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Related Concept Videos

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
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  11. Good Statistical Monitoring: A Flexible Open-source Tool To Detect Risks In Clinical Trials

Good Statistical Monitoring: A Flexible Open-Source Tool to Detect Risks in Clinical Trials

George Wu1, Spencer Childress2, Zhongkai Wang2

  • 1Gilead Sciences Inc., 333 Lakeside Dr, Foster City, CA, 94404, USA. George.Wu@gilead.com.

Therapeutic Innovation & Regulatory Science
|May 9, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

Good Statistical Monitoring is a new open-source R package for clinical trials. It enables proactive risk detection and mitigation through flexible data analysis and reporting, enhancing quality management.

Area of Science:

  • Clinical trial management
  • Regulatory science
  • Data analytics in healthcare

Background:

  • Risk-based quality management is recommended for clinical trials.
  • Risk-based monitoring is crucial for early detection of trial risks.
  • Limited open-source tools exist for clinical trial risk analytics.

Purpose of the Study:

  • To introduce Good Statistical Monitoring, an open-source R package.
  • To provide a flexible and efficient tool for end-to-end risk analysis in clinical trials.
  • To support risk-based quality management strategies.

Main Methods:

  • Developed collaboratively by statisticians, data scientists, and clinical experts.
  • An R package supporting data mapping from various formats.
  • Includes evaluation of 12 key risk indicators and interactive reporting.
Keywords:
Interactive graphicsRRisk-based monitoringRisk-based quality management

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Main Results:

  • The package is freely available on GitHub.
  • Enables proactive monitoring and customized risk assessments.
  • Results are exportable and visualized in interactive reports.

Conclusions:

  • Good Statistical Monitoring facilitates statistical monitoring of critical risks.
  • It supports a comprehensive risk-based quality management strategy.
  • The open-source solution empowers clinical study teams.
Statistical monitoring