American Association for Cancer Research
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Figure 3 from Developing and Validating a Multivariable Prognostic-Predictive Classifier for Treatment Escalation of Oropharyngeal Squamous Cell Carcinoma: The PREDICTR-OPC Study

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posted on 2024-01-17, 08:21 authored by Hisham Mehanna, Davy Rapozo, Sandra V. von Zeidler, Kevin J. Harrington, Stuart C. Winter, Andrew Hartley, Paul Nankivell, Andrew G. Schache, Philip Sloan, Edward W. Odell, Selvam Thavaraj, Keith D. Hunter, Ketan A. Shah, Gareth J. Thomas, Anna Long, Rasoul Amel-Kashipaz, Rachel M. Brown, Brendan Conn, Gillian L. Hall, Paul Matthews, Justin Weir, Yen Yeo, Miranda Pring, Catharine M.L. West, James McCaul, Pawel Golusinski, Alice Sitch, Rachel Spruce, Nikolaos Batis, Jennifer L. Bryant, Jill M. Brooks, Terence M. Jones, Francesca Buffa, Syed Haider, Max Robinson

A–C, Prognostic and predictive assessment of risk groups predicted by multivariable survival model (trained with backward elimination using AIC) based on molecular biomarkers only with OS, when applied to the training cohort. D–F, Prognostic and predictive assessment of risk groups predicted by the molecular biomarkers only multivariable model, when applied to the validation cohort. Risk groups in the validation cohort were created using the thresholds (two-group classification: median risk score; three-group classification: tertiles of risk score) derived from the training set. Color key A, D: black = low-risk group, red = high-risk group; B, E: black = low-risk, red = intermediate (Int.)-risk, Blue=high-risk group; C, F: Red = low-risk surgery, black = low-risk no surgery, pink = high-risk surgery, blue = high-risk no surgery group. Models were adjusted for clinical covariates: T-category, N-category, smoking status, age, radiotherapy, and chemotherapy.


Cancer Research UK (CRUK)

National Institute for Health and Care Research (NIHR)



While there are several prognostic classifiers, to date, there are no validated predictive models that inform treatment selection for oropharyngeal squamous cell carcinoma (OPSCC).Our aim was to develop clinical and/or biomarker predictive models for patient outcome and treatment escalation for OPSCC. We retrospectively collated clinical data and samples from a consecutive cohort of OPSCC cases treated with curative intent at ten secondary care centers in United Kingdom and Poland between 1999 and 2012. We constructed tissue microarrays, which were stained and scored for 10 biomarkers. We then undertook multivariable regression of eight clinical parameters and 10 biomarkers on a development cohort of 600 patients. Models were validated on an independent, retrospectively collected, 385-patient cohort. A total of 985 subjects (median follow-up 5.03 years, range: 4.73–5.21 years) were included. The final biomarker classifier, comprising p16 and survivin immunohistochemistry, high-risk human papillomavirus (HPV) DNA in situ hybridization, and tumor-infiltrating lymphocytes, predicted benefit from combined surgery + adjuvant chemo/radiotherapy over primary chemoradiotherapy in the high-risk group [3-year overall survival (OS) 63.1% vs. 41.1%, respectively, HR = 0.32; 95% confidence interval (CI), 0.16–0.65; P = 0.002], but not in the low-risk group (HR = 0.4; 95% CI, 0.14–1.24; P = 0.114). On further adjustment by propensity scores, the adjusted HR in the high-risk group was 0.34, 95% CI = 0.17–0.67, P = 0.002, and in the low-risk group HR was 0.5, 95% CI = 0.1–2.38, P = 0.384. The concordance index was 0.73. We have developed a prognostic classifier, which also appears to demonstrate moderate predictive ability. External validation in a prospective setting is now underway to confirm this and prepare for clinical adoption.

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