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Epidemiology

Risk-stratified selection to colonoscopy in FIT colorectal cancer screening: development and temporal validation of a prediction model

Abstract

Background

Faecal immunochemical tests (FITs) yield many false positives and challenge colonoscopy capacity in colorectal cancer (CRC) screening programmes. We aimed to develop a risk-based selection of participants to undergo diagnostic colonoscopy.

Methods

The study was observational and used registry data from the Danish CRC screening programme. We included all participants invited 2014–2016 with a positive FIT (≥ 20 μg fHb/g) who underwent colonoscopy (n = 56,459). We predicted the risk of CRC or advanced neoplasia (AN) from age, gender and FIT value using logistic regression. We evaluated calibration and discrimination and conducted temporal validation. We compared the number of CRCs and adenomas identified by risk cut-offs and by a corresponding FIT cut-off.

Results

AUCs were 74.9% (95% CI: 73.6; 76.3) and 67.4% (95% CI: 66.8%; 68.0%) for the models predicting CRC and AN in the validation dataset. The cut-off of CRC risk calculated from age, gender and FIT value identified 1.03 times (95% CI: 1.02; 1.05) more CRCs and 1.01 times (95% CI: 1.01; 1.01) more medium/high-risk adenomas compared with the corresponding FIT cut-off.

Conclusions

With existing data, risk-stratified FIT screening using a risk cut-off instead of a FIT cut-off can slightly improve the selection to colonoscopy of those at highest risk of cancer and adenomas.

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Fig. 1: Flow diagram of the study population.
Fig. 2: Receiver-operator characteristic (ROC) curves.

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Data availability

The data for this study are not publicly available, but access to the data sources can be granted by the Danish Colorectal Cancer Screening database and Statistics Denmark, if certain criteria are fulfilled.

References

  1. Schreuders EH, Ruco A, Rabeneck L, Schoen RE, Sung JJY, Young GP, et al. Colorectal cancer screening: a global overview of existing programmes. Gut. 2015;64:1637–49.

    Article  PubMed  Google Scholar 

  2. Danish Health Authority. Recommendations regarding screening for colorectal cancer [Danish] [Internet]. 2010. Available from: https://www.sst.dk/-/media/Udgivelser/2012/Publ2012/Anbefalninger-vedrørende-screening-for-tyk--og-endetarmskræft.ashx.

  3. Thomsen MK, Rasmussen M, Njor SH, Mikkelsen EM. Demographic and comorbidity predictors of adherence to diagnostic colonoscopy in the Danish Colorectal Cancer Screening Program: a nationwide cross-sectional study. Clin Epidemiol. 2018;10:1733–42.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Lawler M, Alsina D, Adams RA, Anderson AS, Brown G, Fearnhead NS, et al. Critical research gaps and recommendations to inform research prioritisation for more effective prevention and improved outcomes in colorectal cancer. Gut. 2018;671136:179–93.

    Article  Google Scholar 

  5. Fraser CG. Faecal haemoglobin concentration and personalised assessment of the risk of colorectal neoplasia. J Lab Precis Med. 2017;2:71–71.

    Article  Google Scholar 

  6. Steele RJ, McDonald PJ, Digby J, Brownlee L, Strachan JA, Libby G, et al. Clinical outcomes using a faecal immunochemical test for haemoglobin as a first-line test in a national programme constrained by colonoscopy capacity. U Eur Gastroenterol J. 2013;1:198–205.

    Article  Google Scholar 

  7. Toes-Zoutendijk E, Leerdam ME, van, Dekker E, Hees F, van, Penning C, Nagtegaal I, et al. Real-time monitoring of results during first year of Dutch colorectal cancer screening program and optimization by altering fecal immunochemical test cut-off levels. Gastroenterology. 2017;152:767–775.e2.

    Article  PubMed  Google Scholar 

  8. Njor SH, Andersen B, Friis-Hansen L, Haas N de, Linnemann D, Nørgaard H, et al. The optimal cut-off value in fit-based colorectal cancer screening: an observational study. Cancer Med. 2021;10:1872–9.

