Familial myelodysplastic syndromes: a review of the literature
Bibliographic record
Abstract
Familial cases of myelodysplastic syndromes are rare, but are immensely valuable for the investigation of the molecular pathogenesis of myelodysplasia in general. The best-characterized familial myelodysplastic syndrome is that of familial platelet disorder with propensity to myeloid malignancy, caused by heterozygous germline RUNX1 mutations. Recently, there has been an increase in the number of reported cases, allowing for better understanding of the incidence, clinical features, and pathogenesis of this disorder. These recent cases have highlighted the clinical variability of the disorder and confirmed that many patients lack a bleeding and/or thrombocytopenia history. Additionally, several cases of T-acute lymphoblastic leukemia have now been reported, confirming a risk of lymphoid leukemia in patients with inherited RUNX1 mutations. Furthermore, an increased awareness of clinicians has helped detect a number of additional families affected by inherited myelodysplastic syndromes, resulting in the identification of novel causative mechanisms of disease, such as RUNX1 deficiency resulting from constitutional microdeletions of 21q22 and myelodysplasia-associated with telomerase deficiency. Awareness of predisposition to myelodysplastic syndromes and acute myeloid leukemia in families may be of critical importance in the management of younger patients with myelodysplasia in whom allogeneic hematopoietic stem cell transplantation is considered. Such families should be investigated for inherited deficiencies of RUNX1 and/or telomerase to prevent the use of an affected sibling as a donor for transplantation. Here we provide an update on familial platelet disorder in addition to a review of other known familial myelodysplastic syndromes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".