Predictive value of red cell distribution width for SF3B1 mutation status in myelodysplastic neoplasms
Bibliographic record
Abstract
Abstract Background: yelodysplastic neoplasms (MDS) with SF3B1-mutations represent a distinct subtype associated with ring sideroblasts, preserved platelet counts, and overall favourable outcomes. These mutations have diagnostic, prognostic, and therapeutic relevance. Given the association between SF3B1 mutations, mitochondrial iron overload, and ineffective erythropoiesis, we explored whether red cell distribution width (RDW), a parameter routinely measured on the complete blood count (CBC), could help predict SF3B1 mutation status in patients with MDS. Methods: We retrospectively reviewed all adults diagnosed with MDS at a tertiary care centre in Southwestern Ontario, Canada between January 2018 and December 2019. All patients who had SF3B1 mutation testing by next-generation sequencing (Oncomine Myeloid Research Assay, ThermoFisher Scientific, Waltham, MA) and available pre-transfusion CBC data were included. We compared RDW, platelet counts, and other routine hematologic parameters between SF3B1-mutated and wild-type groups. The ability of RDW to discriminate between SF3B1-mutated and wild-type cases was evaluated using receiver operating characteristic (ROC) curves. Results: Among 165 patients with MDS meeting inclusion criteria, 21 (12.7%) had SF3B1 mutations. RDW was higher in the SF3B1-mutated group (19.4% vs. 17.5%; p = 0.056) but demonstrated only modest discrimination (AUC 0.632). A cut-off of 18.6% yielded 65% sensitivity and 67% specificity. Platelet count was significantly higher in SF3B1-mutated cases (mean 293.5 × 10⁹/L vs. 129.8 × 10⁹/L; p < 0.001), with better discrimination (AUC 0.844). A threshold of 156 × 10⁹/L provided 95% sensitivity and 75% specificity. Conclusion: RDW showed a trend toward association with SF3B1 mutations in patients with MDS but on its own lacked sufficient accuracy as a predictor of mutation status. Platelet count performed better and may serve as a useful screening tool to prioritize molecular testing, especially in settings with limited access to costly next-generation sequencing panels. Although RDW showed limited discriminatory ability in this study, these findings highlight the potential utility of other routine CBC parameters as cost-effective, accessible tools to guide genomic investigation in MDS, warranting evaluation in larger cohorts.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".