The negative impact of opioids on cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis

The negative impact of opioids on cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis | 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 The negative impact of opioids on cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis Ziming Gao, Mingguang Ju, Xiaofang Liu, Heng Zhou, Ruiying Wang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1732605/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 As one of the most effective analgesics, opioids are essential for patients with cancer-related pain, even in the context of the opioid abuse crisis. The current meta-analysis aimed to identify whether concomitant exposure to opioids can affect the efficacy of ICIs and lead to a worse prognosis. Methods PubMed, Embase, and the Cochrane Library were searched Based on the PRISMA checklist, through April 2022, for the following terms: ("opioids" OR "concomitant medication") AND ("Neoplasm" OR "Carcinoma" OR "Cancer" OR "Tumor") AND ("Immunotherapy" OR "Immune Checkpoint Inhibitor" OR "PD-L1 Inhibitor" OR "PD-1 Inhibitor" OR "CTLA-4 Inhibitor"). The outcomes considered were overall survival (OS) and progression-free survival (PFS) calculated using the random-effects or fixed-effects model. RESULTS After screening 531 studies, a total of 7 articles involving 2690 patients were eligible for quantitative analysis. The use of opioids was negatively correlated with OS (HR = 1.75, 95%CI = 1.32–2.31, P < .001; I 2 = 81%, P < .001) and significantly reduced the PFS (HR = 1.61, 95%CI = 1.41–1.83, P < .001; I 2 = 0%, P = .63) of patients treated with ICIs. Similar results were obtained in each subgroup analysis. While NSAIDs could lead to poor OS (HR = 1.25, 95% CI = 1.03–1.51, P = 0.02) but not PFS (HR = 1.11, 95% CI = 0.89–1.39, P = 0.36) for ICIs patients. And sensitivity analyses confirmed the reliability of the results. CONCLUSIONS Opioids significantly reduced OS and PFS in patients receiving ICI therapy. Thus, the use of different types of opioids should be considered with caution, and it is necessary to actively develop alternative treatments. Opioids Immune checkpoint inhibitors Overall survival Progression-free survival Meta-analysis Figures Figure 1 Figure 2 Figure 3 Introduction Since being approved in 2014, immune checkpoint inhibitors (ICIs), represented by PD-1, PD-L1, and CTLA-4, have significantly improved the prognosis of patients and changed the treatment paradigm for several solid tumors[1-4]. However, ICIs also show some shortcomings in clinical application, including inconsistent efficacy and susceptibility to influence by other factors. Some concomitant medications, such as antibiotics or proton pump inhibitors (PPIs), have been indicated to reduce the survival benefit of ICIs[5-7]. Thus, the combined utilization of ICIs and other drugs deserves more attention. Pain is a common symptom in advanced and metastatic cancer. Nearly 80% of patients who died of cancer suffered moderate-severe pain for an average of 90 days in less-developed countries[8, 9]. The World Health Organization (WHO) guidelines suggest the use of opioids in adults or adolescents with cancer-related pain based on clinical assessment and pain severity[10]. Thus, even in the crisis of opioid abuse, pain management using opioids is still necessary for cancer patients and remains the best clinical analgesic for cancer-related pain. With the application of ICIs in the first-line therapeutic regimen, the use of opioids combined with ICIs became common, and there have been inconsistent findings in some studies[11-13]. Therefore, it is urgently necessary to evaluate the actual effect of opioids on ICI efficacy. We wish to provide a reference for the pain management of cancer patients, especially for those who are treated with ICIs. Methods Literature search A systematic search was conducted using the PubMed, Embase, and Cochrane Library databases as well as related references retrieved up to April 2022 using the following search terms: ("opioids" OR "concomitant medication") AND ("Neoplasm" OR "Carcinoma" OR "Cancer" OR "Tumor") AND ("Immunotherapy" OR "Immune Checkpoint Inhibitor" OR "PD-L1 Inhibitor" OR "PD-1 Inhibitor" OR "CTLA-4 Inhibitor"). The search strategy was shown in supplementary table 1 in the Supplement. Eligibility criteria Following the PRISMA guidelines[14], the authors searched the database according to the retrieval strategy and independently evaluated all articles. The title and abstract of the search results were browsed, and the full text was read to determine whether it met the inclusion criteria. Discrepancies were resolved by consensus. The inclusion criteria used for article selection were as follows: (1) adult patients with cancer receiving ICI treatment, (2) patients were treated with opioids before, during, or after ICI administration, and the control group was not treated with opioids within the corresponding period, and (3) the outcomes were the efficacy of ICIs, including overall survival (OS) or progression-free survival (PFS). The exclusion criteria were as follows: (1) conference abstracts, review papers, papers without original data, and studies with duplicate data; (2) studies published in languages other than English; and (3) full-text article was not available. Data extraction We extracted the following data from eligible studies: first author, publication year, country, study type, cancer type, sample size, patient characteristics, ICI type, opioid type, and outcomes. We extracted the hazard ratio (HR) and 95% confidence interval (CI) of the multivariate analysis in the included articles. For the studies that only provided a survival curve we referred to the Engauge Digitizer method reported by Tierney to extract HR and 95% CI indirectly[15]. Quality assessment The quality of each study was evaluated using the Newcastle–Ottawa scale (NOS)[16]. In the NOS system, studies with scores ≥ 6 are defined as high quality. Statistical analysis and visualization tools The effect of opioids on the survival of patients treated with ICIs was explored, and the results were reported as HRs and 95% CIs. OS was the primary outcome, and PFS was the secondary outcome. Heterogeneity was identified using the Q test, and we estimated and quantified it by I 2 values[17]. When I 2 was >50% and/or P< 0.10, heterogeneity was considered statistically significant. A random-effects model or fixed-effects model was selected according to the heterogeneity results. Subgroup and sensitivity analyses were performed to determine the potential factors underlying the heterogeneity. Publication bias was evaluated by funnel plot, along with Begg's and Egger's tests. If publication bias existed, trim-and-fill analysis was used to assess it. All p values were two-sided, and the significance level was set at P< 0.05. Review STATA 15.1 and Revman 5.4 were used for statistical analysis and visualization. Results Study selection A total of 531 studies were retrieved from the initial broad search through April 2022. Based on the inclusion and exclusion criteria, 7 articles[11-13, 18-21] were eligible for quantitative analysis, with a total of 2690 patients (Figure 1). There were 620 opioid-treated patients and 2070 opioid-free patients. The most common cancer types were non-small cell lung cancer (NSCLC), melanoma, and renal cell carcinoma (RCC). Finally, five studies[11-13, 18, 20] provided both OS and PFS, and the other two[19, 21] only reported OS. The baseline characteristics of the included studies are shown in Table 1. Table 1. The Baseline Characteristics of Included Studies Source Country Study type Cancer type ICI type Opioid type Patients, No. (Y/N) Male, No. (%) Age, Median, y Quality evaluation Outcome Botticelli (2021)[13] Italy Retrospective NSCLC, melanoma, renal cancer, Merkel tumor, and colon cancer Nivolumab, pembrolizumab, atezolizumab, and avelumab NR 193(42/151) 120(62.0) 70.0 6 OS, PFS