This review evaluates stool- and blood-based colorectal cancer screening tests and explains how test performance, adherence, follow-up capacity, and equity should guide implementation.
Review Article
Non-Invasive Colorectal Cancer Screening Using Stool- and Blood-Based Tests: Evidence, Feasibility, and Equity Considerations
In This Article
Summary
Abstract
Colorectal cancer (CRC) remains a major cause of cancer incidence and mortality worldwide. Because colonoscopy is resource-intensive and participation is incomplete, non-invasive screening tests are central to population-level prevention. This review synthesizes recent evidence on fecal immunochemical testing (FIT), multi-omics stool DNA-FIT (mt-sDNA-FIT), multi-omics stool RNA-FIT (mt-sRNA-FIT), and blood-based assays, with emphasis on screening of asymptomatic individuals at average risk, the distinction between cancer detection and advanced precancerous lesion detection, and the operational requirements needed to translate test performance into public health benefit. FIT remains the most scalable first-line option in many programs because it is inexpensive, repeatable, and supported by evidence from organized screening. Its performance depends on hemoglobin threshold, sampling and handling, lesion biology, repeated adherence, and colonoscopy completion after a positive result. Molecular stool assays generally improve single-application sensitivity for CRC and advanced precancerous lesions but reduce specificity and increase costs and demand for colonoscopy. Blood-based assays may improve acceptability among people who decline stool testing or colonoscopy; however, current evidence indicates reduced detection of advanced precancerous lesions, limiting their preventive value when used as direct replacements for stool-based strategies. Implementation barriers occur across the screening pathway, including invitation, test access, sample return, laboratory processing, result communication, diagnostic colonoscopy, pathology, treatment access, and registry tracking. Future progress should prioritize risk-adapted screening, validated molecular and multiomics biomarkers, and artificial intelligence–assisted triage, and equitable program design. The most defensible strategy is not universal adoption of a single assay but a resource-stratified pathway that matches screening modality to population risk, patient acceptability, and system capacity.
Introduction
Colorectal cancer (CRC) is one of the most preventable major cancers because many cases develop through a detectable adenoma-carcinoma or serrated-neoplasia sequence over several years. Global cancer surveillance estimates indicate that more than 1.9 million new CRC cases and more than 900,000 CRC deaths occurred in 2022, placing CRC among the leading causes of cancer-related morbidity and mortality worldwide1. Projections suggest that the absolute burden will continue to rise because of population growth, population aging, lifestyle changes, obesity, dietary exposures, and unequal access to preventive services1,2. These trends are particularly important for health systems that have limited endoscopy capacity, fragmented primary care, or low participation in organized screening.
Screening is clinically valuable only when it functions as a complete pathway. A test must identify people with CRC or clinically important precursor lesions, communicate results effectively, and lead to timely diagnostic colonoscopy, histopathology, treatment, and longitudinal registry tracking. Colonoscopy remains the definitive diagnostic and therapeutic procedure because it can identify, biopsy, and remove many precursor lesions. Nevertheless, it is invasive, costly, dependent on trained personnel and high-quality bowel preparation, and less acceptable to some individuals. Consequently, population programs increasingly rely on non-invasive stool- or blood-based screening tests to increase reach, especially among average-risk adults who are not up to date with screening3,4,5.
This review focuses primarily on average-risk, asymptomatic population screening. Symptomatic diagnostic triage, post-polypectomy surveillance, and screening in hereditary or high-risk conditions are discussed only when needed to clarify interpretation. This distinction is essential because test performance and clinical implications differ across settings. A FIT threshold used to prioritize symptomatic patients for urgent colonoscopy cannot be interpreted in the same way as a repeated FIT strategy in an organized asymptomatic screening program. Similarly, a molecular assay evaluated in an average-risk cohort should not be generalized to surveillance populations unless the intended-use population has been separately validated3,6,7.
