Evaluation of the performance characteristics of newer tests, particularly sensitivity and specificity, is crucial for understanding their effectiveness in detecting early-stage cancers and precancerous lesions.

Table 1 presents the sensitivity of each screening method for detecting CRC overall and at different stages, as well as advanced precancerous lesions (APL) and advanced adenomas (AA) with definitions that are not the same in all studies and publications. It is worth noting that most of the data was not retrieved from head-to-head studies.

Colonoscopy has long been considered the test with the highest sensitivity for CRC overall and is the benchmark against which other tests are compared, though the next-generation mt-sDNA test and the mt-sRNA test has been shown to have similar cancer sensitivity as colonoscopy (2). Stool-based tests offer varying levels of sensitivity for CRC and APL/AA, with multi-target stool DNA (mt-sDNA) and multi-target stool RNA (mt-sRNA) tests generally outperforming FIT, especially for early-stage cancers and advanced precancerous lesions (5–7). Both the mt-sDNA tests and the mt-sRNA test have proven to have higher sensitivity as compared to FIT in head-to-head pivotal trials (6, 7). mt-sDNA tests are more likely to detect sessile serrated lesions (so-called “flat lesions”) than FIT or mt-sRNA. As of March 2025, there is no head-to-head comparison between mt-sDNA and mt-sRNA. The performance for stool-based tests in terms of CRC sensitivity ranged from 74%–94%, while the performance for CRC sensitivity in blood-based test was 83% (8, 10). It is worth noting that recent publications have suggested wide variability in FIT performance depending on test used (15).

Specificity is generally high across all testing modalities, with most methods demonstrating specificity at or above 90% except for mt-sRNA and mt-DNA.

It's important to note that lower specificity may lead to more follow-up colonoscopies, which can impact healthcare resources and patient experience. However, the high specificity across all testing modalities suggests that false positives are relatively rare (4–14, 5% (6, 7, 16)), which is crucial for maintaining patient trust and minimizing unnecessary procedures.

The interval and adherence rates (Table 3) for different CRC screening methods vary significantly. Colonoscopy has the longest recommended interval at 10 years (18), with adherence rates of about 30% in real-world settings. Fecal immunochemical test (FIT) has an annual interval, with adherence rates of 35% without navigation and 41.5% in real-world and study settings. Cologuard, a multi-target stool DNA test, has a recommended interval of 3 years (with a range of 1–3 years), and shows adherence rates of 71.3% overall with commercial insurance at 72.3%, Medicare Advantage at 70.2%, Medicare at 69.9%, and Medicaid at 52% (19).

Cologuard Plus, the next-generation, will maintain a 3-year interval and is expected to mirror that of Cologuard, since ordering processes and patient experience will not change with study adherence reported at 71% (20). ColoSense, a multi-target stool RNA test, also has an anticipated 3-year interval and does not yet have real world adherence. It demonstrated an 78% adherence rate in study settings. The blood-based test, Shield, has an adherence of 96% based on real world clinical usage and integrating a blood-based test into CRC screening discussion leads to a twofold increase of the screening rates (21), with Shield’s interval to be determined (estimated 1–3 years) while PREEMPT CRC’s proposed at 3 years. It is worth noting that adherence rates for newer tests are often based on study data and may differ in real-world applications. A recent systematic literature review across 36 million patients undergoing routine USPSTF recommended blood-based screening tests, adherence rates ranged from 34%–68% indicating that outside of clinical trials, real-world adherence to recommended blood-based screening may be suboptimal (22).

Colonoscopy follow-up, access, and costs are critical factors in evaluating the effectiveness of CRC screening programs. According to the data presented in Table 4, follow-up colonoscopy rates vary significantly across different screening modalities. For FIT, follow-up rates range from 47% to 83%, highlighting the importance of robust tracking and reminder systems (33). Cologuard demonstrates higher follow-up rates of 71.5%–84.9% in real-world settings. While neither ColoSense nor Shield have conducted studies with endpoints that look at follow up colonoscopy adherence, ColoSense showed an 88% follow-up rate in study settings and Shield had a rate of 44% in a real world, claims analysis for individual with a colonoscopy within 6 months of the positive test (34, 35), emphasizing the need for improved follow-up strategies for blood-based tests.

Access to screening tests varies, with colonoscopy, FIT and Cologuard being widely available and covered by most insurance plans. Shield is available under the CRC screening National Coverage Determinations (NCDs). However, newer tests like ColoSense are not currently guideline-recommended but is FDA-approved to screen for CRC, advanced adenomas, and sessile serrated lesions, in average-risk individuals over the age of 45. Cost considerations play a significant role in screening implementation. Colonoscopy has the highest cost at an average cash price of $2,750, which may present a barrier for uninsured or underinsured individuals. FIT is the most affordable option, ranging from $18 to $21 with an estimation of $153 per screening cycle when including the patient support costs (37). Cologuard and ColoSense have a Medicare reimbursement rate of $508, and $592 for Cologuard Plus, positioning them as mid-range options that also have screening navigation programs built into the price of the tests. Further, there is no charge for Cologuard or ColoSense until resulted, meaning the manufacturers bear the burden of ensuring a kit’s return, which is not the case with most FIT kits. The announced cash price for Shield is $1,495, which may limit its accessibility without adequate insurance coverage. It is available with no out-pocket costs for patients eligible for Medicare Part B. There are other considerations as well. As newer tests enter the market, their cost and coverage will be crucial factors in determining their accessibility and impact on overall screening rates and health system resources.

