Abstract
Background The SCOT colorectal cancer trial is a phase III randomised controlled, multi-centre, non-inferiority trial comparing the efficacy of 12 weeks of chemotherapy versus 24 weeks and the associated toxicity, along with a lifetime economic analysis. The economic analysis will use prospective trial data to inform a lifetime cost-effectiveness model. Quality of life and toxicity data are only collected in a proportion of patients as the sample size required for these comparisons is much smaller than that required to show a significant difference in efficacy. This paper reports on an analysis of adverse events (AEs) and quality of life data, undertaken to determine whether it was appropriate to stop collecting quality of life data from new recruits. Do we have a large enough sample to detect whether the AEs and severity of AEs impact on quality of life?
Highlights
The SCOT colorectal cancer trial is a phase III randomised controlled, multi-centre, non-inferiority trial comparing the efficacy of 12 weeks of chemotherapy versus 24 weeks and the associated toxicity, along with a lifetime economic analysis
This paper reports on an analysis of adverse events (AEs) and quality of life data, undertaken to determine whether it was appropriate to stop collecting quality of life data from new recruits
Univariate analysis showed that the majority of AEs significantly reduce quality of life; multivariate analysis was inconclusive as AEs were highly correlated with one another
Summary
The SCOT colorectal cancer trial is a phase III randomised controlled, multi-centre, non-inferiority trial comparing the efficacy of 12 weeks of chemotherapy versus 24 weeks and the associated toxicity, along with a lifetime economic analysis. The economic analysis will use prospective trial data to inform a lifetime cost-effectiveness model. Quality of life and toxicity data are only collected in a proportion of patients as the sample size required for these comparisons is much smaller than that required to show a significant difference in efficacy. This paper reports on an analysis of adverse events (AEs) and quality of life data, undertaken to determine whether it was appropriate to stop collecting quality of life data from new recruits. Do we have a large enough sample to detect whether the AEs and severity of AEs impact on quality of life?
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