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Systematic Review

The outcome of gynecologic cancer patients with Covid-19 infection: A systematic review and meta-analysis

[version 1; peer review: awaiting peer review]
I Gde Sastra Winata1, Januar Simatupang
https://orcid.org/0000-0002-8952-7671
2, Arie A Polim3,4, Yakob Togar
https://orcid.org/0000-0001-6554-6379
2, Advenny Elisabeth Tondang
https://orcid.org/0000-0002-7703-4220
2
I Gde Sastra Winata1, Januar Simatupang
https://orcid.org/0000-0002-8952-7671
2, [...] Arie A Polim3,4, Yakob Togar
https://orcid.org/0000-0001-6554-6379
2, Advenny Elisabeth Tondang
https://orcid.org/0000-0002-7703-4220
2
PUBLISHED 16 May 2022
Author details Author details
OPEN PEER REVIEW
REVIEWER STATUS AWAITING PEER REVIEW

This article is included in the Oncology gateway.

This article is included in the Emerging Diseases and Outbreaks gateway.

This article is included in the Coronavirus collection.

Abstract

Background: Cancer is a comorbidity that leads to progressive worsening of coronavirus disease 2019 (Covid-19) with increased mortality. This is a systematic review and meta-analysis to yield evidence of adverse outcomes of Covid-19 in gynecologic cancer.

Methods: Searches through PubMed, Google Scholar, ScienceDirect, and medRxiv to find articles on the outcome of gynecologic cancer with Covid-19 (24 July 2021–19 February 2022). The Newcastle-Ottawa Scale tool was used to evaluate the quality of included studies. Pooled odds ratio (OR), 95% confidence interval (CI) and random-effects model were presented.

Results: We accepted 51 studies (a total of 1991 gynecologic cancer patients with Covid-19). Covid-19 infection cases were lower in gynecologic cancer vs hematologic cancer (OR 0.71, CI 0.56-0.90, p 0.005). Severe Covid-19 infection and death were lower in gynecologic cancer vs lung and hematologic cancer (OR 0.36, CI 0.16-0.80, p 0.01), (OR 0.52, CI 0.44-0.62, p <0.0001), (OR 0.26, CI 0.10-0.67 p 0.005), (OR 0.63, CI 0.47-0.83, p 0.001) respectively. Increased Covid death was seen in gynecologic cancer vs population with breast cancer, non-Covid cancer, and non-cancer Covid (OR 1.50, CI 1.20-1.88, p 0.0004), (OR 11.83, CI 8.20-17.07, p <0.0001), (OR 2.98, CI 2.23-3.98, p <0.0001) respectively.   

Conclusion: Gynecologic cancer has higher Covid-19 adverse outcomes compared to non-cancer, breast cancer, non-metastatic, and Covid-19 negative population. Gynecologic cancer has fewer Covid-19 adverse outcomes compared to other cancer types, lung cancer, and hematologic cancer. These findings may aid health policies and services during the ongoing global pandemic.

PROSPERO Registration: CRD42021256557 (22/05/21)

Keywords

COVID-19, Critical care outcome, Female genital neoplasms, Hospitalization, Morbidity, Mortality

Corresponding author: Yakob Togar
Competing interests: No competing interests were disclosed.
Grant information: The author(s) declared that no grants were involved in supporting this work.
Copyright:  © 2022 Winata IGS 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 work is properly cited.
How to cite: Winata IGS, Simatupang J, Polim AA et al. The outcome of gynecologic cancer patients with Covid-19 infection: A systematic review and meta-analysis [version 1; peer review: awaiting peer review]. F1000Research 2022, 11:525 (https://doi.org/10.12688/f1000research.111349.1) First published: 16 May 2022, 11:525 (https://doi.org/10.12688/f1000research.111349.1) Latest published: 16 May 2022, 11:525 (https://doi.org/10.12688/f1000research.111349.1)

Introduction

The Covid-19 pandemic has changed the way health care providers around the world manage care provided to their patients. The pandemic has also proven to shift the attitude of standard practice and procedure between providers and patients, for example, to reduce gynecologic cancer patients visiting the hospital as possible because the risk of getting infected with Covid-19 is increased regarding their comorbidities.1 Despite this circumstance, gynecologic cancer patients are still often required to perform routine hospital visits for treatments or other medical procedures under guidance made by gynecological cancer societies during the Covid-19 pandemic.2 The cancer incidence and mortality are still increasing around the world. According to Global Cancer Statistic: 2020 for gynecologic cancer, there are 604.127, 417.367, 313.959, 45.240, and 17.908 new cases of cancer of the cervix uteri, corpus uteri, ovary, vulva, and vagina respectively.3 Most concerns are coming from these patients about how they may proceed to seek or continue their cancer treatment and surveillance during the Covid-19 pandemic.4 Studies are showing various results on increased mortality and severity among cancer patients infected with Covid-19. Systematic review and meta-analysis studying the outcome of cancer patients with Covid-19 show 2.1–4% proportion of cancer patients among those infected with Covid-19, additionally compared to non-cancer with Covid-19 greater amount of mortality and severity are observed in cancer population with Covid-19.5–7 However studies and data on the outcome of gynecologic cancer patients with Covid-19 are still lacking. Several SARS-CoV-2 variants of concern listed by WHO (World Health Organization) pose challenges in mitigating the pandemic as these variants often increase transmission rate and severity.8 The world has been experiencing a wave of active case surges by these variants and on 26 November 2021 the WHO designated the variant Omicron (B.1.1.529) as an addition to the list.9 Thus we attempt to review the literature and quantify the effect of the SARS-Cov-2/Covid-19 infection among gynecologic cancer patients to assess whether the risk of infection, hospitalization, severity, and mortality are increased than non-gynecologic cancer population.

Methods

We conducted this systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses/PRISMA statement.10,82 This study and its protocol were registered to PROSPERO (CRD42021256557).

Eligibility criteria

We took into consideration of studies with observational cohort studies, case-control, cross-sectional, case report, and case series designs that evaluate the outcome of gynecologic cancer patients infected with Covid-19 from the year 2019. Each study ought to report Covid-19 associated infection, hospital admission, mortality, severity, or admission to the intensive care unit (ICU); a summary of eligible studies and its extracted outcome of interest were managed in the Microsoft Excel spreadsheet provided in the Underlying data.82 We exclude studies other than the English language, reviews or guidelines, and inconceivable results of the sought outcome.

Comparator(s)/control

Non-cancer Covid-19 patients, non-Covid-19 cancer patients, other cancer types/non-gynecological cancer with Covid-19.

Database and literature search

Study articles were systematically searched through PubMed/Medline, ScienceDirect, Google Scholar, and medRxiv. Relevant articles had been screened from 24 July 2021 to 19 February 2022. Reference searches from retrieved articles citation lists were identified if any were needed. Boolean operators technique used for Pubmed/Medline search with (“COVID-19” or “2019-nCoV” or “SARS-CoV” or SARSCOV2 or 2019-nCov or “2019 coronavirus” or covid19) AND (gynecology or gynaecology) AND (tumor or malignancy or cancer) AND (outcomes or outcome) AND (gyn* tum* or gyn *malign* or gyn* cancer) AND (cancer surgery or oncolog* surger*) AND (brachytherapy or radiotherapy). We used “Gynecologic cancer AND Covid-19” with Google Scholar, Science Direct, and medRxiv. Two authors separately handled the literature search. Findings were accumulated and stored in Mendeley and Zotero for management and automated duplicate identification. Thorough stepwise screening from title and abstract was then conducted to determine possible article inclusion. Potentially eligible studies were then evaluated for in-depth full-text review. Each author would consult senior authors to resolve any differences found during the literature’s selection process.

Data extraction and quality assessment

The data was extracted independently by two authors and stored them in the Microsoft Excel spreadsheet. Data was then discussed for an agreement. Name of authors, year of publication, country, type of studies, study period, number of patients, comparators, and target conditions was collected. The NOS/Newcastle-Ottawa Scale was used by authors to assess the quality of the cohort and case-control study, and The Joanna Briggs Institute (JBI) Critical Appraisal Checklist for an analytical cross-sectional study.11 The assessment was performed by two authors and the results were discussed with the first author.

Meta-analysis outcome

The main outcome of interest was Covid-19 mortality and severity. Covid-19 severity is defined as either ICU admission, acute respiratory distress syndrome (ARDS), or need for mechanical ventilation. Covid-19 infection and hospitalization were decided as secondary outcomes.

Data analysis & synthesis

We performed data analysis mainly using Review Manager 5.4.1 (RevMan 5.4.1) by Cochrane collaboration.12 If needed, additional synthesis was then performed with STATA-16. We synthesized the dichotomous outcome from each study with an odds ratio (OR). The random-effects model (DerSimonian and Laird) was used to present pooled OR with 95% CI (confidence interval) and the result of overall effect (p). We addressed the presence of heterogeneity with I2 as 0% to 40%: might not be important; 30% to 60%: may represent moderate heterogeneity; 50% to 90%: may represent substantial heterogeneity; 75% to 100%: considerable heterogeneity according to the Cochrane Handbook for Systematic Reviews of Interventions. We performed subgroup analysis by age, gender, other comorbidities status, cancer type, cancer stage, presence of metastatic disease, and active cancer treatment. Sensitivity analysis was performed by dividing multi-center/single-center studies and removing/including the latest study period if concerns were raised of patients population duplication thus we could present robust pooled evidence.13

Results

All supplementary files can be found in the Extended data.82

A total of 51 studies involving the Covid-19 positive population were identified; among them were 1991 gynecologic cancer patients, 221465 non-cancer patients, and 28138 other cancer type patients. In total, 3,717,078 cancer patients were found to be Covid-19 free. Study selection and summary of included studies were presented in Figure 1 and Table 1. The risk of bias in each study was shown in Figures S1 and S2. Due to high heterogeneity found in adverse Covid-19 outcomes (Covid-19 death I2 82%), (Covid-19 hospitalization I2 92%), (Covid-19 infection case I2 72%), we decided to perform subgroup analysis.

