Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


Background

Several diagnostic prediction models to help clinicians discriminate between benign and malignant adnexal masses are available. This study is a head-to-head comparison of the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model with that of the Risk of Ovarian Malignancy Algorithm (ROMA).

Methods

This is a retrospective study based on prospectively included consecutive women with an adnexal tumour scheduled for surgery at five oncology centres and one non-oncology centre in four countries between 2015 and 2019. The reference standard was histology. Model performance for ADNEX and ROMA was evaluated regarding discrimination, calibration, and clinical utility.

Results

The primary analysis included 894 patients, of whom 434 (49%) had a malignant tumour. The area under the receiver operating characteristic curve (AUC) was 0.92 (95% CI 0.88-0.95) for ADNEX with CA125, 0.90 (0.84-0.94) for ADNEX without CA125, and 0.85 (0.80-0.89) for ROMA. ROMA, and to a lesser extent ADNEX, underestimated the risk of malignancy. Clinical utility was highest for ADNEX. ROMA had no clinical utility at decision thresholds <27%.

Conclusions

ADNEX had better ability to discriminate between benign and malignant adnexal tumours and higher clinical utility than ROMA.

Clinical trial registration

clinicaltrials.gov NCT01698632 and NCT02847832.

References 


Articles referenced by this article (52)


Show 10 more references (10 of 52)

Citations & impact 


This article has not been cited yet.

Impact metrics

Alternative metrics

Altmetric item for https://www.altmetric.com/details/158557465
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/158557465

Data 


Data behind the article

This data has been text mined from the article, or deposited into data resources.

Similar Articles 


To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.


Funding 


Funders who supported this work.

Fonds Wetenschappelijk Onderzoek (1)

Fonds Wetenschappelijk Onderzoek (Research Foundation Flanders) (1)

Kom Op Tegen Kanker Internal Funds

    Linbury Trust Grant

      National Institute for Health Research (NIHR)

        Vetenskapsrådet (1)

        Vetenskapsrådet (Swedish Research Council) (1)

        the Malmö General Hospital Foundation for fighting against cancer Avtal om läkarutbildning och forskning (ALF)-medel Landstingsfinansierad Regional Forskning