OBJECTIVE: To develop nomograms predicting cancer-specific and all-cause mortality in patients managed with either surgery or no surgery for adrenocortical carcinoma (ACC). PATIENTS AND METHODS: The models were developed in 205 patients with ACC and externally validated using 207 other patients with ACC, identified in the 1973-2004 Surveillance, Epidemiology and End Results database. The predictors comprised age, gender, race, stage and surgery status. Nomograms based on Cox regression model-derived coefficients were used for predicting the cancer-specific and all-cause mortality, and were tested using area under the receiver operating characteristics (ROC) curve. RESULTS: In cancer-specific analyses, the median survival of patients within the development cohort was 26 months, vs 71 months in the external validation cohort (P < 0.001). In overall survival analyses, the median values were 21 vs 32 months for, respectively, the development and the external validation cohort (P < 0.001). Three variables (age, stage and surgical status) were included in the nomograms predicting cancer-specific and all-cause mortality. In the external validation cohort, the nomograms achieved between 72 and 80% accuracy for prediction of cancer-specific or all-cause mortality at 1-5 years after either surgery or diagnosis of ACC for non-surgical patients. CONCLUSION: Our models are the first standardized and individualized prognostic tools for patients with ACC. Their accuracy was confirmed within a large external population-based cohort of patients with ACC.
OBJECTIVE: To develop nomograms predicting cancer-specific and all-cause mortality in patients managed with either surgery or no surgery for adrenocortical carcinoma (ACC). PATIENTS AND METHODS: The models were developed in 205 patients with ACC and externally validated using 207 other patients with ACC, identified in the 1973-2004 Surveillance, Epidemiology and End Results database. The predictors comprised age, gender, race, stage and surgery status. Nomograms based on Cox regression model-derived coefficients were used for predicting the cancer-specific and all-cause mortality, and were tested using area under the receiver operating characteristics (ROC) curve. RESULTS: In cancer-specific analyses, the median survival of patients within the development cohort was 26 months, vs 71 months in the external validation cohort (P < 0.001). In overall survival analyses, the median values were 21 vs 32 months for, respectively, the development and the external validation cohort (P < 0.001). Three variables (age, stage and surgical status) were included in the nomograms predicting cancer-specific and all-cause mortality. In the external validation cohort, the nomograms achieved between 72 and 80% accuracy for prediction of cancer-specific or all-cause mortality at 1-5 years after either surgery or diagnosis of ACC for non-surgical patients. CONCLUSION: Our models are the first standardized and individualized prognostic tools for patients with ACC. Their accuracy was confirmed within a large external population-based cohort of patients with ACC.
Authors: Yuhree Kim; Georgios A Margonis; Jason D Prescott; Thuy B Tran; Lauren M Postlewait; Shishir K Maithel; Tracy S Wang; Jason A Glenn; Ioannis Hatzaras; Rivfka Shenoy; John E Phay; Kara Keplinger; Ryan C Fields; Linda X Jin; Sharon M Weber; Ahmed Salem; Jason K Sicklick; Shady Gad; Adam C Yopp; John C Mansour; Quan-Yang Duh; Natalie Seiser; Carmen C Solorzano; Colleen M Kiernan; Konstantinos I Votanopoulos; Edward A Levine; George A Poultsides; Timothy M Pawlik Journal: Ann Surg Date: 2017-01 Impact factor: 12.969
Authors: Yuhree Kim; Georgios A Margonis; Jason D Prescott; Thuy B Tran; Lauren M Postlewait; Shishir K Maithel; Tracy S Wang; Douglas B Evans; Ioannis Hatzaras; Rivfka Shenoy; John E Phay; Kara Keplinger; Ryan C Fields; Linda X Jin; Sharon M Weber; Ahmed I Salem; Jason K Sicklick; Shady Gad; Adam C Yopp; John C Mansour; Quan-Yang Duh; Natalie Seiser; Carmen C Solorzano; Colleen M Kiernan; Konstantinos I Votanopoulos; Edward A Levine; George A Poultsides; Timothy M Pawlik Journal: JAMA Surg Date: 2016-04 Impact factor: 14.766