Recommended guidelines of diagnosis for women with an ovarian cyst or tumour

Česká verzia

Authors: D. Fischerová
Authors place of work: Gynekologicko-porodnická klinika 1. LF UK a VFN, Praha, přednosta prof. MUDr. A. Martan, DrSc.
Published in the journal: Ceska Gynekol 2014; 79(6): 477-486

Summary

Transvaginal ultrasonography is the first-line and best imaging technique for characterising adnexal masses preoperatively. The optimal approach is the subjective assessment of ultrasound images by experts. An alternative evidence-based approach to the pre-surgical diagnosis of adnexal tumours is to use simple ultrasound rules or logistic regression model LR2 developed by the International Ovarian Tumor Analysis (IOTA) group. Their test performance matches subjective assessment by experienced examiners and should be adopted as the principal test to characterize masses as benign or malignant. Measurements of serum CA 125 are not necessary for characterization of ovarian pathology in premenopausal women and are unlikely to improve the performance of experienced ultrasound examiners, even in the postmenopausal group. However, in postmenopausal patients, serum CA 125 may play a role as a second-stage test, especially in centers with less-experienced ultrasound examiners.

Keywords:
ovarian tumor, ovarian cyst, ultrasonography, guidelines, IOTA, simple rules, logistic regression model

Zdroje

1. Alcazar, JL., Pascual, MA., Olartecoechea, B., et al. IOTA simple rules for discriminating between benign and malignant adnexal masses: prospective external validation. Ultrasound Obstet Gynecol, 2013, 42, 4, p. 467–471.

2. American College of O., Gynecologists Committee on Gynecologic, P. Committee Opinion No. 477: the role of the obstetrician-gynecologist in the early detection of epithelial ovarian cancer. Obstet Gynecol, 2011, 117, 3, p. 742–726.

3. Ameye, L., Timmerman, D., Valentin, L., et al. Clinically oriented three-step strategy for assessment of adnexal pathology. Ultrasound Obstet Gynecol, 2012, 40, 5, p. 582–591.

4. Dearking, AC., Aletti, GD., McGree, ME., et al. How relevant are ACOG and SGO guidelines for referral of adnexal mass? Obstet Gynecol, 2007, 110, 4, p. 841–848.

5. DePriest, PD., Shenson, D., Fried, A., et al. A morphology index based on sonographic findings in ovarian cancer. Gynecol Oncol, 1993, 51, 1, p. 7–11.

6. Ferrazzi, E., Zanetta, G., Dordoni, D., et al. Transvaginal ultrasonographic characterization of ovarian masses: comparison of five scoring systems in a multicenter study. Ultrasound Obstet Gynecol, 1997, 10, 3, p. 192–197.

7. Finkler, NJ., Benacerraf, B., Lavin, PT., et al. Comparison of serum CA 125, clinical impression, and ultrasound in the preoperative evaluation of ovarian masses. Obstet Gynecol, 1988, 72, 4, p. 659–664.

8. Fischerová, D. Pánevní anatomie v ultrazvukovém obraze. In Calda, P. Ultrazvuková diagnostika v těhotenství a gynekologii. Praha: Aprofema, 2010, s. 380–401.

9. Fischerová, D., Pinkavová, I., Sláma, J., et al. Racionální předoperační diagnostika benigních a maligních ovariálních nádorů – zobrazovací metody, nádorové markery (přehledový článek). Čes Gynek, 2012, 77, 4, p. 272–287.

10. Granberg, S., Norstrom, A., Wikland, M. Tumors in the lower pelvis as imaged by vaginal sonography. Gynecol Oncol, 1990, 37, 2, p. 224–229.

11. Jacobs, I., Oram, D., Fairbanks, J., et al. A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. Br J Obstet Gynaecol, 1990, 97, 10, p. 922–929.

12. Kaijser, J., Bourne, T., Valentin, L., et al. Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies. Ultrasound Obstet Gynecol, 2013, 41, 1, p. 9–20.

13. Kaijser, J., Sayasneh, A., Van Hoorde, K., et al. Presurgical diagnosis of adnexal tumours using mathematical models and scoring systems: a systematic review and meta-analysis. Hum Reprod Update, 2013.

14. Kaijser, J., Van Gorp, T., Sayasneh, A., et al. Differentiating stage I epithelial ovarian cancer from benign disease in women with adnexal tumors using biomarkers or the ROMA algorithm. Gynecol Oncol, 2013, 130, 2, p. 398–389.

15. Kaijser, J., Vandecaveye, V., Deroose, C., et al. Imaging techniques for the pre-surgical diagnosis of adnexal tumors. Best Practice & Researcg Clinical Obstetrics and Gynaecology, 2014, in print.

16. Lu, C., Van Gestel, T., Suykens, JA., et al. Preoperative prediction of malignancy of ovarian tumors using least squares sup-port vector machines. Artif Intell Med, 2003, 28, 3, p. 281–306.

17. Nunes, N., Yazbek, J., Ambler, G., et al. Prospective evaluation of the IOTA logistic regression model LR2 for the diagnosis of ovarian cancer. Ultrasound Obstet Gynecol, 2012, 40, 3, p. 355–359.

18. Sassone, AM., Timor-Tritsch, IE., Artner, A., et al. Transvaginal sonographic characterization of ovarian disease: evaluation of a new scoring system to predict ovarian malignancy. Obstet Gynecol, 1991, 78, 1, p. 70–76.

