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Diagnostic Accuracy of the Risk of Ovarian Malignancy Algorithm in Clinical Practice at a Single Hospital in Korea.

ABSTRACT: BACKGROUND:The risk of ovarian malignancy algorithm (ROMA) is used for assessing ovarian cancer risk in women with a pelvic mass. Its diagnostic accuracy is variable. We investigated whether the clinically acceptable minimal sensitivity of >80.0% could be obtained with the suggested cutoff of 7.4%/25.3% for pre/postmenopausal women and with adjusted cutoffs set to a specificity of ≥75.0% or a sensitivity of 95.0%, in a hospital with a lower ovarian cancer (OC) prevalence than previously reported. METHODS:ROMA scores were calculated from measurements of human epididymis protein 4 and cancer antigen 125 in blood specimens from 443 patients with a pelvic mass. The ROMA-based risk group was compared against biopsy (N=309) or clinical follow-up with imaging (N=134) results. The ROMA sensitivity and specificity for predicting epithelial OC (EOC) and borderline ovarian tumor (BOT) were calculated for the suggested and adjusted cutoff values. RESULTS:When targeting BOT and EOC, the prevalence was 7.4% and sensitivity and specificity at the suggested cutoff were 63.6% and 90.7%, respectively. Sensitivity was 81.8% at the 4.65%/13.71% cutoff set to a specificity of 75.0%. When targeting only EOC, the prevalence was 4.1% and sensitivity and specificity at the suggested cutoff were 77.8% and 89.4%, respectively. Sensitivity was 88.9% at the 4.78%/14.35% cutoff set to a specificity of 75.0%. CONCLUSIONS:The sensitivity of ROMA was lower than expected when using the suggested cutoff. When using the adjusted cutoff, its sensitivity reached 80.0%.

SUBMITTER: Park H

PROVIDER: S-EPMC6340842 | biostudies-other | 2019 May

REPOSITORIES: biostudies-other

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Diagnostic Accuracy of the Risk of Ovarian Malignancy Algorithm in Clinical Practice at a Single Hospital in Korea.

Park Haeil H Shin Jae Eun JE Lee Dae Woo DW Kim Min Jeong MJ Lee Hae Nam HN

Annals of laboratory medicine 20190501 3

<h4>Background</h4>The risk of ovarian malignancy algorithm (ROMA) is used for assessing ovarian cancer risk in women with a pelvic mass. Its diagnostic accuracy is variable. We investigated whether the clinically acceptable minimal sensitivity of >80.0% could be obtained with the suggested cutoff of 7.4%/25.3% for pre/postmenopausal women and with adjusted cutoffs set to a specificity of ≥75.0% or a sensitivity of 95.0%, in a hospital with a lower ovarian cancer (OC) prevalence than previously ...[more]

PMID: 30623617

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Project description:BackgroundsRisk for Ovarian Malignancy Algorithm (ROMA) and Human epididymis protein 4 (HE4) appear to be promising predictors for epithelial ovarian cancer (EOC), however, conflicting results exist in the diagnostic performance comparison among ROMA, HE4 and CA125.MethodsRemote databases (MEDLINE/PUBMED, EMBASE, Web of Science, Google Scholar, the Cochrane Library and ClinicalTrials.gov) and full texts bibliography were searched for relevant abstracts. All studies included were closely assessed with the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2). EOC predictive value of ROMA was systematically evaluated, and comparison among the predictive performances of ROMA, HE4 and CA125 were conducted within the same population. Sensitivity, specificity, DOR (diagnostic odds ratio), LR ± (positive and negative likelihood ratio) and AUC (area under receiver operating characteristic-curve) were summarized with a bivariate model. Subgroup analysis and sensitivity analysis were used to explore the heterogeneity.ResultsData of 7792 tests were retrieved from 11 studies. The overall estimates of ROMA for EOC predicting were: sensitivity (0.89, 95% CI 0.84-0.93), specificity (0.83, 95% CI 0.77-0.88), and AUC (0.93, 95% CI 0.90-0.95). Comparison of EOC predictive value between HE4 and CA125 found, specificity: HE4 (0.93, 95% CI 0.87-0.96) > CA125 (0.84, 95% CI 0.76-0.90); AUC: CA125 (0.88, 95% CI 0.85-0.91) > HE4 (0.82, 95% CI 0.78-0.85). Comparison of OC predictive value between HE4 and CA125 found, AUC: CA125 (0.89, 95% CI 0.85-0.91) > HE4 (0.79, 95% CI 0.76-0.83). Comparison among the three tests for EOC prediction found, sensitivity: ROMA (0.86, 95%CI 0.81-0.91) > HE4 (0.80, 95% CI 0.73-0.85); specificity: HE4 (0.94, 95% CI 0.90-0.96) > ROMA (0.84, 95% CI 0.79-0.88) > CA125 (0.78, 95%CI 0.73-0.83).ConclusionsROMA is helpful for distinguishing epithelial ovarian cancer from benign pelvic mass. HE4 is not better than CA125 either for EOC or OC prediction. ROMA is promising predictors of epithelial ovarian cancer to replace CA125, but its utilization requires further exploration.

Project description:Background In 2017, the Liver Imaging Reporting and Data System (LI-RADS) included an algorithm for the assessment of hepatocellular carcinoma (HCC) treated with local-regional therapy. The aim of the algorithm was to enable standardized evaluation of treatment response to guide subsequent therapy. However, the performance of the algorithm has not yet been validated in the literature. Purpose To evaluate the performance of the LI-RADS 2017 Treatment Response algorithm for assessing the histopathologic viability of HCC treated with bland arterial embolization. Materials and Methods This retrospective study included patients who underwent bland arterial embolization for HCC between 2006 and 2016 and subsequent liver transplantation. Three radiologists independently assessed all treated lesions by using the CT/MRI LI-RADS 2017 Treatment Response algorithm. Radiology and posttransplant histopathology reports were then compared. Lesions were categorized on the basis of explant pathologic findings as either completely (100%) or incompletely (<100%) necrotic, and performance characteristics and predictive values for the LI-RADS Treatment Response (LR-TR) Viable and Nonviable categories were calculated for each reader. Interreader association was calculated by using the Fleiss κ. Results A total of 45 adults (mean age, 57.1 years ± 8.2; 13 women) with 63 total lesions were included. For predicting incomplete histopathologic tumor necrosis, the accuracy of the LR-TR Viable category for the three readers was 60%-65%, and the positive predictive value was 86%-96%. For predicting complete histopathologic tumor necrosis, the accuracy of the LR-TR Nonviable category was 67%-71%, and the negative predictive value was 81%-87%. By consensus, 17 (27%) of 63 lesions were categorized as LR-TR Equivocal, and 12 of these lesions were incompletely necrotic. Interreader association for the LR-TR category was moderate (κ = 0.55; 95% confidence interval: 0.47, 0.67). Conclusion The Liver Imaging Reporting and Data System 2017 Treatment Response algorithm had high predictive value and moderate interreader association for the histopathologic viability of hepatocellular carcinoma treated with bland arterial embolization when lesions were assessed as Viable or Nonviable. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Gervais in this issue.

Dataset Information

Diagnostic Accuracy of the Risk of Ovarian Malignancy Algorithm in Clinical Practice at a Single Hospital in Korea.

Publications

Diagnostic Accuracy of the Risk of Ovarian Malignancy Algorithm in Clinical Practice at a Single Hospital in Korea.

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