scholarly journals Lesion size affects diagnostic performance of IOTA logistic regression models, IOTA simple rules and risk of malignancy index in discriminating between benign and malignant adnexal masses

2012 ◽  
Vol 40 (3) ◽  
pp. 345-354 ◽  
Author(s):  
A. Di Legge ◽  
A. C. Testa ◽  
L. Ameye ◽  
B. Van Calster ◽  
A. A. Lissoni ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Diagnostic Performance ◽  
Lesion Size ◽  
Adnexal Masses ◽  
Logistic Regression Models ◽  
Simple Rules ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index

Comparison of the diagnostic performances of the Assessment of Different NEoplasias in the adneXa model, Simple Rules model, and Risk of Malignancy Index for adnexal masses in a gynecological oncology centre  in China

2020 ◽  
Author(s):  
Le Qian ◽  
Qinwen Du ◽  
Meijiao Jiang ◽  
Fei Yuan ◽  
Hui Chen ◽  
...  
Keyword(s):  
Prediction Models ◽  
Roc Curves ◽  
Chinese Patients ◽  
Malignant Tumours ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Adnexal Masses ◽  
Simple Rules ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index

Abstract Background This study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of adnexal mass. Methods This single-centre, retrospective study of diagnostic accuracy involved 486 patients. All ultrasound examinations were analyzed and the prediction models were applied. Pathology was the clinical reference standard. The diagnostic performances of prediction models were measured by evaluating receiver-operating characteristic (ROC) curves, sensitivities, specificities, positive and negative predictive values, positive and negative likelihood ratios, and diagnostic odds ratios. Results To discriminate benign and malignant tumours, areas under the ROC curves (AUCs) for ADNEX models were 0.94 (95% CI: 0.92–0.96) with CA125 and 0.94 (95% CI: 0.91–0.96) without CA125, which were significantly higher than the AUCs for RMI I-III: 0.87 (95% CI: 0.83–0.90), 0.83 (95% CI: 0.80–0.86), and 0.82 (95% CI: 0.78–0.86), (all P < 0.0001). At a cut-off of 10%, the ADNEX model with CA125 had the highest sensitivity (0.93; 95% CI: 0.87–0.97) compared with the other models. The SRs model achieved a sensitivity of 0.93 (95% CI: 0.86–0.97) and a specificity of 0.86 (95% CI: 0.82–0.89) when inconclusive diagnoses (11.7%) were classified as malignant. Conclusion ADNEX and SRs models were excellent at characterising adnexal masses which were superior to the RMI in Chinese patients.

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