Karyotypic clonal fraction predicts adverse outcome in <i>TP53</i> -mutated myeloid neoplasms: an International <i>TP53</i> investigators Network (iTiN) study
Bibliographic record
Abstract
We investigated the prognostic impact of blast counts, TP53 allelic state determinants (number of hits, del(17p), variant allele frequency, complex karyotype),and a novel karyotypic clonal cell fraction (≤50% clonal cells vs >50% clonal cells (termed ‘CK50’)) in 495 individuals with TP53- mutated ( TP53 MUT ) myeloid neoplasms. Outcome examined was 24-month survival (OS24). The cohort (median age 71) included 29% (144/495) myelodysplastic syndromes (MDS)/MDS-acute myeloid leukaemia (AML) (1%–19% blasts) and 71% (351/495) AML (≥20% blasts), with 18% (81/460) having low CK50. Overall, 83% received front-line hypomethylating agents. Higher blast counts (<20% vs ≥20%) were marginally associated with CK50 (p=0.08). In the OS24 analysis, blast count showed a marginal association with OS24 (HR 1.3 (95% CI 1.0 to 1.6); p=0.07), while CK50 predicted significantly inferior outcomes (HR=1.7 (95% CI 1.2 to 2.3); p=0.002). In a multivariable model including all TP53 allelic state determinants, only CK50 and complex karyotype remained relevant for predicting adverse outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".