Challenges. Immunotherapy. Jun. 2016;8(7):821–37. 10.2217/IMT-2016-0002 . Song H, Liu X, Jiang L, Li F, Zhang R, Wang P. Current Status and Prospects of Camrelizumab, A Humanized Antibody Against Programmed Cell Death Receptor 1, Recent Pat Anticancer Drug Discov , vol. 16, no. 3, pp. 312–332, Feb. 2021, 10.2174/1574892816666210208231744 Xiang-Chong L, Gao-Feng L. Application of PD-1 inhibitor Camrelizumab in advanced malignancies, Medical Journal of Chinese People’s Liberation Army , vol. 45, no. 6, pp. 672–679, Jul. 2020, 10.11855/J.ISSN.0577-7402.2020.06.16 Zhang H. Apatinib for molecular targeted therapy in tumor, Nov. 13, 2015, Dove Medical Press Ltd. 10.2147/DDDT.S97235 Scott AJ, Messersmith WA, Jimeno A. Apatinib: a promising oral antiangiogenic agent in the treatment of multiple solid tumors. Drugs Today (Barc). Apr. 2015;51(4):223–9. 10.1358/DOT.2015.51.4.2320599 . Fukumura D, Kloepper J, Amoozgar Z, Duda DG, Jain RK. Enhancing cancer immunotherapy using antiangiogenics: Opportunities and challenges. Nat Publishing Group. May 2018;01. 10.1038/nrclinonc.2018.29 . Xu J, et al. Camrelizumab in Combination with Apatinib in Patients with Advanced Hepatocellular Carcinoma (RESCUE): A Nonrandomized, Open-label, Phase II Trial. Clin Cancer Res. Feb. 2021;27(4):1003–11. 10.1158/1078-0432.CCR-20-2571 . Page MJ, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. Mar. 2021;372. 10.1136/BMJ.N71 . Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M. Chapter 10: Analysing data and undertaking meta-analyses, in Cochrane Handbook for Systematic Reviews of Interventions , 2022. [Online]. Available: https://training.cochrane.org/handbook/current/chapter-10 Review Manager (RevMan) [Computer program]. Version 7.2.0. The Cochrane Collaboration. 2024. Available at revman.cochrane.org. Cochrane Handbook for Systematic Reviews of Interventions | Cochrane Training. Accessed: Feb. 01. 2025. [Online]. Available: https://training.cochrane.org/handbook Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M. Chapter 14: Completing ‘Summary of findings’ tables and grading the certainty of the evidence, in Cochrane Handbook for Systematic Reviews of Interventions., 2022. [Online]. Available: https://training.cochrane.org/handbook/current/chapter-14 Supplementary Files searchstrategyfinal.docx 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6063875","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":459349998,"identity":"ac87fb18-f908-4df3-909c-afa26c77299a","order_by":0,"name":"Mahmoud Rashad Kamal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYFACHhDBDGHwHADS7MwgUkKGBC3MbAkgLTykaOExgItjA7rtZ49u+Nhmnc/ff/bghzdn7KL5m3k+v7pRY8HDwH746AYsWszO5KXdnNmWbjnjRl6y5JwbybkzDvNus845BnQYT1raDWxaDuSY3eZtO2zAcIPHQJrnA3NuA1CLcQ4bUIsEjxlWLeffQLTInz9j/JvnQ33u/MM8z4xz/uHRcgNqiwHQOmmeG4dzNxzmYX6c24ZPyxuzmzPOpRsYAvVazjlzPHfjYTYz5tw+CR42XH45n2N240OZtYEc0GE33hyrzp13vPnx55xvdXL87IePYdOCFbBJgElilYMA8wdSVI+CUTAKRsGwBwDmqGqHAEmuZAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0005-9526-4432","institution":"Damanhour University Faculty of Science","correspondingAuthor":true,"prefix":"","firstName":"Mahmoud","middleName":"Rashad","lastName":"Kamal","suffix":""},{"id":459349999,"identity":"21b6393c-8cf9-4d00-ad2d-fd2aa32c10cb","order_by":1,"name":"Maria Dulce Estêvão","email":"","orcid":"","institution":"Universidade do Algarve","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Dulce","lastName":"Estêvão","suffix":""},{"id":459350000,"identity":"2a69f330-1596-4b48-a067-98f9fcbbd501","order_by":2,"name":"Chun Hoong Wong","email":"","orcid":"","institution":"Hospital Kuala Lumpur","correspondingAuthor":false,"prefix":"","firstName":"Chun","middleName":"Hoong","lastName":"Wong","suffix":""},{"id":459350001,"identity":"496c9220-b30a-4a6c-a835-721c3e13e270","order_by":3,"name":"Maria Azizian","email":"","orcid":"","institution":"Vrije Universiteit Amsterdam","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Azizian","suffix":""},{"id":459350002,"identity":"18bfd3ed-9eb3-47b0-b3c5-f1aec8d84b87","order_by":4,"name":"Mayam Mohamed Aziz","email":"","orcid":"","institution":"Menoufia University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Mayam","middleName":"Mohamed","lastName":"Aziz","suffix":""}],"badges":[],"createdAt":"2025-02-19 11:59:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6063875/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6063875/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84104475,"identity":"b5e859b4-3270-4efd-8803-225a43fa8b02","added_by":"auto","created_at":"2025-06-06 21:51:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":721949,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6063875/v1/33e5266c-89ee-4e00-b70f-41cc9a5d8962.pdf"},{"id":83266514,"identity":"7ee48ccf-e81e-4279-87d0-07121fc73bb3","added_by":"auto","created_at":"2025-05-22 06:10:31","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":15519,"visible":true,"origin":"","legend":"","description":"","filename":"searchstrategyfinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-6063875/v1/ed6ce79b136b9a920a877d7f.docx"}],"financialInterests":"","formattedTitle":"Protocol for a Systematic Review: Camrelizumab plus Apatinib in Solid Tumors","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer encompasses a diverse range of diseases, broadly