In early-stage breast cancer, high TS expression is associated with a significantly worse prognosis in node-positive patients. Node-positive patients with high TS levels demonstrate the most significant improvement in DFS and OS when treated with six cycles of conventional adjuvant CMF therapy.
Assessment of health related quality of life has become an important endpoint in many cancer clinical trials. Because the participants of these trials often experience disease and treatment related morbidity and mortality, non-random missing assessments are inevitable. Examples are presented from several such trials that illustrate the impact of missing data on the analysis of QOL in these trials. The sensitivity of different analyses depends on the proportion of assessments that are missing and the strength of the association of the underlying reasons for missing data with disease and treatment related morbidity and mortality. In the setting of clinical trials of cancer therapy, the assumption that the data are missing completely at random (MCAR) and analyses of complete cases is usually unjustified. Further, the assumption of missing at random (MAR) may also be violated in many trials and models appropriate for non-ignorable missing data should be explored. Recommendations are presented to minimize missing data, to obtain useful documentation concerning the reasons for missing data and to perform sensitivity analyses.
Any prognostic significance of QL scores in the adjuvant setting is minimal or obscured by chemotherapy effects, but there is strong prognostic significance of QL scores after disease relapse. The contrast suggests that patient perception of the severity of underlying illness may determine reported QL scores.
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