The next generation of evidence-based medicine

被引：157

作者：

Subbiah, Vivek ^{[1
,2
,3
]}

机构：

[1] Univ Texas MD Anderson Canc Ctr, Dept Invest Canc Therapeut, Div Canc Med, Houston, TX 77030 USA

[2] Univ Texas MD Anderson Canc Ctr, Div Pediat, Houston, TX 77030 USA

[3] Univ Texas MD Anderson Canc Ctr, MD Anderson Canc Network, Houston, TX 77030 USA

来源：

NATURE MEDICINE | 2023年 / 29卷 / 01期

基金：

美国国家卫生研究院;

关键词：

CLINICAL-TRIAL; OPEN-LABEL; CANCER ARROW; MULTI-COHORT; LUNG; EFFICACY; INDUSTRY; SELPERCATINIB; PRALSETINIB; SMARTWATCH;

D O I：

10.1038/s41591-022-02160-z

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Technological advances are transforming evidence generation in medicine; for these advances to impact public health, the clinical trial landscape must evolve and adapt to keep pace. Recently, advances in wearable technologies, data science and machine learning have begun to transform evidence-based medicine, offering a tantalizing glimpse into a future of next-generation 'deep' medicine. Despite stunning advances in basic science and technology, clinical translations in major areas of medicine are lagging. While the COVID-19 pandemic exposed inherent systemic limitations of the clinical trial landscape, it also spurred some positive changes, including new trial designs and a shift toward a more patient-centric and intuitive evidence-generation system. In this Perspective, I share my heuristic vision of the future of clinical trials and evidence-based medicine.

引用

页码：49 / 58

页数：10

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