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Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study

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Van Calster, B., Van Hoorde, K., Valentin, L., Testa, A. C., Fischerova, D., Van Holsbeke, C., Savelli, L., Franchi, D., Epstein, E., Kaijser, J., Van Belle, V., Czekierdowski, A., Guerriero, S., Fruscio, R., Lanzani, C., Scala, F., Bourne, T., Timmerman, D., International Ovarian Tumour Analysis (IOTA) group·2014·BMJ
DOI 10.1136/bmj.g5920PMC PMC4198550
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Abstract

OBJECTIVES: To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours. DESIGN: Observational diagnostic study using prospectively collected clinical and ultrasound data. SETTING: 24 ultrasound centres in 10 countries. PARTICIPANTS: Women with an ovarian (including para-ovarian and tubal) mass and who underwent a standardised ultrasound examination before surgery. The model was developed on 3506 patients recruited between 1999 and 2007, temporally validated on 2403 patients recruited between 2009 and 2012, and then updated on all 5909 patients. MAIN OUTCOME MEASURES: Histological classification and surgical staging of the mass. RESULTS: The Assessment of Different NEoplasias in the adneXa (ADNEX) model contains three clinical and six ultrasound predictors: age, serum CA-125 level, type of centre (oncology centres v other hospitals), maximum diameter of lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites. The area under the receiver operating characteristic curve (AUC) for the classic discrimination between benign and malignant tumours was 0.94 (0.93 to 0.95) on temporal validation. The AUC was 0.85 for benign versus borderline, 0.92 for benign versus stage I cancer, 0.99 for benign versus stage II-IV cancer, and 0.95 for benign versus secondary metastatic. AUCs between malignant subtypes varied between 0.71 and 0.95, with an AUC of 0.75 for borderline versus stage I cancer and 0.82 for stage II-IV versus secondary metastatic. Calibration curves showed that the estimated risks were accurate. CONCLUSIONS: The ADNEX model discriminates well between benign and malignant tumours and offers fair to excellent discrimination between four types of ovarian malignancy. The use of ADNEX has the potential to improve triage and management decisions and so reduce morbidity and mortality associated with adnexal pathology.

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Fig 1 Calibration plots of predicted probabilities for each type of tumour. Data have been calculated using validation data (n=2403). Plots show how well the predicted probabilities (x axis) agree with observed probabilities (y axis). For perfect agreement, the calibration curve falls on the ideal diagonal line. Histograms below plots show distribution of predicted probabilities
Fig 1 Calibration plots of predicted probabilities for each type of tumour. Data have been calculated using validation data (n=2403). Plots show how well the predicted probabilities (x axis) agree with observed probabilities (y axis). For perfect agreement, the calibration curve falls on the ideal diagonal line. Histograms below plots show distribution of predicted probabilitiesCC BY-NC · PubMed Central
Fig 2 Discrimination plot of ADNEX model after it was updated on pooled dataset (n=5909). For each predicted tumour type, box plots of probabilities are presented for each confirmed tumour type (reference standard). Red vertical lines show baseline probabilities for each type of tumour. For example, the baseline probability of a benign tumour is 0.681; for most women with a benign tumour the predicted probability of a benign tumour was higher than 0.9, whereas most women with an ovarian malignancy (most notably stage II-IV cancer) had clearly lower predicted probabilities of a benign tumour
Fig 2 Discrimination plot of ADNEX model after it was updated on pooled dataset (n=5909). For each predicted tumour type, box plots of probabilities are presented for each confirmed tumour type (reference standard). Red vertical lines show baseline probabilities for each type of tumour. For example, the baseline probability of a benign tumour is 0.681; for most women with a benign tumour the predicted probability of a benign tumour was higher than 0.9, whereas most women with an ovarian malignancy (most notably stage II-IV cancer) had clearly lower predicted probabilities of a benign tumourCC BY-NC · PubMed Central

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Metadata

Authors
Van Calster, B., Van Hoorde, K., Valentin, L., Testa, A. C., Fischerova, D., Van Holsbeke, C., Savelli, L., Franchi, D., Epstein, E., Kaijser, J., Van Belle, V., Czekierdowski, A., Guerriero, S., Fruscio, R., Lanzani, C., Scala, F., Bourne, T., Timmerman, D., & International Ovarian Tumour Analysis (IOTA) group
Affiliations
  • Lund University (SE)
  • Università Cattolica del Sacro Cuore (IT)
  • IRCCS Azienda Ospedliero-Universitaria di Bologna Policlinico di Sant'Orsola (IT)
  • European Institute of Oncology (IT)
  • Karolinska University Hospital (SE)
  • Universitair Ziekenhuis Leuven (BE)
  • Medical University of Lublin (PL)
  • Azienda Ospedaliero-Universitaria Cagliari (IT)
  • University of Milan (IT)
  • Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" (IT)
ORCID
Venue
BMJ
Publisher
BMJ
Published
2014-10-15
Volume
349
Issue
oct07 3
Pages
g5920-g5920
ISSN
1756-1833 (ISSN-L)
DOI
10.1136/bmj.g5920
PMC
PMC4198550
OpenAlex
W2099878111
Cited by
510
References
57
Citations by year
2026: 52 · 2025: 60 · 2024: 70 · 2023: 54 · 2022: 55 · 2021: 59 · 2020: 36 · 2019: 24 · 2018: 30 · 2017: 19 · 2016: 27 · 2015: 19 · 2014: 4
FWCI
27.87
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • BMJ (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • BOA (University of Milano-Bicocca) (submittedVersion, cc-by-nc)
  • Lirias (KU Leuven) (submittedVersion, cc-by-nc)
  • UNICA IRIS Institutional Research Information System (University of Cagliari) (submittedVersion, other-oa)
  • Lund University Publications (Lund University) (submittedVersion, other-oa)
  • HighWire Press Open Archive (submittedVersion)
  • PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, cc-by-nc)
  • Spiral (Imperial College London) (submittedVersion, other-oa)
Funders
  • National Institute for Health and Care Research
  • Imperial College London
  • Imperial College Healthcare NHS Trust
  • Fonds Wetenschappelijk Onderzoek (G049312N)
  • iMinds
  • Malmö Högskola
  • Skånes universitetssjukhus
  • Vlaamse regering (G049312N)
  • Medical Research Council
Topics
  • Health Sciences › Medicine › Oncology › Ovarian cancer diagnosis and treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Breast Lesions and Carcinomas
Keywords
ovarian cancer, ADNEX model, preoperative risk prediction, ovarian ultrasonography, borderline ovarian tumors, CA125, surgical staging, adnexal mass, triage
MeSH terms
Adnexal Diseases, Adult, Female, Humans, Neoplasm Staging, Ovarian Neoplasms, Predictive Value of Tests, Prospective Studies, Ultrasonography, Models, Statistical, Risk Assessment

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