7f7153db-4310-454a-97fa-47a861a5bef3_figure1.gif

Figure 1. Study flow diagram.

Table 1. Characteristics of included studies.

AuthorLocationType of studyTime of studyPublication yearNon cancer Covid patientsGynecology Oncology Covid patientsOther Oncology Covid patientsCancer non Covid patientsGender*Cancer stage*Comorbidities*Cancer treatment*Age*Outcome
Angelis V et al.14United KingdomMulti center, prospective cohortMarch–April 20202020NA6107 (Lung 15, Breast 18, Hematological 18)13376 (Gynecological 967)Male 63, Female 50NAHypertension 39, Diabetes 18, Ischemic heart disease 13, COPD 6SACT 85, Radiotherapy 11Median 66, IQR: 54–69, range 21–91Covid infection & Covid death
Ayhan A et al.15TurkeyMulti center, retrospective cohortMarch–April 20202020NA46NA642 (Gynecological)Female 688NAHypertension 29, Diabetes 16, Chronic pulmonary disease 11, Coronary heart disease 6, CKD 1.Major/Complex Cancer Surgery 688<65: 34, >65: 12Covid death
Ayhan M et al.16TurkeySingle center, retrospective cohortMarch–June 20202021NA4 (Ovarian 1, Endometrium 3)80 (Lung 27, Breast 18)1065 (Ovarian 59, Endometrium 21)Female 33, Male 51I: 2, II: 7, III: 18, IV:57,Metastasis 57, Non-meta 27Hypertension 12, Diabetes 16, Coronary artery disease 3, COPD 3, CKD 1SACT 84Median 61, IQR: 21–84Covid infection & Covid hospitalization
Ayhan M et al.17TurkeySingle center, retrospective cohortMarch–May 2020202122897 (Cervix 3, Endometrial 2, Ovarian 2)85 (Lung 26, Breast 17)NAFemale 41, Male 51Metastasis 53, Non-meta 39Hypertension 31, Dibetes 16, COPD 14, Coronary artery disease 13, CKD 4, Chronic liver disease 2, Cerebrovascular disease 2SACT 62<67: 45, >67: 47Covid death
Basse C et al.18FranceSingle center, prospective cohortMarch 20202020NA12129 (Lung 18, Breast 57, Hematological 19)NAFemale 102, Male 39Localized 38, Metastasis 84Chronic lung disease 7, Diabetes 24, Hypertension 48, Other heart disease 21, Systemic disease 6Surgery 11, Radiotheraphy 13, SACT 120, None 17>70: 141Covid death
Bernard A et al.19FranceMulti center, retrospective cohortMarch–April 20202021833291855537 (Lung 873, Breast 561, Hematological 1389)NAFemale 39919, Male 45079Metastasis 1775, Non-meta 2558Hypertension 28163, Heart failure 6641, Chronic respiratory disease 1334, CKD 6948, Diabetes 16216, COPD 4516, Obesity 8289, Chirosis 673NAWith cancer: mean 72, Without cancer: mean 65Covid death
Bersanelli M et al.20ItalyMulti center, prospective cohortJanuary–April 20202020NA1 (Endometrial)13 (Lung 9, Breast 1)52Female 3, Male 10IV: 9Splenectomy 1, Hypertension 8, HIV 1, Diabetes 1ICI 13, ICI + Chemotherapy 1<65: 5, >65: 9Covid death
Bogani G et al.21ItalySingle center, retrospective cohortFebruary–March 20202020NA19 (Ovarian 14, Endometrial 3, Cervical 1, Ovarian+Endometrial 1)NA336 (Gynecological)Female 19NACardiovascular disease 5, CKD 1, Hypothyroidism 2, Plummer disease 1Surgery 5, SACT 8, Planned treatment 6<65: 9, >65: 10Covid death
Cavanna L et al.22ItalySingle center, retrospective cohortApril–June 20202021NA010 (Lung 2)250 (Gynecologic cancer 29)Female 2, Male 8NANASACT 7, Hormonal 1Mean 69.2, Range 54–80Covid infection
Chai C et al.83ChinaMulti center, prospective cohortJanuary–March 2020Pre-prints49816 (Cervical 9, Ovarian 4, Endometrial 3)150 (Lung 25, Breast 19, Hematological 17)498Female 336, Male 328NAHypertension 226, Diabetes 128, Hyperlipidemia 109, Heart disease 78, Cerebrovascular disease 22, COPD 36, CKD 14, Chronic liver disease 12NAMedian 65, IQR 59–70
Dai M et al.23ChinaMulti center, prospective cohortJanuary–February 202020201058 (Cervical 6, Ovarian 1, Endometrial 1)97 (Lung 22, Breast 11, Hematological 8)NAFemale 46, Male 59I/II: 42, III/IV: 37, Metastasis 17Hypertension 160, Cardiovascular disease 51, Diabetes 36, Cerebrovascular disease 26, CKD 28, Chronic liver disease 42Surgery 8, SACT 27, Radiotherapy 13<65: 54, >65: 51Covid death and Severe Covid
de Melo AC et al.24BrazilSingle center, retrospective cohortApril–May 20202020NA22 (Cervical 12, Ovarian 3, Endometrial 5, Vulvar 2)159 (Lung 7, Breast 40, Hematological 34)NAFemale 110, Male 71I/II: 27, III/IV: 124, Metastasis 87Hypertension 77, diabetes 31, CKD 10, COPD/Asthma 7Surgery 12, Radiotheraphy 10, SACT 88, Palliative 32, Hormonal 20<60: 89, 60–74: 67, >75: 25Covid death and Severe Covid
Dettore G et al.25OnCovid-EuropeMulti center, prospective cohortFebruary–June 20202021NA571014 (Lung 154, Breast 177, Hematological 87)NAFemale 231, Male 296Localized 173, Metastatic 223Hypertension 251, Diabetes 115, Cardiovascular disease 128, Chronic pulmonary disease 80, CKD 62, Cerebrovascular disease 37, Liver impairment 11, Immunosuppression 16Ongoing treatment at diagnosis 516, Surgery 510, SACT 319, Radiotherapy 319, Palliative 277Mean: 67.9Covid death
Duarte M et al.26BrazilMulti center, retrospective cohortJanuary–September 202020203846875 (Cervix 47, Uterine 6, Ovaries 22)606 (Lung 51, Breast 90, Hematological 155)NAFemale 374, Male 307I/II: 106, III/IV: 444Heart disease 143, Diabetes 104, Neurologic disease 13, Chronic lung disease 29, Nephropathy 39SACT 431<65: 441, >65: 240Covid death
Fang M et al.84ChinaSingle center, retrospective cohortFebruary–April 2020pre-printsNA452 (Lung 9, Breast 4, Hematological 10)NAFemale 24, Male 32NAHypertension 23, Diabetes 7, Cardiovascular disease 5, Chronic pulmonary disease 1, Chirrosis 2, CNS disease 2NAMedian: 64, IQR 54–71Covid death
Fernandes G et al.27BrazilCross sectionalApril–August 20202021NA26385 (Lung 18, Breast 93, Hematological 47)NAFemale 234, Male 177NANANA<60: 215, >60: 196Covid death
Glasbey J et al.28InternationalMulti center, prospective cohortApril–June 20202020NA25263 (Lung 25, Breast 24, Other 214)8683 (Gyncecological 1057)Female 119, Male 169Early 181, Advance 107Pre-existing respiratory condition 45, Obese 56Minor Surgery 36, Major Surgery 252<50: 30, 50–59: 39, 60–69: 87, 70–79: 96, >80: 36Covid infection
Grivas P et al.29CCC19-InternationalMulti center, prospective cohortMarch–November 20202021NA3224796 (Lung 409, Breast 967, Hematological 1097)NAFemale 2527, Male 2436NACardiovascular 1582, Pulmonary 1091, Renal disease 831, Diabetes 1385Chemotherapy 802, Immunotherapy 248, Targeted therapy 693, Endocirne therapy 483, Locoregional therapy 422<65: 2282, 65–74: 1309, >75: 1375Covid hospitalization & Covid death
Hathout L et al.30United States of AmericaMulti center, retrospective cohortFebruary–June 20202020NA3 (Cervical)044 (Endometrial 24, Cervical 12)Female 3NARespiratory disease 1, Vascular disease 23, Respiratory+Vascular 4, HIV 3Brachytherapy 3NACovid infection
Jee J et al.31United States of AmericaSingle center, retrospective cohortMarch–April 20202020NA15 (Cervical 2, Endometrial 6, Ovarian 5, Vaginal 1, Vulvar 1)294 (Lung 29, Breast 56, Hematological 71)NAFemale 150, Male 159Metastasis 168Pulmonary disease 35, Cardiovascular disease 221, Metabolic disease 156, Neurologic disease 29, HIV 3, Liver disease 4Chemotherapy 102<60: 158, >60: 151Covid death and Severe Covid
Johannesen T et al.32NorwayMulti center, retrospective cohortJanuary–May 20202021NA33514 (Lung 13, Breast 85, Hematological 54)305299 (Gynecologic cancer 23827)NALocalized 36, Distant disease 6NASACT 71, Surgery 90, Radiotherapy 7NACovid infection
Kulle C et al.33TurkeySingle center, retrospective cohortMarch–June 20202021NA01403 (Ovarian 14, Endometrial 9, Cervical 5, Uterine Sarcoma 1, Vulva 1)NANANASurgery 1NACovid infection
Kuru B et al.34TurkeySingle center, retrospective cohortMarch–October 2020202121 (Ovarian)061Female 3NAHypertension 2Surgery 1>65: 1, <65: 2Covid infection
Kwon D et al.85United States of AmericaMulti center, retrospective cohortFebruary–December 2020pre-printsNA1191662 (Lung 33, Breast 241, Hematological 321)48137 (Gynecologic cancer 2877)Female 950, Male 831NAHeart disease 321, Pulmonary disease 294, CKD 273, Diabetes 474, Obese 481SACT 601, Hormonal therapy 8618–65: 1044, 65–75: 420, >75: 317Covid infection
Lara O et al.35United States of AmericaMulti center, prospective cohortMarch–June 20202021NA193 (Uterine 87, Epithelial Ovarian 62, Cervical 24, Vulva 8, Non-Epithelial Ovarian 3, Vaginal 3)NANAFemale 193I/II: 74, III/IV: 100Hypertension 115, Diabetes 70, Asthma 21, COPD 5, Coronary artery disease 13, Autoimune disease 18, CKD 21Surgery 12, Radiotherapy 8, SACT 98Median 65, IQR 54–73Covid hospitalization, Severe Covid & Covid death
