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      Diagnostic measures comparison for ovarian malignancy risk in Epithelial ovarian cancer patients: a meta-analysis

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          Abstract

          Epithelial ovarian cancer has become the most frequent cause of deaths among gynecologic malignancies. Our study elucidates the diagnostic performance of Risk of Ovarian Malignancy Algorithm (ROMA), Human epididymis secretory protein 4 (HE4) and cancer antigen (CA125). To compare the diagnostic accuracy of ROMA, HE-4 and CA125 in the early diagnosis and screening of Epithelial Ovarian Cancer. Literature search in electronic databases such as Medicine: MEDLINE (through PUBMED interface), EMBASE, Google Scholar, Science Direct and Cochrane library from January 2011 to August 2020. Studies that evaluated the diagnostic measures of ROMA, HE4 and CA125 by using Chemilumincence immunoassay or electrochemiluminescence immunoassay (CLIA or ECLIA) as index tests. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). We included 32 studies in our meta-analysis. We calculated AUC by SROC, pooled estimated like sensitivity, specificity, likelihood ratio, diagnostic odds ratio (DOR), Tau square, Cochran Q through random effect analysis and meta-regression. Data was retrieved from 32 studies. The number of studies included for HE4, CA125 and ROMA tests was 25, 26 and 22 respectively. The patients with EOC were taken as cases, and women with benign ovarian mass were taken as control, which was 2233/5682, 2315/5875 and 2281/5068 respectively for the markers or algorithm. The pooled estimates of the markers or algorithm were sensitivity: ROMA (postmenopausal) (0.88, 95% CI 0.86–0.89) > ROMA (premenopausal) 0.80, 95% CI 0.78–0.83 > CA-125(0.84, 95% CI 0.82–0.85) > HE4 (0.73, 95% CI 0.71–0.75) specificity: HE4 (0.90, 95% CI 0.89–0.91) > ROMA (postmenopausal) (0.83, 95% CI 0.81–0.84) > ROMA (premenopausal) (0.80, 95% CI 0.79–0.82) > CA125 (0.73, 95%CI 0.72–0.74), Diagnostic odd’s ratio ROMA (postmenopausal) 44.04, 95% CI 31.27–62.03, ROMA (premenopausal)-18.93, 95% CI 13.04–27.48, CA-125-13.44, 95% CI 9.97–18.13, HE4-41.03, 95% CI 27.96–60.21 AUC(SE): ROMA (postmenopausal) 0.94(0.01), ROMA (premenopausal)-0.88(0.01), HE4 0.91(0.01), CA125-0.86(0.02) through bivariate random effects model considering the heterogeneity. Our study found ROMA as the best marker to differentiate EOC from benign ovarian masses with greater diagnostic accuracy as compared to HE4 and CA125 in postmenopausal women. In premenopausal women, HE4 is a promising predictor of Epithelial ovarian cancer; however, its utilisation requires further exploration. Our study elucidates the diagnostic performance of ROMA, HE4 and CA125 in EOC. ROMA is a promising diagnostic marker of Epithelial ovarian cancers in postmenopausal women, while HE4 is the best diagnostic predictor of EOC in the premenopausal group. Our study had only EOC patients as cases and those with benign ovarian masses as controls. Further, we considered the studies estimated using the markers by the same index test: CLIA or ECLIA. The good number of studies with strict inclusion criteria reduced bias because of the pooling of studies with different analytical methods, especially for HE4. We did not consider the studies published in foreign languages. Since a few studies were available for HE4 and CA125 in the premenopausal and postmenopausal group separately, data were inadequate for sub-group analysis. Further, we did not assess these markers' diagnostic efficiency stratified by the stage and type of tumour due to insufficient studies.

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          Meta-DiSc: a software for meta-analysis of test accuracy data

          Background Systematic reviews and meta-analyses of test accuracy studies are increasingly being recognised as central in guiding clinical practice. However, there is currently no dedicated and comprehensive software for meta-analysis of diagnostic data. In this article, we present Meta-DiSc, a Windows-based, user-friendly, freely available (for academic use) software that we have developed, piloted, and validated to perform diagnostic meta-analysis. Results Meta-DiSc a) allows exploration of heterogeneity, with a variety of statistics including chi-square, I-squared and Spearman correlation tests, b) implements meta-regression techniques to explore the relationships between study characteristics and accuracy estimates, c) performs statistical pooling of sensitivities, specificities, likelihood ratios and diagnostic odds ratios using fixed and random effects models, both overall and in subgroups and d) produces high quality figures, including forest plots and summary receiver operating characteristic curves that can be exported for use in manuscripts for publication. All computational algorithms have been validated through comparison with different statistical tools and published meta-analyses. Meta-DiSc has a Graphical User Interface with roll-down menus, dialog boxes, and online help facilities. Conclusion Meta-DiSc is a comprehensive and dedicated test accuracy meta-analysis software. It has already been used and cited in several meta-analyses published in high-ranking journals. The software is publicly available at .
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            The use of multiple novel tumor biomarkers for the detection of ovarian carcinoma in patients with a pelvic mass.

