Interval cancer risk after the upper age limit of screening has been reached: Informing risk stratification in FIT‐based colorectal cancer screening

Abstract

Upper age limits are currently fixed for all fecal immunochemical test (FIT)‐based colorectal cancer (CRC) screening programs. A risk‐stratified upper age limit may be beneficial. Therefore, we assessed differences in interval CRC risk among individuals who had reached the upper age limit of screening (75 years). Individuals with a negative FIT (<47 μg Hb/g feces) in the final round of the Dutch CRC screening program were selected from the national screening database and linked to the national cancer registry to identify CRCs diagnosed within 24 months (interval CRCs). Survival analyses assessed whether sex and last fecal hemoglobin (f‐Hb) concentration were associated with interval CRC risk. A multivariable logistic regression assessed whether sex, last f‐Hb concentration and screening round were associated with stage distribution (early vs. late). Last f‐Hb concentrations were considered detectable when they were >0 μg Hb/g feces. Among 305,761 individuals with a complete follow‐up (24 months), 661 were diagnosed with interval CRC (21.6 per 10,000 negative FITs). Individuals with detectable f‐Hb (15%) were 5 times more likely to be diagnosed with interval CRC than those without (HR 4.87, 95%CI: 4.19–5.65). Moreover, their cancers were more often detected at a late stage compared to individuals without detectable f‐Hb (OR 1.45, 95%CI: 1.06–2.01). Our results show that interval CRC risk among individuals aged ≥75 differs substantially by last f‐Hb concentration, indicating a uniform age to stop screening is suboptimal. Future research, taking into account multiple screening rounds and FIT results, should determine the optimal risk‐stratified screening strategy.

What's new?

Using hemoglobin concentrations from prior negative fecal immunochemical tests has emerged as a promising approach for risk stratification in colorectal cancer screening. Most stratification efforts have however focused on the current screening target population. This study examined interval cancer risk among individuals with a negative FIT in their final screening round at age 75. Within this group, those with detectable fecal hemoglobin had a five‐time higher interval colorectal cancer risk and less favorable stage distribution compared to those without. These results suggest that establishing a risk‐stratified age limit for colorectal cancer screening based on prior fecal immunochemical test concentrations is worth considering.

1. INTRODUCTION

Colorectal cancer (CRC) screening programs have shown to be effective in reducing CRC incidence and mortality and have therefore been implemented worldwide. ¹ , ² , ³ , ⁴ , ⁵ Risk stratification offers opportunities for further optimization of screening programs by better balancing the harms and benefits of screening. Several potential strategies have already been suggested, of which those using information on age, sex and/or screening history are considered most feasible. ⁶

For fecal immunochemical test (FIT)‐based programs, risk stratification based on fecal hemoglobin (f‐Hb) concentrations of prior negative FITs appears to be a promising approach. ⁷ Multiple studies have shown that prior f‐Hb concentration is a strong predictor of advanced neoplasia (AN), ⁶ , ⁸ , ⁹ , ¹⁰ , ¹¹ , ¹² , ¹³ , ¹⁴ , ¹⁵ , ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ with f‐Hb concentrations below the FIT cut‐off being highly predictive. ¹³ , ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ Furthermore, prior f‐Hb concentrations have also been shown to be predictive of interval CRC. ⁸ , ²⁰

While risk stratification based on prior f‐Hb concentrations seems promising, ongoing trials mainly focus on personalizing screening approaches for the current target population of screening, that is, predefined age groups. ²¹ , ²² Screening beyond the upper age limit of screening might, however, be beneficial considering the increasing life expectancy of the population and CRC incidence increasing with age. ²³ , ²⁴ To this day, upper age limits are fixed for all organized screening programs. ⁶ The benefit of a personalized upper age limit, only targeting high risk groups, remains unclear.

The aim of this study was to assess the interval CRC risk in individuals who had reached the upper age limit of the Dutch CRC screening program, taking into account sex, prior f‐Hb concentration and number of screening rounds.

2. METHODS

2.1. Dutch CRC screening program

In the Netherlands, a nationwide FIT‐based CRC screening program has been gradually implemented since 2014. After the phased implementation, starting with older age groups, the entire target population (aged 55 through 75) was biennially invited from 2019 onwards. As the rollout of the program started 1 year later than initially planned, individuals aged 76 were one‐off invited in 2014.

