Comparison of the risk of ovarian malignancy algorithm and Copenhagen Index for the preoperative assessment of Japanese women with ovarian tumors.

OBJECTIVE: To compare the risk of ovarian malignancy algorithm (ROMA) and Copenhagen Index (CPH-I) in their ability to distinguish epithelial ovarian cancer (EOC) and malignant ovarian tumors (MLOT) from benign ovarian tumors (BeOT) in Japanese women. METHODS: Patients with pathologically diagnosed ovarian tumors were included in this study. The study validated the diagnostic performance of ROMA and CPH-I. RESULTS: Among the 463 Japanese women included in this study, 312 had BeOT, 99 had EOC, and 52 had other MLOT. The receiver-operator characteristic (ROC) area under the curve (AUCs) of ROMA (0.89) and CPH-I (0.89) for distinguishing EOC from BeOT were significantly higher than that of CA125 (0.82) (CA 125 vs. ROMA; p = 0.002, vs. CPH-I; p < 0.001). The ROC-AUCs of ROMA (0.82) and CPH-I (0.81) for distinguishing MLOT from BeOT were significantly higher than that of CA125 (0.75) (CA 125 vs. ROMA: p = 0.003, vs. CPH-I: p < 0.001). The sensitivity (SN)/specificity (SP) of ROMA and CPH-I for distinguishing EOC from BeOT at standard cut-off points were 69%/90%, and 69%/90%, respectively, those for distinguishing MLOT from BeOT were 54%/90%, and 55%/90%, respectively. CONCLUSION: ROMA and CPH-I performed comparably well and better than CA125 in distinguishing EOC from BeOT in Japanese women. ROMA and CHP-I should be used with caution in practical situations, where all histological possibilities for must be considered, because the SNs of ROMA and CPH-I were only 54% and 55%.

Diagnostic performance of CA125, HE4, ROMA, and CPH-I in identifying primary ovarian cancer.

AIMS: To evaluate the ability of carbohydrate antigen 125 (CA125), human epididymis protein 4 (HE4), risk of ovarian malignancy algorithm (ROMA), and Copenhagen Index (CPH-I) to identify primary ovarian cancer (OC) from borderline and benign ovarian tumors (OTs) and explore ideal cutoff points. METHODS: A total of 684 OTs containing 276 OC patients, 116 ovarian borderline OTs and 292 benign OTs patients who underwent surgery in our hospital were included. We retrospectively searched the results of CA125 and HE4 before patients' surgery from the hospital's electronic medical records system. ROMA and CPH-I were calculated according to their menopausal status and age, respectively. Diagnostic performance of these four were assessed by drawing receiver operating characteristic (ROC) curves. RESULTS: CA125, HE4, ROMA, and CPH-I were all significantly higher in OC women compared with borderline OTs (p < 0.001), followed by benign OTs (p < 0.001). Area under the curves (AUCs) for distinguishing OC were 0.850 (0.818-0.882), 0.891 (0.865-0.916), 0.910 (0.888-0.933) and 0.906 (0.882-0.930), respectively, and the corresponding ideal cutoff values for CA125, HE4, ROMA, and CPH-I were 132.5, 68.6, 23.8, and 6.4, respectively. The difference between ROMA and CPH-I was not significant (p = 0.97), but both were higher than CA125 and HE4 (p < 0.05). HE4 showed a significantly higher AUC than CA125 (p < 0.05). For postmenopausal women, CA125 performed equivalently to ROMA (p = 0.73) and CPH-I (p = 0.91). CONCLUSIONS: In identifying patients with OC, ROMA and CPH-I outperformed single tumor marker. The diagnostic performance of HE4 was significantly higher than that of CA125. CA125 was more suitable for postmenopausal women.

Value of the Copenhagen index in the diagnosis of malignant adnexal tumors: A meta-analysis.

