{
  "abstract": "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.",
  "authors": [
    {
      "affiliations": [
        "Department of Development and Regeneration, KU Leuven, Leuven, Belgium"
      ],
      "name": "Lasai Barreñada"
    },
    {
      "affiliations": [
        "Department of Development and Regeneration, KU Leuven, Leuven, Belgium"
      ],
      "name": "Ashleigh Ledger"
    },
    {
      "affiliations": [
        "Department of Gynecology and Oncology, Faculty of Medicine, Jagiellonian University Medical College, Kraków, Poland"
      ],
      "name": "Agnieszka Kotlarz"
    },
    {
      "affiliations": [
        "Centre for Statistics in Medicine, Nuffield, Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK"
      ],
      "name": "Paula Dhiman"
    },
    {
      "affiliations": [
        "Centre for Statistics in Medicine, Nuffield, Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK"
      ],
      "name": "Gary Stephen Collins"
    },
    {
      "affiliations": [
        "Department of Development and Regeneration, KU Leuven, Leuven, Belgium",
        "Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, Netherlands"
      ],
      "name": "Laure Wynants"
    },
    {
      "affiliations": [
        "Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium",
        "Leuven Unit for Health Technology Assessment Research (LUHTAR), KU Leuven, Leuven, Belgium"
      ],
      "name": "Jan Yvan Jos Verbakel"
    },
    {
      "affiliations": [
        "Department of Obstetrics and Gynaecology, Skåne University Hospital, Malmö, Sweden",
        "Department of Clinical Sciences Malmö, Lund University, Lund, Sweden"
      ],
      "name": "Lil Valentin"
    },
    {
      "affiliations": [
        "Department of Development and Regeneration, KU Leuven, Leuven, Belgium",
        "Department of Obstetrics and Gynaecology, University Hospitals Leuven, Leuven, Belgium"
      ],
      "name": "Dirk Timmerman"
    },
    {
      "affiliations": [
        "Department of Development and Regeneration, KU Leuven, Leuven, Belgium",
        "Leuven Unit for Health Technology Assessment Research (LUHTAR), KU Leuven, Leuven, Belgium"
      ],
      "name": "Ben Van Calster"
    }
  ],
  "title": "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",
  "uid": "a8545659-40ee-55ea-9c72-e4df17b7a9a8"
}