Non-invasive CRC screening technologies have expanded rapidly. FIT detects human hemoglobin in stool. Molecular stool tests combine fecal hemoglobin with DNA, RNA, methylation, or other neoplasia-associated signals. Blood-based assays evaluate circulating cell-free DNA, methylation patterns, fragmentomic features, or other tumor-derived signals. These platforms differ in biological targets, preanalytic vulnerabilities, cost, specificity, interval assumptions, and effects on the demand for colonoscopy. A scientifically useful comparison must therefore distinguish CRC detection from advanced precancerous lesion detection and evaluate both diagnostic accuracy and implementation feasibility8,9,10,11,12,13,14,15,16,17.
Review and Perspective
Evidence sources and review approach
A narrative evidence review was performed to summarize clinically relevant literature on validated and emerging non-invasive CRC screening tests. PubMed, Embase, Scopus, Web of Science, regulatory documents, major guideline statements, and high-impact review articles were consulted for literature published primarily from 2017 through June 2026, while seminal earlier studies were retained when they established pivotal evidence of diagnostic performance or provided guideline context. Search concepts included colorectal cancer screening, fecal immunochemical test, stool DNA, stool RNA, circulating tumor DNA, methylated SEPT9, cell-free DNA, blood-based screening, advanced adenoma, advanced precancerous lesion, adherence, colonoscopy follow-up, equity, cost-effectiveness, polygenic risk score, microbiome, multi-omics, and artificial intelligence. Figure 1 summarizes the screening pathway and interpretation framework used throughout this review. A modality-specific evidence framework is provided in Table 1.
The evidence was interpreted by study type rather than pooled across heterogeneous designs. Diagnostic accuracy studies, screening program evaluations, randomized screening invitation trials, cost-effectiveness models, adherence studies, regulatory summaries, and implementation reports address different questions. Accuracy studies describe test performance against colonoscopy or another reference standard; program studies estimate real-world effectiveness only when test completion and follow-up colonoscopy occur; economic models depend heavily on assumptions about interval, adherence, payer perspective, and colonoscopy costs. Because of this heterogeneity, the manuscript avoids pooled estimates and presents representative performance results only when they are tied to the specific assay, population, and reference standard5,13,18,19,20,21,22.
Studies in symptomatic diagnostic pathways were not combined with average-risk screening studies. Symptomatic cohorts have higher pretest probability, different referral thresholds, and different downstream consequences. Likewise, studies in high-risk or surveillance populations were treated separately because previous adenomas, inflammatory bowel disease, hereditary syndromes, or a strong family history change both baseline risk and acceptable follow-up strategy. The practical interpretation used throughout this review is that test performance must be linked to intended use, screening interval, adherence, and capacity for colonoscopy after a positive result.
Global burden and public health context
The public health rationale for CRC screening is strongest when the burden of preventable disease is high and when the screening pathway can be delivered reliably. Global Cancer Observatory estimates and global cancer reports show substantial CRC incidence and mortality across regions, but burden alone does not determine the best screening test. A high-burden country with limited colonoscopy capacity may obtain greater public health benefit from high-adherence FIT outreach than from an expensive molecular test that generates more positive results than the system can evaluate. Conversely, in settings where stool collection is a major barrier to participation and colonoscopy capacity is sufficient, offering additional validated options may increase screening completion3,4,5.
Program organization is as important as test selection. Data from global cancer-screening program repository indicate that cancer-screening program data are incomplete in many countries, particularly for pathway indicators such as invitation coverage, participation, positivity, diagnostic follow-up, and treatment linkage23. These gaps limit the ability to compare assay strategies across regions. Screening policy should therefore be based on pathway bottlenecks: identifying eligible adults, delivering the test, returning or processing the sample, communicating results, ensuring colonoscopy after a positive result, and tracking outcomes. Without these steps, even highly sensitive tests may not reduce CRC incidence or mortality.
Randomized and programmatic evidence reinforces the distinction between test efficacy and program effectiveness. The randomized colorectal cancer screening trial showed that invitation to repeated FIT screening achieved higher participation than invitation to one-time colonoscopy and was non-inferior for CRC mortality at 10 years in intention-to-screen analysis, whereas per-protocol findings favored completed colonoscopy5. Observational data from organized screening programs also associate FIT-based programs with reductions in CRC mortality and shifts toward earlier-stage disease24,25,26. These findings support FIT as a practical population strategy while also emphasizing that repeated participation and follow-up colonoscopy are indispensable.
