Comparison of HE4, CA125, and ROMA Diagnostic Accuracy

Zhang, Pengjun; Wang, Chuanxin; Cheng, Liming; Zhang, Peng; Guo, Lin; Liu, Wanli; Zhang, Zhongying; Yan-chun, Huang; Ou, Qishui; Wen, Xin; Tian, Yaping

doi:10.1097/md.0000000000002402

Cited by 18 publications

(6 citation statements)

References 40 publications

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“…HE4 is encoded by WAP four-disulfide core domain 2, which resides on the most frequently amplified genomic sequence in OC 9 . In this study, the AUC of HE4 for predicting stage I-IV EOC was 0.920, and the results were consistent with those of previous studies 2 - 8 . However, caution should be exercised because HE4 levels may increase in older adults, smokers, and in those with renal disease, lung cancer, and endometrial cancer 32 .…”

Section: Discussionsupporting

confidence: 92%

“…Following the establishment of predictor models, their AUC values were compared with those of ROMA or CPH-I. In this study, the AUC of ROMA in predicting stage I-IV EOC was 0.918; the results were consistent with those of previous studies 2 - 6 , 8 , 10 - 13 , 37 . Furthermore, the AUC of ROMA in predicting stage I-II EOC was 0.816; these results were consistent with those of previous studies 6 , 10 , 11 .…”

Section: Discussionsupporting

confidence: 88%

“…The Risk of Ovarian Malignancy algorithm (ROMA), which is composed of CA125 and HE4, is a US Food and Drug Administration-cleared predictive algorithm. The AUC of ROMA in predicting EOC ranged from 0.90 to 0.95 2 - 6 , 8 , 10 - 13 . In Moore et al's study, there was a significant difference in the AUC between ROMA and CA125 and no significant difference between ROMA and HE4 in predicting EOC 3 .…”

Section: Introductionmentioning

confidence: 99%

“…Cancer antigen 125 (CA125) and human epididymis secretory protein 4 (HE4) are key serum tumor markers for detecting ovarian malignancies. The area under the curve (AUC) of CA125 for predicting EOC ranged from 0.86 to 0.93 [2][3][4][5][6][7][8]. In a meta-analysis, the pooled sensitivity (SE) and specificity (SP) of serum CA125 for predicting EOC were 82% and 73%, respectively [2].…”

Section: Introductionmentioning

confidence: 99%

“…HE4 is encoded by WAP four-disulfide core domain 2, which resides on the most frequently amplified genomic sequence in ovarian cancer [9]. The AUC of HE4 in predicting EOC ranged from 0.87 to 0.94 [2][3][4][5][6][7][8]. In a meta-analysis, the pooled SE and SP of HE4 for predicting EOC were 73% and 90%, respectively [2].…”

Section: Introductionmentioning

confidence: 99%

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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

Jang¹,

Kim²,

Eo³

et al. 2023

J. Cancer

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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.

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