Investigator

Lasai Barreñada

KU Leuven Association

About

LBLasai Barreñada
Papers(1)
Head-to-head comparis…
Collaborators(4)
Paula DhimanBen Van CalsterGary Stephen CollinsJan Yvan Jos Verbakel
Institutions(2)
Ku LeuvenUniversity of Oxford

Papers

Head-to-head comparison of the RMI and ADNEX models to estimate the risk of ovarian malignancy: a systematic review and meta-analysis of external validation studies

Objectives Assessment of Different NEoplasias in the adneXa (ADNEX) and Risk of Malignancy Index (RMI) are models that estimate the risk of malignancy in ovarian masses based on clinical and ultrasound information. The aim is to perform a meta-analysis of studies that compared the performance of the two models in the same patients (‘head-to-head comparison’). Design Systematic review and meta-analysis. Data sources Systematic literature search from publication of ADNEX model (15/10/2014) up to 31/07/2024 in Embase, Web of Science, Scopus, Medline (via PubMed) and EuropePMC. Eligibility criteria for selecting studies We included all studies that externally validated the performance of ADNEX (with or without CA125) and RMI on the same data. Data extraction and synthesis Two independent reviewers extracted data using a standardised extraction sheet. We assessed risk of bias using PROBAST. We performed random effects meta-analysis of the area under the receiver operating characteristic curve (AUC), sensitivity, specificity and clinical utility (net benefit, relative utility and probability of being useful in a hypothetical new centre) at thresholds commonly used clinically (10% risk of malignancy for ADNEX, 200 for RMI). Results We included 11 studies comprising 8271 tumours. Most studies were at high risk of bias. The summary AUC to distinguish benign from malignant tumours in operated patients for ADNEX with CA125 was 0.92 (95% CI 0.90 to 0.94) and for RMI it was 0.85 (0.81 to 0.89). Sensitivity and specificity for ADNEX with CA125 were 0.93 (0.90 to 0.96) and 0.77 (0.71 to 0.81) and for RMI, they were 0.61 (0.56 to 0.67) and 0.92 (0.89 to 0.94). The probability of the test being useful in a hypothetical new centre in operated patients was 96% for ADNEX with CA125 and 15% for RMI at the selected thresholds. Conclusions ADNEX has better discrimination and clinical utility than RMI.

12Works
1Papers
4Collaborators

Positions

Researcher

KU Leuven Association

2022–

PhD Candidate

KU Leuven · Dept of Development and Regeneration

2025–

Graduate Research Assistant (Visiting)

Memorial Sloan Kettering Cancer Center · Department of Epidemiology and Biostatistics

2024–

Visiting researcher

University Medical Center Utrecht · Julius Centrum

2021–

Machine Learning Research Technician

Basque Center for Applied Mathematics · Data Science

Education

2022

PhD Biomedical Sciences

KU Leuven · Patient Related and public health

2021

European Master in Official Statistics (EMOS)

Universidad Complutense de Madrid · Mathematics

Country

BE

Keywords
Machine learningSupervised LearningClinical Modelling
Links & IDs
0000-0001-8020-0210LinkedinBlueskyPersonal page

Scopus: 58299949400

Researcher Id: ACY-2331-2022