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Oral Oncol. 2016 Dec;63:66-73. doi: 10.1016/j.oraloncology.2016.11.005. Epub 2016 Nov 23.

Individualized risk prediction of outcomes for oral cavity cancer patients.

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Department of Otolaryngology, University of Michigan, Ann Arbor, MI 48109, United States.
Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States.
Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States. Electronic address:



Optimal management of oral cancer relies upon accurate and individualized risk prediction of relevant clinical outcomes. Individualized prognostic calculators have been developed to guide patient-physician communication and treatment-related decision-making. However it is critical to scrutinize their accuracy prior to integrating into clinical care.


To compare and evaluate oral cavity cancer prognostic calculators using an independent dataset.


Five prognostic calculators incorporating patient and tumor characteristics were identified that evaluated five-year overall survival. A total of 505 patients with previously untreated oral cancer diagnosed between 2003 and 2014 were analyzed. Calculators were applied to each patient to generate individual predicted survival probabilities. Predictions were compared among prognostic tools and with observed outcomes using Kaplan-Meier plots, ROC curves and calibration plots.


Correlation between the five calculators varied from 0.59 to 0.86. There were considerable differences between individual predictions from pairs of calculators, with as many as 64% of patients having predictions that differed by more than 10%. Four of five calculators were well calibrated. For all calculators the predictions were associated with survival outcomes. The area under the ROC curve ranged from 0.65 to 0.71, with C-indices ranging from 0.63 to 0.67. An average of the 5 predictions had slightly better performance than any individual calculator.


Five prognostic calculators designed to predict individual outcomes of oral cancer differed significantly in their assessments of risk. Most were well calibrated and had modest discriminatory ability. Given the increasing importance of individualized risk prediction, more robust models are needed.


Calculator; Calibration; Discrimination; Nomogram; Oral cavity; Overall survival; Risk prediction

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