ArticleCancer management and research2019
Clinical value of ROMA index in diagnosis of ovarian cancer: meta-analysis.
Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diagnostic value of the Risk of Ovarian Malignancy Algorithm (ROMA) index in the detection of ovarian cancer in postmenopausal women: a systematic review and meta-analysis.BMC women's health · 2025Pooled it
- Automated classification of cancer from fine needle aspiration cytological image use neural networks: A meta-analysis.Diagnostic cytopathology · 2020Pooled it
- Superiority of the ROMA index over HE4 and CA125 for diagnosing ovarian cancer in a Bangladeshi cohort.Clinics (Sao Paulo, Brazil) · 2026Article
- The Evaluation, Diagnosis, and Management of Ovarian Cysts, Masses, and Their Complications in Fetuses, Infants, Children, and Adolescents.Healthcare (Basel, Switzerland) · 2025Review
- Large-scale proteomics reveals precise biomarkers for detection of ovarian cancer in symptomatic women.Scientific reports · 2024Article
- Prediction of ovarian cancer using artificial intelligence tools.Health science reports · 2024Article
- Diagnostic Utility of Selected Matrix Metalloproteinases (MMP-2, MMP-3, MMP-11, MMP-26), HE4, CA125 and ROMA Algorithm in Diagnosis of Ovarian Cancer.International journal of molecular sciences · 2024Article
- Serum anti-CFL1, anti-EZR, and anti-CYPA autoantibody as diagnostic markers in ovarian cancer.Scientific reports · 2024Article
- Review
- Exosomal biomarkers in the differential diagnosis of ovarian tumors: the emerging roles of CA125, HE4, and C5a.Journal of ovarian research · 2024Article
- Diagnostic biomarkers in ovarian cancer: advances beyond CA125 and HE4.Therapeutic advances in medical oncology · 2024Review
- Application of Nonlinear Models Combined with Conventional Laboratory Indicators for the Diagnosis and Differential Diagnosis of Ovarian Cancer.Journal of clinical medicine · 2023Article
- Article
- Molecular Management of High-Grade Serous Ovarian Carcinoma.International journal of molecular sciences · 2022Review
- Molecular Biomarkers for the Early Detection of Ovarian Cancer.International journal of molecular sciences · 2022Review
- Construction and validation of a prognostic risk model for breast cancer based on protein expression.BMC medical genomics · 2022Article
- Multiple biomarkers are more accurate than a combination of carbohydrate antigen 125 and human epididymis protein 4 for ovarian cancer screening.Obstetrics & gynecology science · 2022Article
- Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study.Cancers · 2022Article
- Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer.Cancers · 2022Article
- Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment.Communications medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe role of retrospective analysis has evolved greatly in cancer research. We undertook this network meta-analysis to evaluate retrospectively the diagnostic value of ROMA in ovarian cancer. MATERIALS AND
methodsWe systematically retrieved 56 relevant articles published about ROMA index from 2009-2018 and about ovarian cancer from China National Knowledge Infrastructure (CNKI), PubMed and EMBASE. Data were comprehensively analyzed by Rev-Man 5.3 and MetaDisc 12.4 software.
resultsData of 5,954 cases were retrieved from 23 literatures. Among them, 2,117 cases were in the ovarian cancer group and 3,837 cases in the control group. The pooled estimates for the ROMA index were sensitivity: 0.90 (95% CI: 0.88-0.93), specificity: 0.91 (95% CI: 0.89-0.94), positive predictive: 0.90 (95% CI: 0.88-0.95), negative predictive: 0.93 (95% CI: 0.91-0.95), and area under ROC curve: 0.96, compared to 0.71 (95% CI: 0.56-0.82), 0.87 (95% CI: 0.80-0.92), 0.82 (95% CI: 0.78-0.86), 0.92 (95% CI: 0.90-0.94), and 0.88 of HE4, respectively.
conclusionsThis meta-analysis confirms that the risk of ovarian malignancy algorithm can facilitate the diagnosis of ovarian cancer to some extent.
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