Скрининг на рак цветов у лиц с множественным склерозом: исследование по смешанным методам.

Introduction

Colorectal cancer (CRC) is among the most common cancer types and the second leading cause of cancer-related mortality in the general population. In people with multiple sclerosis (pwMS), it remains an important cause of morbidity and mortality. 1 , 2 Research on CRC in pwMS reported inconsistent results: although incidence studies show either a reduction 1 , 3 or no difference in CRC risk, 4 – 6 mortality studies report increased CRC-related mortality among pwMS. 7 , 8 CRC survival strongly depends on early detection and timely treatment, and lower access to colorectal cancer screening (CCS) in pwMS may lead to a higher proportion of delayed-diagnosis or symptom-detected cancer, explaining lower incidence but higher mortality. 9 A meta-analysis on cancer inequalities showed higher mortality rates and consistently lower screening uptake for breast, CRC, and cervical cancer in individuals with mental and physical disability, 10 including multiple sclerosis (MS), which is the leading cause of disability in young adults. However, a Canadian case–control study observed no difference between pwMS and matched controls in CRC diagnosis route (screening vs symptomatic) and time to diagnosis. However, the small number of pwMS with CRC ( n = 54) may have limited the ability to detect modest differences or draw generalizable conclusions. 11 Our group recently showed lower breast cancer screening (BCS) rates in pwMS compared to the French general population, especially in older individuals. 12 Perceived barriers included feelings of overmedicalization and accessibility issues (transportation, procedure, scheduling conflicts) that may also affect CCS uptake. Therefore, population-based studies are needed to quantify CCS access in pwMS and to identify the factors associated with lower uptake and the underlying mechanisms.

The objective of this study was to assess and compare CCS rates between pwMS and the general population and to identify barriers and facilitators of CCS uptake using a mixed-methods approach.

Methods

Study design

This study used a convergent mixed-methods design combining quantitative and qualitative analyses to examine the research question: “What are the barriers and facilitators to CCS in MS?.” A parallel analysis approach was used, with both components collected and analyzed separately, and then integrated at the interpretation stage. 13 Reporting followed the Good Reporting of A Mixed Methods Study (GRAMMS) checklist ( Supplemental Table S1 ). 14

Quantitative analysis

Population and design

A 2022–2024 population-based retrospective matched cohort study was performed using data from the Système National des Données de Santé (SNDS), the French national administrative healthcare database (~99% of the population). 15 It collects exhaustive data on healthcare consumption in France, including hospitalizations (in- and out-patient), ambulatory care, and screening procedures. The aim was to evaluate and compare CCS coverage rates in pwMS and in a matched control group.

Individuals with prevalent MS on 31 December 2021 were identified in the SNDS database with a previously used algorithm 1 , 12 , 16 , 17 based on the long-term disease (LTD) status, MS-related hospitalizations, and MS-specific drug prescriptions. 18 Selection criteria were being eligible for CCS (50–74 years) and without a history of chronic inflammatory bowel disease or cancer (any type) in the past 3 years.

The follow-up start, defined as the index date, began on 1 January 2022 or 50th birthday. Each patient was exactly matched to three controls from the general population on birth year, health insurance status, residence area, and index date. All participants were followed until the first censoring event: 31 December 2024, 75th birthday, first cancer occurrence (not restricted to CRC), or death.

Main outcome: CCS coverage

The CCS coverage rate was defined as follows:

Number of days during which an individual is considered covered by a CCS procedure Number of days during which an individual is eligible for CCS * 100

Two medical procedures were considered: fecal immunochemical test (FIT), which is the recommended screening tool to be performed every 2 years, and colonoscopy, which is done every 5–10 years and is usually recommended for surveillance in people with personal or familial history of CRC or high-risk profiles ( Supplemental Table S2 ). To accurately assess CCS coverage, colonoscopies from 2012 to 2024 and FIT tests from 2020 to 2024 were retrieved.

