Journal of Ultrasound in Medicine, Vol 20, Issue 8 841-848, Copyright © 2001 by American Institute of Ultrasound in Medicine
Assessment of a new logistic model in the preoperative evaluation of adnexal masses
J. L. Alcazar, T. Errasti, C. Laparte, M. Jurado and G. Lopez-Garcia
Department of Obstetrics and Gynecology, Clinica Universitaria de Navarra, School of Medicine, University of Navarra, Pamplona, Spain.
OBJECTIVE: To assess a new logistic regression model developed to predict
malignancy in adnexal masses. METHODS: In the first part of this study, we
developed a logistic model by applying logistic regression analysis in a
series of 268 adnexal masses (203 benign and 65 malignant lesions) in 248
patients (mean age, 43.6 years; SD, 14.2 years) evaluated and treated at
our institution. Eleven parameters were entered in the logistic regression
analysis in a forward stepwise way. In the second part of the study, we
evaluated the model's diagnostic performance in a further set of 135
adnexal masses (103 benign and 32 malignant tumors) in 129 patients (mean
age, 44.4 years; SD, 14.6 years). This diagnostic performance was compared
with that of age, tumor volume, Sassone's and Ferrazzi's B-mode
ultrasonographic morphologic scoring systems, serum cancer antigen 125
level, and the tumor's lowest resistive index. Comparison was done by
calculating the area under the receiver operating characteristic curve.
RESULTS: In logistic analysis, only menopausal status, the presence of
papillary projections, the logarithm of the cancer antigen 125 value, tumor
blood flow location, and the lowest resistive index were retained in the
model. The model had the best area under the curve (0.97), significantly
higher than patient age (area under the curve, 0.78; P = .001), tumor
volume (area under the curve, 0.68; P < .0001), cancer antigen 125 (area
under the curve, 0.88; P = .008), lowest resistive index (area under the
curve, 0.85; P = .011), Ferrazzi's scoring system (area under the curve,
0.89; P = .01), and maximal peak systolic velocity (area under the curve,
0.71; P< .0001). Comparison with Sassone's scoring system (area under
the curve, 0.91) did not reach statistical significance, but a clear trend
was found (P = .116). CONCLUSIONS: The model had the best diagnostic
performance for discriminating between benign and malignant adnexal masses.
A clinical prospective evaluation is needed to confirm its actual value.