BACKGROUND AND OBJECTIVE: Randomization does not protect against bias due to missing observations. In addition, different reasons for missing observations may lead to different invalid results. The purpose of this study was to illustrate how randomized intervention studies can be threatened by bias due to missing observations because of death or nonresponse. METHODS: A randomized clinical trial of the effect of psychosocial intervention on well-being after an operation for colorectal cancer was conducted in Denmark. Patients were interviewed 3, 6, 12, and 24 months after discharge from hospital. RESULTS: We found that the probability of nonresponse decreased with increasing anxiety score in the intervention group, but it increased with increasing anxiety score in the control group. This could lead to severe bias in an analysis of the effect of intervention on anxiety. Low physical functioning and low global health status and quality of life were related to an increased probability of dying before the next follow-up, and this association could explain the associations between anxiety and depression, respectively, and the probability of dying observed in crude analyses. CONCLUSION: Our study emphasizes the importance of performing specific missing data analyses in any study of well-being variables.
RCT Entities:
BACKGROUND AND OBJECTIVE: Randomization does not protect against bias due to missing observations. In addition, different reasons for missing observations may lead to different invalid results. The purpose of this study was to illustrate how randomized intervention studies can be threatened by bias due to missing observations because of death or nonresponse. METHODS: A randomized clinical trial of the effect of psychosocial intervention on well-being after an operation for colorectal cancer was conducted in Denmark. Patients were interviewed 3, 6, 12, and 24 months after discharge from hospital. RESULTS: We found that the probability of nonresponse decreased with increasing anxiety score in the intervention group, but it increased with increasing anxiety score in the control group. This could lead to severe bias in an analysis of the effect of intervention on anxiety. Low physical functioning and low global health status and quality of life were related to an increased probability of dying before the next follow-up, and this association could explain the associations between anxiety and depression, respectively, and the probability of dying observed in crude analyses. CONCLUSION: Our study emphasizes the importance of performing specific missing data analyses in any study of well-being variables.
Authors: Lone Ross; Annemette G Abild-Nielsen; Birthe L Thomsen; Randi V Karlsen; Ellen H Boesen; Christoffer Johansen Journal: Support Care Cancer Date: 2006-11-14 Impact factor: 3.603
Authors: Anne Moyer; Sarah K Knapp-Oliver; Stephanie J Sohl; Stefan Schnieder; Anna H L Floyd Journal: Cancer J Date: 2009 Sep-Oct Impact factor: 3.360