Fecal immunochemical testing
FIT is the foundation of most scalable non-invasive CRC screening programs. It uses antibodies specific for human globin and therefore avoids dietary restrictions required by older guaiac-based fecal occult blood tests. FIT is inexpensive, can be mailed to participants, quantified, and repeated annually or biennially. Its major limitation is biological: bleeding from neoplastic lesions is intermittent, and advanced adenomas may bleed less consistently than established cancers. Consequently, FIT generally performs better for CRC than for advanced precancerous lesions8,9,26.
FIT performance varies for several reasons. First, positivity thresholds determine the balance between sensitivity and the demand for colonoscopy. Lower fecal hemoglobin cutoffs detect more disease but increase false positives and require more diagnostic colonoscopies. Higher thresholds preserve colonoscopy capacity but miss more lesions. Second, sample stability and handling affect the measured hemoglobin, especially when transport is delayed or when temperatures are high. Third, one-sample and two-sample strategies differ in positivity and detection. Fourth, lesion location, stage, sex, age, medication use, and baseline risk influence fecal hemoglobin concentration and, therefore, sensitivity8,9,10,26.
Analytically, FIT depends on the preservation of human globin in the collection buffer. Delayed return, heat exposure, inadequate sampling, and stool heterogeneity can reduce measurable hemoglobin, whereas non-neoplastic lower gastrointestinal bleeding can contribute to positive FIT results in the absence of CRC or advanced precancerous lesions. These limitations explain why thresholds, kit instructions, transport windows, and laboratory quality control are determinants of screening performance rather than minor technical details8,9.
The distinction between screening and symptomatic triage is central. In average-risk screening, FIT is a repeated population intervention designed to reduce future CRC incidence and mortality through early detection and removal of precursor lesions. In symptomatic pathways, FIT is a triage tool used to prioritize colonoscopy among patients with possible CRC symptoms. Guidelines for symptomatic FIT use define specific thresholds and referral actions, but those thresholds should not be transferred directly to asymptomatic screening programs7.
The effectiveness of FIT also depends on behavior and system design. Annual or biennial testing only prevents disease when individuals complete testing repeatedly and when positive results are followed by a colonoscopy. Failure to undergo colonoscopy after a positive FIT substantially increases the risk of death from CRC10. Effective FIT programs therefore, require accurate registries, mailed or in-clinic kit distribution, clear instructions, reminders, laboratory quality control, rapid reporting of results, navigation for abnormal results, and sufficient colonoscopy capacity. In lower-resource settings, calibrating the positivity threshold may be necessary to align detection with available endoscopy services rather than overwhelming the system.
FIT remains attractive for low- and middle-resource because it is comparatively inexpensive and operationally flexible. However, a low-cost test can still fail if the pathway lacks postal systems, laboratory infrastructure, electronic recall, patient navigation, or affordable colonoscopy. FIT should therefore be viewed not simply as a test but as a program component whose value depends on repeated adherence and diagnostic completion.
Multi-omics stool DNA-FIT, multitarget stool RNA–FIT, and other molecular stool assays
Molecular stool assays attempt to improve detection by measuring biomarkers shed by neoplastic cells into stool. The original mt-sDNA-FIT platform combined fecal hemoglobin with DNA methylation markers, KRAS mutations, and additional assay components. In its pivotal average-risk screening study, mt-sDNA-FIT achieved higher sensitivity than FIT for CRC and advanced precancerous lesions, although specificity was lower12. A next-generation mt-sDNA-FIT assay reported 93.9% sensitivity for CRC, 43.4% sensitivity for advanced precancerous lesions, and 90.6% specificity for advanced neoplasia in a large average-risk screening population; in the same study, FIT showed lower sensitivity for both CRC and advanced precancerous lesions at the evaluated threshold13.
