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Optimizing Exclusion Criteria for Clinical Trials of Persistent Lyme Disease Using Real-World Data.

Lorraine Johnson¹, Mira Shapiro², Deanna Needell³

¹LymeDisease.org, Los Angeles, CA 91040, USA.

Healthcare (Basel, Switzerland)

|January 10, 2025

Summary

Optimizing clinical trial eligibility criteria for Persistent Lyme Disease (PLD) using real-world data (RWD) can significantly increase patient recruitment. Loosening criteria for coinfections and misdiagnoses could boost sample yield from 10% to 64%.

Keywords:

PTLDS big data chronic Lyme disease eligibility criteria enrollment generalizability persistent Lyme disease real-world data recruitment sample yield

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Area of Science:

Medical research methodology
Clinical trial design
Infectious diseases

Background:

Eligibility criteria for clinical trials often lack scientific justification, leading to recruitment delays and limited generalizability.
Persistent Lyme disease (PLD) presents unique challenges for clinical trials due to symptom variability and lack of biomarkers.
Scientifically justified eligibility criteria are crucial for successful PLD research.

Purpose of the Study:

To examine the impact of common enrollment criteria on sample yield in PLD clinical trials using real-world data (RWD).
To compare enrollment effects for PLD versus acute Lyme disease (ALD) trials.
To evaluate the scientific rationale behind various eligibility criteria.

Main Methods:

Analysis of RWD from 4183 Lyme disease patients in the MyLymeData registry.
Assessment of the prevalence and cumulative impact of eligibility criteria on sample yield.
Comparative analysis of PLD (n=3589) and ALD (n=594) cohorts to identify differences in sample attrition.

Main Results:

Current eligibility criteria would exclude approximately 90% of PLD patients, severely limiting study generalizability.
Significant differences in sample attrition were observed between PLD and ALD cohorts, indicating a need for tailored criteria.
The scientific justification for commonly used criteria varied considerably.

Conclusions:

RWD is essential for optimizing eligibility criteria in PLD clinical trials, enhancing feasibility and generalizability.
Adjusting criteria for coinfections and misdiagnosed conditions (chronic fatigue, fibromyalgia, psychiatric) could increase sample yield from 10% to 64%.
Balancing sample attrition with scientific justification is key to robust clinical trial design.