https://orcid.org/0000-0002-1369-4625
Figures
Abstract
Background
COVID-19 is spreading rapidly worldwide, and the population is generally susceptible to SARS-CoV-2, especially those with cancer. Hence, our study aims to design a protocol for a systematic review and meta-analysis of the clinical characteristics and prognoses of lung cancer patients with COVID-19.
Methods
The protocol is prepared following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The literature will be searched in Embase, Pubmed, the Cochrane Library, LitCovid, and CNKI for potentially eligible articles. The quality of the articles will be used in the Newcastle-Ottawa Quality Assessment Scale (NOS) and Cochrane Handbook for Systematic Reviews of Interventions. Statistical analysis will be performed through RevMan 5 software. This review protocol has been registered in PROSPERO (CRD42022306866).
Citation: Wu M, Liu S, Yang Y, Lin J, Liu J (2022) Clinical characteristics and outcomes of lung cancer patients with COVID-19: A systematic review and meta-analysis protocol. PLoS ONE 17(8): e0273691. https://doi.org/10.1371/journal.pone.0273691
Editor: Muhammad Shahzad Aslam, Xiamen University - Malaysia Campus: Xiamen University - Malaysia, MALAYSIA
Received: May 8, 2022; Accepted: August 14, 2022; Published: August 31, 2022
Copyright: © 2022 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data from this study will be made available upon study completion.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
The COVID-19 epidemic continues to spread all over the world. The novel highly transmissible Omicron variant of COVID-19 may become the dominant strain of the virus. The clinical symptoms show new features and the number of infections patients continue to rise. As of February 6, 2022, more than 392 million confirmed cases and more than 5.7 million deaths have been reported worldwide, with a patient mortality rate of 1.44% [1]. COVID-19 is generally susceptible to the population, especially in cancer patients [2]. This may be related to the weakened immunity of cancer patients [3]. Some studies have shown that the proportion and number of lymphocytes, especially the number of T-lymphocytes, are reduced to varying degrees in COVID-19 patients [4]. The infection rate and severity of COVID-19 are closely related to the immune function of the patient [5, 6]. At the same time, when a malignant tumour appears in the organism, the factors secreted by tumour cells can reduce the level of lymphocytes and lead to impaired immune response [7]. The decreased ability of the organism to recognize and kill mutated cells not only accelerates the growth of tumour cells but also makes cancer patients vulnerable to COVID-19 infection. It has been shown that cancer patients have a higher risk and worse prognosis for COVID-19 infection compared to non-cancer patients.
According to the latest report of the World Health Organization (WHO), there were 50.55 million prevalent cases (5 years) of cancer, including 2.60 million lung cancer patients (5.2%) in 2020. And there were an estimated 19.3 million new cancer cases (18.1 million, excluding non-melanoma skin cancer) and nearly 10 million cancer deaths (9.9 million, excluding non-melanoma skin cancer) in 2020 [8]. Lung cancer was an estimated 2.2 million new cases in 2020, with an estimated 1.8 million deaths (18%), making it the second most common cancer in the world (Fig 1) [9]. Therefore, the prevention and treatment of lung cancer with COVID-19 is essential. Several studies have reported that lung disease and cancer are risk factors for mortality outcomes in patients with COVID-19 [2, 10–18]. However, the evidence is still inadequate. This study will evaluate the clinical characteristics and prognoses of lung cancer with COVID-19 through a systematic review and meta-analysis, and provide an evidence-based basis for the management of lung cancer with COVID-19.
(A) Estimated number of prevalent cases (5-year) in 2020, worldwide, both sexes, all ages. (B) Estimated number of new cases in 2020, worldwide, both sexes, all ages. (C) Estimated number of deaths in 2020, worldwide, both sexes, all ages. (Datasource: Globocan2020 Graph production: Global Cancer Observatory).
Methods
Study design
We completed the systematic review protocol following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [19]. Furthermore, this systematic review protocol has been registered at the International Prospective Registry of Systematic Reviews (PROSPERO) (registration number: CRD42022306866). The study will use published data and does not require ethical approval.
