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 Matthews; Justin 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

doi:10.1158/1078-0432.CCR-23-1013

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 language	English
Pages (from-to)	356–367
Journal	Clinical Cancer Research
Volume	30
Issue number	2
Early online date	23 Oct 2023
DOIs	https://doi.org/10.1158/1078-0432.CCR-23-1013
Publication status	Published - 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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10.1158/1078-0432.CCR-23-1013Licence: Creative Commons: Attribution (CC BY)

MehannaH2024Developing Final published version, 7.61 MBLicence: Creative Commons: Attribution (CC BY)

Biomarker Classifiers to Predict Prognosis Following Treatment of Oropharyngeal Carcinoma (PredicTr-OPC)
Mehanna, H. (Principal Investigator)
Cancer Research UK
1/12/12 → 30/11/14
Project: Research

Cite this

Mehanna, H., Rapozo, D., Zeidler, S. V. V., Harrington, K., Winter, S., Hartley, A., Nankivell, P., Schache, A., Sloan, P., Odell, E., Thavaraj, S., Hunter, K., Shah, K., Thomas, G., Long, A., Amel-Kashipaz, R., Brown, R., Conn, B., Hall, G., ... Robinson, M. (2024). Developing and validating a multivariable prognostic-predictive classifier for treatment escalation of oropharyngeal squamous cell carcinoma: the PREDICTR-OPC study. Clinical Cancer Research, 30(2), 356–367. https://doi.org/10.1158/1078-0432.CCR-23-1013

@article{d342d4de618c41e09d18fbd511fb5004,

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

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.",

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

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.",

year = "2024",

month = jan,

day = "17",

doi = "10.1158/1078-0432.CCR-23-1013",

language = "English",

volume = "30",

pages = "356–367",

journal = "Clinical Cancer Research",

issn = "1078-0432",

publisher = "American Association for Cancer Research",

number = "2",

}

Mehanna, H, Rapozo, D, Zeidler, SVV, Harrington, K, Winter, S, Hartley, A, Nankivell, P, Schache, A, Sloan, P, Odell, E, Thavaraj, S, Hunter, K, Shah, K, Thomas, G, Long, A, Amel-Kashipaz, R, Brown, R, Conn, B, Hall, G, Matthews, P, Weir, J, Yeo, Y, Pring, M, West, C, McCaul, J, Golusinski, P, Sitch, A, Spruce, R, Batis, N, Bryant, J, Brooks, J, Jones, TM, Buffa, F, Haider, S & Robinson, M 2024, 'Developing and validating a multivariable prognostic-predictive classifier for treatment escalation of oropharyngeal squamous cell carcinoma: the PREDICTR-OPC study', Clinical Cancer Research, vol. 30, no. 2, pp. 356–367. https://doi.org/10.1158/1078-0432.CCR-23-1013

Developing and validating a multivariable prognostic-predictive classifier for treatment escalation of oropharyngeal squamous cell carcinoma: the PREDICTR-OPC study. / Mehanna, Hisham; Rapozo, Davy; Zeidler, Sandra Ventorin von et al.
In: Clinical Cancer Research, Vol. 30, No. 2, 17.01.2024, p. 356–367.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Developing and validating a multivariable prognostic-predictive classifier for treatment escalation of oropharyngeal squamous cell carcinoma

T2 - the PREDICTR-OPC study

AU - Mehanna, Hisham

AU - Rapozo, Davy

AU - Zeidler, Sandra Ventorin von

AU - Harrington, Kevin

AU - Winter, Stuart

AU - Hartley, Andrew

AU - Nankivell, Paul

AU - Schache, Andrew

AU - Sloan, Phil

AU - Odell, Edward

AU - Thavaraj, Selvam

AU - Hunter, Keith

AU - Shah, Ketan

AU - Thomas, Gareth

AU - Long, Anna

AU - Amel-Kashipaz, Rasoul

AU - Brown, Rachel

AU - Conn, Brendan

AU - Hall, Gillian

AU - Matthews, Paul

AU - Weir, Justin

AU - Yeo, Yen

AU - Pring, Miranda

AU - West, Catharine

AU - McCaul, James

AU - Golusinski, Pawel

AU - Sitch, Alice

AU - Spruce, Rachel

AU - Batis, Nikos

AU - Bryant, Jennifer

AU - Brooks, Jill

AU - Jones, Terence M

AU - Buffa, Francesca

AU - Haider, Syed

AU - Robinson, Max

N1 - 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.

PY - 2024/1/17

Y1 - 2024/1/17

N2 - 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.

AB - 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.

U2 - 10.1158/1078-0432.CCR-23-1013

DO - 10.1158/1078-0432.CCR-23-1013

M3 - Article

C2 - 37870417

SN - 1078-0432

VL - 30

SP - 356

EP - 367

JO - Clinical Cancer Research

JF - Clinical Cancer Research

IS - 2

ER -

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

Abstract

Bibliographical note

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Projects

Biomarker Classifiers to Predict Prognosis Following Treatment of Oropharyngeal Carcinoma (PredicTr-OPC)

Cite this