After initially using a FIT cut‐off value of 15 μg Hb/g feces, the threshold was raised to 47 μg Hb/g feces mid‐2014, with only individuals with a positive FIT result (≥47 μg Hb/g feces) being referred for colonoscopy. Depending on the findings at colonoscopy, individuals are subsequently designated to colonoscopy surveillance or re‐invited to participate in FIT‐screening after 10 years (if still of eligible age). The screening program has currently reached a steady state with high participation rates and yield of screening, resulting in a decrease in overall and late‐stage CRC incidence. ⁵ , ²⁵ , ²⁶

2.2. Study population

Data of all individuals with a negative FIT (<47 μg Hb/g feces) in the final screening round of the screening program, after reaching the upper age limit, were collected from the Dutch national screening information system (ScreenIT). Individuals screened with a cut‐off value of 15 μg Hb/g feces were excluded from our analyses. Data were linked to the Netherlands Cancer Registry (NCR) to identify CRCs diagnosed within 24 months of the analysis date of the negative FIT (interval CRCs). The NCR had complete data available on cancers diagnosed up to June 2022. To ensure a follow‐up time of at least 6 months, individuals were only included when a negative FIT was analyzed before January 2022. Due to the phased implementation of the screening program, starting with older age groups, some individuals were only invited for the first time at the upper age limit of screening, while others had the opportunity to participate in more screening rounds. Repeat participation in follow‐up rounds was high, limiting data on interval CRCs (n = 14) among individuals with inconsistent participation. Therefore, those with inconsistent participation (n = 14.732) were excluded from the analysis.

2.3. Definitions

An interval CRC was defined as a CRC diagnosed within 24 months of the analysis date of a negative FIT (<47 μg Hb/g feces).

The last f‐Hb concentration was classified into undetectable f‐Hb (0 μg Hb/g feces) and detectable f‐Hb (>0 μg Hb/g feces), as prior research has shown that even values below the limit of detection (2.6 μg/g feces) are predictive of cancer risk. ¹⁶ Due to the limited number of interval CRCs in our population, further categorization was not possible.

The screening round indicates the number of times an individual participated in the screening program. Since only individuals with consistent participation patterns were included, these are consecutive rounds of screening (with a negative test result).

Stage distribution was determined using the Tumor, Node, Metastases (TNM) classification system effective at diagnosis (7th edition through 2016, 8th edition from 2017 onwards). A CRC was defined as an early‐stage cancer when detected at stage I or stage II and as a late‐stage cancer when detected at stage III or stage IV. ²⁷ , ²⁸

2.4. Statistical analyses

The primary outcome was interval CRC risk, calculated as the number of individuals diagnosed with interval CRC per 10,000 individuals with a negative FIT. Interval CRC risk was compared between subgroups (sex, last f‐Hb concentration, screening round) and tested for statistical significance using a Chi‐squared test. Calculated p values are two‐sided and considered statistically significant when <.05. Survival and multivariable logistic regression analyses examined whether sex, last f‐Hb concentration and screening round were associated with interval CRC and stage distribution, respectively. As Schoenfeld residuals showed non‐proportional hazards for screening round in the Cox model, a stratified Cox model was performed. By stratifying for screening round, we accounted for potential differences in baseline hazard functions across strata while estimating the effects of the other covariates that satisfied the proportional hazards assumption (sex and last f‐Hb concentration). Except for the survival analyses, analyses only included individuals with a complete follow‐up of 24 months after the negative FIT.

The first sensitivity analysis was performed using the limit of detection (2.6 μg Hb/g feces) instead of 0 μg Hb/g feces as the threshold for detectable f‐Hb. This limit is set by the manufacturer of the FIT (FOB‐Gold) and represents the lowest concentration of f‐Hb that can be detected with acceptable precision and accuracy. The second sensitivity analysis was performed including only participants with 0–20 μg Hb/g feces in their last FIT, to assess whether a FIT cut‐off of 20 μg Hb/g feces would result in similar results to a cut‐off of 47 μg Hb/g feces. The cut‐off of 20 μg Hb/g feces was chosen because this is the most commonly used cut‐off in CRC screening programs worldwide.

Statistical analyses were performed using R statistical software (v4.2.3; R Core Team 2022).