Eligibility criteria
The inclusion and exclusion criteria are based on the construction of systematic reviews with the PICOS. Each aspect is clearly defined as follows (Table 1).
Search strategy
The literature search process will be performed independently by two researchers, including the preservation of online searches, deduplication and screening of titles, abstracts and full texts. Possible disagreements will be resolved by consulting a third author.
We will search Embase, PubMed, Cochrane Library, LitCovid, and China National Knowledge Infrastructure (CNKI) databases for articles published in English and Chinese. A combination of Medical Subject Headings (MeSH) and textual data will be applied as the search strategy. MeSH terms used for our searches are "COVID-19", "sars-cov-2", "coronavirus disease 2019", "cancer", "Neoplasms", "carcinoma", "Lung", "Pulmonary", "outcome", "signs and symptoms" (Table 2). The search terms will be translated into Chinese when searching the Chinese database (CNKI).
Screening procedure
For the visual display of a large amount of literature, the retrieved studies will be imported into RevMan 5 to remove duplicates. At first, two researchers (MW and SL) will independently screen the literature according to the titles and abstracts. Then, the full-text screening will be performed. Finally, two researchers will cross-check the included studies, disagreements will be resolved by discussion between the researchers until consensus is achieved. If disagreements persist, a third reviewer (JL) will make the final decision. The flow chart of the literature screening is shown in Fig 2. The Gantt chart of the status and timeline of the study is shown in Fig 3.
Risk of bias and quality assessment
The Newcastle-Ottawa Quality Assessment Scale (NOS) will be used to assess the quality of case-control and cohort studies [20], and the Cochrane Handbook for Systematic Reviews of Interventions to assess randomized controlled trials (RCTs) [21]. Four authors will independently assess the quality and risk of bias of the included studies and cross-check them. Disagreements will be resolved through group discussion and mutual consultation.
Data extraction
Two researchers (MW and SL) will independently extract these data and fill in the pre-set form. The extracted information was as follows:
- Author information: name of the first author, country of the corresponding author, year of publication, name of the journal.
- Study information: sample size, type of study design [(retrospective, prospective), (RCT, case-control, cohort study)], time range, patient characteristics, diagnosis, clinical characteristics (fever, cough, dyspnea, imaging manifestations, laboratory indicators, pathological findings), prognosis (mortality, ICU hospitalization rate, intubation rate, disease outcome), adverse events, follow-up, etc.
Two researchers will cross-check the extracted data. If there is disagreement, it will be discussed. If no agreement is reached, a third investigator (JL) will make the final decision. The study authors will be contacted for more information if needed.
Data synthesis
The RevMan 5 software will be used for statistical analyses. The odds ratio (OR) or risk ratio (RR) and the 95% confidence interval (CI) will be used to estimate the dichotomous variables. The standard mean difference (SMD) and 95% CI will be used to describe continuous variables. The I2 test will be applied to assess the heterogeneity among the included studies. If the level of heterogeneity is not significant (P > 0.1, I2 < 50%), we will use the fixed-effect model; If there is heterogeneity among the studies (P ≤ 0.1, I2 ≥ 50%), we will use the random-effects model [22]. When heterogeneity is fairly high, subgroup analyses or meta-regression will be conducted to assess the possible sources of heterogeneity. Sensitivity analyses will be used to assess the stability of the results. We will use funnel plots, Egger’s test and Begg’s test to assess the publications bias [23].
Discussion
COVID-19 emerged as a health emergency in the 21st century across the globe. Despite the hope that the widespread vaccine use will reduce morbidity and mortality associated with COVID-19, the pathogenic and ever-mutating SARS-CoV-2 remains a major global concern [24]. While many infected individuals were reported to suffer pathological changes in multiple organs and systems such as lung, heart, liver, kidney, and gastrointestinal mucosa, the first organ with pathological changes was the lung, such as lung consolidation, infiltration of inflammatory cytokines, etc. [25–28].
