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在随机临床试验中评估生活质量:对缺失数据进行校正。

Assessing quality of life in a randomized clinical trial: correcting for missing data.

作者信息

Gunnes Nina, Seierstad Taral G, Aamdal Steinar, Brunsvig Paal F, Jacobsen Anne-Birgitte, Sundstrøm Stein, Aalen Odd O

机构信息

Department of Biostatistics, University of Oslo, P,O, Box 1122 Blindern, N-0317 Oslo, Norway.

出版信息

BMC Med Res Methodol. 2009 Apr 30;9:28. doi: 10.1186/1471-2288-9-28.

Abstract

BACKGROUND

Health-related quality of life is a topic of current interest. This paper considers a randomized phase III study of radiation therapy with concurrent chemotherapy (docetaxel) versus radiation therapy alone in non-small cell lung cancer, stage III A/B. Longitudinal data on quality of life have been obtained through repeated administration of a multi-item questionnaire (EORTC QLQ-C30) developed by the European Organisation for Research and Treatment of Cancer. Missingness in the data is owing to patients having failed to complete the questionnaire at some of the scheduled filling-in times.

METHODS

We have analysed a monotone (in terms of missingness) subset of the data as regards estimation of the mean score of a summary measure of self-reported quality of life in a hypothetical drop-out-free population at different points in time. Missingness is a difficult issue of great importance. We have therefore chosen to compare three different methods that are relatively easy to implement: the linear-increments method, the inverse-probability-weighting method and the Markov-process method. Single imputation has been applied in a supplementary analysis to fill in for all the non-consecutive missing score values prior to the execution of the estimation procedure.

RESULTS

For the response in focus, the observed mean score at a certain time is larger than the estimated mean scores, which implies that the true mean score is easily overestimated unless the missingness is appropriately adjusted for. Comparison of the treatment arms shows a significant difference in mean score at the end of treatment.

CONCLUSION

Use of proper methodology developed for analysing data subject to missingness is necessary to reduce potential estimation bias. The quality of life of patients receiving radiation therapy with concurrent chemotherapy (docetaxel) appears somewhat worse than that of patients receiving radiation therapy alone in the period during which treatment is given. The conclusions are robust for the choice of statistical methods.

摘要

背景

健康相关生活质量是当前备受关注的话题。本文探讨了一项随机III期研究,该研究对比了同步化疗(多西他赛)联合放疗与单纯放疗在III A/B期非小细胞肺癌治疗中的效果。通过重复使用由欧洲癌症研究与治疗组织开发的多项目问卷(EORTC QLQ-C30)获取了生活质量的纵向数据。数据缺失是由于患者未能在部分预定填写时间完成问卷。

方法

我们分析了数据的一个单调(就缺失情况而言)子集,以估计在不同时间点假设无失访人群中自我报告生活质量综合指标的平均得分。缺失问题是一个极为重要且棘手的问题。因此,我们选择比较三种相对易于实施的不同方法:线性增量法、逆概率加权法和马尔可夫过程法。在补充分析中应用了单一填补法,在执行估计程序之前填补所有非连续缺失得分值。

结果

对于所关注的反应,在某一时刻观察到的平均得分高于估计的平均得分,这意味着除非对缺失情况进行适当调整,否则真实平均得分很容易被高估。治疗组之间的比较显示治疗结束时平均得分存在显著差异。

结论

使用为分析存在缺失的数据而开发的适当方法对于减少潜在的估计偏差是必要的。在治疗期间,接受同步化疗(多西他赛)联合放疗的患者的生活质量似乎比单纯接受放疗的患者略差。这些结论对于统计方法的选择具有稳健性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cde6/2698910/ab532aa29336/1471-2288-9-28-1.jpg

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