Risk of cervical cancer and high-grade lesions in vulnerable women in high and upper middle-income countries: systematic review and meta-analysis.

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Marc Bardou, Amir Hassine, Anna Tisler, Myriam Martel This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6180822/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Mar, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Background: Cervical cancer (CC) is largely preventable but still causes around 300,000 deaths annually, particularly among vulnerable women. Methods: This systematic review and meta-analysis included studies from four databases (MEDLINE, EMBASE, CENTRAL, ISI Web of Science) up to February 2024 (from 2004 for HIV). We examined seven vulnerable groups in middle- and high-income countries: women of low socioeconomic status (WLSES), prisoners, sex workers, women with substance use disorders (WSUD), mental illness (WMI), migrants, and women living with HIV (WLWH). Observational studies on CC and high-grade lesion (HGL) risk, incidence, or prevalence were included. Independent reviewers assessed all articles. The main outcome was CC or HGL risk, measured assessed by incidence rate ratio (IRR), risk ratio (RR), standardized incidence ratio (SIR), or odds ratio (OR). PROSPERO registration: CRD42024535331. Findings: We included 126 studies. Vulnerable women had a significantly higher risk of CC (RR 2.78, 95%CI 2.32-3.32) and HGL (RR 2.51, 95%CI 2.02-3.11), with WSUD, prisoners, and WLWH facing a 2- to 5-fold increased risk. Interpretation: Marginalised women face a higher CC and HGL risk, highlighting the need for targeted policies to improve screening and treatment access. Funding: this systematic review and meta-analysis is funded by the CBIG-SCREEN project (The CBIG-SCREEN project has received funding from the EU Horizon 2020 research and innovation program under Grant Agreement No 964049). Health sciences/Oncology/Cancer/Cancer epidemiology Health sciences/Oncology/Cancer/Cancer prevention Figures Figure 1 Figure 2 Figure 3 Figure 4 RESEARCH IN CONTEXT Evidence before this study Numerous cohort studies have shown that socially disadvantaged women face a higher risk of developing cervical cancer (CC) and high-grade lesions (HGL). Meta-analyses conducted on specific groups of vulnerable women have reported a significant increase in risk for both outcomes—for instance, women living with HIV (WLWH) had a CC relative risk (RR) of 6.07 (95% CI: 4.4–8.37). However, no studies have been conducted to assess this risk using a broader definition of vulnerability, and there is a lack of research on these populations in middle- and high-income countries Added value of this study We calculated the pooled estimate of CC risk based on 106 studies, encompassing over 48 million vulnerable women. Similarly, the analysis of HGL was derived from 32 individual studies, including over 6 million vulnerable women. Additionally, we provided pooled estimates for each specific vulnerability group. Implication of all the available evidence Vulnerable women have more than twice the risk of developing both CC and HGL compared to the general population (RR 2.8, 95% CI 2.34–3.35; RR 2.45, 95% CI 2.0–3.01, respectively). Our study highlights the increased risk of progression from HGL to CC, which may indicate deficiencies in follow-up care. Countries such as England and the United States have begun implementing patient navigator programs aimed at reconnecting these populations with healthcare services. While initial results are promising, further research is needed to assess the effectiveness and long-term economic sustainability of these interventions within healthcare systems. INTRODUCTION The World Health Organization (WHO) launched a global initiative aimed to eliminate cervical cancer (CC) by 2030. The strategy, aimed at eradicated the more than 600,000 new cases reported worldwide each year, 1 rests on three pillars: 90% of young girls vaccinated against human papillomavirus (HPV) by age 15; 70% of adult women screened by the age 35 to 45; and 90% of early-stage cancers treated appropriately. 2 While risk of CC and mortality are higher in low- and middle-income countries, CC persists even in developed countries, demonstrating a marked socioeconomic gradient. Vulnerable groups—including women living with HIV (WLWH), female sex workers (FSW), migrants, prisoners, and women with substance use disorder (WSUD) or mental illness (WMI)—have less access to vaccination, screening, and treatment. Though these disparities are well known, policy responses in many developed countries have been insufficient to effectively reduce them. 3 The last recommendations of the US Preventive Services Task Force (USPSTF) on CC screening, highlighted the need for risk-based, tailored approaches to reduce the burden of the disease. 4 To support these approaches, we must quantify risk so public health decision makers can adapt policies, and re-allocate resources to reduce CC risk and improve public health outcomes. We thus conducted a systematic review and meta-analysis to assess these disparities. We reported risk estimates for vulnerability groups overall and then for subgroups of women at high risk in high- and upper-middle-income countries. METHODS This systematic review and meta-analysis follows the Cochrane Handbook and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 5 based on the full search protocol published in Prospero (ID: CRD42024535331). 6 Eligibility Criteria We included any English-language epidemiological studies (cohort, case-control, cross-sectional, and registry linkage studies) of cervical high-grade lesions (HGL) or cancer among vulnerable women with or without a comparison group, conducted in upper-middle and high-income countries, as classified by the OECD (Appendix 4). We excluded articles that reported only irrelevant outcomes (mortality or low grade lesions), populations outside our scope (paediatric, men, animals, or patients with cancer at baseline), or data that could not be analysed. We also excluded abstracts conference proceeding, cases studies, protocols, systematic reviews and meta-analyses. Our definition of vulnerability was based on previous research, 3 and included women of low socio-economic status (WLSES) living with HIV infection (WLWH), and female migrants, sex workers (FSW), prisoners, and women with substance use disorders (WSUD) or mental illness (WMI). Information Sources and Search strategy We searched MEDLINE, EMBASE, CENTRAL and ISI Web of Science from database inception until February 2024. For the HIV group, we considered only articles published since 2004, after highly active antiretroviral therapy had been approved. 7 , 8 We searched a combination of MeSH terms and controlled vocabulary, which we adapted to each database, for 1) cervical neoplasia and/or cancer, 2) vulnerability group, and 3) risk-related terms including relative risk, incidence, prevalence and epidemiology (see Appendix 1). We also cross-referenced with the “similar articles” function and conducted hand searches to capture missing articles. For articles not available online, we sent a reprint request to the authors. 5 Selection process and data collection process After a systematic search, we imported the articles into EndNote® (X9, Clarivate Analytics) and both automatically and manually eliminated duplicates. All citations and subsequently the full-text articles were independently screened and assessed twice by three qualified reviewers (AH, AT, MM) used our inclusion and exclusion criteria to screen and assess the citations and full-text articles independently. Each was screened and assessed twice (by different reviewers), and a fourth reviewer (MB) resolved conflicts. Data were extracted into an Excel® (Office 365, Microsoft, Redmond, WA, USA) sheet. If several publications reported the same study, we extracted the data from the main publication, which described the authors’ methods in the greatest detail and contained the most complete data on our criteria of interest. Data items We extracted the following information: author; title; year; journal; country; study design; data sources; age; inclusion and exclusion criteria; study period; duration of follow-up (if applicable); definition of cervical high-grade lesions and cancer; definition of vulnerable group, exposure, and control group (if any); sizes; point estimates and 95% confidence intervals (CI). Study risk of bias assessment Two reviewers (AH and AT) used Newcastle-Ottawa Scale (NOS) tool 9 to independently rate the quality of studies, NOS uses a grid, which is adapted to each study design, and a star system with maximum of nine stars to rate a study in three domains: selection of participants; comparability of study groups; and ascertainment of outcomes of interest. Studies with nine stars were considered to be at low risk of bias, studies with seven or eight stars were at moderate risk, and studies with six or fewer stars were at high risk. 10 Effect measures Our primary outcome was overall risk of CC (regardless of the stage) or high-grade lesions (HGL) compared to controls (general population or patients without the vulnerability). HGL was defined as Cervical Intraepithelial Neoplasia (CIN) 2+, CIN 3+, and carcinoma in situ, 11 and high-grade squamous intraepithelial lesion (HSIL), as per the Bethesda system. 