Lee L et al.36United KingdomMulti center, prospective cohortMarch–April 20202020NA45755 (Lung 90, Breast 102, Hematological 169)NAFemale 349, Male 449Localized 149, Metastatic 347, Advanced stage 78Cardiovascular disease 109, COPD 61, Diabetes 131, Hypertension 247SACT 461, Surgery 29, Radiotherapy 76Median 69, IQR 59–76Covid death
Lei S et al.37ChinaMulti center, retrospective cohortJanuary–February 20202020251 (Ovarian)8NAFemale 20, Male 14NAHypertension 13, Diabetes 8, Cardiovascular disease 7, Cerebrovascular disease 2, COPD 1, CKD 1Surgery 9Median 55, IQR 43–63Covid death
Li H et al.38United KingdomMulti center, retrospective cohortMarch–October 2020202127517 (Uterine 7, Ovarian 10)272 (Lung 18, Breast 42, Hematological 53)4161 (Uterine 107, Ovarian 115)Female 120, Male 168Localized 235, Metastasis 53NANA50–59: 28, 60–69: 62, 70–79: 159, 80–84: 39Covid infection & Covid death
Liang J et al.39ChinaSingle center, retrospective cohortJanuary–April 20202020NA10 (Uterine 4, Cervical 5, Ovarian 1)99 (Lung 14, Breast 11, Hematological 12)NAFemale 52, Male 57I/II/III: 86, IV: 23Hypertension 38, Diabetes 18, Cardiovascular disease 10, Cerebrovascular disease 4, Chronic pulmonary disease 19, CKD 3, Chronic liver disease 10Surgery 69, Adjuvant 79, Chemo-radiation 71, Targeted-immunotherapy 12>65: 55, <65: 54Covid death
Liu C et al.40ChinaMulti center, prospective cohortDecember 2019–March 20202020NA17199 (Lung 49, Breast 34)NAFemale 103, Male 113I-II: 83, III-IV: 85Diabetes 33, Hypertension 74, Cardiovascular 27, Cerebrovascular 18, COPD 21, Chronic liver disease 13, CKD 978Median 63, IQR 57–70, 2Covid death
Mehta V et al.41United States of AmericaSingle center, retrospective cohortMarch–April 20202020109012206 (Lung 11, Breast 29, Hematological 108)NAFemale 91, Male 127Metastasis 42, Active cancer 92DM 80, Hypertension 147, Chronic lung disease 62, CKD 53, Coronary artery disease 43, CHF 33Chemotherapy 42, Immunotherapy 5, Radiotherapy 490–17: 3, 18–44: 13, 45–64: 64, 65–74: 59, >75: 79Covid death
Modi C et al.42United States of AmericaMulti center, prospective cohortApril–July 20202021NA14 (Lung 1, Breast 1)331 (Gynecologic 26)Female 3, Male 2I-II: 3, III-IV: 2Comorbidity score#: 2: 2, 5: 2, 8: 1Radiotherapy 5<65: 3, >65: 2Covid infection
Monroy-Iglesias MJ et al.43ItalyMulti center, prospective cohortMarch–September 20202021NA2143014 (Gynecological 382)Female 2NANASurgery 16NACovid infection, Severe Covid & Covid death
Mousavi S et al.44IranSingle center, retrospective cohortFebruary–April 20202021NA3 (Ovarian)30 (Lung 4, Breast 6)NAFemale 15, Male 18I/II/III: 17, IV:16Cardiovascular & cerebrovascular disease 9, Diabetes 8, Chronic pulmonary disease 5, Chronic liver disease 1Cytotoxic chemotherapy 18Mean 63.9Covid death
Nakamura S et al.45JapanSingle center, restrospective cohortJanuary–May 20202020NA1 (Cervical)31 (Lung 2, Breast 2, Hematological 7)NAFemale10, Male 22Active cancer 17Diabetes 7, Hypertension 13, Coronary heart disease 4, COPD 4, Asthma 2Surgery 13, SACT 17>70: 20, <70: 12Covid death
Ning M et al.46United States of AmericaSingle center, prospective cohortMarch–April 20202020NA2 (Endometrial 1, Vaginal 1)5 (Breast 1)114 (Gynecological 12)Female 2Metastasis 2, III-IV: 2, Recurrent disease 2NARadiotherapy 7<65: 4, >65: 3Covid death, Covid infection & Covid death
OnCovid Study Group47OnCovid-EuropeMulti center, prospective cohortFebruary 2020–February 20212021NA1152413 (Lung 11, Breast 29, Hematological 108)NAFemale 1240, Male 1390Localized 1237, Advanced 12440–1: 1414, >2: 12201305<65: 1083, >65: 1538Covid death
Ramaswamy A et al.48IndiaSingle center, prospective cohortApril–June 20202020NA13217 (Lung 12, Breast 30, Hematological 90)NAFemale 106, Male 124Advanced 52, I-III: 93Diabetes 30, Hypertension 25, Cardiac illness 2SACT 230Median 42, IQR1–75Covid death
Roel E et al.49SpainMulti center, retrospective cohortMarch–May 2020202193558436 (Corpus Uterus 291, Cervix 81, Ovary 64)4957 (Lung 159, Breast 1236, Hematological 513)255274 (Corpus Uterus 12665, Cervix 3232, Ovary 3564)Female 57507, Male 41444NAAutoimmune 6322, CKD 4167, COPD 2476, Heart disease 11076, Diabetes 6239, Obese 27840, Dementia 2011, Hyperlipidemia 11015NA18–39: 30648, 40–59: 44909, 60–69: 10602, 70–79: 6419, >80: 6373Covid infection, Covid hospitalization & Covid death
Russell B et al.50United KingdomSingle center, retrospective cohortMarch–June 20202021NA10180 (Lung 22, Breast 27, Hematological 33)1962Female 78, Male 112I-II: 55, III-IV: 110NASACT 92, Combination therapy 11<50: 30, 50–59: 36, 60–69: 55, 70–79: 40, >80: 29Covid infection
Shi Z et al.86United KingdomMulti center, prospective cohortJune 2020pre-prints13069 (Cervix 2, Corpus Uteri 2, Ovary 5)409 (Lung 10, Breast 47, Hematological 49)2139 (Vulva 6, Cervix 7, Corpus Uteri 26, Ovary 20)Female 746, Male 816NACOPD 239, Asthma 240, Heart disease 672, Stroke 67, Hypertension 689, Obese 124, Diabetes 232NACancer: Mean 61.36, IQR 56.5–67.5, Non cancer: Mean 56.11, IQR 47.5–64.5Covid infection & Covid death
Song C et al.51ChinaMulti center, retrospective cohortDecember 2019–March 20202020NA17 (Ovarian 3, Endometrial 4, Cervical 10)206 (Lung 39, Breast 31, Hematological 15)NAFemale 107, Male 116NABMI >25: 30126Median 63, IQR 56–71Covid death
Song K et al.52ChinaMulti center, retrospective cohortJanuary–July 20202020NA10238 (Lung 61, Breast 37)NAFemale 120, Male 128I-III: 148, IV: 66Diabetes 38, Hypertension 83, Cardiovascular 28, Cerebrovascular 18, COPD 21Surgery 25, Radiotherapy 10, Combined 15, SACT 51Median 63, IQR 57–70Covid death and Severe Covid
Tian J et al.53ChinaMulti center, retrospective cohortJanuary–March 2020202051915 (Cervical 11, Endometrial 3, Ovarian 1)217 (Lung 23, Breast 31, Hematological 12)NAFemale 379, Male 372I-III: 192, IV: 34Hypertension 292, Diabtes 198, Coronary heart disease 74, CKD 23, Cerebrovascular disease 23, Hepatitis 10, COPD 4Surgery 197, Chemo/Radiotherapy 214, Targeted/Immunotherapy 32Median 64, IQR 57–69Covid death and Severe Covid
Villegas A et al.54SpainSingle center, retrospective cohortMarch–April 20202020NA1 (Ovarian)6138Female 2, Male 1Advance 1, Initial staging 1, Recurrence 1NANA>65: 3Covid infection & Covid death
Wang Q et al.55United States of AmericaMulti center, Case controlAugust 20202020NA30 (Endometrial)1440 (Lung 140, Breast 370, Hematological 220)3070260 (Endometrial 41710)Female 9700, Male 6830NANANA<18: 20, 18–65: 11610, >65: 3900Covid infection
Yang F et al.56ChinaSingle center, retrospective cohortJanuary–April 20202020NA6 (Cervical 4, Endometrial 1, Ovarian 1)46 (Lung 10, Breast 9)NAFemale 24, Male 28NAHypertension 17, Diabetes 7, Coronary heart disease 5, Cerebrovascular disease 4, COPD 4, CKD 1, Cirrhosis 1Chemotherapy 6, Surgery 2, Immunotherapy 1<60: 20, >60: 32Covid death
Yang K et al.57ChinaMulti center, retrospective cohortJanuary–March 20202020NA9 (Cervical)142 (Lung 24, Breast 40, Hematological 22)NAFemale 109, Male 96I-II: 109, III-IV: 40Hypertension 67, Diabetes 22, COPD 5, Coronary heart disease 16, CKD 4Surgery 140, Radiotherapy 37, SACT 129<60: 86, >60:119Covid death
Yang S et al.58ChinaSingle center, retrospective cohortJanuary 2020202012 (Ovarian 1, Cervical 1)NA31Female 3I: 1, III: 1Diabetes & Hypertension 2, Hypertension 1Surgery 2>45: 3Covid infection
Zhang L et al.59ChinaMulti center, retrospective cohortJanuary–February 20202020NA3 (Ovary 1, Endometrial 1, Cervix 1)25 (Lung 7, Breast 3)NAFemale 11, Male 17I/II/III: 18, IV: 10Diabetes 4, Cardio&Cerebrovascular disease 4, Chronic pulmonary disease 1, Chronic liver disease 2Surgery 21, Chemo/radiotherapy 25, Target/Immunotherapy 6Median 65, IQR 56–70Covid death and Severe Covid
Zhou K et al.60FranceMulti center, retrospective cohortJune–November 20202021NA565 (Lung 8, Breast 36)808 (Gynecological 81)Female 56, Male 14Localized 19, Locally advanced 9, Metastasis 32Hypertension 18, Diabetes 6, CKD 7, Heart failure 2, Autoimmune disease 2SACT 70, Radiotherapy 2, Surgery 4Median 61, IQR 27–81Covid infection

