Sensitivity of the cancer screening items in Japan’s Comprehensive Survey of Living Conditions: a medical record-linked cross-sectional validation study

Sensitivity of the cancer screening items in Japan’s Comprehensive Survey of Living Conditions: a medical record-linked cross-sectional validation study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sensitivity of the cancer screening items in Japan’s Comprehensive Survey of Living Conditions: a medical record-linked cross-sectional validation study Toshifumi Namba, Noriaki Takahashi, Masaaki Otomo, Katsuaki Kato, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8914059/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background In Japan, national estimates of cancer screening utilization rely primarily on self-reported data from the Comprehensive Survey of Living Conditions (CSLC). However, the validity of the CSLC cancer screening items introduced in 2013 has not been verified against objective screening records. The study aimed to validate the cancer screening items used in Japan’s CSLC by comparing self-reported screening histories with medical records. Methods We conducted a cross-sectional validation study by mailing a questionnaire replicating the CSLC cancer screening items to randomly selected individuals with known screening histories at a large screening center. Returned questionnaires were linked to electronic medical records. The primary outcome was the sensitivity of the questionnaire items for gastric and breast cancer screening within a 2-year window (fiscal years [FY] 2022–2023). Exploratory analyses assessed colorectal cancer screening within a 1-year window and cervical cancer screening within a 2-year window. To evaluate the effects of survey timing (late FY2024), we conducted a sensitivity analysis that expanded the medical record window to include screenings performed in early FY2024. Results The questionnaire was mailed to 4,000 individuals, of whom 1,151 were included in the analysis. The sensitivity of the questionnaire was 96.1% for gastric cancer screening (318/331) and 95.8% for breast cancer screening (276/288). Similarly, the sensitivity was high for colorectal (93.6%) and cervical cancer screening (96.3%). The sensitivity estimates changed minimally when early FY2024 examinations were included. Other crude agreement measures, such as specificity, were not interpretable as classification accuracy parameters because screenings conducted outside the center were unobservable. Conclusions The CSLC cancer screening items demonstrated high sensitivity, indicating that individuals who were recently screened generally reported their participation accurately. However, given Japan’s likely moderate true uptake, even modest shortfalls in specificity could inflate the national survey–based estimates. Improving questionnaire clarity and developing integrated screening registries can enhance the accuracy of population-level monitoring. Cancer screening self-report validation study sensitivity survey measurement Japan comprehensive survey of living conditions Figures Figure 1 Background Accurate monitoring of population-level cancer screening uptake is essential for assessing progress toward national cancer control targets and guiding public health resource allocation [ 1 – 3 ]. Many countries maintain program-based registries that comprehensively capture screening encounters and enable routine estimation of screening rates [ 4 – 7 ]. In Japan, cancer screening services are provided by a wide range of entities, including municipalities, occupational health programs, and individual medical institutions, with no nationwide system integrating records across providers [ 8 ]. As of 2025, the government recommends age-based population screening for five major cancers: colorectal (annual fecal occult blood test from ≥ 40 years); lung (annual chest radiography from ≥ 40 years, with sputum cytology for individuals at increased risk from ≥ 50 years); gastric (biennial barium radiography or endoscopy from ≥ 50 years); breast (biennial mammography for women ≥ 40 years); and cervical (biennial cytology for women ≥ 20 years or human papillomavirus testing every 5 years for women ≥ 30 years) [ 8 ]. In the absence of an integrated screening registry, national statistics rely primarily on the triennial Comprehensive Survey of Living Conditions (CSLC), which reports an overall screening uptake of approximately 50%, with substantial variations across cancer sites [ 9 ]. Although these estimates have gradually increased over the past few decades, they remain below the 60% target set by the Fourth Basic Plan to Promote Cancer Control Programs [ 10 ]. As with any survey based on self-reported screening, CSLC estimates are vulnerable to measurement errors, including recall bias [ 11 ], misunderstanding of the reference period (telescoping) [ 12 ], confusion between screening and diagnostic procedures [ 13 , 14 ], and biases from low response rates [ 15 ]. Notably, the 2013 CSLC survey round introduced major revisions to the questionnaire, coinciding with an apparent increase of more than 10% in the reported uptake for several cancer types compared with the previous round [ 9 ]. Although minor modifications were introduced in 2013, the overall structure of the questionnaire remained largely unchanged. International evidence shows that survey-based screening rates often differ from registry-based rates [ 16 – 19 ], and meta-analyses indicate that the accuracy of self-reported cancer screening varies by cancer type and test [ 11 , 20 – 23 ]. In Japan, a recent validation study comparing self-reported histories with municipal administrative records offered preliminary insights [ 24 ]; however, the questionnaire used differed in structure from the CSLC instrument. To date, no study has directly evaluated the cancer screening items introduced in the 2013 CSLC. Before implementation, Shibuya et al. assessed the comprehensibility and validity of a prototype of the current CSLC items [ 25 ]. Although the prototype demonstrated high comprehensibility and acceptable validity, the evaluation relied on a post-hoc telephone survey using only self-reported data, precluding validation against objective screening records. A persistent challenge in Japan is the absence of a comprehensive reference standard, as individuals may be screened by multiple providers [ 8 ]. Even under these circumstances, sensitivity (the proportion of individuals with documented screening who correctly report it) can be estimated using data from a single institution, providing an essential first step in characterizing the measurement properties of CSLC screening items. Therefore, we conducted a cross-sectional validation study linking self-reported cancer screening histories, obtained via a mailed questionnaire replicating CSLC items, with objectively recorded examinations at a large screening center in Japan. We focused on gastric and breast cancer screening, as both programs target middle-aged and older adults and are recommended biennially, enabling straightforward stratification during the sampling process. Sensitivity was estimated within the recommended 2-year recall window, with exploratory analyses for other screening sites. Methods Study design, setting, and population We conducted a cross-sectional, medical record-linked validation study comparing self-reported cancer screening participation, obtained via a mailed questionnaire, with electronic medical records at the Miyagi Cancer Society Cancer Detection Center. The center delivers high-volume, population-based screening for gastric, colorectal, cervical, and breast cancers in accordance with national quality assurance standards [ 26 – 28 ]. This study focused on population-based screening, defining screening receipt as having undergone gastric cancer screening using barium radiography, breast cancer screening using mammography, colorectal cancer screening using fecal occult blood testing, or cervical cancer screening using cervical cytology (Pap test). In Japan, local governments commission these screenings and screening facilities are required to maintain records for at least 5 years [ 29 ]. However, participants may have been screened by other providers, meaning the center’s