12 Secondary outcome included pooled risk estimate of CC and HGL by vulnerability type. Data Synthesis and Analysis The risk estimates in our studies included incidence rate ratio (IRR), risk ratio (RR), and standardised incidence ratio (SIR) or odds ratio (OR). We considered these outcomes equivalent to pool our analyses for both CC and HGL. When point estimates and CI were reported, we calculated sampling variance of the log ratios and their confidence interval with the Wald-type test, using the function conv.wald within the Metafor package. If crude numbers were available, we created 2×2 tables and calculated log-transformed relative risk (RR) and variability for each treatment group based on sample size. To combine these data, we applied random-effects models that gave more weight to studies with more precise estimates while accounting for differences between studies. We reported results as percentages with 95% confidence intervals (CIs). 13 , 14 An inverse variance weighting method combined the summary measures, with random-effects models minimizing the impact of between-study heterogeneity. 15 We used the I 2 statistic to assess heterogeneity: 16 0%-40% (low); 30%-60% (moderate); 50%-90% (substantial); 75%-100% (considerable). Additionally, a Chi-square test of homogeneity at a 0.10 significance level helped determine whether differences between studies were incidental or indicated real variability in the effects. We also used funnel plots to assess publication bias when at least 10 studies were available. Subgroup analysis was provided for each type of vulnerability. All statistical analyses were performed with the Meta package in R version 4.3.3, (R Foundation for Statistical Computing, Vienna, Austria, 2008). RESULTS Our systematic search yielded 11539 citations; from these, we identified 196 fully published studies that met our eligibility criteria, data was extractable from 126 studies. See Appendix 5 for our Prisma diagram and Appendix 3 for a complete list of excluded studies. The quantitative analysis included studies of WLWH (n = 59), migrants (n = 22), FSW (n = 7), WSUD (n = 9), WLSES (n = 6), prisoners (n = 7), and WMI (n = 16). For the comparative meta-analysis, we found considerable significant heterogeneity for all outcomes and subgroups, except for HGL with both WSUD (p = 0.22, I² = 34%) and prisoners (p = 0.39, I² = 0%). We generated funnel plots where applicable, revealing substantial publication bias. We also found overall high risk of bias in 44% of included studies, moderate risk in 42%, and a low risk in only 14%, assessed with the NOS. Risk of bias was low to moderate in over 50% of studies for the following three groups: WLSES (50%); WSUD (67%); and WMI (56%). Common methodological weaknesses included insufficient observation periods, inadequate reporting on loss to follow-up, and no comparison group. Definitions of exposure varied within vulnerability groups. In the WSUD group, six studies focused exclusively on alcohol use disorders, one reported on drug but excluded alcohol use disorders and tobacco use, one included any type of substance abuse, and one did not define drug use disorders. Of studies on migrants, four focused on migrants from developed countries, four on migrants from developing countries, and 14 did not specify country of origin. For WLSES, definitions varied within studies. Definitions were based on family income (n = 2), education level (n = 1), living in economically deprived areas (n = 5), remote/rural areas (n = 4). Some papers reported more than one definition. A full description of included studies and their definitions of exposure is available in Supplementary Table 6. PRIMARY OUTCOME Our pooled risk estimate analysis compared CC to the control group for 126 studies that included seven vulnerable groups. Vulnerable women had significantly higher risk of CC (RR 2.78; 95%CI: 2.32–3.32; 104 studies) but there was considerable heterogeneity among studies (I²=98.3%) (Fig. 1 ). The same pattern was found with HGL (RR 2.45; 95% CI 2-3.01; 32 studies) with a significant heterogeneity (I 2 = 99.6%) (Fig. 3 ). SECONDARY OUTCOME: Risk of CC and HGL by vulnerability In the subgroup analysis, we found overall pooled risk of CC was significantly higher for WSUD (RR 2.75; 95%CI: 2.02–3.74, 8 studies), WLWH (RR 5.02; 95%CI: 4.05–6.21, 50 studies), migrants (RR 1.43 95% CI: 1.01–2.03, 20 studies), WMI (RR 1.37; 95% CI: 1.04–1.80, 14 studies), prisoners (RR 3.01; 95%CI: 1.67–5.43, 5 studies), WLSES (RR 1.12; 95% CI 1.01–1.23, 6 studies) and FSW (RR 50.51; 95%CI: 2.72-937.35, with only 1 study),.(Fig. 1 , 2) HGL risk was found to be significantly higher among all groups: WSUD (RR 2.31; 1.09–4.89, 3 studies); WLWH (RR 2.78; 2.00-3.88, 17 studies); migrants (RR 1.68; 1.36–2.06, 5 studies); WLSES (RR 1.33; 1.11–1.60, 3 studies); FSW (RR 4.04; 95% CI 2.55–6.4, 7 studies) and prisoners (RR 2.31; 1.49–3.58, 3 studies). We included only two studies for women with mental illness (RR 4.47; 95%CI: 1.13; 17.62) (Fig. 3 , 4 ). DISCUSSION Our systematic review and meta-analysis included 126 studies. Our findings show that the relative risk of CC is higher than that of HGL among most vulnerable groups with a risk of HGL and CC for seven vulnerable groups ranging between 2.45 and 2.78 compared to the general population respectively. This suggests that while HGLs are often detected through screening—potentially more accessible for some due to targeted interventions—there are barriers that prevent timely diagnosis and treatment. These gaps in follow-up care, treatment access, and healthcare system preparedness may contribute to the progression from precancerous lesions to invasive cervical cancer. Intersectional risk factors Women in the vulnerable groups we focused on faced multiple challenges, including low vaccination coverage and low participation in screening programmes. Factors like low resources, drug consumption, and HIV infection combine bidirectionally to increase HGL and cancer risk in these populations. For example, a study in Canada found high prevalence of both HIV infection (11.5%) and mental illness (57%) in female sex workers. 17 Thus, when interpreting these results, researchers should carefully consider concomitant factors to which each groups is exposed and note their definitions. HIV, substance use disorder, and prostitution: a powerful example of intersectionality Sex workers with HIV and substance use disorders accumulate common risk factors, including early initiation of sexual activity, many sexual partners, and higher exposure to persistent human papillomavirus (HPV) infection. 18 – 20 Unprotected sex 21 increases risk for co-infection with HIV, which can increase immune suppression and increase the likelihood HPV will persist and progress to HGL. 22 We believe this is why women who belong to these groups had 2- to 5-fold higher risk of HGL and CC than the general population. Our findings align with two prior meta-analysis that reported a 3- to 5-fold increase. 23 , 24 Migrants and socio-economic status: the importance of context and definitions Both migrants and socio-economic status are heterogeneous variously defined, so risk assessments must consider context and definitions. Migrants were at higher risk of HGL (RR 1.68 ;1.36–2.06), which may have been attributable to higher prevalence of HPV infections in their country of origin, low vaccination coverage, and lower adherence to screening. 25 Women who immigrated after becoming sexually active 26 and women from countries with high HPV prevalence, such as eastern Europe and western Africa, may be especially at risk. 27 However, CC among migrants was significant but more heterogeneous (RR 1.43 ; 1.01–2.03). Some studies suggest that risk decreases the longer migrants remain in their host country and could be higher for women who were older when they migrated. 28 , 29 Country of origin also plays a pivotal role in shaping risk patterns. Women who migrated from more societies where cultural and religious norms—such as prohibitions against premarital sex or multiple sexual partners—may be less exposed to HPV infection, and thus may be at lower risk of developing CC. 28 , 30 For example, a study from Australia compared infection-related cancer patterns in migrants and found similar stomach and liver cancer trends, but CC incidence varied by country of origin; rates were lowest among women from North Africa (IRR 0.42;0.23–0.77) and the Middle East (IRR 0,63; 0.49–0.81). 31 A Swedish study also found significantly lower risk for women from these regions (HR 0.31; 0.24–0.39). 32 WLSES had a modestly elevated risk of both HGL (RR 1.33; 1.11–1.6) and CC (1.12; 1.01–1.23), possibly because studies classified cancer differently. The technique used can also fail to effectively detect cancer lesions as reported by Prummel et al. for Pap tests 33 which could lead to underdiagnoses of CC. 34 , 35 A second explanation to this insignificant result may be attributable to the study setting, where the comparison group already faces significant socioeconomic challenges as found in Luce’s et al. study carried in the French West Indies. 