* Covid-19 population.

# Charlson comorbidity index.

Gynecologic cancer VS other cancer

Covid-19 infection was equivalent between gynecologic cancer and other cancer patients gathered from eight studies (OR 1.02, CI 0.84–1.22, p 0.87, I2 57%) Figure S3.32,38,49,50,54,55 Gynecologic cancer patients had fewer Covid-19 associated deaths compared to other cancers according to 30 studies (OR 0.82, CI 0.71–0.94, p 0.006, I2 0%) Figure 2.17–19,23–27,29,31,36,38–41,44,45,47,49,51–54,56,57,59 Covid-19 associated severity was not significant from six studies between gynecologic cancer and other cancer types (OR 0.56, CI 0.30–1.03, p 0.06, I2 0%) Figure S4.23,24,31,52,53,59 Data from two studies also showed no significant difference in Covid-19 hospitalizations between gynecologic cancer patients than other cancers (OR 0.73, CI 0.50–1.06, p 0.10, I2 82%) Figure S5.29,49

7f7153db-4310-454a-97fa-47a861a5bef3_figure2.gif

Figure 2. Gynecologic cancer VS other cancer, Covid-19 death.

M-H; mantel-haenszel, CI; confidence interval.

Gynecologic cancer VS non-cancer

Covid-19 infection among gynecologic cancer patients and the non-cancer population was not significant from six studies (OR 1.55, CI 0.81–2.95, p 0.18, I2 90%) Figure S6.34,38,49,55,58 Data from 11 studies revealed death from Covid-19 was higher in gynecologic cancer than non-cancer patients (OR 2.98, CI 2.23–3.98, p < 0.0001, I2 30%) Figure 3.17,19,23,26,37,38,41,49,53 However, severe Covid-19 cases showed no significant difference between gynecologic cancer than non-cancer patients from two studies (OR 1.85, CI 0.77–4.44, p 0.17, I2 0%) Figure S7.23,53

7f7153db-4310-454a-97fa-47a861a5bef3_figure3.gif

Figure 3. Gynecologic cancer VS non-cancer, Covid-19 death.

M-H; mantel-haenszel, CI; confidence interval.

Gynecologic cancer VS non-covid

Data represented from five studies revealed that gynecologic cancer patients were experiencing higher Covid-19 associated death in comparison to other cancer patients without Covid-19 infection (OR 11.83, CI 8.20–17.07, p < 0.0001, I2 5%) Figure 4.15,38,43,49

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Figure 4. Gynecologic cancer with Covid-19 VS other cancer non-Covid, Covid-19 death.

M-H; mantel-haenszel, CI; confidence interval.

Cancer treatment group

We analyzed the effect of active cancer treatment comprising SACT (systemic anti-cancer therapy), radiotherapy, cancer surgery, and hormonal therapy. Data from nine studies showed that, among those who receive active cancer treatment, Covid-19 infection was not significant in gynecologic cancer patients compared to other cancer types (OR 0.75, CI 0.55–1.02, p 0.07, I2 0%) Figure S8.14,16,22,28,30,33,42,46,60 Covid-19 death was not significant among cancer treatment between gynecologic cancer and other cancer types gathered from nine studies (OR 0.86, CI 0.41–1.78, p 0.68, I2 0%) Figure S9.14,20,23,24,31,37,43,46,48 Severe Covid-19 cases among those who were receiving active cancer treatment showed no significant difference between gynecologic cancer than other cancer according to six studies (OR 0.63, CI 0.18–2.25, p 0.48, I2 18%) Figure S10.23,24,31,43,46,59 According to five studies, Covid-19 associated death was comparable in gynecologic cancer with active cancer treatment compared to those who were not receiving cancer treatment (OR 1.06, CI 0.57–1.98, p 0.86, I2 0%) Figure S11.21,23,24,31,35 Lastly, five studies showed severity from Covid-19 was not significant in gynecologic cancer patients who had active cancer treatment compared to those who had none (OR 0.45, CI 0.17–1.20, p 0.11, I2 26%) Figure S12.23,24,31,35,59

Cancer stage and metastatic cancer

There were two studies available for cancer stage analysis.23,24 Overall, adverse Covid-19 events (infection/hospitalization/severity/death) showed no significance between stage I-II gynecologic cancer against stage III-IV other cancer, stage III-IV gynecologic cancer against stage I-II other cancer, and among all cancer patients who had stage III-IV cancer (OR 0.78, CI 0.04–16.18, p 0.88, I2 67%), (OR 0.48, CI 0.15–1.53, p 0.21, I2 0%), (OR 0.59, CI 0.22–1.58, p 0.29, I2 0%) respectively Figures S13–S15. No significance on Covid-19 adverse events between stage III-IV and I-II gynecologic cancer was found in three studies (OR 0.72, CI 0.39–1.33, p 0.29, I2 0%) Figure S16.23,24,35

There were three studies that provided data on metastatic status.19,24,38 Gynecologic cancer with metastasis had increased Covid-19 associated death than those with localized cancer (OR 1.53, CI 1.06–2.21, p 0.02, I2 0%) Figure 5. Contrary, among those who had metastatic diseases, Covid-19 death was not significant between gynecologic cancer compared to other cancer types (OR 0.77, CI 0.54–1.11, p 0.17, I2 0%) Figure S17.

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Figure 5. The Covid-19 death, gynecologic cancer with metastasis VS no metastasis.

M-H; mantel-haenszel, CI; confidence interval.

Gynecologic cancer VS lung cancer

A total of 13 studies provided data on Covid-19 infectivity, infection was not significant in gynecologic cancer than lung cancer (OR 0.86, CI 0.61–1.20, p 0.37, I2 73%) Figure S18.14,16,22,28,32,38,42,49,50,55,60 Data from 30 studies revealed that gynecologic cancer had fewer Covid-19 deaths than lung cancer patients (OR 0.52, CI 0.44–.062, p < 0.0001, I2 0%) Figure 6A.14,17–20,23–27,29,31,36,38,39–41,44,45,47–49,51–53,56,57 Data from six studies showed that gynecologic cancer was having less severity from Covid-19 than lung cancer (OR 0.36, CI 0.16–0.80, p 0.01, I2 0%) Figure 6B.23,24,31,52,53,59 Lastly, two studies reported fewer hospitalizations associated with Covid-19 in gynecologic cancer than lung cancer (OR 0.54, CI 0.40–0.73, p < 0.0001, I2 0%) Figure 6C.16,29

7f7153db-4310-454a-97fa-47a861a5bef3_figure6.gif

Figure 6. Gynecologic cancer VS lung cancer, (A) Covid-19 death, (B) Severe Covid-19, (C) Covid-19 hospitalization.

