Title: Enhancing survival prognostication in patients with choroidal melanoma by integrating pathologic, clinical and genetic predictors of metastasis
Authors: Antonio Eleuteri; Bertil Damato; Sarah E. Coupland; Azzam F.G. Taktak
Addresses: Department of Medical Physics and Clinical Engineering, Royal Liverpool University Hospital, Duncan Building, Daulby St., Liverpool L7 8XP, UK. ' Ocular Oncology Service, Royal Liverpool University Hospital, Prescot St., Liverpool, L7 8XP, UK. ' Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Duncan Building, Daulby Street, Liverpool, L69 3GA, UK. ' Department of Medical Physics and Clinical Engineering, Royal Liverpool University Hospital, 1st Floor, Duncan Building, Daulby St., Liverpool L7 8XP, UK
Abstract: Survival in choroidal melanoma was modelled using accelerated failure time models. We combined pathological, clinical and genetic data, using imputation techniques. Performance was assessed using n-fold cross-validation. Using data from 3653 patients, we generated two models; the first using clinical data only and the second using clinical and laboratory data. The c-index of discrimination was 0.75 for the clinical model and 0.79 for the laboratory model. Calibration showed good correlation between predicted and observed mortality (p-value: 0.699 for clinical model and 0.801 for laboratory model). We conclude that our model provides reasonably reliable prognosis relevant to individual patients.
Keywords: uveal melanoma; mortality; chromosome aberrations; prognostication; histology; mathematical modelling; choroidal melanoma; pathological predictors; clinical predictors; genetic predictors; patient survival.
International Journal of Biomedical Engineering and Technology, 2012 Vol.8 No.1, pp.18 - 35
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 06 Feb 2012 *