Urine CA125 and HE4 for the Detection of Ovarian Cancer in Symptomatic Women

Cancers (Basel). 2023 Feb 16;15(4):1256. doi: 10.3390/cancers15041256.

Abstract

The symptoms of ovarian cancer are vague, and current risk assessment tools such as serum CA125 and transvaginal ultrasound scan fail to reliably detect the disease early. This study aimed to evaluate urine CA125 and HE4 as diagnostic biomarkers for ovarian cancer in symptomatic women. Paired urine and serum samples were collected from women undergoing treatment for ovarian cancer (cases) or investigations for gynaecological symptoms (controls). Biomarkers were measured using an automated chemiluminescent enzyme immunoassay analyser. Standard diagnostic accuracy metrics were calculated. In total, 114 women were included, of whom 17 (15%) were diagnosed with an epithelial ovarian malignancy. Levels of urine CA125 and HE4 were significantly elevated in women with ovarian cancer compared to controls [CA125: 8.5 U/mL (IQR: 2.4-19.5) vs. 2.3 U/mL (IQR: 1.0-6.4), p = 0.01. HE4: 12.0 nmol/L (IQR: 10.3-23.1) vs. 6.7 nmol/L (IQR: 3.4-13.6), p = 0.006]. Urine CA125 and HE4 detected ovarian cancer with an AUC of 0.69 (95% CI: 0.55-0.82) and 0.71 (95% CI: 0.69-0.82), respectively (p = 0.73). A combination of urine CA125 and HE4 at optimal thresholds had a sensitivity of 82.4% (95% CI: 56.6-96.2) and was comparable to the sensitivity of serum CA125 [88.2% (95% CI: 63.6-98.5)]. Larger studies are required to confirm our findings, standardise urine collection, and evaluate optimal biomarker thresholds. Urine CA125 and HE4 may be useful non-invasive diagnostic tools to triage women for formal ovarian cancer investigations.

Keywords: CA125; HE4; detection; non-invasive; ovarian cancer; urine.

Grants and funding

C.E.B. is supported by a Manchester University NHS Foundation Trust Clinical Research Fellowship. E.J.C. was a National Institute for Health and Care Research (NIHR) Clinician Scientist (NIHR-CS-012-009) and is currently an NIHR Advanced Fellow (NIHR300650) supported by the NIHR Manchester Biomedical Research Centre (IS-BRC-1215-20007). K.N. is supported by a Cancer Research UK (CRUK) Manchester Cancer Research Centre Clinical Research Fellowship (C147/A25254) and the Wellcome Trust Manchester Translational Informatics Training Scheme. G.L.O. was an NIHR Academic Clinical Lecturer.