Department of Endocrinology, Diabetes and Metabolic Diseases "Mladen Sekso", University Hospital Center "Sestre Milosrdnice", University of Zagreb School of Medicine, Zagreb, Croatia.
University of Zagreb School of Medicine, Zagreb, Croatia.
Endocrine. 2018 Jun;60(3):395-406. doi: 10.1007/s12020-018-1592-6. Epub 2018 Apr 9.
Chromogranin A (CgA) is a valuable biomarker for detection and follow-up of patients with neuroendocrine neoplasms (NENs). However, various comorbidities may influence serum CgA, which decreases its diagnostic accuracy. We aimed to investigate which laboratory parameters are independently associated with increased CgA in real-life setting and to develop a scoring system, which could improve the diagnostic accuracy of CgA in detecting patients with NENs.
This retrospective study included 55 treatment naïve patients with NENs and160 patients with various comorbidities but without NEN (nonNENs). Scoring system (CgA-score) was developed based on z-scores obtained from receiver operating curve analysis for each parameter that was associated with elevated serum CgA in nonNENs.
CgA correlated positively with serum BUN, creatinine, α2-globulin, red-cell distribution width, erythrocyte sedimentation rate, plasma glucose and correlated inversely with hemoglobin, thrombocytes and serum albumin. Serum CgA was also associated with the presence of chronic renal failure, arterial hypertension and diabetes and the use of PPI. In the entire study population, CgA showed an area under the curve of 0.656. Aforementioned parameters were used to develop a CgA-score. In a cohort of patients with CgA-score <12.0 (N = 87), serum CgA >156.5 ng/ml had 77.8% sensitivity and 91.5% specificity for detecting NENs (AUC 0.841, 95% CI 0.713-0.969, P < 0.001). Serum CgA had no diagnostic value in detecting NENs in patients with CgA-score >12.0 (AUC 0.554, 95% CI 0.405-0.702, P = 0.430).
CgA-score encompasses a wide range of comorbidities and represents a promising tool that could improve diagnostic performance of CgA in everyday clinical practice.
嗜铬粒蛋白 A(CgA)是一种用于检测和随访神经内分泌肿瘤(NEN)患者的有价值的生物标志物。然而,各种合并症可能会影响血清 CgA,从而降低其诊断准确性。我们旨在研究哪些实验室参数与真实环境中 CgA 的升高独立相关,并开发一种评分系统,以提高 CgA 检测 NEN 患者的诊断准确性。
这项回顾性研究纳入了 55 例未经治疗的 NEN 患者和 160 例患有各种合并症但无 NEN(非 NEN)的患者。评分系统(CgA 评分)是基于与非 NEN 患者血清 CgA 升高相关的每个参数的接受者操作特征曲线分析获得的 z 分数而制定的。
CgA 与血清 BUN、肌酐、α2-球蛋白、红细胞分布宽度、红细胞沉降率、血浆葡萄糖呈正相关,与血红蛋白、血小板和血清白蛋白呈负相关。血清 CgA 也与慢性肾衰竭、动脉高血压和糖尿病以及使用质子泵抑制剂(PPI)的存在相关。在整个研究人群中,CgA 的曲线下面积为 0.656。上述参数用于开发 CgA 评分。在 CgA 评分<12.0 的患者队列中(N=87),血清 CgA>156.5ng/ml 对检测 NEN 的敏感性为 77.8%,特异性为 91.5%(AUC 0.841,95%CI 0.713-0.969,P<0.001)。在 CgA 评分>12.0 的患者中,血清 CgA 对检测 NEN 无诊断价值(AUC 0.554,95%CI 0.405-0.702,P=0.430)。
CgA 评分涵盖了广泛的合并症,是一种有前途的工具,可提高 CgA 在日常临床实践中的诊断性能。