Abstract
6004 Background: To date there are no validated predictive tests to inform treatment selection for patients with oropharyngeal cancer (OPC). Currently treatment is decided on disease resectability, clinician preference and patient choice. Methods: Objective To develop a predictive test to select treatment for advanced OPC. Participants Training cohort: 543 cases from 10 cancer centres. External validation cohort: 442 cases from 3 centres. Design Multivariable logistic regression of 8 clinical parameters and 10 biomarkers to develop biomarker-only and composite clinical/biomarker predictive models; subsequently validated on a separate cohort. Biomarkers scored by ≥2 ‘blinded’ pathologists. Outcomes Primary: overall survival (OS). Results: 724 males, 261 females; Median follow-up =8.8 (6.86-10.47) years. More validation cases received surgery (53.5% vs 37.9%, p=0.001) and fewer received chemo/radiotherapy (42%vs67.5%; p=0.001) compared to training cohort. The biomarker-only model performed better than the clinical/biomarker one. The final OS model - comprising p16, high risk HPV DNA ISH, survivin and tumour infiltrating lymphocyte score (TILS)- was not only prognostic for OS, but importantly was predictive for surgery+/-adjuvant RT over CRT (3yr OS 63%, vs 42.5% respectively) in the High Risk group. Treatments were equally effective in the Low Risk group. The RFS model (p16, PLK1, survivin, TILS) was prognostic, but not predictive for treatment. Validation testing confirmed good calibration and concordance (C-index =0.73; 0.68-0.79). The OS model remained prognostic and predictive for surgical treatment in High Risk group (HR=0.51; 95%CI= 0.3-0.85, p=0.01). Conclusions: To our knowledge, this is the first-ever validated model for treatment selection in HNC. Clinicians can now recommend the treatment most likely to be effective on the basis of an easily-applied, relatively inexpensive panel of 4 biomarkers. [Table: see text]
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