records did not capture complete screening histories and thus represented an incomplete reference standard. Therefore, the primary analysis focused on estimating the sensitivity of gastric and breast cancer screening. Using the center’s electronic records, we identified individuals who underwent gastric cancer screening, breast cancer screening, or both in the fiscal year (FY) 2020 or FY2021 (the FY in Japan runs from April to March). Eligibility criteria followed national recommendations: men and women aged 50–69 years for gastric cancer screening, and women aged 40–69 years for breast cancer screening. Age was calculated at the end of FY2024. Individuals with recorded deaths were excluded. Sampling strategy Survey recipients were selected using stratified random sampling based on age, sex, and recent screening history. For men aged 50–69 years, strata were defined by 10-year age categories and whether they had undergone gastric cancer screening in FY2022 or FY2023. For women aged 50–69 years, strata were defined by the same age categories and past screening history for both gastric and breast cancers, allowing this sampling frame to contribute to both analyses. For women aged 40–49 years, strata were defined solely by their breast cancer screening history. Across these strata, 4,000 individuals were sampled, resulting in 2,666 individuals eligible for the gastric cancer screening and 2,667 eligible for breast cancer screening. A total sample size of 4,000 was determined based on feasibility and expected response patterns. We assumed higher response rates among recent screening attendees (60%) than among non-attendees (40%), high accuracy of self-reported screening among true attendees (90%), and lower accuracy among true non-attendees, with 20% expected to report screening despite having no records. Under these assumptions, allocating 2,666 participants to the gastric cancer screening analysis (727 expected attendees and 1,939 non-attendees) and 2,667 to the breast cancer screening analysis (727 attendees and 1,940 non-attendees) yields an expected measurement error of approximately ± 2.8% at the 95% confidence level for both groups. These considerations informed the decision to sample 4,000 participants. Questionnaire and data collection The questionnaire replicated the CSLC cancer screening items with minimal modifications. An English version of the questionnaire is provided as Additional file 1 (Figure S1 ). Respondents reported whether they had undergone each type of screening within the preceding 1 or 2 years, depending on the cancer type, and were instructed to include all examinations. Each questionnaire carried a unique study identifier, enabling linkage to the center’s medical records. The questionnaires were mailed on November 27, 2024, and responses received by January 17, 2025, were included in the analysis. Participants provided informed consent by checking a designated box on the questionnaire and returning it to a pre-addressed envelope. The returned questionnaires were linked to medical records using study identifiers. Measures and statistical analysis Self-reported screening status was compared with participants’ medical records. Individuals who reported undergoing screening and had a corresponding medical record were classified as true positives, whereas those who did not report screening despite having a medical record were classified as false negatives. Sensitivity was calculated as the proportion of individuals with medical record-confirmed screening who accurately reported having been screened. The primary analysis evaluated gastric and breast cancer screening within a 2-year period, corresponding to FY2022 and FY2023, respectively. Secondary analyses examined colorectal cancer screening within 1 year and cervical cancer screening within 2 years, with self-reports matched to medical records for the corresponding time frame. Since the questionnaire asked about screening "in the past 2 years" and the survey was administered in the latter half of FY2024, some respondents may have interpreted the reference period as including examinations conducted earlier in FY2024. To evaluate the extent to which this interpretation could influence the results, we conducted a sensitivity analysis incorporating FY2024 screening records into the time window. Although sensitivity was the primary measure of interest, we also calculated specificity, positive predictive value, and negative predictive value using supplementary descriptive statistics. As screenings conducted outside the center were unobservable, these estimates should not be interpreted as measures of true classification accuracy. Ninety-five percent confidence intervals (CIs) for proportion-based metrics were calculated using the Wilson scoring method. All the analyses were performed using Python version 3.11. Simulation of potential bias under varying specificity To illustrate how varying specificity can influence survey-based uptake estimates, we derived the true uptake ( \(\:{p}_{true}\) ) from the observed self-reported uptake ( \(\:{p}_{observed}\) ) using the Rogan–Gladen estimator [ 30 ], which adjusts the observed prevalence for imperfect sensitivity and specificity. The relationship between the true uptake and observed uptake is defined as $$\:{p}_{true}=\frac{{p}_{observed}+Specificity-1}{Sensitivity+Specificity-1}$$ Sensitivity estimates obtained in this study were used in the simulation. Ethical considerations The study was approved by the Ethics Committee of the National Cancer Center (approval number 2024-063) and the Ethics Committee of the Miyagi Cancer Society (approval number 2408). This study was conducted in accordance with the guidelines outlined in the Declaration of Helsinki. An explanatory leaflet was enclosed with each questionnaire. Participants provided informed consent by checking the designated box on the questionnaire and returning it. Table 1 Participant characteristics of the analytic sample Characteristic Total (n = 1,151) Men (n = 380) Women (n = 771) Age, years 57 (49, 64) 62 (57, 67) 54 (47, 61) Age group, years 40–49 327 (28.4) — 327 (42.4) 50–59 387 (33.6) 168 (44.2) 219 (28.4) 60–69 437 (38.0) 212 (55.8) 225 (29.2) Record-confirmed screening in FY2022–FY2023 Gastric cancer screening 331 (40.2) 156 (41.1) 175 (39.4) Breast cancer screening — — 288 (37.4) Record-confirmed gastric cancer screening by fiscal year FY2020 398 (48.3) 222 (58.4) 176 (39.6) FY2021 491 (59.6) 280 (73.7) 211 (47.5) FY2022 291 (35.3) 140 (36.8) 151 (34.0) FY2023 254 (30.8) 123 (32.4) 131 (29.5) FY2024 281 (34.1) 143 (37.6) 138 (31.1) Record-confirmed breast cancer screening by fiscal year FY2020 — — 296 (38.4) FY2021 — — 351 (45.5) FY2022 — — 162 (21.0) FY2023 — — 136 (17.6) FY2024 — — 172 (22.3) Values are presented as n (%) unless otherwise indicated. Age is shown as median (first quartile, third quartile). Screening history was ascertained from the electronic medical records at the Miyagi Cancer Society Cancer Detection Center. For women, the number of gastric cancer screening attendees was restricted to those aged 50–69 years old. Abbreviations: FY, fiscal year. “—" indicates not applicable. Results Study participants A total of 34,472 individuals (5,730 males and 28,742 females) underwent gastric cancer screening, breast cancer screening, or both between FY2020 and FY2021. Two deceased individuals were excluded from the study. Subsequently, 4,000 individuals were randomly selected and invited to participate in the study. During sampling, the number of men in their 50s who had not undergone gastric cancer screening in FY2022–FY2023 was smaller than anticipated (473 observed vs. 484 planned); therefore, all eligible individuals in this stratum were included, and the remaining 11 samples were reallocated to other strata to maintain the target sample size. Of the 4,000 individuals invited, 1,604 (40.1%) returned the questionnaire, and 1,151 (28.8%) provided informed consent and were included in the final analysis (Table 1 ). The analytical sample comprised 380 men and 771 women, with a median age of 57 years. The age distribution was 38.0% for 60–69 years, 33.6% for 50–59 years, and 28.4% for 40–49 years. Notably, the 40–49 age group consisted entirely of women, representing 42.4% of