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使用潜在增长曲线模型评估达贝泊汀对血红蛋白和疲劳的影响。

Use of latent growth curve models for assessing the effects of darbepoetin alfa on hemoglobin and fatigue.

机构信息

Center for Health Outcomes Research, United BioSource Corporation, 20 Bloomsbury Square, London WC1A 2NS, UK.

出版信息

Contemp Clin Trials. 2010 Mar;31(2):172-9. doi: 10.1016/j.cct.2009.12.006. Epub 2010 Jan 7.

DOI:10.1016/j.cct.2009.12.006
PMID:20060499
Abstract

BACKGROUND

The relationship between darbepoetin alfa and fatigue in chemotherapy-induced anemia (CIA) patients is complex because of patients receiving transfusions and the mediating effect of hemoglobin. Latent growth models (LGMs) were used to examine simultaneously relationships among drug exposure, fatigue outcomes, covariates, and mediating factors.

METHODS

Data from four CIA studies (AMG 20010145: small cell lung cancer, n=547; AMG 980297: lung cancer, n=288; AMG 20000161: lymphoproliferative malignancies, n=339; AMG 20030232: non-myeloid malignancies, n=320) were analyzed separately. Patients reported fatigue using the FACT-Fatigue. The effect of darbepoetin alfa on FACT-F changes mediated through hemoglobin changes was examined with LGMs controlling for transfusions, age, sex, baseline ECOG performance status, and health status (EQ-5D VAS). Model fit was assessed using multiple indices including the comparative fit index (CFI).

RESULTS

Darbepoetin alfa increased hemoglobin levels which were associated with decreases in fatigue. Increases in hemoglobin were statistically significantly (p<0.05) related to decreases in fatigue in the studies (AMG 20030145: beta=0.28; AMG 980297: beta=0.46; AMG 20000161: beta=0.59; and AMG 20030232: beta=0.39). Darbepoetin alfa statistically significantly increased hemoglobin (AMG 20010145:beta=0.50, AMG 980297:beta=0.53, AMG 20000161:beta=0.47, and AMG 20030232:beta=0.30) while controlling for covariates. Model fit was acceptable (CFI> or =0.89) in all studies.

CONCLUSIONS

Results indicate LGMs may be a valuable statistical method for modeling complex relationships among clinical and patient reported outcomes. A statistically significant effect of darbepoetin alfa on fatigue change through hemoglobin change occurred across four studies, after modeling the effects of transfusions, age, sex, EQ-5D VAS and ECOG.

摘要

背景

达贝泊汀α与化疗引起的贫血(CIA)患者疲劳之间的关系很复杂,因为患者接受输血,且血红蛋白具有中介作用。潜增长模型(LGM)用于同时研究药物暴露、疲劳结局、协变量和中介因素之间的关系。

方法

分别分析四项 CIA 研究(AMG 20010145:小细胞肺癌,n=547;AMG 980297:肺癌,n=288;AMG 20000161:淋巴增生性恶性肿瘤,n=339;AMG 20030232:非髓性恶性肿瘤,n=320)的数据。患者使用 FACT-Fatigue 报告疲劳。通过 LGM 控制输血、年龄、性别、基线 ECOG 表现状态和健康状况(EQ-5D VAS),检查达贝泊汀α对血红蛋白变化介导的 FACT-F 变化的影响。使用包括比较拟合指数(CFI)在内的多个指数评估模型拟合度。

结果

达贝泊汀α增加了血红蛋白水平,这与疲劳的减轻有关。在这些研究中,血红蛋白的增加与疲劳的减轻呈统计学显著相关(p<0.05)(AMG 20030145:beta=0.28;AMG 980297:beta=0.46;AMG 20000161:beta=0.59;和 AMG 20030232:beta=0.39)。达贝泊汀α在控制协变量的情况下,统计学上显著增加了血红蛋白(AMG 20010145:beta=0.50,AMG 980297:beta=0.53,AMG 20000161:beta=0.47,和 AMG 20030232:beta=0.30)。所有研究的模型拟合度均可接受(CFI>或=0.89)。

结论

结果表明,LGM 可能是一种用于建模临床和患者报告结局之间复杂关系的有价值的统计方法。在对输血、年龄、性别、EQ-5D VAS 和 ECOG 的影响进行建模后,达贝泊汀α通过血红蛋白变化对疲劳变化的统计学显著影响发生在四项研究中。

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