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Fact check: How does the Cologuard test detect DNA in stool samples?
Executive Summary
The Cologuard multitarget stool DNA (mt-sDNA) test detects tumor-associated DNA and blood in stool by assaying for KRAS mutations, methylation of the NDRG4 and BMP3 gene promoters, and fecal hemoglobin, then combining those measures in a locked algorithm to generate a positive/negative result. Clinical evaluations published since 2014 report higher sensitivity for colorectal cancer and advanced precancerous lesions than fecal immunochemical testing (FIT) but trade that for lower positive predictive value and more false positives; these performance characteristics depend on study population and test thresholds [1] [2] [3].
1. How the test actually reads cancer signals out of stool — the biological toolkit that powers Cologuard
The Cologuard mt-sDNA assay targets three molecular signals shed into stool by colorectal neoplasia: point mutations in the KRAS oncogene, aberrant promoter methylation of tumor-suppressor–associated genes NDRG4 and BMP3, and occult blood as a marker of mucosal disruption. Laboratory processing isolates DNA from the stool specimen, performs mutation detection and quantitative methylation-specific assays, and measures hemoglobin immunochemically. Those raw analytic outputs are combined in a pre-specified mathematical algorithm to produce a single dichotomous result; the algorithm was locked before major trial analyses to avoid post hoc threshold tuning [1].
2. What peer-reviewed studies report about sensitivity and specificity — the tradeoffs revealed in trials
Prospective, colonoscopy-controlled screening studies and pooled analyses from 2014–2019 and later show elevated sensitivity for colorectal cancer and for advanced precancerous lesions compared with FIT, meaning the mt-sDNA catches more true cases in average-risk screening populations. Those studies consistently report lower specificity and a higher false-positive rate relative to FIT, producing more follow-up colonoscopies per cancer detected. The increased sensitivity was observed in large, screen-setting trials that informed regulatory and guideline discussions [2] [1].
3. Critical appraisals and real-world performance concerns — why some researchers urge caution
Retrospective reviews and some hospital-based evaluations have flagged that mt-sDNA’s positive predictive value (PPV) can be unacceptably low in certain settings, meaning many positive tests do not correspond to cancer or advanced adenomas on follow-up colonoscopy. These critiques emphasize spectrum effects: PPV depends strongly on disease prevalence and the population’s risk profile, so performance in selected clinical cohorts or lower-prevalence screening populations may differ substantially from trial results. This has fueled debate about appropriate screening contexts and patient counseling [3].
4. How the algorithm matters — locked formulas vs. single-marker thresholds
Developers and independent investigators stress that the mt-sDNA’s multiparameter algorithm improves sensitivity versus using any single marker cutoff. Premarket analyses compared a composite algorithm to single-marker strategies and found the integrated approach increased detection rates of neoplasia. The algorithm’s lock before analysis is presented as a methodological safeguard against overfitting, but algorithmic thresholds still determine the sensitivity-specificity balance and therefore clinical implications for downstream colonoscopy demand [1].
5. Practical implications for screening programs and patient counseling
In screening program planning, mt-sDNA’s higher sensitivity but lower specificity means programs must weigh increased detection against greater colonoscopy workload and false-positive anxiety. For an individual patient, a positive mt-sDNA mandates diagnostic colonoscopy; a negative test does not rule out all lesions because sensitivity, while higher than FIT, is imperfect. Choice between mt-sDNA and alternative noninvasive tests should account for adherence patterns, resource capacity for follow-up procedures, and population prevalence—factors that materially affect PPV and net benefit [2] [3].
6. Bottom line from the literature and where uncertainties remain
Evidence through at least 2024 supports that Cologuard’s mt-sDNA detects stool DNA by assaying KRAS mutations, NDRG4/BMP3 methylation, and hemoglobin and combining these in a locked algorithm, yielding higher sensitivity than FIT in many screening studies but lower specificity and variable PPV in real-world cohorts. Ongoing questions include long-term outcomes of mt-sDNA-based screening programs, cost-effectiveness across health systems, and optimal frequency and target populations—areas where study designs and prevalence differences drive variable conclusions in the literature [1] [4] [3].