Multitarget stool RNA–FIT assays represent another molecular strategy. In a large average-risk study, an mt-sRNA-FIT assay reported high sensitivity for stage I–III CRC and moderate sensitivity for advanced adenomas, with lower specificity than FIT14. RNA-based markers may capture active cellular processes and complement hemoglobin measurements, but they require careful stabilization, extraction, and assay reproducibility, as well as consideration of laboratory workflow. These requirements distinguish molecular stool assays from point-of-care or basic laboratory FIT and affect implementation in lower-resource settings.
For stool DNA- and RNA-based assays, the analytical challenge is not only marker selection but also preservation and recovery of tumor-derived material from a heterogeneous stool specimen. Neoplastic DNA or RNA is mixed with bacterial nucleic acid, digestive products, non-neoplastic epithelial DNA, and hemoglobin; marker degradation, heterogeneous shedding, variable extraction efficiency, and algorithmic thresholds can therefore influence positivity. False-positive findings may arise when hemoglobin or molecular signals reflect non-advanced lesions, benign bleeding, inflammatory change, background methylation, or analytical variation near the cutoff. Reproducible use requires standardized collection devices, stabilizing chemistry, extraction protocols, locked classifiers, laboratory quality control, and external validation rather than extrapolation from one platform to another12,13,14,15,16,17,21.
The central trade-off for molecular stool testing is that improved sensitivity is not automatically superior at the population level. Lower specificity increases the number of people referred for colonoscopy. In a high-resource setting, this may be acceptable if the system can provide a timely diagnostic evaluation. In a setting with limited endoscopy capacity, lower specificity can delay colonoscopy for people at the highest risk and increase opportunity costs. Cost-effectiveness, therefore, depends on screening interval, adherence assumptions, test price, colonoscopy cost, complication rates, prevalence, willingness-to-pay thresholds, and the health system's ability to manage positive results18,19,27.
Molecular stool tests are most appropriate when patients prefer non-invasive testing, when adherence to repeated FIT is poor, or when higher single-application sensitivity justifies the added cost and the demand for colonoscopy. They are less appropriate as universal first-line tests when budgets are limited, colonoscopy backlogs are substantial, or laboratory infrastructure is unavailable. Because assay platforms differ in biomarker composition, collection kits, algorithms, positivity thresholds, and interval recommendations, evidence should be interpreted assay-by- assay rather than generalized across all stool molecular tests12,13,14,21.
Blood-based assays
Blood-based CRC screening assays are attractive because blood collection can occur during routine clinical encounters and may be more acceptable to people who decline stool collection or colonoscopy. Current platforms evaluate cell-free DNA, methylation signals, tumor-derived genomic alterations, and fragmentomic features. The public health promise is increased participation among unscreened people; the principal concern is whether improved completion rates compensate for lower detection of advanced precancerous lesions22,28,29,30.
The prospective average-risk colorectal cancer screening study of a cell-free DNA-based blood test in an average-risk screening population reported 83.1% sensitivity for CRC, 89.6% specificity for advanced neoplasia, and 13.2% sensitivity for advanced precancerous lesions22. The FDA executive summary emphasizes that positive results require colonoscopy and that a negative blood test does not exclude CRC or advanced precancerous lesions28. These figures illustrate the key limitation: current blood tests can detect many established cancers but detect far fewer removable precancerous lesions than prevention-oriented stool molecular assays or colonoscopy.
The biological limitation of blood-based screening is most evident for advanced precancerous lesions. These lesions are usually smaller, often remain confined to the mucosa, and may shed very small quantities of altered DNA into plasma compared with invasive cancers. Any weak precursor-derived signal is diluted by abundant non-neoplastic cell-free DNA, and specificity-preserving thresholds may further reduce precursor sensitivity. Therefore, acceptable cancer sensitivity in a blood-based assay should not be interpreted as evidence of equivalent prevention potential, because prevention depends heavily on detecting and removing advanced precancerous lesions before invasion17,22,27,28,31.
Methylated SEPT9 and other plasma methylation approaches provided early proof of concept for blood-based CRC detection, but their performance on precancerous lesions and their screening impact have been limited29,30. Newer blood-based approaches may improve detection by combining methylation, cfDNA fragmentation, protein markers, and machine-learning classifiers. However, broad implementation should be based on prospective studies conducted in the intended-use population, longitudinal interval-cancer data, follow-up colonoscopy completion, and cost-effectiveness under realistic adherence assumptions18,19,31.
