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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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Cancer publications using real-world data from the Taiwan National Health Insurance Research Database: Conceptual

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  • 1School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan, ROC.

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This study introduces a new framework for bibliometric analysis of cancer research, incorporating study design and disease factors. The analysis of real-world data reveals trends in cancer research topics and methodologies.

Keywords:
Bibliometric analysisCancerInterrupted time seriesTaiwan National Health Insurance ResearchTarget trial emulation

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Area of Science:

  • Bibliometrics
  • Cancer Research
  • Real-World Data Analysis

Background:

  • Traditional bibliometric analysis often omits crucial study-specific details like aims, design, and statistical methods.
  • This study addresses this gap by proposing a novel conceptual framework for cancer article bibliometrics.
  • The framework integrates both study-based and disease-based components for a more comprehensive analysis.

Purpose of the Study:

  • To develop and validate a conceptual framework for bibliometric analysis of cancer research using real-world data.
  • To investigate the distribution and temporal trends of study-based and disease-based components in cancer articles.
  • To provide a more nuanced understanding of cancer research evolution.

Main Methods:

  • Extracted and cross-validated study-based (aims, design, statistics) and disease-based components from cancer articles.
  • Utilized the Taiwan National Health Insurance Research Database (NHIRD) for data spanning 2006-2022.
  • Analyzed publication trends, common research topics, study designs, statistical methods, and cancer sites.

Main Results:

  • A significant increase in annual cancer publication count was observed from 2011 onwards.
  • Cancer risk factors (52%) were the most studied topic, followed by outcomes (36%).
  • Cohort studies dominated (85%), with a steady rise in propensity score method usage (2.4% to 40% from 2011-2022). Breast, hepatobiliary, and colorectal cancers were frequently studied sites.

Conclusions:

  • Bibliometric analyses should incorporate study-based and disease-based components for a robust understanding of research trends.
  • The proposed framework enhances the analysis of real-world data in cancer research.
  • The framework's principles are applicable to bibliometric studies beyond cancer research.