Post-treatment Lyme disease symptoms score: Developing a new tool for research

Some patients have residual non-specific symptoms after therapy for Lyme disease, referred to as post-treatment Lyme disease symptoms or syndrome, depending on whether there is functional impairment. A standardized test battery was used to characterize a diverse group of Lyme disease patients with a...

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Bibliographic Details
Published in:	PloS one Vol. 14; no. 11; p. e0225012
Main Authors:	Turk, Siu P, Lumbard, Keith, Liepshutz, Kelly, Williams, Carla, Hu, Linden, Dardick, Kenneth, Wormser, Gary P, Norville, Joshua, Scavarda, Carol, McKenna, Donna, Follmann, Dean, Marques, Adriana
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 11-11-2019 Public Library of Science (PLoS)
Subjects:	Antibiotics Anxiety Batteries Biology and Life Sciences Biomedical Research Cancer Cognitive ability Cohort Studies Decision Trees Disturbance Engineering and Technology Fatigue Female Health Humans Immunology Infectious diseases Laboratories Logistic Models Lyme disease Male Medical research Medical schools Medical treatment Medicine and Health Sciences Mental disorders Mental health Middle Aged Model accuracy Pain Patients Post-Lyme Disease Syndrome - diagnosis Quality of life Questionnaires Regression analysis Regression models Reproducibility of Results Research and Analysis Methods Signs and symptoms Sleep Social Sciences Studies Surveys and Questionnaires Vector-borne diseases New York United States > US Maryland Massachusetts
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Summary:	Some patients have residual non-specific symptoms after therapy for Lyme disease, referred to as post-treatment Lyme disease symptoms or syndrome, depending on whether there is functional impairment. A standardized test battery was used to characterize a diverse group of Lyme disease patients with and without residual symptoms. There was a strong correlation between sleep disturbance and certain other symptoms such as fatigue, pain, anxiety, and cognitive complaints. Results were subjected to a Logistic Regression model using the Neuro-QoL Fatigue t-score together with Short Form-36 Physical Functioning scale and Mental Health component scores; and to a Decision Tree model using only the QoL Fatigue t-score. The Logistic Regression model had an accuracy of 97% and Decision Tree model had an accuracy of 93%, when compared with clinical categorization. The Logistic Regression and Decision Tree models were then applied to a separate cohort. Both models performed with high sensitivity (90%), but moderate specificity (62%). The overall accuracy was 74%. Agreement between 2 time points, separated by a mean of 4 months, was 89% using the Decision Tree model and 87% with the Logistic Regression model. These models are simple and can help to quantitate the level of symptom severity in post-treatment Lyme disease symptoms. More research is needed to increase the specificity of the models, exploring additional approaches that could potentially strengthen an operational definition for post-treatment Lyme disease symptoms. Evaluation of how sleep disturbance, fatigue, pain and cognitive complains interrelate can potentially lead to new interventions that will improve the overall health of these patients.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: GPW reports receiving research grants from Immunetics, Inc., Institute for Systems Biology, Rarecyte, Inc., and Quidel Corporation. He owns equity in Abbott/AbbVie; has been an expert witness in malpractice cases involving Lyme disease; and is an unpaid board member of the American Lyme Disease Foundation. KD serves as a member of the Data Safety Monitoring Board for phase 2 trials of Valneva’s Lyme Disease candidate vaccine VLA15. ARM has a patent US 8,926,989 B2; and is an unpaid Scientific Advisor to the Global Lyme Alliance and to the American Lyme Disease Foundation. LH is also an unpaid Scientific Advisor to the Global Lyme Alliance and the American Lyme Disease foundation. LH has research contracts with Sanofi, Moderna and Massbiologics for work unrelated to the content of this manuscript. KL, KL and CW are government contract employees of Leidos Biomedical Research, Inc., dedicated to the operation of The Frederick National Laboratory for Cancer Research, which is funded by the federal government. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0225012