Evaluation of HE4, CA-125, Risk of Ovarian Malignancy Algorithm (ROMA) and Risk of Malignancy Index (RMI) in the Preoperative Assessment of Patients with Adnexal Mass

Musalhi, Khawla Al; Kindi, Manal Al; Aisary, Faiza Al; Ramadhan, Fatma; Rawahi, Thuraya Al; Hatali, Khalsa Al; Mula-Abed, Waad-Allah S.

doi:10.5001/omj.2016.68

Cited by 41 publications

(43 citation statements)

References 25 publications

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“…The GOT-2 combination model CA125 + HE4 increased specificity from 68% (CA125 alone) to 79% (CA125 + HE4), hereby decreasing the number of false positives. This confirms prior knowledge that the addition of HE4 substantially increase specificity and should be used in the differential diagnosis of women with pelvic tumors [2,14,41,42]. HE4 may be affected by several factors other than cancer [15].…”

Section: Discussionsupporting

confidence: 83%

Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers

Lycke

Ulfenborg

Kristjánsdóttir

et al. 2020

JCM

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Ovarian cancer is the most lethal gynecologic cancer. Pre-diagnostic testing lacks sensitivity and specificity, and surgery is often the only way to secure the diagnosis. Exploring new biomarkers is of great importance, but the rationale of combining validated well-established biomarkers and algorithms could be a more effective way forward. We hypothesized that we can improve differential diagnostics and reduce false positives by combining (a) risk of malignancy index (RMI) with serum HE4, (b) risk of ovarian malignancy algorithm (ROMA) with a transvaginal ultrasound score or (c) adding HE4 to CA125 in a simple algorithm. With logistic regression modeling, new algorithms were explored and validated using leave-one-out cross validation. The analyses were performed in an existing cohort prospectively collected prior to surgery, 2013–2016. A total of 445 benign tumors and 135 ovarian cancers were included. All presented models improved specificity at cut-off compared to the original algorithm, and goodness of fit was significant (p < 0.001). Our findings confirm that HE4 is a marker that improves specificity without hampering sensitivity or diagnostic accuracy in adnexal tumors. We provide in this study “easy-to-use” algorithms that could aid in the triage of women to the most appropriate level of care when presenting with an unknown ovarian cyst or suspicious ovarian cancer.

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Section: Discussionsupporting

confidence: 83%

Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers

Lycke

Ulfenborg

Kristjánsdóttir

et al. 2020

JCM

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“…The gold standard for differential diagnosis of adnexal masses is surgery 4 . Preoperatively, the standard tools for detecting OC are pelvic ultrasonography and measuring serum cancer antigen 125 levels, which could be combined with the menopausal status to calculate the risk malignancy index 5 . However, in daily practice, due to the performance limitations and time consumption of the standard tools, new prognostic assessment methods that are easy to use, inexpensive, and effective are needed for these patients.…”

Section: Introductionmentioning

confidence: 99%

The platelet-to-lymphocyte ratio as a predictor of patient outcomes in ovarian cancer: a meta-analysis

Sun

et al. 2017

Climacteric

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Objectives: The platelet-to-lymphocyte ratio (PLR) is a predictive clinical biomarker for different cancers. However, the results of several studies investigating the association between the PLR and the prognosis of ovarian cancer have been inconclusive. Therefore, there is a need to conduct a metaanalysis to estimate the prognostic value of the PLR in ovarian cancer. Methods: We searched the EMBASE, Medline, PubMed, and Web of Science databases to identify clinical studies that had evaluated the association between the PLR and ovarian cancer prognosis. Outcomes evaluated included overall survival (OS) and progression-free survival (PFS). We also analyzed PLR differences between malignant ovarian masses and the controls. Results: Twelve relevant studies that comprised 2340 patients were selected for the meta-analysis. The results revealed that elevated PLR was significantly associated with poor OS (hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.05-2.56, p < 0.01) and PFS (HR 1.61, 95% CI 1.03-2.51, p < 0.01). The PLRs in malignant cases were higher than in controls (mean difference ¼ 63.57, 95% CI 39.47-87.66, p < 0.00001). Conclusion: An elevated PLR is associated with poor prognosis in patients with ovarian cancer. The PLR could be employed as a prognostic marker in patients with ovarian cancer. ARTICLE HISTORY

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“…Accuracy of the ROMA score using Abbott ARCHITECT tumour marker assays Nine studies used Abbott ARCHITECT tumour marker assays. [25][26][27][28][29][30][31][32][33] Only one study included all participants in the analysis, regardless of their final histopathological diagnosis (target condition: all malignant tumours including borderline). 32 Two studies excluded women with histopathological diagnoses other than epithelial ovarian cancer, but included women with borderline tumours.…”

Section: Methodological Quality Of Studies Assessing the Roma Scorementioning

confidence: 99%

“…Figure 1 shows the flow of studies through the review process. Fourteen studies reported data on the accuracy of the ROMA score and were included in this article, [25][26][27][28][29][30][31][32][33][34][35][36][37][38] of which nine used Abbott ARCHITECT tumour marker assays [25][26][27][28][29][30][31][32][33] and five used Roche Elecsys tumour marker assays. [34][35][36][37][38] None of the included studies used the Fujirebio Lumipulse G system.…”

Section: Overview Of Included Studiesmentioning

confidence: 99%

Clinically inappropriate post hoc exclusion of study participants from test accuracy calculations: the ROMA score, an example from a recent NICE diagnostic assessment

et al. 2018

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Objective To explore how the definition of the target condition and post hoc exclusion of participants can limit the usefulness of diagnostic accuracy studies. Methods We used data from a systematic review, conducted for a NICE diagnostic assessment of risk scores to inform secondary care decisions about specialist referral for women with suspected ovarian cancer, to explore how the definition of the target condition and post hoc exclusion of participants can limit the usefulness of diagnostic accuracy studies to inform clinical practice. Results Fourteen of the studies evaluated the ROMA score, nine used Abbott ARCHITECT tumour marker assays, five used Roche Elecsys. The summary sensitivity estimate (Abbott ARCHITECT) was highest, 95.1% (95% CI: 92.4 to 97.1%), where analyses excluded participants with borderline tumours or malignancies other than epithelial ovarian cancer and lowest, 75.0% (95% CI: 60.4 to 86.4%), where all participants were included. Results were similar for Roche Elecsys tumour marker assays. Although the number of patients involved was small, data from studies that reported diagnostic accuracy for both the whole study population and with post hoc exclusion of those with borderline or non-epithelial malignancies suggested that patients with borderline or malignancies other than epithelial ovarian cancer accounts for between 50 and 85% of false-negative ROMA scores. Conclusions Our results illustrate the potential consequences of inappropriate population selection in diagnostic studies; women with non-epithelial ovarian cancers or non-ovarian primaries, and those borderline tumours may be disproportionately represented among those with false negative, 'low risk' ROMA scores. These observations highlight the importance of giving careful consideration to how the target condition has been defined when assessing whether the diagnostic accuracy estimates reported in clinical studies will translate into clinical utility in real-world settings.

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Evaluation of HE4, CA-125, Risk of Ovarian Malignancy Algorithm (ROMA) and Risk of Malignancy Index (RMI) in the Preoperative Assessment of Patients with Adnexal Mass

Cited by 41 publications

References 25 publications

Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers

Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers

The platelet-to-lymphocyte ratio as a predictor of patient outcomes in ovarian cancer: a meta-analysis

Clinically inappropriate post hoc exclusion of study participants from test accuracy calculations: the ROMA score, an example from a recent NICE diagnostic assessment

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