36 . A third explanation is that these women constitute a highly heterogeneous group in the studies we included. The definition of LSES can vary from individual, e.g., women with low household income or low educational attainment, to collective, e.g. women who live in areas far from health services or who are generally disadvantaged, and these differences may dilute or mask the true effect. For example, a nationwide study in Denmark found higher risk for women with the lowest income (IRR 1.17 ; 1.07–1.28) and lower risk for those who lived in rural areas (IRR 0.87; 0.77–0.99). 37 Prison: a difficult context for screening and follow-up Prisoners face risks 2-fold higher for HGL and 3-fold higher for CC. Contributing factors include poverty, migration, prostitution, alcohol and drug abuse, increased risk of HIV infection, 43 and lack of organized screening and follow-up in prison settings. 38 , 39 Notably, loss to follow-up upon release exacerbates this challenge. 40 , 41 A systematic review of a similar population reported that all 21 of the included studies described higher prevalence of dysplasia in prison population than in control groups. 42 Another meta-analyses showed a 5-fold increase in cervical lesions and a 100-fold increase in CC prevalence. 43 Mental illness WMI showed a moderate but significant increase in CC risk (RR 1.37;1.04–1.8), although findings across studies were inconsistent. The meta-analysis by Wotten et al., 44 reported a similar result (OR = 1.35 [1.2–1.5]). Variability may result from differing definitions and severity levels of mental illness; increased risk could result from underreporting of confounders such as reduced sexual activity 45 or medication side effects. 46 Conversely, increased risk may result from higher prevalence of HPV infection, lower adherence to primary and secondary prevention, 47 48, 49 or to smoking or alcohol use. 50 – 52 Strengths and limitations To our knowledge, this is the first analysis including a wide definition of vulnerable groups. The data we present have limitations. The first is that, although we calculated a pooled global estimate of the RR, there was considerable statistical heterogeneity across the studies, as was reported in a previous paper that focused on women living with HIV. 24 In registry linkage studies, data on lifestyle and behavioural variables was rarely collected, so key confounders such as smoking and sexual behaviour may have been omitted. 18 , 19 Definitions of cervical lesions according to cytological and histological classifications and also methods for measuring them varied across studies, which may have impacted the robustness of our findings. In the future, researchers should focus on interventions that ensure efficient follow-up and treatment for women with abnormal screening results. Some studies have explored the use of reminders or phone calls to improve follow-up rates, 53 , 54 but further validation through complementary investigations is needed. A study conducted in England highlighted the positive impact of patient navigators (PNs) in reconnecting underserved women with healthcare services and follow-up care. The findings indicated a reduced time to colposcopy and a decrease in the severity of cervical abnormalities over time. 55 Wells and colleagues, 56 defined three main profiles for PNs shaped by health system structures and the populations they reach: 1) Clinically trained PNs who can interpret and communicate complex healthcare processes to patients, 2) Community-based PNs, often members of marginalized communities, who facilitate healthcare access through trust-building and supportive relationships. While they may not hold clinical degrees, they often have formal or informal training in community health or health promotion, and 3) A hybrid model combining both clinically trained and community-based PNs to address individual, community, and structural barriers to healthcare access In the USA, the Centers for Disease control and prevention (CDC) attributed six activities to PNs 1) Identifying barriers to cancer screening, diagnostic services, and treatment initiation. 2) Providing patient education and support. 3) Addressing and resolving patient barriers to care. 4) Tracking and following up with patients through at least two contacts to ensure completion of screening, diagnostic testing, and treatment initiation. 5) Collecting data on patient navigation outcomes, such as adherence to screening, diagnosis, and treatment. And 6) Gathering patient-reported outcomes related to cancer screening, diagnosis, and treatment. 57 Further studies are needed to determine the most effective PN activities and profiles for minimizing loss to follow-up while ensuring alignment with specific health system structures and target populations. Additionally, evidence on the cost-effectiveness of patient navigation services for cervical cancer screening and follow-up remains limited. 58 The recent introduction of an assessment tool by the International Agency for Research on Cancer (IARC) provides a valuable framework for evaluating healthcare systems’ capacity to effectively prevent and manage cervical cancer in vulnerable populations. 59 Conclusion Vulnerable groups are at higher risk of developing both HGL lesions and CC, highlighting the importance of tailoring interventions to meet their needs. Where multiple disadvantages intersect, the social determinants of health must be addressed by, for example, introducing a Social Vulnerability Index (SVI) into screening programmes to aid policymakers and researchers in identifying and serving vulnerable populations more effectively. 60 Declarations Role of the funding source The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Contributors MB is the originator of the idea. AH, AT, MM and MB designed the study. AH, AT and MM extracted, analysed and interpreted the data. AH and AT did the risk bias assessment and drafted the initial report. MM and MB made critical revisions of the manuscript bringing important content. All authors approved the final version of the report. Declaration of interests We declare no competing interest Funding: this systematic review and meta-analysis is funded by the CBIG-SCREEN project (The CBIG-SCREEN project has received funding from the EU Horizon 2020 research and innovation program under Grant Agreement No 964049). Acknowledgments We acknowledge the EU Horizon 2020 research and innovation program for providing sufficient funding to perform this work (Grant Agreement No 964049). We also acknowledge the contribution of Kali Tal for her valuable assistance with medical writing. Data availability A detailed data extraction table is available in the supplementary material. This SR and MA did not include individual data but only summary estimates reported by authors. References Singh D, Vignat J, Lorenzoni V et al (2023) Global estimates of incidence and mortality of cervical cancer in 2020: a baseline analysis of the WHO Global Cervical Cancer Elimination Initiative. 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J Low Genit Tract Dis 25(2):81–85 Kouyoumdjian FG, Pivnick L, McIsaac KE, Wilton AS, Lofters A, Hwang SW (2017) Cancer prevalence, incidence and mortality in people who experience incarceration in Ontario, Canada: A population-based retrospective cohort study. PLoS ONE 12(2):e0171131 Brousseau EC, Ahn S, Matteson KA (2019) Cervical Cancer Screening Access, Outcomes, and Prevalence of Dysplasia in Correctional Facilities: A Systematic Review. J Women's Health 28(12):1661–1669 Escobar N, Plugge E (2020) Prevalence of human papillomavirus infection, cervical intraepithelial neoplasia and cervical cancer in imprisoned women worldwide: a systematic review and meta-analysis. J Epidemiol Community Health 74(1):95–102 Wootten JC, Wiener JC, Blanchette PS, Anderson KK (2022) Cancer incidence and stage at diagnosis among people with psychotic disorders: Systematic review and meta-analysis. Cancer Epidemiol 80:102233 Tardieu S, Micallef J, Bonierbale M, Frauger E, Lançon C, Blin O (2006) Comportements sexuels chez le patient schizophrène: impact des antipsychotiques. L'Encéphale 32(5):697–704 Mortensen PB (1987) Neuroleptic treatment and other factors modifying cancer risk in schizophrenic patients. Acta psychiatrica Scandinavica 75(6):585–590 Hu K, Barker MM, Herweijer E et al (2024) The role of mental illness and neurodevelopmental conditions in human papillomavirus vaccination uptake within the Swedish school-based vaccination programme: a population-based cohort study. Lancet Public Health 9(9):e674–e83 Power R, David M, Strnadova I et al (2024) Cervical screening participation and access facilitators and barriers for people with intellectual disability: a systematic review and meta-analysis. Front Psychiatry 15:1379497 Solmi M, Firth J, Miola A et al (2020) Disparities in cancer screening in people with mental illness across the world versus the general population: prevalence and comparative meta-analysis including 4 717 839 people. Lancet Psychiatry 