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
|
Preview |
PDF
- Accepted Post-Print Version
Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (590kB) | Preview |
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: | Schools > Engineering Schools > 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 |
Citation Data
Cited 23 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
 |
Edit Item |
Altmetric
Altmetric