Somatic co‐alteration signatures are prognostic in high‐grade <scp><i>TP53</i></scp>‐mutated myeloid neoplasms
Bibliographic record
Abstract
To assess the relevance of co-occurring somatic mutations in TP53-mutated myeloid neoplasms with ≥10% blasts, we pooled 325 individuals from 10 centres. We focused on comparing three published somatic co-alteration signatures comprising (1) nine MDS-related genes ('ICC-MDSR'), (2) ICC-MDSR + additional secondary mutations-related genes ('Tazi signature') and (3) EPI6 (comprising six genes). Outcomes examined were 24-month overall survival (OS24) and front-line complete response (CR1). The median age was 69 years with 77% receiving front-line hypomethylating agents (HMA). All three signatures ICC-MDSR (p = 0.009), Tazi signature (p = 0.001) and EPI6 (p = 0.025) predicted inferior CR1. In the low-intensity (HMA) subgroup, only Tazi signature (p = 0.026) predicted inferior CR1. In OS24 analysis of the HMA-treated subgroup (N = 200), only Tazi signature was adverse (hazard ratio, HR = 1.6 [1.1-2.2]; p = 0.011). However, a forward stepwise multivariable age-adjusted Cox model including all three signatures picked EPI6 as the sole significant adverse predictor in the entire cohort (p = 0.0001) as well as within the HMA-treated subgroup (p = 0.0071). These data confirm the value of testing co-occurring somatic alterations even within a high-grade TP53-mutated myeloid neoplasm cohort.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".