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Diagnostic accuracy of the risk of malignancy index 1 compared to the more recent IOTA ADNEX model in discriminating benign from malignant adnexal masses: a multi-centric study
Artigo | IMSEAR | ID: sea-206528
ABSTRACT

Background:

Identification of the nature of an adnexal mass can ensure optimum management. Single parameters as well as diagnostic models using a combination of several parameters are in use. The International Ovarian Tumor Analysis (IOTA) consortium has developed and published the Assessment of Different NEoplasias in the adneXa (ADNEX) model, which differentiates between benign and malignant masses. Authors conducted this study with the aim of finding a cut off value for this model in the study population and comparing the diagnostic accuracy of this model to that of the risk of malignancy (RMI).

Methods:

Women with adnexal masses admitted to the 3 medical college affiliated hospitals for surgical management were included in this study. Appropriate investigations were done to calculate the RMI-I and ADNEX score for each participant. A cut off score for the ADNEX model was determined and diagnostic accuracy tests were done for comparison.

Results:

At a cut-off of 29 for the ADNEX model and 200 for RMI model the sensitivity was 75% and 77.8, specificity 100% and 80.6%; Positive Predictive Value (PPV) 100%and 60%; Negative Predictive Value (NPV) 91% and 90.6%; Positive Likelihood ratio of infinity and 4 and a negative Likelihood Ratio of 2.8 and 2.5 respectively.

Conclusions:

The ADNEX model rates higher than the RMI in almost all tests of diagnostic accuracy and can be used for triaging, framing a referral policy and prioritizing surgery.

Texto completo: DisponíveL Índice: IMSEAR (Sudeste Asiático) Tipo de estudo: Ensaio Clínico Controlado / Estudo diagnóstico / Estudo de etiologia / Estudo prognóstico Ano de publicação: 2019 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: IMSEAR (Sudeste Asiático) Tipo de estudo: Ensaio Clínico Controlado / Estudo diagnóstico / Estudo de etiologia / Estudo prognóstico Ano de publicação: 2019 Tipo de documento: Artigo