female participants. Based on screening center records, 331 participants (40.2%) underwent gastric cancer screening in FY2022–FY2023, and 288 women (37.4%) underwent breast cancer screening during the same period. A total of 824 participants were eligible for gastric cancer screening and 771 women for breast cancer screening. Sensitivity of Self-Reported Screening Gastric and breast cancer screening (Additional file 2: Table S2 ) Of 331 participants with medical records indicating gastric cancer screening in FY2022–FY2023, 318 reported having undergone screening on the questionnaire, yielding a sensitivity of 96.1% (95% CI, 93.4–97.7%). For breast cancer screening, 288 women had medical records during the same period, and 276 accurately reported screening, resulting in a sensitivity of 95.8% (95% CI, 92.9–97.6%). Other cancer screening (Additional file 2: Table S2 ) Analyses of colorectal and cervical cancer screenings were considered exploratory, as the sampling strategy was based on gastric and breast cancer screening histories. Sensitivity was 93.6% (95% CI, 90.5–95.7%) for colorectal cancer screening assessed within a 1-year window and 96.3% (95% CI, 94.1–97.7%) for cervical cancer screening assessed within a 2-year window. Sensitivity analysis (Expanded record window) To account for the questionnaire referring to screening in “the past 2 years” and its administration in late FY2024, we conducted an analysis incorporating FY2024 medical records. Sensitivity was 94.8% (95% CI, 92.8–96.2%) for gastric cancer screening and 96.1% (95% CI, 94.3–97.4%) for breast cancer screening. These findings indicate that potential differences in respondents’ interpretations of the recall period did not materially affect the sensitivity estimates. Supplementary descriptive analyses Screenings conducted outside the center could not be observed; therefore, the associated classification metrics could not be interpreted as measures of true accuracy. These metrics were calculated only for descriptive purposes, and their crude values are presented in Additional File 2: Table S2 . Simulation of potential bias from imperfect specificity Using the sensitivity estimate obtained in this study, we simulated how varying specificity could influence the discrepancy between self-reported and true screening uptake. As shown in Fig. 1 , with high sensitivity (96%) and true uptake below relatively high levels (approximately 70–80%), even modest decreases in specificity noticeably inflated self-reported uptake. Discussion This medical record-linked validation study was the first to evaluate the sensitivity of the cancer screening questionnaire used in the CSLC, the source of Japan’s national screening statistics. The questionnaire demonstrated high sensitivity, approximately 96%, for gastric and breast cancer screening, with similarly high sensitivity for colorectal and cervical cancer screening. These findings indicate that individuals with documented recent screenings generally report their participation accurately on CSLC-type questionnaires. This pattern aligns with international studies reporting high sensitivity for self-reported screening [ 11 , 20 , 23 , 31 ] and a previous Japanese validation study [ 24 ], although our estimates were slightly higher. A plausible explanation for this is that our sample consisted of younger participants with more recent screening, who may have recalled examinations more accurately. Additionally, our questionnaire closely replicated CSLC items, ensuring its relevance for interpreting national survey estimates. Although the CSLC items demonstrated high sensitivity in identifying screened individuals, our findings highlight the importance of specificity when using self-reported data for population-level monitoring. Previous studies have consistently reported lower specificity than sensitivity for self-reported cancer screening histories [ 11 , 22 , 23 , 31 ], and our simulation suggested that even modest decreases in specificity can substantially inflate screening uptake estimates, particularly when the true uptake is not high, as expected in Japan. We also considered the possibility that the respondents misinterpreted the recall period. Unlike the CSLC, which is typically administered in the first half of the FY, our survey was conducted in late FY2024, so some participants may have included examinations conducted earlier in FY2024 as falling within the “past 2 years.” However, the sensitivity analysis incorporating FY2024 records showed minimal differences from the primary estimates, indicating that misinterpretation of the recall period did not meaningfully influence our results. This study has a few limitations. First, screenings performed outside the center were not observable, preventing estimation of specificity and other classification metrics and limiting assessment of the absolute validity of CSLC-based screening rates. Second, the response rate was moderate, raising the possibility that the differences between respondents and non-respondents influenced the sensitivity estimates. Third, the findings may not be fully generalizable to other settings or populations because the study was conducted at a single regional screening center in Japan. Conclusions The CSLC screening items demonstrated very high sensitivity among individuals who recently underwent gastric, breast, colorectal, or cervical cancer screening. In the context of Japan’s moderate screening uptake, this high sensitivity, combined with the likely limited specificity, suggests that national survey estimates may overstate actual participation. Improving the clarity of questionnaire items, reducing ambiguity regarding the reference window, and developing more comprehensive screening registries would enhance the accuracy and policy relevance of cancer screening surveillance in Japan. Future studies should evaluate the specificity and overall validity of the CSLC items in broader populations and examine whether reporting accuracy varies according to social and demographic factors, thereby clarifying potential sources of differential misclassification. Abbreviations CSLC, Comprehensive Survey of Living Conditions; FY, fiscal year; CI, confidence interval. Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of the National Cancer Center (approval number 2024-063) and the Ethics Committee of the Miyagi Cancer Society (approval number 2408). Participants provided informed consent by checking the designated consent box on the questionnaire and returning it. Consent for publication Not applicable. Availability of data and materials The datasets generated or analyzed in this study are not publicly available because they are derived from medical records and may contain potentially identifiable information. De-identified data may be obtained from the corresponding author upon reasonable request, with permission from the data-holding institution and relevant ethics committees. Competing interests TN1 (Toshifumi Namba) was a member of Cancerscan Inc. from April 2022 to December 2023. NT, MO, KK, TH, and TN2 declare no competing interests. Funding This work was supported by the Ministry of Health, Labour, and Welfare through grant 23EA1005. Authors’ contributions TN1 conceptualized the study, conducted the analyses, and drafted the manuscript. NT, TH, and TN2 supervised the study and contributed to the interpretation. MO and KK curated and managed the screening center data and supported record linkage. All authors critically revised the manuscript for important intellectual content and approved the final version. Acknowledgments The authors thank the study participants and staff of the Miyagi Cancer Society Cancer Detection Center for supporting survey administration and data linkage. We would like to thank Editage (www.editage.jp) for English language editing. Part of this study was presented at JH Retreat 2025. References White MC, Babcock F, Hayes NS, Mariotto AB, Wong FL, Kohler BA, et al. The history and use of cancer registry data by public health cancer control programs in the United States. Cancer. 2017;123(Suppl 24):4969–76. Soleimani M, GhaziSaeedi M, Ayyoubzadeh SM, Jalilvand A. A systematic review and comparative evaluation to develop and validate a comprehensive framework for cancer surveillance systems. Arch Public Health. 