Cargando…
The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach
Heterogeneity and chronicity of Crohn disease (CD) make prediction of outcomes difficult. To date, no longitudinal measure can quantify burden over a patient’s disease course, preventing assessment and integration into predictive modeling. Here, we aimed to demonstrate the feasibility of constructin...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10259218/ https://www.ncbi.nlm.nih.gov/pubmed/37079872 http://dx.doi.org/10.1097/MPG.0000000000003793 |
_version_ | 1785057618845237248 |
---|---|
author | Ashton, James J. Gurung, Abhilasha Davis, Cai Seaby, Eleanor G. Coelho, Tracy Batra, Akshay Afzal, Nadeem A. Ennis, Sarah Beattie, R. Mark |
author_facet | Ashton, James J. Gurung, Abhilasha Davis, Cai Seaby, Eleanor G. Coelho, Tracy Batra, Akshay Afzal, Nadeem A. Ennis, Sarah Beattie, R. Mark |
author_sort | Ashton, James J. |
collection | PubMed |
description | Heterogeneity and chronicity of Crohn disease (CD) make prediction of outcomes difficult. To date, no longitudinal measure can quantify burden over a patient’s disease course, preventing assessment and integration into predictive modeling. Here, we aimed to demonstrate the feasibility of constructing a data driven, longitudinal disease burden score. METHODS: Literature was reviewed for tools used in assessment of CD activity. Themes were identified to construct a pediatric CD morbidity index (PCD-MI). Scores were assigned to variables. Data were extracted automatically from the electronic patient records at Southampton Children’s Hospital, diagnosed from 2012 to 2019 (inclusive). PCD-MI scores were calculated, adjusted for duration of follow up and assessed for variation (ANOVA) and distribution (Kolmogorov-Smirnov). RESULTS: Nineteen clinical/biological features across five themes were included in the PCD-MI including blood/fecal/radiological/endoscopic results, medication usage, surgery, growth parameters, and extraintestinal manifestations. Maximal score was 100 after accounting for follow-up duration. PCD-MI was assessed in 66 patients, mean age 12.5 years. Following quality filtering, 9528 blood/fecal test results and 1309 growth measures were included. Mean PCD-MI score was 14.95 (range 2.2–32.5); data were normally distributed (P = 0.2) with 25% of patients having a PCD-MI < 10. There was no difference in the mean PCD-MI when split by year of diagnosis, F-statistic 1.625, P = 0.147. CONCLUSIONS: PCD-MI is a calculatable measure for a cohort of patients diagnosed over an 8-year period, integrating a wide-range of data with potential to determine high or low disease burden. Future iterations of the PCD-MI require refinement of included features, optimized scores, and validation on external cohorts. |
format | Online Article Text |
id | pubmed-10259218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-102592182023-06-13 The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach Ashton, James J. Gurung, Abhilasha Davis, Cai Seaby, Eleanor G. Coelho, Tracy Batra, Akshay Afzal, Nadeem A. Ennis, Sarah Beattie, R. Mark J Pediatr Gastroenterol Nutr Original Articles: Gastroenterology: Inflammatory Bowel Disease Heterogeneity and chronicity of Crohn disease (CD) make prediction of outcomes difficult. To date, no longitudinal measure can quantify burden over a patient’s disease course, preventing assessment and integration into predictive modeling. Here, we aimed to demonstrate the feasibility of constructing a data driven, longitudinal disease burden score. METHODS: Literature was reviewed for tools used in assessment of CD activity. Themes were identified to construct a pediatric CD morbidity index (PCD-MI). Scores were assigned to variables. Data were extracted automatically from the electronic patient records at Southampton Children’s Hospital, diagnosed from 2012 to 2019 (inclusive). PCD-MI scores were calculated, adjusted for duration of follow up and assessed for variation (ANOVA) and distribution (Kolmogorov-Smirnov). RESULTS: Nineteen clinical/biological features across five themes were included in the PCD-MI including blood/fecal/radiological/endoscopic results, medication usage, surgery, growth parameters, and extraintestinal manifestations. Maximal score was 100 after accounting for follow-up duration. PCD-MI was assessed in 66 patients, mean age 12.5 years. Following quality filtering, 9528 blood/fecal test results and 1309 growth measures were included. Mean PCD-MI score was 14.95 (range 2.2–32.5); data were normally distributed (P = 0.2) with 25% of patients having a PCD-MI < 10. There was no difference in the mean PCD-MI when split by year of diagnosis, F-statistic 1.625, P = 0.147. CONCLUSIONS: PCD-MI is a calculatable measure for a cohort of patients diagnosed over an 8-year period, integrating a wide-range of data with potential to determine high or low disease burden. Future iterations of the PCD-MI require refinement of included features, optimized scores, and validation on external cohorts. Lippincott Williams & Wilkins 2023-04-20 2023-07 /pmc/articles/PMC10259218/ /pubmed/37079872 http://dx.doi.org/10.1097/MPG.0000000000003793 Text en Copyright © 2023 The Author(s). Published by Wolters Kluwer on behalf of European Society for Pediatric Gastroenterology, Hepatology, and Nutrition and North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles: Gastroenterology: Inflammatory Bowel Disease Ashton, James J. Gurung, Abhilasha Davis, Cai Seaby, Eleanor G. Coelho, Tracy Batra, Akshay Afzal, Nadeem A. Ennis, Sarah Beattie, R. Mark The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach |
title | The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach |
title_full | The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach |
title_fullStr | The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach |
title_full_unstemmed | The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach |
title_short | The Pediatric Crohn Disease Morbidity Index (PCD-MI): Development of a Tool to Assess Long-Term Disease Burden Using a Data-Driven Approach |
title_sort | pediatric crohn disease morbidity index (pcd-mi): development of a tool to assess long-term disease burden using a data-driven approach |
topic | Original Articles: Gastroenterology: Inflammatory Bowel Disease |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10259218/ https://www.ncbi.nlm.nih.gov/pubmed/37079872 http://dx.doi.org/10.1097/MPG.0000000000003793 |
work_keys_str_mv | AT ashtonjamesj thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT gurungabhilasha thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT daviscai thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT seabyeleanorg thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT coelhotracy thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT batraakshay thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT afzalnadeema thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT ennissarah thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT beattiermark thepediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT ashtonjamesj pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT gurungabhilasha pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT daviscai pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT seabyeleanorg pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT coelhotracy pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT batraakshay pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT afzalnadeema pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT ennissarah pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach AT beattiermark pediatriccrohndiseasemorbidityindexpcdmidevelopmentofatooltoassesslongtermdiseaseburdenusingadatadrivenapproach |