Individuals with cancers are more susceptible to respiratory viruses due to systemic immunosuppressive states and overall poor health status caused by both cancer and anticancer treatments [29–32]. This has spawned worries that cancer patients are particularly vulnerable to severe COVID-19 infection. So far, several studies have evaluated the impact of cancers on the natural history and prognosis of COVID-19 [33–35]. Prior studies have shown that patients with active cancer or a history of malignant tumours suffer worse prognoses and outcomes [36–40]. Additionally, patients with cancers have an increased risk of mechanical ventilation rate and mortality compared with those individuals without cancers [41]. Liang et al. reported that the mortality and intensive care unit (ICU) admission rates of COVID-19 cancer patients were significantly higher than those of non-cancer patients. However, they ignored the effect of confounding factors, such as age, sex, and comorbidities, which were recognized to contribute to a worse prognosis [3, 38]. Recent research data demonstrate that the incidence rate and mortality of hospitalized COVID-19 cancer patients are similar to those of non-cancer COVID-19 patients after eliminating those influencing factors such as age and number of comorbidity [42].
Although the disease course varies, both COVID-19 and lung cancer begin in the lungs. Here comes a question, how will the combined effect of COVID-19 and lung cancer affect the clinical symptoms and prognosis of patients? Based on this problem, we conducted a preliminary search of the existing literature on COVID-19 and cancer, and we found most of the systematic reviews focus on the comparison of cancer and non-cancer patients [43–46]. However, there is no systematic review of lung cancer patients with and without COVID-19. Therefore, this review and meta-analysis will systematically explore the evidence available on lung cancer patients with COVID-19, and identify the risk factors or determinants associated with lung cancer. By collecting and summarizing information, it is possible to better understand how lung cancer and COVID-19 and related factors interact with each other, especially in the context of long-term COVID. However, with the new long-term COVID public health problem, there is an urgent need for evidence-based data to help manage lung cancer patients with COVID-19. This review will provide direction for further research.
However, this systematic review has some limitations. Our study included only peer-reviewed English and Chinese articles published in academic journals, which may bias the interpretation of the results. In addition, among the included studies, there may be differences in patient characteristics, severity, and complications between studies, which may also lead to clinical heterogeneity.
Conclusion
The results of this study could provide physicians, patients and policymakers with the best clinical evidence in the management of lung cancer patients with COVID-19 patients. We hope that our findings will help fill the knowledge gap in this field and facilitate potential new research on lung cancer patients with COVID-19.
References
- 1.
Organization WH. weekly epidemiological update on covid-19 on 8 February 2022. 2022. https://www.who.int/publications/m/item/weekly-epidemiological-update-on-covid-19-8-february-2022.Accessed 8 August 2022.
- 2. Wang Q, Berger NA, Xu R. Analyses of Risk, Racial Disparity, and Outcomes Among US Patients With Cancer and COVID-19 Infection. JAMA oncology. 2021; 7(2): 220–227. Epub 2020/12/11. https://doi.org/10.1001/jamaoncol.2020.6178 pmid:33300956.
- 3. Liang W, Guan W, Chen R, Wang W, Li J, Xu K, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. The Lancet Oncology. 2020; 21(3): 335–337. Epub 2020/02/19. https://doi.org/10.1016/s1470-2045(20)30096-6 pmid:32066541.
- 4. Li Y, Wang C, Peng M. Aging Immune System and Its Correlation With Liability to Severe Lung Complications. Frontiers in public health. 2021; 9: 735151. Epub 2021/12/11. https://doi.org/10.3389/fpubh.2021.735151 pmid:34888279.
- 5. Li G, Fan Y, Lai Y, Han T, Li Z, Zhou P, et al. Coronavirus infections and immune responses. Journal of medical virology. 2020; 92(4): 424–432. Epub 2020/01/26. https://doi.org/10.1002/jmv.25685 pmid:31981224.
- 6. Liu J, Liu S. The management of coronavirus disease 2019 (COVID-19). Journal of medical virology. 2020; 92(9): 1484–1490. Epub 2020/05/06. https://doi.org/10.1002/jmv.25965 pmid:32369222.