Cortellini (2020)[18] Italy Retrospective NSCLC, melanoma, RCC, and other cancers Pembrolizumab, nivolumab, atezolizumab, and others NR 1012(68/944) 647 (63.9) 68.5 8 OS, PFS Gaucher (2021)[19] France Retrospective Lung cancer, melanoma, renal and urothelial cancer, head and neck cancer, and other cancers Ipilimumab, nivolumab and pembrolizumab NR 372(173/199) 244(65.6) 64.0 6 OS Kostine (2021)[20] France Retrospective Melanoma, NSCLC, renal cancer, and other cancers Anti-PD-1/PD-L1, anti-CTLA-4, sequential CPI Morphine 635(130/505) 443 (70.0) 64.5 7 OS, PFS Miura (2021) Japan Retrospective NSCLC Nivolumab, pembrolizumab NR 300(114/186) 226 (75.3) 65.0 7 OS Santamaría (2019)[11] Spain Retrospective NSCLC, renal cancer, bladder cancer, melanoma, head and neck cancer, and other cancers Nivolumab, pembrolizumab, atezolizumab, and ipilimumab NR 102(55/47) 84 (82.4) 66.0 9 OS, PFS Taniguchi (2020)[12] Japan Retrospective NSCLC Nivolumab Oxycodone, fentanyl, morphine, hydromorphone, tapentadol 76(38/38) 53 (67.9) NR 7 OS, PFS *Obtained via correspondence with primary author Abbreviations: CTLA-4: Cytotoxic T lymphocyte-associated antigen-4; ICIs: Immune Checkpoint Inhibitors; NR, not reported; NSCLC: non-small cell lung cancer; OS, overall survival; PD-1/PD-L1: Programmed cell death protein-1/Programmed cell death-ligand1; PFS, progression-free survival; RCC, renal cell carcinoma; Y/N, opioids use/no opioids use Quality assessment According to the NOS criteria, two reviewers independently evaluated the methodological quality of the included studies. Overall, all studies were considered medium or high quality, which was indicated by scores of at least six (Table 1). Impact of opioids on ICIs (OS) Opioids were negatively correlated with OS (HR=1.75, 95% CI = 1.32-2.31, P< 0.001) with high heterogeneity ( I 2 =80.4%, P< 0.001), as shown in Figure 2A. In the subgroup analysis of NSCLC (HR=1.83, 95% CI=1.46-2.28, P< 0.001; I 2 =46.1%, P =0.157), opioids had negative effects on ICIs. Moreover, the results were consistent based on the ICI type, sample size, and country, indicating that opioids were significantly related to reduced OS (Table 2). Sensitivity analysis suggested that the studies by Botticelli[13] and Kostine[20] were strongly associated with heterogeneity (supplementary figure 1A). After excluding the two studies, the results of OS were HR=1.87, 95% CI = 1.38-2.52, P< 0.001; I 2 =77.6%, P< 0.001 and HR=1.54, 95% CI = 1.25-1.90, P< 0.001; I 2 =51.6%, P =0.066, respectively. Impact of opioids on ICIs (PFS) Opioids significantly reduced the PFS of patients treated with ICIs (HR=1.61, 95% CI=1.41-1.83, P< 0.001) without heterogeneity ( I 2 =0.0%, P =0.629), as shown in Figure 2B. Subgroup analysis also showed that opioids significantly reduced PFS based on ICI type, sample size, and country obtained similar results (Table 2). Sensitivity analyses reported that the results were not dominated by any single study (supplementary figure 1B). Impact of NSAIDs or aspirin on ICIs (OS and PFS) To evaluate the efficacy of non-opioids on ICIs, we analyzed the impact of nonsteroidal anti-inflammatory drugs (NSAIDs) on OS and PFS and further focused on aspirin, which is representative but has been shown to be independent from NSAIDs in some studies. NSAIDs could lead to poor OS (HR= 1.25, 95% CI=1.03-1.51, P= 0.02; I 2 =0%, P= 0.60) but not PFS (HR=1.11, 95% CI=0.89-1.39, P= 0.36; I 2 =0.0%, P= 0.75) for ICI patients (Figure 3A and B). While aspirin didn’t reduce the survival of patients treated with ICI therapy, no matter OS (HR= 0.93, 95% CI = 0.78-1.10, P= 0.27; I 2 =17%, P= .39) or PFS (HR=0.89, 95% CI=0.69-1.16, P= 0.12; I 2 =59%, P= 0.40) (Figure 3C and D). Risk of publication bias The funnel chart (supplementary figure 2) and the results of Begg's test and Egger's test analysis (Table 2) suggested that there was no significant publication bias except for in the overall analysis of PFS ( P Begg's =0.027, P Egger's =0.012). Trim-and-fill analysis showed that publication bias did not affect the PFS results (HR=1.55, 95% CI=1.38-1.74, P< 0.001). Discussion Cancer is the local manifestation of a systemic disease, and cancer patients usually have underlying diseases, such as hypertension, hyperglycemia, infection, and moderate-severe pain, especially in elderly individuals. Based on our search strategy, a total of eight studies[11, 18-24] discussed concomitant medication with ICIs in patients with advanced cancers. The usage rates of analgesics, PPIs, antibiotics, cardiovascular and hypoglycemic drugs were 15.6%, 20.3%, 8.2%, 20.8%, and 5.4%, respectively (supplementary figure 3). Several studies have corroborated that some medications can directly or indirectly influence immunity or immunotherapy[19-24], which has attracted considerable attention. In this meta-analysis, we focused on the impact of opioids on the survival outcomes of ICIs in advanced cancer patients. In recent decades, the opioid abuse crisis has led to severe financial and social burdens and has been one of the biggest challenges facing public health in the 21st century[25]. Although prescription drug-monitoring programs (PDMPs) have reduced the prescription rate of opioids from 255 million to 153 million in America, they have also limited the adequate usage of opioids for patients with cancer-related pain. The current consensus is that pain management is essential for tumor patients, and opioids are preferred for moderate-severe cancer-related pain and can contribute to a high quality of life and adherence to therapy[26]. Thus, it seems unethical to restrict or forbid the use of opioids for severe cancer-related pain, and some investigators suggest providing exemptions for opioids for patients with cancer. However, based on this article, we believe that prescription opioids should be used with caution for tumor patients treated with ICIs, which is a novel but crucial viewpoint that might improve the long-term survival of tumor patients. This study was the first meta-analysis to systematically evaluate the clinical efficacy of opioids on ICIs and included seven articles published in the past three years. Our meta-analysis identified the adverse effects of opioids on the efficacy of ICIs, and the results showed that the use of opioids was negatively correlated with OS and PFS in cancer patients treated with ICIs. Considering the heterogeneity in cancer type, ICI type, sample size, and publication country, we divided the study into several subgroups for further analysis. All subgroups consistently showed the negative effect of opioids on the prognosis of patients. We likewise found similar studies in two conference abstracts[27, 28], of whose results were consistent but were not included because of insufficient evidence regrettably. Sensitivity analysis showed that two studies[13, 20] strongly influenced heterogeneity. In the study of Botticelli[13], ECOG-PS was an independent prognostic factor rather than opioid use, which reflects patients’ health status and the ability to tolerate therapy. 