Evaluation of prognostic factors in localized high-grade undifferentiated pleomorphic sarcoma: report of a multi-institutional experience of Anatolian Society of Medical Oncology

Most data on prognostic factors for patients with high-grade undifferentiated pleomorphic sarcoma (HGUPS) is obtained from analyses of soft tissue sarcomas. The purpose of this study was to evaluate the clinicopathologic features and their impact on outcomes specifically in patients diagnosed with HGUPS. In this multicenter trial, we retrospectively analyzed 112 patients who were diagnosed and treated at 12 different institutions in Turkey. We collected data concerning the patients, tumor characteristics, and treatment modalities. There were 69 males (61.6 %) and 43 females (38.4 %). Median age was 56 years (19–90). The most common anatomic site of tumor origin was the upper extremity. Pleomorphic variant was the predominant histological subtype. Median tumor size was 8.2 cm (0.6–30 cm). Tumors were mainly deeply seated (57.1 %). Fifty-seven patients (50.9 %) were stage II and the remainder were stage III at the time of diagnosis. Median follow-up was 30 months (2–160). The primary site of distant metastasis was the lung (73.5 %) and the second most common site was the liver (11.7 %). The 5-year overall survival, distant metastasis-free survival, and local recurrence-free survival rates were 56.3, 53.4, and 67.2 %, respectively. Multivariate analysis showed that Eastern Cooperative Oncology Group (ECOG) performance score of II (p = 0.033), deep tumor location (p = 0.000), and development of distant metastasis (p = 0.004) were negatively correlated with overall survival, and perioperative radiotherapy and negative microscopic margins were significant factors for local control rates (p = 0.000 for each). Deep tumor location (p = 0.003) was the only adverse factor related to distant metastasis-free survival. Deep tumor location, ECOG performance score of II, and development of distant metastasis carry a poor prognostic implication on overall survival. These will aid clinicians in predicting survival and treatment decision.