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A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis
Clinical trials in patients with ulcerative colitis (UC) face the challenge of high and variable placebo response rates. The Mayo Clinical Score (MCS) is used widely as the primary endpoint in clinical trials to describe the clinical status of patients with UC. The MCS is comprised of four subscores...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8940756/ https://www.ncbi.nlm.nih.gov/pubmed/34657238 http://dx.doi.org/10.1007/s10928-021-09789-2 |
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author | Kawakatsu, Sonoko Zhu, Rui Zhang, Wenhui Tang, Meina T. Lu, Tong Quartino, Angelica L. Kågedal, Matts |
author_facet | Kawakatsu, Sonoko Zhu, Rui Zhang, Wenhui Tang, Meina T. Lu, Tong Quartino, Angelica L. Kågedal, Matts |
author_sort | Kawakatsu, Sonoko |
collection | PubMed |
description | Clinical trials in patients with ulcerative colitis (UC) face the challenge of high and variable placebo response rates. The Mayo Clinical Score (MCS) is used widely as the primary endpoint in clinical trials to describe the clinical status of patients with UC. The MCS is comprised of four subscores, each scored 0, 1, 2 and 3: rectal bleeding (RB), stool frequency (SF), physician’s global assessment (PGA), and endoscopy (ENDO) subscore. Excluding the PGA subscore gives the modified MCS. Quantitative insight on the placebo response, and its impact on the components of the MCS over time, can better inform clinical trial design and interpretation. Longitudinal modeling of the MCS, and the modified MCS, can be challenging due to complex clinical trial design, population heterogeneity, and limited assessments for the ENDO subscore. The current study pooled patient-level placebo/standard of care (SoC) arm data from five clinical trials in the TransCelerate database to develop a longitudinal placebo response model that describes the MCS over time in patients with UC. MCS subscores were modeled using proportional odds models, and the removal of patients from the placebo/SoC arm, or “dropout”, was modeled using logistic regression models. The subscore and dropout models were linked to allow for the prediction of the MCS and the modified MCS. Stepwise covariate modeling identified prior exposure to TNF-α antagonists as a statistically significant predictor on the RB + SF subscore. Patients with prior exposure to TNF-α antagonists had higher post-baseline RB + SF subscores than naive patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10928-021-09789-2. |
format | Online Article Text |
id | pubmed-8940756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-89407562022-04-07 A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis Kawakatsu, Sonoko Zhu, Rui Zhang, Wenhui Tang, Meina T. Lu, Tong Quartino, Angelica L. Kågedal, Matts J Pharmacokinet Pharmacodyn Original Paper Clinical trials in patients with ulcerative colitis (UC) face the challenge of high and variable placebo response rates. The Mayo Clinical Score (MCS) is used widely as the primary endpoint in clinical trials to describe the clinical status of patients with UC. The MCS is comprised of four subscores, each scored 0, 1, 2 and 3: rectal bleeding (RB), stool frequency (SF), physician’s global assessment (PGA), and endoscopy (ENDO) subscore. Excluding the PGA subscore gives the modified MCS. Quantitative insight on the placebo response, and its impact on the components of the MCS over time, can better inform clinical trial design and interpretation. Longitudinal modeling of the MCS, and the modified MCS, can be challenging due to complex clinical trial design, population heterogeneity, and limited assessments for the ENDO subscore. The current study pooled patient-level placebo/standard of care (SoC) arm data from five clinical trials in the TransCelerate database to develop a longitudinal placebo response model that describes the MCS over time in patients with UC. MCS subscores were modeled using proportional odds models, and the removal of patients from the placebo/SoC arm, or “dropout”, was modeled using logistic regression models. The subscore and dropout models were linked to allow for the prediction of the MCS and the modified MCS. Stepwise covariate modeling identified prior exposure to TNF-α antagonists as a statistically significant predictor on the RB + SF subscore. Patients with prior exposure to TNF-α antagonists had higher post-baseline RB + SF subscores than naive patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10928-021-09789-2. Springer US 2021-10-16 2022 /pmc/articles/PMC8940756/ /pubmed/34657238 http://dx.doi.org/10.1007/s10928-021-09789-2 Text en © The Author(s) 2021 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/) . |
spellingShingle | Original Paper Kawakatsu, Sonoko Zhu, Rui Zhang, Wenhui Tang, Meina T. Lu, Tong Quartino, Angelica L. Kågedal, Matts A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis |
title | A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis |
title_full | A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis |
title_fullStr | A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis |
title_full_unstemmed | A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis |
title_short | A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis |
title_sort | longitudinal model for the mayo clinical score and its sub-components in patients with ulcerative colitis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8940756/ https://www.ncbi.nlm.nih.gov/pubmed/34657238 http://dx.doi.org/10.1007/s10928-021-09789-2 |
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