Progrediente Nierenerkrankungen

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• 作者：Prof. Dr. G. Mayer
• 刊名：Der Nephrologe
• 出版年：2016
• 出版时间：July 2016
• 年：2016
• 卷：11
• 期：4
• 页码：246-251
• 全文大小：196 KB
• 刊物主题：Nephrology; Angiology; Metabolic Diseases; Oncology; Transplant Surgery; Urology/Andrology;
• 出版者：Springer Berlin Heidelberg
• ISSN：1862-0418
• 卷排序：11

文摘

In recent years many publications have dealt with new diagnostic, prognostic and predictive biomarkers (BM). Prognostic BMs do not necessarily represent pathophysiologically relevant disease processes but they are often used to establish or improve risk prediction models. Good models estimate the risk of clinically relevant endpoints and take important aspects, such as competing risks into consideration. They are developed in representative cohorts ideally established for this purpose and validated in independent populations; their quality is assessed by statistical parameters describing discrimination and calibration. For the prediction of risk of chronic renal disease progression only few models meet all these criteria. In contrast validated risk estimators, such as the Framingham risk score, are available in cardiovascular medicine. It has been shown that in these models the addition of new BMs does not usually increase the predictive power in general but only in subgroups of the population (e. g. those with intermediate risk). Predictive biomarkers support therapeutic decisions and are marketed as companion diagnostics. They reflect the molecular pathophysiology of the disease as well as the mode of action of the medication used. Because our knowledge on these processes in the field of chronic renal disease is increasing and new drugs will enter the market, it can therefore be assumed that more predictive biomarkers will become available. Before these can be utilized in clinical practice they have to gain acceptance by clinicians as well as healthcare economists. Examples from other disciplines show that this is most likely for BMs that enter the market at the same time as a new drug.KeywordsBiomarkersDiagnosisPrognosisRisk prediction modelCompanion diagnostics