Biomarkers and algorithms for diagnosis of ovarian cancer: CA125, HE4, RMI and ROMA, a review

Ovarian cancer is the 5th leading cause of death for women with cancer worldwide. In more than 70% of cases, it is only diagnosed at an advanced stage. Our study aims to give an update on the biological markers for diagnosing ovarian cancer, specifically HE4, CA 125, RMI and ROMA algorithms. Serum CA125 assay has low sensitivity in the early stag es and can be increased in certain conditions such as menstruation or endometriosis. The level of HE4 is ove rexpressed in ovarian tumors. Its specificity is 94% and its level is not affected by endometriosis cysts. The combined measures of CA125 and HE4 have proved to be highly efficient with an area under the curve (AUC) o f up to 0.96. Furthermore, this combined measure of C A 1 2 5c a nc o r r e c tt h ev a r i a t i o n si nH E 4w h i c ha r ed u et os m o k i n go rc o n t r a c e p t i o nc o m b i n i n ge s t r o g e np l u s progestin. While the specificity of RMI sometimes reaches 92%, the rather low AUC of 0.86 does not make it the best diagnostic tool. The specificity of ROMA is lower than HE4 (84% compared to 94%). To date, the most efficient biological diagnostic tool to diagnose ovarian cancer is the combination of CA125 and HE4.

HE4, CA125, ROMA, RMI, Ovarian cancer

Ovarian cancer is the 5th worldwide leading cause of death of women due to cancer [ 1]. In more than 70% of cases, it is diagnosed at an advanced phase. The progno- sis for ovarian cancer remains poor overall, with a 46% 5-year survival rate [ 2]. The prognosis is closely related to the stage at diagnosis: survival rate of > 70% after 5 years for stage I or II, survival rates between 20 and 40% for stage III or IV [ 3, 4]. More than 90% of benign tumors are found in pre- menopausal patients who have been operated on, whereas in postmenopausal patients only 60% of tumors are benign [ 5]. It seems essential to differentiate early malignant ovarian tumors to benign ovarian tumors. Exams are therefore needed which must be prioritized in order to advise the patient (monitoring, treatment or survey) according to the lesion, and first and foremost to the clinical history of the patient [ 6]. Concerning laboratory exams, several tumor biomarkers have been evaluated. The Carbohydrate Antigen 125 (CA125) was first described in the early 1980 ’s[ 7]. In cases of ovarian cancer, serum CA125 level may be elevated, but this marker has a low sensitivity in the early stages of ovarian cancer [ 8]. Increased CA125 levels are also re- ported in other physiological or pathological conditions, such as menstruation, pregnancy, endometriosis and in- flammatory diseases of the peritoneum [ 9]. Other bio- markers have been developed in order to improve specificity for ovarian carcinomas, such as the Human Epididymis Protein 4 (HE4) [ 10]. This biomarker is re- ported to be overexpressed in ovarian cancer [ 11]. Although the specificity of these markers is rather reliable, they are not very sensitive. For this reason, algorithms, RMI (Risk of Malignancy Index) and ROMA (Risk of Ovarian Malignancy Algorithm), were developed in an at- tempt to improve the inherent characteristics of these biomarkers. HE4 was found to be a reliable biological marker for de- tecting ovarian cancer (level of evidence [LE]1) and ROMA © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. * Correspondence: [email protected] 1Service de Gynécologie-Obstétrique, CHU de Nantes, 44093 Nantes, France Full list of author information is available at the end of the article Dochez et al. Journal of Ovarian Research (2019) 12:28 https://doi.org/10.1186/s13048-019-0503-7 algorithm was more sensitive but less specific than HE4 alone (LE2) for the French National College of Obstetri- cians and Gynaecologists (CNGOF) [12]. CNGOF also con- cluded that complementary studies should be necessary before using HE4 on a routine basis (Grade B). Our study intends to provide a comprehensive update for ovarian can- cer diagnosis using biomarkers (HE4 and CA125) and algo- rithms (RMI and ROMA). The sensitivity, specificity, positive and negative predict i v ev a l u e so ft h e s et o o l sh a v e been collated in Table 1 for CA125 and HE4 and T able 2 for RMI and ROMA algorithms. Only the values of some cited articles are referenced in order to lighten the table and make it readable.