2025;83:99. Vernon SW, Briss PA, Tiro JA, Warnecke RB. Some methodologic lessons learned from cancer screening research. Cancer. 2004;101:1131–45. 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Katz ML, Stump TE, Monahan PO, Emerson B, Baltic R, Young GS, et al. Factors associated with the accurate self-report of cancer screening behaviors among women living in the rural Midwest region of the United States. Prev Med Rep. 2022;30:102063. Additional Declarations Competing interest reported. TN1 (Toshifumi Namba) was a member of Cancerscan Inc. from April 2022 to December 2023. NT, MO, KK, TH, and TN2 declare no competing interests. Supplementary Files 20260224Additionalfile1.pdf Additional file 1 File name: Additional file 1.pdf File format: PDF (.pdf) Title of data: Figure S1. Questionnaire used to assess self-reported participation in cancer screening (Japanese version) Description of data: A self-administered questionnaire replicating the cancer screening items of the Comprehensive Survey of Living Conditions, with minimal modifications. The one-page A4 form, written in Japanese, asked respondents whether they had undergone gastric, lung, colorectal, cervical, and breast cancer screening within the specified recall periods and, for each cancer type, the route through which the screening was received (municipality-based, workplace or health‑ insurance-based, or other). 20260205Additionalfile2.docx Additional file 2 File name: Additional file 2.docx File format: DOCX (.docx) Title of data: Table S2. Crude Validity of Self-reported Cancer Screening Participation Compared to Screening Center Medical Records Description of data: Cross-tabulation of self-reported and recorded screening participation, with crude validity indices (sensitivity, specificity, and positive and negative predictive values) for gastric, breast, colorectal, and cervical cancer screening. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 03 Apr, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers invited by journal 24 Mar, 2026 Editor assigned by journal 23 Mar, 2026 Editor invited by journal 24 Feb, 2026 Submission checks completed at journal 24 Feb, 2026 First submitted to journal 24 Feb, 2026 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-8914059","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":611819647,"identity":"6da4e831-0a01-4ff6-8eee-839321886cd9","order_by":0,"name":"Toshifumi Namba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYJACZgYGGxibjbByHoiWNNK1HCbBUfbSzU83F9Scz+NvP8D84gMDXx5hW2SOmd2ecex2scSZBDbLGQxsxYS1SCSY3eZhu524QYKBzZiHgS2xgbCW9G+3ef6dI0lLjtlt3rYDIC3Mj4nTciOn7PbMvuTEGWcS2xhnGBDhF/YZ6dtuF3yzS+xvP3z4w4eKY4RDDAkwtkkwGBxLIEULA/MHBoYa0rSMglEwCkbBiAAASCs5FElnTjAAAAAASUVORK5CYII=","orcid":"","institution":"National Cancer Center Japan Institute for Cancer Control","correspondingAuthor":true,"prefix":"","firstName":"Toshifumi","middleName":"","lastName":"Namba","suffix":""},{"id":611819648,"identity":"05b2c110-555c-4224-99d9-1044c136afa9","order_by":1,"name":"Noriaki Takahashi","email":"","orcid":"","institution":"National Cancer Center Japan Institute for Cancer Control","correspondingAuthor":false,"prefix":"","firstName":"Noriaki","middleName":"","lastName":"Takahashi","suffix":""},{"id":611819649,"identity":"69f91764-a158-4120-938e-bba0e25433a5","order_by":2,"name":"Masaaki Otomo","email":"","orcid":"","institution":"Miyagi Cancer Society","correspondingAuthor":false,"prefix":"","firstName":"Masaaki","middleName":"","lastName":"Otomo","suffix":""},{"id":611819650,"identity":"42563a04-3a05-4e85-beae-60bf9f9133b2","order_by":3,"name":"Katsuaki Kato","email":"","orcid":"","institution":"Miyagi Cancer Society","correspondingAuthor":false,"prefix":"","firstName":"Katsuaki","middleName":"","lastName":"Kato","suffix":""},{"id":611819651,"identity":"5da30c06-fec1-4d35-908c-6adcff040b74","order_by":4,"name":"Takahiro Higashi","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Takahiro","middleName":"","lastName":"Higashi","suffix":""},{"id":611819652,"identity":"07c6b029-d6c4-48e3-a3be-e23233307f7f","order_by":5,"name":"Tomio Nakayama","email":"","orcid":"","institution":"National Cancer Center Japan Institute for Cancer Control","correspondingAuthor":false,"prefix":"","firstName":"Tomio","middleName":"","lastName":"Nakayama","suffix":""}],"badges":[],"createdAt":"2026-02-19 05:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8914059/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8914059/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105475206,"identity":"3020f6b6-36f5-448d-8ce8-036eda7da41a","added_by":"auto","created_at":"2026-03-26 12:42:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":192990,"visible":true,"origin":"","legend":"\u003cp\u003eTitle: Relationship between true and self-reported screening uptake by questionnaire specificity.\u003c/p\u003e\n\u003cp\u003eDetailed legend: This figure plots expected self-reported screening uptake (vertical axis) against true screening uptake (horizontal axis), with both axes ranging from 0% to 100%. The solid black diagonal line represents the line of equality, where self-reported uptake would exactly match true uptake (no bias; sensitivity and specificity both 100%). The four colored lines (as indicated in the figure key) show the expected self-reported uptake when the questionnaire sensitivity was fixed at 96%, as estimated in this study for gastric and breast cancer screening, and the specificity was assumed to be 100%, 90%, 80%, and 70%, respectively. For each assumed specificity, the curve was derived from the standard relationship between true prevalence, sensitivity, specificity, and the probability of a positive self-report. When the specificity is less than 100%, the curves likely lie above the line of equality at modest true uptake levels, indicating that self-reported screening participation is increasingly overestimated as specificity declines. The figure illustrates that, given the empirically observed high sensitivity of the CSLC-type questionnaire, upward bias in survey-based estimates of screening coverage is driven mainly by imperfect specificity rather than by missed reports among screened individuals.\u003c/p\u003e","description":"","filename":"20260127Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8914059/v1/c233c484600467e0c26fc921.jpg"},{"id":105475223,"identity":"bcf10cf7-3e43-4875-aca6-5f671cc09e8d","added_by":"auto","created_at":"2026-03-26 12:43:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":816108,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8914059/v1/8b57fc0d-e3bc-4f02-9592-e52d8020d161.pdf"},{"id":105475191,"identity":"ca15a455-39d7-431f-98eb-ad4d6a9a37ef","added_by":"auto","created_at":"2026-03-26 12:42:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":206398,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 1\u003c/p\u003e\n\u003cp\u003eFile name: Additional file 1.pdf\u003c/p\u003e\n\u003cp\u003eFile format: PDF (.pdf)\u003c/p\u003e\n\u003cp\u003eTitle of data: Figure S1. Questionnaire used to assess self-reported participation in cancer screening (Japanese version)\u003c/p\u003e\n\u003cp\u003eDescription of data: A self-administered questionnaire replicating the cancer screening items of the Comprehensive Survey of Living Conditions, with minimal modifications. The one-page A4 form, written in Japanese, asked respondents whether they had undergone gastric, lung, colorectal, cervical, and breast cancer screening within the specified recall periods and, for each cancer type, the route through which the screening was received (municipality-based, workplace or health‑ insurance-based, or other).\u003c/p\u003e","description":"","filename":"20260224Additionalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8914059/v1/7d62c71b5a6ed41cfa66e859.pdf"},{"id":105475221,"identity":"639c12d3-c787-4587-ac40-f6e2c39cc756","added_by":"auto","created_at":"2026-03-26 12:42:57","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17757,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 2\u003c/p\u003e\n\u003cp\u003eFile name: Additional file 2.docx\u003c/p\u003e\n\u003cp\u003eFile format: DOCX (.docx)\u003c/p\u003e\n\u003cp\u003eTitle of data: Table S2. Crude Validity of Self-reported Cancer Screening Participation Compared to Screening Center Medical Records\u003c/p\u003e\n\u003cp\u003eDescription of data: Cross-tabulation of self-reported and recorded screening participation, with crude validity indices (sensitivity, specificity, and positive and negative predictive values) for gastric, breast, colorectal, and cervical cancer screening.