7(1):52–63 Herweijer E, Hu K, Wang J et al (2024) Incidence of oncogenic HPV infection in women with and without mental illness: A population-based cohort study in Sweden. PLoS Med 21(3):e1004372 Broberg G, Wang J, Östberg A-L et al (2018) Socio-economic and demographic determinants affecting participation in the Swedish cervical screening program: A population-based case-control study. PLoS ONE 13(1):e0190171 Licciardone JC, Wilkins JR, Brownson RC, Chang JC (1989) Cigarette Smoking and Alcohol Consumption in the Aetiology of Uterine Cervical Cancer. Int J Epidemiol 18(3):533–537 Fogh Jørgensen S, Kellen E, Haelens A, Herck KV, Njor SH (2024) How follow-up rates in cervical cancer screening depend on organizational factors: A comparison of two population-based organized screening programmes. J Med Screen 31(3):191–200 Atlas SJ, Tosteson ANA, Wright A et al (2023) A Multilevel Primary Care Intervention to Improve Follow-Up of Overdue Abnormal Cancer Screening Test Results: A Cluster Randomized Clinical Trial. JAMA 330(14):1348–1358 Percac-Lima S, Benner CS, Lui R et al (2013) The impact of a culturally tailored patient navigator program on cervical cancer prevention in Latina women. J Womens Health (Larchmt) 22(5):426–431 Wells KJ, Valverde P, Ustjanauskas AE, Calhoun EA, Risendal BC (2018) What are patient navigators doing, for whom, and where? A national survey evaluating the types of services provided by patient navigators. Patient Educ Couns 101(2):285–294 Barrington WE, DeGroff A, Melillo S et al (2019) Patient navigator reported patient barriers and delivered activities in two large federally-funded cancer screening programs. Prev Med ; 129s: 105858 Chattopadhyay SK, Pillai A, Reynolds J et al (2024) Breast and Cervical Cancer Screenings: A Systematic Economic Review of Patient Navigation Services. Am J Prev Med 67(4):618–626 Mensah K, Mosquera I, Tisler A et al (2024) Development and pilot implementation of a novel protocol to assess capacity and readiness of health systems to adopt HPV detection-based cervical cancer screening in Europe. Health Res Policy Syst 22(1):102 Tran T, Rousseau MA, Farris DP, Bauer C, Nelson KC, Doan HQ (2023) The social vulnerability index as a risk stratification tool for health disparity research in cancer patients: a scoping review. Cancer Causes Control 34(5):407–420 Additional Declarations There is NO Competing Interest. Supplementary Files SupplementarymaterialMASR.docx Risk of cervical cancer and high-grade lesions in vulnerable women in high and upper middle-income countries: systematic review and meta-analysis. Cite Share Download PDF Status: Published Journal Publication published 02 Mar, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6180822","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":433839808,"identity":"5696b38b-1333-4d06-99c3-72eeadafadf7","order_by":0,"name":"Marc Bardou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIie3SMUsDMRTA8RcCveV58x3FfobAQaAg7VexFM6l4HBjB4VCpvsCgh9CN8fAQbNEi1vhHHrLTQ7XQTgXNY1SUHPF0SH/4W0/8hIC4PP9w5g0g7RmSCCb3dwXXLrJ0JLcEsq+EZROAWNLhCW96E+Eq/uqIfnoPFQ5nyM8DVipHquXuxPAvttwfZZEpJ0Or7TmJUKdsIdZlhzrFDA8dROZ9sxdKGPrGS+P3orJjca0H4sCxuhejK1qQ8SFJRnCnrwDdpH17hRRWEI/SbCMt0IeIDWNJrlisV5m8bW5S6yRJkRMsZOsUtJs2zkL1eK2eTYvFuqgql7FaNBFbD9eBpnZEA6BXwUb+4N8Pp/P99UHHh9gyquFkeMAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0028-1837","institution":"CHU de Dijon","correspondingAuthor":true,"prefix":"","firstName":"Marc","middleName":"","lastName":"Bardou","suffix":""},{"id":433839809,"identity":"16f32aa8-c91b-4242-a803-6cca0ec8a733","order_by":1,"name":"Amir Hassine","email":"","orcid":"https://orcid.org/0000-0002-0833-7746","institution":"CHU de Dijon","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Hassine","suffix":""},{"id":433839811,"identity":"e3a018da-5630-43c7-b9b1-8871b1c73b68","order_by":2,"name":"Anna Tisler","email":"","orcid":"","institution":"University of Tartu","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Tisler","suffix":""},{"id":433839812,"identity":"82c0d98b-44c0-403c-9e79-2b925686bd8f","order_by":3,"name":"Myriam Martel","email":"","orcid":"","institution":"Research Institute of the McGill University Health Center, Montreal,Quebec,Canada","correspondingAuthor":false,"prefix":"","firstName":"Myriam","middleName":"","lastName":"Martel","suffix":""}],"badges":[],"createdAt":"2025-03-07 20:55:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6180822/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6180822/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-026-70050-w","type":"published","date":"2026-03-02T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79242178,"identity":"995ac7a2-f691-4990-848b-64bd7e6492c1","added_by":"auto","created_at":"2025-03-26 06:08:54","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1713993,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of developing cervical cancer among vulnerable women type of vulnerability\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6180822/v1/8d091bdc31ae101353b4cfb3.jpeg"},{"id":79242179,"identity":"b06b58e3-88e9-4e30-af9f-0ee9020ec005","added_by":"auto","created_at":"2025-03-26 06:08:54","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":533558,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSummary of pooled estimates of CC\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6180822/v1/33fc4dedc6e3da5492ef7842.jpeg"},{"id":79242180,"identity":"6e21eb90-a002-4584-ae08-e001fcb22953","added_by":"auto","created_at":"2025-03-26 06:08:54","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1001500,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled risk for HGL\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6180822/v1/a6af4975ee962fbdc6977cca.jpeg"},{"id":79243325,"identity":"cbd0e28b-7523-45a1-96a8-e1de5626ac4b","added_by":"auto","created_at":"2025-03-26 06:24:54","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":525948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSummary of pooled estimates of HGL\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6180822/v1/e74d0f2767a25c765e51e2e2.jpeg"},{"id":106583811,"identity":"9394857f-7a17-4675-b864-36c65af0aec0","added_by":"auto","created_at":"2026-04-10 07:12:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4580694,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6180822/v1/c45a4a2e-7da7-425b-a75d-899786b4b357.pdf"},{"id":79242175,"identity":"70bc0c8f-a37d-48de-926c-26dfe1c8439e","added_by":"auto","created_at":"2025-03-26 06:08:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":367051,"visible":true,"origin":"","legend":"Risk of cervical cancer and high-grade lesions in vulnerable women in high and upper middle-income countries: systematic review and meta-analysis.","description":"","filename":"SupplementarymaterialMASR.docx","url":"https://assets-eu.researchsquare.com/files/rs-6180822/v1/06f46170614e235b7d009c7b.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Risk of cervical cancer and high-grade lesions in vulnerable women in high and upper middle-income countries: systematic review and meta-analysis.","fulltext":[{"header":"RESEARCH IN CONTEXT","content":"\u003cp\u003e\u003cb\u003eEvidence before this study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNumerous cohort studies have shown that socially disadvantaged women face a higher risk of developing cervical cancer (CC) and high-grade lesions (HGL). Meta-analyses conducted on specific groups of vulnerable women have reported a significant increase in risk for both outcomes\u0026mdash;for instance, women living with HIV (WLWH) had a CC relative risk (RR) of 6.07 (95% CI: 4.4\u0026ndash;8.37). However, no studies have been conducted to assess this risk using a broader definition of vulnerability, and there is a lack of research on these populations in middle- and high-income countries\u003c/p\u003e\u003cp\u003e\u003cb\u003eAdded value of this study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe calculated the pooled estimate of CC risk based on 106 studies, encompassing over 48\u0026nbsp;million vulnerable women. Similarly, the analysis of HGL was derived from 32 individual studies, including over 6\u0026nbsp;million vulnerable women. Additionally, we provided pooled estimates for each specific vulnerability group.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImplication of all the available evidence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eVulnerable women have more than twice the risk of developing both CC and HGL compared to the general population (RR 2.8, 95% CI 2.34\u0026ndash;3.35; RR 2.45, 95% CI 2.0\u0026ndash;3.01, respectively). Our study highlights the increased risk of progression from HGL to CC, which may indicate deficiencies in follow-up care. Countries such as England and the United States have begun implementing patient navigator programs aimed at reconnecting these populations with healthcare services. While initial results are promising, further research is needed to assess the effectiveness and long-term economic sustainability of these interventions within healthcare systems.