3. RESULTS

Our study population consisted of 400,656 individuals who received a negative FIT after their participation in the final round of the screening program, of which 305,761 (76.3%) had a complete follow‐up of 24 months. A total of 661 interval CRCs (0.22%) were identified within this group; 336 in men (50.8%) and 325 in women (49.2%) (Table 1). Most interval CRCs (83.2%) were detected in individuals who had participated only once. Of all individuals, 15.1% had detectable f‐Hb under the cut‐off level in their last screening round. Nearly half (46.0%) of all interval CRCs were detected within this group. The mean f‐Hb concentration was higher in those with an interval CRC (8.16 μg Hb/g feces) compared to those without an interval CRC (1.69 μg Hb/g feces) (p < .0001).

TABLE 1.

Characteristics of the study population, including interval CRC risk per subgroup. ^a

	Interval CRC diagnosis n (%)/median (IQR)	No interval CRC diagnosis n (%)/median (IQR)	Interval CRC risk n per 10000 negative FITs (95% CI)	p value b
Sex				.054
Male	336 (50.8)	143,456 (47.0)	23.4 (21.0–26.0)
Female	325 (49.2)	161,644 (53.0)	20.1 (18.0–22.4)
Age at last FIT	75 (75–75)	75 (75–75)	–
Screening round				.017
1	550 (83.2)	240,175 (78.7)	22.8 (21.0–24.8)
2	104 (15.7)	60,085 (19.7)	17.3 (14.3–20.9)
3	7 (1.1)	4840 (1.6)	14.4 (7.0–29.8)
Last f‐Hb concentration				<.001
0 μg Hb/g feces	357 (54.0)	259,238 (85.0)	13.8 (12.4–15.3)
>0 μg Hb/g feces	304 (46.0)	45,862 (15.0)	65.8 (58.9–73.6)
Cancer stage c
Stage I	135 (21.0)	–	–
Stage II	139 (21.6)	–	–
Stage III	217 (33.7)	–	–
Stage IV	153 (23.8)	–	–

Abbreviations: CI, confidence interval; CRC, colorectal cancer; f‐Hb, fecal hemoglobin; FIT, fecal immunochemical test.

^a Characteristics are only shown for individuals with a complete follow‐up (24 months) after their last FIT (n = 305,761).

^b p values for differences in interval CRC risk between subgroups, calculated with a chi‐squared test.

^c For 17 individuals, cancer stage was unknown.

Among those who participated for the first time at the upper age limit of screening, relatively more individuals had detectable f‐Hb in their negative FIT (17.1%) than among those who had previously participated (8.0%).

Within the group of individuals with detectable f‐Hb, 120 ICs (39.5%) were detected within 1 year after screening. This was similar in those without detectable f‐Hb, where 119 interval CRCs (33.3%) were detected within the first year.

3.1. Interval CRC risk

In our population, overall interval CRC risk was 21.6 per 10,000 individuals with a negative FIT (95% CI: 20.0–23.3). Interval CRC risk significantly decreased by screening round, ranging from 22.8 per 10,000 negative FITS after one screening round to 14.4 per 10,000 negative FITS after three screening rounds (p = .017) (Table 1). The largest difference in interval CRC risk was observed between individuals with and without detectable f‐Hb in their last screening round (65.8 vs. 13.8 per 1000 negative FITs, p < .001; Figure 1). There was no significant difference in interval CRC risk between men and women.

FIGURE 1.

Kaplan–Meier curve displaying interval colorectal cancer risk for individuals with and without detectable f‐Hb in their last screening round by time since negative FIT. FIT, fecal immunochemical test; Hb, hemoglobin.

The multivariable survival analysis also showed that individuals with detectable f‐Hb in their last screening round were more likely to be diagnosed with interval CRC compared to those without detectable f‐Hb (HR 4.87, 95%CI: 4.19–5.65) (Table 2). No differences were observed between men and women.

TABLE 2.

Cox regression analysis assessing differences in interval CRC risk by sex and last f‐Hb concentration. ^a

	Hazard ratio (95% CI)
Sex
Male	Ref
Female	0.90 (0.77–1.04)
Last f‐Hb concentration
0 μg Hb/g feces	Ref
>0 μg Hb/g feces	4.87 (4.19–5.65)

Abbreviations: CI, confidence interval; CRC, colorectal cancer; f‐Hb, fecal hemoglobin; Ref, reference.

^a Analysis was performed with data from individuals with a follow‐up of at least 6 months after their last FIT (n = 400,656). The model accounted for violations of the proportional hazards assumption for the screening round covariate by allowing each stratum to have a separate baseline hazard function while estimating the effect of sex and last f‐Hb concentration across strata.

