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Individualized risk prediction of outcomes for oral cavity cancer patients.

ABSTRACT: 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.

SUBMITTER: Prince V

PROVIDER: S-EPMC5193389 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Individualized risk prediction of outcomes for oral cavity cancer patients.

Prince Victoria V Bellile Emily L EL Sun Yilun Y Wolf Gregory T GT Hoban Connor W CW Shuman Andrew G AG Taylor Jeremy M G JM

Oral oncology 20161123

<h4>Background</h4>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.<h4>Aim</h4>To compare and evaluate oral cavity cancer prognostic calculators using an independent dataset.<h4>Methods</h4>Five pr ...[more]

PMID: 27939002

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Project description:ImportancePostoperative complications after head and neck surgery carry the potential for significant morbidity. Estimating the risk of complications in an individual patient is challenging.ObjectiveTo develop a statistical tool capable of predicting an individual patient's risk of developing a major complication after surgery for oral cavity squamous cell carcinoma.Design, setting, and participantsRetrospective case series derived from an institutional clinical oncologic database, augmented by medical record abstraction, at an academic tertiary care cancer center. Participants were 506 previously untreated adult patients with biopsy-proven oral cavity squamous cell carcinoma who underwent surgery between January 1, 2007, and December 31, 2012.Main outcomes and measuresThe primary end point was a major postoperative complication requiring invasive intervention (Clavien-Dindo classification grades III-V). Patients treated between January 1, 2007, and December 31, 2008 (354 of 506 [70.0%]) comprised the modeling cohort and were used to develop a nomogram to predict the risk of developing the primary end point. Univariable analysis and correlation analysis were used to prescreen 36 potential predictors for incorporation in the subsequent multivariable logistic regression analysis. The variables with the highest predictive value were identified with the step-down model reduction method and included in the nomogram. Patients treated between January 1, 2007, and December 31, 2008 (152 of 506 [30.0%]) were used to validate the nomogram.ResultsClinical characteristics were similar between the 2 cohorts for most comparisons. Thirty-six patients in the modeling cohort (10.2%) and 16 patients in the validation cohort (10.5%) developed a major postoperative complication. The 6 preoperative variables with the highest individual predictive value were incorporated within the nomogram, including body mass index, comorbidity status, preoperative white blood cell count, preoperative hematocrit, planned neck dissection, and planned tracheotomy. The nomogram predicted a major complication with a validated concordance index of 0.79. Inclusion of surgical operative variables in the nomogram maintained predictive accuracy (concordance index, 0.77).Conclusions and relevanceA statistical tool was developed that accurately estimates an individual patient's risk of developing a major complication after surgery for oral cavity squamous cell carcinoma.

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Individualized risk prediction of outcomes for oral cavity cancer patients.

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Individualized risk prediction of outcomes for oral cavity cancer patients.

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