Adjustment of serum HE4 to reduced glomerular filtration and its use in biomarker-based prediction of deep myometrial invasion in endometrial cancer
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Josef Chovanec1,2,*, Iveta Selingerova2,*, Kristina Greplova2,3, Sofie Leisby Antonsen4, Monika Nalezinska1, Claus Høgdall4, Estrid Høgdall5, Erik Søgaard-Andersen6, Kirsten M. Jochumsen7, Pavel Fabian8, Dalibor Valik2,3 and Lenka Zdrazilova-Dubska2,3
1Clinic of Surgical Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic
2Regional Centre of Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic
3Department of Laboratory Medicine, Masaryk Memorial Cancer Institute, Brno, Czech Republic
4Gynecologic Clinic, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
5Department of Pathology, Danish Cancer Biobank, Herlev University Hospital, Herlev, Denmark
6Department of Gynecology and Obstetrics, Aalborg University Hospital, Aalborg, Denmark
7Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
8Department of Oncological Pathology, Masaryk Memorial Cancer Institute, Brno, Czech Republic
*These authors have contributed equally to this work
Lenka Zdrazilova-Dubska, email: email@example.com
Keywords: predictive biomarkers; HE4; glomerular filtration rate; endometrial cancer; deep myometrial invasion
Received: August 11, 2017 Accepted: October 28, 2017 Published: November 21, 2017
Background: We investigated the efficacy of circulating biomarkers together with histological grade and age to predict deep myometrial invasion (dMI) in endometrial cancer patients.
Methods: HE4ren was developed adjusting HE4 serum levels towards decreased glomerular filtration rate as quantified by the eGFR-EPI formula. Preoperative HE4, HE4ren, CA125, age, and grade were evaluated in the context of perioperative depth of myometrial invasion in endometrial cancer (EC) patients. Continuous and categorized models were developed by binary logistic regression for any-grade and for G1-or-G2 patients based on single-institution data from 120 EC patients and validated against multicentric data from 379 EC patients.
Results: In non-cancer individuals, serum HE4 levels increase log-linearly with reduced glomerular filtration of eGFR ≤ 90 ml/min/1.73 m2. HE4ren, adjusting HE4 serum levels to decreased eGFR, was calculated as follows: HE4ren = exp[ln(HE4) + 2.182 × (eGFR-90) × 10-2]. Serum HE4 but not HE4ren is correlated with age. Model with continuous HE4ren, age, and grade predicted dMI in G1-or-G2 EC patients with AUC = 0.833 and AUC = 0.715, respectively, in two validation sets. In a simplified categorical model for G1-or-G2 patients, risk factors were determined as grade 2, HE4ren ≥ 45 pmol/l, CA125 ≥ 35 U/ml, and age ≥ 60. Cumulation of weighted risk factors enabled classification of EC patients to low-risk or high-risk for dMI.
Conclusions: We have introduced the HE4ren formula, adjusting serum HE4 levels to reduced eGFR that enables quantification of time-dependent changes in HE4 production and elimination irrespective of age and renal function in women. Utilizing HE4ren improves performance of biomarker-based models for prediction of dMI in endometrial cancer patients.
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