classified into solid tumors and hematologic malignancies. Solid tumors arise from abnormal cell growth in specific organs or tissues, forming discrete masses. Solid tumors represent a significant global health challenge, and approximately 80% of all tumor types are derived from a subset of solid organs, including the breast, prostate, lung, colon, and ovary [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSolid cancers originate mainly from epithelia, develop as distinct lesions capable of invading surrounding structures and metastasizing to distant sites. These tumors account for more than 85% of all cancer cases worldwide and are a leading cause of cancer-related morbidity and mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In 2022, an estimated 20.0\u0026nbsp;million new cancer cases were diagnosed globally, with solid tumors such as lung, breast, colorectal, and prostate cancers being the most prevalent [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe clinical management of solid tumors is complex, particularly in advanced or metastatic stages, where treatment options are often limited, and the prognosis remains poor. Traditional therapies, including surgery, chemotherapy, and radiation, have been the cornerstone of cancer treatment for decades. However, these approaches are often associated with significant toxicity, limited efficacy in advanced disease, and the development of treatment resistance [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. For example, in hepatocellular carcinoma (HCC), systemic therapies such as sorafenib and lenvatinib have shown modest improvements in overall survival, underscoring the need for more effective treatments [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent years, targeted therapies and immunotherapy have transformed the landscape of cancer treatment. Immune checkpoint inhibitors (ICIs), such as programmed cell death protein-1 (PD-1) inhibitors, have demonstrated remarkable efficacy in a variety of solid tumors by enhancing the body's immune response against cancer cells [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Camrelizumab, a humanized PD-1 inhibitor, has shown promising activity in cancers such as hepatocellular carcinoma (HCC), esophageal squamous cell carcinoma (ESCC), and non-small cell lung cancer (NSCLC) [5, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Similarly, antiangiogenic agents such as apatinib, which target vascular endothelial growth factor receptor-2 (VEGFR-2), effectively inhibit tumor angiogenesis and growth, particularly in gastric cancer and hepatocellular carcinoma (HCC) [7, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe combination of camrelizumab and apatinib represents a novel therapeutic strategy that leverages the synergistic effects of immune modulation and angiogenesis inhibition. Preclinical studies suggest that antiangiogenic agents can increase the efficacy of ICIs by normalizing the tumor vasculature, promoting immune cell infiltration, and reducing the levels of immunosuppressive factors within the tumor microenvironment [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Early-phase clinical trials have reported encouraging results for this combination, with improved response rates and survival outcomes in patients with advanced solid tumors [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, the evidence remains fragmented, and a comprehensive synthesis of the available data is needed to evaluate the efficacy and safety of this combination therapy.\u003c/p\u003e \u003cp\u003eThis systematic review aims to address this gap by synthesizing the existing evidence on the use of camrelizumab plus apatinib in solid tumors. By evaluating outcomes such as the objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and adverse events (AEs), this review provides critical insights into the potential benefits and risks of this combination therapy. These findings will inform clinical practice, guide future research, and contribute to ongoing efforts to improve outcomes for patients with solid tumors.\u003c/p\u003e\n\u003ch3\u003eOBJECTIVES\u003c/h3\u003e\n\u003cp\u003eTo assess the efficacy and safety of camrelizumab (a PD-1 inhibitor) plus apatinib in patients with solid cancer.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eCriteria for considering studies for this review\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section4\"\u003e \u003ch2\u003eTypes of studies\u003c/h2\u003e \u003cp\u003eRandomized controlled trials (RCTs), non-randomized controlled trials, cohort studies, and single-arm trials will be included.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \n\u003ch3\u003eTypes of participants\u003c/h3\u003e\n\u003cp\u003ePatients with advanced or metastatic solid tumors with no population restrictions (age, sex, race/ethnicity, geographic origin, or others).\u003c/p\u003e\n\u003ch3\u003eTypes of interventions\u003c/h3\u003e\n\u003cp\u003eCombination therapy using camrelizumab (an anti-PD-1 monoclonal antibody) and apatinib (a VEGFR-2 inhibitor).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eComparator\u003c/h2\u003e \u003cp\u003eStandard therapies (e.g., radiation, chemotherapy, monotherapy with ICIs or antiangiogenic agents, placebo) or other treatments.