\u003c/p\u003e","description":"","filename":"20260205Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8914059/v1/906e200bbb9dce305a2a9ecd.docx"}],"financialInterests":"Competing interest reported. TN1 (Toshifumi Namba) was a member of Cancerscan Inc. from April 2022 to December 2023. NT, MO, KK, TH, and TN2 declare no competing interests.","formattedTitle":"Sensitivity of the cancer screening items in Japan’s Comprehensive Survey of Living Conditions: a medical record-linked cross-sectional validation study","fulltext":[{"header":"Background","content":"\u003cp\u003eAccurate monitoring of population-level cancer screening uptake is essential for assessing progress toward national cancer control targets and guiding public health resource allocation [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Many countries maintain program-based registries that comprehensively capture screening encounters and enable routine estimation of screening rates [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In Japan, cancer screening services are provided by a wide range of entities, including municipalities, occupational health programs, and individual medical institutions, with no nationwide system integrating records across providers [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. As of 2025, the government recommends age-based population screening for five major cancers: colorectal (annual fecal occult blood test from \u0026ge;\u0026thinsp;40 years); lung (annual chest radiography from \u0026ge;\u0026thinsp;40 years, with sputum cytology for individuals at increased risk from \u0026ge;\u0026thinsp;50 years); gastric (biennial barium radiography or endoscopy from \u0026ge;\u0026thinsp;50 years); breast (biennial mammography for women\u0026thinsp;\u0026ge;\u0026thinsp;40 years); and cervical (biennial cytology for women\u0026thinsp;\u0026ge;\u0026thinsp;20 years or human papillomavirus testing every 5 years for women\u0026thinsp;\u0026ge;\u0026thinsp;30 years) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In the absence of an integrated screening registry, national statistics rely primarily on the triennial Comprehensive Survey of Living Conditions (CSLC), which reports an overall screening uptake of approximately 50%, with substantial variations across cancer sites [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although these estimates have gradually increased over the past few decades, they remain below the 60% target set by the Fourth Basic Plan to Promote Cancer Control Programs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs with any survey based on self-reported screening, CSLC estimates are vulnerable to measurement errors, including recall bias [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], misunderstanding of the reference period (telescoping) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], confusion between screening and diagnostic procedures [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and biases from low response rates [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Notably, the 2013 CSLC survey round introduced major revisions to the questionnaire, coinciding with an apparent increase of more than 10% in the reported uptake for several cancer types compared with the previous round [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although minor modifications were introduced in 2013, the overall structure of the questionnaire remained largely unchanged. International evidence shows that survey-based screening rates often differ from registry-based rates [\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and meta-analyses indicate that the accuracy of self-reported cancer screening varies by cancer type and test [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In Japan, a recent validation study comparing self-reported histories with municipal administrative records offered preliminary insights [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]; however, the questionnaire used differed in structure from the CSLC instrument.\u003c/p\u003e \u003cp\u003eTo date, no study has directly evaluated the cancer screening items introduced in the 2013 CSLC. Before implementation, Shibuya et al. assessed the comprehensibility and validity of a prototype of the current CSLC items [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Although the prototype demonstrated high comprehensibility and acceptable validity, the evaluation relied on a post-hoc telephone survey using only self-reported data, precluding validation against objective screening records. A persistent challenge in Japan is the absence of a comprehensive reference standard, as individuals may be screened by multiple providers [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Even under these circumstances, sensitivity (the proportion of individuals with documented screening who correctly report it) can be estimated using data from a single institution, providing an essential first step in characterizing the measurement properties of CSLC screening items.\u003c/p\u003e \u003cp\u003eTherefore, we conducted a cross-sectional validation study linking self-reported cancer screening histories, obtained via a mailed questionnaire replicating CSLC items, with objectively recorded examinations at a large screening center in Japan. We focused on gastric and breast cancer screening, as both programs target middle-aged and older adults and are recommended biennially, enabling straightforward stratification during the sampling process. Sensitivity was estimated within the recommended 2-year recall window, with exploratory analyses for other screening sites.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design, setting, and population\u003c/p\u003e \u003cp\u003e We conducted a cross-sectional, medical record-linked validation study comparing self-reported cancer screening participation, obtained via a mailed questionnaire, with electronic medical records at the Miyagi Cancer Society Cancer Detection Center. The center delivers high-volume, population-based screening for gastric, colorectal, cervical, and breast cancers in accordance with national quality assurance standards [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This study focused on population-based screening, defining screening receipt as having undergone gastric cancer screening using barium radiography, breast cancer screening using mammography, colorectal cancer screening using fecal occult blood testing, or cervical cancer screening using cervical cytology (Pap test). In Japan, local governments commission these screenings and screening facilities are required to maintain records for at least 5 years [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, participants may have been screened by other providers, meaning the center\u0026rsquo;s records did not capture complete screening histories and thus represented an incomplete reference standard. Therefore, the primary analysis focused on estimating the sensitivity of gastric and breast cancer screening.\u003c/p\u003e \u003cp\u003eUsing the center\u0026rsquo;s electronic records, we identified individuals who underwent gastric cancer screening, breast cancer screening, or both in the fiscal year (FY) 2020 or FY2021 (the FY in Japan runs from April to March). Eligibility criteria followed national recommendations: men and women aged 50\u0026ndash;69 years for gastric cancer screening, and women aged 40\u0026ndash;69 years for breast cancer screening. Age was calculated at the end of FY2024. Individuals with recorded deaths were excluded.