- 7. Chen BJ, Zhao JW, Zhang DH, Zheng AH, Wu GQ. Immunotherapy of Cancer by Targeting Regulatory T cells. Int Immunopharmacol. 2022; 104: 108469. Epub 2022/01/11. https://doi.org/10.1016/j.intimp.2021.108469 pmid:35008005.
- 8. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: a cancer journal for clinicians. 2021; 71(3): 209–249. Epub 2021/02/05. https://doi.org/10.3322/caac.21660 pmid:33538338.
- 9.
Organization WH. Cancer 2022. https://www.who.int/news-room/fact-sheets/detail/cancer. Accessed 8 August 2022.
- 10. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020; 395(10229): 1054–1062. Epub 2020/03/15. https://doi.org/10.1016/s0140-6736(20)30566-3 pmid:32171076.
- 11. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. 2020; 180(7): 934–943. Epub 2020/03/14. https://doi.org/10.1001/jamainternmed.2020.0994 pmid:32167524.
- 12.
Caramelo F, Ferreira N, Oliveiros B. Estimation of risk factors for COVID-19 mortality—preliminary results. 2020. https://doi.org/10.1101/2020.02.24.20027268.
- 13.
Su VYF, Yang YH, Yang KY, Chou KT, Su WJ, Chen YM, et al. The Risk of Death in 2019 Novel Coronavirus Disease (COVID-19) in Hubei Province. Social Science Electronic Publishing. 2020. https://doi.org/10.2139/ssrn.3539655.
- 14.
Wang K, Zuo PY, Liu Y, Zhang M, Zhao X, Xie S, et al. Clinical and Laboratory Predictors of In-Hospital Mortality in 305 Patients with COVID-19: A Cohort Study in Wuhan, China. Social Science Electronic Publishing. 2020. https://doi.org/10.2139/ssrn.3546115.
- 15. Zarifkar P, Kamath A, Robinson C, Morgulchik N, Shah SFH, Cheng TKM, et al. Clinical Characteristics and Outcomes in Patients with COVID-19 and Cancer: a Systematic Review and Meta-analysis. Clin Oncol (R Coll Radiol). 2021; 33(3): e180–e191. Epub 2020/12/03. https://doi.org/10.1016/j.clon.2020.11.006 pmid:33261978.
- 16. Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis. Aging (Albany NY). 2020; 12(7): 6049–6057. Epub 2020/04/09. https://doi.org/10.18632/aging.103000 pmid:32267833.
- 17. Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020; 81(2): e16–e25. Epub 2020/04/27. https://doi.org/10.1016/j.jinf.2020.04.021 pmid:32335169.
- 18. Parohan M, Yaghoubi S, Seraji A, Javanbakht MH, Sarraf P, Djalali M. Risk factors for mortality in patients with Coronavirus disease 2019 (COVID-19) infection: a systematic review and meta-analysis of observational studies. Aging Male. 2020; 23(5): 1416–1424. Epub 2020/06/09. https://doi.org/10.1080/13685538.2020.1774748 pmid:32508193.
- 19. Karsten K, Uzung Y, Peter MV. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement and publication bias. Journal of Cranio-Maxillofacial Surgery. 2011; 39(2): 91–92. https://doi.org/10.1016/j.jcms.2010.11.001 pmid:21145753
- 20. Wells G, Shea B, O’Connell J. The Newcastle-Ottawa Scale (NOS) for Assessing The Quality of Nonrandomised Studies in Meta-analyses. Ottawa Health Research Institute Web site. 2014; 7. https://www.ohri.ca//programs/clinical_epidemiology/oxford.asp. Accessed 8 August 2022.
- 21.
Julian Higgins JT. Cochrane Handbook for Systematic Reviews of Interventions 2022. https://training.cochrane.org/handbook/current. Accessed 8 August 2022.
- 22. Sun P, Tang L, Yan D, Li B, Xu L, Wang F. Efficacy and safety of Yunkang oral liquid combined with conventional therapy for threatened miscarriage of first-trimester pregnancy a protocol for systematic review and meta-analysis. PloS one. 2022; 17(2): e0263581. Epub 2022/02/09. https://doi.org/10.1371/journal.pone.0263581 pmid:35134068.