Carbohydrate antigen 125 (CA 125) Carbohydrate Antigen 125 (CA 125), sometimes named as Cancer Antigen 125 or Tumor Antigen 125, is a mucin-type glycoprotein, produced by the MUC16 gene, and associated with the cellular membrane. This biomarker is most often used for ovarian lesions. It has been used in the early 1980 ’s when Bast et al. [ 7] specifically isolated the monoclonal antibody OC125 in cancerous ovarian tissue compared to healthy ovarian tissue. Its upper limit is 35 U/mL in pre and post-menopausal patients [ 13]. However, this measure- ment is not very sensitive in the early phases of ovarian cancer (only reported to be elevated in 23 to 50% of stage I cases) [ 10]. In addition, elevated serum CA125 levels may be observed in other physiological or patho- logical conditions (menstruation, pregnancy, endometri- osis, inflammatory diseases of the peritoneum) [ 9]. In a meta-analysis by Ferraro et al. [ 14], the specificity of CA125 for detecting ovarian cancer was 78% (95%CI 76 – 80). To describe tumor markers and screening tests, the Receiver Operating Characteristic (ROC) area under the curve (AUC) is frequently employed since it represents a useful graphic tool for comparing biomarkers and algo- rithms. The ROC measures the discrimination of a test, i.e. its ability to distinguish between having disease and not having disease for a given patient. In the study by Dikmen et al. [ 15] ,t h eA U Cf o rC A 1 2 5w a sr a t h e rw e a k (0.78), suggesting that it was probably not the ideal marker for diagnosing ovarian cancer. Serum CA125 levels were frequently measured when ovarian cysts are observed, in order to rule out a malignant tumor. But for the past several decades, elevated serum CA125 levels have been seen in endo- metrioma, thus giving a high rate a false positives [16]. This was confirmed in a recent Cochrane review which reported that among the 97 biomarkers stud- ied, CA125 was the only marker which is elevated in cases of endometrioma with 40% sensitivity and 91% specificity with a cut off limit of 35 U/mL [ 17]. In another very recent meta-analysis, Hirsch et al. [ 18] demonstrated that CA125 should be useful to diag- nose endometriosis, especially with an increasing sen- sitivity corresponding simultaneously with the disease phase. Chen et al. [ 19]r e p o r t e dt h a tC A 1 2 5l e v e l s were significantly higher in the group with endome- triotic cysts compared to group with other benign ovarian tumors (49.7 U/mL vs. 21.6 U/mL). Since CA125 has been a tumor marker for several de- cades, the changes in its levels according to the patient ’s demographic characteristics and lifestyles have been evaluated numerous times [ 20, 21]. Smoking does not appear to modify serum CA125 levels [ 22, 23]. Whereas CA125 may vary during menstrual cycles, it has been demonstrated that levels are not affected by a contracep- tion combining estrogen plus progestin [ 21, 24]. Likewise, the body mass index does not appear to modify CA125 levels [25]. In practice, CA125 is often measured in cases of ovarian cysts, but according to its low specificity and the observed increased levels in different physiological situations, it is not considered as a very good differentiating biomarker for ovarian tumors. For this reason, new biomarkers have been evaluated in an attempt to improve early diagnosis of ovarian cancer [26]. Human epididymis protein 4 (HE4) Human Epididymis Protein 4 (HE4) is a new biomarker which has been currently evaluated for diagnosing ovar- ian malignant tumors [ 10]. It is a glycoprotein belonging to the family of whey acidic four-disulfide core proteins, accounting for its alternative name of WFDC2 and the larger protein family called “WAP” for whey acidic pro- teins. The main genes coding for the WAP proteins are mainly located on chromosome 20q12 –13.1 [ 27]. Present in whey, these proteins are called WAP , which is composed of around 50 amino acids, and its biological function has not yet been completely identified [ 28]. HE4, which