External validation of a prognostic model incorporating quantitative PET image features in esophageal cancer

Foley, Kieran G., Shi, Zhenwei, Whybra, Philip, Kalendralis, Petros, Larue, Ruben, Berbee, Maaike, Sosef, Meindert N., Parkinson, Craig ORCID: https://orcid.org/0000-0003-3454-4957, Staffurth, John ORCID: https://orcid.org/0000-0002-7834-3172, Crosby, Tom D. L., Roberts, Stuart Ashley, Dekker, Andre, Wee, Leonard and Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813 2019. External validation of a prognostic model incorporating quantitative PET image features in esophageal cancer. Radiotherapy and Oncology 133 , pp. 205-212. 10.1016/j.radonc.2018.10.033

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Abstract

Aim Enhanced prognostic models are required to improve risk stratification of patients with oesophageal cancer so treatment decisions can be optimised. The primary aim was to externally validate a published prognostic model incorporating PET image features. Transferability of the model was compared using only clinical variables. Methods This was a Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis (TRIPOD) type 3 study. The model was validated against patients treated with neoadjuvant chemoradiotherapy according to the Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS) trial regimen using pre- and post-harmonised image features. The Kaplan–Meier method with log-rank significance tests assessed risk strata discrimination. A Cox proportional hazards model assessed model calibration. Primary outcome was overall survival (OS). Results Between 2010 and 2015, 449 patients were included in the development (n = 302), internal validation (n = 101) and external validation (n = 46) cohorts. No statistically significant difference in OS between patient quartiles was demonstrated in prognostic models incorporating PET image features (X2 = 1.42, df = 3, p = 0.70) or exclusively clinical variables (age, disease stage and treatment; X2 = 1.19, df = 3, p = 0.75). The calibration slope β of both models was not significantly different from unity (p = 0.29 and 0.29, respectively). Risk groups defined using only clinical variables suggested differences in OS, although these were not statistically significant (X2 = 0.71, df = 2, p = 0.70). Conclusion The prognostic model did not enable significant discrimination between the validation risk groups, but a second model with exclusively clinical variables suggested some transferable prognostic ability. PET harmonisation did not significantly change the results of model validation.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering Medicine
Publisher:	Elsevier
ISSN:	0167-8140
Date of First Compliant Deposit:	13 November 2018
Date of Acceptance:	25 October 2018
Last Modified:	08 Nov 2024 12:45
URI:	https://orca.cardiff.ac.uk/id/eprint/116688

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