\u003c/p\u003e \u003cp\u003eSampling strategy\u003c/p\u003e \u003cp\u003eSurvey recipients were selected using stratified random sampling based on age, sex, and recent screening history. For men aged 50\u0026ndash;69 years, strata were defined by 10-year age categories and whether they had undergone gastric cancer screening in FY2022 or FY2023. For women aged 50\u0026ndash;69 years, strata were defined by the same age categories and past screening history for both gastric and breast cancers, allowing this sampling frame to contribute to both analyses. For women aged 40\u0026ndash;49 years, strata were defined solely by their breast cancer screening history. Across these strata, 4,000 individuals were sampled, resulting in 2,666 individuals eligible for the gastric cancer screening and 2,667 eligible for breast cancer screening.\u003c/p\u003e \u003cp\u003eA total sample size of 4,000 was determined based on feasibility and expected response patterns. We assumed higher response rates among recent screening attendees (60%) than among non-attendees (40%), high accuracy of self-reported screening among true attendees (90%), and lower accuracy among true non-attendees, with 20% expected to report screening despite having no records. Under these assumptions, allocating 2,666 participants to the gastric cancer screening analysis (727 expected attendees and 1,939 non-attendees) and 2,667 to the breast cancer screening analysis (727 attendees and 1,940 non-attendees) yields an expected measurement error of approximately\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8% at the 95% confidence level for both groups. These considerations informed the decision to sample 4,000 participants.\u003c/p\u003e \u003cp\u003eQuestionnaire and data collection\u003c/p\u003e \u003cp\u003eThe questionnaire replicated the CSLC cancer screening items with minimal modifications. An English version of the questionnaire is provided as Additional file 1 (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Respondents reported whether they had undergone each type of screening within the preceding 1 or 2 years, depending on the cancer type, and were instructed to include all examinations. Each questionnaire carried a unique study identifier, enabling linkage to the center\u0026rsquo;s medical records.\u003c/p\u003e \u003cp\u003eThe questionnaires were mailed on November 27, 2024, and responses received by January 17, 2025, were included in the analysis. Participants provided informed consent by checking a designated box on the questionnaire and returning it to a pre-addressed envelope. The returned questionnaires were linked to medical records using study identifiers.\u003c/p\u003e \u003cp\u003eMeasures and statistical analysis\u003c/p\u003e \u003cp\u003eSelf-reported screening status was compared with participants\u0026rsquo; medical records. Individuals who reported undergoing screening and had a corresponding medical record were classified as true positives, whereas those who did not report screening despite having a medical record were classified as false negatives. Sensitivity was calculated as the proportion of individuals with medical record-confirmed screening who accurately reported having been screened.\u003c/p\u003e \u003cp\u003eThe primary analysis evaluated gastric and breast cancer screening within a 2-year period, corresponding to FY2022 and FY2023, respectively. Secondary analyses examined colorectal cancer screening within 1 year and cervical cancer screening within 2 years, with self-reports matched to medical records for the corresponding time frame.\u003c/p\u003e \u003cp\u003eSince the questionnaire asked about screening \"in the past 2 years\" and the survey was administered in the latter half of FY2024, some respondents may have interpreted the reference period as including examinations conducted earlier in FY2024. To evaluate the extent to which this interpretation could influence the results, we conducted a sensitivity analysis incorporating FY2024 screening records into the time window.\u003c/p\u003e \u003cp\u003eAlthough sensitivity was the primary measure of interest, we also calculated specificity, positive predictive value, and negative predictive value using supplementary descriptive statistics. As screenings conducted outside the center were unobservable, these estimates should not be interpreted as measures of true classification accuracy. Ninety-five percent confidence intervals (CIs) for proportion-based metrics were calculated using the Wilson scoring method. All the analyses were performed using Python version 3.11.\u003c/p\u003e \u003cp\u003eSimulation of potential bias under varying specificity\u003c/p\u003e \u003cp\u003eTo illustrate how varying specificity can influence survey-based uptake estimates, we derived the true uptake (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{p}_{true}\\)\u003c/span\u003e\u003c/span\u003e) from the observed self-reported uptake (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{p}_{observed}\\)\u003c/span\u003e\u003c/span\u003e) using the Rogan\u0026ndash;Gladen estimator [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], which adjusts the observed prevalence for imperfect sensitivity and specificity. The relationship between the true uptake and observed uptake is defined as\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{p}_{true}=\\frac{{p}_{observed}+Specificity-1}{Sensitivity+Specificity-1}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eSensitivity estimates obtained in this study were used in the simulation.\u003c/p\u003e \u003cp\u003eEthical considerations\u003c/p\u003e \u003cp\u003e The study was approved by the Ethics Committee of the National Cancer Center (approval number 2024-063) and the Ethics Committee of the Miyagi Cancer Society (approval number 2408). This study was conducted in accordance with the guidelines outlined in the Declaration of Helsinki. An explanatory leaflet was enclosed with each questionnaire. Participants provided informed consent by checking the designated box on the questionnaire and returning it.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant characteristics of the analytic sample\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;1,151)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMen (n\u0026thinsp;=\u0026thinsp;380)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen (n\u0026thinsp;=\u0026thinsp;771)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (49, 64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (57, 67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (47, 61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e327 (28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e327 (42.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387 (33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e219 (28.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e437 (38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e212 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e225 (29.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRecord-confirmed screening in FY2022\u0026ndash;FY2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastric cancer screening\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e331 (40.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156 (41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e175 (39.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast cancer screening\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e288 (37.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRecord-confirmed gastric cancer screening by fiscal year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e398 (48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222 (58.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176 (39.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e491 (59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280 (73.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e211 (47.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e151 (34.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e254 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123 (32.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (29.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e281 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e138 (31.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRecord-confirmed breast cancer screening by fiscal year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e296 (38.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e351 (45.