contains 2 WAP domains, was initially isolated in the epididymis and might play a role in sperm maturation [ 29]. This biomarker is weakly expressed in the epithelium tissues of respiratory and reproductive organs, but is overexpressed in ovarian tumors, espe- cially in endometrioid ovarian cancer [ 11]. In addition, it appears that HE4 is not as strongly expressed in clear cell ovarian carcinomas as in other epithelial ovarian cancers [ 30]. Yanaranop et al. [ 31] reported a specificity of 86% for HE4, and the AUC was higher than CA125 alone, with values of 0.893 and 0.865, respectively [ 32]. These data, in accordance with those reported in a re- cent Italian multicentre study included 387 patients, showed that HE4 for diagnosing ovarian epithelial can- cer appeared more reliable than CA125 [ 33]. Dochez et al. Journal of Ovarian Research (2019) 12:28 Page 2 of 9 Table 1 Diagnostic performance of CA125, HE4 and combination of CA125 + HE4 in the subset of studies cited in this article Systematic review or meta- analysis CA125 HE4 CA125 + HE4 Se (%) (95% IC) Sp (%) (95% IC) PPV (%) NPV (%) AUC (95% IC) Se (%) (95% IC) Sp (%) (95% IC) PPV (%) NPV (%) AUC (95% IC) Se (%) (95% IC) Sp (%) (95% IC) PPV (%) NPV (%) AUC (95% IC) Ferraro et al. [ 14] X 79 (77 –82) 78 (76 –80) 79 (76 –81) 93 (92 –94) 82 (78 –86) 76 (72 –80) Dikmen et al. [ 15] 63 0.78 78 0.93 Chen et al. [ 19] 93 67 0.93 (0.88 –.97) 73 99 0.96 (0.93 –1) 97 66 0.96 (0.93 –1) Yanaranop et al. [ 31] 84 53 41 89 0.81 (0.74 –0.87) 66 86 65 87 0.82 (0.76 –.89) Wilailak et al. [ 32] 0.87 (0.80–0.93) 0.89 (0.84 –0.95) 0.89 (0.84 –0.95) Wang et al. [ 36] X 79 (74 –84) 82 (77 –87) 0.87 (0.84 –0.90) 76 (72 –80) 94 (90 –96) 0.89 (0.86 –0.92) Zhen et al. [ 37] X 74 (72 –76) 83 (81 –84) 0.85 74 (72 –76) 90 (89 –91) 0.89 Abdel-Azeez et al. [ 45] 73 (57–86) 79 (58 –93) 0.90 (0.82 –0.97) 83 (68 –93) 88 (68 –97) 0.95 (0.90 –1) 90 79 Holcomb et al. [ 46] 85 (69–95) 59 (52 –66) 27 96 65 (46 –80) 92 (87 –95) 58 94 91 55 26 97 Moore et al. [48] 61 0.84 (0.77 –0.90) 78 0.91 (0.86 –0.95) 81 0.91 (0.87 –0.96) Goff et al. [52] 79 (67–88) 76 (68 –83) 63 87 58 (45 –70) 94 (88 –97) 83 81 Meys et al. [55] X Van Gorp et al. [ 56] 80 (72–85) 82 (76 –86) 75 (67 –81) 83 (78 –88) Al Musalhi et al. [ 57] 79 62 38 91 0.81 71 90 68 91 0.82 Moore et al. [62] 89 (85–93) 75 (70 –79) 60 94 Li et al. [ 64] X 77 (58 –89) 84 (76 –90) 0.88 (0.85 –0.91) 79 (74 –84) 93 (87 –96) 0.82 (0.78 –0.85) Wei et al. [ 66] 8 59 2 9 1 8 9 7 59 8 9 6 8 5 Sandri et al. [67] 91 71 0.90 (0.86 –0.93) 83 91 0.92 (0.89 –.95) CA125 carbohydrate antigen 125, HE4 human epididymis protein 4, Se sensitivity, Sp specificity, PPV positive predictive value, NPV negative predictive value, AUC area under the curve Dochez et al. Journal of Ovarian Research (2019) 12:28 Page 3 of 9 To measure this biomarker, an immune-enzymatic (EIA) assay described by the Fujirebio lab was developed [34]. Other immunological methods have since been de- veloped and evaluated such as electrochemiluminescent (ECLIA) or chemiluminescent microparticle immuno- assay (CMIA). A recent study evaluated these different measurement techniques for HE4 levels [ 35]. The au- thors reported that ECLIA and CMIA were well com- pared with the reference method and could be routinely used in practice. However, significantly different mean values were reported according to the immunological assay used; HE4 marker levels might always be interpreted according to the immunological assay employed. The cut off level of 70 pmol/L is often used for pre-menopause pa- tients and 140 pmol/L for menopause patients; but some- times the threshold level of 140 pmol/L is employed, or even other close but outlying values. The threshold value of HE4 used, including whether or not the menopausal status, is left to the choice of clinicians [ 36, 37]. Indeed, these values can be used whatever the immunological

