RARE-55. CHALLENGES AND SPECIFIC STRATEGIES FOR CONSTITUTIONAL MISMATCH REPAIR DEFICIENCY SYNDROME IN LOW RESOURCE SETTINGS. ON BEHALF OF THE INTERNATIONAL RRD CONSORTIUM IN LOW RESOURCE SETTINGS PANEL
Bibliographic record
Abstract
Abstract Germline biallelic mutations in one of the mismatch repair genes (MSH2/MSH6/MLH1/PMS2 results in constitutional mismatch repair deficiency (CMMRD), a condition associated with multiple tumors arising from multiple organs during childhood, and these individuals rarely reach adulthood. The paucity of information with respect to these conditions leads to mismanagement and may be a factor in the high mortality of patients with CMMRD. Two international consortia, the European CARE4CMMRD, and the international replication repair deficiency (RRD) consortium, are addressing the many challenges associated with this condition. To address specific issues surrounding the management of CMMRD in low and middle income countries (LMIC), a multidisciplinary taskforce of 11 specialists from nine countries was formed. Preliminary conclusions are: 1) Immunohistochemistry for CMMRD should be considered for all patients with suggestive clinical features. In countries where CMMRD is common, malignant gliomas, colon cancers and T cell lymphomas should be stained routinely as the prevalence of CMMRD in these tumors can exceed 40%. 2) Temozolomide should not be used in the management of malignant glioma. By contrast, preclinical studies have suggested increased sensitivity to nitrosoureas. For the management of CMMRD related lymphoma and leukemia, mercaptopurines should not be avoided or discontinued as a part of the standard of care before more data are collected. 3) Management with checkpoint inhibitors should be limited to centers with intensive care units and expertise in complex supportive care to manage side effects of immune therapy. 4) Surveillance protocols have demonstrated long term survival benefits and should be implemented in LMIC.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".