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162 (21.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136 (17.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172 (22.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are presented as n (%) unless otherwise indicated. Age is shown as median (first quartile, third quartile). Screening history was ascertained from the electronic medical records at the Miyagi Cancer Society Cancer Detection Center. For women, the number of gastric cancer screening attendees was restricted to those aged 50\u0026ndash;69 years old. Abbreviations: FY, fiscal year. \u0026ldquo;\u0026mdash;\" indicates not applicable.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eStudy participants\u003c/p\u003e \u003cp\u003eA total of 34,472 individuals (5,730 males and 28,742 females) underwent gastric cancer screening, breast cancer screening, or both between FY2020 and FY2021. Two deceased individuals were excluded from the study. Subsequently, 4,000 individuals were randomly selected and invited to participate in the study. During sampling, the number of men in their 50s who had not undergone gastric cancer screening in FY2022\u0026ndash;FY2023 was smaller than anticipated (473 observed vs. 484 planned); therefore, all eligible individuals in this stratum were included, and the remaining 11 samples were reallocated to other strata to maintain the target sample size. Of the 4,000 individuals invited, 1,604 (40.1%) returned the questionnaire, and 1,151 (28.8%) provided informed consent and were included in the final analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The analytical sample comprised 380 men and 771 women, with a median age of 57 years. The age distribution was 38.0% for 60\u0026ndash;69 years, 33.6% for 50\u0026ndash;59 years, and 28.4% for 40\u0026ndash;49 years. Notably, the 40\u0026ndash;49 age group consisted entirely of women, representing 42.4% of female participants. Based on screening center records, 331 participants (40.2%) underwent gastric cancer screening in FY2022\u0026ndash;FY2023, and 288 women (37.4%) underwent breast cancer screening during the same period. A total of 824 participants were eligible for gastric cancer screening and 771 women for breast cancer screening.\u003c/p\u003e \u003cp\u003eSensitivity of Self-Reported Screening\u003c/p\u003e \u003cp\u003eGastric and breast cancer screening (Additional file 2: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eOf 331 participants with medical records indicating gastric cancer screening in FY2022\u0026ndash;FY2023, 318 reported having undergone screening on the questionnaire, yielding a sensitivity of 96.1% (95% CI, 93.4\u0026ndash;97.7%). For breast cancer screening, 288 women had medical records during the same period, and 276 accurately reported screening, resulting in a sensitivity of 95.8% (95% CI, 92.9\u0026ndash;97.6%).\u003c/p\u003e \u003cp\u003eOther cancer screening (Additional file 2: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAnalyses of colorectal and cervical cancer screenings were considered exploratory, as the sampling strategy was based on gastric and breast cancer screening histories. Sensitivity was 93.6% (95% CI, 90.5\u0026ndash;95.7%) for colorectal cancer screening assessed within a 1-year window and 96.3% (95% CI, 94.1\u0026ndash;97.7%) for cervical cancer screening assessed within a 2-year window.\u003c/p\u003e \u003cp\u003eSensitivity analysis (Expanded record window)\u003c/p\u003e \u003cp\u003eTo account for the questionnaire referring to screening in \u0026ldquo;the past 2 years\u0026rdquo; and its administration in late FY2024, we conducted an analysis incorporating FY2024 medical records. Sensitivity was 94.8% (95% CI, 92.8\u0026ndash;96.2%) for gastric cancer screening and 96.1% (95% CI, 94.3\u0026ndash;97.4%) for breast cancer screening. These findings indicate that potential differences in respondents\u0026rsquo; interpretations of the recall period did not materially affect the sensitivity estimates.\u003c/p\u003e \u003cp\u003eSupplementary descriptive analyses\u003c/p\u003e \u003cp\u003eScreenings conducted outside the center could not be observed; therefore, the associated classification metrics could not be interpreted as measures of true accuracy. These metrics were calculated only for descriptive purposes, and their crude values are presented in Additional File 2: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eSimulation of potential bias from imperfect specificity\u003c/p\u003e \u003cp\u003eUsing the sensitivity estimate obtained in this study, we simulated how varying specificity could influence the discrepancy between self-reported and true screening uptake. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with high sensitivity (96%) and true uptake below relatively high levels (approximately 70\u0026ndash;80%), even modest decreases in specificity noticeably inflated self-reported uptake.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis medical record-linked validation study was the first to evaluate the sensitivity of the cancer screening questionnaire used in the CSLC, the source of Japan\u0026rsquo;s national screening statistics. The questionnaire demonstrated high sensitivity, approximately 96%, for gastric and breast cancer screening, with similarly high sensitivity for colorectal and cervical cancer screening. These findings indicate that individuals with documented recent screenings generally report their participation accurately on CSLC-type questionnaires. This pattern aligns with international studies reporting high sensitivity for self-reported screening [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and a previous Japanese validation study [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], although our estimates were slightly higher. A plausible explanation for this is that our sample consisted of younger participants with more recent screening, who may have recalled examinations more accurately. Additionally, our questionnaire closely replicated CSLC items, ensuring its relevance for interpreting national survey estimates.\u003c/p\u003e \u003cp\u003eAlthough the CSLC items demonstrated high sensitivity in identifying screened individuals, our findings highlight the importance of specificity when using self-reported data for population-level monitoring. Previous studies have consistently reported lower specificity than sensitivity for self-reported cancer screening histories [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and our simulation suggested that even modest decreases in specificity can substantially inflate screening uptake estimates, particularly when the true uptake is not high, as expected in Japan.\u003c/p\u003e \u003cp\u003eWe also considered the possibility that the respondents misinterpreted the recall period. Unlike the CSLC, which is typically administered in the first half of the FY, our survey was conducted in late FY2024, so some participants may have included examinations conducted earlier in FY2024 as falling within the \u0026ldquo;past 2 years.\u0026rdquo; However, the sensitivity analysis incorporating FY2024 records showed minimal differences from the primary estimates, indicating that misinterpretation of the recall period did not meaningfully influence our results.\u003c/p\u003e \u003cp\u003eThis study has a few limitations. First, screenings performed outside the center were not observable, preventing estimation of specificity and other classification metrics and limiting assessment of the absolute validity of CSLC-based screening rates. Second, the response rate was moderate, raising the possibility that the differences between respondents and non-respondents influenced the sensitivity estimates. Third, the findings may not be fully generalizable to other settings or populations because the study was conducted at a single regional screening center in Japan.