To determine the prognostic significance of histologic subtype in a large series of patients with primary liposarcoma (LS) and to construct a LS-specific postoperative nomogram for disease-specific survival (DSS).Summary Background Data:
Nomograms, used to define and predict outcome following operative intervention, may contain variables not conventionally used in standard staging systems. A 12-year DSS postoperative nomogram for all sarcomas has already been established.Methods:
From a single-institution prospective sarcoma database, patients with primary extremity, truncal, or retroperitoneal LS treated between 1982 and 2005 were identified. Histology was reviewed by a sarcoma pathologist and divided into 5 subtypes. A nomogram predictive of 5- and 12-year DSS was developed.Results:
Of 801 patients with primary LS resected with curative intent, 369 (46%) presented with well-differentiated, 143 (18%) dedifferentiated, 144 (18%) myxoid, 81 (10%) round cell, and 64 (8%) pleomorphic histology. The median tumor burden was 15 cm (range, 1-139 cm). At last follow-up, 560 patients were alive with a median follow-up time of 45 months (range, 1-264 months) and 51 months for surviving patients. The 5- and 12-year DSS rates were 83% (95% confidence interval [CI], 80%-86%) and 72% (95% CI, 67%-77%), respectively. The nomogram was drawn on the basis of a Cox regression model. The independent predictors of DSS were age, presentation status, histologic variant, primary site, tumor burden, and gross margin status. The nomogram was internally validated using bootstrapping and shown to have excellent calibration. The concordance index was 0.827 compared with 0.776 for the general sarcoma postoperative nomogram for 12-year DSS.Conclusion:
The LS-specific nomogram based on histologic subtype provides more accurate survival predictions for patients with primary LS than the previously established generic sarcoma nomogram. DSS nomograms aid in more accurate counseling of patients, identification of patients appropriate for adjuvant therapy, and stratification of patients for clinical trials and molecular analysis.