\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eThe World Health Organization (WHO) launched a global initiative aimed to eliminate cervical cancer (CC) by 2030. The strategy, aimed at eradicated the more than 600,000 new cases reported worldwide each year,\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e rests on three pillars: 90% of young girls vaccinated against human papillomavirus (HPV) by age 15; 70% of adult women screened by the age 35 to 45; and 90% of early-stage cancers treated appropriately.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhile risk of CC and mortality are higher in low- and middle-income countries, CC persists even in developed countries, demonstrating a marked socioeconomic gradient. Vulnerable groups\u0026mdash;including women living with HIV (WLWH), female sex workers (FSW), migrants, prisoners, and women with substance use disorder (WSUD) or mental illness (WMI)\u0026mdash;have less access to vaccination, screening, and treatment. Though these disparities are well known, policy responses in many developed countries have been insufficient to effectively reduce them.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe last recommendations of the US Preventive Services Task Force (USPSTF) on CC screening, highlighted the need for risk-based, tailored approaches to reduce the burden of the disease.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e To support these approaches, we must quantify risk so public health decision makers can adapt policies, and re-allocate resources to reduce CC risk and improve public health outcomes.\u003c/p\u003e \u003cp\u003eWe thus conducted a systematic review and meta-analysis to assess these disparities. We reported risk estimates for vulnerability groups overall and then for subgroups of women at high risk in high- and upper-middle-income countries.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis systematic review and meta-analysis follows the Cochrane Handbook and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines,\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e based on the full search protocol published in Prospero (ID: CRD42024535331).\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEligibility Criteria\u003c/h2\u003e \u003cp\u003eWe included any English-language epidemiological studies (cohort, case-control, cross-sectional, and registry linkage studies) of cervical high-grade lesions (HGL) or cancer among vulnerable women with or without a comparison group, conducted in upper-middle and high-income countries, as classified by the OECD (Appendix 4). We excluded articles that reported only irrelevant outcomes (mortality or low grade lesions), populations outside our scope (paediatric, men, animals, or patients with cancer at baseline), or data that could not be analysed. We also excluded abstracts conference proceeding, cases studies, protocols, systematic reviews and meta-analyses.\u003c/p\u003e \u003cp\u003eOur definition of vulnerability was based on previous research,\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and included women of low socio-economic status (WLSES) living with HIV infection (WLWH), and female migrants, sex workers (FSW), prisoners, and women with substance use disorders (WSUD) or mental illness (WMI).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInformation Sources and Search strategy\u003c/h3\u003e\n\u003cp\u003eWe searched MEDLINE, EMBASE, CENTRAL and ISI Web of Science from database inception until February 2024. For the HIV group, we considered only articles published since 2004, after highly active antiretroviral therapy had been approved.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e We searched a combination of MeSH terms and controlled vocabulary, which we adapted to each database, for 1) cervical neoplasia and/or cancer, 2) vulnerability group, and 3) risk-related terms including relative risk, incidence, prevalence and epidemiology (see Appendix 1).\u003c/p\u003e \u003cp\u003eWe also cross-referenced with the \u0026ldquo;similar articles\u0026rdquo; function and conducted hand searches to capture missing articles. For articles not available online, we sent a reprint request to the authors.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eSelection process and data collection process\u003c/h3\u003e\n\u003cp\u003eAfter a systematic search, we imported the articles into EndNote\u0026reg; (X9, Clarivate Analytics) and both automatically and manually eliminated duplicates. All citations and subsequently the full-text articles were independently screened and assessed twice by three qualified reviewers (AH, AT, MM) used our inclusion and exclusion criteria to screen and assess the citations and full-text articles independently. Each was screened and assessed twice (by different reviewers), and a fourth reviewer (MB) resolved conflicts.\u003c/p\u003e \u003cp\u003eData were extracted into an Excel\u0026reg; (Office 365, Microsoft, Redmond, WA, USA) sheet. If several publications reported the same study, we extracted the data from the main publication, which described the authors\u0026rsquo; methods in the greatest detail and contained the most complete data on our criteria of interest.\u003c/p\u003e\n\u003ch3\u003eData items\u003c/h3\u003e\n\u003cp\u003eWe extracted the following information: author; title; year; journal; country; study design; data sources; age; inclusion and exclusion criteria; study period; duration of follow-up (if applicable); definition of cervical high-grade lesions and cancer; definition of vulnerable group, exposure, and control group (if any); sizes; point estimates and 95% confidence intervals (CI).\u003c/p\u003e\n\u003ch3\u003eStudy risk of bias assessment\u003c/h3\u003e\n\u003cp\u003eTwo reviewers (AH and AT) used Newcastle-Ottawa Scale (NOS) tool\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e to independently rate the quality of studies, NOS uses a grid, which is adapted to each study design, and a star system with maximum of nine stars to rate a study in three domains: selection of participants; comparability of study groups; and ascertainment of outcomes of interest. Studies with nine stars were considered to be at low risk of bias, studies with seven or eight stars were at moderate risk, and studies with six or fewer stars were at high risk.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEffect measures\u003c/h2\u003e \u003cp\u003eOur primary outcome was overall risk of CC (regardless of the stage) or high-grade lesions (HGL) compared to controls (general population or patients without the vulnerability). HGL was defined as Cervical Intraepithelial Neoplasia (CIN) 2+, CIN 3+, and carcinoma in situ,\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e and high-grade squamous intraepithelial lesion (HSIL), as per the Bethesda system.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSecondary outcome included pooled risk estimate of CC and HGL by vulnerability type.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Synthesis and Analysis\u003c/h3\u003e\n\u003cp\u003eThe risk estimates in our studies included incidence rate ratio (IRR), risk ratio (RR), and standardised incidence ratio (SIR) or odds ratio (OR). We considered these outcomes equivalent to pool our analyses for both CC and HGL. When point estimates and CI were reported, we calculated sampling variance of the log ratios and their confidence interval with the Wald-type test, using the function conv.wald within the Metafor package. If crude numbers were available, we created 2\u0026times;2 tables and calculated log-transformed relative risk (RR) and variability for each treatment group based on sample size.\u003c/p\u003e \u003cp\u003eTo combine these data, we applied random-effects models that gave more weight to studies with more precise estimates while accounting for differences between studies. We reported results as percentages with 95% confidence intervals (CIs).\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e An inverse variance weighting method combined the summary measures, with random-effects models minimizing the impact of between-study heterogeneity.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e We used the I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e statistic to assess heterogeneity:\u003csup\u003e16\u003c/sup\u003e 0%-40% (low); 30%-60% (moderate); 50%-90% (substantial); 75%-100% (considerable). Additionally, a Chi-square test of homogeneity at a 0.10 significance level helped determine whether differences between studies were incidental or indicated real variability in the effects.\u003c/p\u003e \u003cp\u003eWe also used funnel plots to assess publication bias when at least 10 studies were available.\u003c/p\u003e \u003cp\u003eSubgroup analysis was provided for each type of vulnerability. All statistical analyses were performed with the Meta package in R version 4.3.3, (R Foundation for Statistical Computing, Vienna, Austria, 2008).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOur systematic search yielded 11539 citations; from these, we identified 196 fully published studies that met our eligibility criteria, data was extractable from 126 studies. See Appendix 5 for our Prisma diagram and Appendix 3 for a complete list of excluded studies.