ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2016
Can ROMA algorithm stratify ovarian tumor patients better when being based on specific age ranges instead of the premenopausal and postmenopausal status?
Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 11 citations in OpenAlex.
- Liquid biopsy in ovarian cancer: Catching the silent killer before it strikes.World journal of clinical oncology · 2020Review
- Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers.Journal of clinical medicine · 2020Article
- [Comparison of serum cancer antigen 125, human epididymis protein 4, ROMA, and CPH-I for diagnosis of ovarian cancer in Chinese patients with ovarian mass].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2019Article
- Biomarkers and algorithms for diagnosis of ovarian cancer: CA125, HE4, RMI and ROMA, a review.Journal of ovarian research · 2019Review
- Does the Risk of Ovarian Malignancy Algorithm Provide Better Diagnostic Performance Than HE4 and CA125 in the Presurgical Differentiation of Adnexal Tumors in Polish Women?Disease markers · 2018Article
- [Diagnostic value of CA125, HE4 and Copenhagen Index in differentiating benign from malignant epithelial ovarian tumors].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2017Article
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4 authors at 1 institution in 1 country.
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Abstract
After several years of research, HE4 was found to be characterized by slightly worse sensitivity but significantly higher specificity as compared with CA125. Further studies led to the diagnostic potential of both markers (CA125 and HE4) being combined in a single risk of malignancy algorithm (ROMA) algorithm. The objective of this study was to assess the diagnostic capabilities of the ROMA algorithm using age ranges instead of dichotomization of patients according to the pre- and postmenopausal status. A total of 413 female patients were included in the study, including 162 premenopausal and 251 postmenopausal women. Calculation of the final ROMA values was achieved by means of stepwise reduction of coefficients in the proposed formula of: %ROMA = exp(PI)/[1-exp(PI)]*100) and PI = A + W(HE4)(*)ln(HE4) + W(CA125)(*)ln (CA125) and the arrangement of values with consideration to the age group, HE4 level, differentiation of modification, and directional coefficients as well as determination of individual deviations affecting the widening of the median. The cutoff value of modified algorithm ROMA P for the entire study population was calculated from receiver operating characteristic (ROC) curve and DeLong method at the levels of 23.5 %. Marked higher sensitivity and negative predictive value (NPV) values are observed for the standard ROMA algorithm while higher specificity and positive predictive value (PPV) values are observed for the modified algorithm ROMA P. The proposed age-related modification of algorithm calculation does not require the patients being dichotomized according to their pre- or postmenopausal status, and satisfactory diagnostic values may be obtained using a single cutoff point for the entire population.
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