3.2. Stage distribution

Of all interval CRCs, 370 (57.5%) were detected at a late stage. Interval CRCs were more likely to be diagnosed at a late stage for individuals who had detectable f‐Hb in their last screening round (62.5%) compared to those without detectable f‐Hb (53.0%) (OR 1.45, 95%CI: 1.06–2.01). Sex and screening round were not associated with stage distribution (Table 3).

TABLE 3.

Multivariable logistic regression with late‐stage (vs. early‐stage) interval CRC as outcome variable. ^a , ^b

	Late‐stage interval CRC (%) b	Odds ratio (95% CI)
Sex
Male	57.8	Ref
Female	57.1	0.99 (0.72–1.35)
Screening round
1	58.3	Ref
2 or 3	53.3	0.89 (0.58–1.37)
Last f‐Hb concentration
0 μg Hb/g feces	53.0	Ref
>0 μg Hb/g feces	62.5	1.45 (1.06–2.01)

Abbreviations: CI, confidence interval; CRC, colorectal cancer; f‐Hb, fecal hemoglobin; Ref, reference.

^a Analysis was performed using data from interval CRC‐diagnosed individuals with a complete follow‐up (24 months) and registered stage distribution (n = 644).

^b Late‐stage interval CRC: stage III or IV.

3.3. Sensitivity analyses

3.3.1. Different threshold detectable f‐Hb (2.6 μg Hb/g)

A total of 40.4% of interval CRCs were detected within the group of individuals with at least 2.6 μg Hb/g feces in their last negative FIT, which accounts for 11.1% of the total population. The sensitivity analysis showed similar results for the survival analysis, with individuals with detectable f‐Hb (≥2.6 μg Hb/g feces) being more likely to be diagnosed with interval CRC than those without (<2.6 μg Hb/g feces) (HR 5.49, 95% CI: 4.72–6.39). However, unlike the main analysis, no association was found between last f‐Hb concentration and stage distribution (Tables S1–S3).

3.3.2. Different FIT cut‐off (20 μg Hb/g)

Within the group of individuals with <20 μg Hb/g feces in their last FIT, the overall interval CRC risk was 18.3 per 10,000 individuals, which was slightly lower than in the main analysis. The interval CRC risk was higher for those with detectable f‐Hb compared to those without (50.5 vs. 13.8 per 10,000 individuals, p < .001). Both the survival and logistic regression analysis showed similar results to the main analysis. Individuals with detectable f‐Hb below 20 μg Hb/g feces were more likely to be diagnosed with an interval CRC compared to those without detectable f‐Hb (HR 3.71, 95% CI: 3.11–4.42). Besides, they were also more likely to be diagnosed with a late‐stage (vs. early‐stage) interval CRC (OR 1.67, 95% CI: 1.14–2.46) (Tables S4–S6).

4. DISCUSSION

This study evaluated interval CRC risk in individuals who had reached the upper age limit of screening. The risk of interval CRC was high, but varied widely within this group. Individuals with detectable f‐Hb had an almost 5 times higher interval CRC risk and a less favorable stage distribution than individuals without detectable f‐Hb in their last screening round.

Our findings show that individuals at an older age (i.e., ≥75 years old) still have a high interval CRC risk after their last participation in our nationwide FIT‐based CRC screening program: 21.6 per 10,000 negative FITs. Their risk is roughly twice as high as previously reported for the entire target population of screening, ⁸ , ²⁰ which is most likely due to the fact that CRC incidence substantially increases with age. ²⁴ While we were unable to obtain an adjusted interval risk by screening round due to non‐proportional hazards, the absolute interval CRC risk varied significantly by screening round. This suggests that the interval CRC risk decreases with repeated participation. This emphasizes the importance of repeated participation and indicates that overall interval CRC risk may decrease in future years as all individuals have had the opportunity to participate in multiple consecutive rounds of screening. The effect of consecutive screening may then compensate for the increased risk of CRC with age. However, interval CRC risk in our population also largely differed by prior f‐Hb concentration. Nearly half of all interval CRCs were detected within the group of participants with detectable f‐Hb in their last FIT (i.e., 15% of the total population). Interval CRC risk in this group was roughly 5 times higher than that for individuals without detectable f‐Hb, indicating that additional screening may be worthwhile for this high‐risk group.

