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Optimal Percent Myxoid Component to Predict Outcome in High-Grade Myxofibrosarcoma and Undifferentiated Pleomorphic
Ann Y Lee1, Narasimhan P Agaram2, Li-Xuan Qin3
1Sarcoma Biology Laboratory, Sarcoma Disease Management Program, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Background:
Myxofibrosarcoma and undifferentiated pleomorphic sarcoma (UPS) are aggressive, genetically complex sarcomas. The minimum myxoid component used as a criterion for myxofibrosarcoma varies widely, so we determined the optimal myxoid component cutpoints for stratifying outcomes of UPS and myxofibrosarcoma. We also analyzed clinicopathologic factors associated with outcome.
Methods:
Review of a prospective, single-institution database identified 197 patients with primary, high-grade extremity/truncal myxofibrosarcoma or UPS resected during 1992-2013. Histology was reviewed and percent myxoid component determined for each tumor. Disease-specific survival (DSS) and distant recurrence-free survival (DRFS) were analyzed using the Kaplan-Meier method, log-rank test, and Cox regression.
Results:
Median follow-up for survivors was 6.4 years. In minimum p value analysis of myxoid component, the best cutpoint for both DSS and DRFS was 5% (adjusted p ≤ 0.001), followed by 70%. Therefore, sarcomas with <5% myxoid component (n = 69) were classified as UPS and those with ≥5% myxoid component (n = 128) as myxofibrosarcoma. Five-year DRFS was 24% for UPS, 51% for 5-69% myxoid component myxofibrosarcoma, and 65% for ≥70% myxoid component myxofibrosarcoma. Myxoid component, tumor size, and age were independently associated with DSS; myxoid component and tumor size were associated with DRFS. Only tumor site was associated with local recurrence.
Conclusions:
Percent myxoid component and tumor size are the two most important predictors of DSS and DRFS in high-grade myxofibrosarcoma and UPS. A 5% myxoid component cutpoint is an improved criterion for classifying myxofibrosarcoma. Myxoid component-based classification improves stratification of patient outcome and will aid in selection of patients for systemic therapy and clinical trials.