M-H; mantel-haenszel, CI; confidence interval.

Gynecologic cancer VS breast cancer

Data from 13 studies showed gynecologic cancer and breast cancer were equivalent on the rate of Covid-19 infection (OR 1.05, CI 0.94–1.17, p 0.37, I2 7%) Figure S19.14,16,28,32,38,42,46,49,50,55,60 Interestingly, from 25 studies, gynecologic cancer patients experience higher Covid-19 death compared to breast cancer patients (OR 1.50, CI 1.20–1.88, p 0.0004, I2 19%) Figure 7A.14,17–19,24–27,29,31,36,38–41,44,47–49,52,53,56,57 Covid-19 severity was not significant from seven studies between gynecologic cancer and breast cancer patients (OR 0.83, CI 0.40–1.72, p 0.62, I2 0%) Figure S20.23,24,31,46,52,53,59 Lastly, data from two studies showed gynecologic cancer patients experience higher hospitalization from Covid-19 compared to breast cancer (OR 1.52, CI 1.18–1.96, p 0.001, I2 0%) Figure 7B.16,29

7f7153db-4310-454a-97fa-47a861a5bef3_figure7.gif

Figure 7. Gynecologic cancer VS breast cancer, (A) Covid-19 death, (B) Covid-19 hospitalization.

M-H; mantel-haenszel, CI; confidence interval.

Gynecologic cancer VS hematologic cancer

Data available from eight studies revealed gynecologic cancer patients had less Covid-19 infections compared to hematologic cancer patients (OR 0.71, CI 0.56–0.90, p 0.005, I2 68%) Figure 8A.14,32,38,49,50,55 Data also showed that gynecologic cancer patients were experiencing fewer Covid-19 deaths compared to hematologic cancer from 24 studies (OR 0.63, CI 0.47–0.83, p 0.001, I2 46%) Figure 8B.14,18,19,23–27,29,31,36,38,39,41,45,47–49,51,53,57 Lastly, four studies also showed that gynecologic cancer patients were having less severity from Covid-19 compared to hematologic cancer (OR 0.26, CI 0.10–0.67, p 0.005, I2 0%) Figure 8C.23,24,31,53

7f7153db-4310-454a-97fa-47a861a5bef3_figure8.gif

Figure 8. Gynecologic cancer VS hematologic cancer, (A) Covid-19 infection, (B) Covid-19 death, (C) Severe Covid-19.

M-H; mantel-haenszel, CI; confidence interval.

Gynecologic cancer VS men

Based on 10 studies available for synthesis, there was no significance on Covid-19 infection between gynecologic cancer population and men with cancer (OR 0.58, CI 0.27–1.22, p 0.15, I2 94%) Figure S21.16,22,28,38,42,50,55,60 Compared to men with cancer, the Covid-19 associated death retrieved from 23 studies showed no significant difference (OR 0.75, CI 0.54–1.05, p 0.09, I2 23%) Figure S22.14,17,20,23,24,26,27,29,31,36,38–41,45,48,51,52,56,57 According to six studies, severe Covid-19 was higher in men with cancer compared to gynecologic cancer patients (OR 0.47, CI 0.25–0.88, p 0.02, I2 0%) Figure 9A.23,24,31,52,53,59 Hospitalization from Covid-19 was also higher in men with cancer compared to gynecologic cancer patients synthesized from two studies (OR 0.71, CI 0.56–0.89, p 0.004, I2 0%) Figure 9B.16,29

7f7153db-4310-454a-97fa-47a861a5bef3_figure9.gif

Figure 9. Gynecologic cancer patients VS men with cancer, (A) Severe Covid-19, (B) Covid-19 hospitalization.

M-H; mantel-haenszel, CI; confidence interval.

Age stratification

Data from four studies showed that among the gynecologic cancer population, those who were > 65 compared to <65 years of age had comparable overall adverse Covid-19 outcomes (infection/hospitalization/severity/death), (OR 1.13, CI 0.48–2.62, p 0.78, I2 14%) Figure S23.15,21,23,24 We performed a pairwise comparison of gynecologic cancer with <65 years old against other cancer with >65 years old, and gynecologic cancer with >65 years old against other cancer with <65 years old.23,24,59 Covid-19 adverse outcome was found to be lower in <65 year old gynecologic cancer than >65 years old other cancer population (OR 0.16, CI 0.06–0.47, p 0.0007, I2 0%) Figure 10. Contrary, there was an equivalent Covid-19 adverse outcome between gynecologic cancer with >65 years old and other cancer with <65 years old (OR 1.08, CI 0.36–3.26, p 0.89, I2 0%) Figure S24.

7f7153db-4310-454a-97fa-47a861a5bef3_figure10.gif

Figure 10. The Covid-19 adverse outcome, <65 years old gynecologic cancer VS >65 years old other cancer population.

M-H; mantel-haenszel, CI; confidence interval.

Comorbidities

Cancer is a comorbidity, aside from which we tried to analyze other comorbidities (hypertension, diabetes, cardiovascular disease, pulmonary disease, renal disease, liver disease, immune disease, metabolic-endocrine disease) present within the cancer population. Among those with comorbidities, gynecologic cancer patients had fewer adverse Covid-19 outcomes than other cancer populations according to four studies (OR 0.31, CI 0.12–082, p 0.02, I2 0%) Figure 11.20,23,24,59 Data from five studies showed there was no significant adverse Covid-19 outcome between gynecologic cancer patients with comorbidities against no comorbidities (OR 2.34, CI 0.59–9.79, p 0.24, I2 79%) Figure S25.15,21,23,24,35 Gynecologic cancer patients without comorbidities against other cancer patients with comorbidities had no significant difference in adverse Covid-19 outcomes, according to three studies (OR 0.29, CI 0.04–2.22, p 0.23, I2 56%) Figure S26. 23,24,59 Gynecologic cancer patients with comorbidities against other cancer patients without comorbidities also showed no significant difference in adverse Covid-19 outcomes, according to four studies (OR 0.61, CI 0.22–1.72, p 0.35, I2 0%) Figure S27.20,23,24,59

7f7153db-4310-454a-97fa-47a861a5bef3_figure11.gif

Figure 11. The Covid-19 adverse outcome with comorbidities, gynecologic cancer VS other cancer.

M-H; mantel-haenszel, CI; confidence interval.

Sensitivity analysis

We performed sensitivity analysis by reproducing each outcome synthesis to pre-specified single center to multi-center studies, furthermore excluding overlapped study periods associated with its study centers, thus only one center with the most recent study period was included in Table S1. After exclusion of three studies, a difference of significance was found in severe Covid-19 between gynecologic cancer and cancer men population (OR 0.47, CI 0.19–1.17, p 0.10, I2 0%)24,31,52 Aside from that, the remainder of the calculated OR from reproducing each outcome synthesis by exclusion were within good accordance.

Publication bias

We found no publication bias within our included studies though at first, we identified an asymmetrical funnel plot; it was caused solely by heterogeneity nonetheless (Figures S28–31). After subgroup identification, the funnel plot was corrected and the calculated Egger & Begg’s test for overall Covid death, severity, and hospitalization were p 0.15 and p 1.6. For data associated with Covid-19 infection, the values were p 0.17 and p 1.87.