Blood-based assays should therefore be framed as adjuncts or alternatives for people who would otherwise remain unscreened, rather than direct replacements for FIT, mt-sDNA-FIT, mt-sRNA-FIT, or colonoscopy. Their most defensible role is in shared decision-making when patients decline or do not complete preferred stool-based or visual-examination options. As with stool tests, a positive blood test is not diagnostic; it must trigger a colonoscopy to complete the screening process3,4.
Equity and implementation across the screening pathway
Equity should be analyzed across the full screening pathway rather than described only by country income category. Barriers may occur during eligibility identification, invitation, health-literacy–appropriate communication, test delivery, stool-sample collection and return, access to phlebotomy, laboratory processing, result notification, follow-up colonoscopy, pathology, treatment, and surveillance. Each barrier has different solutions. Low invitation coverage may require registries and primary-care outreach. Low sample return may require simplified kits, reminders, community health workers, or navigation. Low colonoscopy completion may require transportation support, scheduling assistance, insurance coverage, and capacity planning10,23,32,33,34,35,36. Table 2 summarizes pathway barriers, supporting evidence types, and practical implications for test selection.
Regional and resource-level recommendations should follow bottleneck diagnosis. Where colonoscopy capacity is the limiting factor, high-specificity strategies, FIT threshold calibration, and risk stratification may be more important than maximizing single-test sensitivity. Where participation is the limiting factor, offering more acceptable tests, mailed outreach, culturally adapted messaging, and navigation may generate larger gains than changing the assay alone. Where laboratory capacity is the limiting factor, FIT may be more feasible than molecular stool or blood assays. Where treatment access is limited, screening expansion must be coordinated with oncology, surgery, pathology, and palliative care capacity.
Recent implementation studies illustrate the heterogeneity of barriers. Rural populations and younger adults may have lower FIT completion unless programs simplify distribution and return32. FIT-positive and population-based studies from Bahrain, Hainan, and Taiwan further show that demographic characteristics, fecal hemoglobin concentration, screening history, and program organization influence positivity, follow-up, and detection33,34,35. During health-system disruptions, such as the COVID-19 pandemic, completion of diagnostic colonoscopy after a positive non-invasive test may decline, threatening the effectiveness of screening even when test access remains available36.
Assay selection must also consider affordability and opportunity cost. A high-cost test may be clinically attractive for selected patients but can reduce total coverage if it consumes resources that could otherwise fund broader FIT outreach, colonoscopy capacity, or navigation. In contrast, a lower-cost test may be insufficient if participation remains low. The key equity question is therefore not which test has the highest single-application sensitivity, but which pathway produces the greatest number of completed, timely, and equitable screening episodes per available resource.
Future CRC screening will likely become more risk-adapted. Risk-adapted screening can combine age, sex, family history, prior screening history, lifestyle factors, fecal hemoglobin concentration, comorbidity, and polygenic risk scores (PRSs) to determine screening age, interval, test modality, and referral threshold. PRSs have shown potential to identify individuals whose CRC risk differs substantially from age-based averages in the general population, but implementation requires calibration across ancestry groups, transparent communication, privacy safeguards, and evidence that risk stratification improves outcomes rather than widening inequity37,38,39.
Microbiome and multi-omics approaches may improve non-invasive detection by integrating microbial species, microbial metabolites, host-derived methylation markers, RNA transcripts, proteins, and fecal hemoglobin. CRC-associated microbiome changes are detectable in stool and may help distinguish adenomas or early cancers from normal colonoscopy findings, but reproducibility across diet, geography, antibiotic exposure, sample processing, and sequencing pipelines remains a major challenge37,40,41. Multi-omics algorithms should be benchmarked against clinically meaningful endpoints, especially advanced precancerous lesions and interval cancers, rather than only established cancer.
