Johansen H K, Gotzsche P C
The Nordic Cochrane Centre, Rigshospitalet, Copenhagen, Denmark.
JAMA. 1999 Nov 10;282(18):1752-9. doi: 10.1001/jama.282.18.1752.
Meta-analyses may become biased if the reported data in the individual trials are biased and if overlap among trials cannot be identified. We describe the unanticipated problems we encountered in collecting data for a meta-analysis comparing a new antifungal agent, fluconazole, with amphotericin B in patients with cancer complicated by neutropenia. In 3 large trials that comprised 43% of the patients identified for the meta-analysis, results for amphotericin B were combined with results for nystatin in a "polyene" group. Because nystatin is recognized as an ineffective drug in these circumstances, this approach creates a bias in favor of fluconazole. Furthermore, 79% of the patients were randomized to receive oral amphotericin B, which is poorly absorbed and not an established treatment, in contrast to intravenous amphotericin B, which was administered in 4 of 5 placebo-controlled trials, or 86% of patients. It was unclear whether there was overlap among the "polyene" trials, and it is possible that results from single-center trials were included in multicenter trial reports. We were unable to obtain information to clarify these issues from the trial authors or the manufacturer of fluconazole. Two of 11 responding authors replied that the data were with the drug manufacturer and two indicated that they did not have access to their data because of change of affiliation. In the meta-analyses, fluconazole and amphotericin B (mostly given orally) had similar effects (13 trials), whereas nystatin was no better than placebo (3 trials). Since individual trials are rarely conclusive, investigators, institutions, and pharmaceutical companies should provide essential details about their work to ensure that meta-analyses can accurately reflect the studies conducted and that patients will realize maximum benefits from treatments. We recommend that investigators keep copies of their trial data to help facilitate accurate and unbiased meta-analyses.
如果各个试验报告的数据存在偏差，且无法识别试验之间的重叠情况，那么荟萃分析可能会产生偏差。我们描述了在为一项荟萃分析收集数据时遇到的意外问题，该荟萃分析旨在比较一种新型抗真菌药物氟康唑与两性霉素B在合并中性粒细胞减少症的癌症患者中的疗效。在3项大型试验中，共有43%纳入荟萃分析的患者，两性霉素B的结果与制霉菌素的结果合并为一个“多烯”组。由于在这些情况下制霉菌素被认为是一种无效药物，这种方法会产生有利于氟康唑的偏差。此外，79%的患者被随机分配接受口服两性霉素B，其吸收不良且并非既定治疗方法，相比之下，5项安慰剂对照试验中有4项（即86%的患者）使用的是静脉注射两性霉素B。尚不清楚“多烯”试验之间是否存在重叠，而且单中心试验的结果有可能被纳入了多中心试验报告中。我们无法从试验作者或氟康唑制造商处获得信息来澄清这些问题。11位回复的作者中有两位表示数据在药物制造商处，另外两位表示由于所属机构变更而无法获取数据。在荟萃分析中，氟康唑和两性霉素B（大多为口服给药）具有相似的效果（13项试验），而制霉菌素并不比安慰剂更好（3项试验）。由于单个试验很少能得出定论，研究人员、机构和制药公司应提供其工作的基本细节，以确保荟萃分析能够准确反映所开展的研究，并且患者能够从治疗中获得最大益处。我们建议研究人员保留试验数据的副本，以帮助进行准确且无偏差的荟萃分析。
