Colorectal Cancer Screening within Colonoscopy Capacity Constraints: Can FIT-Based Programs Save More Lives by Trading off More Sensitive Test Cutoffs against Longer Screening Intervals?

Introduction. Colorectal cancer (CRC) prevention programs using fecal immunochemical testing (FIT) in screening rely on colonoscopy for secondary and surveillance testing. Colonoscopy capacity is an important constraint. Some European programs lack sufficient capacity to provide optimal screening intensity regarding age ranges, intervals, and FIT cutoffs. It is currently unclear how to optimize programs within colonoscopy capacity constraints. Design. Microsimulation modeling, using the MISCAN-Colon model, was used to determine if more effective CRC screening programs can be identified within constrained colonoscopy capacity. A total of 525 strategies were modeled and compared, varying 3 key screening parameters: screening intervals, age ranges, and FIT cutoffs, including previously unevaluated 4- and 5-year screening intervals (using a lifetime horizon and 100% adherence). Results were compared with the policy decisions taken in Ireland to provide CRC screening within available colonoscopy capacity. Outcomes estimated net costs, quality-adjusted life-years (QALYs), and required colonoscopies. The optimal strategies within finite colonoscopy capacity constraints were identified. Results. Combining a reduced FIT cutoff of 10 µg Hb/g, an extended screening interval of 4 y and an age range of 60–72 y requires 6% fewer colonoscopies, reduces net costs by 23% while preventing 15% more CRC deaths and saving 16% more QALYs relative to a strategy (FIT 40 µg Hb/g, 2-yearly, 60–70 year) approximating current policy. Conclusion. Previously overlooked longer screening intervals may optimize cancer prevention with finite colonoscopy capacity constraints. Changes could save lives, reduce costs, and relieve colonoscopy capacity pressures. These findings are relevant to CRC screening programs across Europe that employ FIT-based testing, which face colonoscopy capacity constraints.Health Research BoardHealth and Social Care Northern IrelandNational Cancer Institute Health Economics FellowshipNational Institutes of Health/National Cancer Institute Cancer CenterCancer Intervention and Surveillance Modeling Network (CISNET

Bowel cancer registry data made whole: filling in the blanks through imputation in Northern Ireland

In healthcare, cost-effectiveness analysis (CEA) compares alternative strategies based on consequences and costs to allocate healthcare resources to benefit public health. CEA modelling assembles components of costs, quality of life utilities and survival analysis. Survival analysis can project the lifetime of a simulated individual based on available data, therefore survival data is vital within CEA.Supplementary data requested from the Northern Ireland Cancer Registry (NICR) obtained outputs published in the Pathway to a Cancer Diagnosis report [1] in NI, to inform colorectal cancer (CRC) natural history contained within a larger CEA model. The proportion of individuals diagnosed with CRC was presented based on the route, stage, sex and age, with the proportions of individuals alive after 3, 6 and 12 months. Missingness existed within the data to protect the patient’s identity. If &lt; 10 individuals were diagnosed with CRC based on a specified route, age group, stage and sex, the data were omitted. Also, if &lt; 3 individuals died 3/6/12 months after diagnosis, the data were omitted. Most missing data problems are solved by Rubin’s multiple imputation methods [2]. However, this approach can be biased towards missing not-at-random data compared to missing at/completely at-random data; thus, other approaches are required.Three approaches were developed to impute the missing values. The first approach randomly generated values based on why the data was initially omitted. The second and third approaches used the NICR’s publicly available 1 and 5-year net survival rates (NSRs) for CRC, categorised by age, sex and stage, however, did not incorporate the same routes found in [1]. The second approach considered the lowest NSRs based on route, stage and age. The third approach randomly generated values within the range of possible NSRs, using both the normal and uniform distributions. The 5-year NSRs from NICR were used to estimate the proportions of individuals after 5 years, to better inform and extend survival within the CEA model. After comparing all imputation approaches with the true NICR 1-year NSRs, the most appropriate choice was the third approach, using the normal distribution. Using this approach, we can illustrate the lifetime of an individual within the CEA model and produce more plausible results.Reference:1.Bannon F, Harbinson A, Mayock M, McKenna H. Pathways to a Cancer Diagnosis: Monitoring variation in the patient journey across Northern Ireland 2012 to 2016.2.Rubin DB. Multiple imputations in sample surveys - a phenomenological Bayesian approach to nonresponse. American Statistical Association. 1978;1:20–34.<br/

