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Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy
  1. Inge Stegeman1,2,
  2. Thomas R de Wijkerslooth3,
  3. Esther M Stoop4,
  4. Monique E van Leerdam4,
  5. Evelien Dekker3,
  6. Marjolein van Ballegooijen5,
  7. Ernst J Kuipers4,6,
  8. Paul Fockens3,
  9. Roderik A Kraaijenhagen2,
  10. Patrick M Bossuyt1
  1. 1Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, The Netherlands
  2. 2Department of Research, NDDO Institute for Prevention and Early Diagnostics, Amsterdam, The Netherlands
  3. 3Department of Gastroenterology and Hepatology, Academic Medical Center, Amsterdam, The Netherlands
  4. 4Department of Gastroenterology and Hepatology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands
  5. 5Department of Public Health, Erasmus MC University Medical Centre, Rotterdam, The Netherlands
  6. 6Department of Internal Medicine, Erasmus MC University Medical Centre, Rotterdam, The Netherlands
  1. Correspondence to Inge Stegeman, Clinical Epidemiology, Biostatistics and Bioinformatics (room J1b-210-1), Academic Medical Center, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands; i.stegeman{at}


Objective Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could increase the sensitivity and diagnostic yield of FIT-based screening. We explored the use of a risk prediction model in CRC screening.

Design We collected data in the colonoscopy arm of the Colonoscopy or Colonography for Screening study, a multicentre screening trial. For this study 6600 randomly selected, asymptomatic men and women between 50 years and 75 years of age were invited to undergo colonoscopy. Screening participants were asked for one sample FIT (OC-sensor) and to complete a risk questionnaire prior to colonoscopy. Based on the questionnaire data and the FIT results, we developed a multivariable risk model with the following factors: total calcium intake, family history, age and FIT result. We evaluated goodness-of-fit, calibration and discrimination, and compared it with a model based on primary screening with FIT only.

Results Of the 1426 screening participants, 1112 (78%) completed the questionnaire and FIT. Of these, 101 (9.1%) had advanced neoplasia. The risk based model significantly increased the goodness-of-fit compared with a model based on FIT only (p<0.001). Discrimination improved significantly with the risk-based model (area under the receiver operating characteristic (ROC) curve: from 0.69 to 0.76, (p=0.02)). Calibration was good (Hosmer-Lemeshow test; p=0.94).

By offering colonoscopy to the 102 patients at highest risk, rather than to the 102 cases with a FIT result >50 ng/mL, 5 more cases of advanced neoplasia would be detected (net reclassification improvement 0.054, p=0.073).

Conclusions Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes.

  • Screening
  • Cancer Epidemiology
  • Cancer Prevention
  • Colorectal Cancer

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