Factors associated with CCS

Variables potentially associated with CCS included socio-demographic, MS-related and overall health, healthcare utilization, and MS management indicators.

Socio-demographic factors at inclusion were age, sex, department of residence, FDep index (a city-level social deprivation index; quasi-log-linear relationship with mortality), 19 and CMU/C2S status (social deprivation index at the individual level based on income). MS-related and overall health variables were computed in the 12 months preceding inclusion and comprised the Bannay-Charlson comorbidity index (CCI; from hospitalization, medical procedures, LTD-status and drug reimbursement, and excluding cancer and hemiplegia; Supplemental Table S3 ), 20 hemiplegia identified through hospitalization data (derived from the CCI but entered separately), MS duration (time from SNDS identification to inclusion), and MS-related overnight hospitalizations. Healthcare utilization indicators included general practitioner (GP), nursing, physiotherapy, and pharmacy visits and ambulatory (i.e. 1-day) hospitalizations. Disease-modifying therapy (DMT) reimbursements in the previous year were retrieved as a proxy of MS management. All variables were computed at the index date.

Statistical analysis

CCS coverage rates and their 95% confidence intervals (CI) were calculated and compared between pwMS and controls, overall and stratified by age, sex, comorbidity status, and FDep quintile. Age- and sex-standardized CCS coverage rates were also stratified by MS duration. The proportion of individuals with no CCS coverage (0%), partial coverage (1%–79%), and adequate coverage (⩾80%) was compared according to age and MS duration.

Factors that could act as barriers and facilitators and were associated with CCS were evaluated only in pwMS with complete data. The main outcome of interest was having a CCS coverage ⩾80%. 21 Associations were assessed using a multivariable mixed-effects logistic model with a random effect on the region of residence. A sensitivity analysis was conducted using different CCS coverage rate thresholds (50% and 0%).

Qualitative analysis

Semi-structured interviews were conducted with pwMS eligible to the organized CCS. Recruitment was conducted through a call for testimonies on social media and MS association websites. To ensure a wide range of screening behaviors, the call only mentioned preventive services in the context of MS and not CCS. Among 31 eligible volunteers, 20 were selected to maximize the profile diversity (age, sex, MS duration, screening behaviors, employment status, region of residence). After obtaining verbal informed consent, each interview was recorded using Teams or a microphone and transcribed with the ShareDocs platform (one participant refused to be recorded, manual notes were used). 22 After anonymization and transcription, the recordings were deleted.

An interview grid was developed to address, particularly, the following topics: healthcare pathways, general knowledge about CRC, its screening program and procedure, general knowledge of CCS prevention campaigns, perceived barriers and facilitators to CCS, and the perceived role of healthcare professionals in CCS ( Supplemental Table S4 ). Barriers and facilitators were identified using an empirically inductive thematic method in which patterns or themes are identified and analyzed in qualitative data without imposing preconceived theories or categories. 23 Key topics were identified first individually, then reviewed and combined (R.B. and C.P.). Interviews were conducted until thematic saturation was reached.

The quantitative and qualitative data were analyzed separately and integrated (C.P. and R.B.) through the identification and reporting of convergencies, divergencies, complementarities (different but not contradictory), and expansions (overlapping findings with space for additional interpretation). 24

Data access and ethics approval

Data access approvals were obtained according to the current French legislation (R.1461-11-R.1461-17, CNIL-2016-316) and the study was declared to the EHESP SNDS registry, equivalent to an Institutional Review Board approval.

Results

Quantitative results

Study population

The cohort study included 63,509 pwMS matched to 190,527 controls ( Figure 1 ). Their median age at the index date was 58 years (IQR, 53–65) and 72.0% were women. The median MS duration was 14.5 years (IQR, 8.6–21.5) and was ⩾10 years in 70.1% of participants ( Table 1 ). In the year before the index date, 46.2% of pwMS received at least one DMT (high efficacy: 17.1%). Overall, 10.4% of participants had ⩾1 comorbidity.