28 Considering that patients treated with opioids may be weaker and have more complications than others, there was significant collinearity between opioid use and ECOG-PS, which might be one of the main causes for the heterogeneity in our meta-analysis. In addition, opioids had various immunoregulatory levels according to different targets, and morphine and fentanyl were stronger than others[29-32]. Two included articles[12, 20] disclosed relevant details of the opioid types. Of these, the main opioid in the article by Taniguchi was oxycodone, with a utilization rate of 52.6%, but fentanyl and morphine had utilization rates of 18.4% and 15.8%, respectively[12]. Kostine’s study[20] referred only to morphine, which seemed to have more negative effects on ICIs than in other studies and acted as another source of heterogeneity in our meta-analysis. Multimodal analgesia is a promising therapeutic strategy and is drawing increasing attention to the management of cancer-related pain[33]. Based on previous studies, the opioids with weak or no immune modulation (buprenorphine, oxycodone, hydromorphone, and tramadol) should be considered for the combined utilization with morphine or fentanyl, which can reduce the immunosuppressive effect of opioids for ICIs patients[29-32]. In addition, alternative drugs for chronic pain, including NSAIDs, antidepressants, and anticonvulsants, might be another choice[34]. A network meta-analysis reported that certain nonopioid analgesics and NSAIDs can serve as effectively as opioids for chronic cancer-related pain[35]. In this study, we revealed that NSAIDs could lead to poor OS but not PFS for ICI patients. Even so, NSAIDs seem to have a better effect than opioids on OS. As one of the representative NSAIDs, aspirin was researched independently in some studies because of its anti-thrombogenesis. Thus, we also focus specifically on aspirin for its pain relief efficacy, and aspirin had no additional effect on ICIs in terms of either OS or PFS. Interestingly, a meta-analysis reported that acupuncture and/or acupressure was significantly associated with reduced cancer pain and could decrease use of analgesics, which deserves more attention[36]. Limitations There are several limitations to this study. First, our meta-analysis was based on retrospective studies. Considering the lower-level evidence and the number of included studies in some subgroups, the results should be interpreted with caution. Second, due to a lack of basic data, we could not perform an in-depth analysis in terms of opioid type, dosage, or drug exposure time, which might be the factors driving nonstatistical heterogeneity. In addition, tumor staging is an independent factor for prognosis, but only two articles provided information on staging, which might affect the accuracy of the results[11, 18]. Third, since one of the included studies did not perform a multivariate analysis, we used the method of Tierney et al. to extract the HR and 95% CI according to the survival curve, which might lead to a certain bias. Conclusions As one of the most effective analgesics, adequate application of opioids is essential for patients with cancer-related pain, even in the context of the opioid abuse crisis. However, our study showed that opioids were associated with poor prognosis in patients treated with ICIs. Thus, caution should be taken when prescribing a drug combination. It is necessary to clarify appropriate opioids based on immunoregulatory levels of ICI therapy and actively develop alternative drugs in the future. Abbreviations CI confidence interval CTLA-4 Cytotoxic T lymphocyte-associated antigen-4 HR hazard ratio ICIs Immune Checkpoint Inhibitors NR, not reported NSAIDs nonsteroidal anti-inflammatory drugs NSCLC non-small cell lung cancer OS, overall survival PD-1/PD-L1 Programmed cell death protein-1/Programmed cell death-ligand1 PDMPs prescription drug-monitoring programs PFS, progression-free survival PPIs proton pump inhibitors RCC, renal cell carcinoma Declarations CONFLICT OF INTEREST DISCLOSURES : The authors have no relevant financial or non-financial interests to disclose Role of the Funder/Sponsor : The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Author Contributions: Formal analysis, Methodology, funding acquisition, visualization, and writing–original draft. Mingguang Ju: Formal analysis, methodology, visualization and writing–original draft. Xiaofang Liu: Formal analysis, data curation, Visualization. Heng Zhou: Investigation, Visualization. Ruiying Wang: Investigation and software. Chen Zheng: Investigation. Daosong Dong: Investigation and methodology. Zhi Zhu: Conceptualization, funding acquisition, supervision, and writing–review and editing. Kai Li: Conceptualization, funding acquisition, project administration, supervision, resources and writing–review and editing. All authors read and approved the final manuscript. Acknowledgments ： Funding: Li received support from Liaoning Revitalization Talents Program (Liaoning Revitalization Talents Program) and Gao received support from China Postdoctoral Science Foundation (2020M681021). The funder had no role in the design and conduct of the study. 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JAMA Oncol;6:271–278. Tables Table 2 is not available with this version. Additional Declarations No competing interests reported. Supplementary Files supplment6.6.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-1732605","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":111650215,"identity":"71268966-c361-410e-b3ab-aa7499273e3a","order_by":0,"name":"Ziming Gao","email":"","orcid":"","institution":"The First Affiliated Hospital of China Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ziming","middleName":"","lastName":"Gao","suffix":""},{"id":111650216,"identity":"6e16552f-7a48-44c8-9cbe-ee922fed3e47","order_by":1,"name":"Mingguang Ju","email":"","orcid":"","institution":"The First 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Hospital of China Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ruiying","middleName":"","lastName":"Wang","suffix":""},{"id":111650220,"identity":"b1b64114-5d35-4c28-b49f-150bf62f4a9d","order_by":5,"name":"Chen Zheng","email":"","orcid":"","institution":"The First Affiliated Hospital of China Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Zheng","suffix":""},{"id":111650221,"identity":"d366961f-09cb-4676-a99d-d8a61e34ab3e","order_by":6,"name":"Daosong Dong","email":"","orcid":"","institution":"The First Affiliated Hospital of China Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daosong","middleName":"","lastName":"Dong","suffix":""},{"id":111650222,"identity":"fedfb7e0-cff8-4067-9ebf-28b5ac49ab59","order_by":7,"name":"Zhi Zhu","email":"","orcid":"","institution":"The First Affiliated Hospital of China Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhi","middleName":"","lastName":"Zhu","suffix":""},{"id":111650223,"identity":"ac192382-cc48-4346-9299-494ac3c2d5fd","order_by":8,"name":"Kai Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYLCCBwYJDGzsjY0PPxCtJQGkhedws7EE8VqAkEEivU2AhxjV/NPOGDAkFKTJ80k+bGOQYLCT020goEXidg5Qi0GOYZt0YtuDAoZkY7MDBLQYSIO1VDACtbQbSDAcSNxGrBb7NsmDbRI8JGjJSWyTYCRSi8TttAKglrTkNp5EYCAbEOEX/tnJGxg+/Em2nd9+/OHDDxV2cgS1AAH7DyR3ElY+CkbBKBgFo4AIAAA2DTtVC6AvXAAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital of China Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2022-06-07 05:59:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1732605/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1732605/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":22588225,"identity":"54e0cbea-fb0a-4fa2-beec-b981ffc59b53","added_by":"auto","created_at":"2022-06-13 15:56:40","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":96534,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Study Selection.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1732605/v1/801ad772c42b647e299261e8.jpg"},{"id":22588224,"identity":"40b76814-3cac-42c9-b81d-e4da3b79ece8","added_by":"auto","created_at":"2022-06-13 15:56:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":115720,"visible":true,"origin":"","legend":"\u003cp\u003eForest Plots of Opioid Use Associated with OS (A) and PFS (B) in Cancer Patients Treated with ICIs.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1732605/v1/68515eb2a10bcff88b490036.jpg"},{"id":22588227,"identity":"5b927cf8-f195-46fc-a9ce-652e81e1db0e","added_by":"auto","created_at":"2022-06-13 15:56:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":138867,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of NSAIDs and aspirin use associated with OS (A and C) and PFS (B and D) in cancer patients treated with ICIs.