Development and validation of new flexible statistical methods for etiological and prognostic studies

我的研究方案将继续侧重于开发和验证用于分析健康数据的新的统计方法。特别是，与我的受训人员和合作者一起，我们将致力于制定新的方法，能够解释导致各种疾病发生或影响疾病发展的过程的复杂性。还将开发专门的方法，以便更有效地检测药物的潜在不良影响。这个问题具有越来越重要的社会意义，因为最近非常受欢迎的止痛药被高度宣传地撤回，被发现使心脏病发作和死亡的风险增加了一倍，这一问题得到了戏剧性的说明。检测这种不良影响并准确评估其影响是具有挑战性的，因为药物使用的剂量、模式和持续时间因受试者和时间的不同而不同。此外，目前还不清楚药物使用与其负面影响之间是否存在延迟，以及存在何种延迟。然而，最近在计算资源和统计理论方面的加速进展将使我们能够开发灵活的方法，避免限制性假设，并反映潜在和影响人类健康的过程的复杂性。

My research programme will continue focusing on the development and validation of new statistical methods for the analysis of health data. In particular, with my trainees and collaborators, we will aim at elaborating new methods that will be able to account for the complexity of the processes leading to the occurrence of various diseases or affecting disease progression. Specialized methods will also be developed to allow a more efficient detection of potential adverse effects of medications. This issue is of increasing societal importance as it has been recently dramatically illustrated by highly publicized withdrawals of very popular pain relief drugs that were found to double the risks of heart attacks and deaths due to heart disease. Detection of such adverse effects and accurate assessment of their impact are challenging because dose, patterns and duration of drug use vary across subjects and over time. Moreover, it is unclear whether and what delay may exist between drug use and its negative effects. However, recent accelerated progress in both computational resources and statistical theory will allow us to develop flexible methods that avoid restrictive assumptions and reflect the complexity of the processes underlying and affecting human health.