Department of Laboratory Medicine, Third Affiliated Hospital, Sun Yat-sen University, PR China.
Cell-gene Therapy Translational Medicine Research Center, Key Laboratory of Liver Disease of Guangdong Province, Third Affiliated Hospital of Sun Yat-sen University, PR China.
Clin Chim Acta. 2018 Mar;478:7-12. doi: 10.1016/j.cca.2017.12.018. Epub 2017 Dec 13.
Hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF) in china is a critical clinical syndrome with a high short-term mortality. This study aimed to construct and validate a model for neutrophil to lymphocyte ratio (NLR)-based nomogram for 3-month mortality estimation for patients with ACLF.
The nomogram was based on a retrospectively study of 96 patients with ACLF. The predictive accuracy and discriminative ability of nomogram were evaluated by a concordance index (C-index), and calibration curve, comparing with model for end-stage liver disease (MELD) score. The results were validated using bootstrap resampling and an external cohort of 88 patients.
A total of 184 patients with ACLF were enrolled, with 3-month mortality of 40.76%. The cut-off value for NLR was 5.7 using X-tile program. Patients with NLR>5.7 had significantly higher mortality (p<0.001). On multivariate analysis of the training cohort, independent factors for survival were age, NLR and total bilirubin, which were all selected into the nomogram. The calibration curve for probability of survival showed optimal agreement between prediction by nomogram and actual observation. The C-index of nomogram was higher than that of MELD score for predicting survival (0.72 vs 0.56). The results were confirmed in validation cohort.
The proposed nomogram with NLR resulted in more accurate prognostic prediction for patients with HBV-related ACLF.
中国乙型肝炎病毒（HBV）相关慢加急性肝衰竭（ACLF）是一种具有高短期死亡率的严重临床综合征。本研究旨在构建和验证基于中性粒细胞与淋巴细胞比值（NLR）的列线图模型，用于预测 ACLF 患者的 3 个月死亡率。
该列线图基于 96 例 ACLF 患者的回顾性研究。通过一致性指数（C 指数）和校准曲线评估列线图的预测准确性和判别能力，并与终末期肝病模型（MELD）评分进行比较。使用 bootstrap 重采样和 88 例外部队列对结果进行验证。
共纳入 184 例 ACLF 患者，3 个月死亡率为 40.76%。X-tile 程序确定 NLR 的截断值为 5.7。NLR>5.7 的患者死亡率明显更高（p<0.001）。在训练队列的多变量分析中，生存的独立因素是年龄、NLR 和总胆红素，这些因素均被选入列线图。生存率预测的校准曲线显示，列线图预测与实际观察之间具有最佳一致性。列线图的 C 指数高于 MELD 评分（0.72 比 0.56）用于预测生存率。验证队列的结果得到了证实。
该 NLR 列线图模型可更准确地预测 HBV 相关 ACLF 患者的预后。
Zotero 插件