Discussion

We believe this is the first comprehensive meta-analysis with a large population regarding the outcome of Covid-19 on the gynecologic cancer population. With the 1991 Covid-19 positive gynecologic cancer, we hope we provide new insight into how the global pandemic is affecting practice and services affecting gynecologic cancer. Several meta-analyses showed the prevalence of cancer with Covid-19 infection was 2–4%, Covid-19 mortality was also higher in the cancer patients cohort.5–7,61–65 In this meta-analysis, it was found that gynecologic cancer patients are at an increased risk of Covid-19 death compared to the non-cancer population (OR 2.98, CI 2.23–3.98, p < 0.0001, I2 30%), most studies also support this finding by providing evidence of greater Covid-19 adverse outcome in cancer patients.5–7,61–65 Contrary to the National COVID Cohort Collaborative (N3C) multicenter study from the United States, our result present a significant increase of death in gynecologic cancer with Covid-19 than other cancer types without Covid-19 (OR 11.83, CI 8.20–17.07, p < 0.0001, I2 5%).66 Our finding shows gynecologic cancer with metastatic disease has an increased Covid-19 death compared to those whose cancer is localized (OR 1.53, CI 1.06–2.21, p 0.02, I2 0%), most studies also report identical outcomes to ours.65,67,68 Our analysis also shows gynecologic cancer is associated with higher Covid-19 death and hospitalization compared to breast cancer patients (OR 1.50, CI 1.20–1.88, p 0.0004, I2 19%), (OR 1.52, CI 1.18–1.96, p 0.001, I2 0%) respectively. Other meta-analyses, as well as studies done by the clinical impact of Covid-19 patients with cancer (CCC19) and the “N3C” also supported this finding.62,66,67 Our analysis presents that gynecologic cancer patients have lower Covid-19 death compared to overall other cancer types (OR 0.82, CI 0.71–0.94, p 0.006, I2 0%). Further analysis shows that gynecologic cancer patients with Covid-19 have fewer adverse outcome compared to Covid-19 lung and hematologic cancer. Our findings are (OR 0.52, CI 0.44–.062, p < 0.0001, I2 0%), (OR 0.36, CI 0.16–0.80, p 0.01, I2 0%), (OR 0.54, CI 0.40–0.73, p < 0.0001, I2 0%) for Covid-19 associated death, severity, and hospitalization versus lung cancer respectively. Hematologic cancer (OR 0.71, CI 0.56–0.90, p 0.005, I2 68%), (OR 0.63, CI 0.47–0.83, p 0.001, I2 46%), (OR 0.26, CI 0.10–0.67, p 0.005, I2 0%) for Covid-19 infectivity, death, and severity respectively. The “TERAVOLT” study and the one conducted by Luo et al. also support our finding of a high level of Covid-19 associated adverse outcomes among lung cancer patients.69,70 Other meta-analyses show lung cancer with Covid-19 has a 32.9% case fatality rate (378 lung cancer), compared to the non-lung cancer population the Covid-19 death among lung cancer is also higher (92 lung cancer, 554 control, OR 1.83, p 0.05), (78 lung cancer, 482 control, RR 1.46, p 0.7).5,62,63 Lastly, most studies also support our findings on the increased Covid-19 adverse outcome in the hematologic cancer population, as their results are 34.2% case fatality rate (480 hematologic cancer), (120 hematologic cancer, 758 control, OR 2.39, p 0.02).62,63,65–68 We believe our meta-analysis results correspond to several studies that present the safety of continuing gynecologic cancer care and service during the global pandemic. Safety protocols have been published for gynecologic cancer patients who are seeking treatment and some even recommend the implementation of ERAS (Enhanced Recovery After Surgery).2,71,72 Data from the French Society for Pelvic and Gynecological Surgery (SCGP) and the French (FRANCOGYN) Group reveal there are changes in cancer management strategy during the pandemic time and from 181 gynecologic cancer patients, eight tested positive for Covid-19.73 A multicenter study from three New York City hospitals also show a similar result; among 302 gynecologic cancer patients, 117 experienced a COVID-19-related treatment modification, 19 had a positive Covid-19 result and among them three were asymptomatic, 11 had mild symptoms, three were hospitalized, and two died.74 Lastly, data from the United Kingdom, Turkey, and Italy show that while maintaining gynecologic cancer treatment during the pandemic time the Covid-19 infection rate is found at a low level, 1/289 is Covid-19 positive and 1 post-operative death suspected of Covid-19 (UK), 2/200 is suspected with Covid-19 but neither was positive for COVID-19 on polymerase chain reaction testing (Turkey), and 1/930 is Covid-19 positive (Italy).75–77 Other meta-analysis shows Covid-19 infection with existing comorbidities such as hypertension (OR 1.95, p < 0.0001), diabetes (OR 1.97, p < 0.0001), respiratory disease (OR 2.74, p < 0.0001), cardiovascular disease (OR 3.05, p < 0.0001), cerebrovascular disease (OR 4.78, p < 0.0001), kidney disease (OR 4.90, p < 0.0001), and cancer (OR 1.89, p < 0.0001) increase the risk of mortality.78 Our analyzed population comprises cancer as the main comorbidity, however with comorbidities other than cancer, our study shows that the gynecologic cancer population with additional comorbidities has fewer adverse events than other cancer with comorbidities (OR 0.31, CI 0.12–082, p 0.02, I2 0%). Other meta-analyses prove that men have increased Covid-19 severity and mortality.78,79 Our findings correspond by showing that severity and hospitalization from Covid-19 were higher in men with cancer compared to gynecologic cancer patients (OR 0.47, CI 0.25–0.88, p 0.02, I2 0%), (OR 0.71, CI 0.56–0.89, p 0.004, I2 0%) respectively. Age thresholds above 50 and 60 years old have an effect on Covid-19 mortality.78,80 In our study Covid-19 adverse outcome was lower in <65 years old gynecologic cancer than <65 years old other cancer patients (OR 0.16, CI 0.06–0.47, p 0.0007, I2 0%). Other meta-analysis on Covid-19 with active cancer treatment shows that cancer surgery (OR 1.14, p < 0.01), chemotherapy (OR 1.60, <0.01), and overall cancer treatment type (OR 1.16, p < 0.01) have a higher risk of death.81 However in our study Covid-19 death is equivalent in gynecologic cancer with active cancer treatment compared to those who are not receiving cancer treatment (OR 1.06, CI 0.57–1.98, p 0.86, I2 0%).

We hope these findings will be useful among gynecologist-oncologists in cancer centers or tertiary cancer referral centers who provide care to gynecologic cancer patients during the ongoing Covid-19 pandemic.

In several data syntheses with the statistically nonsignificant value, we analyze few data regarding severity, hospitalization, age, cancer stage/metastatic status, other comorbidities aside from cancer, and cancer treatment type due to limited data, however those aforementioned are well represented and distributed through other synthesis based on the patient’s characteristics available in Table 1.

Data availability

Underlying data

Figshare: Systematic review and Meta-analysis file. https://doi.org/10.6084/m9.figshare.19470131.82

This project contains the following underlying data:

  • • Outcome of Gynaecologic Cancer Patients With The Covid-19 Infection A Systematic Review And Meta Analysis (26.3.2022).rm5

  • • Meta Qulitative.xlsx

  • • Meta Data.xlsx

  • • Table 1.docx

Extended data

This project contains the following extended data:

  • • Supplementary Materials.docx

Reporting guidelines

Figshare: PRISMA checklist and flow diagram for ‘The outcome of gynecologic cancer patients with Covid-19 infection: A systematic review and meta-analysis’. https://doi.org/10.6084/m9.figshare.19470131.82

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Acknowledgments

We thank the staff of Gynecology Oncology (Sanglah Hospital, Faculty of Medicine, Udayana University, Denpasar, Bali, Indonesia), staff of Reproductive Endocrinology and Infertility (Morula IVF), (School of Medicine and Health Sciences, Atmajaya Catholic University of Indonesia, Jakarta, Indonesia), and staff of Department of Obstetrics and Gynecology (UKI Hospital, Faculty of Medicine, Christian University of Indonesia, Jakarta, Indonesia) to make this research collaboration possible.

Previous versions of this article can be found on medRXiv (https://doi.org/10.1101/2022.03.20.22272676) and Research Square (https://doi.org/10.21203/rs.3.rs-1472028/v1).