\u003c/p\u003e \u003cp\u003eThe quantitative analysis included studies of WLWH (n\u0026thinsp;=\u0026thinsp;59), migrants (n\u0026thinsp;=\u0026thinsp;22), FSW (n\u0026thinsp;=\u0026thinsp;7), WSUD (n\u0026thinsp;=\u0026thinsp;9), WLSES (n\u0026thinsp;=\u0026thinsp;6), prisoners (n\u0026thinsp;=\u0026thinsp;7), and WMI (n\u0026thinsp;=\u0026thinsp;16). For the comparative meta-analysis, we found considerable significant heterogeneity for all outcomes and subgroups, except for HGL with both WSUD (p\u0026thinsp;=\u0026thinsp;0.22, I\u0026sup2; = 34%) and prisoners (p\u0026thinsp;=\u0026thinsp;0.39, I\u0026sup2; = 0%).\u003c/p\u003e \u003cp\u003eWe generated funnel plots where applicable, revealing substantial publication bias. We also found overall high risk of bias in 44% of included studies, moderate risk in 42%, and a low risk in only 14%, assessed with the NOS. Risk of bias was low to moderate in over 50% of studies for the following three groups: WLSES (50%); WSUD (67%); and WMI (56%). Common methodological weaknesses included insufficient observation periods, inadequate reporting on loss to follow-up, and no comparison group.\u003c/p\u003e \u003cp\u003eDefinitions of exposure varied within vulnerability groups. In the WSUD group, six studies focused exclusively on alcohol use disorders, one reported on drug but excluded alcohol use disorders and tobacco use, one included any type of substance abuse, and one did not define drug use disorders.\u003c/p\u003e \u003cp\u003eOf studies on migrants, four focused on migrants from developed countries, four on migrants from developing countries, and 14 did not specify country of origin.\u003c/p\u003e \u003cp\u003eFor WLSES, definitions varied within studies. Definitions were based on family income (n\u0026thinsp;=\u0026thinsp;2), education level (n\u0026thinsp;=\u0026thinsp;1), living in economically deprived areas (n\u0026thinsp;=\u0026thinsp;5), remote/rural areas (n\u0026thinsp;=\u0026thinsp;4). Some papers reported more than one definition. A full description of included studies and their definitions of exposure is available in Supplementary Table\u0026nbsp;6.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePRIMARY OUTCOME\u003c/h2\u003e \u003cp\u003eOur pooled risk estimate analysis compared CC to the control group for 126 studies that included seven vulnerable groups. Vulnerable women had significantly higher risk of CC (RR 2.78; 95%CI: 2.32\u0026ndash;3.32; 104 studies) but there was considerable heterogeneity among studies (I\u0026sup2;=98.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The same pattern was found with HGL (RR 2.45; 95% CI 2-3.01; 32 studies) with a significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSECONDARY OUTCOME: Risk of CC and HGL by vulnerability\u003c/h2\u003e \u003cp\u003eIn the subgroup analysis, we found overall pooled risk of CC was significantly higher for WSUD (RR 2.75; 95%CI: 2.02\u0026ndash;3.74, 8 studies), WLWH (RR 5.02; 95%CI: 4.05\u0026ndash;6.21, 50 studies), migrants (RR 1.43 95% CI: 1.01\u0026ndash;2.03, 20 studies), WMI (RR 1.37; 95% CI: 1.04\u0026ndash;1.80, 14 studies), prisoners (RR 3.01; 95%CI: 1.67\u0026ndash;5.43, 5 studies), WLSES (RR 1.12; 95% CI 1.01\u0026ndash;1.23, 6 studies) and FSW (RR 50.51; 95%CI: 2.72-937.35, with only 1 study),.(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 2)\u003c/p\u003e \u003cp\u003eHGL risk was found to be significantly higher among all groups: WSUD (RR 2.31; 1.09\u0026ndash;4.89, 3 studies); WLWH (RR 2.78; 2.00-3.88, 17 studies); migrants (RR 1.68; 1.36\u0026ndash;2.06, 5 studies); WLSES (RR 1.33; 1.11\u0026ndash;1.60, 3 studies); FSW (RR 4.04; 95% CI 2.55\u0026ndash;6.4, 7 studies) and prisoners (RR 2.31; 1.49\u0026ndash;3.58, 3 studies). We included only two studies for women with mental illness (RR 4.47; 95%CI: 1.13; 17.62) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur systematic review and meta-analysis included 126 studies. Our findings show that the relative risk of CC is higher than that of HGL among most vulnerable groups with a risk of HGL and CC for seven vulnerable groups ranging between 2.45 and 2.78 compared to the general population respectively. This suggests that while HGLs are often detected through screening\u0026mdash;potentially more accessible for some due to targeted interventions\u0026mdash;there are barriers that prevent timely diagnosis and treatment. These gaps in follow-up care, treatment access, and healthcare system preparedness may contribute to the progression from precancerous lesions to invasive cervical cancer.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eIntersectional risk factors\u003c/h2\u003e \u003cp\u003eWomen in the vulnerable groups we focused on faced multiple challenges, including low vaccination coverage and low participation in screening programmes. Factors like low resources, drug consumption, and HIV infection combine bidirectionally to increase HGL and cancer risk in these populations. For example, a study in Canada found high prevalence of both HIV infection (11.5%) and mental illness (57%) in female sex workers.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Thus, when interpreting these results, researchers should carefully consider concomitant factors to which each groups is exposed and note their definitions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eHIV, substance use disorder, and prostitution: a powerful example of intersectionality\u003c/h2\u003e \u003cp\u003eSex workers with HIV and substance use disorders accumulate common risk factors, including early initiation of sexual activity, many sexual partners, and higher exposure to persistent human papillomavirus (HPV) infection.\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Unprotected sex\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e increases risk for co-infection with HIV, which can increase immune suppression and increase the likelihood HPV will persist and progress to HGL.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e We believe this is why women who belong to these groups had 2- to 5-fold higher risk of HGL and CC than the general population. Our findings align with two prior meta-analysis that reported a 3- to 5-fold increase.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMigrants and socio-economic status: the importance of context and definitions\u003c/h2\u003e \u003cp\u003eBoth migrants and socio-economic status are heterogeneous variously defined, so risk assessments must consider context and definitions.\u003c/p\u003e \u003cp\u003eMigrants were at higher risk of HGL (RR 1.68 ;1.36\u0026ndash;2.06), which may have been attributable to higher prevalence of HPV infections in their country of origin, low vaccination coverage, and lower adherence to screening.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Women who immigrated after becoming sexually active\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and women from countries with high HPV prevalence, such as eastern Europe and western Africa, may be especially at risk.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e However, CC among migrants was significant but more heterogeneous (RR 1.43 ; 1.01\u0026ndash;2.03). Some studies suggest that risk decreases the longer migrants remain in their host country and could be higher for women who were older when they migrated.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Country of origin also plays a pivotal role in shaping risk patterns. Women who migrated from more societies where cultural and religious norms\u0026mdash;such as prohibitions against premarital sex or multiple sexual partners\u0026mdash;may be less exposed to HPV infection, and thus may be at lower risk of developing CC.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e For example, a study from Australia compared infection-related cancer patterns in migrants and found similar stomach and liver cancer trends, but CC incidence varied by country of origin; rates were lowest among women from North Africa (IRR 0.42;0.23\u0026ndash;0.77) and the Middle East (IRR 0,63; 0.49\u0026ndash;0.81).\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e A Swedish study also found significantly lower risk for women from these regions (HR 0.31; 0.24\u0026ndash;0.39).\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWLSES had a modestly elevated risk of both HGL (RR 1.33; 1.11\u0026ndash;1.6) and CC (1.12; 1.01\u0026ndash;1.23), possibly because studies classified cancer differently. The technique used can also fail to effectively detect cancer lesions as reported by Prummel et al. for Pap tests \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e which could lead to underdiagnoses of CC.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eA second explanation to this insignificant result may be attributable to the study setting, where the comparison group already faces significant socioeconomic challenges as found in Luce\u0026rsquo;s et al. study carried in the French West Indies.