Analysis of messy longitudinal data from a randomized clinical trial. MRC Lung Cancer Working Party.

The randomized clinical trial, LU19, conducted by the Medical Research Council Lung Cancer Working Party, was designed to compare ACE (doxorubicin, cyclophosphamide and etoposide) chemotherapy plus G-CSF (granulocyte colony-stimulating factor) at 2-week intervals versus ACE chemotherapy alone at standard 3-week intervals in patients with small-cell lung cancer. This trial investigated whether more intensive administration of ACE would improve overall survival and affect the quality of life of patients. The report on overall survival and other outcome measures will be published in the Journal of Clinical Oncology. In this paper we focus on methods of analysing aspects of data reflecting quality of life. Twelve symptoms of lung cancer and its treatment - cough, haemoptysis, pain, nausea, vomiting, hoarse voice, sore mouth, rash, lethargy, lack of appetite, alopecia, and dysphagia - were scheduled to be assessed on seven occasions for the ACE arm and on eight occasions for the ACE+G-CSF arm by clinicians during the first 18 weeks of the treatment period. However, in practice the number of assessment forms completed per patient ranged from 1 to 9, and assessment time-points were very different from those planned. These 'messy' longitudinal data are explored by both a summary measure approach, in which experience of a symptom is summarized by a single value, and an extensive model-based statistical approach, which explicitly takes into account correlation within repeated measures. These analyses provide a clear picture of symptom comparisons between the two treatments. The application of various methods offers not only an approach to assessing the robustness of the results but also a basis for investigating reasons for inconsistency of results across methods. We conclude that except lethargy, which is worse in the ACE+G-CSF arm, all symptoms are similar across the two arms during the treatment period.

RCT Entities:   Population Interventions Outcomes