performed. Nevertheless, given the fact that is proven that HE4 increases significantly over the age, the use of 2 thresholds (70 and 140 pmol/l) seems preferable than the use of a single threshold (140 pmol/l) [ 38, 39]. In conclusion, the review of the literature demonstrates that all meta-analyses always take into account the different

used to measure HE4 and the results must be carefully handled. Although CA125 levels seem to be elevated in endo- metrioma, HE4 levels appear to remain stable [ 19, 40, 41]. HE4 levels in patients with endometrioma were comparable to levels in patients with other benign ovar- ian cysts (53.0 pmol/L vs. 52.8 pmol/L) [ 19], quite under- standable since the gene coding for HE4 is not overexpressed in endometriotic lesions [ 42]. A recent study has also confirmed that serum HE4 was a better Table 2 Diagnostic performance of RMI and ROMA algorithms in the subset of studies cited in this article Systematic review or meta- analysis RMI ROMA Se (%) (95% IC) Sp (%) (95% IC) PPV (%) NPV (%) AUC (95% IC) Se (%) (95% IC) Sp (%) (95% IC) PPV (%) NPV (%) AUC (95% IC) Ferraro et al. [ 14] X Dikmen et al. [ 15] 88 0.96 Chen et al. [ 19] 97 80 0.97 (0.95 –1) Yanaranop et al. [31] 78 80 60 90 0.88 (0.83 –0.93) 84 69 52 91 0.86 (0.81 –0.91) Wilailak et al. [32] 0.84 (0.77–0.91) 0.86 (0.81 –0.91) Wang et al. [36] X 85 (81 –89) 82 (77 –87) 0.91 (0.88 –0.93) Zhen et al. [37] X Abdel-Azeez et al. [ 45] Holcomb et al. [46] Moore et al. [ 48] Goff et al. [ 52] Meys et al. [ 55] X 75 (72 –79) 92 (88 –94) Van Gorp et al. [56] Al Musalhi et al. [57] 77 82 56 93 0.85 75 88 65 92 0.84 Moore et al. [ 62] Li et al. [ 64] X 89 (84 –93) 83 (77 –88) 0.93 (0.90 –0.95) Wei et al. [ 66]9 4 9 3 9 0 8 6 Sandri et al. [ 67] 89 81 0.93 (0.90 –0.96) RMI risk of malignancy index, ROMA risk of ovarian malignancy algorithm, Se sensitivity, Sp specificity, PPV positive predictive value, NPV negative predictive value, AUC area under the curve Dochez et al. Journal of Ovarian Research (2019) 12:28 Page 4 of 9 diagnostic biomarker than CA125 in ovarian cancer pa- tients with endometriosis [ 38]. Variations of HE4 levels in variable situations were also evaluated. Whereas Bolstad et al. [ 38] reported modified levels of HE4 according to Body Mass Index (BMI), Ferraro et al. [ 25] did not report significant dif- ferent levels of HE4 in 103 patients according to BMI, probably explained by inclusion of men and women in this study which should constitute a bias. In conclusion, serum HE4 levels appeared to not be modified by the BMI, as CA125. Nevertheless, in opposite to CA125, smoking seems to be a significant factor which affects serum HE4 varia- tions [ 43]. HE4 level is increased from 20 to 30% in smokers compared to non-smokers [ 23, 38, 44]. So, HE4 level should be always interpreted carefully in smokers, since it could be misinterpreted as a false positive result. In opposite to CA125, contraceptive use contributes to variations in HE4 levels. Ferraro et al. [ 24] reported a significantly lower level of HE4 in patients using oral contraception compared to patients using other contra- ceptive methods ( p = 0.008). Therefore, in order to mis- interpret HE4 levels, it appears noteworthy to include the contraceptive method in the patient ’s clinical history. Associating HE4 + CA125 Three meta-analyzes or systematic reviews show the use of HE4 or CA125, always with different thresholds for HE4 [ 14, 36, 37]. The combined use of these markers is only sometimes studied [ 45–47]. Chen et al. [ 19] re- ported a specificity of 65.7% using the ECLIA immuno- logical method with a cut-off value for HE4 of 140 pmol/L. In a different study using another technique to assess serum HE4, the specificity of the association CA125 and HE4 was much better (80%) [ 48]. However, the ROC AUC when combining the two markers was high, varying from 0.96 (IC95% 0.93 –1) [ 19] to 0.91 (IC95% 86.7 –96.0) [ 48]. Thus, the association of CA125 and HE4 is a useful diagnostic tool in ovarian cancer and may be used in addition to each biomarker. These results are confirmed by another study ana- lyzing each marker separately