Multi-center real-world comparison of the fully automated Idylla™ microsatellite instability assay with routine molecular methods and immunohistochemistry on formalin-fixed paraffin-embedded tissue of colorectal cancer
Why this work is in the frame
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Bibliographic record
Abstract
Microsatellite instability (MSI) is present in 15-20% of primary colorectal cancers. MSI status is assessed to detect Lynch syndrome, guide adjuvant chemotherapy, determine prognosis, and use as a companion test for checkpoint blockade inhibitors. Traditionally, MSI status is determined by immunohistochemistry or molecular methods. The Idylla™ MSI Assay is a fully automated molecular method (including automated result interpretation), using seven novel MSI biomarkers (ACVR2A, BTBD7, DIDO1, MRE11, RYR3, SEC31A, SULF2) and not requiring matched normal tissue. In this real-world global study, 44 clinical centers performed Idylla™ testing on a total of 1301 archived colorectal cancer formalin-fixed, paraffin-embedded (FFPE) tissue sections and compared Idylla™ results against available results from routine diagnostic testing in those sites. MSI mutations detected with the Idylla™ MSI Assay were equally distributed over the seven biomarkers, and 84.48% of the MSI-high samples had ≥ 5 mutated biomarkers, while 98.25% of the microsatellite-stable samples had zero mutated biomarkers. The concordance level between the Idylla™ MSI Assay and immunohistochemistry was 96.39% (988/1025); 17/37 discordant samples were found to be concordant when a third method was used. Compared with routine molecular methods, the concordance level was 98.01% (789/805); third-method analysis found concordance for 8/16 discordant samples. The failure rate of the Idylla™ MSI Assay (0.23%; 3/1301) was lower than that of referenced immunohistochemistry (4.37%; 47/1075) or molecular assays (0.86%; 7/812). In conclusion, lower failure rates and high concordance levels were found between the Idylla™ MSI Assay and routine tests.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it