Literature DB >> 24418200

A predictive model combining human epididymal protein 4 and radiologic features for the diagnosis of ovarian cancer.

A Stiekema1, C A R Lok2, G G Kenter2, W J van Driel2, A D Vincent3, C M Korse4.   

Abstract

OBJECTIVE: Ovarian cancer is the leading cause of death in women with gynecologic cancer. CA125 is the commonly used biomarker in the diagnosis of ovarian cancer, but has limitations in both sensitivity and specificity. Human Epididymal secretory protein (HE4) is a promising biomarker and is included in the Risk of Ovarian Malignancy Algorithm (ROMA) score, which is suggested to further increase the diagnostic accuracy than either marker alone. However, information from ultrasound and CT-scan is not included in this algorithm. This study evaluated the diagnostic accuracy of HE4 in the pre-operative diagnosis of ovarian cancer and the predictive values of biomarkers, ultrasound and CT-scan and combinations hereof.
METHODS: HE4 and CA125 were measured in 361 subjects (34 benign, 147 ovarian cancer and 180 controls). Sensitivity, specificity and area under the curve (AUC) for CA125, HE4, ROMA and RMI scores were calculated using the receiver operating characteristic (ROC) methodology. The additional predictive value of ultrasound or CT-scan to the individual markers was analyzed using logistic regression.
RESULTS: The sensitivity in predicting ovarian cancer of CA125 was 91% and of HE4 90%. The specificity was 65% and 97% respectively. HE4 demonstrated the highest discrimination (ROC-AUC=0.96), compared to ROMA, RMI and CA125 (AUC=0.95, 0.89 and 0.90 respectively). ROMA did not improve when it was combined with different ultrasound factors. The presence of intra-abdominal metastasis on CT-scan improved the discriminative potential of HE4 (p=0.0004).
CONCLUSION: HE4 in combination with CT-scan may be incorporated in the diagnostic work-up in women with a pelvic mass.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CT-scan; HE4; Ovarian cancer; RMI; Ultrasound

Mesh:

Substances:

Year:  2014        PMID: 24418200     DOI: 10.1016/j.ygyno.2014.01.005

Source DB:  PubMed          Journal:  Gynecol Oncol        ISSN: 0090-8258            Impact factor:   5.482


  6 in total

1.  Ultrasound Features Improve Diagnostic Performance of Ovarian Cancer Predictors in Distinguishing Benign and Malignant Ovarian Tumors.

Authors:  Yong-Ning Chen; Fei Ma; Ya-di Zhang; Li Chen; Chan-Yuan Li; Shi-Peng Gong
Journal:  Curr Med Sci       Date:  2020-03-13

2.  [Diagnostic value of CA125, HE4 and Copenhagen Index in differentiating benign from malignant epithelial ovarian tumors].

Authors:  Shi-Peng Gong; Yong-Ning Chen; Ya-di Zhang; Wei Yao; Li Chen; Shi-San Liu; Huan Wu
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2017-05-20

3.  Detection of glyco-mucin profiles improves specificity of MUC16 and MUC1 biomarkers in ovarian serous tumours.

Authors:  Sara Ricardo; Lara Marcos-Silva; Daniela Pereira; Rita Pinto; Raquel Almeida; Ola Söderberg; Ulla Mandel; Henrik Clausen; Ana Felix; Nuno Lunet; Leonor David
Journal:  Mol Oncol       Date:  2014-10-22       Impact factor: 6.603

4.  Clinical value of ROMA index in diagnosis of ovarian cancer: meta-analysis.

Authors:  Ranliang Cui; Yichao Wang; Ying Li; Yueguo Li
Journal:  Cancer Manag Res       Date:  2019-03-28       Impact factor: 3.989

Review 5.  ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors.

Authors:  Dirk Timmerman; François Planchamp; Tom Bourne; Chiara Landolfo; Andreas du Bois; Luis Chiva; David Cibula; Nicole Concin; Daniela Fischerova; Wouter Froyman; Guillermo Gallardo Madueño; Birthe Lemley; Annika Loft; Liliana Mereu; Philippe Morice; Denis Querleu; Antonia Carla Testa; Ignace Vergote; Vincent Vandecaveye; Giovanni Scambia; Christina Fotopoulou
Journal:  Int J Gynecol Cancer       Date:  2021-06-10       Impact factor: 3.437

6.  Distinguishing benign from malignant pelvic mass utilizing an algorithm with HE4, menopausal status, and ultrasound findings.

Authors:  Sarikapan Wilailak; Karen K L Chan; Chi An Chen; Joo Hyun Nam; Kazunori Ochiai; Tar Choon Aw; Subathra Sabaratnam; Sudarshan Hebbar; Jaganathan Sickan; Beth A Schodin; Chuenkamon Charakorn; Walfrido W Sumpaico
Journal:  J Gynecol Oncol       Date:  2014-10-13       Impact factor: 4.401

  6 in total

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