Effects of Autoimmune Disorders on Myelodysplastic Syndrome Outcomes: A Systematic Review
Bibliographic record
Abstract
Background: Autoimmune disorders (ADs) are prevalent among patients with myelodysplastic syndrome (MDS), yet their impact on MDS outcomes, including overall survival (OS), mortality, and transformation to acute myeloid leukemia (AML), is not well defined. Methods: We conducted a systematic review of articles published up to April 2024, sourced from PubMed, Web of Science, Embase, and Google Scholar, focusing on the influence of ADs on survival and AML transformation rates in MDS patients. The methodological quality of each study was assessed using the Newcastle Ottawa Scale. Results: From 8 studies that met the inclusion criteria, ADs were present in 17.5% (3074/17,481) of MDS patients. Data analysis indicated mortality rates ranging from 15.3% to 67% in MDS patients with ADs and 12% to 69% in those without. The rate of AML transformation varied from 0% to 23% in patients with ADs compared to 4% to 30% in those without. Conclusions: The influence of ADs on survival and AML transformation in MDS patients appears variable. This systematic review highlights the need for further large-scale prospective studies to clarify the relationship between ADs and MDS outcomes.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".