Lowering the colorectal cancer screening age improves predicted outcomes in a microsimulation model

Abstract

Aims

While most guidelines still recommend colorectal cancer (CRC) screening initiation at age 50 years in average-risk individuals, guideline-creating bodies are starting to lower the recommended age of initiation to 45 years to mitigate the trend of increasing CRC rates in younger populations. Using CRC-AIM, we modeled the impact of lowering the CRC screening initiation age, incorporating theoretical and reported adherence rates, for triennial multi-target stool DNA (mt-sDNA) or annual fecal immunochemical test (FIT) screening.

Methods and Materials

Screening strategies were simulated for individuals without CRC at age 40 and screened from ages 50 to 75 or 45 to 75 years. Outcomes included CRC incidence, CRC mortality, and life-years gained (LYG) per 1000 individuals screened (compared with no screening). Models used theoretically perfect (100%) and previously reported (71% mt-sDNA; 43% FIT) adherence rates.

Results

With perfect adherence, mt-sDNA and FIT resulted in 22.2 and 23.4 more predicted LYG, respectively, with screening initiation at age 45 versus 50 years; reported adherence resulted in 23.9 and 24.4 more LYG, respectively. With perfect adherence, screening initiation at age 45 versus 50 years resulted in 26.1 and 28.6 CRC cases, respectively, with mt-sDNA and 22.8 and 25.5 cases with FIT; with reported real-world adherence there were 28.5 and 31.2 cases, respectively, with mt-sDNA and 37.1 and 40.2 cases with FIT. Similar patterns were observed for CRC deaths. With screening initiation at age 45 and reported adherence, mt-sDNA averted 8.6 more CRC cases and 3.3 more deaths per 1000 individuals than FIT.

Conclusions

Estimated CRC screening outcomes improved by lowering the initiation age from 50 to 45 years. Incorporating reported adherence rates yields greater benefits from triennial mt-sDNA versus annual FIT screening.

Keywords:

• Adenoma
• adherence
• age
• colorectal cancer
• Medicare
• screening
• simulation model

Transparency

Declaration of funding

Financial support for this study was provided by a contract with Exact Sciences Corporation. https://www.exactsciences.com/

The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.

Declaration of financial/other relationships

DAF is a consultant for Exact Sciences and Guardant Health. LS, DB and ABO are employees of Exact Sciences Corporation. LJFR is a consultant for Exact Sciences Corporation through a contractual agreement between Mayo Clinic and Exact Sciences Corporation. PJL serves as Chief Medical Officer for Screening at Exact Sciences through a contracted services agreement with Mayo Clinic. PL and the Mayo Clinic have contractual rights to receive royalties through this agreement. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

DAF contributed to conceptualization of the study and to the review and editing of the manuscript. LS contributed to the methodology, data curation, formal analysis, investigation, software, and visualization of the study and to the review and editing of the manuscript. LJFR contributed to conceptualization of the study and to the review and editing of the manuscript. ABO contributed to the conceptualization, methodology, supervision, and visualization of the study and to the review and editing of the manuscript. PJL contributed to the conceptualization and methodology of the study and to the review and editing of the manuscript. DB contributed to the review and editing of the manuscript.

Acknowledgements

Medical writing and editorial assistance were provided by Erin P. Scott, PhD, of Maple Health Group, LLC, funded by Exact Sciences Corporation.

Data availability

CRC-AIM demonstrates the approach by which existing CRC models can be reproduced from publicly available information and provides a ready opportunity for interested researchers to leverage the model for future collaborative projects or further adaptation and testing. To promote transparency and credibility of this new model, we have made available CRC-AIM’s formulas and parameters on a public repository (https://github.com/CRCAIM/CRC-AIM-Public).

Previous presentations

These data were presented at the American College of Gastroenterology Annual Meeting, Virtual Meeting, 2020.