Statistical analyses
REGRESSION
All descriptive statistics were performed and reported overall and by study group affiliation (intervention and control). Due to the exploratory nature of the current study, we assessed all the scales from the QLQ-C30 questionnaire without selecting any primary scales. For each scale, we used Cox proportional hazard models to investigate possible associations of the corresponding pre-treatment score with the risk of dying (for any cause) over 1 year, and logistic regression for 1-year NRM, respectively. For each clinical outcome, we first ran a univariable model using sociodemographic and clinical variables. Then, we ran a multivariable model, including the statistically significant variables in univariable analysis, i.e., age, living arrangements (living alone vs. not), stem cell source (peripheral blood vs. bone marrow), and EBMT score. In addition, we forced key variables that we deemed important from a clinical point of view into the multivariable model, i.e., gender, study group (intervention vs. control), HCT-CI score, body mass index and donor type (related vs. unrelated). Then, for each outcome, we ran the same multivariable model also including the pre-treatment score of each QLQ-C30 scale. The additional information provided by a scale was evaluated by the likelihood ratio test, testing the null hypothesis that the scale did not significantly increase the model fit when added to sociodemographic and clinical variables. Values are reported as hazard ratio (HR) or odds ratio (OR). The significance level was set at 0.05 with no adjustment for multiple testing, and all statistical tests were two-sided. All analyses were performed by SAS software v.4 (SAS Institute Inc., Cary, NC, USA).