Overview of Organization and Capacity
Mission Statement
ILADS is a nonprofit, international, multidisciplinary medical society dedicated to the appropriate diagnosis and treatment of Lyme and associated diseases.
ILADEF, ILADS’ sister organization, has a mission to advance the education of medical professionals and to promote research supporting improved as to the appropriate diagnosis and treatment of tick-borne diseases.
History
Founded in 1999. ILADS is the ONLY nonprofit professional membership organization focusing on vector-borne diseases representing over 500 programs and professionals worldwide.
Conceived as a medical society for doctors and researchers who were interested in Lyme and other tick-borne diseases – ILADS is an organization that offers a medical forum incorporating functions of education and communication for specialists focusing on the spirochetal and other vector-borne illnesses.
Overview of Unmet Need/Problem Statement
Lyme disease, a multi-system infection caused by the bacterium Borreliella burgdorferi, is the most common vector-borne disease in the United States. Each year, according to the CDC, an estimated 500,000 individuals contract Lyme disease, across all 50 states.
The Lyme disease agent, or Borrelia burgdorferi, is typically transmitted through the bite of an infected tick. Along with Borrelia burgdorferi, ticks often transmit other infections including Babesia spp., ci, Bartonella spp., Rickettsia spp., Anaplasmosis, Q-fever, and Ehrlichia.
In its early stages, Lyme disease commonly results in a rash, joint pain and headaches. The Lyme disease bacteria has the ability to enter the brain less than 24 hours after a tick bite. Later-stage Lyme disease is characterized by arthritic pain, cognitive difficulties, psychiatric illness, fatigue and other symptoms that can have an enormous, damaging effect on a patient’s life leading to partial or total disability.
Diagnosing Lyme disease can often be complex and easy to miss, given the severe limitations of diagnostic testing, wide-ranging symptoms, and a lack of education about the disease.
No study to-date has captured the data and logic of diagnosing and treating patients from the perspective of the treating physician. This ground-breaking research directed by ILADS will empower doctors with the data to make better, more informed treatment decisions.
ILADS doctors pioneers in the medical field for diagnosing and treating chronic illness and stealth infections, including tick-borne disease and Long COVID.
How do doctors make informed decisions on how to treat patients and uncover the root cause of illness: Through Precision Medicine.
In the spectrum of conditions that might loosely be termed "Lyme disease," there is much confusion and need for not only improved diagnostic testing but also improved and more consistent protocols. Essentially, this complex field needs to be reduced to a science. There have been recent advances in diagnostics, in clinical trial design, and the ready availability of data science tools that finally enable this to occur.
Good Data = Informed Decisions
ILADEF Big Data Registry
Project/Program Purpose: The Big Data Project
What drives Precision Medicine? Big Data is the way to validate the current treatments your doctor is performing are effective and safe. It is also the way to efficiently design treatment protocols. Using big data, a picture emerges of what is effective for each individual in the setting of each chronic infection.
The ILADS Big Data Registry is the first and only of its kind seeking to obtain physician-generated data on clinical outcomes paired with specific treatment modalities to retrospectively ascertain the most efficacious therapeutic modalities.
This study would be an essential complement to the patient-reported data in MyLymeData.org as it would provide much needed practitioner perspectives on the same patient population. The study would work in partnership with MyLymeData.org to provide the physician’s perspective.
The concept behind this project is a method for streamlined data acquisition to inform and support later studies that may be used to validate new diagnostics and therapeutics. This study would employ a Bayesian adaptive design in a registry model. This would allow the fusion of clinical research with medical practice with data acquired from a broader collective of practitioners. A unique characteristic of this study, drawn from registry experiences, would be to NOT apply selection criteria that would restrict the enrollment criteria. In fact, the study would have no specified criteria for enrollment other than the clinician’s suspicion of "Lyme or related disease." This way, exemplary cases could be abstracted and compiled, and then, machine learning may be applied to support expert review by both statisticians and experienced clinicians. The summary data from such a study (essentially a registry) would be reviewed every three months, and the results would then be considered by the treating physician and/or the diagnostic laboratories to inform their decisions.
The clinicians would provide their interpretation, state how the data may or may not alter their protocols, and then consistently apply those protocols in their subsequent clinical experience. It is hoped that by reviewing the summary statistics every few months, the clinician would be able to learn more rapidly about the experience of others and their response and then use that to guide their treatment protocols until the next data review.
We have an Institutional Review Board (IRB) approved study that remains open, recently renewed by Advara IRB. This may be modified for use in this proposed study. The design of this study is much like a registry as it does not dictate any diagnostic test or treatment.
Ideally, for each patient, then we would develop a timeline where we would visualize (for each patient and for the group) the temporal correlation of treatment with the changes in symptoms and determine if and how any particular diagnostic test provided adequate decision support in directing the course and choice of therapies.
As we collect more data through this registry, we foresee spin-off study protocols also approved through an IRB that would then focus on one aspect, for example, a new treatment plan or a new diagnostic approach.
Goals
Goal: To arm clinicians with the data such that doctors can personalize and update the treatment protocol for every patient. Through periodic review of statistics, clinicians will enhance their knowledge through the experience of their colleagues. This will enable a faster response to then use to guide their treatment protocols until the next data review.
Timeline
The project will have two major data collection/extraction arms which will feed into the analysis pipeline. In the first arm we will hire a qualified individual to help collect the needed data from patient charts of participating ILADS members.
As soon as a staff person oriented, the next 6-8 months would focus on beginning to populate the database. The next step would be to publish interim summary stats, and then, at 3 month intervals, collect data on how the results impacted precision medical care for the patient cohort as individuals and as a group.
Impact
ILADS doctors are clinicians on the front line. They treat patients. They show a personal interest in the outcomes of “patients,” not the outcomes of a “drug trial.” They deserve access to cutting-edge technology to make decisions on personalized care.
Funding
Since the ILADS Big Data Project will encompass data sets that are too large or complex to be dealt with by traditional data-processing application software, ILADS and ILADEF are actively seeking foundation, corporate, and individual support.