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All Journal Indonesian Journal of Obstetrics and Gynecology (Majalah Obstetri dan Ginekologi Indonesia)
Sastradinata, Irawan
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
p53 Gene Codon 72 Polymorphisms among Cervical Carcinoma Patients Basyar, Rustham; Saleh, Agustria Z; Sastradinata, Irawan; Yuwono, Yuwono
Indonesian Journal of Obstetrics and Gynecology Volume. 3, No. 3, July 2015
Publisher : Indonesian Socety of Obstetrics and Gynecology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (145.277 KB) | DOI: 10.32771/inajog.v3i3.48

Abstract

Objective: To identify the association between p53 gene codon 72 polymorphism and cervical carcinoma. Method: An analytic observational study with case-control design, from November 2013 until March 2014 in the Department of Obstetrics and Gynecology and Microbiology Laboratory Faculty of Medicine, Sriwijaya University, Dr. Moh. Hoesin Hospital Palembang. Result: In total there are 100 samples analyzed consisting of 50 subjects and 50 control groups. Genotype distribution in subject group are 54% Arg/Arg, 42% Pro/Arg and 4% Pro/Pro, and in control group are 36% Arg/Arg, 46% Pro/Arg and 18% Pro/Pro. Arg/Arg genotype is at risk of cervical carcinoma 6.7 times higher compared with Pro/Pro genotype (p=0.013; OR 6.75; 95% CI 1.34-34.94). Arg allele in the p53 gene codon 72 increase the risk of cervical carcinoma 2.6 times more than Pro allele. Conclusion: Proline mutation to Arginine in gene p53 P72R is one of the risk factor for cervical carcinoma. Keywords: arginine, cervical carcinoma, gene p53 codon 72, polymorphism, proline
p53 Gene Codon 72 Polymorphisms among Cervical Carcinoma Patients Basyar, Rustham; Saleh, Agustria Z; Sastradinata, Irawan; Yuwono, Yuwono
Indonesian Journal of Obstetrics and Gynecology Volume. 3, No. 3, July 2015
Publisher : Indonesian Socety of Obstetrics and Gynecology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (145.277 KB) | DOI: 10.32771/inajog.v3i3.48

Abstract

Objective: To identify the association between p53 gene codon 72 polymorphism and cervical carcinoma. Method: An analytic observational study with case-control design, from November 2013 until March 2014 in the Department of Obstetrics and Gynecology and Microbiology Laboratory Faculty of Medicine, Sriwijaya University, Dr. Moh. Hoesin Hospital Palembang. Result: In total there are 100 samples analyzed consisting of 50 subjects and 50 control groups. Genotype distribution in subject group are 54% Arg/Arg, 42% Pro/Arg and 4% Pro/Pro, and in control group are 36% Arg/Arg, 46% Pro/Arg and 18% Pro/Pro. Arg/Arg genotype is at risk of cervical carcinoma 6.7 times higher compared with Pro/Pro genotype (p=0.013; OR 6.75; 95% CI 1.34-34.94). Arg allele in the p53 gene codon 72 increase the risk of cervical carcinoma 2.6 times more than Pro allele. Conclusion: Proline mutation to Arginine in gene p53 P72R is one of the risk factor for cervical carcinoma. Keywords: arginine, cervical carcinoma, gene p53 codon 72, polymorphism, proline
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 Forbes, Darlin PATIYUS AGUSTIANSYAH, PATIYUS Rustham Basyar, Rustham Saleh, Agustria Z Theodorus Theodorus Yuwono Yuwono