            The CA125 tumor marker is used to help predict the presence of ovarian cancer in patients with an adnexal mass. Because elevated CA125 levels occur in many benign gynecologic conditions, we set out to identify other novel biomarkers that would increase the sensitivity and specificity of CA125. Serum and urine samples were obtained preoperatively from women undergoing surgery for an adnexal mass. The samples were analyzed for levels of CA125, SMRP, HE4, CA72-4, activin, inhibin, osteopontin, epidermal growth factor (EGFR), and ERBB2 (Her2) and were compared to final pathology results. Logistic regression models were estimated for all markers and combinations, with cross-validation analysis performed to obtain the sensitivities at set specificities of 90%, 95%, and 98%. Two hundred and fifty-nine patients with adnexal masses were enrolled. Of these, 233 patients were eligible for analysis with 67 invasive epithelial ovarian cancers and 166 benign ovarian neoplasms. Mean values for all marker levels except Her2 differed significantly between patients with benign masses and cancer. As a single marker, HE4 had the highest sensitivity at 72.9% (specificity 95%). Comparatively, combined CA125 and HE4 yielded the highest sensitivity at 76.4% (specificity 95%), with additional markers adding minimally to the sensitivity of this combination. HE4 was the best single marker for Stage I disease, with no increase in sensitivity when combined with CA125 or any other marker. As a single tumor marker, HE4 had the highest sensitivity for detecting ovarian cancer, especially Stage I disease. Combined CA125 and HE4 is a more accurate predictor of malignancy than either alone.
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              Evaluation of HE4, CA125, risk of ovarian malignancy algorithm (ROMA) and risk of malignancy index (RMI) as diagnostic tools of epithelial ovarian cancer in patients with a pelvic mass.

              Diagnostic factors are needed to improve the currently used serum CA125 and risk of malignancy index (RMI) in differentiating ovarian cancer (OC) from other pelvic masses, thereby achieving precise and fast referral to a tertiary center and correct selection for further diagnostics. The aim was to evaluate serum Human Epididymis protein 4 (HE4) and the risk of ovarian malignancy algorithm (ROMA) for these purposes. Serum from 1218 patients in the prospective ongoing pelvic mass study was collected prior to diagnosis. The HE4 and CA125 data were registered and evaluated separately and combined in ROMA and compared to RMI. 809 benign tumors, 79 borderline ovarian tumors, 252 OC (64 early and 188 late stage), 9 non-epithelial ovarian tumors and 69 non-ovarian cancers were evaluated. Differentiating between OC and benign disease the specificity was 62.2 (CA125), 63.2 (HE4), 76.5 (ROMA) and 81.5 (RMI) at a set sensitivity of 94.4 which corresponds to RMI=200. The areas under the curve (AUC) were 0.854 (CA125), 0.864 (HE4), 0,897 (ROMA) and 0.905 (RMI) for benign vs. early stage OC. For premenopausal benign vs. OC AUC were 0.925 (CA125), 0.905 (HE4), 0.909 (ROMA) and 0.945 (RMI). HE4 and ROMA helps differentiating OC from other pelvic masses, even in early stage OC. ROMA performs equally well as the ultrasound depending RMI and might be valuable as a first line biomarker for selecting high risk patients for referral to a tertiary center and further diagnostics. Further improvements of HE4 and ROMA in differentiating pelvic masses are still needed, especially regarding premenopausal women. Copyright © 2012. Published by Elsevier Inc.
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                Author and article information

                Contributors
                pvanamail@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 August 2021
                27 August 2021
                2021
                : 11
                : 17308
                Affiliations
                [1 ]GRID grid.449187.7, ISNI 0000 0004 4655 4957, Department of Biochemistry, , SGT Medical College Hospital and Research Institute, ; Gurugram, Haryana 122505 India
                [2 ]GRID grid.413618.9, ISNI 0000 0004 1767 6103, Department of Obstetrics and Gynaecology, , All India Institute of Medical Sciences, ; New Delhi, India
                [3 ]GRID grid.418784.6, ISNI 0000 0004 1804 4108, Department of Biochemistry, , Institute of Liver and Biliary Sciences, ; D1 ILBS Road, Vasant Kunj, New Delhi, Delhi 110070 India
                Article
                96552
                10.1038/s41598-021-96552-9
                8397730
                34453074
                73a463e7-fbeb-48af-9005-953dda32e140
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 February 2020
                : 9 August 2021
                Categories
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                © The Author(s) 2021

                Uncategorized
                biochemistry,cancer,immunology,biomarkers,diseases,oncology
                Uncategorized
                biochemistry, cancer, immunology, biomarkers, diseases, oncology

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