The increased CRC risk for individuals with small concentrations of f‐Hb in their FIT has been established in recent years. Several studies reported higher CRC and AN risks for individuals with detectable f‐Hb below the FIT cut‐off than for individuals without detectable f‐Hb. ¹⁸ , ²⁹ , ³⁰ A similar association has been reported for interval CRC risk as well, showing a higher interval CRC risk for those with detectable f‐Hb. ⁸ , ³¹ However, all previous studies have assessed the associations between f‐Hb and CRC risk for the entire target population of CRC screening. Our findings expand upon this research by quantifying how this translates into differences in interval CRC risk among those who are no longer eligible for screening due to reaching the upper age limit, which will need to be considered as we move towards risk‐stratified CRC screening strategies in the future.

In addition to a higher interval CRC risk, individuals with detectable f‐Hb appear to have a less favorable stage distribution, which is associated with lower survival. ³² Accordingly, f‐Hb concentrations below the FIT cut‐off were previously associated with CRC‐related mortality. ³³ However, our sensitivity analysis showed no association between last f‐Hb concentration and stage distribution when using the limit of detection as a cut‐off for detectable f‐Hb (2.6 instead of 0 μg Hb/g feces). This could be explained by the fact that the stage distribution of interval CRCs in those with 0–2.6 μg Hb/g feces, now classified as having no detectable f‐Hb, may be more similar to that of those with 2.6–47 μg than to those with 0 μg Hb/g feces. This implies that variations in stage distribution persist even below the limit of detection. Although the power of our analysis may have been insufficient to demonstrate a significant difference, our sensitivity analysis also showed a smaller effect size. However, the precise relationship between f‐Hb levels and stage distribution remains inconclusive. Our sensitivity analysis revealed a higher effect size in the subgroup of individuals with f‐Hb levels below 20 μg Hb/g feces compared to those with levels below 47 μg Hb/g feces, which implies that higher f‐Hb levels are not associated with a worse stage distribution. A previous study showed a similar result, indicating that the FIT cut‐off has limited impact on the stage distribution of screen‐detected CRCs. ³⁴

A fixed upper age limit is currently the standard within organized CRC screening programs. ⁶ Our results clearly show that a personalized approach may be more effective. To illustrate, up to one‐fourth of interval CRCs in our population may have been prevented by offering additional screening to only 15% of the population (e.g., those with detectable f‐Hb) 1 year after their last screening round. Our sensitivity analysis demonstrated that differences in interval CRC risk were still evident if a (hypothetical) lower cut‐off (20 μg Hb/g feces) had been used in the last screening round. This suggests that our findings are not limited to the Dutch screening program, but can be applied to screening programs using other FIT cut‐offs. In particular a FIT cut‐off of 20 μg Hb/g feces, which is the most commonly used threshold internationally. Moreover, using prior f‐Hb values to identify those most at risk may be even more effective when quantitative FIT values from multiple prior screening rounds are combined. ⁸ , ¹⁸ , ³⁵ , ³⁶ Current initiatives for risk‐stratified CRC screening do not yet consider a risk‐stratified age to stop screening. ²¹ , ²² It may be challenging to identify an optimal screening approach that considers not only the benefits of additional screening, but also takes into account the harms involved in screening older individuals. The harm‐to‐benefit ratio of screening above age 75 is adversely impacted by the number of colonoscopy‐related serious adverse events that increases with age, hence most guidelines suggest that screening in elderly populations should be considered only for those with a life expectancy of at least 10 years. ³⁷ Thus, a risk‐stratified age to stop screening should ideally take into account an individual's life expectancy in addition to interval CRC risk.

However, it remains unclear whether assessing life expectancy is feasible within the logistics of a nationwide screening program. The Charlson Comorbidity Index (CCI) has been proven to predict 10‐year survival, ³⁸ but information required to determine CCI scores is currently not readily available for screening. Screening the elderly may therefore require an alternative design of screening programs, potentially by linking to electronic health records or by inviting elderly with an increased CRC risk to request a FIT by completing a CCI tool, with or without the help of a GP. In addition to CCI, self‐reported health has also been shown valuable in predicting mortality, indicating this tool might be valuable as well. ³⁹ Our analysis shows that it is well worth exploring these options in more detail in future research. Moreover, the potential of using a lower cut‐off in the final round of the screening program is also worthy of further investigation.