Artificial intelligence may contribute at several points in the pathway. Prediction models could prioritize outreach, identify people unlikely to return kits, personalize reminders, interpret multivariable risk scores, or assist colonoscopy quality assurance. Early work using routinely available blood-count data and machine learning suggests that risk stratification may capture some CRC cases, but such models are not substitutes for validated screening tests and require prospective external validation before program deployment37,42. AI tools should be evaluated for calibration, bias, explainability, clinical utility, and effects on completed screening, not only discrimination metrics.
The most important evidence gaps are longitudinal and implementation-oriented. New tests should report not only cross-sectional sensitivity and specificity but also repeated-round adherence, interval cancer rates, detection of advanced precancerous lesions, demand for colonoscopy, false-positive burden, false-negative outcomes, patient acceptability, cost, equity effects, and feasibility in lower-resource settings. Comparative-effectiveness studies should model realistic adherence because a moderately sensitive test that many people complete may outperform a more sensitive test with poor uptake. Regulatory approval and market availability are not sufficient evidence of population-level benefit.
Conclusions
Non-invasive CRC screening should be evaluated by both biological performance and pathway feasibility. FIT remains the most scalable option in many organized programs because it is inexpensive, repeatable, and supported by evidence linking program participation to lower CRC mortality. Molecular stool tests improve single-application detection of CRC and advanced precancerous lesions, but their lower specificity, higher cost, and greater demand for colonoscopy must be weighed against local resources. Blood-based tests may expand participation among individuals who decline stool testing or colonoscopy, but current assays have limited sensitivity for advanced precancerous lesions and should be positioned as adjuncts or alternatives for otherwise unscreened people rather than direct replacements for more prevention-oriented strategies.
The most defensible implementation approach is a resource-stratified pathway. Programs should first identify the dominant bottleneck: low invitation coverage, poor test completion, insufficient laboratory processing, limited colonoscopy access, weak result communication, or inadequate treatment linkage. Test selection should then be matched to that bottleneck, the intended-use population, and the health system's ability to complete follow-up. Future evidence should prioritize validated risk-adapted pathways, diverse populations, transparent cost assumptions, and outcomes across the full screening continuum.
Figure 1: Framework for non-invasive colorectal cancer screening implementation. The figure summarizes how population eligibility, test choice, follow-up after a positive result, outcome tracking, biological performance, analytical limitations, system capacity, and equity jointly determine whether non-invasive screening yields a public health benefit. Please click here to view a larger version of this figure.
| Test category | Representative assay type | Intended population / use | Reference standard or evidence type | CRC detection evidence | Advanced precancerous lesion evidence | Specificity / false-positive considerations | Implementation interpretation | Representative references |
| FIT | Quantitative fecal hemoglobin immunoassay | Average-risk asymptomatic population screening; repeated annual or biennial use | Colonoscopy in accuracy studies; organized-program outcomes in population studies | Generally stronger for established CRC than for precursor lesions; varies by threshold, stage, location, sex, age, and repeated adherence | Limited and threshold-dependent; advanced adenomas may bleed intermittently | Higher thresholds reduce colonoscopy demand; lower thresholds increase sensitivity but increase positives | Most scalable first-line option when registry, kit distribution, laboratory processing, and colonoscopy follow-up are available | (3,4,6,8,9,10,24,25,26) |
| FIT in symptomatic triage | Quantitative FIT with referral threshold | Patients with symptoms or signs suggestive of CRC; not equivalent to population screening | Symptomatic diagnostic pathway guidelines and colonoscopy work-up | Useful to prioritize investigation when pretest probability differs from screening populations | Not designed as a stand-alone prevention test | Thresholds are chosen for triage and urgent referral, not population-level interval screening | Interpret separately from average-risk screening; do not pool with asymptomatic screening accuracy | 7 |