Test performance is a key consideration in CRC screening. Colonoscopy, sometimes referred to as the gold standard, has high sensitivity (95%) for detecting CRC and advanced precancerous lesions. Stool-based tests show sensitivity for CRC detection at 79% (FIT), 92% (mt-sDNA) and up to 94% for ColoSense and Cologuard Plus, though lower sensitivity for advanced precancerous lesions (precancerous lesion performance is highly heterogeneous, and was not systematically assessed due to the lack of available data and should be interpreted with caution). Emerging blood-based tests, while promising, currently show similar sensitivity for advanced adenomas compared to stool-based tests (40). Test characteristics significantly impact patient preferences. Stool-based tests are often preferred over colonoscopy due to their non-invasive nature, convenience, and ability to be completed at home. A national survey found that 65.4% of respondents preferred mt-sDNA tests over colonoscopy, and 61% preferred FIT/gFOBT over colonoscopy (41). Handling stool samples may be a barrier for some patients, making blood-based tests a potential alternative for those patients who would not otherwise get screened, however the patients need to travel to a venipuncture site and some patients may fear needles. Test interval is another important characteristic, with patients generally preferring longer intervals between screenings (41).

Contextual factors such as travel distance, insurance coverage, health system test, geography, access availability of colonoscopy impact screening decisions. A study in rural Southern Illinois found that long-distance travel for care was normalized but not necessarily preferable for patients. Providers identified distance-related challenges specific to CRC screening, including transportation issues and the need for patients to take time off work (42). Insurance coverage also influences screening choices. Among adults aged 45–49 years, those with Medicare or Medicaid were more likely to prefer colonoscopy (62.8%) compared to those with private insurance (54.8%) or no insurance (46.7%) (41). Uninsured individuals are more likely to prefer stool-based tests over colonoscopy due to cost considerations.

Geographic location plays a role, with rural residents facing unique barriers to CRC screening. In rural Southern Illinois, providers reported that distance to care remains a significant challenge to increasing CRC screening and contributes to disparities in rural communities (42–44). They suggested various solutions to reduce distance and transportation barriers, such as mobile screening units and telemedicine options for pre-screening consultations.

Patient preferences are shaped by multiple factors. Convenience and ease of use are primary considerations, with many patients citing forgetfulness or procrastination as reasons for not completing stool-based tests (45, 46). A study on pharmacy-based CRC screening programs found that 93% of participants preferred completing the test at home, and 85% valued the ability to drop off the completed test at a convenient location. Perceived accuracy also influences choice, with some patients believing blood tests to be more accurate than stool tests, despite lacking information on actual test characteristics. In a qualitative study, patients were receptive about completing a blood test for CRC screening, citing simplicity, ease, convenience, and high perceived accuracy (47, 48). Cultural factors can impact screening preferences. A study focusing on Latino patients found varying levels of awareness about FIT testing, with some expressing doubts about its efficacy compared to colonoscopy (49). This underscores the need for culturally tailored education and outreach efforts.

Healthcare provider preferences are influenced by factors such as test accuracy, patient compliance, and system integration. A survey of 1,281 primary care providers found that 82.9% rated colonoscopy as very effective for patients aged 50-74, compared to 59.6% for FIT (50). Moreover, 26.3% rated colonoscopy as more effective than FIT, despite some modeling studies suggesting comparable effectiveness. Providers express concerns about patient adherence to different screening modalities. The same survey found that providers recommended colonoscopy every 10 years for 77.9% of patients aged 50-74, while 92.4% recommended FIT annually. System integration is crucial, with providers favoring options that are easy to implement within their healthcare systems. The ability to integrate screening programs with electronic health records and existing workflows is an important consideration for many healthcare organizations (51).

Education and communication play vital roles in test choice and screening adherence. Both patients and providers express a need for clear, comprehensive information about different screening options (52–54). A study on Latino patients’ perceptions of FIT testing found that awareness levels varied based on prior screening experiences, highlighting the need for targeted education efforts, especially for underserved populations (49). Providers may benefit from education about the comparative effectiveness of different screening modalities. The survey of primary care providers revealed discrepancies between provider perceptions and evidence from modeling studies regarding the effectiveness of FIT compared to colonoscopy (50). Addressing these knowledge gaps could influence provider recommendations and, subsequently, patient choices. Effective communication strategies and decision aids can help patients make informed choices aligned with their preferences and values. A study on older adults found that a targeted patient decision aid influenced screening preferences, particularly among those in poorer health states (55). This suggests that decision aids can be valuable tools for facilitating shared decision-making about CRC screening.

As technology advances, new screening options are emerging that may further influence test choices. Artificial intelligence (AI) is being explored to enhance the accuracy of existing screening methods. For instance, AI-assisted colonoscopy has shown promise in improving adenoma detection rates (56, 57). These emerging technologies may address some of the current barriers to screening, such as the invasiveness of colonoscopy or the discomfort associated with stool-based tests. However, their implementation will require careful consideration of factors such as cost-effectiveness, accessibility, and integration into existing healthcare systems (58, 59).

Policies that address barriers to screening, such as lack of insurance coverage or limited access to healthcare facilities, can significantly impact screening rates and test choices. For instance, the Affordable Care Act’s requirement for insurance plans to cover preventive services, including CRC screening, has been associated with increased screening rates (60).

The choice of CRC screening test is influenced by a complex interplay of factors related to test performance, characteristics, context, and stakeholder preferences. Understanding and addressing these multifaceted influences is key to optimizing CRC screening strategies and outcomes. Future efforts to increase screening rates should focus on addressing barriers related to access, education, and communication, while considering the diverse needs and preferences of different patient populations. As new technologies emerge and our understanding of CRC screening evolves, it will be crucial to continually reassess and adapt screening strategies. This may involve integrating new screening modalities, refining risk-stratification approaches, or developing more personalized screening recommendations based on individual risk factors and preferences through early detection and prevention. By carefully considering the various factors that influence screening test choices and working to optimize these choices for different populations and contexts, we can make significant strides towards this important public health goal.