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.
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.
Authors: Ximena Mimica; Marlena McGill; Ashley Hay; Daniella Karassawa Zanoni; Jatin P Shah; Richard J Wong; Alan L Ho; Marc A Cohen; Snehal G Patel; Ian Ganly Journal: Oral Oncol Date: 2019-05-22 Impact factor: 5.337
Authors: Safina Ali; Robert Bryant; Frank L Palmer; Monica DiLorenzo; Jatin P Shah; Snehal G Patel; Ian Ganly Journal: Ann Surg Oncol Date: 2015-03-06 Impact factor: 5.344
Authors: Ximena Mimica; Marlena McGill; Ashley Hay; Daniella Karassawa Zanoni; Jatin P Shah; Richard J Wong; Alan Ho; Marc A Cohen; Snehal G Patel; Ian Ganly Journal: Cancer Date: 2020-02-25 Impact factor: 6.860
Authors: Ian Ganly; Moran Amit; Lei Kou; Frank L Palmer; Jocelyn Migliacci; Nora Katabi; Changhong Yu; Michael W Kattan; Yoav Binenbaum; Kanika Sharma; Ramer Naomi; Agbetoba Abib; Brett Miles; Xinjie Yang; Delin Lei; Kristine Bjoerndal; Christian Godballe; Thomas Mücke; Klaus-Dietrich Wolff; Dan Fliss; André M Eckardt; Copelli Chiara; Enrico Sesenna; Safina Ali; Lukas Czerwonka; David P Goldstein; Ziv Gil; Snehal G Patel Journal: Eur J Cancer Date: 2015-11-19 Impact factor: 9.162
Authors: Turki M Almuhaimid; Won Sub Lim; Jong-Lyel Roh; Jungsu S Oh; Jae Seung Kim; Soo-Jong Kim; Seung-Ho Choi; Soon Yuhl Nam; Sang Yoon Kim Journal: J Cancer Res Clin Oncol Date: 2018-10-06 Impact factor: 4.553