Uric acid and the prediction models of tumor lysis syndrome in AML.
Uric acid and the prediction models of tumor lysis syndrome in AML.
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DOI：
10.1371/journal.pone.0119497
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Hsu JW
中科院分区：
文献类型：
--
作者：
Ejaz AA;Pourafshar N;Mohandas R;Smallwood BA;Johnson RJ;Hsu JW
我们研究了血清尿酸（SUA）预测实验室肿瘤溶解综合征（LTLS）的能力，并将其与急性髓系白血病患者的常见实验室变量、细胞遗传学特征、肿瘤标志物和预测模型进行了比较。在这项回顾性研究中，根据SUA临界值对患者进行LTLS风险分层，并将区分能力与当前预测模型进行比较。低、中、高危组LTLS发生率分别为17.8%、21%和62.5%。SUA是LTLS的独立预测因子（校正OR 1.12，CI 95% 1.0-1.3，p = 0.048）。根据ROC曲线，SUA预测LTLS的区分能力上级LDH、细胞遗传学谱、肿瘤标志物和联合模型，但不优于WBC（AUCWBC 0.679）。然而，在高危SUA和高危WBC之间的比较中，SUA的区分能力上级WBC（AUCSUA 0.664 vs. AUCWBC 0.520; p <0.001）。SUA也表现出比预测模型更好的性能（高风险SUAAUC 0.695，p<0.001）。在高风险组的直接比较中，SUA再次证明在预测LTLS方面优于预测模型（高风险SUAAUC 0.668，p = 0.001），接近组合模型（AUC 0.685，p<0.001）。总之，与其他预测模型相比，单独的SUA对LTLS具有相当的预测性。
We investigated the ability of serum uric acid (SUA) to predict laboratory tumor lysis syndrome (LTLS) and compared it to common laboratory variables, cytogenetic profiles, tumor markers and prediction models in acute myeloid leukemia patients. In this retrospective study patients were risk-stratified for LTLS based on SUA cut-off values and the discrimination ability was compared to current prediction models. The incidences of LTLS were 17.8%, 21% and 62.5% in the low, intermediate and high-risk groups, respectively. SUA was an independent predictor of LTLS (adjusted OR 1.12, CI95% 1.0–1.3, p = 0.048). The discriminatory ability of SUA, per ROC curves, to predict LTLS was superior to LDH, cytogenetic profile, tumor markers and the combined model but not to WBC (AUCWBC 0.679). However, in comparisons between high-risk SUA and high-risk WBC, SUA had superior discriminatory capability than WBC (AUCSUA 0.664 vs. AUCWBC 0.520; p <0.001). SUA also demonstrated better performance than the prediction models (high-risk SUAAUC 0.695, p<0.001). In direct comparison of high-risk groups, SUA again demonstrated superior performance than the prediction models (high-risk SUAAUC 0.668, p = 0.001) in predicting LTLS, approaching that of the combined model (AUC 0.685, p<0.001). In conclusion, SUA alone is comparable and highly predictive for LTLS than other prediction models.
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影响因子：
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2007-01-01
影响因子：
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