Literature DB >> 31311023

Risk of Ovarian Malignancy Algorithm versus Risk Malignancy Index-I for Preoperative Assessment of Adnexal Masses: A Systematic Review and Meta-Analysis.

Enrique Chacón1, Joana Dasí2, Carolina Caballero3, Juan Luis Alcázar4.   

Abstract

PURPOSE: To perform a systematic review and meta-analysis of studies comparing the diagnostic accuracy of Risk of Ovarian Malignancy Algorithm (ROMA) and risk of malignancy index (RMI) for detecting ovarian cancer.
METHODS: A systematic review and meta-analysis was performed according to PRISMA statement. A search for studies evaluating the diagnostic performance of ROMA and RMI-I indices for detecting ovarian malignancy from January 2010 to October 2018 was performed in the PubMed/MEDLINE and Web of Science databases. The quality of the studies was evaluated by the Quality Assessment of Diagnostic Accuracy Studies 2.
RESULTS: Sixty-six citations were identified. After exclusions, 8 papers comprising 2,662 women (1,319 premenopausal and 1,343 postmenopausal) were ultimately included. The mean prevalence of ovarian malignancy was 29.0% in premenopausal women and 51.0% in postmenopausal women. High risk of bias for patient selection was observed for most studies. ROMA and RMI-I had a similar diagnostic performance in postmenopausal women (pooled sensitivity [87 vs. 77%] and specificity [75 vs. 85%], respectively. p = 0.29). In premenopausal women, RMI-I showed better specificity than ROMA (89 vs. 78%, p = 0.022) with similar sensitivity (73 vs. 80%, p= 0.27). Significant heterogeneity was found for sensitivity and specificity in comparisons of both groups.
CONCLUSIONS: ROMA and RMI-I have similar diagnostic performance for detecting ovarian cancer in women presenting with an adnexal mass. However, RMI-I showed a higher specificity than ROMA in premenopausal women. Notwithstanding, as the risk of bias is high in most studies, our results should be interpreted with caution.
© 2019 S. Karger AG, Basel.

Entities:  

Keywords:  Diagnosis; Ovarian malignancy; Risk malignancy index; Risk of ovarian malignancy algorithm

Year:  2019        PMID: 31311023     DOI: 10.1159/000501681

Source DB:  PubMed          Journal:  Gynecol Obstet Invest        ISSN: 0378-7346            Impact factor:   2.031


  7 in total

Review 1.  Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis.

Authors:  Julio Vara; Nabil Manzour; Enrique Chacón; Ana López-Picazo; Marta Linares; Maria Ángela Pascual; Stefano Guerriero; Juan Luis Alcázar
Journal:  Cancers (Basel)       Date:  2022-06-27       Impact factor: 6.575

2.  A Novel Classifier Based on Urinary Proteomics for Distinguishing Between Benign and Malignant Ovarian Tumors.

Authors:  Maowei Ni; Jie Zhou; Zhihui Zhu; Jingtao Yuan; Wangang Gong; Jianqing Zhu; Zhiguo Zheng; Huajun Zhao
Journal:  Front Cell Dev Biol       Date:  2021-08-30

3.  Diagnostic Performance of Risk of Malignancy Algorithm (ROMA), Risk of Malignancy Index (RMI) and Expert Ultrasound Assessment in a Pelvic Mass Classified as Inconclusive by International Ovarian Tumour Analysis (IOTA) Simple Rules.

Authors:  Siew Fei Ngu; Yu Ka Chai; Ka Man Choi; Tsin Wah Leung; Justin Li; Gladys S T Kwok; Mandy M Y Chu; Ka Yu Tse; Vincent Y T Cheung; Hextan Y S Ngan; Karen K L Chan
Journal:  Cancers (Basel)       Date:  2022-02-05       Impact factor: 6.639

4.  Protein Panel of Serum-Derived Small Extracellular Vesicles for the Screening and Diagnosis of Epithelial Ovarian Cancer.

Authors:  Huiling Lai; Yunyun Guo; Liming Tian; Linxiang Wu; Xiaohui Li; Zunxian Yang; Shuqin Chen; Yufeng Ren; Shasha He; Weipeng He; Guofen Yang
Journal:  Cancers (Basel)       Date:  2022-07-30       Impact factor: 6.575

Review 5.  Diagnostic Models Combining Clinical Information, Ultrasound and Biochemical Markers for Ovarian Cancer: Cochrane Systematic Review and Meta-Analysis.

Authors:  Clare F Davenport; Nirmala Rai; Pawana Sharma; Jon Deeks; Sarah Berhane; Sue Mallett; Pratyusha Saha; Rita Solanki; Susan Bayliss; Kym Snell; Sudha Sundar
Journal:  Cancers (Basel)       Date:  2022-07-26       Impact factor: 6.575

Review 6.  ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors.

Authors:  Dirk Timmerman; François Planchamp; Tom Bourne; Chiara Landolfo; Andreas du Bois; Luis Chiva; David Cibula; Nicole Concin; Daniela Fischerova; Wouter Froyman; Guillermo Gallardo Madueño; Birthe Lemley; Annika Loft; Liliana Mereu; Philippe Morice; Denis Querleu; Antonia Carla Testa; Ignace Vergote; Vincent Vandecaveye; Giovanni Scambia; Christina Fotopoulou
Journal:  Int J Gynecol Cancer       Date:  2021-06-10       Impact factor: 3.437

7.  Kinetics of HE4 and CA125 as prognosis biomarkers during neoadjuvant chemotherapy in advanced epithelial ovarian cancer.

Authors:  Jorge A Alegría-Baños; José C Jiménez-López; Arely Vergara-Castañeda; David F Cantú de León; Alejandro Mohar-Betancourt; Delia Pérez-Montiel; Gisela Sánchez-Domínguez; Mariana García-Villarejo; César Olivares-Pérez; Ángel Hernández-Constantino; Acitlalin González-Santiago; Miguel Clara-Altamirano; Liz Arela-Quispe; Diddier Prada-Ortega
Journal:  J Ovarian Res       Date:  2021-07-19       Impact factor: 4.234

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.