Why the study?
Does the extended SAM model improve the accuracy of 10-year sarcoma-specific survival prediction compared to the SIN model in patients with extremity and trunk wall soft tissue sarcomas?
Does the extended SAM model improve the accuracy of 10-year sarcoma-specific survival prediction compared to the SIN model in patients with extremity and trunk wall soft tissue sarcomas?
The addition of grade, depth, location, and continuous tumor size to a prognostic model significantly improves the prediction of 10-year sarcoma-specific survival.
May support refined STS risk stratification with SAM over SIN; leaves open impact on management pending prospective validation.
BACKGROUND: We developed a web-based, prognostic tool for extremity and trunk wall soft tissue sarcoma to predict 10-year sarcoma-specific survival. External validation was performed. METHODS: Patients referred during 1987-2002 to Helsinki University Central Hospital are included. External validation was obtained from the Lund University Hospital register. Cox proportional hazards models were fitted with the Helsinki data. The previously described model (SIN) includes size, necrosis, and vascular invasion. The extended model (SAM) includes the SIN factors and in addition depth, location, grade, and size on a continuous scale. Models were statistically compared according to accuracy (area under the ROC curve=AUC) of 10-year sarcoma-specific survival prediction. RESULTS: The AUC of the SAM model in 10-year survival prediction in the Helsinki patient series was 0.81 as compared with 0.74 for the SIN model (P=0.0007). The corresponding AUCs in the external validation series were 0.77 for the SAM model and 0.73 for the SIN model (P=0.03). A web-based calculator for the SAM model is available at http://www.prognomics.org/sam. CONCLUSION: Addition of grade, depth, and location as well as tumour size on a continuous scale significantly improved the accuracy of the prognostic model when compared with a model that includes only size, necrosis, and vascular invasion.
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Sampo et al. (2012) studied this question.
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