A prediction model for treatment decisions in high-grade extremity soft-tissue sarcomas: Personalised sarcoma care (PERSARC)

Publication date: September 2017
Source:European Journal of Cancer, Volume 83
Author(s): Veroniek M. van Praag, Anja J. Rueten-Budde, Lee M. Jeys, Minna Laitinen, Rob Pollock, Will Aston, Jos A. van de Hage, P.D. Sander Dijkstra, Peter C. Ferguson, Anthony M. Griffin, Julie J. Willeumier, Jay S. Wunder, Michiel A.J. van de Sande, Marta Fiocco
BackgroundTo support shared decision-making, we developed the first prediction model for patients with primary soft-tissue sarcomas of the extremities (ESTS) which takes into account treatment modalities, including applied radiotherapy (RT) and achieved surgical margins. The PERsonalised SARcoma Care (PERSARC) model, predicts overall survival (OS) and the probability of local recurrence (LR) at 3, 5 and 10 years.AimDevelopment and validation, by internal validation, of the PERSARC prediction model.MethodsThe cohort used to develop the model consists of 766 ESTS patients who underwent surgery, between 2000 and 2014, at five specialised international sarcoma centres. To assess the effect of prognostic factors on OS and on the cumulative incidence of LR (CILR), a multivariate Cox proportional hazard regression and the Fine and Gray model were estimated. Predictive performance was investigated by using internal cross validation (CV) and calibration. The discriminative ability of the model was determined with the C-index.ResultsMultivariate Cox regression revealed that age and tumour size had a significant effect on OS. More importantly, patients who received RT showed better outcomes, in terms of OS and CILR, than those treated with surgery alone. Internal validation of the model showed good calibration and discrimination, with a C-index of 0.677 and 0.696 for OS and CILR, respectively.ConclusionsThe PERSARC model is the first to incorporate known clinical risk factors with the use of different treatments and surgical outcome measures. The developed model is internally validated to provide a reliable prediction of post-operative OS and CILR for patients with primary high-grade ESTS.Level of significancelevel III.



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