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1732605/v1/d4856a42c50b70ba8e7bfa35.jpg"},{"id":22588230,"identity":"242445c0-3db7-4c54-b66b-8e2c1a79aaeb","added_by":"auto","created_at":"2022-06-13 15:56:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":622123,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1732605/v1/715ccba1-a0e9-49ef-87ba-42871c6185fa.pdf"},{"id":22588229,"identity":"fdd6d8a2-bc89-4ead-896b-b1396a32a365","added_by":"auto","created_at":"2022-06-13 15:56:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":622123,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1732605/v1/48cf50ad-7632-4a8b-a14d-b3e6c86437f7.pdf"},{"id":22588226,"identity":"809671c3-3d7a-47f4-b0ed-7498a4e00473","added_by":"auto","created_at":"2022-06-13 15:56:40","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":5586839,"visible":true,"origin":"","legend":"","description":"","filename":"supplment6.6.docx","url":"https://assets-eu.researchsquare.com/files/rs-1732605/v1/326e9a079b0bafc8cf72f9bf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The negative impact of opioids on cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince being approved in 2014, immune checkpoint inhibitors (ICIs), represented by PD-1, PD-L1, and CTLA-4,\u0026nbsp;have\u0026nbsp;significantly improved the prognosis of patients and changed\u0026nbsp;the\u0026nbsp;treatment paradigm for several solid tumors[1-4].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eHowever, ICIs also show some\u0026nbsp;shortcomings\u0026nbsp;in clinical application, including inconsistent efficacy and susceptibility to influence by other factors.\u0026nbsp;Some\u0026nbsp;concomitant medications, such as antibiotics or proton pump inhibitors (PPIs), have been\u0026nbsp;indicated\u0026nbsp;to reduce the survival benefit of ICIs[5-7]. Thus,\u0026nbsp;the\u0026nbsp;combined utilization\u0026nbsp;of\u0026nbsp;ICIs and other drugs deserves more attention.\u003c/p\u003e\n\u003cp\u003ePain is a common symptom in advanced and metastatic cancer. Nearly 80% of patients who died of cancer suffered moderate-severe pain for an average of 90 days in less-developed countries[8, 9].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eThe World Health Organization (WHO) guidelines suggest the use of opioids in adults or adolescents with cancer-related pain based on clinical assessment and pain severity[10]. Thus, even in the crisis of opioid abuse, pain management using opioids is still necessary for cancer patients and remains the best clinical\u0026nbsp;analgesic\u0026nbsp;for cancer-related pain.\u003c/p\u003e\n\u003cp\u003eWith the application of ICIs in the first-line therapeutic regimen, the use of opioids combined with ICIs became common, and there have been inconsistent findings in some studies[11-13].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTherefore, it is urgently necessary to evaluate the actual effect of opioids on ICI efficacy. We wish to provide a reference for the pain management of cancer patients, especially for those who are treated with ICIs.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eLiterature search\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA systematic search was conducted using the PubMed, Embase, and Cochrane Library databases as well as related references retrieved up to April 2022 using the following search terms: \u003cem\u003e(\u0026quot;opioids\u0026quot; OR \u0026quot;concomitant medication\u0026quot;) AND (\u0026quot;Neoplasm\u0026quot; OR \u0026quot;Carcinoma\u0026quot; OR \u0026quot;Cancer\u0026quot; OR \u0026quot;Tumor\u0026quot;) AND (\u0026quot;Immunotherapy\u0026quot; OR \u0026quot;Immune Checkpoint Inhibitor\u0026quot; OR \u0026quot;PD-L1 Inhibitor\u0026quot; OR \u0026quot;PD-1 Inhibitor\u0026quot; OR \u0026quot;CTLA-4 Inhibitor\u0026quot;).\u003c/em\u003e The search strategy was shown in\u0026nbsp;supplementary\u0026nbsp;table 1 in the Supplement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEligibility criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the PRISMA guidelines[14], the\u0026nbsp;authors\u0026nbsp;searched the database according to the retrieval strategy and independently evaluated all articles. The title and abstract of the search results were browsed, and the full text was read to determine whether it met the inclusion criteria. Discrepancies were resolved by consensus.\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria used for article selection were as follows: (1) adult patients with cancer receiving ICI treatment, (2) patients were treated with opioids before, during, or after ICI administration, and the control group was not treated with opioids within the corresponding period, and (3) the outcomes were the efficacy of ICIs, including overall survival (OS) or progression-free survival (PFS). The exclusion criteria were as follows: (1) conference abstracts, review papers, papers without original data, and studies with duplicate data; (2) studies published in languages other than English; and (3) full-text article was not available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extracted the following data from eligible studies: first author, publication year, country, study type, cancer type, sample size, patient characteristics, ICI type, opioid type, and\u0026nbsp;outcomes.\u0026nbsp;We extracted the hazard ratio (HR) and 95% confidence interval (CI) of the multivariate analysis in the included articles.\u0026nbsp;For the studies that only provided a survival curve we referred to the Engauge Digitizer\u0026nbsp;method\u0026nbsp;reported by\u0026nbsp;Tierney\u0026nbsp;to extract HR and\u0026nbsp;95% CI\u0026nbsp;indirectly[15].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe quality of each study was evaluated using the Newcastle\u0026ndash;Ottawa scale (NOS)[16]. In the NOS system, studies with scores \u0026ge; 6 are defined as high quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis and visualization tools\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of opioids on the survival of patients treated with ICIs was explored, and\u0026nbsp;the\u0026nbsp;results were reported as\u0026nbsp;HRs\u0026nbsp;and\u0026nbsp;95% CIs. OS was the primary outcome, and PFS was the secondary\u0026nbsp;outcome. Heterogeneity was identified using the Q test, and we estimated and quantified it by \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e values[17]. When \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e was \u0026gt;50%\u0026nbsp;and/or \u003cem\u003eP\u0026lt;\u003c/em\u003e0.10, heterogeneity was considered statistically significant.\u0026nbsp;A random-effects model or fixed-effects model\u0026nbsp;was\u0026nbsp;selected according to the heterogeneity results. Subgroup and sensitivity analyses were performed to\u0026nbsp;determine\u0026nbsp;the potential factors underlying the heterogeneity. Publication bias was evaluated by funnel plot, along with Begg\u0026apos;s and Egger\u0026apos;s tests. If publication bias existed, trim-and-fill analysis was used to\u0026nbsp;assess\u0026nbsp;it. All \u003cem\u003ep\u003c/em\u003e values were two-sided, and the significance level was set at \u003cem\u003eP\u0026lt;\u003c/em\u003e0.05. Review STATA 15.1 and Revman 5.4 were used for statistical analysis and visualization.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 531 studies were retrieved from the initial broad search through April 2022. Based on the inclusion and exclusion criteria, 7 articles[11-13, 18-21] were eligible for quantitative analysis, with a total of 2690 patients (Figure 1). There were 620 opioid-treated patients and 2070 opioid-free patients. The most common cancer types were non-small cell lung cancer (NSCLC), melanoma, and renal cell carcinoma (RCC). Finally, five studies[11-13, 18, 20] provided both OS and PFS, and the other two[19, 21] only reported OS. The baseline characteristics of the included studies are shown in Table 1. