What question did this study set out to answer?

This research aims to clarify how secondary-type mutations affect absolute survival rates in patients with NPM1-mutated acute myeloid leukemia classified as ELN-favorable.

May 30, 2026

Translating meta-analytic risk into absolute survival: Projection modeling of secondary-type mutations in ELN-favorable NPM1-mutated acute myeloid leukemia.

Key Points

This research aims to clarify how secondary-type mutations affect absolute survival rates in patients with NPM1-mutated acute myeloid leukemia classified as ELN-favorable.
Conducted meta-analysis–based projection modeling using pooled overall survival hazard ratios from 4,022 NPM1-mutated AML patients.
Calculated absolute survival probabilities under a proportional hazards framework, deriving estimates from the baseline 5-year survival rate and hazard ratios for presence of secondary-type mutations.
Simulated outcomes for a hypothetical cohort of 1,000 future ELN-favorable NPM1-mutated AML patients to quantify uncertainty with confidence intervals.
Projected that presence of secondary-type mutations reduces 5-year survival from 70% to approximately 50%.
Estimated about 501 deaths in the presence of secondary-type mutations compared to 300 deaths without them in a cohort of 1,000 patients, yielding roughly 200 excess deaths (range 90–320).
Confirmed robustness of findings across various visualization techniques, indicating a significant survival decrement due to secondary-type mutations.

Abstract

e18536 Background: Nucleophosmin 1 (NPM1) mutation is traditionally associated with a favorable prognosis in acute myeloid leukemia (AML), leading to classification of these patients within the European LeukemiaNet (ELN) favorable risk group. However, emerging evidence indicates that co-occurring secondary-type mutations (STMs), including ASXL1 , RUNX1 , EZH2 , and SRSF2 , may substantially modify this prognosis. While meta-analyses have quantified the relative risk associated with STMs using hazard ratios, the corresponding absolute survival impact remains unclear, limiting clinical interpretability and decision-making. Methods: We performed meta-analysis–based projection modeling using pooled overall survival hazard ratios reported in a recent systematic review and meta-analysis of 4,022 NPM1-mutated AML patients. For the ELN-favorable subgroup, the pooled hazard ratio for overall survival associated with STMs (HR 1.95; 95% CI 1.39–2.73) was combined with externally derived baseline 5-year survival estimates under a proportional hazards framework. Absolute survival probabilities were calculated using established survival–hazard transformations, and results were translated into projected outcomes for a hypothetical cohort of 1,000 future ELN-favorable NPM1-mutated AML patients. Uncertainty was quantified using the meta-analytic confidence interval. Results: Assuming a baseline 5-year overall survival of 70% for ELN-favorable NPM1-mutated AML patients without STMs, the presence of STMs was projected to reduce 5-year survival to approximately 50%. Based on the confidence interval of the pooled hazard ratio, projected survival with STMs ranged from 38% to 61%. In a simulated cohort of 1,000 patients, this corresponds to approximately 300 deaths at 5 years in the absence of STMs versus 501 deaths in the presence of STMs, yielding an estimated 200 excess deaths per 1,000 patients (plausible range: 90–320 excess deaths). These findings were robust across visualizations including absolute survival projections, stacked outcome distributions, and excess mortality estimates. Conclusions: Meta-analysis–based projection modeling demonstrates that secondary-type mutations may negate much of the favorable prognosis traditionally attributed to ELN-favorable NPM1-mutated AML, translating into a large absolute survival decrement in future patient cohorts. Converting relative risk estimates into absolute survival and event projections provides clinically actionable insight and supports the incorporation of secondary-type mutation status into risk stratification, trial design, and therapeutic decision-making.

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