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTypes of outcome measures\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePrimary outcomes\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eProgression-free survival (PFS): Time from enrollment to the first documented progression of disease or death.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eObjective response rate (ORR): Proportion of patients who achieve a complete or partial response according to the RECIST criteria.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSecondary outcomes\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eOverall survival (OS): Time from enrollment to death from any cause\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAdverse events (AEs) and serious adverse events (SAEs) will be reported. The severity of AEs will be assessed according to the National Cancer Institute-Common Terminology Criteria for Adverse Events (NCI‐CTCAE, 2010), if available. If severity grading is not provided, adverse event data will still be included, and the grading system used will be noted where applicable.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eExclusion Criteria\u003c/h2\u003e \u003cp\u003eThe following will be excluded:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAnimal studies, \u003cem\u003ein vitro\u003c/em\u003e experiments, and basic research.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eConference abstracts, reviews, commentaries, and case reports.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStudies with aggregate reporting of results from multiple populations or disease cohorts.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDuplicate publications.\u003c/p\u003e\u003cp\u003eLiterature from which valid outcome data cannot be extracted.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSearch methods for the identification of studies\u003c/h2\u003e \u003cp\u003eWe will search the following databases from 2018 to the present, as the combination of camrelizumab and apatinib was not available (even in clinical trials) before 2018:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePubMed\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWeb of Science\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScopus\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eClinicalTrials.gov (only completed trials will be included)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eData collection and analysis\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003eSelection of studies\u003c/h2\u003e \u003cp\u003eThe study selection process will follow the PRISMA 2020 diagram [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. First, studies will be imported into Covidence, which facilitates the selection process for the reviewers. The screening process will include screening the titles and abstracts and reviewing the full texts of the eligible articles. Two independent reviewers (CH, MDE) will systematically perform the selection process. The selected articles will be divided into three categories: included, excluded, and uncertain. Any disagreements among reviewers will be resolved through discussion or by consulting a third reviewer (MR).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eData extraction and management\u003c/h2\u003e \u003cp\u003eTwo independent reviewers (MA, MM) will collect information from the included studies. This process will be conducted by using a standardized data extraction template. The following information will be extracted: Reference details (authors, year of publication, title, country, DOI, funding source); Study characteristics (study design and objectives, sample size, locations, follow-up duration); Population characteristics (age, sex, race/ethnicity, type of cancer, previous treatments); Interventions (intervention group, intervention dose, control group, treatment duration); Outcomes (primary and secondary outcomes, including PFS, ORR, OS, and the number of SAEs; numerical outcomes will include the exact figures and units).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of risk of bias in included studies\u003c/h2\u003e \u003cp\u003eThe risk of bias in the included studies will be assessed independently by two reviewers (MM, MR) via standardized tools appropriate for the study designs, as presented below. Discrepancies will be resolved through discussion or, if necessary, by consulting a third reviewer (MA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e1. Tools for Risk of Bias Assessment\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRandomized Controlled Trials (RCTs)\u003c/b\u003e: The Cochrane Risk of Bias Tool (RoB 2) will be used to assess the following domains:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRandomization process.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDeviations from intended interventions.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMissing outcome data.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMeasurement of the outcome.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSelection of the reported result.\u003c/p\u003e \u003cp\u003eEach domain will be judged as \u003cb\u003e\"low risk,\" \"some concerns,\" or \"high risk\"\u003c/b\u003e of bias.