Signal Detection for Medical Scientists

Likelihood Ratio Test-based Methodology

Ram Tiwari, Jyoti Zalkikar, Lan Huang

• Publisher: Chapman and Hall/CRC
• Year: 2021
• ISBN:
  9780429535390
• Edition: 1
• Topic: Medicina
• Subtopic: Biostatistica

Signal Detection for Medical Scientists: Likelihood Ratio Based Test-Based Methodology presents the data mining techniques with focus on likelihood ratio test (LRT) based methods for signal detection. It emphasizes computational aspect of LRT methodology and is pertinent for first-time researchers and graduate students venturing into this interesting field.

The book is written as a reference book for professionals in pharmaceutical industry, manufactures of medical devices, and regulatory agencies. The book deals with the signal detection in drug/device evaluation, which is important in the post-market evaluation of medical products, and in the pre-market signal detection during clinical trials for monitoring procedures.

It should also appeal to academic researchers, and faculty members in mathematics, statistics, biostatistics, data science, pharmacology, engineering, epidemiology, and public health. Therefore, this book is well suited for both research and teaching.

Key Features:

• Includes a balanced discussion of art of data structure, issues in signal detection, statistical methods and analytics, and implementation of the methods
• Provides a comprehensive summary of the LRT methods for signal detection including the basic theory and extensions for varying datasets that may be large post-market data or pre-market clinical trial data
• Contains details of scientific background, statistical methods, and associated algorithms that a reader can quickly master the materials and apply methods in the book on one's own problems

Part I LRT Methodology

1

Introduction

1.1 Background of Data Mining for Safety Signals

With greater technological advancements and medical innovations, post-market safety surveillance plays a critical role in ensuring public health. Companies manufacturing medical products evaluate the safety issues/signals of the medical products during product development and monitor them after the product is on the market upon approval. Consistent with the mission to protect and advance public health, FDA monitors the benefit-risk balance of medical products over their life cycle [50]. FDA's safety surveillance begins early in the product's life cycle as part of the review process that may lead up to FDA approval. Once the FDA approves a product, a risk-based post-marketing safety surveillance phase begins and continues for the life of the product [51].

According to FDA guidance for pharmacovigilance practices [13], safety signal refers to a concern about an excess of adverse events (AEs) compared to what would be expected to be associated with a product's use. A safety signal identified in the development and post-market surveillance may indicate a possible safety concern that needs further assessment. Such signal identification may be done using potential sources including large post-market databases such as FDA Adverse Event Reporting System (FAERS [4], formerly Adverse Event Reporting System (AERS)), registries, clinical trial databases, observational study databases, medical literature, etc.

The safety evaluation at the product development stage (such as Phase 2 or 3 clinical trials) is limited due to the relatively small number of patients/subjects enrolled and limited follow-up time. Clinical trials are usually powered for the primary efficacy endpoint(s), but not to study the safety endpoints. Collecting safety events, especially rare events, takes several years, which is not usually possible in clinical trials with a short (one- or two-years) follow-up. Therefore, some safety issues may not be identified during the development stage. It is essential for both companies and the FDA to continue monitoring the safety profile of medical products on the market in the intended patient population worldwide over extended time.

Large s...