| Original mt-sDNA-FIT | Stool DNA markers plus fecal hemoglobin | Average-risk adults who prefer non-invasive stool-based screening | Pivotal colonoscopy-controlled average-risk study | Higher single-application CRC sensitivity than FIT in pivotal evidence | Higher advanced precancerous lesion sensitivity than FIT, but still incomplete | Lower specificity than FIT increases false positives and colonoscopy referrals | Useful when higher sensitivity and patient preference justify greater cost and colonoscopy demand | (12,19) |
| Next-generation mt-sDNA-FIT | Updated stool DNA/methylation marker panel plus FIT | Average-risk screening; assay-specific interpretation required | BLUE-C colonoscopy-controlled trial | Reported 93.9% CRC sensitivity in the evaluable population | Reported 43.4% sensitivity for advanced precancerous lesions | Specificity for advanced neoplasia reported as 90.6%; false positives remain important in low-prevalence screening | Promising improvement over FIT for single-application detection, but cost, interval, and colonoscopy capacity determine feasibility | (4,13,18,20,27) |
| mt-sRNA-FIT | Stool RNA transcripts plus FIT and algorithmic variables | Average-risk adults; intended as non-invasive stool molecular screening | CRC-PREVENT colonoscopy-controlled study | High sensitivity for stage I-III CRC in the pivotal study | Moderate sensitivity for advanced adenomas; higher than FIT in the same study | Specificity lower than FIT; requires laboratory RNA stabilization and processing | Useful as an emerging molecular stool option; long-term repeated-round adherence and interval-cancer data remain needed | (4,14) |
| Blood-based cfDNA assay | Cell-free DNA, methylation, and fragmentomic signals | Average-risk adults who decline or do not complete preferred stool/visual options | ECLIPSE trial and FDA/regulatory summaries | ECLIPSE reported 83% sensitivity for CRC | ECLIPSE reported 13% sensitivity for advanced precancerous lesions | Specificity for advanced neoplasia reported as 90%; positive results require colonoscopy | May increase participation among otherwise unscreened people but should not be framed as equivalent to prevention-oriented stool tests | (4,22,28) |
| Blood methylation assays | Methylated SEPT9 and other plasma methylation panels | Blood-based opportunistic screening or adjunctive detection | Prospective and validation studies with variable populations | Can detect a proportion of established CRC cases | Generally weak for advanced adenomas/precancerous lesions | False negatives for precursor lesions limit prevention impact | Better considered as adjuncts or alternatives when preferred tests are refused, pending stronger prevention endpoint evidence | (29,30,31) |
| Risk-adapted FIT pathways | FIT combined with questionnaire, prior screening, or risk score | Population programs that need to prioritize colonoscopy capacity | Population cohort and modeling evidence | May improve selection of participants for colonoscopy compared with FIT alone in some settings | Potential to improve advanced neoplasia yield when calibrated locally | Depends on model calibration and local prevalence | Useful where colonoscopy is the bottleneck; requires validation across demographic groups | (11,38,39) |
| Emerging multi-omics and AI models | Microbiome, metabolomics, methylation, fragmentomics, PRS, or AI-assisted risk models | Future screening and triage frameworks; not universal replacements for validated tests | Early validation studies, reviews, and risk-prediction cohorts | Potential to improve risk stratification or multimodal detection | Must be benchmarked against advanced precancerous lesion detection and interval cancers | High risk of overfitting, bias, and poor transportability without prospective validation | Should be evaluated by clinical utility, equity effects, and completed screening, not only discrimination metrics | (15,16,17,37,40,41,42) |
| Abbreviations: APL, advanced precancerous lesion; cfDNA, cell-free DNA; CRC, colorectal cancer; FIT, fecal immunochemical test; mt-sDNA, multitarget stool DNA; mt-sRNA, multitarget stool RNA; PRS, polygenic risk score. Values are representative assay- or study-specific findings and are not pooled estimates; citation numbers correspond to the manuscript reference list. | ||||||||
Table 1: Evidence framework for non-invasive stool- and blood-based colorectal cancer screening tests. The table summarizes test modality, biomarker target, intended population, reference standard, principal outcome, representative performance data, and implementation interpretation. Values are extracted from representative studies or regulatory summaries and are not pooled because the included evidence differs by assay, threshold, screening interval, and study population. Please click here to download this Table.
