Mismatch Repair and Microsatellite Instability Testing for Immune Checkpoint Inhibitor Therapy: Guideline From the College of American Pathologists in Collaboration With the Association for Molecular Pathology and Fight Colorectal Cancer
Why this work is in the frame
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Bibliographic record
Abstract
CONTEXT.—: The US Food and Drug Administration (FDA) approved immune checkpoint inhibitor therapy for patients with advanced solid tumors that have DNA mismatch repair defects or high levels of microsatellite instability; however, the FDA provided no guidance on which specific clinical assays should be used to determine mismatch repair status. OBJECTIVE.—: To develop an evidence-based guideline to identify the optimal clinical laboratory test to identify defects in DNA mismatch repair in patients with solid tumor malignancies who are being considered for immune checkpoint inhibitor therapy. DESIGN.—: The College of American Pathologists convened an expert panel to perform a systematic review of the literature and develop recommendations. Using the National Academy of Medicine-endorsed Grading of Recommendations Assessment, Development and Evaluation approach, the recommendations were derived from available evidence, strength of that evidence, open comment feedback, and expert panel consensus. Mismatch repair immunohistochemistry, microsatellite instability derived from both polymerase chain reaction and next-generation sequencing, and tumor mutation burden derived from large panel next-generation sequencing were within scope. RESULTS.—: Six recommendations and 3 good practice statements were developed. More evidence and evidence of higher quality were identified for colorectal cancer and other cancers of the gastrointestinal (GI) tract than for cancers arising outside the GI tract. CONCLUSIONS.—: An optimal assay depends on cancer type. For most cancer types outside of the GI tract and the endometrium, there was insufficient published evidence to recommend a specific clinical assay. Absent published evidence, immunohistochemistry is an acceptable approach readily available in most clinical laboratories.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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