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eThe Baseline Characteristics of Included Studies\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eCountry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eStudy type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eCancer type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003eICI type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eOpioid type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003ePatients, No. (Y/N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003eMale, No. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003eAge,\u003c/p\u003e\n \u003cp\u003eMedian, y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003eQuality\u0026nbsp;\u003cbr\u003e\u0026nbsp;evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eBotticelli (2021)[13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eRetrospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eNSCLC, melanoma, renal cancer, Merkel tumor,\u0026nbsp;and colon cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003eNivolumab, pembrolizumab, atezolizumab, and avelumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003e193(42/151)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003e120(62.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003e70.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOS, PFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eCortellini (2020)[18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eRetrospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eNSCLC, melanoma, RCC, and other cancers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003ePembrolizumab, nivolumab, atezolizumab, and others \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003e1012(68/944)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003e647 (63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003e68.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOS, PFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eGaucher (2021)[19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eFrance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eRetrospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eLung cancer, melanoma, renal and urothelial cancer, head and neck cancer, and other cancers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003eIpilimumab, nivolumab and pembrolizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003e372(173/199)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003e244(65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003e64.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eKostine (2021)[20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eFrance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eRetrospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eMelanoma, NSCLC, renal cancer, and other cancers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003eAnti-PD-1/PD-L1,\u0026nbsp;anti-CTLA-4, sequential CPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eMorphine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003e635(130/505)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003e443 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003e64.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOS, PFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eMiura (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eRetrospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eNSCLC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003eNivolumab, pembrolizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003e300(114/186)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003e226 (75.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eSantamar\u0026iacute;a (2019)[11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eRetrospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eNSCLC, renal cancer, bladder cancer, melanoma, head and neck cancer, and other cancers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003eNivolumab, pembrolizumab, atezolizumab, and ipilimumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003e102(55/47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003e84 (82.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003e66.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOS, PFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.657247037374658%\"\u003e\n \u003cp\u003eTaniguchi (2020)[12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.013673655423883%\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003eRetrospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.494074749316317%\"\u003e\n \u003cp\u003eNSCLC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.22880583409298%\"\u003e\n \u003cp\u003eNivolumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.217866909753875%\"\u003e\n \u003cp\u003eOxycodone, fentanyl, morphine, hydromorphone, tapentadol\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.568824065633546%\"\u003e\n \u003cp\u003e76(38/38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.74567000911577%\"\u003e\n \u003cp\u003e53 (67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.834092980856882%\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.654512306289882%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.01640838650866%\"\u003e\n \u003cp\u003eOS, PFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Obtained via correspondence with primary author\u003c/p\u003e\n\u003cp\u003eAbbreviations: CTLA-4: Cytotoxic T lymphocyte-associated antigen-4; ICIs: Immune Checkpoint Inhibitors; NR, not reported; NSCLC: non-small cell lung cancer; OS, overall survival; PD-1/PD-L1: Programmed cell death protein-1/Programmed cell death-ligand1; PFS, progression-free survival; RCC, renal cell carcinoma; Y/N, opioids use/no opioids use\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the NOS criteria, two reviewers independently evaluated the methodological quality of the included studies. Overall, all studies were considered medium or high quality, which was indicated by scores of at least six (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of opioids on ICIs (OS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOpioids were negatively correlated with OS (HR=1.75, 95% CI = 1.32-2.31, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001) with high heterogeneity (\u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=80.4%, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001), as shown in Figure 2A. In the subgroup analysis of NSCLC (HR=1.83, 95% CI=1.46-2.28, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001; \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=46.1%, \u003cem\u003eP\u003c/em\u003e=0.157), opioids had negative effects on ICIs. Moreover, the results were consistent based on the ICI type, sample size, and country, indicating that opioids were significantly related to reduced OS (Table 2). Sensitivity analysis suggested that the studies by Botticelli[13] and Kostine[20] were strongly associated with heterogeneity (supplementary figure 1A). After excluding the two studies, the results of OS were HR=1.87, 95% CI = 1.38-2.52, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001; \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=77.6%, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001 and HR=1.54, 95% CI = 1.25-1.90, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001; \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=51.6%, \u003cem\u003eP\u003c/em\u003e=0.066, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of opioids on ICIs (PFS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOpioids significantly reduced the PFS of patients treated with ICIs (HR=1.61, 95% CI=1.41-1.83, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001) without heterogeneity (\u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.0%, \u003cem\u003eP\u003c/em\u003e=0.629), as shown in Figure 2B. Subgroup analysis also showed that opioids significantly reduced PFS based on ICI type, sample size, and country obtained similar results (Table 2). Sensitivity analyses reported that the results were not dominated by any single study (supplementary figure 