Premium
External validation of a nomogram predicting mortality in patients with adrenocortical carcinoma
Author(s) -
Zini Laurent,
Capitanio Umberto,
Jeldres Claudio,
Lughezzani Giovanni,
Sun Maxine,
Shariat Shahrokh F.,
Isbarn Hendrik,
Arjane Philippe,
Widmer Hugues,
Perrotte Paul,
Graefen Markus,
Montorsi Francesco,
Karakiewicz Pierre I.
Publication year - 2009
Publication title -
bju international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.773
H-Index - 148
eISSN - 1464-410X
pISSN - 1464-4096
DOI - 10.1111/j.1464-410x.2009.08660.x
Subject(s) - nomogram , medicine , cohort , adrenocortical carcinoma , proportional hazards model , receiver operating characteristic , stage (stratigraphy) , cancer , epidemiology , oncology , surgery , cohort study , paleontology , biology
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.