References

  • 1.  Ramirez PT, Chiva L, Eriksson AGZ, et al.: COVID-19 Global Pandemic: Options for Management Gynecologic Cancers. Int J Gynecol Cancer. 2020; 30: 561–563. Publisher Full Text
  • 2.  Uwins C, Bhandoria GP, Shylasree TS, et al.: COVID-19 and gynecological cancer: a review of the published guidelines. Int J Gynecol Cancer. 2020; 30: 1424–1433. Publisher Full Text
  • 3.  Sung H, Ferlay J, Siegel RL, et al.: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021; 71: 209–249. Publisher Full Text
  • 4.  Frey MK, Blank SV: Coronavirus Concerns: What do women with gynecologic cancer need to know during The Covid-19 crisis?. Gynecol Oncol. 2020; 158: 32–33. PubMed Abstract | Publisher Full Text
  • 5.  Han S, Zhuang Q, Chiang J, et al.: Impact of cancer diagnoses on the outcomes of patients with COVID- 19: a systematic review and meta- analysis. BMJ Open. 2022; 12: e044661. PubMed Abstract | Publisher Full Text
  • 6.  ElGohary GM, Hashmi S, Styczynski J, et al.: The risk and prognosis of COVID-19 infection in cancer patients: A systematic review and meta-analysis. Hematol Oncol Stem Cell Ther. PubMed Abstract | Publisher Full Text
  • 7.  Giannakoulis VG, Papoutsi E, Siempos II: Effect of Cancer on Clinical Outcomes of Patients With Covid-19: A Meta-Analysis of Patient Data. JCO Global Oncology. 2020; 6: 799–808. PubMed Abstract | Publisher Full Text
  • 8.  Choi JY, Smith DM: SARS-CoV-2 Variants of Concern. Yonsei Med J. 2021 Nov; 62(11): 961–968. Publisher Full Text
  • 9.  Minol: Enhancing Readiness for Omicron (B.1.1.529): Technical Brief and Priority Actions forMember States.2021. Publisher Full Text
  • 10.  Page MJ, McKenzie JE, Bossuyt PM, et al.: The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021; 372: n71. Publisher Full Text
  • 11.  Ma LL, Wang YY, Yang ZH, et al.: Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better?. Military Med Res. 2020; 7: 7. PubMed Abstract | Publisher Full Text
  • 12.   Review Manager (RevMan) [Computer program]. Version 5.4. The Cochrane Collaboration; 2020.
  • 13.  Bauchner H, Golub RM, Zylke J: Editorial Concern-Possible Reporting of the Same Patients With COVID-19 in Different Reports. JAMA. 2020 Apr 7; 323(13): 1256. PubMed Abstract | Publisher Full Text
  • 14.  Angelis V, Tippu Z, Joshi K, et al.: Defining the true impact of coronavirus disease 2019 in the at-risk population of patients with cancer. Eur J Cancer. 2020; 136: 99–106. Publisher Full Text
  • 15.  Ayhan A, Oz M, Topfedaisi Ozkan N, et al.: Perioperative SARS-CoV-2 infection among women undergoing major gynecologic cancer surgery in the COVID-19 era: A nationwide, cohort study from Turkey. Gynecol Oncol. 2021; 160(2): 499–505. Publisher Full Text
  • 16.  Ayhan M, Laçin Ş, Özyükseler DT, et al.: Does systemic anti-tumor therapy increase COVID-19 risk in patients with cancer?. J Oncol Pharm Pract. 2021; 27(6): 1461–1467. Publisher Full Text
  • 17.  Ayhan M, Odabas H, Turan N, et al.: Factors affecting the mortality rate of patients with cancer hospitalized with COVID-19: a single center’s experience. J Chemother. 2021; 33(7): 499–508. PubMed Abstract | Publisher Full Text
  • 18.  Basse C, Diakite S, Servois V, et al.: Characteristics and Outcome of SARS-CoV-2 Infection in Cancer Patients. JNCI cancer Spectr. 2021; 5(1). PubMed Abstract | Publisher Full Text
  • 19.  Bernard A, Cottenet J, Bonniaud P, et al.: Comparison of Cancer Patients to Non-Cancer Patients among COVID-19 Inpatients at a National Level. Cancers (Basel). 2021; 13(6): 1–15. PubMed Abstract | Publisher Full Text
  • 20.  Bersanelli M, Giannarelli D, De Giorgi U, et al.: Symptomatic COVID-19 in advanced-cancer patients treated with immune-checkpoint inhibitors: prospective analysis from a multicentre observational trial by FICOG. Ther Adv. Med Oncol. 2020; 12. PubMed Abstract | Publisher Full Text
  • 21.  Bogani G, Ditto A, Bosio S, et al.: Cancer patients affected by COVID-19: Experience from Milan, Lombardy. Gynecol Oncol. 2020; 158(2): 262–265. PubMed Abstract | Publisher Full Text
  • 22.  Cavanna L, Citterio C, Di Nunzio C, et al.: Prevalence of COVID-19 Infection in Asymptomatic Cancer Patients in a District With High Prevalence of SARS-CoV-2 in Italy. Cureus. 2021; 13(3): e13774. PubMed Abstract | Publisher Full Text
  • 23.  Dai M, Liu D, Liu M, et al.: Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak. Cancer Discov. 2020; 10(6): 783–791. PubMed Abstract | Publisher Full Text
  • 24.  De Melo AC, Thuler LCS, Da Silva JL, et al.: Cancer inpatients with COVID-19: A report from the Brazilian National Cancer Institute. PLoS One. 2020; 15(10): e0241261. PubMed Abstract | Publisher Full Text
  • 25.  Dettorre GM, Dolly S, Loizidou A, et al.: Systemic pro-inflammatory response identifies patients with cancer with adverse outcomes from SARS-CoV-2 infection: the OnCovid Inflammatory Score. J Immunother cancer. 2021; 9(3): e002277. PubMed Abstract | Publisher Full Text
  • 26.  Duarte MBO, Leal F, Argenton JLP, et al.: Outcomes of COVID-19 Patients under Cytotoxic Cancer Chemotherapy in Brazil. Cancers (Basel). 2020; 12(12): 1–13. PubMed Abstract | Publisher Full Text
  • 27.  Fernandes GA, Feriani D, França e Silva ILA, et al.: Differences in mortality of cancer patients with COVID-19 in a Brazilian cancer center. Semin Oncol. 2021; 48(2): 171. Publisher Full Text
  • 28.  Glasbey JC, Nepogodiev D, Simoes JFF, et al.: Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study. J Clin Oncol. 2021; 39(1): 66–78. PubMed Abstract | Publisher Full Text
  • 29.  Grivas P, Khaki AR, Wise-Draper TM, et al.: Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium. Ann Oncol Off J Eur Soc Med Oncol. 2021; 32(6): 787–800. Publisher Full Text
  • 30.  Hathout L, Ennis RD, Mattes MD, et al.: The Impact of COVID-19 on Brachytherapy During the Pandemic: A Rutgers-Robert Wood Johnson Barnabas Health Multisite Experience. Adv. Radiat Oncol. 2021; 6(1). PubMed Abstract | Publisher Full Text | Free Full Text
  • 31.  Jee J, Foote MB, Lumish M, et al.: Chemotherapy and COVID-19 Outcomes in Patients With Cancer. J Clin Oncol. 2020; 38(30): 3538–3546. PubMed Abstract | Publisher Full Text
  • 32.  Johannesen TB, Smeland S, Aaserud S, et al.: COVID-19 in Cancer Patients, Risk Factors for Disease and Adverse Outcome, a Population-Based Study From Norway. Front Oncol. 2021; 11. Publisher Full Text
  • 33.  Kulle CB, Azamat IF, Vatansever D, et al.: Is elective cancer surgery feasible during the lock-down period of the COVID-19 pandemic? Analysis of a single institutional experience of 404 consecutive patients. J Surg Oncol. 2021; 123(7): 1495–1503. PubMed Abstract | Publisher Full Text
  • 34.  Kuru B, Kale A, Basol G, et al.: Is it safe to perform elective gynaecologic surgery during the two peaks of COVID-19 pandemic?. Int J Clin Pract. 2021; 75(11): e14816. PubMed Abstract | Publisher Full Text
  • 35.  Lara OD, Smith M, Wang Y, et al.: COVID-19 outcomes of patients with gynecologic cancer in New York City: An updated analysis from the initial surge of the pandemic. Gynecol Oncol. 2022; 164(2): 304–310. Publisher Full Text
  • 36.  Lee LYW, Cazier JB, Angelis V, et al.: COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study. Lancet (London, England). 2020; 395(10241): 1919–1926. PubMed Abstract | Publisher Full Text
  • 37.  Lei S, Jiang F, Su W, et al.: Clinical characteristics and outcomes of patients undergoing surgeries during the incubation period of COVID-19 infection. EClinicalMedicine. 2020; 21: 100331. PubMed Abstract | Publisher Full Text
  • 38.  Li H, Baldwin E, Zhang X, et al.: Comparison and impact of COVID-19 for patients with cancer: a survival analysis of fatality rate controlling for age, sex and cancer type. BMJ Heal Care Informatics. 2021; 28(1): e100341. PubMed Abstract | Publisher Full Text
  • 39.  Liang J, Jin G, Liu T, et al.: Clinical characteristics and risk factors for mortality in cancer patients with COVID-19. Front Med. 2021; 15(2): 264–274. PubMed Abstract | Publisher Full Text
  • 40.  Liu C, Li L, Song K, et al.: A nomogram for predicting mortality in patients with COVID-19 and solid tumors: a multicenter retrospective cohort study. J Immunother Cancer. 2020; 8(2): e001314. PubMed Abstract | Publisher Full Text
  • 41.  Mehta V, Goel S, Kabarriti R, et al.: Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System. Cancer Discov. 2020; 10(7): 935–941. PubMed Abstract | Publisher Full Text
  • 42.  Modi C, Dragun AE, Henson CF, et al.: A Statewide Multi-Institutional Study of Asymptomatic Pretreatment Testing of Radiation Therapy Patients for SARS-CoV-2 in a High-Incidence Region of the United States. Adv Radiat Oncol. 2021; 6(4). PubMed Abstract | Publisher Full Text | Free Full Text
  • 43.  Monroy-Iglesias MJ, Tagliabue M, Dickinson H, et al.: Continuity of Cancer Care: The Surgical Experience of Two Large Cancer Hubs in London and Milan. Cancers (Basel). 2021; 13(7). Publisher Full Text
  • 44.  Mousavi SA, Rostami T, Kiumarsi A, et al.: COVID-19 and cancer: A comparative case series. Cancer Treat Res Commun. 2021; 27: 100339. PubMed Abstract | Publisher Full Text
  • 45.  Nakamura S, Kanemasa Y, Atsuta Y, et al.: Characteristics and outcomes of coronavirus disease 2019 (COVID-19) patients with cancer: a single-center retrospective observational study in Tokyo, Japan. Int J Clin Oncol. 2021; 26: 485–493. Publisher Full Text
  • 46.  Ning MS, McAleer MF, Jeter MD, et al.: Mitigating the impact of COVID-19 on oncology: Clinical and operational lessons from a prospective radiation oncology cohort tested for COVID-19. Radiother Oncol. 2020; 148: 252–257. PubMed Abstract | Publisher Full Text