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eNon-Randomized Studies\u003c/b\u003e: The Risk of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool will be used to assess the following domains:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBias due to confounding factors.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBias on the selection of participants.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBias in the classification of interventions.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBias due to deviations from intended interventions.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBias due to missing data.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBias in the measurement of outcomes.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBias in the selection of the reported result.\u003c/p\u003e \u003cp\u003eEach domain will be judged as \u003cb\u003e\"low risk,\" \"moderate risk,\" \"serious risk,\" or \"critical risk\"\u003c/b\u003e of bias.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSingle-Arm Trials\u003c/b\u003e: The NIH Quality Assessment Tool for Before-After (Pre-Post) Studies with No Control Group will be used to assess methodological quality. The key domains include the following:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eClear study question.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAppropriate eligibility criteria.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eConsistent and reliable outcome measures.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAppropriate statistical analysis.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMinimization of bias.\u003c/p\u003e \u003cp\u003eEach domain will be judged as \u003cb\u003e\"yes,\" \"no,\" or \"not applicable.\"\u003c/b\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e2. Process for Risk of Bias Assessment\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePilot testing\u003c/b\u003e: A pilot test will be conducted on a sample of studies to ensure consistency between reviewers.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eIndependent assessment\u003c/b\u003e: Two reviewers independently assess the risk of bias for each study.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eResolution of Discrepancies\u003c/b\u003e: Disagreements will be resolved through discussion or by consulting a third reviewer.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSummary of Findings\u003c/b\u003e: The risk of bias assessments will be summarized in a table and incorporated into the results and discussion sections of the review.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3. Reporting\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe risk of bias assessments will be presented as follows:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRisk of Bias Tables: Summarizing judgments for each domain.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRisk of Bias Graphs: Visualizing the overall risk of bias across studies.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSensitivity Analysis: If applicable, studies with a high risk of bias will be excluded to assess their impact on the results.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMeasures of treatment effect\u003c/h2\u003e \u003cp\u003eDescriptive statistics will be conducted to describe the characteristics of all eligible studies. Meta-analysis will be performed if enough studies are obtained. For dichotomous outcomes, including the ORR and adverse events, risk ratios (RRs) with 95% confidence intervals (CIs) will be calculated. For time-to-event outcomes, including PFS and OS, HRs with 95% CIs will be computed. Statistical significance will be considered at a p-value of less than 0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eDealing with missing data\u003c/h2\u003e \u003cp\u003eFor studies with missing outcome data, the extent and reasons for missing data will be assessed. A complete case analysis will be performed as the primary analysis. Missing data will be imputed by multiple imputations under the missing-at-random assumption. Sensitivity analyses will be applied to the articles with more than 25% missing data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of heterogeneity\u003c/h2\u003e \u003cp\u003eStatistical heterogeneity among studies will be assessed via the Cochran\u0026rsquo;s Q statistic p-value and the I\u0026sup2; statistic. An I\u0026sup2; value greater than 50% or a Cochran\u0026rsquo;s Q test p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.10 will be considered substantial heterogeneity.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eData synthesis\u003c/h2\u003e \u003cdiv id=\"Sec24\" class=\"Section4\"\u003e \u003ch2\u003eMeta-analysis\u003c/h2\u003e \u003cp\u003eWe will use a random-effect model for the meta-analysis unless we can assume that all studies estimate the same intervention effect. If homogeneity is assumed, we will use a fixed-effect model. However, we will interpret random-effects meta-analyses with caution due to the potential for small study effects and refer to Chap.