Aberdeen Applied Renal Research Collaboration, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK NHS Grampian, Aberdeen, UK.
NHS Grampian, Aberdeen, UK.
Nephrol Dial Transplant. 2015 Sep;30(9):1507-17. doi: 10.1093/ndt/gfv089. Epub 2015 May 5.
Chronic kidney disease (CKD) is common and important due to poor outcomes. An ability to stratify CKD care based on outcome risk should improve care for all. Our objective was to develop and validate 5-year outcome prediction tools in a large population-based CKD cohort. Model performance was compared with the recently reported 'kidney failure risk equation' (KFRE) models.
Those with CKD in the Grampian Laboratory Outcomes Mortality and Morbidity Study-I (3396) and -II (18 687) cohorts were used to develop and validate a renal replacement therapy (RRT) prediction tool. The discrimination, calibration and overall performance were assessed. The net reclassification index compared performance of the developed model and the 3- and 4-variable KFRE model to predict RRT in the validation cohort.
The developed model (with measures of age, sex, excretory renal function and proteinuria) performed well with a C-statistic of 0.938 (0.918-0.957) and Hosmer-Lemeshow (HL) χ(2) statistic 4.6. In the validation cohort (18 687), the developed model falsely identified fewer as high risk (414 versus 3278 individuals) compared with the KFRE 3-variable model (measures of age, sex and excretory renal function), but had more false negatives (58 versus 21 individuals). The KFRE 4-variable model could only be applied to 2274 individuals because of a lack of baseline urinary albumin creatinine ratio data, thus limiting its use in routine clinical practice.
CKD outcome prediction tools have been developed by ourselves and others. These tools could be used to stratify care, but identify both false positives and -negatives. Further refinement should optimize the balance between identifying those at increased risk with clinical utility for stratifying care.
慢性肾脏病（CKD）较为常见且后果严重，因此意义重大。若能根据结局风险对 CKD 患者进行分层管理，将有望改善整体照护水平。本研究旨在建立并验证一个在大型基于人群的 CKD 队列中预测 5 年结局的工具，并与最近报道的“肾衰竭风险方程”（KFRE）模型进行比较。
利用 Grampian 实验室结局、死亡率和发病率研究 I（3396 例）和 II（18687 例）队列中患有 CKD 的患者建立并验证肾脏替代治疗（RRT）预测工具。评估其区分度、校准度和整体性能。通过净重新分类指数比较该模型和 3 变量及 4 变量 KFRE 模型在验证队列中预测 RRT 的性能。
该模型（包含年龄、性别、肾功能和蛋白尿的指标）性能良好，C 统计量为 0.938（0.918-0.957），Hosmer-Lemeshow（HL）χ2 统计量为 4.6。在验证队列（18687 例）中，与 KFRE 3 变量模型（包含年龄、性别和肾功能的指标）相比，该模型错误地将较少的患者划分为高危（414 例比 3278 例），但漏诊的患者更多（58 例比 21 例）。由于缺乏基线尿白蛋白/肌酐比值数据，KFRE 4 变量模型仅能应用于 2274 例患者，这限制了其在常规临床实践中的应用。
我们和其他研究人员已经建立了 CKD 结局预测工具。这些工具可用于分层管理，但会出现假阳性和假阴性。进一步优化可在提高识别高危患者的准确性和为分层管理提供临床实用性之间取得平衡。
