The Comparison of Three Predictive Indexes to Discriminate Malignant Ovarian Tumors from Benign Ovarian Endometrioma: The Characteristics and Efficacy

This study aimed to evaluate the prediction efficacy of malignant transformation of ovarian endometrioma (OE) using the Copenhagen Index (CPH-I), the risk of ovarian malignancy algorithm (ROMA), and the R2 predictive index. This retrospective study was conducted at the Department of Gynecology, Nara Medical University Hospital, from January 2008 to July 2021. A total of 171 patients were included in the study. In the current study, cases were divided into three cohorts: pre-menopausal, post-menopausal, and a combined cohort. Patients with benign ovarian tumor mainly received laparoscopic surgery, and patients with suspected malignant tumors underwent laparotomy. Information from a review chart of the patients’ medical records was collected. In the combined cohort, a multivariate analysis confirmed that the ROMA index, the R2 predictive index, and tumor laterality were extracted as independent factors for predicting malignant tumors (hazard ratio (HR): 222.14, 95% confidence interval (CI): 22.27–2215.50, p < 0.001; HR: 9.80, 95% CI: 2.90–33.13, p < 0.001; HR: 0.15, 95% CI: 0.03–0.75, p = 0.021, respectively). In the pre-menopausal cohort, a multivariate analysis confirmed that the CPH index and the R2 predictive index were extracted as independent factors for predicting malignant tumors (HR: 6.45, 95% CI: 1.47–28.22, p = 0.013; HR: 31.19, 95% CI: 8.48–114.74, p < 0.001, respectively). Moreover, the R2 predictive index was only extracted as an independent factor for predicting borderline tumors (HR: 45.00, 95% CI: 7.43–272.52, p < 0.001) in the combined cohort. In pre-menopausal cases or borderline cases, the R2 predictive index is useful; while, in post-menopausal cases, the ROMA index is better than the other indexes.


Introduction
Ovarian cancer is the fifth leading cause of cancer-related death in women [1]. This disease cannot be diagnosed in the early stages and is called the silent killer [2][3][4]. As such, most ovarian cancer cases are diagnosed at advanced stages [5][6][7], and over 185,000 deaths due to this disease are reported annually worldwide [8,9].
Molecular genetics and morphologic characteristics revealed that ovarian cancer can be divided into two categories, designated types 1 and 2 [10][11][12]. Type 1 tumors show a stepwise progression (adenoma-carcinoma sequence), which comprise endometriosisassociated ovarian cancer (EAOC), such as clear cell carcinoma and low-grade endometrioid carcinoma, as well as mucinous carcinoma and low-grade serous carcinoma [13,14]. Type 2 tumors range from the normal epithelium to precursor lesions, and finally to high-grade serous and endometrioid carcinoma, malignant mixed mesodermal tumors (carcinosarcomas), and undifferentiated carcinoma [13,15]. The former shows low progression but is A list of patients with primary, previously untreated, histologically-confirmed ovarian tumors who were treated at Nara Medical University Hospital between January 2008 and July 2021 was generated from our institutional registry. We retrospectively included in this study the following cases of OE as benign ovarian tumor and EAOC cases as malignant tumor with available blood samples for tumor marker calculations. All of the OE and EAOC cases were histologically confirmed. Written consent for the use of the patients' clinical data for research was obtained at the first hospitalization, and after approval by the Ethics Review Committee of the Nara Medical Hospital; the opt-out form was provided through our institutional homepage. The current study consisted of three cohorts: the pre-menopausal, post-menopausal, and combined cohorts. Pre-menopause and postmenopause were divided by age, namely under 50 years old was defined as pre-menopause and over 50 years old as post-menopause. The pre-menopausal cohort included 115 patients with newly diagnosed ovarian tumors. A total of 56 patients were included in the postmenopause cohort. No patients had undergone chemotherapy or radiotherapy for the ovarian tumors prior to treatment. Patients with OE mainly received laparoscopic surgery, and the patients suspected of harboring malignant tumors underwent laparotomy. The following factors were collected through a chart review of the patients' medical records: age; body mass index (BMI); parity; postoperative diagnosis, including FIGO (The International Federation of Gynecology and Obstetrics) stage; the date of surgery; tumor diameter; menopausal status; and pre-treatment blood test results, including CA125, carbohydrate Diagnostics 2022, 12, 1212 3 of 16 antigen 19-9 (CA 19-9), carcinoembryonic antigen (CEA), and HE4 as a tumor marker. The cases shared with a previous study [35] were 72 cases (42.1%).

