Developing and validating a multivariable prognostic-predictive classifier for treatment escalation of oropharyngeal squamous cell carcinoma: the PREDICTR-OPC study

Hisham Mehanna*, Davy Rapozo, Sandra Ventorin von Zeidler, Kevin Harrington, Stuart Winter, Andrew Hartley, Paul Nankivell, Andrew Schache, Phil Sloan, Edward Odell, Selvam Thavaraj, Keith Hunter, Ketan Shah, Gareth Thomas, Anna Long, Rasoul Amel-Kashipaz, Rachel Brown, Brendan Conn, Gillian Hall, Paul MatthewsJustin Weir, Yen Yeo, Miranda Pring, Catharine West, James McCaul, Pawel Golusinski, Alice Sitch, Rachel Spruce, Nikos Batis, Jennifer Bryant, Jill Brooks, Terence M Jones, Francesca Buffa, Syed Haider, Max Robinson

*Corresponding author for this work

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Abstract

Purpose: Whilst 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.

Methods: We retrospectively collated clinical data, and samples from a consecutive cohort of OPSCC cases treated with curative intent at ten secondary care centres in UK and Poland between 1999-2012. 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.

Results: 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 HPV DNA in-situ hybridisation, and tumour-infiltrating lymphocytes predicted benefit from combined surgery+adjuvant chemo/radiotherapy over primary chemoradiotherapy in the high-risk group (3yr OS 63.1% versus 41.1%, respectively, HR= 0.32, 95% 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, CI 95% = 0.1-2.38, p =0.384. The Concordance index was 0.73.

Conclusions: 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.
Original languageEnglish
Pages (from-to)356–367
JournalClinical Cancer Research
Volume30
Issue number2
Early online date23 Oct 2023
DOIs
Publication statusPublished - 17 Jan 2024

Bibliographical note

Acknowledgments:
This research was funded by a research grant from Cancer Research UK (C19677/A12617). Professor Mehanna was supported as a National Institute for Health Research (NIHR) Senior Investigator. The views expressed in this article are those of the author(s) and not necessarily those of the NIHR, or the Department of Health and Social Care.

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