A novel clinical prediction model for prognosis in malignant pleural mesothelioma using decision tree analysis
Journal of Thoracic Oncology 2016 January 6 [Epub ahead of print] [Link]
Brims FJ, Meniawy TM, Duffus I, de Fonseka D, Segal A, Creaney J, Maskell N, Lake RA, de Klerk N, Nowak AK.
Malignant pleural mesothelioma (MPM) is a rare cancer with a heterogeneous prognosis. Prognostic models are not widely utilised clinically. Classification and regression tree (CART) analysis examines the interaction of multiple variables with a given outcome.
Between 2005-2014, all cases with pathologically confirmed MPM had routinely available histological, clinical and laboratory characteristics recorded. CART analysis was performed using 29 variables with 18-month survival as the dependent variable. Risk groups were refined according to survival and clinical characteristics. The model was then tested on an external international cohort.
482 cases were included in the derivation cohort, median survival was 12.6 months, median age 69 years. The model defined four risk groups with clear survival differences (p<0.0001). The strongest predictive variable was the presence of weight loss. The group with the best survival at 18 months (86.7% alive: 'risk group 1', median survival 34.0 months) had no weight loss, haemoglobin >153 g/L and serum albumin >43 g/L. The group with the worst survival (0% alive: ‘risk group 4d’, median survival 7.5 months) had weight loss, performance score 0-1 and sarcomatoid histology. The C-statistic for the model was 0.761, sensitivity 94.5%. Validation on 174 external cases confirmed the model’s ability to discriminate between risk groups on an alternative dataset with fair performance (C-statistic 0.68).
We have developed and validated a simple, clinically relevant model to reliably discriminate cases at high and lower risk of death using routinely available variables from the time of diagnosis in unselected populations of MPM patients.