Tumor Imaging and Diagnoses
All patients first visited the outpatient clinic and underwent internal examination, including ultrasound followed by routine MR imaging using T1W and T2W sequences. Tumor diameter was recorded as the largest diameter among axial, sagittal, and coronal imaging. Patients were largely diagnosed with OE or EAOC by MRI, and this was confirmed by the histological examination using the surgically removed tumors by at least two pathologists who were blinded to the study. The number of EAOC cases that were histologically proven as arising from endometriosis were 41 cases (54.7%).
2.3. Detection of CA125, CA19-9, CEA, and HE4 Concentrations Samples were collected from all the patients prior to surgery using blood collection tubes without anticoagulants. Each blood sample was centrifuged at 3000 rpm and stored at −80 • C until use. Tumor markers including CA125 (ARCHITECT CA125 II, Abbott Japan LLC, Tokyo, Japan), CA19-9 (CL AIA-PACK ® SLa, Tosoh Corporation, Tokyo, Japan), CEA (CL AIA-PACK ® CEA, Tosoh Corporation, Tokyo, Japan), and HE4 (ARCHITECT HE4, Abbott Japan LLC, Tokyo, Japan) were measured using a chemiluminescence immunoassay, according to the manufacturer's instructions. Serum samples in dry ice were transported to the Tosoh diagnostics product divisions (Tosoh Corporation, Kanagawa, Japan), and CA19-9 and CEA concentrations were determined immediately. HE4 and CA125 (ARCHITECT CA125 II) were measured at BML INC., Tokyo, Japan. In case of CA125 and HE4 levels under the limit, we recorded the lower limit of calibration as 1 (U/mL) and 20 (pmol/L), respectively. Measurements were performed by clinical laboratory technologists who were blinded to the study.

Calculation of the ROMA, the CPH, and the R2 Predictive Value
Using the concentrations of CA125, HE4, and CEA, we calculated the Copenhagen (CPH) index, the risk of ovarian malignancy algorithm (ROMA) index, and the R2 predictive index, according to the mathematical equations presented below.
The ROMA index was calculated using the following equations [44]:

Statistical Analysis
Analyses were performed using SPSS version 25.0 (IBM SPSS, Armonk, NY, USA). The differences of each factor, including the CPH index, the ROMA index, and the R2 predictive index among groups, were compared using a Mann-Whitney U test or Kruskal-Wallis one-way ANOVA test. The receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off value for predicting malignant ovarian tumors in each pre-menopausal, post-menopausal, and combined (pre-and post-menopause) cohort. The cut-off value was based on the highest Youden index (i.e., sensitivity + specificity − 1). We next used a logistic regression analysis to assess the risk factors for malignant ovarian tumors (i.e., EAOC). A two-sided p < 0.05 was considered as indicating a statistically significant difference.

Patients
From January 2008 to July 2021, a total of 171 patients included in this study were divided as follows: 115 patients who were under 50 years old as the pre-menopausal cohort, and 56 patients over 50 years old as the post-menopausal cohort. The combined cohort consisted of the pre-and post-menopausal cohorts. The demographic and clinical characteristics of the combined cohort are outlined in Table 1. In the combined cohort, a post-operative diagnosis of OE was found in 96 (56.1%) and malignant tumors in 75 (43.9%) patients, including eight cases of borderline tumor. In this cohort, there was significant differentiation in age, BMI, gravida, parity, cyst size, menopausal status, and tumor laterality. Table 2 shows the distribution of each biological marker. CEA, HE4, CA125, and D-dimer reached significant differentiation between a benign tumor and malignant tumor.

The Characteristics of Each Biological Marker in Each Cohort
The results of the ROC curve analysis based on the detection of malignant tumors are shown in Figure 1, concerning each predictive index, and in Figures 2 and 3 regarding other biological markers. The optimal cutoff value was determined by analyzing the ROC curve among malignant ovarian tumors and OE. Table 3 shows the cut-off values discriminating benign from malignant tumors for each cohort. In the post-menopause cohort, CEA and tumor diameter, which comprise the R2 predictive index, did not reach significant differentiation; on the other hand, CA125, comprising the CPH index and the ROMA index, in the pre-menopause cohort did not reach significant differentiation. This characteristic influences the AUC of each index, including the CPH index, the ROMA index, and the R2 predictive index.

The Usefulness of the R2 Predictive Index in Discriminating OE from Borderline Tumors
In the combined cohort, some factors indicating a borderline tumor were extracted by the univariate analysis (Table 7). Multivariate analysis confirmed that the R2 predictive index was only extracted as an independent factor for predicting malignant tumors (HR: 45.00, 95% CI: 7.43-272.52, p < 0.001). When excluding the CPH index, the ROMA index, and the R2 predictive index from the factor and including tumor diameter, CEA, HE4, and CA125, only tumor diameter was indicated as an independent factor (HR: 7.33, 95% CI: 1.32-40.48, p = 0.022) ( Table 7).

