Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study

Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study

Objective To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively. Design Multicentre cohort study. Setting 36 oncology referral centres (tertiary centres with a specific gynaecological oncology un...

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Bibliographic Details
Main Authors: Calster, B. (Ben) van, Valentin, L. (Lil), Froyman, W. (Wouter), Landolfo, C. (Chiara), Ceusters, J. (Jolien), Testa, A.C. (Antonia Carla), Wynants, L. (Laure), Sladkevicius, P. (Povilas), Holsbeke, C. (Caroline) van, Domali, E. (Ekaterine), Fruscio, R. (Robert), Epstein, E. (Elizabeth), Franchi, D. (Dorella), Kudla, M.J. (Marek J.), Chiappa, V. (Valentina), Alcazar, J.L. (Juan Luis), Leone, F.P.G. (Francesco Paolo Giuseppe), Buonomo, F. (Francesca), Coccia, M.E. (Maria Elisabetta), Guerriero, S. (Stefano), Deo, N. (Nandita), Jokubkiene, L. (Ligita)
Format: info:eu-repo/semantics/article
Language:eng
Published: 2024
Subjects:
Ovarian cancer
Diganostic prediction models
Online Access:https://hdl.handle.net/10171/68859

Internet

https://hdl.handle.net/10171/68859

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