Risk-prediction models in postmenopausal patients with symptoms of suspected ovarian cancer in the UK (ROCkeTS): a multicentre, prospective diagnostic accuracy study
Authors
D. Timmerman (ORCID: https://orcid.org/0000-0002-3707-6645)
Jonathan J Deeks (ORCID: https://orcid.org/0000-0002-8850-1971)
Risk-prediction models in postmenopausal patients with symptoms of suspected ovarian cancer in the UK (ROCkeTS): a multicentre, prospective diagnostic accuracy study
D. Timmerman, Jonathan J Deeks, Partha Pratim Sengupta, Tom Bourne et al.
Citations
31 citations
Journal
The Lancet Oncology
Topics
Ovarian cancer diagnosis and treatment
Field-Weighted Citation Impact (FWCI)
16.65
article
Risk-prediction models in postmenopausal patients with symptoms of suspected ovarian cancer in the UK (ROCkeTS): a multicentre, prospective diagnostic accuracy study
D. Timmerman, Jonathan J Deeks, Partha Pratim Sengupta, Tom Bourne, Sean Kehoe, Lauren Sturdy, A. Gentry-Maharaj, Ryan Ottridge, Sudha Sundar, Ridhi Agarwal, Caroline Rick, Katie Scandrett, Richard D Neal, Fong Lien Kwong, S. Johnson, Usha Menon, Clare Davenport, Hilary Stobart, Ben Van Calster, Susan Mallett, Radhika Selvi-Vikram
article en
31 citations
Abstract
No abstract available for this paper.
Publication Tag
The Lancet OncologyVol. 25(10)
Institutions
University of Nottingham (GB), University of Exeter (GB), Sandwell & West Birmingham Hospitals NHS Trust (GB), County Durham and Darlington NHS Foundation Trust (GB), West Hertfordshire Hospitals NHS Trust (GB), University Hospital Southampton NHS Foundation Trust (GB), University of Oxford (GB), Collaborative Group (United States) (US), Cancer Research UK Clinical Trials Unit (GB), University College London (GB), Imperial College London (GB), University of Birmingham (GB)
Funders
AstraZeneca, Samsung Medison, National Institute for Health and Care Research, Department of Health and Social Care, University College London, KU Leuven, Samsung, Medical Research Council, Health Technology Assessment Programme