The Differentiation of R2 Predictive Value between OE and Borderline Tumor or Advanced Malignant Tumors
In the combined cohort, the R2 predictive index, the ROMA index, and the CPH index showed significant differentiation among ovarian endometriosis, borderline tumor, and carcinoma ( Figure 4). The ROMA index and the CPH index could discriminate the carcinoma from the others; on the contrary, the R2 predictive index discriminated the endometriosis from malignant tumors ( Figure 4, Table 8).
In the combined cohort, the R2 predictive index, the ROMA index, and the CPH index showed significant differentiation among ovarian endometriosis, borderline tumor, and carcinoma ( Figure 4). The ROMA index and the CPH index could discriminate the carcinoma from the others; on the contrary, the R2 predictive index discriminated the endometriosis from malignant tumors ( Figure 4, Table 8).

Discussion
In the current study, the ROMA index, the CPH index, and the R2 predictive index were shown to be effective tools to discriminate benign OE from EAOC, and showed similar results to those reported previously [46,47]. In particular, in the combined cohort, the ROMA index was the most effective predictor among the three indexes (Table 4); however, in the pre-menopausal cohort, the R2 predictive index was more effective than the others (Table 5) for discriminating malignant tumors. This is partly because HE4 and

Discussion
In the current study, the ROMA index, the CPH index, and the R2 predictive index were shown to be effective tools to discriminate benign OE from EAOC, and showed similar results to those reported previously [46,47]. In particular, in the combined cohort, the ROMA index was the most effective predictor among the three indexes (Table 4); however, in the pre-menopausal cohort, the R2 predictive index was more effective than the others (Table 5) for discriminating malignant tumors. This is partly because HE4 and CA125, which consist of the CPH and the ROMA index have a weaker ability to discriminate malignancy in pre-menopausal durations; on the other hand, CEA, which consists of the R2 predictive value, was stronger in the pre-menopausal cohort than HE4 and CA125 (Table 3). Serum CA125 levels are frequently measured when ovarian cysts are observed, in order to rule out a malignant tumor. However, it is well known that elevated serum CA125 levels are not only seen in endometrioma [48], but also in adenomyosis [49] or menstrual cycle [50], thus giving a high rate of false positives [51,52]. This was confirmed in a recent Cochrane review, which reported that among the 97 biomarkers studied, CA125 was the only marker that is elevated in cases of endometrioma, with 40% sensitivity and 91% specificity, with a cut-off limit of 35 U/mL [53].
On the other hand, HE4 is the most promising. HE4 protein is encoded by the WAP four-disulfide core domain 2 (WFDC2) [54], which was found to be highly expressed in ovarian carcinoma, especially in serous and endometrioid cancers [55,56]. Unlike CA125, HE4 is not overexpressed in benign ovarian disease, normal ovarian tissue, or tumors with low malignant potential [55]. Terlikowska KM et al. reported that the HE4 level in serum elevates with age, and the specificity was better in post-menopausal patients than in pre-menopausal patients [57]. This trend is similar to that in our results, in which the CPH and the ROMA index were useful tools to discriminate malignancy in post-menopausal patients. In particular, in pre-menopausal patients there is a major challenge in choosing the surgical method (i.e., laparotomy or laparoscopic surgery), and this index could be helpful for the physician.
We previously reported that OE has a higher iron concentration than EAOC and can discriminate either cyst fluid iron concentration or transverse magnetic relaxation rate R2 or R2* value, using a complex, chemical shift-encoded MR examination [37,38]. However, no evidence concerning the standpoint of borderline tumor (i.e., the degree of iron concentration or R2 value) exists, because of the rare incidence of this disease. We demonstrated that the R2 predictive index was the independent factor to discriminate borderline tumor from OE in the combined cohort (Table 7). Moreover, the R2 predictive index of OE was higher than other malignant tumors with significant differentiation (Table 8). We can hypothesize that borderline tumors could show lower iron concentrations than OE, and this may discriminate benign OE from EAOC, even in borderline cases, by iron concentration and transverse magnetic relaxation rate R2 or R2* value.
This study has some limitations. The first limitation is that the number of OE in post-menopausal patients was too small to assess the effectiveness of these indexes in the post-menopausal cohort. Second, the sample sizes of the borderline ovarian tumor and phenotype were too small to conclude the efficacy of the R2 predictive index in discriminating borderline tumors from endometriosis, and further case accumulation is needed.

Conclusions
In conclusion, in pre-menopausal cases or borderline cases, the R2 predictive index is useful; and in post-menopausal cases, the ROMA index is better than the other indexes.
Funding: This research was funded by Japan Society for the Promotion of Science, grant number 21K16819.

Institutional Review Board Statement:
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee of Nara Medical University Hospital (protocol code: 2944 and 3115).

Informed Consent Statement:
The consent form making patients' data available for research use was obtained at the first hospitalization, and after approval by the Ethics Review Committee of the Nara Medical Hospital, and the opt-out form was provided through our institutional homepage.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author.