  9. Digby J, Fraser CG, Carey FA, McDonald PJ, Strachan JA, Diament RH, et al. Faecal haemoglobin concentration is related to severity of colorectal neoplasia. J Clin Pathol. 2013; 66:415–9.

  10. Cooper JA, Moss SM, Smith S, Seaman HE, Taylor-Phillips S, Parsons N, et al. FIT for the future: a case for risk-based colorectal cancer screening using the faecal immunochemical test. Color Dis. 2016;18:650–3.

    Article  CAS  Google Scholar 

  11. Schreuders EH, Grobbee EJ, Spaander MCW, Kuipers EJ. Advances in fecal tests for colorectal cancer screening. Curr Treat Options Gastroenterol. 2016;14:152–62.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Cooper JA, Parsons N, Stinton C, Mathews C, Smith S, Halloran SP, et al. Risk-adjusted colorectal cancer screening using the FIT and routine screening data: development of a risk prediction model. Br J Cancer. 2018;118:285–93.

    Article  PubMed  Google Scholar 

  13. Rasmussen M, Andersen ABT, Njor SH, Andersen VD. Danish colorectal cancer screening database, annual report 2017 National Prevalence Screening Round [Danish] [Internet]. København/Århus; 2018 [cited 2019 Jan 15]. Available from: https://www.sundhed.dk/content/cms/45/61245_dts_årsrapport-2017_final.pdf.

  14. Larsen MB, Mikkelsen E, Rasmussen M, Friis-Hansen L, Ovesen A, Rahr HB, et al. Sociodemographic characteristics of nonparticipants in the Danish colorectal cancer screening program: a nationwide cross-sectional study. Clin Epidemiol. 2017;9:345–54.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Nielsen KT. Danish Colorectal Cancer Group’s national guidelines for diagnostics and treatment of colorectal cancer - screening [Danish] [Internet]. [cited 2018 Jun 13]. Available from: https://dccg.dk/wp-content/uploads/2017/08/2014_screening.pdf.

  16. Thomsen MK, Njor SH, Rasmussen M, Linnemann D, Andersen B, Baatrup G, et al. Validity of data in the Danish colorectal cancer screening database. Clin Epidemiol. 2017;9:105.

  17. Ingeholm P, Gögenür I, Iversen L. Danish colorectal cancer group database. Clin Epidemiol. 2016;8:465–8.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Schmidt M, Pedersen L, Sørensen HT. The Danish Civil Registration System as a tool in epidemiology. Eur J Epidemiol. 2014;29:541–9.

    Article  PubMed  Google Scholar 

  19. Danish Colorectal Cancer Screening Database, Annual report 2016 The first 34 months of the first national screening round [Danish] [Internet]. [cited 2020 Jan 4]. Available from: https://www.sundhed.dk/content/cms/45/61245_dtsårsrapport-2016_offentlig-version.pdf.

  20. Fraser CG, Allison JE, Halloran SP, Young GP. A proposal to standardize reporting units for fecal immunochemical tests for hemoglobin. JNCI J Natl Cancer Inst. 2012;104:810–4.

    Article  CAS  PubMed  Google Scholar 

  21. Gies A, Cuk K, Schrotz-King P, Brenner H. Direct comparison of ten quantitative fecal immunochemical tests for hemoglobin stability in colorectal cancer screening. Clin Transl Gastroenterol. 2018;9:e168.

    Article  Google Scholar 

  22. Moons KGM, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: what, why, and how? BMJ. 2009;338:b375.

    Article  PubMed  Google Scholar 

  23. Royston P, Moons KGM, Altman DG, Vergouwe Y. Prognosis and prognostic research: developing a prognostic model. BMJ. 2009;338:b604.

    Article  PubMed  Google Scholar 

  24. Altman DG, Vergouwe Y, Royston P, Moons KGM. Prognosis and prognostic research: validating a prognostic model. BMJ. 2009;338:b605.

    Article  PubMed  Google Scholar 

  25. Collins GS, Reitsma JB, Altman DG, Moons K. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMC Med. 2015;13:1.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Steyerberg EW, Vergouwe Y. Towards better clinical prediction models: seven steps for development and an ABCD for validation. Eur Heart J. 2014;35:1925–31.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, Obuchowski N, et al. Assessing the performance of prediction models: a framework for some traditional and novel measures. Epidemiology. 2010;21:128–38.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Fraser CG, Allison JE, Young GP, Halloran SP, Seaman HE. Improving the reporting of evaluations of faecal immunochemical tests for haemoglobin: the Fitter standard and checklist. Eur J Cancer Prev Eur J Cancer Prev. 2015;24:24–6.

