Literature DB >> 32085617

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

Alda Cunha Rola1, Azzam Taktak1,2, Antonio Eleuteri1,2, Helen Kalirai1, Heinrich Heimann1, Rumana Hussain1, Laura J Bonnett3, Christopher J Hill1, Matthew Traynor4, Martine J Jager5, Marina Marinkovic5, Gregorius P M Luyten5, Mehmet Dogrusöz5, Emine Kilic6, Annelies de Klein6, Kyra Smit6, Natasha M van Poppelen6, Bertil E Damato7,8, Armin Afshar7, Rudolf F Guthoff9, Björn O Scheef9, Vinodh Kakkassery9,10, Svetlana Saakyan11, Alexander Tsygankov11, Carlo Mosci12, Paolo Ligorio12, Silvia Viaggi13,14, Claudia H D Le Guin15, Norbert Bornfeld15, Nikolaos E Bechrakis15, Sarah E Coupland1,16.   

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.

Entities:  

Keywords:  C-statistics; LUMPO3; calibration; discrimination; external centers.; eye cancer; prognostic model; survival probabilities; uveal melanoma

Year:  2020        PMID: 32085617     DOI: 10.3390/cancers12020477

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  13 in total

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

Authors:  Sophie Thornton; Sarah E Coupland; Lisa Olohan; Julie S Sibbring; John G Kenny; Christiane Hertz-Fowler; Xuan Liu; Sam Haldenby; Heinrich Heimann; Rumana Hussain; Natalie Kipling; Azzam Taktak; Helen Kalirai
Journal:  Cancers (Basel)       Date:  2020-04-23       Impact factor: 6.639

2.  Applying Single-Cell Technology in Uveal Melanomas: Current Trends and Perspectives for Improving Uveal Melanoma Metastasis Surveillance and Tumor Profiling.

Authors:  Mona Meng Wang; Chuanfei Chen; Myoe Naing Lynn; Carlos R Figueiredo; Wei Jian Tan; Tong Seng Lim; Sarah E Coupland; Anita Sook Yee Chan
Journal:  Front Mol Biosci       Date:  2021-01-06

Review 3.  Application of Multimodal and Molecular Imaging Techniques in the Detection of Choroidal Melanomas.

Authors:  Xuying Li; Lixiang Wang; Li Zhang; Fei Tang; Xin Wei
Journal:  Front Oncol       Date:  2021-02-01       Impact factor: 6.244

4.  Prognosis Prediction of Uveal Melanoma After Plaque Brachytherapy Based on Ultrasound With Machine Learning.

Authors:  Jingting Luo; Yuning Chen; Yuhang Yang; Kai Zhang; Yueming Liu; Hanqing Zhao; Li Dong; Jie Xu; Yang Li; Wenbin Wei
Journal:  Front Med (Lausanne)       Date:  2022-01-21

5.  Small High-Risk Uveal Melanomas Have a Lower Mortality Rate.

Authors:  Rumana N Hussain; Sarah E Coupland; Helen Kalirai; Azzam F G Taktak; Antonio Eleuteri; Bertil E Damato; Carl Groenewald; Heinrich Heimann
Journal:  Cancers (Basel)       Date:  2021-05-08       Impact factor: 6.639

6.  Survival analysis following enucleation for uveal melanoma.

Authors:  Guy S Negretti; Sarega Gurudas; Beatrice Gallo; Bertil Damato; Amit K Arora; Sobha Sivaprasad; Mandeep S Sagoo
Journal:  Eye (Lond)       Date:  2021-08-02       Impact factor: 4.456

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

Authors:  Hongrun Zhang; Helen Kalirai; Amelia Acha-Sagredo; Xiaoyun Yang; Yalin Zheng; Sarah E Coupland
Journal:  Transl Vis Sci Technol       Date:  2020-09-01       Impact factor: 3.283

Review 8.  MicroRNAs and Uveal Melanoma: Understanding the Diverse Role of These Small Molecular Regulators.

Authors:  Karen Aughton; Helen Kalirai; Sarah E Coupland
Journal:  Int J Mol Sci       Date:  2020-08-06       Impact factor: 5.923

9.  Parsimonious Models for Predicting Mortality from Choroidal Melanoma.

Authors:  Bertil Damato; Antonio Eleuteri; Rumana Hussain; Helen Kalirai; Sophie Thornton; Azzam Taktak; Heinrich Heimann; Sarah E Coupland
Journal:  Invest Ophthalmol Vis Sci       Date:  2020-04-09       Impact factor: 4.799

10.  Patients presenting with metastases: stage IV uveal melanoma, an international study.

Authors:  Gaurav Garg; Paul T Finger; Tero T Kivelä; E Rand Simpson; Brenda L Gallie; Svetlana Saakyan; Anush G Amiryan; Vladimir Valskiy; Kimberly J Chin; Ekaterina Semenova; Stefan Seregard; Maria Filì; Matthew Wilson; Barrett Haik; Josep Maria Caminal; Jaume Catala-Mora; Cristina Gutiérrez; David E Pelayes; Anibal Martin Folgar; Martine Johanna Jager; Mehmet Doğrusöz; Gregorius P M Luyten; Arun D Singh; Shigenobu Suzuki
Journal:  Br J Ophthalmol       Date:  2021-01-15       Impact factor: 4.638

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