A risk prediction model for head and neck cancers incorporating lifestyle factors, HPV serology and genetic markers

Abstract

Head and neck cancer is often diagnosed late and prognosis for most head and neck cancer patients remains poor. To aid early detection, we developed a risk prediction model based on demographic and lifestyle risk factors, human papillomavirus (HPV) serological markers and genetic markers. A total of 10 126 head and neck cancer cases and 5254 controls from five North American and European studies were included. HPV serostatus was determined by antibodies for HPV16 early oncoproteins (E6, E7) and regulatory early proteins (E1, E2, E4). The data were split into a training set (70%) for model development and a hold‐out testing set (30%) for model performance evaluation, including discriminative ability and calibration. The risk models including demographic, lifestyle risk factors and polygenic risk score showed a reasonable predictive accuracy for head and neck cancer overall. A risk model that also included HPV serology showed substantially improved predictive accuracy for oropharyngeal cancer (AUC = 0.94, 95% CI = 0.92‐0.95 in men and AUC = 0.92, 95% CI = 0.88‐0.95 in women). The 5‐year absolute risk estimates showed distinct trajectories by risk factor profiles. Based on the UK Biobank cohort, the risks of developing oropharyngeal cancer among 60 years old and HPV16 seropositive in the next 5 years ranged from 5.8% to 14.9% with an average of 8.1% for men, 1.3% to 4.4% with an average of 2.2% for women. Absolute risk was generally higher among individuals with heavy smoking, heavy drinking, HPV seropositivity and those with higher polygenic risk score. These risk models may be helpful for identifying people at high risk of developing head and neck cancer.

Development and external validation of a head and neck cancer risk prediction model

“…The discrepancy in performance could perhaps be explained by the larger sample size from the pooled studies used by Budhathoki et al for both model development and validation via randomly splitting the dataset rather than using an independent external validation dataset as conducted by our study. 47 The models using HPV serostatus were highly predictive of OPC but seemingly less predictive for overall HNC risk, as consistent with our findings. Similarly, the models using a combination of epidemiological and PRS had good predictive performance.…”

“…The models included epidemiological risk factors, HPV serostatus, polygenic risk scores (PRS) and combinations of these. 47 Our model took a different approach, opting ultimately for feasibility and practicality of use by predicting overall HNC risk using epidemiological predictors that could readily be captured in a clinical setting, as opposed to the site and gender specific models created by Budhathoki and colleagues. 47 These epidemiology models performed marginally better than our model using demographic and behavioral factors.…”

“…This allowed the investigators to detect HPV positive OPC cases at an earlier stage. 61 Suggestions for any further modeling would be to utilize HPV serology status data (ideally with the development of a "rapid" test that could be used in primary care) for use in a separate OPC risk model, as conducted by Budhathoki et al or Tota et al 47,62 However, as stated, this was out of the scope of this project. While genomic or HPV biomarkers could improve the predictive accuracy of a risk model, their inclusion limits the utility of a tool in primary care settings with limited time/resources.…”

Testing for Human Papillomaviruses in Urine, Blood, and Oral Specimens: an Update for the Laboratory

“…Blood as a specimen has attracted significant recent attention for the detection and management of HPV-associated disease because it can contain detectable biofragments that may be indicative of underlying or recurrent neoplastic disease ( 25 , 55 ). Such fragments include microRNA (miRNA), circulating tumor DNA (ctDNA), and/or circulating HPV DNA (cHPV DNA), sometimes referred to collectively as “liquid biopsies” or “cell-free DNA.” In addition, the detection of antibodies against the HPV-16 E6 protein in blood has been explored extensively in the last decade as a potential screening, diagnostic, and prognostic tool for the early detection and monitoring of HPV-AOC ( 15 , 56 ).…”