    Article  PubMed  Google Scholar 

  29. Collins GS, Groot JA, de, Dutton S, Omar O, Shanyinde M, Tajar A, et al. External validation of multivariable prediction models: a systematic review of methodological conduct and reporting. BMC Med Res Methodol. 2014;14:40.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Stegeman I, Wijkerslooth TR, de Stoop EM, Leerdam ME, van, Dekker E, Ballegooijen Mvan, et al. Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy. Gut. 2014;63:466–71.

    Article  PubMed  Google Scholar 

  31. Usher-Smith JA, Walter FM, Emery JD, Win AK, Griffin SJ. Risk prediction models for colorectal cancer: a systematic review. Cancer Prev Res. 2016;9:13–26.

  32. Kortlever TL, Vlugt M, van der, Dekker E, Bossuyt PMM. Individualized faecal immunochemical test cut-off based on age and sex in colorectal cancer screening. Prev Med Rep. 2021;23:101447.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Roos VH, Kallenberg FGJ, Vlugt M, van der, Bongers EJC, Aalfs CM, Bossuyt PMM, et al. Addition of an online, validated family history questionnaire to the Dutch FIT-based screening programme did not improve its diagnostic yield. Br J Cancer. 2020;122:1865–71.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Cooper JA, Ryan R, Parsons N, Stinton C, Marshall T, Taylor-Phillips S. The use of electronic healthcare records for colorectal cancer screening referral decisions and risk prediction model development. BMC Gastroenterol. 2020;20:1–16.

    Article  Google Scholar 

  35. Duran-Sanchon S, Moreno L, Gómez-Matas J, Augé JM, Serra-Burriel M, Cuatrecasas M, et al. Fecal microRNA-based algorithm increases effectiveness of fecal immunochemical test-based screening for colorectal cancer. Clin Gastroenterol Hepatol. 2021;19:323–330.e1.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We wish to thank Research Professor A. Cecile J.W. Janssens, Department of Epidemiology, Emory University, for initial advice and discussions on the conduct of prediction studies. We also thank colleagues Anne-Sofie Dam Laursen, Mette Lauge Kristensen and Carl Felix Jan Wittstrom for their valuable input on the presentation of results. Data on screening participants were kindly provided by the Danish Colorectal Cancer Screening database.

Funding

The study received funding from the Danish Cancer Society, Danish Health foundation, King Christian X Foundation, Inge and Jørgen Larsens Memorial Trust and, Else and Mogens Wedell-Wedellsborgs Foundation.

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Authors and Affiliations

Authors

Contributions

The idea for the study was developed by MKT and further specified by MKT and EMM. MKT, RE, LP, HTS, TLL and EMM designed the study and protocol. MKT conducted the statistical analysis and LP and EMM were involved in developing the methodology. MKT and EMM drafted the manuscript. All authors contributed to the manuscript through critical revision of drafts and approved the final manuscript.

Corresponding author

Correspondence to Mette Kielsholm Thomsen.

Ethics declarations

Competing interests

The authors declare no competing interests. Department of Clinical Epidemiology, Aarhus University, is involved in studies with institutional funding from regulators and from various pharmaceutical companies, as research grants to and administered by Aarhus University. None of these studies is related to this study.

Ethics approval and consent to participate

The registry data used in this study was made available to us in an anonymized form at the servers of Statistics Denmark. The study was included in the Danish Data Protection Agency data approval administered by Aarhus University (j. no. 2016-051-000001, 1193). Studies using registry data in Denmark do not require specific consent and does not require approval by a research ethics committee.

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Thomsen, M.K., Pedersen, L., Erichsen, R. et al. Risk-stratified selection to colonoscopy in FIT colorectal cancer screening: development and temporal validation of a prediction model. Br J Cancer 126, 1229–1235 (2022). https://doi.org/10.1038/s41416-022-01709-6

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