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe CSLC screening items demonstrated very high sensitivity among individuals who recently underwent gastric, breast, colorectal, or cervical cancer screening. In the context of Japan\u0026rsquo;s moderate screening uptake, this high sensitivity, combined with the likely limited specificity, suggests that national survey estimates may overstate actual participation. Improving the clarity of questionnaire items, reducing ambiguity regarding the reference window, and developing more comprehensive screening registries would enhance the accuracy and policy relevance of cancer screening surveillance in Japan. Future studies should evaluate the specificity and overall validity of the CSLC items in broader populations and examine whether reporting accuracy varies according to social and demographic factors, thereby clarifying potential sources of differential misclassification.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCSLC, Comprehensive Survey of Living Conditions; FY, fiscal year; CI, confidence interval.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of the National Cancer Center (approval number 2024-063) and the Ethics Committee of the Miyagi Cancer Society (approval number 2408). Participants provided informed consent by checking the designated consent box on the questionnaire and returning it.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated or analyzed in this study are not publicly available because they are derived from medical records and may contain potentially identifiable information. De-identified data may be obtained from the corresponding author upon reasonable request, with permission from the data-holding institution and relevant ethics committees.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTN1 (Toshifumi Namba) was a member of Cancerscan Inc. from April 2022 to December 2023. NT, MO, KK, TH, and TN2 declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Ministry of Health, Labour, and Welfare through grant 23EA1005.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTN1 conceptualized the study, conducted the analyses, and drafted the manuscript. NT, TH, and TN2 supervised the study and contributed to the interpretation. MO and KK curated and managed the screening center data and supported record linkage. All authors critically revised the manuscript for important intellectual content and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the study participants and staff of the Miyagi Cancer Society Cancer Detection Center for supporting survey administration and data linkage. We would like to thank Editage (www.editage.jp) for English language editing. Part of this study was presented at JH Retreat 2025.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWhite MC, Babcock F, Hayes NS, Mariotto AB, Wong FL, Kohler BA, et al. The history and use of cancer registry data by public health cancer control programs in the United States. Cancer. 2017;123(Suppl 24):4969\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoleimani M, GhaziSaeedi M, Ayyoubzadeh SM, Jalilvand A. 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J Natl Cancer Inst. 1993;85:566\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson J, Bourne D, Peterson K, Mackey K. Evidence brief: accuracy of self-report for cervical and breast cancer screening. Department of Veterans Affairs; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuraki I, Sobue T, Yamagishi K, Tsugane S, Sawada N, Iso H. Validity of self-reported participation in cancer screenings and health checkups in Japan. J Epidemiol. 2024;35:47\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShibuya D, Kuriyama S, Shimada T, Kato K, Kikuchi R, Inomata Y. A new questionnaire for monitoring the cancer screening rates. Nihon Gan Kenshin Shindan Gakkaishi. 2011;18:246\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFukao A, Tsubono Y, Tsuji I, Hisamichi S, Sugahara N, Takano A. 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Ministry of Health, Labour and Welfare; 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mhlw.go.jp/content/10900000/001642974.pdf\u003c/span\u003e\u003cspan address=\"https://www.mhlw.go.jp/content/10900000/001642974.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRogan WJ, Gladen B. Estimating prevalence from the results of a screening test. Am J Epidemiol. 1978;107:71\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatz ML, Stump TE, Monahan PO, Emerson B, Baltic R, Young GS, et al. Factors associated with the accurate self-report of cancer screening behaviors among women living in the rural Midwest region of the United States. Prev Med Rep. 2022;30:102063.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cancer screening, self-report, validation study, sensitivity, survey measurement, Japan, comprehensive survey of living conditions","lastPublishedDoi":"10.21203/rs.3.rs-8914059/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8914059/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn Japan, national estimates of cancer screening utilization rely primarily on self-reported data from the Comprehensive Survey of Living Conditions (CSLC). However, the validity of the CSLC cancer screening items introduced in 2013 has not been verified against objective screening records. The study aimed to validate the cancer screening items used in Japan\u0026rsquo;s CSLC by comparing self-reported screening histories with medical records.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional validation study by mailing a questionnaire replicating the CSLC cancer screening items to randomly selected individuals with known screening histories at a large screening center. Returned questionnaires were linked to electronic medical records. The primary outcome was the sensitivity of the questionnaire items for gastric and breast cancer screening within a 2-year window (fiscal years [FY] 2022\u0026ndash;2023). Exploratory analyses assessed colorectal cancer screening within a 1-year window and cervical cancer screening within a 2-year window. To evaluate the effects of survey timing (late FY2024), we conducted a sensitivity analysis that expanded the medical record window to include screenings performed in early FY2024.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe questionnaire was mailed to 4,000 individuals, of whom 1,151 were included in the analysis. The sensitivity of the questionnaire was 96.1% for gastric cancer screening (318/331) and 95.8% for breast cancer screening (276/288). Similarly, the sensitivity was high for colorectal (93.6%) and cervical cancer screening (96.3%). The sensitivity estimates changed minimally when early FY2024 examinations were included. Other crude agreement measures, such as specificity, were not interpretable as classification accuracy parameters because screenings conducted outside the center were unobservable.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe CSLC cancer screening items demonstrated high sensitivity, indicating that individuals who were recently screened generally reported their participation accurately. However, given Japan\u0026rsquo;s likely moderate true uptake, even modest shortfalls in specificity could inflate the national survey\u0026ndash;based estimates. Improving questionnaire clarity and developing integrated screening registries can enhance the accuracy of population-level monitoring.\u003c/p\u003e","manuscriptTitle":"Sensitivity of the cancer screening items in Japan’s Comprehensive Survey of Living Conditions: a medical record-linked cross-sectional validation study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 12:42:17","doi":"10.21203/rs.3.rs-8914059/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-03T14:35:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"277802364421033140530139722540920538239","date":"2026-03-27T09:20:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-24T19:03:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-23T12:46:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-25T04:55:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-24T06:19:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-24T06:14:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"24d701d7-0554-4c26-9ac1-7136ef7a93c5","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T12:42:17+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 12:42:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8914059","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8914059","identity":"rs-8914059","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}