Cargando…

Statistical Issues in TBI Clinical Studies

The identification and longitudinal assessment of traumatic brain injury presents several challenges. Because these injuries can have subtle effects, efforts to find quantitative physiological measures that can be used to characterize traumatic brain injury are receiving increased attention. The res...

Descripción completa

Detalles Bibliográficos
Autores principales: Rapp, Paul E., Cellucci, Christopher J., Keyser, David O., Gilpin, Adele M. K., Darmon, David M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832983/
https://www.ncbi.nlm.nih.gov/pubmed/24312072
http://dx.doi.org/10.3389/fneur.2013.00177
_version_ 1782291768619827200
author Rapp, Paul E.
Cellucci, Christopher J.
Keyser, David O.
Gilpin, Adele M. K.
Darmon, David M.
author_facet Rapp, Paul E.
Cellucci, Christopher J.
Keyser, David O.
Gilpin, Adele M. K.
Darmon, David M.
author_sort Rapp, Paul E.
collection PubMed
description The identification and longitudinal assessment of traumatic brain injury presents several challenges. Because these injuries can have subtle effects, efforts to find quantitative physiological measures that can be used to characterize traumatic brain injury are receiving increased attention. The results of this research must be considered with care. Six reasons for cautious assessment are outlined in this paper. None of the issues raised here are new. They are standard elements in the technical literature that describes the mathematical analysis of clinical data. The purpose of this paper is to draw attention to these issues because they need to be considered when clinicians evaluate the usefulness of this research. In some instances these points are demonstrated by simulation studies of diagnostic processes. We take as an additional objective the explicit presentation of the mathematical methods used to reach these conclusions. This material is in the appendices. The following points are made: (1) A statistically significant separation of a clinical population from a control population does not ensure a successful diagnostic procedure. (2) Adding more variables to a diagnostic discrimination can, in some instances, actually reduce classification accuracy. (3) A high sensitivity and specificity in a TBI versus control population classification does not ensure diagnostic successes when the method is applied in a more general neuropsychiatric population. (4) Evaluation of treatment effectiveness must recognize that high variability is a pronounced characteristic of an injured central nervous system and that results can be confounded by either disease progression or spontaneous recovery. A large pre-treatment versus post-treatment effect size does not, of itself, establish a successful treatment. (5) A procedure for discriminating between treatment responders and non-responders requires, minimally, a two phase investigation. This procedure must include a mechanism to discriminate between treatment responders, placebo responders, and spontaneous recovery. (6) A search for prodromes of neuropsychiatric disorders following traumatic brain injury can be implemented with these procedures.
format Online
Article
Text
id pubmed-3832983
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-38329832013-12-05 Statistical Issues in TBI Clinical Studies Rapp, Paul E. Cellucci, Christopher J. Keyser, David O. Gilpin, Adele M. K. Darmon, David M. Front Neurol Neuroscience The identification and longitudinal assessment of traumatic brain injury presents several challenges. Because these injuries can have subtle effects, efforts to find quantitative physiological measures that can be used to characterize traumatic brain injury are receiving increased attention. The results of this research must be considered with care. Six reasons for cautious assessment are outlined in this paper. None of the issues raised here are new. They are standard elements in the technical literature that describes the mathematical analysis of clinical data. The purpose of this paper is to draw attention to these issues because they need to be considered when clinicians evaluate the usefulness of this research. In some instances these points are demonstrated by simulation studies of diagnostic processes. We take as an additional objective the explicit presentation of the mathematical methods used to reach these conclusions. This material is in the appendices. The following points are made: (1) A statistically significant separation of a clinical population from a control population does not ensure a successful diagnostic procedure. (2) Adding more variables to a diagnostic discrimination can, in some instances, actually reduce classification accuracy. (3) A high sensitivity and specificity in a TBI versus control population classification does not ensure diagnostic successes when the method is applied in a more general neuropsychiatric population. (4) Evaluation of treatment effectiveness must recognize that high variability is a pronounced characteristic of an injured central nervous system and that results can be confounded by either disease progression or spontaneous recovery. A large pre-treatment versus post-treatment effect size does not, of itself, establish a successful treatment. (5) A procedure for discriminating between treatment responders and non-responders requires, minimally, a two phase investigation. This procedure must include a mechanism to discriminate between treatment responders, placebo responders, and spontaneous recovery. (6) A search for prodromes of neuropsychiatric disorders following traumatic brain injury can be implemented with these procedures. Frontiers Media S.A. 2013-11-19 /pmc/articles/PMC3832983/ /pubmed/24312072 http://dx.doi.org/10.3389/fneur.2013.00177 Text en Copyright © 2013 Rapp, Cellucci, Keyser, Gilpin and Darmon. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Rapp, Paul E.
Cellucci, Christopher J.
Keyser, David O.
Gilpin, Adele M. K.
Darmon, David M.
Statistical Issues in TBI Clinical Studies
title Statistical Issues in TBI Clinical Studies
title_full Statistical Issues in TBI Clinical Studies
title_fullStr Statistical Issues in TBI Clinical Studies
title_full_unstemmed Statistical Issues in TBI Clinical Studies
title_short Statistical Issues in TBI Clinical Studies
title_sort statistical issues in tbi clinical studies
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832983/
https://www.ncbi.nlm.nih.gov/pubmed/24312072
http://dx.doi.org/10.3389/fneur.2013.00177
work_keys_str_mv AT rapppaule statisticalissuesintbiclinicalstudies
AT celluccichristopherj statisticalissuesintbiclinicalstudies
AT keyserdavido statisticalissuesintbiclinicalstudies
AT gilpinadelemk statisticalissuesintbiclinicalstudies
AT darmondavidm statisticalissuesintbiclinicalstudies