Ovarian cancer is a common gynecological malignant tumor. Early diagnosis is important for the prognosis of patients with ovarian cancer. To evaluate the accuracy of the Copenhagen Index (CPH-I) in detecting malignant adnexal tumors and to compare the diagnostic accuracy of CPH-I and the Risk of Ovarian Malignancy Algorithm (ROMA). PubMed, Web of Science, and Cochrane Library databases were used to retrieve eligible studies. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the (summary receiver operating characteristic) curve (AUC) were 0.81, 0.88, 6.61, 0.22, 30.43, and 0.91, respectively, in diagnosing malignant adnexal tumors. In addition, using ROMA, the sensitivity, specificity, and AUC were 0.83, 0.85, and 0.90, respectively. CPH-I showed high accuracy in diagnosing malignant adnexal tumors, which could be an alternative method with similar efficacy to ROMA. CPH-I was more advantageous in diagnosing adnexal tumors in postmenopausal women.

Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study.

Ovarian cancer (OC) is the most lethal genital malignancy in women. We aimed to develop and validate new proteomic-based models for non-invasive diagnosis of OC. We also compared them to the modified Risk of Ovarian Malignancy Algorithm (ROMA-50), the Copenhagen Index (CPH-I) and our earlier Proteomic Model 2017. Biomarkers were assessed using bead-based multiplex technology (Luminex®) in 356 women (250 with malignant and 106 with benign ovarian tumors) from five European centers. The training cohort included 279 women from three centers, and the validation cohort 77 women from two other centers. Of six previously studied serum proteins (CA125, HE4, osteopontin [OPN], prolactin, leptin, and macrophage migration inhibitory factor [MIF]), four contributed significantly to the Proteomic Model 2021 (CA125, OPN, prolactin, MIF), while leptin and HE4 were omitted by the algorithm. The Proteomic Model 2021 revealed a c-index of 0.98 (95% CI 0.96, 0.99) in the training cohort; however, in the validation cohort it only achieved a c-index of 0.82 (95% CI 0.72, 0.91). Adding patient age to the Proteomic Model 2021 constituted the Combined Model 2021, with a c-index of 0.99 (95% CI 0.97, 1) in the training cohort and a c-index of 0.86 (95% CI 0.78, 0.95) in the validation cohort. The Full Combined Model 2021 (all six proteins with age) yielded a c-index of 0.98 (95% CI 0.97, 0.99) in the training cohort and a c-index of 0.89 (95% CI 0.81, 0.97) in the validation cohort. The validation of our previous Proteomic Model 2017, as well as the ROMA-50 and CPH-I revealed a c-index of 0.9 (95% CI 0.82, 0.97), 0.54 (95% CI 0.38, 0.69) and 0.92 (95% CI 0.85, 0.98), respectively. In postmenopausal women, the three newly developed models all achieved a specificity of 1.00, a positive predictive value (PPV) of 1.00, and a sensitivity of >0.9. Performance in women under 50 years of age (c-index below 0.6) or with normal CA125 (c-index close to 0.5) was poor. CA125 and OPN had the best discriminating power as single markers. In summary, the CPH-I, the two combined 2021 Models, and the Proteomic Model 2017 showed satisfactory diagnostic accuracies, with no clear superiority of either model. Notably, although combining values of only four proteins with age, the Combined Model 2021 performed comparably to the Full Combined Model 2021. The models confirmed their exceptional diagnostic performance in women aged ≥50. All models outperformed the ROMA-50.

Copenhagen index (CPH-I) is more favorable than CA125, HE4, and risk of ovarian malignancy algorithm (ROMA): Nomogram prediction models with clinical-ultrasonographic feature for diagnosing ovarian neoplasms.

Background: We aimed to analyze the benign and malignant identification efficiency of CA125, HE4, risk of ovarian malignancy algorithm (ROMA), Copenhagen Index (CPH-I) in ovarian neoplasms and establish a nomogram to improve the preoperative evaluation value of ovarian neoplasms. Methods: A total of 3,042 patients with ovarian neoplasms were retrospectively classified according to postoperative pathological diagnosis [benign, n = 2389; epithelial ovarian cancer (EOC), n = 653]. The patients were randomly divided into training and test cohorts at a ratio of 7:3. Using CA125, HE4, ROMA, and CPH-I, Receiver operating characteristic (ROC) curves corresponding to different truncation values were calculated and compared, and optimal truncation values were selected. Clinical and imaging risk factors were calculated using univariate regression, and significant variables were selected for multivariate regression analysis combined with ROMA and CPH-I. Nomograms were constructed to predict the occurrence of EOC, and the accuracy was assessed by external validation. Results: When the cutoff value of CA125, HE4, ROMA, and CPH-I was 100 U/ml, 70 pmol/L, 12.5/14.4% (premenopausal/postmenopausal) and 5%, respectively, the AUC was 0.674, 0.721, 0.750 and 0.769, respectively. From univariate regression, the clinical risk factors were older age, menopausal status, higher birth rate, hypertension, and diabetes; imaging risk factors were multilocular tumors, solid nodules, bilateral tumors, larger tumor diameter, and ascites. The AUC of the nomogram containing ROMA and CPH-I was 0.8914 and 0.9114, respectively, which was better than the prediction accuracies of CA125, HE4, ROMA, and CPH-I alone. The nomogram with CPH-I was significantly better than that with ROMA (P < 0.001), and a nomogram decision curve analysis (DCA) containing CPH-I seemed to have better clinical benefits than ROMA. For external validation of this nomogram containing ROMA and CPH-I, the C-indices were 0.889 and 0.900, and the calibration curves were close to 45°, showing good agreement with the predicted values. Conclusion: We conclude that CPH-I and ROMA have higher diagnostic values in the preoperative diagnosis of EOC than other single tumor markers like CA125 or HE4. A nomogram based on CPH-I and ROMA with clinical and ultrasonic indicators had a better diagnostic value, and the CPH-I nomogram had the highest diagnostic efficacy.

Assessing the diagnostic performance of four ovarian malignancy prediction risk models in differentiating benign and malignant ovarian masses in a tertiary hospital / Philippine Journal of Obstetrics and Gynecology

Introduction@#Ovarian cancer is considered the most lethal gynecologic malignancy because it is difficult to diagnose in its early stages. Ovarian malignancy prediction models may be useful in discriminating between benign and malignant masses, allowing for accurate and timely referral as well as proper therapeutic care@*Objective@#To evaluate the diagnostic performance of the four ovarian prediction models: Risk of Malignancy Index‑4 (RMI‑4), Risk of Ovarian Malignancy Algorithm (ROMA), Copenhagen Index (CPH‑I), and International Ovarian Tumor Analysis (IOTA)‑Assessment of Different NEoplasias in the AdneXa (ADNEX) in identifying malignant and benign ovarian masses@*Materials and Methods@#This was a retrospective, cross‑sectional, analytical diagnostic study in a tertiary hospital between January 2017 and December 2020. Receiver operating characteristic (ROC) curves, area under the curves (AUCs), sensitivities, specificities, positive and negative predictive values, and positive and negative likelihood ratios were used to assess the diagnostic performance of the prediction models.@*Results@#We analyzed a total of 248 patients. One hundred and sixty‑one (65%) had benign tumors, 28 (11%) had borderline, and 59 (24%) had malignant tumors. The AUCs of all models were all above 90%, but when compared to the other models, CPH‑I had the best estimate. RMI‑4 had the highest sensitivity (98.3%) in diagnosing malignancy. For appropriately diagnosing benign disease, the IOTA‑ADNEX model exhibited the highest specificity (92.1%). Overall, RMI‑4 had the lowest diagnostic accuracy (74.6%), whereas IOTA‑ADNEX had the greatest (93.2%).@*Conclusion@#The four malignancy prediction models in this study were all useful tools in discriminating between benign and malignant ovarian tumors. IOTA‑ADNEX, CPH‑I, and ROMA all demonstrated overlapping diagnostic performances indicating that they are equal in that regard. In terms of sensitivity in predicting malignancy, RMI‑4 was the most sensitive. CPH‑I is the predictor with the best overall estimate. Lastly, IOTA‑ADNEX was the most specific, and displayed highest diagnostic accuracy among the four

Copenhagen Index versus ROMA in preoperative ovarian malignancy risk stratification: Result from the first Vietnamese prospective cohort study.

OBJECTIVES: This study aimed to evaluate the diagnostic performances of the Copenhagen Index (CPH-I) and Risk of Ovarian Malignancy Algorithm (ROMA) in the preoperative prediction of ovarian cancer. METHODS: In a prospective cohort study, data were collected from 475 patients with ovarian masses diagnosed by gynecologic examination / ultrasound who were hospitalized at the Departments of Obstetrics and Gynecology, Hue University of Medicine and Pharmacy Hospital and Hue Central Hospital, Vietnam, between January 2018 and June 2020. ROMA and CPH-I were calculated based on measurements of serum carbohydrate antigen (CA-125) and human epididymis protein (HE4). The final diagnosis was based on clinical features, radiologic and histologic findings, and the International Federation of Gynecology and Obstetrics (FIGO) 2014 stages of ovarian cancer were recorded. Matching the values of ROMA and CPH-I to postoperative histopathology reports resulted in the preoperative prediction values. RESULTS: Among the 475 women, 408 had benign tumors, 5 had borderline tumors and 62 had malignant tumors. The two indices showed similar discriminatory performances with no significant differences (p > 0.05). At an optimal cut-off, the sensitivities/specificities of ROMA and CPH-I for ovarian cancer diagnosis were 74.2% and 91.8%, 87.1% and 78.5%, respectively. The optimal cut-off for CPH-I was 1.89%. The areas under the ROC curves (AUCs) of ROMA and CPH-I were 0.882 (95% CI: 0.849-0.909) and 0.898 (95% CI: 0.867-0.924), respectively. CONCLUSIONS: The introduction of the Copenhagen Index to help stratify the malignancy risk of ovarian tumors, irrespective of menopausal status, might be applied as a simple alternative with a similar efficacy to ROMA in clinical practice.

[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].

OBJECTIVE: To compare the performance of serum cancer antigen 125 (CA125), human epididymis protein 4 (HE4), Risk of Ovarian Malignancy Algorithm (ROMA) and Copenhagen index (CPH-I) for differential diagnosis of benign and malignant diseases in patients with ovarian mass. METHODS: We retrospectively analyzed the data of 719 women with pelvic mass, and the performance of preoperative serum levels of CA125 and HE4, ROMA and CPH-I for differential diagnosis of the masses was compared. RESULTS: Of the 710 women analyzed, 531 were diagnosed with benign ovarian lesions, 44 with borderline ovarian tumors (BOTs), 119 with epithelial ovarian cancers (EOCs), and 25 with non-EOCs. In differentiating ovarian cancer (OC) and BOT from benign lesions, the area under the receiver-operator characteristic (ROC) curve (AUC) was 0.854 for HE4, 0.856 for ROMA, 0.854 for CPH-I, and 0.792 for CA125, demonstrating better diagnostic performance of HE4, ROMA, and CPH-I than CA125 alone; the diagnostic sensitivity was 56.9% for HE4, 70.2% for CA125, 69.1% for ROMA, and 63.8% for CPH-I; the specificity was the best with HE4 (94.4%) and CPH-I (94.7%). In sub-analysis of EOC vs benign lesions, the AUCs of HE4, ROMA, and CPH-I increased to 0.946, 0.947, and 0.943, respectively, all greater than that of CA125 (0.888). In other sub-analyses, HE4, ROMA, and CPH-I all showed greater AUCs than CA125 alone. CONCLUSIONS: This study confirms the accuracy of HE4, ROMA, and CPH-I for differentiating malignant from benign ovarian mass, and all these 3 tests show better performance than CA125. Furthermore, HE4 and CPH-I is superior to ROMA and CA125 in terms of specificity, while CA125 and ROMA have better diagnostic sensitivities.

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 / 南方医科大学学报

OBJECTIVE@#To compare the performance of serum cancer antigen 125 (CA125), human epididymis protein 4 (HE4), Risk of Ovarian Malignancy Algorithm (ROMA) and Copenhagen index (CPH-I) for differential diagnosis of benign and malignant diseases in patients with ovarian mass.@*METHODS@#We retrospectively analyzed the data of 719 women with pelvic mass, and the performance of preoperative serum levels of CA125 and HE4, ROMA and CPH-I for differential diagnosis of the masses was compared.@*RESULTS@#Of the 710 women analyzed, 531 were diagnosed with benign ovarian lesions, 44 with borderline ovarian tumors (BOTs), 119 with epithelial ovarian cancers (EOCs), and 25 with non-EOCs. In differentiating ovarian cancer (OC) and BOT from benign lesions, the area under the receiver-operator characteristic (ROC) curve (AUC) was 0.854 for HE4, 0.856 for ROMA, 0.854 for CPH-I, and 0.792 for CA125, demonstrating better diagnostic performance of HE4, ROMA, and CPH-I than CA125 alone; the diagnostic sensitivity was 56.9% for HE4, 70.2% for CA125, 69.1% for ROMA, and 63.8% for CPH-I; the specificity was the best with HE4 (94.4%) and CPH-I (94.7%). In sub-analysis of EOC benign lesions, the AUCs of HE4, ROMA, and CPH-I increased to 0.946, 0.947, and 0.943, respectively, all greater than that of CA125 (0.888). In other sub-analyses, HE4, ROMA, and CPH-I all showed greater AUCs than CA125 alone.@*CONCLUSIONS@#This study confirms the accuracy of HE4, ROMA, and CPH-I for differentiating malignant from benign ovarian mass, and all these 3 tests show better performance than CA125. Furthermore, HE4 and CPH-I is superior to ROMA and CA125 in terms of specificity, while CA125 and ROMA have better diagnostic sensitivities.

Comparison of the Copenhagen Index versus ROMA for the preoperative assessment of women with ovarian tumors.

OBJECTIVE: To compare the Copenhagen Index (CPH-I) and the Risk of Ovarian Malignancy Algorithm (ROMA) in the differential diagnosis of ovarian tumors. METHODS: In a retrospective study, data were reviewed from women with ovarian tumors who attended University Hospital Brno, Czech Republic, between July 2011 and June 2015. The women were classified into the benign tumor group or malignant tumor group (borderline and malignant tumors). Serum levels of CA125 and HE4 were extracted from medical records. The two tumor indices were calculated using relevant clinical data. RESULTS: Among 267 included women, 110 had benign tumors, 42 had borderline ovarian tumors, and 115 had malignant tumors. The two indices showed similar discriminatory performance with no significant differences (P>0.05). In the differentiation of benign tumors from all stages of borderline tumor and ovarian cancer, ROMA showed a sensitivity of 71% at a specificity of 88%, whereas CPH-I showed a sensitivity of 69% at a specificity of 85%. CONCLUSION: CPH-I is a potential tumor index that is independent of menopausal status. It might be applied as a simple alternative to ROMA in settings of basic medical care.

Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project.

Ovarian cancer is a silent killer and, due to late diagnosis, the primary cause of death amongst gynecological cancers, killing approximately 376 women annually in Denmark. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, but also treatment, by predicting which patients will benefit from specific treatment strategies. The Mermaid III project is consisting of 3 parts including "Early detection, screening and long-term survival," "Biomarkers and/or prognostic markers" and "The infection theory." The present paper gives an overview of the part regarding biomarkers and/or prognostic markers, with a focus on rationale and design. The study described has 3 major branches: microRNAs, epigenetics and Next Generation Sequencing. Tissue and blood from ovarian cancer patients, already enrolled in the prospective ongoing pelvic mass cohort, will be examined. Relevant microRNAs and DNA methylation patterns will be investigated using array technology. Patient exomes will be fully sequenced, and identified genetic variations will be validated with Next Generation Sequencing. In all cases, data will be correlated with clinical information on the patient, in order to identify possible biomarkers. A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.

Approaches to the detection of ovarian cancer.

BACKGROUND: Ovarian cancer (OC) represents the eighth most common cancer among women and the second most frequently diagnosed gynecological malignancy in the United States and Europe. Correct and fast referral of patients with OC is mandatory to ensure optimal treatment and to improve the prognosis of patients with OC. Approaches to detect OC may be based on a gynecological examination, an elevated serum CA125 level, a Risk of Malignancy Index (RMI) higher than 200, an elevated serum HE4 level, or other modalities such as Risk of Ovarian Malignancy Algorithm (ROMA), Risk of Ovarian Cancer Algorithm (ROCA), or Copenhagen Index (CPH-I). AIM: To describe biomarkers that potentially improve the detection/risk estimation of OC. RESULTS: The ability to differentiate OC from benign and borderline ovarian tumors was analyzed using Receiver Operating Characteristics (ROC) curves resulting in Area Under the Curve (AUC) of 0.920 for CA125, 0.933 for HE4 and 0.946 for ROMA. The ROC curves of OC versus benign ovarian tumors shows that the CPH-I (AUC = 0.959) is equivalent with RMI (AUC = 0.958). CONCLUSION: Both ROMA and CPH-I could potentially shorten the time spent before OC patients reach a tertiary center thereby improve risk estimation/diagnosis. Biomarker research still has to be performed in relevant clinical settings before any overall decisions can be made with respect to screening.

A novel diagnostic index combining HE4, CA125 and age may improve triage of women with suspected ovarian cancer - An international multicenter study in women with an ovarian mass.

AIM: To develop and validate a biomarker-based index to optimize referral and diagnosis of patients with suspected ovarian cancer. Furthermore, to compare this new index with the Risk of Malignancy Index (RMI) and Risk of Ovarian Malignancy Algorithm (ROMA). PATIENTS AND METHODS: A training study, consisting of patients with benign ovarian disease (n=809) and ovarian cancer (n=246), was used to develop the Copenhagen Index (CPH-I) utilizing the variables serum HE4, serum CA125 and patient age. Eight international studies provided the validation population; comprising 1060 patients with benign ovarian masses and 550 patients with ovarian cancer. RESULTS: Overall, 2665 patients were included. CPH-I was highly significant in discriminating benign from malignant ovarian disease. At the defined cut-off of 0.070 for CPH-I the sensitivity and specificity were 95.0% and 78.4% respectively in the training cohort and 82.0% and 88.4% in the validation cohort. Comparison of CPH-I, ROMA and RMI demonstrated area-under-curve (AUC) at 0.960, 0.954 and 0.959 respectively in the training study and 0.951, 0.953 and 0.935 respectively in the validation study. Using a sensitivity of 95.0%, the specificities for CPH-I, ROMA and RMI in the training cohort were 78.4%, 71.7% and 81.5% respectively, and in the validation cohort 67.3%, 70.7% and 69.5% respectively. CONCLUSION: All three indices perform well at the clinically relevant sensitivity of 95%, but CPH-I, unlike RMI and ROMA, is independent of ultrasound and menopausal status, and may provide a simple index to optimize referral of women with suspected ovarian cancer.