19. Sayasneh, A., Kaijser, J., Preisler, J., et al. A multicenter prospective external validation of the diagnostic performance of IOTA simple descriptors and rules to characterize ovarian masses. Gynecol Oncol, 2013, 130, 1, p. 140–146.

20. Sayasneh, A., Wynants, L., Preisler, J., et al. Multicentre external validation of IOTA prediction models and RMI by operators with varied training. Br J Cancer, 2013, 108, 12, p. 2448–2454.

21. Testa, AC., Kaijser, J., Wynants, L., et al. Strategies to diagnose ovarian cancer: a meta-analysis of centre-specific data from the multicentre IOTA 3 study. Br J Cancer, in print, 2014.

22. Timmerman, D., Bourne, TH., Tailor, A., et al. A comparison of methods for preoperative discrimination between malignant and benign adnexal masses: the development of a new logistic regression model. Am J Obstet Gynecol, 1999, 181, 1, p. 57–65.

23. Timmerman, D., Verrelst, H., Bourne, TH., et al. Artificial neural network models for the preoperative discrimination between malignant and benign adnexal masses. Ultrasound Obstet Gynecol, 1999, 13, 1, p. 17–25.

24. Timmerman, D., Valentin, L., Bourne, TH., et al. Terms, definitions and measurements to describe the sonographic features of adnexal tumors: a consensus opinion from the International Ovarian Tumor Analysis (IOTA) Group. Ultrasound Obstet Gynecol, 2000, 16, 5, p. 500–505.

25. Timmerman, D., Testa, AC., Bourne, T., et al. Simple ultrasound-based rules for the diagnosis of ovarian cancer. Ultrasound Obstet Gynecol, 2008, 31, 6, p. 681–690.

26. Timmerman, D., Ameye, L., Fischerova, D., et al. Simple ultrasound rules to distinguish between benign and malignant adnexal masses before surgery: prospective validation by IOTA group. BMJ, 2010, 341, p. c6839.

27. Timmerman, D., Van Calster, B., Testa, AC., et al. Ovarian cancer prediction in adnexal masses using ultrasound-based logistic regression models: a temporal and external validation study by the IOTA group. Ultrasound Obstet Gynecol, 2010, 36, 2, p. 226–234.

28. Timmerman, D., Van Calster, B., Vergote, I., et al. Performance of the American College of Obstetricians and Gynecologists‘ ovarian tumor referral guidelines with a multivariate index assay. Obstet Gynecol, 2011, 118, 5, p. 1179–1181; author reply 1181.

29. Valentin, L., Hagen, B., Tingulstad, S., Eik-Nes, S. Comparison of ‚pattern recognition‘ and logistic regression models for discrimination between benign and malignant pelvic masses: a prospective cross validation. Ultrasound Obstet Gynecol, 2001, 18, 4, p. 357–365.

30. Valentin, L., Jurkovic, D., Van Calster, B., et al. Adding a single CA 125 measurement to ultrasound imaging performed by an experienced examiner does not improve preoperative discrimination between benign and malignant adnexal masses. Ultrasound Obstet Gynecol, 2009, 34, 3, p. 345–354.

31. Van Belle, VM., Van Calster, B., Timmerman, D., et al. A mathematical model for interpretable clinical decision support with applications in gynecology. PLoS One, 2012, 7, 3, p. e34312.

32. Van Calster, B., Timmerman, D., Bourne, T., et al. Discrimination between benign and malignant adnexal masses by specialist ultrasound examination versus serum CA-125. J Natl Cancer Inst, 2007, 99, 22, p. 1706–1714.

33. Van Calster, B., Valentin, L., Van Holsbeke, C., et al. A novel approach to predict the likelihood of specific ovarian tumor pathology based on serum CA-125: a multicenter observational study. Cancer Epidemiol Biomarkers Prev, 2011, 20, 11, p. 2420–2428.

34. Van Calster, B., Timmerman, D., Valentin, L., et al. Triaging women with ovarian masses for surgery: observational diagnostic study to compare RCOG guidelines with an International Ovarian Tumour Analysis (IOTA) group protocol. BJOG, 2012, 119, 6, p. 662–671.

35. Van Calster, B., Van Hoorde, K., Valentin, L., et al. Diagnosing ovarian cancer using the ADNEX risk model from the International Ovarian Tumour Analysis group: differentiating between benign, borderline, stage I invasive, advanced stage invasive, and secondary metastatic tumours. BMJ (in print), 2014.

36. Van Gorp, T., Veldman, J., Van Calster, B., et al. Subjective assessment by ultrasound is superior to the risk of malignancy index (RMI) or the risk of ovarian malignancy algorithm (ROMA) in discriminating benign from malignant adnexal masses. Eur J Cancer, 2012, 48, 11, p. 1649–1656.

37. Van Holsbeke, C., Daemen, A., Yazbek, J., et al. Ultrasound experience substantially impacts on diagnostic performance and confidence when adnexal masses are classified using pattern recognition. Gynecol Obstet Invest, 2010, 69, 3, p. 160–168.

38. Van Holsbeke, C., Van Calster, B., Bourne, T., et al. External validation of diagnostic models to estimate the risk of malignancy in adnexal masses. Clin Cancer Res, 2012, 18, 3, p. 815–825.

39. Verleye, L., Vergote, I., van der Zee, AG. Patterns of care in surgery for ovarian cancer in Europe. Eur J Surg Oncol, 2010, 36, Suppl 1, p. S108–114.

40. Woo, YL., Kyrgiou, M., Bryant, A., et al. Centralisation of services for gynaecological cancers – a Cochrane systematic review. Gynecol Oncol, 2012, 126, 2, p. 286–290.