OBJECTIVES: ITT-analyses of oncology trials tend to underestimate the treatment effect on overall survival, due to the impact of subsequent therapy. Inverse probability of censoring weighted analysis (IPCW)  was explored to estimate an adjusted treatment effect on OS in VISTA, a phase III randomized clinical trial comparing melphalan and prednisone with or without bortezomib (VMP vs MP) in previously untreated multiple myeloma patients ineligible for stem cell transplantation. METHODS: The IPCW consisted of 2 steps. First, time-varying weights were estimated using multivariate logistic regression, including age, gender, stage, M-protein type, creatinine-clearance as baseline covariates and M-protein as time-varying covariate. In a second step, these time-dependent weights were incorporated in a proportional hazards model, including the same baseline characteristics, with patients censored at initiation of subsequent therapy. RESULTS: CONCLUSIONS: In oncology, particularly in early line treatment, it is common that patients receive subsequent treatment lines. This typically happens more frequently and earlier in the comparator arm, which may bias the estimate for the treatment effect on OS. The IPCW-approach was explored to adjust for this bias, which resulted in an increased estimate of the treatment-effect on OS of VMP vs MP, compared to the original ITT-analysis. With overall survival being a key input in economic evaluation, estimating the accurate effect on OS is key. Employing this type of approaches may result in more accurate cost effectiveness results and thus more consistent/appropriate Health Technology Assessment recommendations.