Acute myeloid leukemia (AML) commonly affects the elderly with a poor prognosis. Body water composition analysis provides a new perspective for biomedical research. This study aims to develop and validate a simple nomogram for predicting overall survival (OS) in AML survivors. A total of 291patients were enrolled and randomly divided into a training cohort and an internal validation cohort. The median duration of follow-up was 32.2 months.The LASSO regression was used to screen predictors of survival in the training cohort, and the multivariate Cox model was used to establish a nomogram. The discrimination and calibration of the nomogram were evaluated using the C-index, area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration plots. The net benefits of the nomogram at different threshold probabilities were quantified. Five predictors of AML survival were identified: Age, Extracellular water/Intracellular water (ECW/ICW) ratio, European Leukemia Net Risk, Sarcopenia, and WBC. The nomogram showed good performance in both the training cohort (C-index 0.755, 95% CI 0.728-0.782) and the internal validation cohort (C-index 0.773, 95% CI 0.729 to 0.817). The AUC values for the training cohort were 0.866, 0.849, 0.818, and 0.779 at 12, 24, 36, and 48 months, respectively
the AUC values for the internal validation cohort were 0.799, 0.779, 0.797, and 0.786 at 12, 24, 36, and 48 months, respectively. The calibration curves of the nomogram showed acceptable consistency, and the decision curve analysis indicated higher net benefit in clinical practice. In this study, we developed and validated an easily applicable model to predict OS in AML patients.