Strengths of our study include the use of NCR data, allowing determination of incidence and stage distribution of all interval CRCs diagnosed after negative FITs in the Dutch CRC screening program. The use of quantitative data on f‐Hb concentration offered valuable insights beyond the binary outcome of the FIT. However, our population did not include sufficient interval CRCs to consider f‐Hb values in a more granular way and explore variations in interval CRC risk in more detail. Another limitation of our study is the fact that death and migration data were not available and could therefore not be accounted for in the survival analyses. Individuals who died within 2 years after screening could be misclassified as having a complete follow‐up. The number of deaths may be higher in the group with detectable f‐Hb compared to the group without, resulting in a slightly underestimated HR. ³³ Furthermore, due to the phased implementation of the program, the majority of our population was only invited for the first time when already reaching the upper age limit of screening. It is therefore too early to draw conclusions for a fully mature screening program, where individuals will have the opportunity to participate in 11 rounds of screening. While the relative difference between those with and without f‐Hb concentration may still exist, the absolute risk of interval CRC may decrease after more rounds of screening. What absolute and relative risk is still acceptable should be discussed as more information becomes available in the coming years. Lastly, due to limited heterogeneity in screening behavior within our population, we were not able to assess the variety in interval CRC risk across different participation patterns. This area warrants further exploration as we move towards personalized screening approaches in the future.

In conclusion, our analysis shows that interval CRC risk after participation in the final round of the screening program differs substantially by prior f‐Hb concentration. A risk‐stratified age to stop screening, only offering additional screening to high‐risk groups, may therefore be beneficial. However, screening the elderly is not without harms. Future research should offer insight into CRC risk after participation in multiple screening rounds and assess the harm‐to‐benefit ratio of a risk‐stratified upper age limit in order to identify the optimal screening approach.

AUTHOR CONTRIBUTIONS

Brenda J. van Stigt: Conceptualization; methodology; writing – original draft; writing – review and editing; visualization; formal analysis. Iris Lansdorp‐Vogelaar: Conceptualization; methodology; writing – review and editing; supervision. Manon C. W. Spaander: Writing – review and editing; conceptualization. Anneke J. van Vuuren: Writing – review and editing; conceptualization. Evelien Dekker: Writing – review and editing; conceptualization. Folkert J. van Kemenade: Writing – review and editing; conceptualization. Iris D. Nagtegaal: Writing – review and editing; conceptualization. Monique E. van Leerdam: Writing – review and editing; conceptualization. Esther Toes‐Zoutendijk: Conceptualization; writing – review and editing; supervision; formal analysis; methodology.

FUNDING INFORMATION

This research was funded by the National Institute for Public Health and the Environment. The funder had no role in the data collection, statistical analyses, interpretation of the results and writing the manuscript.

CONFLICT OF INTEREST STATEMENT

MS: Received research support from Sentinel, Sysmex, Medtronic and Norgine. ED: Endoscopic equipment on loan of FujiFilm, and received a research grant from FujiFilm; Honoraria for consultancy from Olympus, Fujifilm, Ambu, InterVenn, Norgine, and Exact Sciences. PM Nykode & Almirall; Speakers' fees from Olympus, GI Supply, Norgine, IPSEN/Mayoly and FujiFilm.

All other authors declare no conflict of interest.

ETHICS STATEMENT

This study was conducted in accordance with the Dutch population screening act (WBO). Returning the FIT is considered as consent for using pseudonymized data of all screening reports, following the WBO. All individuals had the right to object to the use of their data. Within the Dutch CRC screening program, the number of individuals who object to the use of their data is very low (0.05%) and did thus not influence our results.

Supporting information

DATA S1. Supporting Information.

van Stigt BJ, Lansdorp‐Vogelaar I, Spaander MCW, et al. Interval cancer risk after the upper age limit of screening has been reached: Informing risk stratification in FIT‐based colorectal cancer screening. Int J Cancer. 2025;156(9):1783‐1790. doi: 10.1002/ijc.35294

DATA AVAILABILITY STATEMENT

Researchers had access to the data for the purpose of evaluating the national screening program. The data is owned by Bevolkingsonderzoek Nederland (BVO‐NL) and stored in the national screening database (ScreenIT). Researchers interested in accessing and analysing data ScreenIT may contact the data officer of BVO‐NL (wetenschappelijkonderzoek@bevolkingsonderzoeknederland.nl).