Comparison of ‘pattern recognition’ and logistic regression models for discrimination between benign and malignant pelvic masses: a prospective cross validation

Abstract

Results Pattern recognition performed better than the two logistic regression models (sensitivity around 85%, specificity around 90%). Using a risk of malignancy of > 50% to indicate malignancy (as suggested in the original publications), the sensitivity of the Tailor model was 69% and the specificity 88% (n = 133). The corresponding values for the Timmerman model were 62% and 79% (n = 82). The receiver operating characteristics curves showed the two logistic regression models to have similar diagnostic properties (area under the curve, 0.87 vs. 0.84; P = 0.25; n = 79).The diagnostic performance of the mathematical models was much poorer in this study than in those in which the models had been created. Conclusion

External Validation of Diagnostic Models to Estimate the Risk of Malignancy in Adnexal Masses

“…Unfortunately, when tested prospectively, most models did worse than in the studies where they had been created, and they did not achieve the performance of experienced sonologists using subjective assessment of the ultrasound image (4,(15)(16)(17)(18). The Royal College of Obstetricians and Gynecologists (19) and a recent review article by Geomini and colleagues (20) recommend the risk of malignancy index (RMI; ref.…”

A Study of Adnexal Masses in Pregnancy

“…18 However, when the diagnostic performance of risk-stratification models are compared to "pattern recognition" (i.e., subjective evaluation of grayscale and Doppler flow features), the latter is found to perform better, yielding a sensitivity of around 85% and specificity of around 90%. 19 In our study, ultrasonological morphology was found to be accurate in 100% cases that were detected prior to surgery.…”

Comparison of Two Ovarian Malignancy Prediction Models Based on Age Sonographic Findings and Serum Ca125 Measurement

“…Sonography alone is highly sensitive in detection of ovarian mass malignancy, but its specificity is relatively low (Valentin, 2001;Diamandis, 2003;Valentin, 2004;Enakpene, 2009 DOI:http://dx.doi.org/10.7314/APJCP.2012.13.8.4199 Ovarian Malignancy Prediction Models Based on Age Sonographic and Serum CA125 serum CA125 measurement is a specific test in prediction of ovarian malignancy (Edgell, 2010).…”