Predicting oral cancer survival—Development and validation of an Asia‐Pacific nomogram

Author:

Wang Weilan1,Zhang Qingpeng1,Thomson Peter2ORCID,Sharma Dileep3,Ramamurthy Poornima2,Choi Siu‐Wai4ORCID

Affiliation:

1. School of Data Science The City University of Hong Kong Hong Kong China

2. College of Medicine and Dentistry James Cook University Cairns Queensland Australia

3. Oral Health, School of Health Sciences University of Newcastle Callaghan New South Wales Australia

4. Department of Orthopaedics and Traumatology University of Hong Kong Hong Kong China

Abstract

AbstractBackgroundNomograms are graphical calculating devices that predict response to treatment during cancer management. Oral squamous cell carcinoma (OSCC) is a lethal and deforming disease of rising incidence and global significance. The aim of this study was to develop a nomogram to predict individualized OSCC survival using a population‐based dataset obtained from Queensland, Australia and externally validated using a cohort of OSCC patients treated in Hong Kong.MethodsClinico‐pathological data for newly diagnosed OSCC patients, including age, sex, tumour site and grading, were accessed retrospectively from the Queensland Cancer Registry (QCR) in Australia and the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong. Multivariate Cox proportional hazard regression was used to construct overall survival (OS) and cancer‐specific survival (CSS) prediction models. Nomograms were internally validated using 10‐fold cross validation, and externally validated against the Hong Kong dataset.ResultsData from 9885 OSCC patients in Queensland and 465 patients from Hong Kong were analysed. All clinico‐pathological variables significantly influenced survival outcomes. Nomogram calibration curves demonstrated excellent agreement between predicted and actual probability for Queensland patients. External validation in the Hong Kong population demonstrated slightly poorer nomogram performance, but predictive power remained strong.ConclusionBased upon readily available data documenting patient demographic and clinico‐pathological variables, predictive nomograms offer pragmatic aid to clinicians in individualized treatment planning and prognosis assessment in contemporary OSCC management.

Publisher

Wiley

Subject

Periodontics,Cancer Research,Otorhinolaryngology,Oral Surgery,Pathology and Forensic Medicine

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