or in combination [ 49]. That is, in case of increased HE4 and CA125, the specificity was better. The use of a third marker, for example clinical, could also improve the detection of these ovarian cancers. Besides its use diagnosing ovarian cancer, the measure- ments of the association HE4 + CA125 can also be useful in differential diagnosis of different ovarian tumors. Anastasi et al. [ 50] studied 57 patients with endome- trioma; all had increased CA125 levels, while the HE4 levels remained normal. Another very recent study con- firmed the significant difference between HE4 and CA125 levels in endometrioma cases [ 51]. Thus, endometrioma could be suspected whenever CA125 levels are elevated while HE4 levels remain normal. In addition, while HE4 level varies in smokers and in contraceptive combining es- trogen plus progestin users, simultaneous CA125 evalu- ation which is not affected by these variables should allow better interpretation of abnormal HE4 levels. In conclusion, it seems worthwhile to measure both markers in cases of suspected benign ovarian tumors: an increased value of the 2 markers being suggestive of an ovarian cancer As suggested in a recent study by Goff et al., thresholds of 70 and 140 pmol/l according to meno- pausal status and 35UI/ml for CA125 seems preferable [52]. Furthermore, the use of this combined HE4 and CA125 assay may also be of major interest in ovarian cancer screening in the general population, as shown by Urban et al. [ 44]. However, in this context, the place of transvaginal ultrasound remains to be clarified, and the use of a second positive test could reduce sensitivity (key principle of a screening test). Risk of malignancy index (RMI) RMI was proposed in 1990 by Jacobs et al. [ 53], using CA125, ultrasound findings and menopausal status ac- cording to the formula: RMI = U x M x CA125 with U = ultrasound score (U = 0 if ultrasound score = 0, U = 1 if ultrasound score = 1, U = 3 if ultrasound score 2 to5), M = menopause status (M = 1 for pre-menopausal women, M = 3 for post-menopausal women). A RMI score above 200 proved to have a strong association with a high risk of malignancy (sensitivity 85.4% and specificity 96.9%). Another study performed in 2012 on nearly 1000 pa- tients demonstrated that the ultrasound assessment was superior according to IOTA (International Ovarian Tumor Analysis) criteria compared to RMI [ 54]. These data were confirmed in a recent meta-analysis published in 2016 [ 55]. This study of almost 20,000 ovarian tumors reported better results with the use of ultrasound criteria (sensitivity 93% and specificity 80%) compared to that obtained with the RMI algorithm (sensitivity 75% and spe- cificity 92%). The specificity of RMI for diagnosing ovarian cancer is rather high, 92.4% [ 56] and 92% in a recent meta-analysis [55]. This specificity could be increased by modifying the threshold level for malignancy (using 250, as reported by Al Musalhi et al. [ 57]). Since 1990 with Jacobs ’ suggestion to use RMI algo- rithms, several variations in RMI formula have been de- veloped. Chopra et al. [ 58] studied 100 patients, using a modified RMI with the maximum values for the U et M parameters were 4 instead of 3, which increased the sen- sitivity to 96.7% with 84% specificity, and a positive pre- dictive value of 85.5%. Recently, the use of four different RMI formulas showed the same results for sensitivity. The positive likelihood ratio was reported between 3.52 and 4.41 [ 59]. Dochez et al. Journal of Ovarian Research (2019) 12:28 Page 5 of 9 For screening tests, the use of ROC AUC seems to be a useful indicator for detecting cancer. That of RMI re- mains weak (0.86) [ 60] compared to other biomarkers which emphasize that RMI algorithm don ’t appear to be the most useful diagnostic tool for ovarian cancer. According to this hypothesis, a 2-steps triage model, associating ultrasound findings first, RMI could improve screening results. Using this 2-step model, a recent study in 2016 reported an