Hematopoietic stem cell transplantation for adult patients with isolated NPM1 mutated acute myeloid leukemia in first remission

Acute myeloid leukemia (AML) in first remission (CR1) with isolated NPM1 mutation (iNPM1m) is considered a good prognosis genotype, although up to one-third relapse. To evaluate the best transplant strategy, we retrospectively compared autologous stem cell transplantation (auto-SCT), related (MSD), and fully matched unrelated (MUD) allogeneic stem cell transplantation (allo-SCT). We identified 256 adult patients including 125 auto-SCT, 72 MSD, and 59 MUD. The 2-year leukemia-free survival (LFS) was 62% in auto-SCT, 69% in MUD, and 81% in MSD (P = .02 for MSD vs others). The 2-year overall survival (OS) was not different among auto-SCT, MUD, and MSD, reaching 83% (P = .88). The 2-year non-relapse mortality (NRM) was 2.5% in auto-SCT and 7.5% in allo-SCT (P = .04). The 2-year cumulative incidence of relapse (RI) was higher after auto-SCT (30%) than after MUD (22%) and MSD (12%, P = .01). In multivariate analysis, MSD versus auto-SCT but not MUD versus auto-SCT was associated with lower RI (P < .01 and P = .13, respectively) and better LFS (P = .01 and P = .31, respectively). Age correlated with higher NRM (P < .01). Allo-SCT using MSD appears as a reasonable transplant option for young patients with iNPM1m AML in CR1. Auto-SCT was followed by worse RI and LFS, but similar OS to both allo-SCT modalities

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran