Risk Of Ovarian Malignancy Algorithm Research Articles

Fragmentomics features of ovarian cancer.

Ovarian cancer (OC) is a major cause of cancer mortality in women worldwide. Due to the occult onset of OC, its nonspecific clinical symptoms in the early phase, and a lack of effective early diagnostic tools, most OC patients are diagnosed at an advanced stage. In this study, shallow whole-genome sequencing was utilized to characterize fragmentomics features of circulating tumor DNA (ctDNA) in OC patients. By applying a machine learning model, multiclass fragmentomics data achieved a mean area under the curve (AUC) of 0.97 (95% CI 0.962-0.976) for diagnosing OC. OC scores derived from this model strongly correlated with the disease stage. Further comparative analysis of OC scores illustrated that the fragmentomics-based technology provided additional clinical benefits over the traditional serum biomarkers cancer antigen 125 (CA125) and the Risk of Ovarian Malignancy Algorithm (ROMA) index. In conclusion, fragmentomics features in ctDNA are potential biomarkers for the accurate diagnosis of OC.

Risk of Ovarian Malignancy Algorithm and Pelvic Mass Score for the prediction of malignant ovarian tumors: a prospective comparative study.

Ovarian cancer is the seventh most common female cancer worldwide. Nevertheless, there is no available universal screening method for malignant ovarian masses. This study compares the value of the Risk of Ovarian Malignancy Algorithm (ROMA) and Pelvic Mass Score (PMS) scoring systems in the diagnosis of malignant ovarian masses. This prospective comparative study was conducted from March 2021 until April 2022. A total of 258 women diagnosed with ovarian mass and eligible for surgical intervention according to institutional guidelines were enrolled in the study. Ultrasound was performed for the assessment of masses, ascites and metastases, also color flow Doppler was done to measure the resistance index of the mass vasculature. Preoperative venous blood samples were collected to measure CA 125 and HE4. PMS and ROMA scoring systems were calculated for each patient. All women were subjected to a surgical intervention (according to applicable institutional guidelines), using either open or laparoscopic techniques. Histopathological examination of the removed specimens was done, and in line with the recognized gold standard, the results were compared with the pre-operative diagnosis of both scoring systems. Both PMS and ROMA showed a high predictive probability for ovarian malignancies (AUC = 0.93, sensitivity = 83.3%, specificity = 90.37%; AUC = 0.91, sensitivity = 84.4%, specificity = 95.56%, respectively), yet no statistical significant difference was found between the two scoring systems (p = 0.353, 95% CI -0.025 to 0.070). Both PMS and ROMA seem to be promising scoring systems for discriminating benign from malignant ovarian masses, but more research is needed to determine the optimum diagnostic pathway, especially one yielding the least false-negative results.

Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively

PurposeThe preoperative diagnosis of endometriosis associated ovarian cancer (EAOC) remains challenging for lack of effective diagnostic biomarker. We aimed to study clinical characteristics and develop a nomogram for diagnosing EAOC before surgery.MethodsA total of 87 patients with EAOC and 348 patients with ovarian endometrioma (OEM) were enrolled in our study. Least absolute shrinkage and selection operator (LASSO) regression and Logistic regression were utilized to select variables and construct the prediction model. The performance of the model was assessed using receiver operating characteristic (ROC) analyses and calibration plots, while decision curve analyses (DCAs) were conducted to assess clinical value. Bootstrap resampling was used to evaluated the stability of the model in the derivation set.ResultsThe EAOC patients were older compared to the OEM patients (46.41 ± 9.62 vs. 36.49 ± 8.09 year, P < 0.001) and proportion of postmenopausal women was higher in EAOC group than in the OEM group (34.5 vs. 1.5%, P < 0.001). Our prediction model, which included age at diagnosis, tumor size, cancer antigen (CA) 19–9 and risk of ovarian malignancy algorithm (ROMA), demonstrated an area under the curve (AUC) of 0.858 (95% confidence interval (CI): 0.795–0.920) in the derivation set (N = 304) and an AUC of 0.870 (95% CI: 0.779–0.961) in the validation set (N = 131). The model fitted both the derivation (Hosmer–Lemeshow test (HL) chi-square = 12.600, P = 0.247) and the validation (HL chi-square = 8.210, P = 0.608) sets well.ConclusionCompared to patients with OEM, those with EAOC exhibited distinct clinical characteristics. Our four-variable prediction model demonstrated excellent performance in both the derivation and validation sets, suggesting its potential to assist with preoperative diagnosis of EAOC.

Evaluation of Human Epididymis Protein 4, Risk of Ovarian Malignancy Algorithm, and Risk of Malignancy Index Efficiency for Ameliorating Sensitivity and Specificity for Differentiating Benign from Malignant Adnexal Masses

Abstract Background Inadequacy of effective sensitive and specific screening modalities results in late-stage diagnosis of ovarian cancer. Cancer Antigen-125 (CA-125) individually possesses limited specificity for differentiating adnexal masses. The present study aimed to evaluate the Human Epididymis Protein 4 (HE4), Risk of Ovarian Malignancy Algorithm (ROMA), and Risk of Malignancy Index (RMI) for ameliorating sensitivity and specificity for differentiating benign from malignant adnexal masses. Materials and Methods This study was conducted on 96 preoperative women with suspected adnexal mass (patients) and 48 healthy females without adnexal mass (controls) for the duration of 2 years. Both study participants were divided into two groups, pre- and postmenopausal. CA-125 and HE4 were done using commercially available kits. ROMA% and RMI were calculated. We validated their performances using histopathology as the gold standard. The statistical analysis was done using SPSS 21, Kruskal–Wallis, and Tukey's tests. The best cutoff points to best values of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also evaluated. Results For differentiating benign from malignant masses in the premenopausal group, the sensitivity, specificity, PPV, NPV, and area under the curve (AUC) were 93.7%, 78.3%, 65.2%, 96.6%, 0.892 for CA-125; 87.5%, 83.7%, 70%, 93.9%, 0.926 for HE4; 93.7%, 70.2%, 57.6%, 96.2%, 0.927 for ROMA; and 68.7%, 86.4%, 68.7%, 86.5%, 0.916 for RMI. While in the postmenopausal group, the sensitivity, specificity, PPV, NPV, and AUC were 92.3%, 76.4%, 85.7%, 86.6%, 0.907 for CA-125; 78.5%, 94%, 95.6%, 80%, 0.955 for HE4; 92.3%, 94.1%, 96%, 88.8%, 0.968 for ROMA; and 88.4%, 88.2%, 92%, 83.3%, 0.943 for RMI. Conclusion For differentiating benign from malignant masses more specifically in women with a suspected adnexal mass, ROMA and HE4 appear to be more effective than CA-125.

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

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. Patients with pathologically diagnosed ovarian tumors were included in this study. The study validated the diagnostic performance of ROMA and CPH-I. 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. 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%.

Current Diagnostic Possibilities for the Initial Forms of External Endometriosis

Background. Routine use of ultrasound methods does not always allow detecting endometriosis in the early stages. It is necessary to develop more accurate criteria for the diagnosis of endometriosis in its initial stages of development. Objective: to assess ultrasound and biological markers of endometriosis “small” forms of different localization in infertile women.Material and methods. Ultrasound examination of 208 infertile patients with initial stages of external endometriosis (1–15 points by revised American Fertility Society (rAFS) classificatoon) was performed (main group). The control group consisted of 195 healthy women of childbearing age. To verify the diagnosis, it is suggested to use a panel of biomarkers, including interleukins (IL) 1β and 6, CA125, HE4 as well as the ROMA (Risk of Ovarian Malignancy Algorithm) index in the dynamics of the menstrual cycle.Results. On ultrasound scans, 56 (94.9%) patients had small one- and two-sided ovarian cysts corresponding to endometriosis stage 1–2 (rAFS), and in 3 (5.4%) of them, the ultrasound result was questionable. Detectability during the initial ultrasound examination in the Douglas space was 76.9%, in the rest of cases the ultrasound picture was doubtful. Peritoneal endometriosis was detected only in 5 patients. In the remaining cases (88.9%), additional studies were necessary, including surgical (laparoscopy). The average content of CA125 in the main group on days 3–5 of the menstrual cycle was 42.6 (2.1) U/ml, on days 21–23 – 39.6(2.2) U/ml (p=0.32); in the control group, 5.1 (0.4) and 4.8 (0.7) U/ml, respectively (p = 0.71). The increase in CA125 in the main group was almost 8 times higher than in the control group, however, according to the indicators of HE4 and the ROMA index, statistically significant differences in the groups were not obtained. In the dynamics of the menstrual cycle, the content of ILs in the main group significantly decreased by days 21–23 of the cycle, while the content of CA125 and HE4 remained practically unchanged. Such sharp fluctuations of the considered biomarkers were not detected in the control group. However, even on days 21–23 of the cycle, the average content of ILs and CA125 in women of the main group remained statistically significantly higher than in the control group.Conclusion. In infertile women with dubious ultrasound criteria of external endometriosis, the use of IL1β and IL-6, which stimulate the immune inflammatory response, as well as tumor markers CA125, HE4 and ROMA index allows to differentiate the disease in the initial stages.

Ultrasound examination, MRI, or ROMA for discriminating between inconclusive adnexal masses as determined by IOTA Simple Rules: a prospective study

ObjectiveTo determine the best second-step approach for discriminating benign from malignant adnexal masses classified as inconclusive by International Ovarian Tumour Analysis Simple Rules (IOTA-SR).MethodsSingle-center prospective study comprising a consecutive series...

A label-free dual immunosensor for the simultaneous electrochemical determination of CA125 and HE4 biomarkers for the early diagnosis of ovarian cancer.

The blood levels of cancer antigen 125 (CA125) and human epididymal secretory protein 4 (HE4) are measured in the diagnosis and progression monitoring of ovarian cancer (OC), and the Risk of Ovarian Malignancy Algorithm (ROMA) score% values are calculated for cancer risk assessment. For the first time, disposable dual screen-printed carbon electrodes modified with reduced graphene oxide, polythionine, and gold nanoparticles were used to fabricate label-free electrochemical dual CA125-HE4 immunosensors for the sensitive, fast, and practical simultaneous determination of CA125 and HE4. DPV and SWV methods were used to simultaneously determine antigens in two different linear ranges (1-100pgmL-1 and 1-50ngmL-1). High sensitivity, low LOD, and LOQ were obtained for two linear ranges with a correlation coefficient above 0.99. The application stability of the dual CA125-HE4 immunosensors was determined as 60days, and the storage stability was determined as 16weeks. The dual immunosensors exhibited high selectivity in eight different antigen mixtures. The reusability of the dual immunosensors has been tested up to 9 cycles. ROMA score% values for pre-menopausal and post-menopausal status were calculated using the concentration of CA125 and HE4 in the blood serum and assessing OC risk. The disposable dual immunosensors can be used in point-of-care tests for rapid and practical simultaneous determination of CA125 and HE4 with high selectivity, sensitivity, and repeatability.

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

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. 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. 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. 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.

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

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. 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. 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). 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.

The Utility of Preoperative Serum CA125 Combined with HE4 to Predict Lymph Node Metastasis in Endometrial Cancer

Objectives: To investigate the diagnostic performance of the serum cancer antigen 125 (CA125), human epididymis protein 4 (HE4), a combination of CA125 and HE4, and a risk of ovarian malignancy algorithm (ROMA) in the preoperative prediction of high-risk lymph node metastasis (LMN) in patients with early stage endometrial cancer (EC). Designs: This is a cross-sectional study. Participants/Materials, Setting, and Methods: A cross-sectional study of data for patients with early stage endometrioid EC treated surgically at Rajavithi Hospital between April 2020 and April 2021 was commenced. The preoperative serum levels of CA125 and HE4 were measured and analyzed. The ROC curves were generated to determine the optimal cutoff values of CA125, HE4, and ROMA with optimum sensitivity and specificity for predicting LMN. Results: Eighty-six patients with surgically staged EC were identified. Lymph node involvement was detected in 9 patients (10.5%). The median serum CA125, HE4, and ROMA levels were significantly higher in EC patients having LMN than in those who did not (p < 0.05). Based on the ROC curve, both serum markers showed good discrimination for the prediction of LMN, with an optimal cutoff value of 35 U/mL for CA125 (AUC 0.789, 95% CI; 0.647–0.932), 200 pMol/L for HE4 (AUC 0.825, 95% CI; 0.700–0.950), and 60% for ROMA (AUC 0.856, 95% CI; 0.720–0.982). Additionally, HE4 showed the highest sensitivity, whereas the combination of CA125 and HE4 had the highest specificity. Limitations: The lack of ultra-staging might have been an important issue in underestimating the rate of nodal metastasis in low-risk patients and made the number of patients who developed LMN low (10.5%) in this study. Conclusions: The preoperative combined CA125 and HE4 levels are associated with an increased risk of having LMN in patients with early stage EC. This biomarker panel can guide identifying EC patients who might most benefit from lymphadenectomy.

Are ROMA and HE4 More Accurate than CA-125, in Predicting of Ovarian Epithelial Carcinoma?

Evaluation of ovarian tumors based on tumor markers could have high clinical importance. In this study, we aimed to assess the predictive value of HE4 and Risk of Ovarian Malignancy Algorithm (ROMA) compared to CA-125 in the Malignancy of ovarian epithelial masses. This cross-sectional study was performed in 2020-2021 including 203 patients. Serum HE4 and CA-125 levels were checked before surgery. According to the pathology report (benign, borderline, or malignant epithelial mass), the predictive values of the three markers were evaluated. About 146 cases were benign; 14 cases were borderline and 43 cases were malignant. Most patients (69.8%) in the malignant group were in stage 3. Significantly higher levels of all three markers (CA-125, HE4, and ROMA) were found in patients with malignant tumors compared to benign or borderline tumors (P < 0.001 for all). The sensitivity of CA-125 was the highest (90.7%) in pre- and post-menopausal patients but the specificity of HE4 and ROMA were higher than CA-125 (98.1% and 97.5%, respectively, versus 86.9% for CA-125). In post-menopausal patients, both sensitivities of HE4 and ROMA were 90.5% and the specificity and sensitivity of CA-125 were the highest (95.2% and 100%). In premenopausal patients, the sensitivity of ROMA (90.9%) and the specificity of HE4 (100%) were the highest. HE4 and ROMA are not necessary for postmenopausal patients in low-resource areas and a check of serum CA-125 will be enough. The higher-cost, ROMA, and HE4 checks are recommended in premenopausal people because they are more sensitive.

Clinical Significance of the Combination of Serum HE4 Levels, Hemoglobin-to-Red Cell Distribution Width Ratio, and CT Imaging for the Pretreatment Assessment of Adnexal Masses.

Background: This study aimed to determine the optimal combination of biomarkers that can predict epithelial ovarian cancer (EOC) and compare the combination with the risk of ovarian malignancy algorithm (ROMA) or Copenhagen index (CPH-I). Methods: Data from 66 patients with EOC and 599 patients with benign ovarian masses who underwent definitive tissue diagnosis of adnexal masses between January 2017 and March 2021 were analyzed. The Mann-Whitney U test or Kruskal-Wallis test was used for between-group comparisons of medians. Logistic regression was used to establish an EOC predictor model. Area under the curve (AUC) comparisons between models were performed using the Delong nonparametric approach. Results: The median age of the patients was 43 years. Twenty-nine (43.9%) patients had early-stage disease (stages I-II) and 37 (56.1%) patients had advanced-stage disease (stages III-IV). The median age, body mass index, white blood cell count, hemoglobin-to-red cell distribution width ratio (HRR), platelet count, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, serum albumin level, cancer antigen 125, human epididymal secretory protein 4 (HE4), ROMA, and CPH-I were significantly different between the stage I-IV EOC and benign ovarian mass groups. Multivariate logistic regression analysis revealed that HE4, HRR, and computed tomography (CT) imaging were significant predictors of both stages I-IV and I-II EOC. Using these covariates, an interim model (IM) (consisting of HE4 and HRR) and a full model (FM) (consisting of HE4, HRR, and CT imaging) were constructed. When predicting stage I-IV EOC, the AUC of IM was comparable to that of ROMA or CPH-I, whereas the AUC of FM outperformed ROMA or CPH-I. In predicting stage I-II EOC, the AUC of IM was comparable to that of CPH-I but higher than that of ROMA, and the AUC of FM outperformed ROMA or CPH-I. Conclusion: FM outperformed ROMA or CPH-I in predicting stage I-IV EOC and stage I-II EOC. Therefore, FM could be a promising model for improving preoperative prediction of EOC at an early stage. However, further prospective studies are required to validate these results.

The use of CA125, human epididymis protein 4 (HE4), risk of ovarian malignancy algorithm (ROMA), risk of malignancy index (RMI) and subjective assessment (SA) in preoperative diagnosing of ovarian tumors.

To compare utility of CA125, human epididymis protein 4 (HE4), risk of ovarian malignancy algorithm (ROMA), risk of malignancy index (RMI) and subjective assessment (SA) in preoperative diagnosis of ovarian tumors. Research was conducted among 456 patients qualified for surgery due to ovarian tumor. Preoperatively, CA125 and HE4 serum levels were estimated, and transvaginal ultrasound was performed. ROMA and RMI values and SA qualifications were obtained. Results were compared with pathomorphological findings. Receiver Operating Characteristic (ROC)-Area Under Curve (AUC) values for CA125, HE4, ROMA, RMI and SA in preoperative diagnosis of malignant lesions were 0.819, 0.909, 0.911, 0.895 and 0.895, respectively. Combinations of biochemical and sonographic methods increased sensitivity in diagnosis of ovarian tumors. Combinations utilizing serum HE4 concentrations were most useful. CA125, HE4, ROMA, RMI and SA proved to be useful in preoperative diagnosis of ovarian tumors. HE4 and ROMA occurred to be the most useful. Ultrasonographic methods are considerably useful in diagnosis of ovarian tumors. RMI and SA present similar overall diagnostic value.

The Discrepancy between Preoperative Tumor Markers and Imaging Outcomes in Predicting Ovarian Malignancy

Preoperative tumor markers and imaging often differ in predicting whether an ovarian tumor is malignant. Therefore, we evaluated the correlation between the predictive values of imaging and tumor markers for diagnosing ovarian tumors, especially when there were discrepancies between the two. We enrolled 1047 patients with ovarian tumors. The predictive values and concordance rates between the preoperative risk of ovarian malignancy algorithm (ROMA) and imaging, including CT and MRI, were evaluated. Diagnoses of 561 CT (77.9%) and 322 MRI group (69.2%) participants were consistent with the ROMA. Among them, 96.4% of the CT (541/561) and 92.5% of the MRI (298/322) group predicted an accurate diagnosis. In contrast, 67.3% (101/150) of CT and 75.2% (100/133) of MRI cases accurately predicted the diagnosis in cases with discrepancies between ROMA and CT or MRI; a total of 32% (48/150) of the CT and 25.5% (34/133) of the MRI group showed an accurate ROMA diagnosis in cases with discrepancies between ROMA and imaging. In the event of a discrepancy between ROMA and imaging when ovarian tumor malignancy prediction, the question is which method should take precedence. This study demonstrates that MRI has the greatest diagnostic accuracy, followed by CT and ROMA. It is also important to understand underlying diseases and benign conditions and rare histopathologies of malignant tumors.

A nomogram model based on clinical markers for predicting malignancy of ovarian tumors.

The aim of this study was to build a nomogram based on clinical markers for predicting the malignancy of ovarian tumors (OTs). A total of 1,268 patients diagnosed with OTs that were surgically removed between October 2017 and May 2019 were enrolled. Clinical markers such as post-menopausal status, body mass index (BMI), serum human epididymis protein 4 (HE4) value, cancer antigen 125 (CA125) value, Risk of Ovarian Malignancy Algorithm (ROMA) index, course of disease, patient-generated subjective global assessment (PG-SGA) score, ascites, and locations and features of masses were recorded and analyzed (p 0.05). Significant variables were further selected using multivariate logistic regression analysis and were included in the decision curve analysis (DCA) used to assess the value of the nomogram model for predicting OT malignancy. The significant variables included post-menopausal status, BMI, HE4 value, CA125 value, ROMA index, course of disease, PG-SGA score, ascites, and features and locations of masses (p 0.05). The ROMA index, BMI (≥ 26), unclear/blurred mass boundary (on magnetic resonance imaging [MRI]/computed tomography [CT]), mass detection (on MRI/CT), and mass size and features (on type B ultrasound [BUS]) were screened out for multivariate logistic regression analysis to assess the value of the nomogram model for predicting OT malignant risk (p 0.05). The DCA revealed that the net benefit of the nomogram's calculation model was superior to that of the CA125 value, HE4 value, and ROMA index for predicting OT malignancy. We successfully tailored a nomogram model based on selected clinical markers which showed superior prognostic predictive accuracy compared with the use of the CA125, HE4, or ROMA index (that combines both HE and CA125 values) for predicting the malignancy of OT patients.

Molecular Biomarkers for the Early Detection of Ovarian Cancer.

Ovarian cancer is the deadliest gynecological cancer, leading to over 152,000 deaths each year. A late diagnosis is the primary factor causing a poor prognosis of ovarian cancer and often occurs due to a lack of specific symptoms and effective biomarkers for an early detection. Currently, cancer antigen 125 (CA125) is the most widely used biomarker for ovarian cancer detection, but this approach is limited by a low specificity. In recent years, multimarker panels have been developed by combining molecular biomarkers such as human epididymis secretory protein 4 (HE4), ultrasound results, or menopausal status to improve the diagnostic efficacy. The risk of ovarian malignancy algorithm (ROMA), the risk of malignancy index (RMI), and OVA1 assays have also been clinically used with improved sensitivity and specificity. Ongoing investigations into novel biomarkers such as autoantibodies, ctDNAs, miRNAs, and DNA methylation signatures continue to aim to provide earlier detection methods for ovarian cancer. This paper reviews recent advancements in molecular biomarkers for the early detection of ovarian cancer.

Value of the risk of ovarian malignancy algorithm index in predicting the recurrence of epithelial ovarian cancer.

Aim: This study aimed to assess the predictive and diagnostic value of the risk of ovarian malignancy algorithm (ROMA) index for epithelial ovarian cancer (EOC) recurrence. Materials & methods: The clinical features and follow-up data of 159 EOC cases were studied. The ROMA indexwas calculated by serum CA125 andHE4 levels withmenopausal status. Recurrence-free survival was evaluated for an end point. Results: The ROMA was strongly associated with clinical characteristics. The ROMAindexabove the cutoff value (34.71%) was significantly associated with recurrence-free survival. The ROMA indexhad a significantly higher sensitivity (90.59%) than CA125 (84.71%) and HE4 (80.80%) for recurrence diagnosis, and its optimal cutoff value was 17.07%. Conclusion: The primary ROMA index is a predictive factor in EOC recurrence and has better performance in the diagnosis of EOC recurrence.

A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses.

To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts. Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed. A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76-0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84-0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84-0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone. A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

Cost-analysis comparison of clinical risk assessment with and without ROMA for the management of women with pelvic masses

Objective: Pelvic masses can be classified as low risk (likely benign) and high risk (likely malignant) based on an initial clinical risk assessment, which involves a detailed history, physical exam, basic laboratory tests, and imaging. In recent years, the Risk of Ovarian Malignancy Algorithm (ROMA), which combines CA125, HE4 and menopausal status, has emerged as a powerful tool in the classification of pelvic masses and triage of patients to either a generalist gynecologist or a gynecologic oncologist for management. The objective of this study was to evaluate whether the use of ROMA, alone or in combination with Initial Clinical Risk Assessment (ICRA), provides cost savings compared to triage based on ICRA alone. Methods: A health-economic decision model was developed to assess clinical and cost differences associated with three different clinical pathways of risk assessment for a pelvic mass: ICRA alone, ROMA alone, or ICRA + ROMA in combination. Using previously reported accuracy rates and patient characteristics from a prospective, multicenter, blinded clinical trial, total healthcare costs were modeled for each clinical pathway using the Medicare 2020 reimbursement rates. Results: A total of 461 patients with pelvic masses were included with 10.4% ultimately diagnosed with epithelial ovarian cancer. Total healthcare costs for patients with benign disease, EOC, or low malignant potential tumors (LMP) (n = 441) triaged using ROMA alone were 3.3% lower than when triaged using ICRA alone. While lab costs increased 55% using ROMA, the use of ROMA alone resulted in a 4% decrease in laparoscopy costs and a 3.1% decrease in laparotomy costs compared with ICRA alone. Similarly, total costs associated with a combination of ICRA + ROMA were 3.9% lower than total costs associated with ICRA alone. The model also predicted a 63% reduction in repeat surgeries resulting from false negative ICRA when using ROMA to triage patients. Conclusion: Triage of women with pelvic masses using the more sensitive ROMA score lowers overall healthcare costs compared to ICRA alone. With fewer false negative results than ICRA alone, the ROMA score improves initial detection of malignancy and reduces second surgical treatments in women with pelvic masses.