title: Postoperative Nomogram for Predicting Cancer-Specific Mortality in Medullary Thyroid Cancer.
abstract: BACKGROUND
  Medullary thyroid cancer (MTC) is a rare thyroid cancer accounting for 5 % of all thyroid malignancies. The purpose of our study was to design a predictive nomogram for cancer-specific mortality (CSM) utilizing clinical, pathological, and biochemical variables in patients with MTC.
  
  
  METHODS
  MTC patients managed entirely at Memorial Sloan-Kettering Cancer Center between 1986 and 2010 were identified. Patient, tumor, and treatment characteristics were recorded, and variables predictive of CSM were identified by univariable analyses. A multivariable competing risk model was then built to predict the 10-year cancer specific mortality of MTC. All predictors of interest were added in the starting full model before selection, including age, gender, pre- and postoperative serum calcitonin, pre- and postoperative CEA, RET mutation status, perivascular invasion, margin status, pathologic T status, pathologic N status, and M status. Stepdown method was used in model selection to choose predictive variables.
  
  
  RESULTS
  Of 249 MTC patients, 22.5 % (56/249) died from MTC, whereas 6.4 % (16/249) died secondary to other causes. Mean follow-up period was 87 ± 67 months. The seven variables with the highest predictive accuracy for cancer specific mortality included age, gender, postoperative calcitonin, perivascular invasion, pathologic T status, pathologic N status, and M status. These variables were used to create the final nomogram. Discrimination from the final nomogram was measured at 0.77 with appropriate calibration.
  
  
  CONCLUSIONS
  We describe the first nomogram that estimates cause-specific mortality in individual patients with MTC. This predictive nomogram will facilitate patient counseling in terms of prognosis and subsequent clinical follow up.
authors.affiliation: Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Allen S
authors.initials: AS
authors.lastname: Ho
authors.forename: Lu
authors.initials: L
authors.lastname: Wang
authors.forename: Frank L
authors.initials: FL
authors.lastname: Palmer
authors.forename: Changhong
authors.initials: C
authors.lastname: Yu
authors.forename: Arnbjorn
authors.initials: A
authors.lastname: Toset
authors.forename: Snehal
authors.initials: S
authors.lastname: Patel
authors.forename: Michael W
authors.initials: MW
authors.lastname: Kattan
authors.forename: R Michael
authors.initials: RM
authors.lastname: Tuttle
authors.forename: Ian
authors.initials: I
authors.lastname: Ganly
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D001808:Blood Vessels / Q000473:pathology; D002116:Calcitonin / Q000097:blood; D018278:Carcinoma, Neuroendocrine / Q000401:mortality* / Q000473:pathology / Q000601:surgery; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging; D049451:Nomograms; D011184:Postoperative Period; D011237:Predictive Value of Tests; D012737:Sex Factors; D015996:Survival Rate; D013964:Thyroid Neoplasms / Q000401:mortality* / Q000473:pathology / Q000601:surgery
chemical_list: D002116:Calcitonin