1B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of NSAIDs or aspirin on ICIs (OS and PFS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the efficacy of non-opioids on ICIs, we analyzed the impact of nonsteroidal anti-inflammatory drugs (NSAIDs) on OS and PFS and further focused on aspirin, which is representative but has been shown to be independent from NSAIDs in some studies. NSAIDs could lead to poor OS (HR= 1.25, 95% CI=1.03-1.51, \u003cem\u003eP=\u003c/em\u003e0.02; \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e =0%, \u003cem\u003eP=\u003c/em\u003e0.60) but not PFS (HR=1.11, 95% CI=0.89-1.39, \u003cem\u003eP=\u003c/em\u003e0.36; \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.0%, \u003cem\u003eP=\u003c/em\u003e0.75) for ICI patients (Figure 3A and B). While aspirin didn\u0026rsquo;t reduce the survival of patients treated with ICI therapy, no matter OS (HR= 0.93, 95% CI = 0.78-1.10, \u003cem\u003eP=\u003c/em\u003e0.27; \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=17%, \u003cem\u003eP=\u003c/em\u003e.39) or PFS (HR=0.89, 95% CI=0.69-1.16, \u003cem\u003eP=\u003c/em\u003e0.12; \u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=59%, \u003cem\u003eP=\u003c/em\u003e0.40) (Figure 3C and D).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk of publication bias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe funnel chart (supplementary figure 2) and the results of Begg\u0026apos;s test and Egger\u0026apos;s test analysis (Table 2) suggested that there was no significant publication bias except for in the overall analysis of PFS (\u003cem\u003eP\u003csub\u003eBegg\u0026apos;s\u003c/sub\u003e\u003c/em\u003e =0.027, \u003cem\u003eP\u003csub\u003eEgger\u0026apos;s\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=0.012). Trim-and-fill analysis showed that publication bias did not affect the PFS results (HR=1.55, 95% CI=1.38-1.74, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCancer is the local manifestation of a systemic disease,\u0026nbsp;and\u0026nbsp;cancer patients usually\u0026nbsp;have\u0026nbsp;underlying diseases, such as hypertension, hyperglycemia, infection, and moderate-severe pain, especially in\u0026nbsp;elderly individuals. Based on our search strategy, a total of eight studies[11, 18-24]\u0026nbsp;discussed concomitant medication with ICIs in patients with advanced cancers.\u0026nbsp;The\u0026nbsp;usage rates of analgesics, PPIs, antibiotics, cardiovascular and hypoglycemic drugs were 15.6%, 20.3%, 8.2%, 20.8%, and 5.4%, respectively\u0026nbsp;(supplementary figure 3). Several studies have corroborated that some medications can directly or indirectly influence immunity or immunotherapy[19-24], which has attracted considerable attention. In this meta-analysis, we\u0026nbsp;focused\u0026nbsp;on the impact of opioids on the survival outcomes of ICIs in advanced cancer patients.\u003c/p\u003e\n\u003cp\u003eIn\u0026nbsp;recent\u0026nbsp;decades,\u0026nbsp;the\u0026nbsp;opioid abuse crisis\u0026nbsp;has\u0026nbsp;led to severe financial and social burdens and has been one of the biggest challenges facing public health in the 21st century[25]. Although\u0026nbsp;prescription drug-monitoring programs\u0026nbsp;(PDMPs) have reduced the prescription rate of opioids from 255 million to 153 million in America,\u0026nbsp;they have\u0026nbsp;also limited the adequate usage of opioids for patients with cancer-related pain. The current consensus is that pain management is essential for tumor patients, and opioids are preferred for moderate-severe cancer-related pain and can contribute to a high quality of life and adherence to therapy[26]. Thus, it seems unethical to restrict or forbid the use of opioids for severe cancer-related pain, and some investigators suggest providing exemptions for opioids for patients with cancer.\u0026nbsp;However,\u0026nbsp;based on this article, we\u0026nbsp;believe\u0026nbsp;that prescription opioids should be\u0026nbsp;used with caution\u0026nbsp;for tumor patients treated with ICIs, which\u0026nbsp;is\u0026nbsp;a novel but crucial viewpoint that might improve\u0026nbsp;the\u0026nbsp;long-term survival of tumor patients.\u003c/p\u003e\n\u003cp\u003eThis study was the first meta-analysis to systematically evaluate\u0026nbsp;the\u0026nbsp;clinical efficacy of opioids on ICIs and included seven articles published in the past three years. Our meta-analysis identified the adverse effects of opioids on the efficacy of ICIs, and the results showed that the use of opioids was negatively correlated with OS and PFS in cancer patients treated with ICIs. Considering the heterogeneity in cancer type,\u0026nbsp;ICI\u0026nbsp;type, sample size, and publication country, we divided the study into several subgroups for further analysis. All subgroups\u0026nbsp;consistently\u0026nbsp;showed the negative effect of opioids on the prognosis of patients. We likewise found similar studies in two conference abstracts[27, 28], of whose results were consistent but were not included because of insufficient evidence regrettably.\u003c/p\u003e\n\u003cp\u003eSensitivity analysis\u0026nbsp;showed\u0026nbsp;that two studies[13, 20]\u0026nbsp;strongly\u0026nbsp;influenced\u0026nbsp;heterogeneity. In the study of\u0026nbsp;Botticelli[13], ECOG-PS was an independent prognostic factor rather than opioid use, which reflects patients\u0026rsquo; health status and the ability to tolerate therapy.\u003csup\u003e28\u003c/sup\u003e Considering\u0026nbsp;that\u0026nbsp;patients treated with opioids may be weaker and have more complications than others, there was significant collinearity between\u0026nbsp;opioid\u0026nbsp;use and ECOG-PS,\u0026nbsp;which\u0026nbsp;might be one of the main causes for the heterogeneity in our meta-analysis. In addition, opioids had various\u0026nbsp;immunoregulatory\u0026nbsp;levels according to different targets, and morphine and fentanyl were stronger than others[29-32].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eTwo\u0026nbsp;included articles[12, 20]\u0026nbsp;disclosed relevant details of the\u0026nbsp;opioid\u0026nbsp;types. Of\u0026nbsp;these,\u003csup\u003e\u0026nbsp;\u003c/sup\u003ethe main\u0026nbsp;opioid in the article by Taniguchi was\u0026nbsp;oxycodone, with a utilization rate of 52.6%, but fentanyl and morphine had utilization rates of 18.4% and 15.8%, respectively[12]. Kostine\u0026rsquo;s study[20]\u0026nbsp;referred only to morphine, which seemed to have more negative effects on ICIs than in other studies and acted as another source of heterogeneity in our meta-analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMultimodal analgesia is a promising therapeutic strategy and is drawing increasing attention to the management of cancer-related pain[33]. Based on previous studies, the opioids with weak or no immune modulation (buprenorphine, oxycodone, hydromorphone, and tramadol) should be considered for the combined utilization with morphine or fentanyl, which can reduce the immunosuppressive effect of opioids for ICIs patients[29-32]. In addition, alternative drugs for chronic pain, including NSAIDs, antidepressants, and anticonvulsants, might be another choice[34]. A network meta-analysis reported that certain nonopioid analgesics and NSAIDs can serve as effectively as opioids for chronic cancer-related pain[35]. In this study, we revealed that NSAIDs could lead to poor OS but not PFS for ICI patients. Even so, NSAIDs seem to have a better effect than opioids on OS. As one of the representative NSAIDs, aspirin was researched independently in some studies because of its anti-thrombogenesis. Thus, we also focus specifically on aspirin for its pain relief efficacy, and aspirin had no additional effect on ICIs in terms of either OS or PFS. Interestingly, a meta-analysis reported that acupuncture and/or acupressure was significantly associated with reduced cancer pain and could decrease use of analgesics, which deserves more attention[36].