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Updated: Jun 28, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Validating an Oropharyngeal Cancer Risk Prediction Model with Data from a Canadian Population
Background:
The incidence of oropharyngeal cancer (OPC) related to human papillomavirus (HPV) has increased significantly in North America. Identifying high-risk individuals can guide preventive efforts. However, OPC risk prediction models validated for the Canadian population are lacking. This study aimed to externally validate an existing OPC risk prediction model developed in the United States using a Canadian dataset and to assess its performance. Methods The model was validated using data from the HeNCe Life study, a hospital-based case-control study on the causes of head and neck cancer. The dataset comprised 214 cases of oropharyngeal squamous cell carcinoma and 433 controls frequency-matched by age and sex, recruited from 4 referral hospitals in Montreal. Participants were 30 to 79 years of age. Predictors included age, sex, race, lifetime smoking history, previous year's consumption of alcohol, number of lifetime sex partners, HPV infection, and interactions between the number of sex partners and HPV infection, as well as between smoking and HPV infection. Model performance was assessed using various metrics and plots.
Results:
The model showed above-average overall performance (Somers delta score, 0.49; scaled Brier score, 68.8%; Nagelkerke R2, 0.2) and discrimination (concordance statistic, 0.74; discrimination slope, 0.18), but calibration was suboptimal (calibration-in-the-large, 4.93; calibration slope, 0.57).
Conclusions:
The model's overall predictive performance was above-average;however, the calibration was suboptimal. Therefore, recalibration using a Canadian dataset is warranted. Further studies are required to refine the model for Canadian populations.
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