\u0026nbsp;10 of the Cochrane Handbook for Systematic Reviews of Interventions for further guidance[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. We will perform meta-analyses via Review Manager Web [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], following the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eSubgroup analysis and investigation of heterogeneity\u003c/h2\u003e \u003cp\u003eIf applicable, subgroup analysis will be conducted to evaluate the effects of predefined characteristics on the outcomes. A subgroup will be applied if any specific factors contribute to heterogeneity. The subgroup analysis will be performed considering the type of cancer, patient characteristics, and location.\u003c/p\u003e \u003c/div\u003e "},{"header":"Summary of findings and assessment of the certainty of the evidence","content":"\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003cp\u003eA summary of the findings table will be created for primary and secondary outcomes. The quality of the evidence will be independently assessed by two reviewers using the GRADE Quality Assessment Checklist (Grading of Recommendations, Assessment, Development, and Evaluation) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The certainty of the evidence will be categorized into high, moderate, low, and very low level, based on criteria including risk of bias, consistency of findings, precision, directness, and publication bias.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNajafi M, Majidpoor J, Toolee H, Mortezaee K. The current knowledge concerning solid cancer and therapy. J Biochem Mol Toxicol. Nov. 2021;35(11):e22900. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/JBT.22900\u003c/span\u003e\u003cspan address=\"10.1002/JBT.22900\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBray Bsc F, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 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Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://training.cochrane.org/handbook\u003c/span\u003e\u003cspan address=\"https://training.cochrane.org/handbook\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiggins J, Thomas J, Chandler J, Cumpston M, Li T, Page M. Chapter 14: Completing \u0026lsquo;Summary of findings\u0026rsquo; tables and grading the certainty of the evidence, in Cochrane Handbook for Systematic Reviews of Interventions., 2022. [Online]. Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://training.cochrane.org/handbook/current/chapter-14\u003c/span\u003e\u003cspan address=\"https://training.cochrane.org/handbook/current/chapter-14\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Camrelizumab, Apatinib, Combination Therapy, Immune Checkpoint Inhibitors, Anti-Angiogenic Therapy","lastPublishedDoi":"10.21203/rs.3.rs-6063875/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6063875/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eSolid tumors represent a significant global health burden, with limited treatment options for advanced or metastatic stages. The combination of camrelizumab, a programmed cell death protein-1 (PD-1) inhibitor, and apatinib, a vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitor, has shown promise in preclinical and early-phase clinical studies. However, the efficacy and safety of this combination therapy remain unclear. This systematic review aims to synthesize the available evidence on the use of camrelizumab plus apatinib in solid tumors to inform clinical practice and guide future research.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eA comprehensive search of electronic databases, including PubMed, Scopus, Web of Science, and ClinicalTrials.gov, will be conducted from January 2018 to the present. Randomized controlled trials, non-randomized controlled trials, cohort studies, and single-arm trials evaluating camrelizumab plus apatinib in patients with advanced or metastatic solid tumors will be included. The primary outcomes will include the objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). The secondary outcomes will focus on the incidence and severity of adverse events (AEs). Two reviewers will independently screen studies, extract data, and assess the risk of bias using standardized tools. Data will be synthesized narratively and, if appropriate, through meta-analysis.\u003c/p\u003e\u003ch2\u003eDiscussion:\u003c/h2\u003e \u003cp\u003eThis systematic review will provide a comprehensive evaluation of the efficacy and safety of camrelizumab plus apatinib in solid tumors. The findings will inform clinical decision-making, highlight gaps in the current evidence, and guide the design of future studies. By synthesizing the available data, this review aims to contribute to the development of more effective treatment strategies for patients with advanced or metastatic solid tumors.\u003c/p\u003e","manuscriptTitle":"Protocol for a Systematic Review: Camrelizumab plus Apatinib in Solid Tumors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-22 06:02:26","doi":"10.21203/rs.3.rs-6063875/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":"b3cb34f8-972e-4ed8-9c8e-c461793503ef","owner":[],"postedDate":"May 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-06T21:43:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-22 06:02:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6063875","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6063875","identity":"rs-6063875","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}