Henderson Valerie C, Demko Nadine, Hakala Amanda, MacKinnon Nathalie, Federico Carole A, Fergusson Dean, Kimmelman Jonathan
Studies of Translation, Ethics and Medicine Research Group, Biomedical Ethics Unit, McGill University, Montréal, Canada.
Department of Clinical Epidemiology, Ottawa Hospital Research Institute, Ottawa, Canada.
Elife. 2015 Oct 13;4:e08351. doi: 10.7554/eLife.08351.
Poor study methodology leads to biased measurement of treatment effects in preclinical research. We used available sunitinib preclinical studies to evaluate relationships between study design and experimental tumor volume effect sizes. We identified published animal efficacy experiments where sunitinib monotherapy was tested for effects on tumor volume. Effect sizes were extracted alongside experimental design elements addressing threats to valid clinical inference. Reported use of practices to address internal validity threats was limited, with no experiments using blinded outcome assessment. Most malignancies were tested in one model only, raising concerns about external validity. We calculate a 45% overestimate of effect size across all malignancies due to potential publication bias. Pooled effect sizes for specific malignancies did not show apparent relationships with effect sizes in clinical trials, and we were unable to detect dose-response relationships. Design and reporting standards represent an opportunity for improving clinical inference.
在临床前研究中，糟糕的研究方法会导致治疗效果的测量存在偏差。我们利用现有的舒尼替尼临床前研究来评估研究设计与实验肿瘤体积效应大小之间的关系。我们确定了已发表的动物疗效实验，这些实验测试了舒尼替尼单药治疗对肿瘤体积的影响。效应大小与解决有效临床推断威胁的实验设计要素一同提取。报告中针对内部有效性威胁所采用的方法有限，没有实验采用盲法结局评估。大多数恶性肿瘤仅在一种模型中进行测试，这引发了对外部有效性的担忧。由于潜在的发表偏倚，我们计算出所有恶性肿瘤的效应大小被高估了45%。特定恶性肿瘤的合并效应大小与临床试验中的效应大小没有明显关系，并且我们无法检测到剂量反应关系。设计和报告标准是改善临床推断的一个机会。
