Bernhard J, Cella D F, Coates A S, Fallowfield L, Ganz P A, Moinpour C M, Mosconi P, Osoba D, Simes J, Hürny C
SIAK Coordinating Center, Bern, Switzerland.
Stat Med. 1998;17(5-7):517-32. doi: 10.1002/(sici)1097-0258(19980315/15)17:5/7<517::aid-sim799>3.0.co;2-s.
Measurement of quality of life (QOL) in cancer clinical trials has increased in recent years as more groups realize the importance of such endpoints. A key problem has been missing data. Some QOL data may unavoidably be missing, as for example when patients are too ill to complete forms. Other important sources are potentially avoidable and can broadly be divided into three categories: (i) methodological factors; (ii) logistic and administrative factors; (iii) patient-related factors. Logistic and administrative factors, for example, staff oversights, have proven to be most important. Since most QOL measurements require patient self-report, it is usually not possible to rectify the failure to collect baseline data or any follow-up assessments. There is strong evidence that such data are not 'missing at random', and cannot be ignored without introducing bias. Although several approaches to the analysis of partly missing data have been described, none is entirely satisfactory. Prevention of avoidable missing data is better than attempted cure. In July 1996, an international conference on missing QOL data in cancer clinical trials reported the experience of most major groups involved. This paper will serve as an introduction to the problem and provide an estimation of its magnitude, and approaches to its prevention and solution.
近年来，随着越来越多的研究团队认识到此类终点的重要性，癌症临床试验中生活质量（QOL）的测量有所增加。一个关键问题是数据缺失。一些生活质量数据可能不可避免地缺失，例如当患者病情太重而无法完成表格时。其他重要来源可能是可以避免的，大致可分为三类：（i）方法学因素；（ii）后勤和管理因素；（iii）患者相关因素。例如，后勤和管理因素，如工作人员疏忽，已被证明是最重要的。由于大多数生活质量测量需要患者自我报告，通常无法纠正未能收集基线数据或任何随访评估的情况。有强有力的证据表明，此类数据并非“随机缺失”，若不加以考虑则会引入偏差。尽管已经描述了几种分析部分缺失数据的方法，但没有一种是完全令人满意的。预防可避免的缺失数据比试图补救更好。1996年7月，一次关于癌症临床试验中生活质量数据缺失的国际会议报告了大多数主要研究团队的经验。本文将介绍该问题，估计其严重程度，并探讨预防和解决该问题的方法。
