Development and validation of a prognostic scale for use in patients with advanced cancer

Abstract

The aim of this study was to develop a new prognostic indicator to help predict survival in advanced cancer patients more accurately. Data on 329 patients obtained from a multi-centre study in London were analysed. A multifactorial Cox regression model was applied and validated using bootstrapping techniques. Predictive scores were calculated and used to produce a new prognostic index. The value of the index in predicting 14-day survival was then assessed. Four variables were found to be associated with worse survival: primary lung cancer, secondary liver cancer, raised C-Reactive protein and poor performance status (ECOG 4). Survival curves showed that patients designated as ‘high’ risk by the resulting index had significantly shorter survival than those designated as ‘low’ risk. A high score on the newly derived prognostic index is associated with poorer survival, but its clinical utility is limited by the relatively low predictive probability of the score.