These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Postoperative nomograms predictive of survival after surgical management of malignant tumors of the major salivary glands.
    Author: Ali S, Palmer FL, Yu C, DiLorenzo M, Shah JP, Kattan MW, Patel SG, Ganly I.
    Journal: Ann Surg Oncol; 2014 Feb; 21(2):637-42. PubMed ID: 24132626.
    Abstract:
    OBJECTIVES: The objective of this study was to create a nomogram predictive of survival in salivary gland cancer. METHODS: Clinical, tumor, and treatment characteristics were collected for 301 patients who underwent surgery for salivary gland cancer between 1985 and 2009 at Memorial Sloan Kettering Cancer Centre. Factors predictive of overall survival (OS) and cancer-specific survival (CSS) were determined by univariate analysis. Cox risk regression was used to model OS data. Competing risks regression was used for cancer-specific death. Deaths from other causes were treated as competing risks for cancer-specific death. Predictive nomograms for OS and CSS were then created using stepdown method to select predictors of outcome. RESULTS: The median age was 62 (range 9-89) years. There were 156 (52%) males and 145 (48%) females. Five variables predictive for OS (age, clinical T4 stage, histological grade, perineural invasion, and tumor dimension) were used to generate a parsimonious model, and a nomogram was created to predict 10-year survival probability. The concordance index (CI) for this nomogram was 0.809. Five variables predictive for CSS (histological grade, perineural invasion, clinical T4 stage, positive nodal status, and status of margins) were used to generate a second nomogram predicting CSS. This nomogram had a CI of 0.856. Both nomograms were validated internally by assessing discrimination and calibration. CONCLUSIONS: We have developed the first nomograms to predict prognosis in an individual patient with salivary gland cancer.
    [Abstract] [Full Text] [Related] [New Search]