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. A third explanation is that these women constitute a highly heterogeneous group in the studies we included. The definition of LSES can vary from individual, e.g., women with low household income or low educational attainment, to collective, e.g. women who live in areas far from health services or who are generally disadvantaged, and these differences may dilute or mask the true effect. For example, a nationwide study in Denmark found higher risk for women with the lowest income (IRR 1.17 ; 1.07\u0026ndash;1.28) and lower risk for those who lived in rural areas (IRR 0.87; 0.77\u0026ndash;0.99).\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePrison: a difficult context for screening and follow-up\u003c/h2\u003e \u003cp\u003ePrisoners face risks 2-fold higher for HGL and 3-fold higher for CC. Contributing factors include poverty, migration, prostitution, alcohol and drug abuse, increased risk of HIV infection,\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e and lack of organized screening and follow-up in prison settings.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Notably, loss to follow-up upon release exacerbates this challenge. \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e A systematic review of a similar population reported that all 21 of the included studies described higher prevalence of dysplasia in prison population than in control groups.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Another meta-analyses showed a 5-fold increase in cervical lesions and a 100-fold increase in CC prevalence.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eMental illness\u003c/h2\u003e \u003cp\u003eWMI showed a moderate but significant increase in CC risk (RR 1.37;1.04\u0026ndash;1.8), although findings across studies were inconsistent. The meta-analysis by Wotten et al.,\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e reported a similar result (OR\u0026thinsp;=\u0026thinsp;1.35 [1.2\u0026ndash;1.5]). Variability may result from differing definitions and severity levels of mental illness; increased risk could result from underreporting of confounders such as reduced sexual activity\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e or medication side effects.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e Conversely, increased risk may result from higher prevalence of HPV infection, lower adherence to primary and secondary prevention,\u003csup\u003e47 48,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e or to smoking or alcohol use.\u003csup\u003e\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eTo our knowledge, this is the first analysis including a wide definition of vulnerable groups.\u003c/p\u003e \u003cp\u003eThe data we present have limitations. The first is that, although we calculated a pooled global estimate of the RR, there was considerable statistical heterogeneity across the studies, as was reported in a previous paper that focused on women living with HIV.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e In registry linkage studies, data on lifestyle and behavioural variables was rarely collected, so key confounders such as smoking and sexual behaviour may have been omitted.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDefinitions of cervical lesions according to cytological and histological classifications and also methods for measuring them varied across studies, which may have impacted the robustness of our findings.\u003c/p\u003e \u003cp\u003eIn the future, researchers should focus on interventions that ensure efficient follow-up and treatment for women with abnormal screening results. Some studies have explored the use of reminders or phone calls to improve follow-up rates, \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e but further validation through complementary investigations is needed.\u003c/p\u003e \u003cp\u003eA study conducted in England highlighted the positive impact of patient navigators (PNs) in reconnecting underserved women with healthcare services and follow-up care. The findings indicated a reduced time to colposcopy and a decrease in the severity of cervical abnormalities over time.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e Wells and colleagues,\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e defined three main profiles for PNs shaped by health system structures and the populations they reach: 1) Clinically trained PNs who can interpret and communicate complex healthcare processes to patients, 2) Community-based PNs, often members of marginalized communities, who facilitate healthcare access through trust-building and supportive relationships. While they may not hold clinical degrees, they often have formal or informal training in community health or health promotion, and 3) A hybrid model combining both clinically trained and community-based PNs to address individual, community, and structural barriers to healthcare access\u003c/p\u003e \u003cp\u003eIn the USA, the Centers for Disease control and prevention (CDC) attributed six activities to PNs 1) Identifying barriers to cancer screening, diagnostic services, and treatment initiation. 2) Providing patient education and support. 3) Addressing and resolving patient barriers to care. 4) Tracking and following up with patients through at least two contacts to ensure completion of screening, diagnostic testing, and treatment initiation. 5) Collecting data on patient navigation outcomes, such as adherence to screening, diagnosis, and treatment. And 6) Gathering patient-reported outcomes related to cancer screening, diagnosis, and treatment.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurther studies are needed to determine the most effective PN activities and profiles for minimizing loss to follow-up while ensuring alignment with specific health system structures and target populations. Additionally, evidence on the cost-effectiveness of patient navigation services for cervical cancer screening and follow-up remains limited.\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e The recent introduction of an assessment tool by the International Agency for Research on Cancer (IARC) provides a valuable framework for evaluating healthcare systems\u0026rsquo; capacity to effectively prevent and manage cervical cancer in vulnerable populations.\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eVulnerable groups are at higher risk of developing both HGL lesions and CC, highlighting the importance of tailoring interventions to meet their needs. Where multiple disadvantages intersect, the social determinants of health must be addressed by, for example, introducing a Social Vulnerability Index (SVI) into screening programmes to aid policymakers and researchers in identifying and serving vulnerable populations more effectively.\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e "},{"header":"Declarations","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eRole of the funding source\u003c/h2\u003e \u003cp\u003eThe funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003eContributors\u003c/h2\u003e \u003cp\u003eMB is the originator of the idea. AH, AT, MM and MB designed the study. AH, AT and MM extracted, analysed and interpreted the data. AH and AT did the risk bias assessment and drafted the initial report. MM and MB made critical revisions of the manuscript bringing important content. All authors approved the final version of the report.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eDeclaration of interests\u003c/h2\u003e \u003cp\u003eWe declare no competing interest\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003ethis systematic review and meta-analysis is funded by the CBIG-SCREEN project (The CBIG-SCREEN project has received funding from the EU Horizon 2020 research and innovation program under Grant Agreement No 964049).\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe acknowledge the EU Horizon 2020 research and innovation program for providing sufficient funding to perform this work (Grant Agreement No 964049). We also acknowledge the contribution of Kali Tal for her valuable assistance with medical writing.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eA detailed data extraction table is available in the supplementary material. This SR and MA did not include individual data but only summary estimates reported by authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSingh D, Vignat J, Lorenzoni V et al (2023) Global estimates of incidence and mortality of cervical cancer in 2020: a baseline analysis of the WHO Global Cervical Cancer Elimination Initiative. 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Virology 493:247\u0026ndash;254\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDenslow SA, Rositch AF, Firnhaber C, Ting J, Smith JS (2014) Incidence and progression of cervical lesions in women with HIV: a systematic global review. Int J STD AIDS 25(3):163\u0026ndash;177\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStelzle D, Tanaka LF, Lee KK et al (2021) Estimates of the global burden of cervical cancer associated with HIV. Lancet Glob Health 9(2):e161\u0026ndash;e9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlam Z, Shafiee Hanjani L, Dean J, Janda M (2021) Cervical Cancer Screening Among Immigrant Women Residing in Australia: A Systematic Review. Asia Pac J Public Health 33(8):816\u0026ndash;827\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarques P, Nunes M, Antunes ML, Heleno B, Dias S (2020) Factors associated with cervical cancer screening participation among migrant women in Europe: a scoping review. 