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The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study
BACKGROUND: Lumbar spinal stenosis (LSS) is a common degenerative condition that contributes to back and back-related leg pain in older adults. Most patients with symptomatic LSS initially receive non-operative care before surgical consultation. However, there is a scarcity of data regarding prognos...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9306038/ https://www.ncbi.nlm.nih.gov/pubmed/35864487 http://dx.doi.org/10.1186/s12891-022-05598-x |
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author | Rundell, Sean D. Saito, Ayumi Meier, Eric N. Danyluk, Stephanie T. Jarvik, Jeffrey G. Seebeck, Kelley Friedly, Janna L. Heagerty, Patrick J. Johnston, Sandra K. Smersh, Monica Horn, Maggie E. Suri, Pradeep Cizik, Amy M. Goode, Adam P. |
author_facet | Rundell, Sean D. Saito, Ayumi Meier, Eric N. Danyluk, Stephanie T. Jarvik, Jeffrey G. Seebeck, Kelley Friedly, Janna L. Heagerty, Patrick J. Johnston, Sandra K. Smersh, Monica Horn, Maggie E. Suri, Pradeep Cizik, Amy M. Goode, Adam P. |
author_sort | Rundell, Sean D. |
collection | PubMed |
description | BACKGROUND: Lumbar spinal stenosis (LSS) is a common degenerative condition that contributes to back and back-related leg pain in older adults. Most patients with symptomatic LSS initially receive non-operative care before surgical consultation. However, there is a scarcity of data regarding prognosis for patients seeking non-surgical care. The overall goal of this project is to develop and evaluate a clinically useful model to predict long-term physical function of patients initiating non-surgical care for symptomatic LSS. METHODS: This is a protocol for an inception cohort study of adults 50 years and older who are initiating non-surgical care for symptomatic LSS in a secondary care setting. We plan to recruit up to 625 patients at two study sites. We exclude patients with prior lumbar spine surgeries or those who are planning on lumbar spine surgery. We also exclude patients with serious medical conditions that have back pain as a symptom or limit walking. We are using weekly, automated data pulls from the electronic health records to identify potential participants. We then contact patients by email and telephone within 21 days of a new visit to determine eligibility, obtain consent, and enroll participants. We collect data using telephone interviews, web-based surveys, and queries of electronic health records. Participants are followed for 12 months, with surveys completed at baseline, 3, 6, and 12 months. The primary outcome measure is the 8-item PROMIS Physical Function (PF) Short Form. We will identify distinct phenotypes using PROMIS PF scores at baseline and 3, 6, and 12 months using group-based trajectory modeling. We will develop and evaluate the performance of a multivariable prognostic model to predict 12-month physical function using the least absolute shrinkage and selection operator and will compare performance to other machine learning methods. Internal validation will be conducted using k-folds cross-validation. DISCUSSION: This study will be one of the largest cohorts of individuals with symptomatic LSS initiating new episodes of non-surgical care. The successful completion of this project will produce a cross-validated prognostic model for LSS that can be used to tailor treatment approaches for patient care and clinical trials. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-022-05598-x. |
format | Online Article Text |
id | pubmed-9306038 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93060382022-07-23 The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study Rundell, Sean D. Saito, Ayumi Meier, Eric N. Danyluk, Stephanie T. Jarvik, Jeffrey G. Seebeck, Kelley Friedly, Janna L. Heagerty, Patrick J. Johnston, Sandra K. Smersh, Monica Horn, Maggie E. Suri, Pradeep Cizik, Amy M. Goode, Adam P. BMC Musculoskelet Disord Study Protocol BACKGROUND: Lumbar spinal stenosis (LSS) is a common degenerative condition that contributes to back and back-related leg pain in older adults. Most patients with symptomatic LSS initially receive non-operative care before surgical consultation. However, there is a scarcity of data regarding prognosis for patients seeking non-surgical care. The overall goal of this project is to develop and evaluate a clinically useful model to predict long-term physical function of patients initiating non-surgical care for symptomatic LSS. METHODS: This is a protocol for an inception cohort study of adults 50 years and older who are initiating non-surgical care for symptomatic LSS in a secondary care setting. We plan to recruit up to 625 patients at two study sites. We exclude patients with prior lumbar spine surgeries or those who are planning on lumbar spine surgery. We also exclude patients with serious medical conditions that have back pain as a symptom or limit walking. We are using weekly, automated data pulls from the electronic health records to identify potential participants. We then contact patients by email and telephone within 21 days of a new visit to determine eligibility, obtain consent, and enroll participants. We collect data using telephone interviews, web-based surveys, and queries of electronic health records. Participants are followed for 12 months, with surveys completed at baseline, 3, 6, and 12 months. The primary outcome measure is the 8-item PROMIS Physical Function (PF) Short Form. We will identify distinct phenotypes using PROMIS PF scores at baseline and 3, 6, and 12 months using group-based trajectory modeling. We will develop and evaluate the performance of a multivariable prognostic model to predict 12-month physical function using the least absolute shrinkage and selection operator and will compare performance to other machine learning methods. Internal validation will be conducted using k-folds cross-validation. DISCUSSION: This study will be one of the largest cohorts of individuals with symptomatic LSS initiating new episodes of non-surgical care. The successful completion of this project will produce a cross-validated prognostic model for LSS that can be used to tailor treatment approaches for patient care and clinical trials. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-022-05598-x. BioMed Central 2022-07-21 /pmc/articles/PMC9306038/ /pubmed/35864487 http://dx.doi.org/10.1186/s12891-022-05598-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Study Protocol Rundell, Sean D. Saito, Ayumi Meier, Eric N. Danyluk, Stephanie T. Jarvik, Jeffrey G. Seebeck, Kelley Friedly, Janna L. Heagerty, Patrick J. Johnston, Sandra K. Smersh, Monica Horn, Maggie E. Suri, Pradeep Cizik, Amy M. Goode, Adam P. The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study |
title | The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study |
title_full | The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study |
title_fullStr | The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study |
title_full_unstemmed | The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study |
title_short | The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study |
title_sort | lumbar stenosis prognostic subgroups for personalizing care and treatment (prospects) study: protocol for an inception cohort study |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9306038/ https://www.ncbi.nlm.nih.gov/pubmed/35864487 http://dx.doi.org/10.1186/s12891-022-05598-x |
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