CCS coverage rates

Mean CCS coverage rate was 41.2% (95% CI = 40.9–41.6) in pwMS and 42.4% (42.2–42.6) in controls, corresponding to a 3% relative decrease in pwMS ( p < 0.0001). A substantial proportion had no CCS coverage during the study period (46.2% vs 44.5% in pwMS and controls, respectively; p < 0.0001). Among individuals with any coverage (⩾1 day), mean coverage was similar between groups (76.7% vs 76.4%, p = 0.2), indicating that the overall difference was driven by individuals without coverage.

Analysis of CCS coverage by age ( Figure 2 ) showed that in the 50–59 years groups, the proportion of individuals with adequate coverage (⩾80%) was slightly higher in pwMS than controls (50–54 years: +1.5%, p < 0.001; 55–59 years: +1.7%, p < 0.001). Conversely, in the 60–74 years groups, coverage was lower in pwMS. The gap widened as age increased: from a 1.6-point decrease in the 60–64 years group ( p = 0.001) to a 6.2-point decrease in the 70–74 years group ( p < 0.0001). Results were similar in both sexes ( Figure S1 ). CCS coverage rates by MS duration showed minimal difference (<1 point) until 19 years of disease ( Figure 3 ). The strongest difference was observed in the proportion of those with no coverage in the ⩾20 years MS duration group (+3.3% for pwMS; p < 0.0001).

Factors associated with CCS

Crude and adjusted mixed-effect logistic regression models identified factors associated with CCS coverage rate ⩾80% in pwMS ( Table 2 ). Coverage was positively associated with healthcare utilization, including DMT use (OR = 1.12 [1.08–1.16]), at-home nursing visits (1.18 [1.13–1.23]), pharmacy visits (1.81 [1.55–2.11]), and frequent GP visits (3–4 visits/year: 1.21 [1.14–1.27], ⩾5 visits/year: 1.47 [1.40–1.54], ref. 1–2).

MS duration, comorbidities, physiotherapy, and MS-unrelated hospitalizations (⩾1 overnight stays) showed no association.

Conversely, social deprivation and disease severity indicators were negatively associated, including CMU status (0.68 [0.63–0.73]), living in the most deprived areas (fifth vs first quintile, 0.81 [0.76–0.86]), hemiplegia (0.63 [0.58–0.69]), and overnight MS-related hospitalizations (0.76 [0.68–0.85]). Male sex was negatively associated (0.90 [0.86–0.93]). Findings were similar when using CCS thresholds of ⩾50% or >0%, except that comorbidity became negatively associated at both thresholds ( Supplemental Table S5 ).

Qualitative results

Interviews were carried out with 20 pwMS ( n = 14 women; mean age = 59.6 years, range = 5–72, MS duration range = 1–50, Supplemental Table S6 ). Ten required the use of a walking aid or wheelchair, and six had limited mobility. Seventeen participants had undergone CCS at least once (FIT or colonoscopy) and 11 reported adherence to the national screening recommendation. Awareness of organized screening campaigns was limited: only 10 were aware of CCS awareness campaigns, and one person knew specifically about the “Colorectal Cancer Awareness Month” campaign known as “Blue March.” The perceived barriers and facilitators are summarized in Table 3 .

Barriers

Limited knowledge of CRC and organized screening

Knowledge of CRC and screening remained vague and limited. Many felt they had insufficient knowledge on CRC “Nothing. I know it exists, that’s all” and also on prevention campaigns “I don’t remember it at all. I didn’t pay attention.” This was associated with a general lack of discussion about the topic in public and private circles.

Limited discussion with healthcare providers and family

CCS was rarely initiated by clinicians. Participants often needed to bring up the topic: “Even my GP [. . .] if I don’t go in with the intention of leaving with a screening kit, he’s not going to . . .” Other healthcare professionals (e.g. neurologists or gynecologists) were not identified as resources, namely due to “pretty time-restricted” consultations. Similarly, none of the participants reported having discussed it with their pharmacist. Participants also reported limited discussion with friends and family outside immediate relatives: “It’s a subject that we don’t talk about much. [. . .] My brother does it.” This contributed to low perceived concern about colorectal cancer.

