Diagnostic criteria for constitutional mismatch repair deficiency (CMMRD): recommendations from the international consensus working group
Bibliographic record
Abstract
Background Constitutional mismatch repair deficiency syndrome (CMMRD) is the most aggressive cancer predisposition syndrome associated with multiorgan cancers, often presenting in childhood. There is variability in age and presentation of cancers and benign manifestations mimicking neurofibromatosis type 1. Genetic testing may not be informative and is complicated by pseudogenes associated with the most commonly associated gene, PMS2 . To date, no diagnostic criteria exist. Since surveillance and immune-based therapies are available, establishing a CMMRD diagnosis is key to improve survival. Methods In order to establish a robust diagnostic path, a multidisciplinary international working group, with representation from the two largest consortia (International Replication Repair Deficiency (IRRD) consortium and European Consortium Care for CMMRD (C4CMMRD)), was formed to establish diagnostic criteria based on expertise, literature review and consensus. Results The working group established seven diagnostic criteria for the diagnosis of CMMRD, including four definitive criteria (strong evidence) and three likely diagnostic criteria (moderate evidence). All criteria warrant CMMRD surveillance. The criteria incorporate germline mismatch repair results, ancillary tests and clinical manifestation to determine a diagnosis. Hallmark cancers for CMMRD were defined by the working group after extensive literature review and consultation with the IRRD and C4CMMRD consortia. Conclusions This position paper summarises the evidence and rationale to provide specific guidelines for CMMRD diagnosis, which necessitates appropriate surveillance and treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.017 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".