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Ovarian cancer prediction in adnexal masses using ultrasound-based logistic regression models: a temporal and external validation study by the IOTA group

Timmerman, D.; Van Calster, B.; Testa, A. C.; Guerriero, S.; Fischerova, D.; Lissoni, A. A.; Van Holsbeke, C.; Fruscio, R.; Czekierdowski, A. and Jurkovic, D., et al. (2010) In Ultrasound in Obstetrics & Gynecology 36(2). p.226-234
Abstract
Objectives The aims of the study were to temporally and externally validate the diagnostic performance of two logistic regression models containing clinical and ultrasound variables in order to estimate the risk of malignancy in adnexal masses, and to compare the results with the subjective interpretation of ultrasound findings carried out by an experienced ultrasound examiner ('subjective assessment'). Methods Patients with adnexal masses, who were put forward by the 19 centers participating in the study, underwent a standardized transvaginal ultrasound examination by a gynecologist or a radiologist specialized in ultrasonography. The examiner prospectively collected information on clinical and ultrasound variables, and classified each... (More)
Objectives The aims of the study were to temporally and externally validate the diagnostic performance of two logistic regression models containing clinical and ultrasound variables in order to estimate the risk of malignancy in adnexal masses, and to compare the results with the subjective interpretation of ultrasound findings carried out by an experienced ultrasound examiner ('subjective assessment'). Methods Patients with adnexal masses, who were put forward by the 19 centers participating in the study, underwent a standardized transvaginal ultrasound examination by a gynecologist or a radiologist specialized in ultrasonography. The examiner prospectively collected information on clinical and ultrasound variables, and classified each mass as benign or malignant on the basis of subjective evaluation of ultrasound findings. The gold standard was the histology of the mass with local clinicians deciding whether to operate on the basis of ultrasound results and the clinical picture. The models' ability to discriminate between malignant and benign masses was assessed, together with the accuracy of the risk estimates. Results Of the 1938 patients included in the study, 1396 had benign, 373 had primary invasive, 111 had borderline malignant and 58 had metastatic tumors. On external validation (997 patients from 12 centers), the area under the receiver operating characteristics curve (AUC) for a model containing 12 predictors (LR1) was 0.956, for a reduced model with six predictors (LR2) was 0.949 and for subjective assessment was 0.949. Subjective assessment gave a positive likelihood ratio of 11.0 and a negative likelihood ratio of 0.14. The corresponding likelihood ratios for a previously derived probability threshold (0.1) were 6.84 and 0.09 for LR1, and 6.36 and 0.10 for LR2. On temporal validation (941 patients from seven centers), the AUCs were 0.945 (LR1), 0.918 (LR2) and 0.959 (subjective assessment). Conclusions Both models provide excellent discrimination between benign and malignant masses. Because the models provide an objective and reasonably accurate risk estimation, they may improve the management of women with suspected ovarian pathology. Copyright (C) 2010 ISUOG. Published by John Wiley & Sons, Ltd. (Less)
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keywords
ultrasonography, sensitivity and specificity, ovarian neoplasms, color Doppler ultrasonography, logistic models
in
Ultrasound in Obstetrics & Gynecology
volume
36
issue
2
pages
226 - 234
publisher
John Wiley & Sons
external identifiers
  • wos:000281086100017
  • scopus:77956138548
ISSN
1469-0705
DOI
10.1002/uog.7636
language
English
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yes
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6a9786f0-0ec0-4b0b-ae1b-79e76df3bfe2 (old id 1673522)
date added to LUP
2010-09-23 11:02:20
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2018-06-24 04:12:43
@article{6a9786f0-0ec0-4b0b-ae1b-79e76df3bfe2,
  abstract     = {Objectives The aims of the study were to temporally and externally validate the diagnostic performance of two logistic regression models containing clinical and ultrasound variables in order to estimate the risk of malignancy in adnexal masses, and to compare the results with the subjective interpretation of ultrasound findings carried out by an experienced ultrasound examiner ('subjective assessment'). Methods Patients with adnexal masses, who were put forward by the 19 centers participating in the study, underwent a standardized transvaginal ultrasound examination by a gynecologist or a radiologist specialized in ultrasonography. The examiner prospectively collected information on clinical and ultrasound variables, and classified each mass as benign or malignant on the basis of subjective evaluation of ultrasound findings. The gold standard was the histology of the mass with local clinicians deciding whether to operate on the basis of ultrasound results and the clinical picture. The models' ability to discriminate between malignant and benign masses was assessed, together with the accuracy of the risk estimates. Results Of the 1938 patients included in the study, 1396 had benign, 373 had primary invasive, 111 had borderline malignant and 58 had metastatic tumors. On external validation (997 patients from 12 centers), the area under the receiver operating characteristics curve (AUC) for a model containing 12 predictors (LR1) was 0.956, for a reduced model with six predictors (LR2) was 0.949 and for subjective assessment was 0.949. Subjective assessment gave a positive likelihood ratio of 11.0 and a negative likelihood ratio of 0.14. The corresponding likelihood ratios for a previously derived probability threshold (0.1) were 6.84 and 0.09 for LR1, and 6.36 and 0.10 for LR2. On temporal validation (941 patients from seven centers), the AUCs were 0.945 (LR1), 0.918 (LR2) and 0.959 (subjective assessment). Conclusions Both models provide excellent discrimination between benign and malignant masses. Because the models provide an objective and reasonably accurate risk estimation, they may improve the management of women with suspected ovarian pathology. Copyright (C) 2010 ISUOG. Published by John Wiley & Sons, Ltd.},
  author       = {Timmerman, D. and Van Calster, B. and Testa, A. C. and Guerriero, S. and Fischerova, D. and Lissoni, A. A. and Van Holsbeke, C. and Fruscio, R. and Czekierdowski, A. and Jurkovic, D. and Savelli, L. and Vergote, I. and Bourne, T. and Van Huffel, S. and Valentin, Lil},
  issn         = {1469-0705},
  keyword      = {ultrasonography,sensitivity and specificity,ovarian neoplasms,color Doppler ultrasonography,logistic models},
  language     = {eng},
  number       = {2},
  pages        = {226--234},
  publisher    = {John Wiley & Sons},
  series       = {Ultrasound in Obstetrics & Gynecology},
  title        = {Ovarian cancer prediction in adnexal masses using ultrasound-based logistic regression models: a temporal and external validation study by the IOTA group},
  url          = {http://dx.doi.org/10.1002/uog.7636},
  volume       = {36},
  year         = {2010},
}