improved detection rate of ovarian cancer through 72 to 85% [ 61]. Finally, concerning this RMI algorithm or modified RMI algorithms, the variable U may be equal to 0, the RMI score may be 0 (RMI = U x M x CA125). This value 0 may sometimes seem aberrant in the interpretation of a score. Nevertheless, the RMI score is based on a threshold (200). The calculation of specificity, sensitivity and positive and negative predictive values is not based on the value of the score but on its value below or above that threshold. The value 0 therefore impacts the interpretation of this algo- rithm only very moderately. Risk of ovarian malignancy algorithm (ROMA) In 2009, Moore proposed a new algorithm: Risk of Ovar- ian Malignancy Algorithm (ROMA) [ 62]. He associated HE4 and CA125 levels according to the menopausal sta- tus, defined by lack of menstruation or clinical signs of menopause for 6 months. Pre−menopausal Predictive Index PIðÞ ¼ −12:0 þ 2:38 /C2 LN HE4ðÞ þ 0:0626 /C2 LN CA125ðÞ Post−menopausal Predictive Index PIðÞ ¼ −8:09 þ 1:04 /C2 LN HE4ðÞ þ 0:732 /C2 LN CA125ðÞ Predicted Probability PPðÞ ¼ exp PIðÞ = 1 þ exp PIðÞ½/C138 /C2 100 Therefore, the ROMA score corresponds to Predicted Probability [PP] and is expressed by a percentage rate. Different cut off levels are proposed for non-menopausal women, and another for women having reached meno- pause. According to the immunological assay for meas- uring CA125 and HE4, the cut off levels can differ to classify patients into either a low or an high risk group [63]. In fact, with the Roche Diagnostics Laboratory ’s ECLIA method, the cut off level to classify patients in a high risk group was 11.4% for pre-menopausal patients, and 29.9% for menopause patients. Whereas with Abbott Diagnostics Laboratory ’s CMIA method, the cut off levels were respectively 7.4 and 25.3% [ 32]. It is thus in- dispensable to know which method is used or to refer to the normal values given by the lab perform- ing the tests in order to correctly interpret the re- sults of this algorithm. In a meta-analysis, the ROMA algorithm was reported with less specificity than that associated with HE4 levels (84% vs. 94%), but a better correlation than with CA125 levels (84% vs. 78%) [ 64]. In this meta-analysis, the AUC for the ROMA algorithm was better than HE4 or CA125 (0.93, 0.82 and 0.88; respectively), as in the meta-analysis performed by Wang et al. (0.91, 0.89 and 0.87; respectively) [ 36]. Another meta-analysis by Kaijser et al. [ 65] demon- strated a ROMA sensitivity between 76 and 86%, while specificity was evaluated between 74 and 95%, in spite of using different methods for measuring the markers. Recently, ROMA was reported having a non-significant different specificity to CA125 (approximately 92.5%) but with significantly improved sensitivity levels: 93.7% vs. 85.0% [ 66]. For Chen et al. [ 19], ROMA was more sensi- tive than HE4, respectively 96.7 and 73.3%, but with less specificity (80% vs. 98.6%). In this same study, AUC for ROMA and HE4 were not significantly different (0.97 and 0.96, respectively). Several more recent studies con- firm these results [ 32, 67]. Nevertheless, it should be noted that it is difficult to interpret these meta-analyses results. When studies have used different measuring tech- niques for CA125 and HE4 [ 14, 36, 64], the results thus indirectly implied different ROMA calculations. There- fore, one must be cautious in interpreting cut off levels. Although the dual measurement of CA125 and HE4 is apparently the best diagnostic tool over and above ROMA algorithms; the fact of including ages in the ROMA model could be a valuable contribution for diag- nosing ovarian cancer [ 68]. It was reported that serum HE4 levels regularly increased with age, without any sudden peak at menopause [ 38, 39]. Using age in the algorithm, it should be a valuable contribution for evalu- ating serum HE4 levels. Modified risk of ovarian malignancy algorithm: CPH-I and ROMA P In 2015, the Copenhagen Index (CPH-I) was reported as a