Multicenter External Validation of the Liverpool Uveal Melanoma Prognosticator Online: An OOG Collaborative Study

Abstract

Uveal melanoma (UM) is fatal in ~50% of patients as a result of disseminated disease. This study aims to externally validate the Liverpool Uveal Melanoma Prognosticator Online V3 (LUMPO3) to determine its reliability in predicting survival after treatment for choroidal melanoma when utilizing external data from other ocular oncology centers. Anonymized data of 1836 UM patients from seven international ocular oncology centers were analyzed with LUMPO3 to predict the 10-year survival for each patient in each external dataset. The analysts were masked to the patient outcomes. Model predictions were sent to an independent statistician to evaluate LUMPO3’s performance using discrimination and calibration methods. LUMPO3’s ability to discriminate between UM patients who died of metastatic UM and those who were still alive was fair-to-good, with C-statistics ranging from 0.64 to 0.85 at year 1. The pooled estimate for all external centers was 0.72 (95% confidence interval: 0.68 to 0.75). Agreement between observed and predicted survival probabilities was generally good given differences in case mix and survival rates between different centers. Despite the differences between the international cohorts of patients with primary UM, LUMPO3 is a valuable tool for predicting all-cause mortality in this disease when using data from external centers.

Targeted Next-Generation Sequencing of 117 Routine Clinical Samples Provides Further Insights into the Molecular Landscape of Uveal Melanoma

“…Furthermore, chr3 results obtained using the NGS panel were comparable to previous MLPA and MSA analyses. We recommend that this bespoke NGS panel ultimately replaces MLPA/MSA testing in routine labs, with the possibility of incorporating molecular data into prognostic tools-e.g., the LUMPO (Liverpool Uveal Melanoma Prognosticator Online), which was recently externally validated in a multicentre study [29].…”

MicroRNAs and Uveal Melanoma: Understanding the Diverse Role of These Small Molecular Regulators

“…In UM, chromosomal mutations and genetic aberrations in the primary tumour can predict with relatively high accuracy whether a UM has a low or high risk of metastasis. When incorporated with other prognostic parameters, i.e., clinical and histological characteristics, expected survival for an individual patient can be predicted [113]. This is a robust approach that has been translated into the clinic; however, it requires tissue samples obtained by fine-needle biopsies, tumour resections or enucleations [114].…”

Piloting a Deep Learning Model for Predicting Nuclear BAP1 Immunohistochemical Expression of Uveal Melanoma from Hematoxylin-and-Eosin Sections

“…Other well-known prognostic variables for UM, such as patient age and gender, were not considered in this work. In the future, we intend to develop a multivariable prognostic model, similar to (or a revision of) the Liverpool-developed prognostic algorithm, LUMPO3, 46 which could incorporate the DL tool and its analysis of various morphological, IHC, and genetic parameters of UM.…”