Influence of <i>FLT3‐ITD</i> and <i>NPM1 </i>status on allogeneic hematopoietic cell transplant outcomes in patients with cytogenetically normal AML
Bibliographic record
Abstract
Abstract Objective In individuals with cytogenetically normal (CN) AML, disease risk is estimated using molecular features such as the status of NPM1 and FLT3‐ITD genes. However, data regarding the impact of NPM1 and FLT3‐ITD status on hematopoietic stem cell transplant (HCT) outcomes are limited. We examined the effect of NPM1 and FLT3‐ITD status on transplant outcomes in 131 CN AML patients transplanted at Princess Margaret Hospital between 2006 and 2017. Methods Overall survival (OS) was calculated using Kaplan‐Meier analysis and multivariable Cox proportional hazards regression. Cumulative incidence of relapse (CIR) and non‐relapse mortality (NRM) were calculated using competing risk regression. Results There was no difference in 3‐year OS among NPM1 + /FLT3‐ITD − , NPM1 − /FLT3‐ITD − , NPM1 + /FLT3‐ITD + and NPM1 − /FLT3‐ITD + patients: 56% (95% CI, 29%‐76%), 61% (95% CI, 46%‐73%), 53% (95% CI, 34%‐70%) and 52% (95% CI, 17%‐78%), respectively. CIR at 3‐years was similar among NPM1 − /FLT3‐ITD − , NPM1 + /FLT3‐ITD + and NPM1 − /FLT3‐ITD + patients—14% (95% CI, 6%‐26%), 13% (95% CI, 4%‐28%) and 19% (95% CI, 4%‐41%), respectively—while there were no relapses in the NPM1 + / FLT3‐ITD − group. NRM at 3 years for NPM1 + /FLT3‐ITD − , NPM1 − /FLT3‐ITD − , NPM1 + /FLT3‐ITD + and NPM1 − /FLT3‐ITD + patients was similar at 44% (95% CI, 19%‐67%), 38% (95% CI, 25%‐50%), 43% (95% CI, 25%‐59%) and 44% (95% CI, 14%‐71%), respectively. Conclusion NPM1 and FLT3‐ITD status may provide limited prognostic information about transplant outcomes in CN AML patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".