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Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs
Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be u...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492202/ https://www.ncbi.nlm.nih.gov/pubmed/32982952 http://dx.doi.org/10.3389/fneur.2020.00961 |
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author | Naidech, Andrew M. Lawlor, Patrick N. Xu, Haolin Fonarow, Gregg C. Xian, Ying Smith, Eric E. Schwamm, Lee Matsouaka, Roland Prabhakaran, Shyam Marinescu, Ioana Kording, Konrad P. |
author_facet | Naidech, Andrew M. Lawlor, Patrick N. Xu, Haolin Fonarow, Gregg C. Xian, Ying Smith, Eric E. Schwamm, Lee Matsouaka, Roland Prabhakaran, Shyam Marinescu, Ioana Kording, Konrad P. |
author_sort | Naidech, Andrew M. |
collection | PubMed |
description | Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be useful. We used regression discontinuity design (RDD), a technique well-established in economics, on the Get With The Guidelines-Stroke (GWTG-Stroke) data set. RDD, based on regression, measures the occurrence of a discontinuity in an outcome (e.g., odds of home discharge) as a function of an intervention (e.g., alteplase) that becomes significantly more likely when crossing the threshold of a continuous variable that determines that intervention (e.g., time from symptom onset, since alteplase is only given if symptom onset is less than e.g., 3 h). The technique assumes that patients near either side of a threshold (e.g., 2.99 and 3.01 h from symptom onset) are indistinguishable other than the use of the treatment. We compared outcomes of patients whose estimated onset to treatment time fell on either side of the treatment threshold for three cohorts of patients in the GWTG-Stroke data set. This data set spanned three different treatment thresholds for alteplase (3 h, 2003–2007, N = 1,869; 3 h, 2009–2016, N = 13,086, and 4.5 h, 2009–2016, N = 6,550). Patient demographic characteristics were overall similar across the treatment thresholds. We did not find evidence of a discontinuity in clinical outcome at any treatment threshold attributable to alteplase. Potential reasons for failing to find an effect include violation of some RDD assumptions in clinical care, large sample sizes required, or already-well-chosen treatment threshold. |
format | Online Article Text |
id | pubmed-7492202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74922022020-09-25 Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs Naidech, Andrew M. Lawlor, Patrick N. Xu, Haolin Fonarow, Gregg C. Xian, Ying Smith, Eric E. Schwamm, Lee Matsouaka, Roland Prabhakaran, Shyam Marinescu, Ioana Kording, Konrad P. Front Neurol Neurology Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be useful. We used regression discontinuity design (RDD), a technique well-established in economics, on the Get With The Guidelines-Stroke (GWTG-Stroke) data set. RDD, based on regression, measures the occurrence of a discontinuity in an outcome (e.g., odds of home discharge) as a function of an intervention (e.g., alteplase) that becomes significantly more likely when crossing the threshold of a continuous variable that determines that intervention (e.g., time from symptom onset, since alteplase is only given if symptom onset is less than e.g., 3 h). The technique assumes that patients near either side of a threshold (e.g., 2.99 and 3.01 h from symptom onset) are indistinguishable other than the use of the treatment. We compared outcomes of patients whose estimated onset to treatment time fell on either side of the treatment threshold for three cohorts of patients in the GWTG-Stroke data set. This data set spanned three different treatment thresholds for alteplase (3 h, 2003–2007, N = 1,869; 3 h, 2009–2016, N = 13,086, and 4.5 h, 2009–2016, N = 6,550). Patient demographic characteristics were overall similar across the treatment thresholds. We did not find evidence of a discontinuity in clinical outcome at any treatment threshold attributable to alteplase. Potential reasons for failing to find an effect include violation of some RDD assumptions in clinical care, large sample sizes required, or already-well-chosen treatment threshold. Frontiers Media S.A. 2020-09-02 /pmc/articles/PMC7492202/ /pubmed/32982952 http://dx.doi.org/10.3389/fneur.2020.00961 Text en Copyright © 2020 Naidech, Lawlor, Xu, Fonarow, Xian, Smith, Schwamm, Matsouaka, Prabhakaran, Marinescu and Kording. http://creativecommons.org/licenses/by/4.0/ 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) and the copyright owner(s) 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 | Neurology Naidech, Andrew M. Lawlor, Patrick N. Xu, Haolin Fonarow, Gregg C. Xian, Ying Smith, Eric E. Schwamm, Lee Matsouaka, Roland Prabhakaran, Shyam Marinescu, Ioana Kording, Konrad P. Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs |
title | Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs |
title_full | Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs |
title_fullStr | Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs |
title_full_unstemmed | Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs |
title_short | Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs |
title_sort | probing the effective treatment thresholds for alteplase in acute ischemic stroke with regression discontinuity designs |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492202/ https://www.ncbi.nlm.nih.gov/pubmed/32982952 http://dx.doi.org/10.3389/fneur.2020.00961 |
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