novel diagnostic score index in ovarian tumors [ 69]. It used the same mathematical method than the ROMA algorithm with a Predicted Probability called PP. The CPH-I formula is: CPH-I =− 14.0647 + 1.0649 x log2(HE4) + 0.6050 x log2(CA125) + 0.2672 x age / 10 with PP = e(CPH-I) /( 1+e ( C P H - I ) ) . The ROC AUC were comparable according to the dif- ferent respective algorithms: CPH-I, ROMA and RMI (0.96, 0.95 and 0.96, respectively). Thus, the introduction of the age in the algorithm did not improve the diagnostic of ovarian cancer. More recently, Chudecka-Glaz et al. [70] evaluated another modified ROMA algorithm, called ROMA P , which took into account the patient ’s age and not her menopausal status, according to the formula: ROMA P = exp.(PI) / (1-exp(PI)) × 100 with the predictive Dochez et al. Journal of Ovarian Research (2019) 12:28 Page 6 of 9 index formula PI: PI = A + W(HE4) x ln(HE4) + W(CA125) x ln(CA125), and A, W(HE4) et W(CA125) were the varying coefficients for each decade in function of the patient ’s age. ROMA P algorithm had a higher spe- cificity and a higher positive predictive value, but the sen- sitivity and the negative predictive value were lower than the non-modified ROMA algorithm. Otherwise, the ROC AUC for these two algorithms were comparable (0.923 for the ROMA P vs. 0.934 for ROMA).

The best biological diagnostic tool today seems to be a combination of CA125 and HE4 levels in order to predict the risk of ovarian cancer in patients with suspected be- nign ovarian tumors. If the level of CA125 is increased as well as that of HE4, it is necessary to evoke a malignant le- sion and therefore to envisage a surgical treatment for an anatomopathological examination. On the other hand, if one of the markers was above the cut-off as long as the other was below the cut-off specified, a simple ultrasound or biological monitoring may be considered. As the HE4 levels increase with advancing age, it might be interesting to establish algorithms which take into account the pa- tients’ age and not her menopausal status. The previously published algorithms (CHP-I or ROMA P) have not proved to be valuable compared to RMI or ROMA algo- rithms. Serum HE4 levels vary in smokers and in hormo- nal contraceptive users, thus it seems relevant that this information should always be included in the patient ’s clinical history. Nonetheless, since CA125 levels are inde- pendent from these variables, the simultaneous measure of these two markers allows the correction of any possible variations in such specific cases. Abbreviations AUC: Area under the Curve; BMI: Body Mass Index; CA125: Carbohydrate Antigen 125; CMIA: Chemiluminesc ent microparticle immunoassay; ECLIA: Electrochemiluminescent immunoassay; EIA: Immune-Enzymatic assay; HE4: Human Epididymis Protein 4; IOTA: International Ovarian Tumor Analysis; RMI: Risk of Malignancy Index; ROC: Receiver Operating Characteristic; ROMA: Risk of Ovarian Malignancy Algorithm

Not applicable Funding Not applicable Availability of data and materials Not applicable Authors’ contributions VD and GD developed the original design. VD performed the initial literature review. VD and GD wrote the first draft of the report. EV, JD, HC and NW participated in the development and the revisions of the manuscript. All authors contributed to the writing of the final manuscript. All authors read and approved the final manuscript. Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare that they have no competing interest. Publisher’sN o t e Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Author details 1Service de Gynécologie-Obstétrique, CHU de Nantes, 44093 Nantes, France. 2Service de Biochimie, CHU de Nantes, Nantes, France. 3Centre de recherche clinique, Centre Hospitalier Départemental Vendée, La Roche sur Yon, France. 4Service de Gynécologie-Obstétrique, Centre Hospitalier Départemental Vendée, La Roche sur Yon, France. Received: 8 May 2018 Accepted: 19 March 2019

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