| Screening-pathway step | Common barrier | Resource or regional pattern | Evidence / data type | Practical mitigation | Interpretation for test choice | Representative references |
| Eligibility identification | No reliable registry of average-risk adults; unclear age/risk eligibility | Common in opportunistic or fragmented systems | Program reporting and CanScreen5-type indicators | Build registries, primary-care lists, and recall systems | No individual assay can compensate for failure to identify eligible people | 23 |
| Invitation and outreach | Low awareness, language barriers, fear, stigma, low perceived risk | Rural, underserved, younger adults, and minority populations | Implementation studies and community interventions | Culturally adapted invitations, reminders, navigation, community health workers | Acceptable test choices should be paired with outreach rather than offered passively | (32,33) |
| Test access | Cost, insurance coverage, pharmacy/clinic access, mailing logistics | Lower-resource settings and uninsured populations | Guideline and implementation evidence | Subsidized testing, mailed FIT kits, point-of-care distribution, integration into primary care | Low-cost FIT may outperform high-cost molecular tests when coverage is the main bottleneck | (3,4,6) |
| Sample collection or blood draw | Stool aversion, kit complexity, difficulty completing instructions, transport delays | Varies by age, culture, literacy, and rurality | Completion studies and assay-specific collection requirements | Simplified kits, illustrated instructions, multilingual materials, clinic-assisted workflows | Blood tests may help those refusing stool collection but have weaker precursor detection | (14,22,28,32) |
| Sample return and processing | Delayed return, high temperature exposure, postal unreliability, laboratory constraints | More important for FIT and molecular stool assays in hot or remote settings | Preanalytic and laboratory evidence | Stabilizing buffers, defined return windows, local collection points, laboratory quality control | Assay stability and infrastructure should influence test selection | (9,14,21) |
| Result communication | Positive results not understood; delayed notification; weak electronic systems | All resource settings, especially fragmented care | Program implementation evidence | Centralized reporting, patient navigation, electronic alerts, clear explanation of abnormal results | A positive non-invasive test is incomplete screening until colonoscopy occurs | (10,23,36) |
| Follow-up colonoscopy | Limited endoscopy capacity, wait times, costs, transport, fear of procedure | Major bottleneck in many LMICs and under-resourced high-income settings | Program studies and colonoscopy-completion evidence | Navigation, colonoscopy slots reserved for positive tests, threshold calibration, capacity planning | Lower-specificity tests may overload colonoscopy services if capacity is limited | (10,13,22) |
| Pathology and treatment linkage | Insufficient pathology, surgery, oncology, or surveillance services | Settings with limited cancer-care infrastructure | Public-health and health-system evidence | Coordinate screening expansion with diagnostic and treatment capacity | Screening scale-up should not exceed downstream diagnostic and treatment capacity | (1,2,23) |
| Registry tracking | Inability to track participation, positivity, follow-up, interval cancers, and outcomes | Common outside mature organized programs | CanScreen5 and program-quality indicators | Population registries, data linkage, audit dashboards | Program effectiveness cannot be demonstrated without outcome tracking | 23 |
| Affordability and opportunity cost | High molecular-test costs can reduce total population coverage | All systems with constrained budgets | Cost-effectiveness modeling and policy analysis | Budget-impact analysis, interval modeling, resource-stratified pathways | Choose the pathway producing the most completed equitable screening episodes per resource | (18,19,20,27) |
| Health-system disruption | Positive test follow-up interrupted by pandemic or service shocks | Observed during COVID-19 and other disruptions | Real-world adherence studies | Contingency plans, backlog tracking, prioritization of positive tests | Maintaining colonoscopy after positive tests is essential to preserve screening benefit | 36 |
| Abbreviations: CRC, colorectal cancer; FIT, fecal immunochemical test; LMICs, low- and middle-income countries. The table maps evidence-supported implementation barriers along the screening pathway; rows summarize evidence types and practical implications rather than pooled uptake estimates; citation numbers correspond to the manuscript reference list. | ||||||
Table 2: Implementation barriers and uptake evidence across screening pathways. The table maps barriers from invitation through follow-up colonoscopy and treatment linkage, distinguishes reported uptake and adherence data from settings in which values were not consistently reported, and summarizes practical implications for resource-stratified implementation. Please click here to download this Table.
Disclosures
The authors declare no competing interests.
Acknowledgements
Funding Statement: This work was supported by the Natural Science Foundation of Sichuan Province (grant number 2024NSFSC0718).
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