scholarly journals Leveraging electronic health records data to predict multiple sclerosis disease activity

2021 ◽  
Vol 8 (4) ◽  
pp. 800-810
Author(s):  
Yuri Ahuja ◽  
Nicole Kim ◽  
Liang Liang ◽  
Tianrun Cai ◽  
Kumar Dahal ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Electronic Health Records ◽  
Disease Activity ◽  
Health Records ◽  
Multiple Sclerosis Disease ◽  
Electronic Health

scholarly journals Learning longitudinal patterns and identifying subtypes of pediatric Crohn disease treated with infliximab via trajectory cluster analysis of electronic health records

2021 ◽  
Author(s):  
Andrew Chen ◽  
Ronen Stein ◽  
Robert N. Baldassano ◽  
Jing Huang
Keyword(s):  
Electronic Health Records ◽  
Disease Activity ◽  
Crohn Disease ◽  
Cross Sectional ◽  
Health Records ◽  
Disease Evolution ◽  
Current Classification ◽  
Electronic Health ◽  
Over Time

ABSTRACTBackgroundThe current classification of pediatric CD is mainly based on cross-sectional data. The objective of this study is to identify subgroups of pediatric CD through trajectory cluster analysis of disease activity using data from electronic health records.MethodsWe conducted a retrospective study of pediatric CD patients who had been treated with infliximab. The evolution of disease over time was described using trajectory analysis of longitudinal data of C-Reactive Protein (CRP). Patterns of disease evolution were extracted through functional principal components analysis and subgroups were identified based on those patterns using the Gaussian mixture model. We compared patient characteristics, a biomarker for disease activity, received treatments, and long-term surgical outcomes across subgroups.ResultsWe identified four subgroups of pediatric CD patients with differential relapse-and-remission risk profiles. They had significantly different disease phenotype (p < 0.001), CRP (p < 0.001) and calprotectin (p = 0.037) at diagnosis, with increasing percentage of inflammatory phenotype and declining CRP and fecal calprotectin levels from Subgroup 1 through 4. The risk of colorectal surgery within 10 years after diagnosis was significantly different between groups (p < 0.001). We did not find statistical significance in gender or age at diagnosis across subgroups, but the BMI z-score was slightly smaller in subgroup 1 (p =0.055).ConclusionsReadily available longitudinal data from electronic health records can be leveraged to provide a deeper characterization of pediatric Crohn disease. The identified subgroups captured novel forms of variation in pediatric Crohn disease that were not explained by baseline measurements and treatment information.SummaryThe current classification of pediatric Crohn disease mainly relies on cross-sectional data, e.g., the Paris classification. However, the phenotypic classification may evolve over time after diagnosis. Our study utilized longitudinal measures from the electronic health records and stratified pediatric Crohn disease patients with differential relapse-and-remission risk profiles based on patterns of disease evolution. We found trajectories of well-maintained low disease activity were associated with less severe disease at baseline, early initiation of infliximab treatment, and lower risk of surgery within 10 years of diagnosis, but the difference was not fully explained by phenotype at diagnosis.

Estimating the prevalence of multiple sclerosis using 56.6 million electronic health records from the United States

2019 ◽  
Vol 26 (14) ◽  
pp. 1948-1952 ◽  
Author(s):  
Farren BS Briggs ◽  
Eddie Hill
Keyword(s):  
Multiple Sclerosis ◽  
Electronic Health Records ◽  
Census Data ◽  
Black Americans ◽  
The United States ◽  
Health Claims ◽  
Health Records ◽  
Black Race ◽  
Electronic Health ◽  
Age And Sex

Background/objective: In 2019, the 2010 U.S. multiple sclerosis (MS) prevalence was robustly estimated (265.1–309.2/100,000) based on large administrative health-claims datasets. Using 56.6 million electronic health records (EHRs), we sought to generate complementary age, sex, and race standardized estimates. Methods/results: Using de-identified EHRs and 2018 U.S. Census data, we estimated an age- and sex-standardized MS prevalence of 219.5/100,000 which increased to 274.5/100,000 when accounting for White and Black race alone. Women aged 50 to 69 years had the highest prevalence (>600/100,000). Among White and Black Americans, the age- and sex-standardized prevalence was 283.7 and 226.1 per 100,000, respectively. Conclusion: Using 56.6 million EHRs and standardizing for age, sex, and race (White and Black Americans only), we estimated at least 810,504 Americans were living with MS in 2018.

scholarly journals Creation of a ustekinumab external control arm for Crohn's disease using electronic health records data: a pilot study

2021 ◽  
Author(s):  
Vivek Ashok Rudrapatna ◽  
Yao-Wen Cheng ◽  
Colin Feuille ◽  
Arman Mosenia ◽  
Jonathan Shih ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Electronic Health Records ◽  
Disease Activity ◽  
Real World ◽  
External Control ◽  
Health Records ◽  
Electronic Health ◽  
Trial Efficiency ◽  
Manual Review

Objectives: The use of external control arms to support claims of efficacy and safety is growing in interest among drug sponsors and regulators. However, experience with performing these kinds of studies for complex, immune-mediated diseases is limited. We sought to establish a method for creating an external control arm for Crohn's disease. Methods: We queried electronic health records databases and screened records at the University of California, San Francisco to identify patients meeting the major eligibility criteria of TRIDENT, a concurrent trial involving ustekinumab as a reference arm. Timepoints were defined to balance the tradeoff between missing disease activity and bias. We compared two imputation models by their impacts on cohort membership and outcomes. We compared the results of ascertaining disease activity using structured data algorithms against manual review. We used these data to estimate ustekinumab's real-world effectiveness. Results: Screening identified 183 patients. 30% of the cohort had missing baseline data. Two imputation models were tested and had similar effects on cohort definition and outcomes. Algorithms for ascertaining non-symptom-based elements of disease activity were similar in accuracy to manual review. The final cohort consisted of 56 patients. 34% of the cohort was in steroid-free clinical remission by week 24. Conclusions: Differences in the timing and goals of real-world encounters as compared to controlled studies directly translate into significant missing data and lost sample size. Efforts to improve real-world data capture and better align trial design with clinical practice may enable robust external control arm studies and improve trial efficiency.

scholarly journals Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e78927 ◽  
Author(s):  
Zongqi Xia ◽  
Elizabeth Secor ◽  
Lori B. Chibnik ◽  
Riley M. Bove ◽  
Suchun Cheng ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Electronic Health Records ◽  
Disease Severity ◽  
Health Records ◽  
Electronic Health
Sign in / Sign up

Export Citation Format

Share Document