CCS perceived as an uncomfortable and taboo subject

Screening was considered an uncomfortable and “taboo” subject. FIT practical aspects discouraged participation: “The idea of what you have to do to take the test doesn’t appeal to me.” Conversely, BCS was described as “normal,” highlighting social acceptability differences.

MS-related motor and digestive issues

Participants described difficulties with hand function and motor skills that complicate the FIT procedure. “He will not be able to do it himself. Because his motor skills in his hands [. . .] are no longer what they used to be” [carer of MS participant]. Digestive issues, which concerned half of participants and included “constipated” and stools that are “too liquid,” influenced the perceived test feasibility.

Feeling of over-medicalization

The burden of managing MS contributed to preventive care fatigue, including screening. FIT, even when performed at home, was sometimes viewed as an additional medical obligation as they were “fed up” with medical appointments. Some women reported prioritizing BCS over CCS, indicating a perceived hierarchy of preventive procedures.

Facilitators

Participants mentioned wanting to avoid having to manage two chronic illnesses at the same time: “I already have MS, the last thing I need is to catch another disease.” This was part of a general feeling of confidence in the healthcare system. Receipt of a CCS invitation letter from the National Health Insurance also prompted participation: “I received them in my mailbox!.” Some participants interpreted invitations as civic responsibilities of “a responsible citizen,” while others emphasized general preventive health: “I want to take preventive action.” Overall, facilitators were linked to trust in the healthcare system and prevention awareness, rather than CRC-specific concerns. Anticipating worsening mobility limitations, participants noted that the option of receiving home-assistance from a qualified care professional would be valuable.

Integration

The quantitative and qualitative components showed multiple convergences: trust and use of the healthcare system and physical disability emerged, respectively, as facilitator and barrier in both analyses ( Table 4 ). However, some divergences emerged concerning physical disability. In the quantitative analysis, only hemiplegia was statistically associated with CCS and not MS duration (proxy for accumulated disability). Conversely, only motor and digestive issues were mentioned in the interviews. Moreover, the interviewed pwMS reported feelings of overmedicalization (barrier), but higher healthcare use was statistically associated with greater CCS uptake (facilitator). Finally, restricted health awareness (qualitative) and lower socioeconomic status (quantitative) emerged as complementary barriers because low socioeconomic status was associated with lower health literacy and access to care.

Discussion

This study found suboptimal CCS uptake in both pwMS and matched general population controls (41.2% and 42.4% in the 2022–2024 period, respectively). Nearly half of each group had no CCS coverage during 2022–2024 (46.2% and 44.5%, respectively). Overall, pwMS had a 3% relative decrease in CCS coverage compared with their matched controls. This difference was primarily driven by older age groups: the gap progressively increased after the age of 60, and reached its peak (−6.2 points) in the 70–74 years group. Conversely, CCS coverage did not vary meaningfully by MS duration. These results confirm the low participation in CCS in the general population in France, like in other high-income countries. 25 , 26

Quantitative and qualitative analyses of facilitators and barriers to CCS in pwMS identified trust in and use of the healthcare system as the most convergent factor. Physical disability showed partial convergence (walking disability not mentioned in interviews), suggesting that specific functional limitations, rather than overall disease duration, may influence screening participation and may not be accurately measured in quantitative analyses. Limited CCS awareness and lower socioeconomic status were additional barriers. Although the measured constructs differed, altogether these findings suggest that structural and informational barriers may contribute to screening disparities. Feelings of overmedicalization were reported as a barrier in interviews, but higher healthcare use, including DMT-use, was associated with greater CCS coverage. This may reflect greater healthcare engagement and contact, resulting in more preventive care opportunities. Alternatively, it may reflect the cumulative MS care burden: with increasing age, ongoing disease management may reduce the prioritization of preventive screening despite frequent healthcare contacts.

