Ali, Syed Hassan

e18624 Background: Invasive fungal infections (IFIs) are a major cause of morbidity and mortality in patients with hematologic malignancies. Although meta-analyses identify systemic corticosteroid exposure as a strong relative risk factor for IFI, the absolute burden attributable to corticosteroids across heterogeneous baseline risk settings remains poorly defined. We applied meta-analysis-based projection modeling to translate relative risk estimates into absolute, population-level IFI outcomes. Methods: Using pooled odds ratios for IFI associated with systemic corticosteroid exposure from a published meta-analysis (OR 2.84; 95% CI 1.42–5.70), we projected IFI incidence under a proportional odds framework. The primary analysis assumed a baseline IFI incidence of 15% in patients not receiving corticosteroids, with sensitivity analyses conducted across baseline incidences ranging from 10% to 25%. IFI-related mortality was estimated using a case-fatality rate of 45%. Outcomes were expressed as projected IFI incidence, excess IFIs and IFI-attributable deaths per 1,000 patients, population attributable fractions, and one-way sensitivity analyses. Results: At a baseline IFI incidence of 15%, systemic corticosteroid exposure increased projected IFI incidence to approximately 34%, corresponding to an excess of ~190 IFIs per 1,000 patients. This translated into approximately 80 excess IFI-attributable deaths per 1,000 patients, with a plausible range of 25–160 based on uncertainty in the pooled effect estimate. Sensitivity analyses demonstrated a monotonic increase in projected IFI incidence with rising baseline risk, with corticosteroid-associated IFI incidence approaching 50% at higher baseline levels. Population-attributable fraction modeling indicated that when corticosteroid use prevalence exceeded 40%, nearly half of IFIs in the population were attributable to corticosteroid exposure. One-way sensitivity analyses identified the corticosteroid effect size as the dominant driver of excess IFI mortality, exceeding the influence of baseline incidence or IFI case-fatality assumptions. Conclusions: Projection modeling based on meta-analytic risk estimates demonstrates that systemic corticosteroid exposure is associated with a substantial and clinically meaningful absolute increase in IFIs and IFI-related mortality. Translating relative risk estimates into absolute population-level outcomes highlights the potential magnitude of preventable infectious harm associated with corticosteroid use and provides actionable insight to inform risk-mitigation strategies in high-risk hematologic populations.

e18602 Background: Chimeric antigen receptor T-cell (CAR-T) therapy has transformed the treatment of hematologic malignancies but is frequently complicated by cytokine release syndrome (CRS) and immune-mediated neurotoxicity (NS). As CAR-T programs expand, population-level projections of treatment-related toxicities are essential for program planning and risk mitigation, yet remain poorly characterized. Methods: We performed a cohort-based forecasting analysis using pooled incidence rates of CRS and NS derived from published meta-analyses of CAR-T clinical trials. Expected numbers of toxicity events were projected for hypothetical cohorts of 100, 500, and 1,000 CAR-T–treated patients. Uncertainty was quantified using binomial 95% confidence intervals. Disease-specific projections were generated by applying stratified pooled toxicity rates for hematologic malignancies and solid tumors. Results: For a projected cohort of 1,000 CAR-T–treated patients, forecasts estimated approximately 770 patients would experience CRS of any grade, 290 would develop grade ≥3 CRS, 400 would experience NS of any grade, and 280 would develop grade ≥3 NS. Toxicity counts increased proportionally with cohort size and demonstrated predictable uncertainty bounds. When stratified by disease type, hematologic malignancies exhibited substantially higher toxicity burdens than solid tumors across all endpoints. At a cohort size of 1,000 patients, hematologic malignancies were associated with markedly higher rates of both CRS and severe neurotoxicity, whereas solid tumors demonstrated consistently lower toxicity burdens. Conclusions: Using pooled clinical trial data, this forecasting model provides quantitative estimates of CAR-T–associated toxicity burdens at the population level. Severe CRS and neurotoxicity remain common and scale predictably with program size, particularly in hematologic malignancies. These findings offer a pragmatic framework for anticipating resource utilization, toxicity management needs, and safety planning as CAR-T therapy continues to expand.

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.