Chovanec Josef, Selingerova Iveta, Greplova Kristina, Antonsen Sofie Leisby, Nalezinska Monika, Høgdall Claus, Høgdall Estrid, Søgaard-Andersen Erik, Jochumsen Kirsten M, Fabian Pavel, Valik Dalibor, Zdrazilova-Dubska Lenka
Clinic of Surgical Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic.
Regional Centre of Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic.
Oncotarget. 2017 Nov 21;8(64):108213-108222. doi: 10.18632/oncotarget.22599. eCollection 2017 Dec 8.
We investigated the efficacy of circulating biomarkers together with histological grade and age to predict deep myometrial invasion (dMI) in endometrial cancer patients.
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.
In non-cancer individuals, serum HE4 levels increase log-linearly with reduced glomerular filtration of eGFR ≤ 90 ml/min/1.73 m. HE4ren, adjusting HE4 serum levels to decreased eGFR, was calculated as follows: HE4ren = exp[ln(HE4) + 2.182 × (eGFR-90) × 10]. 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.
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.
我们研究了循环生物标志物联合组织学分级和年龄对预测子宫内膜癌患者肌层深部浸润(dMI)的有效性。
根据估算肾小球滤过率的eGFR-EPI公式,对HE4血清水平进行调整以适应肾小球滤过率降低的情况,从而开发出HE4ren。在子宫内膜癌(EC)患者围手术期肌层浸润深度的背景下,评估术前HE4、HE4ren、CA125、年龄和分级。基于120例EC患者的单机构数据,通过二元逻辑回归建立连续和分类模型,用于任何分级以及G1或G2患者,并根据379例EC患者的多中心数据进行验证。
在非癌症个体中,当估算肾小球滤过率(eGFR)≤90 ml/min/1.73 m²时,血清HE4水平呈对数线性增加。HE4ren是将HE4血清水平调整为降低的eGFR后计算得出的,公式如下:HE4ren = exp[ln(HE4) + 2.182 × (eGFR - 90) × 10]。血清HE4与年龄相关,但HE4ren与年龄无关。在两个验证集中,连续的HE4ren、年龄和分级模型分别预测G1或G2 EC患者的dMI时,曲线下面积(AUC)分别为0.833和0.715。在G1或G2患者的简化分类模型中,危险因素确定为2级、HE4ren≥45 pmol/l、CA125≥35 U/ml和年龄≥60岁。加权危险因素的累积能够将EC患者分为dMI的低风险或高风险组。
我们引入了HE4ren公式,将血清HE4水平调整为降低的eGFR,从而能够量化女性中HE4产生和消除的时间依赖性变化,而与年龄和肾功能无关。利用HE4ren可提高基于生物标志物的模型预测子宫内膜癌患者dMI的性能。