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All Journal Indonesian Journal of Obstetrics and Gynecology (Majalah Obstetri dan Ginekologi Indonesia)
Forbes, Darlin
Indonesian Socety of Obstetrics and Gynecology
Health Professions Medicine & Pharmacology Public Health

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The Risk of Ovarian Malignancy Algorithm (ROMA) as a Predictor of Ovarian Tumor Malignancy Forbes, Darlin; Sastradinata, Irawan; Agustiansyah, Patiyus; Theodorus, Theodorus
Indonesian Journal of Obstetrics and Gynecology Volume. 5, No. 4, October 2017
Publisher : Indonesian Socety of Obstetrics and Gynecology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (105.648 KB) | DOI: 10.32771/inajog.v5i4.568

Abstract

Object: To assess the diagnostic value of Risk of Ovarian Malignancy Algorithm (ROMA) in predicting ovarian malignancy. Methods: Diagnostic test was performed at dr. Mohammad Hoesin Hospital Palembang during June 2016 to November 2016. Data were analized with SPSS version 21.0 and Med-calc statistic. Results: A total of 57 subjects were recruited in this study. Subjects were divided into two groups: the premenopausal and postmenopausal group. Analysis with ROC curve was performed, the ROMA optimal cut-off of ROMA was 23.7% and 48.15% in the premenopausal and the post-menopausal group, respectively. With the optimal cut-off, the sensitivity was 79.41% and specivicity was 75%, positive predictive value wa 73.07% and negative predictive value 83.77% with accuracy 76.92% in diagnosing ovarian malignancy. Compared to RMI-3, the sensitivity was 65.5% and specivicity was 85.7% with accuracy 75.44%. Conclusion: ROMA is not a reliable diagnostic tools of ovarian malignancy. Keywords: CA125, HE4, ovarian cancer, risk of ovarian malignancyalgorithm/ ROMA, risk of ovarian malignancy index/RMI
The Risk of Ovarian Malignancy Algorithm (ROMA) as a Predictor of Ovarian Tumor Malignancy Forbes, Darlin; Sastradinata, Irawan; Agustiansyah, Patiyus; Theodorus, Theodorus
Indonesian Journal of Obstetrics and Gynecology Volume. 5, No. 4, October 2017
Publisher : Indonesian Socety of Obstetrics and Gynecology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (105.648 KB) | DOI: 10.32771/inajog.v5i4.568

Abstract

Object: To assess the diagnostic value of Risk of Ovarian Malignancy Algorithm (ROMA) in predicting ovarian malignancy. Methods: Diagnostic test was performed at dr. Mohammad Hoesin Hospital Palembang during June 2016 to November 2016. Data were analized with SPSS version 21.0 and Med-calc statistic. Results: A total of 57 subjects were recruited in this study. Subjects were divided into two groups: the premenopausal and postmenopausal group. Analysis with ROC curve was performed, the ROMA optimal cut-off of ROMA was 23.7% and 48.15% in the premenopausal and the post-menopausal group, respectively. With the optimal cut-off, the sensitivity was 79.41% and specivicity was 75%, positive predictive value wa 73.07% and negative predictive value 83.77% with accuracy 76.92% in diagnosing ovarian malignancy. Compared to RMI-3, the sensitivity was 65.5% and specivicity was 85.7% with accuracy 75.44%. Conclusion: ROMA is not a reliable diagnostic tools of ovarian malignancy. Keywords: CA125, HE4, ovarian cancer, risk of ovarian malignancyalgorithm/ ROMA, risk of ovarian malignancy index/RMI
Co-Authors PATIYUS AGUSTIANSYAH, PATIYUS Sastradinata, Irawan Theodorus Theodorus