- 23. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003; 327(7414): 557–560. Epub 2003/09/06. https://doi.org/10.1136/bmj.327.7414.557 pmid:12958120.
- 24. Conway EM, Pryzdial ELG. Complement contributions to COVID-19. Current opinion in hematology. 2022; 29(5): 259–265. Epub 2022/07/20. https://doi.org/10.1097/moh.0000000000000724 pmid:35852851.
- 25. Bao L, Deng W, Huang B, Gao H, Liu J, Ren L, et al. The pathogenicity of SARS-CoV-2 in hACE2 transgenic mice. Nature. 2020; 583(7818): 830–833. Epub 2020/05/08. https://doi.org/10.1038/s41586-020-2312-y pmid:32380511.
- 26. Hui KPY, Cheung MC, Perera R, Ng KC, Bui CHT, Ho JCW, et al. Tropism, replication competence, and innate immune responses of the coronavirus SARS-CoV-2 in human respiratory tract and conjunctiva: an analysis in ex-vivo and in-vitro cultures. The Lancet Respiratory medicine. 2020; 8(7): 687–695. Epub 2020/05/11. https://doi.org/10.1016/s2213-2600(20)30193-4 pmid:32386571.
- 27. Puelles VG, Lütgehetmann M, Lindenmeyer MT, Sperhake JP, Wong MN, Allweiss L, et al. Multiorgan and Renal Tropism of SARS-CoV-2. The New England journal of medicine. 2020; 383(6): 590–592. Epub 2020/05/14. https://doi.org/10.1056/NEJMc2011400 pmid:32402155.
- 28. Xiao F, Tang M, Zheng X, Liu Y, Li X, Shan H. Evidence for Gastrointestinal Infection of SARS-CoV-2. Gastroenterology. 2020; 158(6): 1831–1833 e1833. Epub 2020/03/07. https://doi.org/10.1053/j.gastro.2020.02.055 pmid:32142773.
- 29. Hijano DR, Maron G, Hayden RT. Respiratory Viral Infections in Patients With Cancer or Undergoing Hematopoietic Cell Transplant. Frontiers in microbiology. 2018; 9: 3097. Epub 2019/01/09. https://doi.org/10.3389/fmicb.2018.03097 pmid:30619176.
- 30. Kamboj M, Sepkowitz KA. Nosocomial infections in patients with cancer. The Lancet Oncology. 2009; 10(6): 589–597. https://doi.org/10.1016/S1470-2045(09)70069-5 pmid:19482247
- 31. Ogimi C, Waghmare AA, Kuypers JM, Xie H, Yeung CC, Leisenring WM, et al. Clinical Significance of Human Coronavirus in Bronchoalveolar Lavage Samples From Hematopoietic Cell Transplant Recipients and Patients With Hematologic Malignancies. Clinical infectious diseases: an official publication of the Infectious Diseases Society of America. 2017; 64(11): 1532–1539. Epub 2017/03/23. https://doi.org/10.1093/cid/cix160 pmid:28329354.
- 32. Chemaly RF, Ghosh S, Bodey GP, Rohatgi N, Safdar A, Keating MJ, et al. Respiratory viral infections in adults with hematologic malignancies and human stem cell transplantation recipients: a retrospective study at a major cancer center. Medicine. 2006; 85(5): 278–287. Epub 2006/09/16. https://doi.org/10.1097/01.md.0000232560.22098.4e pmid:16974212.
- 33. Miyashita H, Mikami T, Chopra N, Yamada T, Chernyavsky S, Rizk D, et al. Do patients with cancer have a poorer prognosis of COVID-19? An experience in New York City. Annals of oncology: official journal of the European Society for Medical Oncology. 2020; 31(8): 1088–1089. Epub 2020/04/25. https://doi.org/10.1016/j.annonc.2020.04.006 pmid:32330541.
- 34. Zhang L, Zhu F, Xie L, Wang C, Wang J, Chen R, et al. Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China. Annals of oncology: official journal of the European Society for Medical Oncology. 2020; 31(7): 894–901. Epub 2020/04/01. https://doi.org/10.1016/j.annonc.2020.03.296 pmid:32224151.