Similarly, a previous study on BCS in MS by our group showed lower screening uptake and an increasing age-related disparity compared with controls. 12 BCS uptake remained higher than CCS in pwMS and controls, despite the identification of additional barriers (e.g. long disease duration, fatigue, procedure accessibility, and scheduling). BCS was seen as a routine procedure and healthcare providers were identified as playing a major role in its uptake. Conversely, CCS was perceived as taboo and rarely discussed. Health awareness and knowledge were identified as important facilitators for BCS, but as barriers for CCS. Unlike for BCS, the majority of the identified barriers and facilitators for CCS were related more to the screening procedure than to MS and had been previously identified in general population-based systematic reviews. 27 – 29 This aligns with our population-based estimates showing low CCS participation in both pwMS and controls.

A key limitation of this study is the lack of precise quantitative disability data. We relied on proxy variables, such as hemiplegia (only partially identified through hospitalizations) and MS duration, which have limited precision. Research using more precise measures of functional impairment (including spasticity, motor, or sensitive disorders) and digestive symptoms is needed to better assess their association with CCS. For colonoscopies, we could not fully distinguish screening from diagnostic procedures, although we minimized this issue by excluding individuals with a history of inflammatory bowel disease or cancer. Nonetheless, some non-differential residual misclassification may persist. These estimates reflect opportunities for colorectal cancer detection and are likely to overestimate true screening adherence while preserving the internal validity of comparative estimates. Strengths include the use of a population-based database that fully captures healthcare procedures from public and private institutions, thus minimizing selection, reporting, and social desirability biases. The qualitative component added context by capturing the participants’ experiences and perceptions, and the mixed-methods design allowed triangulation, enhancing the validity and providing deeper insights into the mechanisms influencing cancer screening and preventive care in MS. The qualitative sample may underrepresent more socially deprived or isolated pwMS, which may have limited the identification of barriers experienced by underserved populations.

To conclude, CCS uptake remains suboptimal in both pwMS and the general population, particularly in older pwMS. Unlike BCS, most of the identified barriers and facilitators to CCS were not MS-specific. They appear to reflect broader preventive care challenges rather than CCS-specific obstacles. These findings suggest that for CCS, general population-level interventions addressing accessibility and engagement could be prioritized and would also benefit pwMS. As pwMS are aging, new challenges are emerging, including mental and physical disability, complex disease management and increasing comorbidities, and more research on disparities in cancer and general preventive care is needed.

Supplemental Material

sj-docx-1-msj-10.1177_13524585261465197 – Supplemental material for Colorectal cancer screening in individuals with multiple sclerosis: A mixed-methods study

Supplemental material, sj-docx-1-msj-10.1177_13524585261465197 for Colorectal cancer screening in individuals with multiple sclerosis: A mixed-methods study by Chloé Pierret, Romane Bouvier, Sandrine Kerbrat and Emmanuelle Leray in Multiple Sclerosis Journal

This work was carried out as part of the INSPIRE research chair, co-sponsored by the EDMUS Foundation, Lyon, France, and EHESP, Rennes, France (fondation-edmus.org/fr/la-chaire-inspire/presentation) and directed by Prof Emmanuelle Leray. This chair aims to understand the determinants of inequalities in multiple sclerosis and their impact on the lives of people affected by the disease.

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: C.P., R.B., and S.K. have nothing to disclose. E.L. received consulting fees from Alexion, Merck, Novartis, Roche, and Biogen, received payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing or educational events from Sanofi Genzyme, and received support for attending meetings and/or travel from Sanofi Genzyme, all of the above unrelated to this work.

Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by the ARSEP & EDMUS Foundation, the “Institut des Neurosciences Cliniques de Rennes,” and the INSPIRE Chair (EHESP, EDMUS). Funding bodies played no role in data access, management, analysis, or interpretation. They were not involved in writing or reviewing the manuscript, nor were they part of the decision-making process regarding its submission for publication.