\u0026nbsp;\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThere are several limitations to this study. First, our meta-analysis was based on retrospective studies. Considering the lower-level evidence and the number of included studies in some subgroups, the results should be interpreted with caution. Second, due to a lack of basic data, we could not perform an in-depth analysis in terms of opioid type, dosage, or drug exposure time, which might be the factors driving nonstatistical heterogeneity. In addition, tumor staging is an independent factor for prognosis, but only two articles provided information on staging, which might affect the accuracy of the results[11, 18]. Third, since one of the included studies did not perform a multivariate analysis, we used the method of Tierney et al. to extract the HR and 95% CI according to the survival curve, which might lead to a certain bias.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eAs one of the most effective analgesics, adequate application of opioids is essential for patients with cancer-related pain, even in the context of the opioid abuse crisis. However, our study showed that opioids were associated with poor prognosis in patients treated with ICIs. Thus, caution should be taken when prescribing a drug combination. It is necessary to clarify appropriate opioids based on immunoregulatory levels of ICI therapy and actively develop alternative drugs in the future.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTLA-4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCytotoxic T lymphocyte-associated antigen-4\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmune Checkpoint Inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNR, not reported\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSAIDs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enonsteroidal anti-inflammatory drugs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSCLC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-small cell lung cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS, overall survival\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD-1/PD-L1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgrammed cell death protein-1/Programmed cell death-ligand1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePDMPs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprescription drug-monitoring programs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFS, progression-free survival\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eproton pump inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRCC, renal cell carcinoma\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST DISCLOSURES\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors have no relevant financial or non-financial interests to disclose\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of the Funder/Sponsor\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFormal analysis,\u0026nbsp;Methodology, funding acquisition, visualization, and writing–original\u0026nbsp;draft.\u0026nbsp;Mingguang Ju:\u0026nbsp;Formal analysis, methodology, visualization and writing–original\u0026nbsp;draft.\u0026nbsp;Xiaofang Liu:\u0026nbsp;Formal analysis, data curation, Visualization.\u0026nbsp;Heng Zhou:\u0026nbsp;Investigation, Visualization.\u0026nbsp;Ruiying Wang:\u0026nbsp;Investigation and software.\u0026nbsp;Chen Zheng:\u0026nbsp;Investigation.\u0026nbsp;Daosong Dong:\u0026nbsp;Investigation\u0026nbsp;and\u0026nbsp;methodology. Zhi Zhu:\u0026nbsp;Conceptualization, funding acquisition, supervision, and writing–review and editing. Kai Li:\u0026nbsp;Conceptualization, funding acquisition, project administration, supervision, resources and writing–review and editing.\u003cem\u003e\u0026nbsp;All authors read and approved the final manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Li received support from Liaoning Revitalization Talents Program (Liaoning Revitalization Talents Program) and Gao received support from China Postdoctoral Science Foundation (2020M681021). The funder had no role in the design and conduct of the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eGrivas P, Monk BJ, Petrylak D, et al(2019) Immune Checkpoint Inhibitors as Switch or Continuation Maintenance Therapy in Solid Tumors: Rationale and Current State. Target Oncol;14:505\u0026ndash;525.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHoos A(2016) Development of immuno-oncology drugs - from CTLA4 to PD1 to the next generations. Nat Rev Drug Discov;15:235\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eXiong A, Wang J, Zhou C(2021) Immunotherapy in the First-Line Treatment of NSCLC: Current Status and Future Directions in China. Front Oncol;11:757993.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eRibas A, Wolchok JD(2018) Cancer immunotherapy using checkpoint blockade. Science;359:1350\u0026ndash;1355.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePinato DJ, Howlett S, Ottaviani D, et al(2019) Association of Prior Antibiotic Treatment With Survival and Response to Immune Checkpoint Inhibitor Therapy in Patients With Cancer. JAMA Oncol;5:1774\u0026ndash;1778.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHopkins AM, Badaoui S, Kichenadasse G, et al(2022) Efficacy of Atezolizumab in Patients With Advanced NSCLC Receiving Concomitant Antibiotic or Proton Pump Inhibitor Treatment: Pooled Analysis of Five Randomized Control Trials. J Thorac Oncol;17:758\u0026ndash;767.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eDerosa L, Routy B, Thomas AM, et al(2022) Intestinal Akkermansia muciniphila predicts clinical response to PD-1 blockade in patients with advanced non-small-cell lung cancer. Nat Med;28:315\u0026ndash;324.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003evan den Beuken-van Everdingen MH, Hochstenbach LM, Joosten EA, Tjan-Heijnen VC, Janssen DJ(2016) Update on Prevalence of Pain in Patients With Cancer: Systematic Review and Meta-Analysis. J Pain Symptom Manage;51:1070\u0026ndash;1090.e9.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKnaul FM, Farmer PE, Krakauer EL, et al(2018) Alleviating the access abyss in palliative care and pain relief-an imperative of universal health coverage: the Lancet Commission report. Lancet;391:1391\u0026ndash;1454.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eWHO Guidelines Approved by the Guidelines Review Committee. WHO Guidelines for the Pharmacological and Radiotherapeutic Management of Cancer Pain in Adults and Adolescents. World Health Organization\u0026nbsp;\u003c/span\u003e\u003cspan\u003e\u0026copy; World Health Organization 2018.; 2018.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eIglesias-Santamar\u0026iacute;a A(2020) Impact of antibiotic use and other concomitant medications on the efficacy of immune checkpoint inhibitors in patients with advanced cancer. Clin Transl Oncol;22:1481\u0026ndash;1490.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTaniguchi Y, Tamiya A, Matsuda Y, et al(2020) Opioids impair Nivolumab outcomes: a retrospective propensity score analysis in non-small-cell lung cancer. BMJ Support Palliat Care;\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eBotticelli A, Cirillo A, Pomati G, et al(2021) The role of opioids in cancer response to immunotherapy. J Transl Med;19:119.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMoher D, Liberati A, Tetzlaff J, Altman DG(2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med;6:e1000097.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR(2007) Practical methods for incorporating summary time-to-event data into meta-analysis. Trials;8:16.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eWells GA, Shea BJ, O\u0026apos;Connell D, Peterson J, Tugwell P(2000) The Newcastle\u0026ndash;Ottawa Scale (NOS) for Assessing the Quality of Non-Randomized Studies in Meta-Analysis.