RESUMO
Aim: Assess the suitability of standard parametric, piecewise and mixture cure models (MCMs) for modeling long-term survival of acute myeloid leukemia patients achieving remission following treatment with gemtuzumab ozogamicin (GO) + standard chemotherapy (SC) or SC alone. MCMs can model survival data comprising of statistically cured (patients in long-term remission) and uncured patients. Materials & methods: Models were fit to patient-level data corresponding to individual treatment arms. Results: Visual inspection showed that MCMs fit the clinical data best. Survival modeling with MCMs showed that treatment with GO + SC versus SC alone results in higher statistical cure rates for event-free survival (rates: 26-35% vs 21-23%) and overall survival (rates: 48-52% vs 38-44%). Conclusion: MCMs are well suited to modeling long-term survival in acute myeloid leukemia patients. Clinical trial registration: NCT00927498 (ClinicalTrials.gov).
Lay abstract To assess the effectiveness of acute myeloid leukemia (AML) treatments, researchers use statistical models to estimate the survival rate of patients who receive a particular treatment. Some patients receiving certain AML treatments can achieve long-term remission and are often considered 'cured'. Standard statistical models cannot differentiate between cured and uncured patients and so tend to underestimate the survival rates of cured patients. Mixture cure models (MCMs) can account separately for the survival of cured versus uncured patients. We tested MCMs and standard statistical models using data from a clinical trial comparing gemtuzumab ozogamicin (GO) + standard chemotherapy against standard chemotherapy alone in AML patients. Of all the models tested, MCMs generated survival extrapolations over time that most closely resembled the data from the clinical trial. Through our analyses, we demonstrated that GO + standard chemotherapy can result in higher survival rates than standard chemotherapy alone.