An observation simulation approach to colorectal cancer in Northern Ireland

Colorectal cancer (CRC) is the third most common cancer diagnosed worldwide [1]. In 2020, approximately 1.9 million new CRC cases were reported, with over 930,000 deaths [2]. CRC develops from abnormal growths in the colon and rectum called polyps [3]. Most polyps are benign but can become malignant. In Northern Ireland (NI), there are an average of 1,216 cases per year, with the odds of developing CRC before the age of 85 is 1 in 12 for men and 1 in 18 for women [4]. Fortunately, CRC is preventable via screening. In 2010, the NI Bowel Cancer Screening Programme (BCSP) was introduced and currently invites 60-74 years olds to participate in screening using a stool-based diagnostic test, the Faecal Immunochemical Test (FIT), with a positivity threshold of 120mg/Hb [5]. The government aim to improve the programme by extending the age range to include 50-year-olds [6]. A cost-effectiveness analysis is needed, a tool used to measure the value for money and evaluate the best strategy for the programme. This presentation will focus on the model build of the natural history component of a cost-effectiveness model built using NI-specific estimates. A discrete event simulation model has been developed, divided into a natural history, no screening and screening components. The natural history component models the progression of polyps for the NI population, simulating polyp onset to the progression of clinical cancer. No screening simulates the NI population during 2010-2023 for non-screen detected CRC cases and helps validate the model. The screening component simulates the programme for 2010-2023 to replicate real-world screening incidences and models from 2024 onwards to implement the current programme along with other potential strategies under consideration. Two million individuals have been simulated to represent the NI population in 2010 using 2011 Census data taken from the Office for National Statistics [7]. Firstly, the age of non-CRC death was modelled using a Gompertz distribution and lifetables data from the NI Statistics and Research Agency [8]. Using the NI Cancer Registry [4], specifically the Colorectal Polyp Register, polyp incidence was used to simulate those at risk of developing polyps in their lifetime. Using the same data, a Poisson regression model simulated the number of polyps for each person. The proportion of malignant polyps and the polyp location in the bowel were simulated using NI literature. The Weibull distribution using polyp register data simulated the age of polyp onset. For those at risk of developing cancer, preclinical CRC stages I-IV, followed by the stage and age of CRC clinical diagnosis were calibrated using CRC data. References [1]. International Agency for Research on Cancer. Cancer Today. 2020. URL: https://gco.iarc.fr/today/home [2]. World Health Organisation (WHO). Colorectal Cancer, Key facts. 2023. URL: https://www.who.int/news-room/fact-sheets/detail/colorectal-cancer [3]. WebMD. Understanding Colorectal Cancer- The Basics. URL: www.webmd.com/colorectal-cancer/understanding-colorectal-cancer-basics [4]. Northern Ireland Cancer Registry (NICR). Colorectal cancer report. 2023. URL: https://www.qub.ac.uk/research-centres/nicr/CancerInformation/official-statistics/BySite/Colorectalc ancer/15 [5]. NI Bowel Cancer Screening Programme (NI BCSP). 2023. URL: https://cancerscreening.hscni.net/bowel-screening/overview/ [6]. BBC Newsline. Bowel cancer: Call for earlier screening to find tumours. 2023. URL: https://www.bbc.co.uk/news/uk-northern-ireland-67099153 [7]. Office for National Statistics (ONS). National life tables: Northern Ireland. 2021. URL:https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/lifeexpecta ncies/datasets/nationallifetablesnorthernirelandreferencetables [8]. Northern Ireland Research and Statistics Agency (NISRA). “Census 2021 main statistics demography tables– age and sex”. 2022. Available: https://www.nisra.gov.uk/publications/census-2021-main-statistics-demography-tables-age-and-se