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Acta Obstet Gynecol Scand 102(1):114\u0026ndash;121\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrummel MV, Young SW, Candido E, Nishri D, Elit L, Marrett LD (2014) Cervical cancer incidence in ontario women: differing sociodemographic gradients by morphologic type (adenocarcinoma versus squamous cell). Int J Gynecol Cancer 24(7):1341\u0026ndash;1346\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchell H, Medley G, Gordon I, Giles G (1995) Cervical cytology reported as negative and risk of adenocarcinoma of the cervix: no strong evidence of benefit. Br J Cancer 71(4):894\u0026ndash;897\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSasieni P, Castanon A, Cuzick J (2009) Screening and adenocarcinoma of the cervix. Int J Cancer 125(3):525\u0026ndash;529\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuce D, Michel S, Dugas J et al (2017) Disparities in cancer incidence by area-level socioeconomic status in the French West Indies. Cancer Causes Control 28(11):1305\u0026ndash;1312\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJensen KE, Hannibal CG, Nielsen A et al (2008) Social inequality and incidence of and survival from cancer of the female genital organs in a population-based study in Denmark, 1994\u0026ndash;2003. Eur J Cancer 44(14):2003\u0026ndash;2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKouyoumdjian FG, McConnon A, Herrington ERS, Fung K, Lofters A, Hwang SW (2018) Cervical Cancer Screening Access for Women Who Experience Imprisonment in Ontario, Canada. JAMA Netw Open 1(8):e185637\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrousseau EC, Ahn S, Matteson KA (2019) Cervical Cancer Screening Access, Outcomes, and Prevalence of Dysplasia in Correctional Facilities: A Systematic Review. J Womens Health (Larchmt) 28(12):1661\u0026ndash;1669\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJodry D, Blemur D, Nguyen ML et al (2021) Criminal Justice Involvement and Abnormal Cervical Cancer Screening Results Among Women in an Urban Safety Net Hospital. J Low Genit Tract Dis 25(2):81\u0026ndash;85\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKouyoumdjian FG, Pivnick L, McIsaac KE, Wilton AS, Lofters A, Hwang SW (2017) Cancer prevalence, incidence and mortality in people who experience incarceration in Ontario, Canada: A population-based retrospective cohort study. PLoS ONE 12(2):e0171131\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrousseau EC, Ahn S, Matteson KA (2019) Cervical Cancer Screening Access, Outcomes, and Prevalence of Dysplasia in Correctional Facilities: A Systematic Review. J Women's Health 28(12):1661\u0026ndash;1669\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEscobar N, Plugge E (2020) Prevalence of human papillomavirus infection, cervical intraepithelial neoplasia and cervical cancer in imprisoned women worldwide: a systematic review and meta-analysis. J Epidemiol Community Health 74(1):95\u0026ndash;102\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWootten JC, Wiener JC, Blanchette PS, Anderson KK (2022) Cancer incidence and stage at diagnosis among people with psychotic disorders: Systematic review and meta-analysis. Cancer Epidemiol 80:102233\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTardieu S, Micallef J, Bonierbale M, Frauger E, Lan\u0026ccedil;on C, Blin O (2006) Comportements sexuels chez le patient schizophr\u0026egrave;ne: impact des antipsychotiques. L'Enc\u0026eacute;phale 32(5):697\u0026ndash;704\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMortensen PB (1987) Neuroleptic treatment and other factors modifying cancer risk in schizophrenic patients. Acta psychiatrica Scandinavica 75(6):585\u0026ndash;590\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu K, Barker MM, Herweijer E et al (2024) The role of mental illness and neurodevelopmental conditions in human papillomavirus vaccination uptake within the Swedish school-based vaccination programme: a population-based cohort study. Lancet Public Health 9(9):e674\u0026ndash;e83\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePower R, David M, Strnadova I et al (2024) Cervical screening participation and access facilitators and barriers for people with intellectual disability: a systematic review and meta-analysis. Front Psychiatry 15:1379497\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSolmi M, Firth J, Miola A et al (2020) Disparities in cancer screening in people with mental illness across the world versus the general population: prevalence and comparative meta-analysis including 4 717 839 people. Lancet Psychiatry 7(1):52\u0026ndash;63\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHerweijer E, Hu K, Wang J et al (2024) Incidence of oncogenic HPV infection in women with and without mental illness: A population-based cohort study in Sweden. PLoS Med 21(3):e1004372\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBroberg G, Wang J, \u0026Ouml;stberg A-L et al (2018) Socio-economic and demographic determinants affecting participation in the Swedish cervical screening program: A population-based case-control study. PLoS ONE 13(1):e0190171\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLicciardone JC, Wilkins JR, Brownson RC, Chang JC (1989) Cigarette Smoking and Alcohol Consumption in the Aetiology of Uterine Cervical Cancer. Int J Epidemiol 18(3):533\u0026ndash;537\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFogh J\u0026oslash;rgensen S, Kellen E, Haelens A, Herck KV, Njor SH (2024) How follow-up rates in cervical cancer screening depend on organizational factors: A comparison of two population-based organized screening programmes. 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Cancer Causes Control 34(5):407\u0026ndash;420\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6180822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6180822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Cervical cancer (CC) is largely preventable but still causes around 300,000 deaths annually, particularly among vulnerable women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This systematic review and meta-analysis included studies from four databases (MEDLINE, EMBASE, CENTRAL, ISI Web of Science) up to February 2024 (from 2004 for HIV). We examined seven vulnerable groups in middle- and high-income countries: women of low socioeconomic status (WLSES), prisoners, sex workers, women with substance use disorders (WSUD), mental illness (WMI), migrants, and women living with HIV (WLWH). Observational studies on CC and high-grade lesion (HGL) risk, incidence, or prevalence were included. Independent reviewers assessed all articles. The main outcome was CC or HGL risk, measured assessed by incidence rate ratio (IRR), risk ratio (RR), standardized incidence ratio (SIR), or odds ratio (OR). PROSPERO registration: CRD42024535331.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings:\u003c/strong\u003e We included 126 studies. Vulnerable women had a significantly higher risk of CC (RR 2.78, 95%CI 2.32-3.32) and HGL (RR 2.51, 95%CI 2.02-3.11), with WSUD, prisoners, and WLWH facing a 2- to 5-fold increased risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterpretation:\u003c/strong\u003e Marginalised women face a higher CC and HGL risk, highlighting the need for targeted policies to improve screening and treatment access.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e this systematic review and meta-analysis is funded by the CBIG-SCREEN project (The CBIG-SCREEN project has received funding from the EU Horizon 2020 research and innovation program under Grant Agreement No 964049).\u003c/p\u003e","manuscriptTitle":"Risk of cervical cancer and high-grade lesions in vulnerable women in high and upper middle-income countries: systematic review and meta-analysis.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-26 06:08:49","doi":"10.21203/rs.3.rs-6180822/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"493c8346-a388-410e-91d8-961ebed07e7f","owner":[],"postedDate":"March 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46196106,"name":"Health sciences/Oncology/Cancer/Cancer epidemiology"},{"id":46196107,"name":"Health sciences/Oncology/Cancer/Cancer prevention"}],"tags":[],"updatedAt":"2026-04-10T07:11:48+00:00","versionOfRecord":{"articleIdentity":"rs-6180822","link":"https://doi.org/10.1038/s41467-026-70050-w","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2026-03-02 05:00:00","publishedOnDateReadable":"March 2nd, 2026"},"versionCreatedAt":"2025-03-26 06:08:49","video":"","vorDoi":"10.1038/s41467-026-70050-w","vorDoiUrl":"https://doi.org/10.1038/s41467-026-70050-w","workflowStages":[]},"version":"v1","identity":"rs-6180822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6180822","identity":"rs-6180822","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}