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHiggins JP, Thompson SG, Deeks JJ, Altman DG(2003) Measuring inconsistency in meta-analyses. Bmj;327:557\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eCortellini A, Tucci M, Adamo V, et al(2020) Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice. J Immunother Cancer;8\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eGaucher L, Adda L, S\u0026eacute;journ\u0026eacute; A, et al(2021) Associations between dysbiosis-inducing drugs, overall survival and tumor response in patients treated with immune checkpoint inhibitors. Ther Adv Med Oncol;13:17588359211000591.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKostine M, Mauric E, Tison A, et al(2021) Baseline co-medications may alter the anti-tumoural effect of checkpoint inhibitors as well as the risk of immune-related adverse events. Eur J Cancer;157:474\u0026ndash;484.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMiura K, Sano Y, Niho S, et al(2021) Impact of concomitant medication on clinical outcomes in patients with advanced non-small cell lung cancer treated with immune checkpoint inhibitors: A retrospective study. Thorac Cancer;12:1983\u0026ndash;1994.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eGandhi S, Pandey M, Ammannagari N, et al(2020) Impact of concomitant medication use and immune-related adverse events on response to immune checkpoint inhibitors. Immunotherapy;12:141\u0026ndash;149.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eAngrish MD, Agha A, Pezo RC(2021) Association of Antibiotics and Other Drugs with Clinical Outcomes in Metastatic Melanoma Patients Treated with Immunotherapy. J Skin Cancer;2021:9120162.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSvaton M, Zemanova M, Zemanova P, et al(2020) Impact of Concomitant Medication Administered at the Time of Initiation of Nivolumab Therapy on Outcome in Non-small Cell Lung Cancer. Anticancer Res;40:2209\u0026ndash;2217.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMacintyre PE, Quinlan J, Levy N, Lobo DN(2022) Current Issues in the Use of Opioids for the Management of Postoperative Pain: A Review. JAMA Surg;157:158\u0026ndash;166.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eScarborough BM, Smith CB(2018) Optimal pain management for patients with cancer in the modern era. CA Cancer J Clin;68:182\u0026ndash;196.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTaniguchi Y, Tamiya A, Isa S, Nakahama K, Atagi S(2019) P1.01-77 Impact of Oral Drugs on the Prognosis of Non-Small-Cell Lung Cancer Patients Treated with Nivolumab. Journal of Thoracic Oncology;14:S390.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eBironzo P, Pignataro D, Audisio M, Tagliamento M, Novello S(2019) P2.04-15 Association Between Opioids and Outcome of 1st Line Immunotherapy in Advanced NSCLC Patients: A Retrospective Evaluation. Journal of Thoracic Oncology;14:S713.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eZajączkowska R, Leppert W, Mika J, et al(2018) Perioperative Immunosuppression and Risk of Cancer Progression: The Impact of Opioids on Pain Management. Pain Res Manag;2018:9293704.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMao M, Qian Y, Sun J(2016) Morphine Suppresses T helper Lymphocyte Differentiation to Th1 Type Through PI3K/AKT Pathway. Inflammation;39:813\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMaher DP, Walia D, Heller NM(2020) Morphine decreases the function of primary human natural killer cells by both TLR4 and opioid receptor signaling. Brain Behav Immun;83:298\u0026ndash;302.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLu H, Zhang H, Weng ML, et al(2021) Morphine promotes tumorigenesis and cetuximab resistance via EGFR signaling activation in human colorectal cancer. J Cell Physiol;236:4445\u0026ndash;4454.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eAvery N, McNeilage AG, Stanaway F, et al(2022) Efficacy of interventions to reduce long term opioid treatment for chronic non-cancer pain: systematic review and meta-analysis. Bmj;377:e066375.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eChe T, Roth BL(2021) Structural Insights Accelerate the Discovery of Opioid Alternatives. Annu Rev Biochem;90:739\u0026ndash;761.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHuang R, Jiang L, Cao Y, et al(2019) Comparative Efficacy of Therapeutics for Chronic Cancer Pain: A Bayesian Network Meta-Analysis. J Clin Oncol;37:1742\u0026ndash;1752.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHe Y, Guo X, May BH, et al(2020) Clinical Evidence for Association of Acupuncture and Acupressure With Improved Cancer Pain: A Systematic Review and Meta-Analysis. JAMA Oncol;6:271\u0026ndash;278.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 2 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Opioids, Immune checkpoint inhibitors, Overall survival, Progression-free survival, Meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-1732605/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1732605/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAs one of the most effective analgesics, opioids are essential for patients with cancer-related pain, even in the context of the opioid abuse crisis. The current meta-analysis aimed to identify whether concomitant exposure to opioids can affect the efficacy of ICIs and lead to a worse prognosis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePubMed, Embase, and the Cochrane Library were searched Based on the PRISMA checklist, through April 2022, for the following terms: (\"opioids\" OR \"concomitant medication\") AND (\"Neoplasm\" OR \"Carcinoma\" OR \"Cancer\" OR \"Tumor\") AND (\"Immunotherapy\" OR \"Immune Checkpoint Inhibitor\" OR \"PD-L1 Inhibitor\" OR \"PD-1 Inhibitor\" OR \"CTLA-4 Inhibitor\"). The outcomes considered were overall survival (OS) and progression-free survival (PFS) calculated using the random-effects or fixed-effects model.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eAfter screening 531 studies, a total of 7 articles involving 2690 patients were eligible for quantitative analysis. The use of opioids was negatively correlated with OS (HR\u0026thinsp;=\u0026thinsp;1.75, 95%CI\u0026thinsp;=\u0026thinsp;1.32\u0026ndash;2.31, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001; \u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;81%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and significantly reduced the PFS (HR\u0026thinsp;=\u0026thinsp;1.61, 95%CI\u0026thinsp;=\u0026thinsp;1.41\u0026ndash;1.83, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001; \u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.63) of patients treated with ICIs. Similar results were obtained in each subgroup analysis. While NSAIDs could lead to poor OS (HR\u0026thinsp;=\u0026thinsp;1.25, 95% CI\u0026thinsp;=\u0026thinsp;1.03\u0026ndash;1.51, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.02) but not PFS (HR\u0026thinsp;=\u0026thinsp;1.11, 95% CI\u0026thinsp;=\u0026thinsp;0.89\u0026ndash;1.39, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.36) for ICIs patients. And sensitivity analyses confirmed the reliability of the results.\u003c/p\u003e\u003ch2\u003eCONCLUSIONS\u003c/h2\u003e \u003cp\u003eOpioids significantly reduced OS and PFS in patients receiving ICI therapy. Thus, the use of different types of opioids should be considered with caution, and it is necessary to actively develop alternative treatments.\u003c/p\u003e","manuscriptTitle":"The negative impact of opioids on cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-06-13 15:56:38","doi":"10.21203/rs.3.rs-1732605/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":"dc298ace-3292-4da8-be78-72bac7e25833","owner":[],"postedDate":"June 13th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-06-13T15:56:40+00:00","versionOfRecord":[],"versionCreatedAt":"2022-06-13 15:56:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1732605","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1732605","identity":"rs-1732605","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}