1.P.11 HOW TO STRATIFY PATIENTS WITH OSTEOSARCOMA. CLASSIFICATION AND REGRESSION TREE ANALYSIS

Abstract

In osteosarcoma, treatment guidelines recommend standard chemotherapy regardless of severity of disease. Treatment individualization will minimize risk of failure and adverse effects, specially in patients who have good prognosis. Therefore, there is a pressing clinical need to develop a risk adapted strategies and to adjust chemotherapy to prognostic factors.

Aim: to asses usefulness of Classification and Regression Tree Analysis (C& RT) for stratifying patients with localised osteosarcoma to the risk groups according to clinical and biological markers.

Material and methods: 100 patients with localised osteosarcoma were included, aged 5–23 years (mean 14), with extremity localisation of the primary tumour. Follow up – at least 5 years since a date of diagnosis. We analysed clinical prognostic factors (tumour size, pathological fracture, alkaline phosphatase, age), histological prognostic factors (% of viable tumour cells after pre-operative chemotherapy, subtype of osteosarcoma and its aggressiveness) and biological factors (expression of VEGF, Ki-67, Topoisomerase II alpha and P glycoprotein). The expressions of proteins were measured immunohistochemically in biopsy samples. C& RT model included all described above factors.

Results: C& RT analysis revealed that the most important prognostic factors in localised osteosarcoma were: VEGF, Topoisomerase II alpha and tumour size. This markers were included into the risk classification and three risk groups were proposed: with poor prognosis (n=13) – 5 year OS 31%, moderate (n=57) – 5 year OS 63% and with good prognosis (n=30) – 5 year OS 93%), P=0.000.

Conclusion: C& RT is useful method for stratifying patients with osteosarcoma to risk groups. The stratification should include biological and clinical prognostic markers.