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Original Investigation
April 2016

Nomograms to Predict Recurrence-Free and Overall Survival After Curative Resection of Adrenocortical Carcinoma

Author Affiliations
  • 1Department of Surgery, The Johns Hopkins University School of Medicine, Baltimore, Maryland
  • 2Department of Surgery, Stanford University School of Medicine, Stanford, California
  • 3Department of Surgery, Emory University, Atlanta, Georgia
  • 4Department of Surgery, Medical College of Wisconsin, Milwaukee
  • 5Department of Surgery, New York University School of Medicine, New York
  • 6Department of Surgery, The Ohio State University, Columbus
  • 7Department of Surgery, Washington University School of Medicine in St Louis, Missouri
  • 8Department of General Surgery, University of Wisconsin School of Medicine and Public Health, Madison
  • 9Department of Surgery, University of California, San Diego
  • 10Department of Surgery, University of Texas Southwestern Medical Center, Dallas
  • 11Department of Surgery, University of California, San Francisco
  • 12Department of Surgery, Vanderbilt University, Nashville, Tennessee
  • 13Department of Surgery, Wake Forest School of Medicine, Winston-Salem, North Carolina
JAMA Surg. 2016;151(4):365-373. doi:10.1001/jamasurg.2015.4516
Abstract

Importance  Adrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined.

Objectives  To define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction.

Design, Setting, and Participants  Nomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015.

Main Outcomes and Measures  The discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves.

Results  In total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63-5.70; P < .001), positive nodal status (HR, 4.78; 95% CI, 1.47-15.50; P = .01), stage III/IV (HR, 1.80; 95% CI, 0.95-3.39; P = .07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27-4.48; P = .01), and capsular invasion (HR, 1.96; 95% CI, 1.02-3.74; P = .04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00-3.17; P = .05), positive nodal status (HR, 5.89; 95% CI, 2.05-16.87; P = .001), and R1 margin (HR, 2.83; 95% CI, 1.51-5.30; P = .001). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.74 for RFS and 0.70 for OS).

Conclusions and Relevance  Independent predictors of survival and recurrence risk after curative-intent surgery for ACC were selected to create nomograms predicting RFS and OS. The nomograms were able to stratify patients into prognostic groups and performed well on internal validation.

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