A Predictive Model for Estimation Risk of Proliferative Lupus Nephritis.
A Predictive Model for Estimation Risk of Proliferative Lupus Nephritis.
复制标题
增殖性狼疮性肾炎评估风险的预测模型
DOI：
10.4103/0366-6999.232809
复制
发表时间：
2018-06-05
影响因子：
6.1
通讯作者：
Yu XQ
中科院分区：
文献类型：
--
作者：
Chen DN;Fan L;Wu YX;Zhou Q;Chen W;Yu XQ
背景资料：狼疮性肾炎（LN）通过肾活检分为增殖性和非增殖性两种形式，其预后不同，但并不是每个LN患者都可以进行肾活检。本研究旨在通过建立预测模型来评估增殖性LN的可能性，从而建立一种替代工具。研究方法：在这项经活检证实的LN回顾性队列中，选择了382例开发队列患者、193例内部验证队列患者和164例外部验证队列新诊断患者。建立Logistic回归模型，计算一致性统计量（C-统计量）、赤池信息准则（AIC）、综合区分度改进、Hosmer-Lemeshow检验和净重新分类改进，评价模型的性能和有效性。结果：增殖型LN的患病率为77.7%。包括年龄、性别、收缩压、血红蛋白、蛋白尿、血尿和血清C3在内的模型在预测增殖性LN的风险方面表现良好（AIC为291，C统计为0.84）。在内部和外部验证队列中，该模型显示出良好的区分和校准能力（C统计量分别为0.84和0.82，P值分别为0.99和0.75）。结论：本研究开发并验证了一个模型，包括人口统计学和临床指标，以评估出现增殖性LN的概率，以指导治疗决策和结果。
Background: Lupus nephritis (LN) is classified by renal biopsy into proliferative and nonproliferative forms, with distinct prognoses, but renal biopsy is not available for every LN patient. The present study aimed to establish an alternate tool by building a predictive model to evaluate the probability of proliferative LN. Methods: In this retrospective cohort with biopsy-proven LN, 382 patients in development cohort, 193 in internal validation cohort, and 164 newly diagnosed patients in external validation cohort were selected. Logistic regression model was established, and the concordance statistics (C-statistics), Akaike information criterion (AIC), integrated discrimination improvement, Hosmer-Lemeshow test, and net reclassification improvement were calculated to evaluate the performance and validation of models. Results: The prevalence of proliferative LN was 77.7% in the whole cohort. A model, including age, gender, systolic blood pressure, hemoglobin, proteinuria, hematuria, and serum C3, performed well on good-of-fit and discrimination in the development chohort to predict the risk of proliferative LN (291 for AIC and 0.84 for C-statistics). In the internal and external validation cohorts, this model showed good capability for discrimination and calibration (0.84 and 0.82 for C-statistics, and 0.99 and 0.75 for P values, respectively). Conclusion: This study developed and validated a model including demographic and clinical indices to evaluate the probability of presenting proliferative LN to guide therapeutic decisions and outcomes.
登录
查看更多内容
影响因子：
13.2
作者：
Mittal, B;Hurwitz, S;Singh, AK
通讯作者：
Singh, AK
影响因子：
19.6
作者：
Yokoyama, H;Wada, T;Furuichi, K
通讯作者：
Furuichi, K
DOI：
10.1016/s1470-2045(14)71116-7
发表时间：
2015-04
期刊：
The Lancet. Oncology
影响因子：
--
作者：
Balachandran VP;Gonen M;Smith JJ;DeMatteo RP
通讯作者：
DeMatteo RP
影响因子：
2.3
作者：
Rovin, Brad H.;Parikh, Samir V.;Alvarado, Anthony
通讯作者：
Alvarado, Anthony
影响因子：
19.6
作者：
Hill, GS;Delahousse, M;Bariéty, J
通讯作者：
Bariéty, J