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Jingxin JIANG, Weiwei PAN, Liyang SUN, Liwei PANG, Hailang CHEN, Jian HUANG, Wuzhen CHEN. Real-world data and evidence: pioneering frontiers in precision oncology[J]. Journal of Zhejiang University Science B, 1998, -1(-1): .
@article{title="Real-world data and evidence: pioneering frontiers in precision oncology",
author="Jingxin JIANG, Weiwei PAN, Liyang SUN, Liwei PANG, Hailang CHEN, Jian HUANG, Wuzhen CHEN",
journal="Journal of Zhejiang University Science B",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B2400285"
}
%0 Journal Article
%T Real-world data and evidence: pioneering frontiers in precision oncology
%A Jingxin JIANG
%A Weiwei PAN
%A Liyang SUN
%A Liwei PANG
%A Hailang CHEN
%A Jian HUANG
%A Wuzhen CHEN
%J Journal of Zhejiang University SCIENCE B
%V -1
%N -1
%P
%@ 1673-1581
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B2400285
TY - JOUR
T1 - Real-world data and evidence: pioneering frontiers in precision oncology
A1 - Jingxin JIANG
A1 - Weiwei PAN
A1 - Liyang SUN
A1 - Liwei PANG
A1 - Hailang CHEN
A1 - Jian HUANG
A1 - Wuzhen CHEN
J0 - Journal of Zhejiang University Science B
VL - -1
IS - -1
SP -
EP -
%@ 1673-1581
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B2400285
Abstract: Real-world studies (RWSs) have emerged as a transformative force in oncology research, complementing traditional randomized controlled trials (RCTs) by providing comprehensive insights into cancer care within routine clinical settings. This review examines the evolving landscape of RWSs in oncology, focusing on their implementation, methodological considerations, and impact on precision medicine. We systematically analyze how RWSs leverage diverse data sources - including electronic health records (EHRs), insurance claims, and patient registries - to generate evidence that bridges the gap between controlled clinical trials and real-world clinical practice. The review underscores the key contributions of RWSs, including capturing therapeutic outcomes in traditionally underrepresented populations, expanding drug indications, and evaluating long-term safety and effectiveness in routine clinical settings. While acknowledging significant challenges, including data-quality variability and privacy concerns, we discuss how emerging technologies like artificial intelligence are helping to address these limitations. Integration of RWSs with traditional clinical research is revolutionizing the paradigm of precision oncology and enabling more personalized treatment approaches based on real-world evidence.
Open peer comments: Debate/Discuss/Question/Opinion
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