Gut · 2001 · 149 citations · 20 references
MedicineOncologyPalliative CarePalliative MedicineSurvival AnalysisCancer Survival AnalysisEsophageal CancerPatient-reported Outcome MeasuresPrognostic AssessmentSurvival OutcomesCancer-related Quality Of LifeCox RegressionPhysical Function AssessmentPhysical Function DeclinePhysical Function MeasurementQuality Of Life EndpointsQuality Of Life PrognosisTnm Staging System
BACKGROUND: Quality of life (QL) data are useful to evaluate the effectiveness of treatment. Accumulating evidence suggests that QL data may predict survival. AIMS: In this study we investigated if baseline QL scores and changes in QL scores before and after intervention are prognostic for patients with oesophageal cancer. PATIENTS: Between 1993 and 1995, 92 consecutive new patients with oesophageal cancer were studied; 89 were followed until death or the end of the study period (survival of seven patients was censored in May 1999). METHODS: All patients completed the European Organisation for Research and Treatment of Cancer (EORTC) core questionnaire (EORTC QLQ-C30) and the dysphagia scale of the oesophageal module (EORTC QLQ-OES24) before treatment and at regular intervals throughout the study. Cox's proportional hazards models assessed the impact of baseline QL variables and changes in QL scores on survival. RESULTS: Cox's proportional hazards models, adjusting for associations between QL scores, age, and TNM stage, found that physical function at baseline was significantly associated with survival (p=0.002). An increase in physical function score of 10 points corresponded to a 12% reduction in the likelihood of death at any given time (95% confidence intervals 4--18%). Further exploratory multivariable analyses suggested that improvement in emotional function six months after treatment was significantly related to longer survival (p<0.0001). CONCLUSIONS: These data provide evidence to support a relationship between patient rated scores of QL and survival. Further understanding of the associations between QL and clinical variables is needed.
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N.K. Aaronson, Sam H. Ahmedzai, Bengt Bergman et al. · JNCI Journal of the National Cancer Institute · 1993 · 16K citations