ORCID iDs: Chloé Pierret https://orcid.org/0009-0006-2702-3343

Emmanuelle Leray https://orcid.org/0000-0001-8424-4499

Data Availability Statement: According to data protection requirements and French regulations, the authors cannot publicly release SNDS data. Access to SNDS data may be requested through the appropriate French regulatory procedures and authorization processes.

Supplemental Material: Supplemental material for this article is available online.

References

1 Pierret C Mulliez A Le Bihan-Benjamin C , et al . Cancer risk among patients with multiple sclerosis: A 10-year nationwide retrospective cohort study . Neurology 2024 ; 103 ( 9 ): e209885. 10.1212/WNL.0000000000209885 PMC11464044 39383482

2 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 ( 3 ): 209 – 249 . 33538338 10.3322/caac.21660

3 Kingwell E Bajdik C Phillips N , et al . Cancer risk in multiple sclerosis: Findings from British Columbia, Canada . Brain J Neurol 2012 ; 135 ( Pt10 ): 2973 – 2979 . 10.1093/brain/aws148 22730559

4 Bahmanyar S Montgomery SM Hillert J , et al . Cancer risk among patients with multiple sclerosis and their parents . Neurology 2009 ; 72 ( 13 ): 1170 – 1177 . 19332695 10.1212/01.wnl.0000345366.10455.62

5 Marrie RA Maxwell C Mahar A , et al . Cancer incidence and mortality rates in multiple sclerosis: A matched cohort study . Neurology 2021 ; 96 ( 4 ): e501–e512. 10.1212/WNL.0000000000011219 33239364

6 Noorgaard M Veres K Sellebjerg FT , et al . Incidence of malignancy in multiple sclerosis: A cohort study in the Danish multiple sclerosis registry . Mult Scler J–Exp Transl Clin 2021 ; 7 ( 4 ): 20552173211053939. 10.1177/20552173211053939 PMC8613897 34840804

7 Grytten N Myhr KM Celius EG , et al . Cancer related mortality in multiple sclerosis. A population based cohort study . Mult Scler Relat Disord 2023 ; 69 : 104417 . 36423459 10.1016/j.msard.2022.104417

8 Marrie RA Maxwell C Mahar A , et al . Colorectal cancer survival in multiple sclerosis . Neurology 2021 ; 97 ( 14 ): e1447–1456. 10.1212/WNL.0000000000012634 PMC8520388 34526374

9 Bouvier AM Jooste V Lillini R , et al . Differences in survival and recurrence of colorectal cancer by stage across population-based European registries . Int J Cancer 2024 ; 155 ( 5 ): 807 – 815 . 38577898 10.1002/ijc.34944

10 Yang Y Afshar N Butchart J , et al . Cancer inequalities experienced by people with disability: A systematic review . Disabil Health J 2025 ; 18 ( 4 ): 101851 . 40399188 10.1016/j.dhjo.2025.101851

11 Groome PA Webber C Maxwell CJ , et al . Multiple sclerosis and the cancer diagnosis: Diagnostic route, cancer stage, and the diagnostic interval in breast and colorectal cancer . Neurology 2022 ; 98 ( 18 ): e1798–e1809. 10.1212/WNL.0000000000200163 35501160

12 Pierret C Philippe L Leray E. Breast cancer screening in women with multiple sclerosis: A mixed-methods study . Eur J Neurol 2025 ; 32 ( 5 ): e70183. 10.1111/ene.70183 PMC12082810 40377370

13 Pluye P Bengoechea E Granikov V , et al . A world of possibilities in mixed methods: Review of the combinations of strategies used to integrate qualitative and quantitative phases, results and data . Int J Mult Res Approach 2018 ; 10 : 41 – 56 .

