Multivariable models for advanced colorectal neoplasms in screen-eligible individuals at low-to-moderate risk of colorectal cancer: towards improving colonoscopy prioritization

Background

Advanced colorectal neoplasms (ACNs), including colorectal cancers (CRC) and high-risk adenomas (HRA), are detected in less than 20% of persons aged 50 years or older who undergo colonoscopy. We sought to derive personalized predictive models of risk of harbouring ACNs to improve colonoscopy wait times for high-risk patients and allocation of colonoscopy resources.

Methods

We characterized colonoscopy indications, neoplasia risk factors and colonoscopy findings through chart review for consecutive individuals aged 50 years or older who underwent outpatient colonoscopy at The Ottawa Hospital (Ottawa, Canada) between April 1, 2008 and March 31, 2012 for non-life threatening indications. We linked patients to population-level health administrative datasets to ascertain additional historical predictor variables and derive multivariable logistic regression models for risk of harboring ACNs at colonoscopy. We assessed model discriminatory capacity and calibration and the ability of the models to improve colonoscopy specificity while maintaining excellent sensitivity for ACN capture.

Results

We modelled 17 candidate predictors in 11,724 individuals who met eligibility criteria. The final CRC model comprised 8 variables and had a c-statistic value of 0.957 and a goodness-of-fit p-value of 0.527. Application of the models to our cohort permitted 100% sensitivity for identifying persons with CRC and > 90% sensitivity for identifying persons with HRA, while improving colonoscopy specificity for ACNs by 23.8%.

Conclusions

Our multivariable models show excellent discriminatory capacity for persons with ACNs and could significantly increase colonoscopy specificity without overly sacrificing sensitivity. If validated, these models could allow more efficient allocation of colonoscopy resources, potentially reducing wait times for those at higher risk while deferring unnecessary colonoscopies in low-risk individuals.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-01965-5.

Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics

Background

Colorectal cancer (CRC) is the 3rd leading cancer killer among men and women in the US. The Strategies and Opportunities to STOP Colon Cancer in Priority Populations (STOP CRC) project aimed to increase CRC screening among patients in Federally Qualified Health Centers (FQHCs) through a mailed fecal immunochemical test (FIT) outreach program. However, rates of completion of the follow-up colonoscopy following an abnormal FIT remain low. We developed a multivariable prediction model using data available in the electronic health record to assess the probability of patients obtaining a colonoscopy following an abnormal FIT test.

Methods

To assess the probability of obtaining a colonoscopy, we used Cox regression to develop a risk prediction model among a retrospective cohort of patients with an abnormal FIT result.

Results

Of 1596 patients with an abnormal FIT result, 556 (34.8%) had a recorded colonoscopy within 6 months. The model shows an adequate separation of patients across risk levels for non-adherence to follow-up colonoscopy (bootstrap-corrected C-statistic > 0.63). The refined model included 8 variables: age, race, insurance, GINI income inequality, long-term anticoagulant use, receipt of a flu vaccine in the past year, frequency of missed clinic appointments, and clinic site. The probability of obtaining a follow-up colonoscopy within 6 months varied across quintiles; patients in the lowest quintile had an estimated 18% chance, whereas patients in the top quintile had a greater than 55% chance of obtaining a follow-up colonoscopy.

Conclusions

Knowing who is unlikely to follow-up on an abnormal FIT test could help identify patients who need an early intervention aimed at completing a follow-up colonoscopy.

Trial registration

This trial was registered at ClinicalTrials.gov (NCT01742065) on December 5, 2012. The protocol is available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-020-05883-2.