- 35. Vuagnat P, Frelaut M, Ramtohul T, Basse C, Diakite S, Noret A, et al. COVID-19 in breast cancer patients: a cohort at the Institut Curie hospitals in the Paris area. Breast cancer research: BCR. 2020; 22(1): 55. Epub 2020/05/29. https://doi.org/10.1186/s13058-020-01293-8 pmid:32460829.
- 36. He W, Chen L, Chen L, Yuan G, Fang Y, Chen W, et al. COVID-19 in persons with haematological cancers. Leukemia. 2020; 34(6): 1637–1645. Epub 2020/04/26. https://doi.org/10.1038/s41375-020-0836-7 pmid:32332856.
- 37. Dai M, Liu D, Liu M, Zhou F, Li G, Chen Z, et al. Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak. Cancer discovery. 2020; 10(6): 783–791. Epub 2020/04/30. https://doi.org/10.1158/2159-8290.cd-20-0422 pmid:32345594.
- 38. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. Jama. 2020; 323(20): 2052–2059. Epub 2020/04/23. https://doi.org/10.1001/jama.2020.6775 pmid:32320003.
- 39. Mehta V, Goel S, Kabarriti R, Cole D, Goldfinger M, Acuna-Villaorduna A, et al. Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System. Cancer discovery. 2020; 10(7): 935–941. Epub 2020/05/03. https://doi.org/10.1158/2159-8290.cd-20-0516 pmid:32357994.
- 40. Mehra MR, Desai SS, Kuy S, Henry TD, Patel AN. Retraction: Cardiovascular Disease, Drug Therapy, and Mortality in Covid-19. N Engl J Med. The New England journal of medicine. 2020; 382(26): 2582. Epub 2020/06/06. pmid:32501665.
- 41. Taghizadeh-Hesary F, Porouhan P, Soroosh D, Peyroshabany B, Shahidsales S, Keykhosravi B, et al. Covid-19 in cancer and non-cancer patients. International Journal of Cancer Management. 2021; 14(4). https://doi.org/10.5812/ijcm.110907.
- 42. Brar G, Pinheiro LC, Shusterman M, Swed B, Reshetnyak E, Soroka O, et al. COVID-19 Severity and Outcomes in Patients With Cancer: A Matched Cohort Study. Journal of clinical oncology: official journal of the American Society of Clinical Oncology. 2020; 38(33): 3914–3924. Epub 2020/09/29. https://doi.org/10.1200/jco.20.01580 pmid:32986528.
- 43. Basse C, Diakite S, Servois V, Frelaut M, Noret A, Bellesoeur A, et al. Characteristics and Outcome of SARS-CoV-2 Infection in Cancer Patients. JNCI Cancer Spectr. 2021; 5(1): pkaa090. Epub 2021/02/20. https://doi.org/10.1093/jncics/pkaa090 pmid:33604509.
- 44. Yang L, Chai P, Yu J, Fan X. Effects of cancer on patients with COVID-19: a systematic review and meta-analysis of 63,019 participants. Cancer Biol Med. 2021; 18(1): 298–307. Epub 2021/02/26. https://doi.org/10.20892/j.issn.2095-3941.2020.0559 pmid:33628602.
- 45. Venkatesulu BP, Chandrasekar VT, Girdhar P, Advani P, Sharma A, Elumalai T, et al. A Systematic Review and Meta-Analysis of Cancer Patients Affected by a Novel Coronavirus. JNCI Cancer Spectr. 2021; 5(2): pkaa102. Epub 2021/04/21. https://doi.org/10.1093/jncics/pkaa102 pmid:33875976.
- 46. Wu Q, Luo S, Xie X. The impact of anti-tumor approaches on the outcomes of cancer patients with COVID-19: a meta-analysis based on 52 cohorts incorporating 9231 participants. BMC Cancer. 2022; 22(1): 241. Epub 2022/03/06. https://doi.org/10.1186/s12885-022-09320-x pmid:35246063.