14 O’Cathain A Murphy E Nicholl J. The quality of mixed methods studies in health services research . J Health Serv Res Policy 2008 ; 13 ( 2 ): 92 – 98 . 10.1258/jhsrp.2007.007074 18416914

15 Tuppin P Rudant J Constantinou P , et al . Value of a national administrative database to guide public decisions: From the système national d’information interrégimes de l’Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France . Rev Epidemiol Sante Publique 2017 ; 65 : S149–S167. 10.1016/j.respe.2017.05.004 28756037

16 Guinebretiere O Pierret C Calonge Q , et al . Updated multiple sclerosis incidence in France, 2011-2021 . Neurology 2025 ; 104 : e213586. 10.1212/WNL.0000000000213586 40228185

17 Pierret C Androdias G Lebrun-Frenay C , et al . Impact of cancer on multiple sclerosis–related healthcare and disease-modifying drug use: A multinational cohort study . Mult Scler J 2026 ; 32 : 525 – 538 . 10.1177/13524585261437966 PMC13100324 41936038

18 Pierret C Mainguy M Leray E. Prevalence of multiple sclerosis in France in 2021: Data from the French health insurance database . Rev Neurol (Paris) 2024 ; 180 : 429 – 437 . 38423846 10.1016/j.neurol.2023.12.007

19 Rey G Jougla E Fouillet A , et al . Ecological association between a deprivation index and mortality in France over the period 1997 – 2001: Variations with spatial scale, degree of urbanicity, age, gender and cause of death . BMC Public Health 2009 ; 9 ( 1 ): 33 . 19161613 10.1186/1471-2458-9-33 PMC2637240

20 Bannay A Chaignot C Blotière PO , et al . The best use of the Charlson comorbidity index with electronic health care database to predict mortality . Med Care 2016 ; 54 ( 2 ): 188 . 26683778 10.1097/MLR.0000000000000471

21 Chubak J Hubbard R. Defining and measuring adherence to cancer screening . J Med Screen 2016 ; 23 ( 4 ): 179 – 185 . 26946420 10.1177/0969141316630766 PMC5011024

22 Huma—Num . Documentation de l’IR* Huma—Num [Page Web] . ShareDocs—présentation—Documentation de l’infrastructure Huma-Num , 2025 , https://documentation.huma-num.fr/sharedocs-stockage/ ( accessed 6 November 2025 ).

23 Green J Thorogood N. Qualitative Methods for Health Research . New York : Sage ; 2009 , p. 392 .

24 Fetters MD Curry LA Creswell JW. Achieving integration in mixed methods designs—Principles and practices . Health Serv Res 2013 ; 48 ( 6 pt. 2 ): 2134 – 2156 . 24279835 10.1111/1475-6773.12117 PMC4097839

25 Baile-Maxía S Pimienta M Sánchez-Ardila C , et al . Systematic review of participation, positivity, and yield over time in fecal immunochemical test-based organized colorectal cancer screening programs . Clin Gastroenterol Hepatol . Epub ahead of print 20 February 2026. DOI: 10.1016/j.cgh.2026.02.009 . 41724209

26 Quintin C Chatignoux E Plaine J , et al . Coverage rate of opportunistic and organised breast cancer screening in France: Department-level estimation . Cancer Epidemiol 2022 ; 81 : 102270 . 36215917 10.1016/j.canep.2022.102270

27 Dressler J Johnsen AT Madsen LJ , et al . Factors affecting patient adherence to publicly funded colorectal cancer screening programmes: A systematic review . Public Health 2021 ; 190 : 67 – 74 . 33360029 10.1016/j.puhe.2020.10.025

28 Zubair NF Mohammed Nawi A Hassan MR , et al . Multilevel factors influencing colorectal cancer screening adherence: A systematic literature review . PLoS ONE 2026 ; 21 ( 2 ): e0342184. 10.1371/journal.pone.0342184 PMC12867220 41632768

29 Wools A Dapper EA de Leeuw JRJ . Colorectal cancer screening participation: A systematic review . Eur J Public Health 2016 ; 26 ( 1 ): 158 – 168 . 26370437 10.1093/eurpub/ckv148