  • 47.  Pinato DJ, Patel M, Scotti L, et al.: Time-Dependent COVID-19 Mortality in Patients With Cancer: An Updated Analysis of the OnCovid Registry. JAMA Oncol. 2022; 8(1): 114–122. Publisher Full Text
  • 48.  Ramaswamy A, Nayak L, Roy Moulik N, et al.: COVID-19 in cancer patients on active systemic therapy - Outcomes from LMIC scenario with an emphasis on need for active treatment. Cancer Med. 2020; 9(23): 8747–8753. PubMed Abstract | Publisher Full Text
  • 49.  Roel E, Pistillo A, Recalde M, et al.: Cancer and the risk of coronavirus disease 2019 diagnosis, hospitalisation and death: A population-based multistate cohort study including 4 618 377 adults in Catalonia, Spain. Int J Cancer. 2022; 150(5): 782–794. PubMed Abstract | Publisher Full Text
  • 50.  Russell B, Moss CL, Palmer K, et al.: COVID-19 Risk Factors for Cancer Patients: A First Report with Comparator Data from COVID-19 Negative Cancer Patients. Cancers. 2021; 13(10): 2479. PubMed Abstract | Publisher Full Text
  • 51.  Song C, Dong Z, Gong H, et al.: An online tool for predicting the prognosis of cancer patients with SARS-CoV-2 infection: a multi-center study. J Cancer Res Clin Oncol. 2021; 147(4): 1247–1257. PubMed Abstract | Publisher Full Text
  • 52.  Song K, Gong H, Xu B, et al.: Association between recent oncologic treatment and mortality among patients with carcinoma who are hospitalized with COVID-19: A multicenter study. Cancer. 2021; 127(3): 437–448. PubMed Abstract | Publisher Full Text
  • 53.  Tian J, Yuan X, Xiao J, et al.: Clinical characteristics and risk factors associated with COVID-19 disease severity in patients with cancer in Wuhan, China: a multicentre, retrospective, cohort study. Lancet Oncol. 2020; 21(7): 893–903. PubMed Abstract | Publisher Full Text
  • 54.  Cabrera Villegas A, Romero Robles LG, Boulvard Chollet XLE, et al.: [18 F]-FDG PET/CT in oncologic patients with unsuspected asymptomatic infection with SARS-CoV-2. Eur J Nucl Med Mol Imaging. 2021; 48(3): 786–793. PubMed Abstract | Publisher Full Text
  • 55.  Wang QQ, Berger NA, Xu R: Analyses of Risk, Racial Disparity, and Outcomes Among US Patients With Cancer and COVID-19 Infection. JAMA Oncol. 2021; 7(2): 220–227. PubMed Abstract | Publisher Full Text
  • 56.  Yang F, Shi S, Zhu J, et al.: Clinical characteristics and outcomes of cancer patients with COVID-19. J Med Virol. 2020; 92(10): 2067–2073. Publisher Full Text
  • 57.  Yang K, Sheng Y, Huang C, et al.: Clinical characteristics, outcomes, and risk factors for mortality in patients with cancer and COVID-19 in Hubei, China: a multicentre, retrospective, cohort study. Lancet Oncol. 2020; 21(7): 904–913. PubMed Abstract | Publisher Full Text
  • 58.  Yang S, Zhang Y, Cai J, et al.: Clinical Characteristics of COVID-19 After Gynecologic Oncology Surgery in Three Women: A Retrospective Review of Medical Records. Oncologist. 2020; 25(6): e982–e985. PubMed Abstract | Publisher Full Text
  • 59.  Zhang L, Zhu F, Xie L, et al.: Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China. Ann Oncol Off J Eur Soc Med Oncol. 2020; 31(7): 894–901. PubMed Abstract | Publisher Full Text
  • 60.  Zhou K, Blanc-Lapierre A, Seegers V, et al.: Anosmia but Not Ageusia as a COVID-19-Related Symptom among Cancer Patients-First Results from the PAPESCO-19 Cohort Study. Cancers (Basel). 2021; 13(14). PubMed Abstract | Publisher Full Text
  • 61.  Salunke AA, Nandy K, Pathak SK, et al.: Impact of COVID -19 in cancer patients on severity of disease and fatal outcomes: A systematic review and meta-analysis. Diabetes Metab Syndr Clin Res Rev. 2020; 14(5): 1431–1437. PubMed Abstract | Publisher Full Text
  • 62.  Venkatesulu BP, Chandrasekar VT, Girdhar P, et al.: A Systematic Review and Meta-Analysis of Cancer Patients Affected by a Novel Coronavirus. JNCI Cancer Spectr. 2021; 5(2). PubMed Abstract | Publisher Full Text
  • 63.  Zhang H, Han H, He T, et al.: Clinical Characteristics and Outcomes of COVID-19-Infected Cancer Patients: A Systematic Review and Meta-Analysis. J Natl Cancer Inst. 2021; 113(4): 371–380. PubMed Abstract | Publisher Full Text
  • 64.  Sorouri M, Kasaeian A, Mojtabavi H, et al.: Clinical characteristics, outcomes, and risk factors for mortality in hospitalized patients with COVID-19 and cancer history: a propensity score-matched study. Infect Agents Cancer. 2020; 15: 74. PubMed Abstract | Publisher Full Text
  • 65.  Chavez-MacGregor M, Lei X, Zhao H, et al.: Evaluation of COVID-19 Mortality and Adverse Outcomes in US Patients With or Without Cancer. JAMA Oncol. 2022; 8(1): 69–78. Publisher Full Text
  • 66.  Sharafeldin N, Bates B, Song Q, et al.: Outcomes of COVID-19 in Patients With Cancer: Report From the National COVID Cohort Collaborative (N3C). J Clin Oncol. 2021; 39(20): 2232–2246. PubMed Abstract | Publisher Full Text
  • 67.  Albiges L, Foulon S, Bayle A, et al.: Determinants of the outcomes of patients with cancer infected with SARS-CoV-2: results from the Gustave Roussy cohort. Nat Cancer. 1: 965–975. Publisher Full Text
  • 68.  Kuderer NM, Choueiri TK, Shah DP, et al.: Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study. Lancet. 2020; 395(10241): 1907–1918. Publisher Full Text
  • 69.  Garassino MC, Whisenant JG, Huang L-C, et al.: COVID-19 in patients with thoracic malignancies (TERAVOLT): first results of an international, registry-based, cohort study. Lancet Oncol. 2020; 21(7): 914–922. PubMed Abstract | Publisher Full Text
  • 70.  Luo J, Rizvi H, Preeshagul IR, et al.: COVID-19 in patients with lung cancer. Ann Oncol Off J Eur Soc Med Oncol. 2020; 31(10): 1386–1396. PubMed Abstract | Publisher Full Text
  • 71.  Thomakos N, Pandraklakis A, Bisch SP, et al.: ERAS protocols in gynecologic oncology during COVID-19 pandemic. Int J Gynecol Cancer. 2020; 30(6): ijgc-2020-001439. Publisher Full Text
  • 72.  Bisch SP, Jago CA, Kalogera E, et al.: Outcomes of enhanced recovery after surgery (ERAS) in gynecologic oncology – A systematic review and meta-analysis. Gynecol Oncol. 2021; 161(1): 46–55. PubMed Abstract | Publisher Full Text
  • 73.  Jouen T, Gauthier T, Azais H, et al.: The impact of the COVID-19 coronavirus pandemic on the surgical management of gynecological cancers: Analysis of the multicenter database of the French SCGP and the FRANCOGYN group. J Gynecol Obstet Hum Reprod. 2021; 50(8): 102133. PubMed Abstract | Publisher Full Text
  • 74.  Frey MK, Fowlkes RK, Badiner NM, et al.: Gynecologic oncology care during the COVID-19 pandemic at three affiliated New York City hospitals. Gynecol Oncol. 2020; 159(2): 470–475. PubMed Abstract | Publisher Full Text
  • 75.  Leung E, Pervaiz Z, Lowe-Zinola J, et al.: Maintaining surgical care delivery during the COVID-19 pandemic: A comparative cohort study at a tertiary gynecological cancer centre. Gynecol Oncol. 2021; 160(3): 649–654. PubMed Abstract | Publisher Full Text
  • 76.  Dursun P, Dervisoglu H, Daggez M, et al.: Performing gynecologic cancer surgery during the COVID-19 pandemic in Turkey: A multicenter retrospective obser.
  • 77.  Palluzzi E, Corrado G, Marchetti C, et al.: Medical treatment of patients with gynecologic cancer during the COVID-19 pandemic. Int J Gynecol Cancer. 2021; 31(8): 1154–1158. Publisher Full Text
  • 78.  Biswas M, Rahaman S, Biswas T, et al.: Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis. Intervirology. 2021; 64: 36–47. PubMed Abstract | Publisher Full Text
  • 79.  Peckham H, de Gruijter NM , Raine C, et al.: Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission. Nat Commun. 2020; 11: 6317. PubMed Abstract | Publisher Full Text
  • 80.  Bonanad C, García-Blas S, Tarazona-Santabalbina F, et al.: The Effect of Age on Mortality in Patients With COVID-19: A Meta-Analysis With 611,583 Subjects. J Am Med Dir Assoc. 2020; 21(7): 915–918. Publisher Full Text
  • 81.  Park R, Lee SA, Kim SY, et al.: Association of active oncologic treatment and risk of death in cancer patients with COVID-19: a systematic review and meta-analysis of patient data. Acta Oncol (Madr). 2021; 60(1): 13–19. PubMed Abstract | Publisher Full Text
  • 82.  Winata IGS, Simatupang J, Polim AA, et al.: Systematic review and Meta-analysis file.2022. Publisher Full Text
  • 83.  Chai C, Feng X, Lu M, et al.: One-Year and Consequences of COVID-19 in Cancer Patients: a Cohort Study. 18 May 2021; PREPRINT (Version 1) available at Research Square.Publisher Full Text
  • 84.  Fang M, Ling J, Wu Y, et al.: Clinical characteristics, outcomes and follow-up of COVID-19 infection in cancer patients. 08 June 2020; PREPRINT (Version 1) available at Research Square.Publisher Full Text
  • 85.  Kwon DH, Cadena J, Nguyen S: COVID- 19 outcomes in patients with cancer: Findings from the University of California health system database. Cancer Med. 2022; 00: 1–12. PubMed Abstract | Publisher Full Text
  • 86.  Shi Z, Resurreccion WK, Wang C-H, et al.: Association of Cancer with Risk and Mortality of COVID-19: Results from the UK Biobank. medRxiv. Published online January 1, 2020: 2020.07.10.20151076. Publisher Full Text

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Winata IGS, Simatupang J, Polim AA et al. The outcome of gynecologic cancer patients with Covid-19 infection: A systematic review and meta-analysis [version 1; peer review: awaiting peer review] F1000Research 2022, 11:525 (https://doi.org/10.12688/f1000research.111349.1)
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