Identification of Nonresponse to Treatment Using Narrative Data in an Electronic Health Record Inflammatory Bowel Disease Cohort

Inflammatory Bowel Disease Patients Who Respond to Treatment with Anti-tumor Necrosis Factor Agents Demonstrate Improvement in Pre-treatment Frailty

BACKGROUND

Frailty may be a risk factor for complications in inflammatory bowel diseases (IBD) patients. We examined the impact of treatment on IBD patients who were frail prior to treatment and identified predictors of post-treatment change in frailty.

METHODS

In an electronic health record-based cohort of IBD patients initiating anti-tumor necrosis factor (TNF)-α agents, we applied a validated claims-based frailty index to determine frailty in the 1 year prior to and after treatment initiation. We characterized treatment non-response using a composite outcome of IBD-related hospitalization, surgery, change in therapy, or initiation of systemic steroids. We constructed multivariable logistic regression models to identify determinants of post-treatment frailty.

RESULTS

The 1210 patients initiating anti-TNF therapy had a median age of 30 years; 20% were ≥ 50 years. In the first year after anti-TNF initiation, 40% were non-responders. Many more treatment non-responders were frail in the year following treatment compared with treatment responders (27% vs 7%, p < 0.001). Pre-treatment frailty (OR 2.01, 95% CI 1.35-3.00) and prior IBD-related hospitalization (OR 1.63, 95% CI 1.15-2.30) were independently predictive of higher likelihood of post-treatment frailty. Therapy response was associated with a lower likelihood (OR 0.24, 95% CI 0.16-0.34) of post-treatment frailty. Nearly 85% of patients who were frail prior to treatment demonstrated improvement in frailty following treatment CONCLUSIONS: Response to anti-TNF therapy is an important determinant of post-treatment frailty in patients with IBD. Our findings suggest that effectively treating inflammatory states in older patients with IBD may improve frailty.

Differences in Biologic Utilization and Surgery Rates in Pediatric and Adult Crohn's Disease: Results From a Large Electronic Medical Record-derived Cohort

BACKGROUND AND AIMS

Crohn's disease (CD) is a chronic illness that affects both the pediatric and adult populations with an increasing worldwide prevalence. We aim to identify a large, single-center cohort of patients with CD using natural language processing (NLP) in combination with codified data and extract surgical rates and medication usage from the electronic medical record (EMR).

METHODS

Patients with CD were identified from the entire Cleveland Clinic EMR using ICD codes and CD-specific terms identified by NLP to fit a logistic regression model. Cohorts were developed for pediatric-onset (younger than 18 years) and adult-onset (18 years and older) CD. Surgeries were identified using current procedural terminology (CPT) codes and NLP. Crohn's disease-related medications were extracted using physician orders in the EMR.

RESULTS

Patients with pediatric-onset (n = 2060) and adult-onset (n = 4973) CD were identified from 2000 to 2017 with a positive predictive value of 98.5%. Rate of CD-related abdominal surgery over time was significantly higher in adult-onset compared with pediatric-onset CD (10-year surgery rate 49.9% vs 37.7%, respectively; P < 0.001). Treatment with biologics was significantly higher in pediatric vs adult-onset CD cohorts (63.6% vs 49.2%; P < 0.001). The overall rate of CD-related abdominal surgery was significantly higher in those who received <6 months of a biologic compared with ≥6 months of a biologic for both cohorts (pediatric 64.1% vs 39.1%, P ≤ 0.001; adult 69.3% vs 56.5%, P ≤ 0.001). Additionally, 60.9% in pediatric-onset CD and 43.5% in adult-onset CD treated with ≥6 months of biologic therapy have not required abdominal surgery. On multivariable analysis, perianal surgery was a significant risk factor for abdominal surgery in both cohorts.

CONCLUSION

We used a combination of codified and NLP data to establish the largest, North American, single-center EMR cohort of pediatric- and adult-onset CD patients and determined that biologics are associated with lower rates of surgery over time, potentially altering the natural history of the disease.

Use of Narrative Concepts in Electronic Health Records to Validate Associations Between Genetic Factors and Response to Treatment of Inflammatory Bowel Diseases

Crohn's disease (CD) and ulcerative colitis (UC) are heterogeneous. With availability of therapeutic classes with distinct immunologic mechanisms of action, it has become imperative to identify markers that predict likelihood of response to each drug class. However, robust development of such tools has been challenging because of need for large prospective cohorts with systematic and careful assessment of treatment response using validated indices. Most hospitals in the United States use electronic health records (EHRs) that warehouse a large amount of narrative (free-text) and codified (administrative) data generated during routine clinical care. These data have been used to construct virtual disease cohorts for epidemiologic research as well as for defining genetic basis of disease states or discrete laboratory values.^1-3 Whether EHR-based data can be used to validate genetic associations for more nuanced outcomes such as treatment response has not been examined previously.

Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records

OBJECTIVES

To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Classification of Diseases (ICD) codes.

METHODS

An enriched cohort of 7853 eligible patients was created from electronic health records of two large hospitals using automated searches (⩾1 ICD codes combined with simple text searches). Key disease concepts from free-text data were extracted using NLP and combined with ICD codes to develop algorithms. We created both supervised regression-based algorithms-on a training set of 127 axSpA cases and 423 non-cases-and unsupervised algorithms to identify patients with high probability of having axSpA from the enriched cohort. Their performance was compared against classifications using ICD codes only.

RESULTS

NLP extracted four disease concepts of high predictive value: ankylosing spondylitis, sacroiliitis, HLA-B27 and spondylitis. The unsupervised algorithm, incorporating both the NLP concept and ICD code for AS, identified the greatest number of patients. By setting the probability threshold to attain 80% positive predictive value, it identified 1509 axSpA patients (mean age 53 years, 71% male). Sensitivity was 0.78, specificity 0.94 and area under the curve 0.93. The two supervised algorithms performed similarly but identified fewer patients. All three outperformed traditional approaches using ICD codes alone (area under the curve 0.80-0.87).

CONCLUSION

Algorithms incorporating free-text data can accurately identify axSpA patients in electronic health records. Large cohorts identified using these novel methods offer exciting opportunities for future clinical research.

The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities

Biobanks linked to electronic health records provide rich resources for health-related research. With improvements in administrative and informatics infrastructure, the availability and utility of data from biobanks have dramatically increased. In this paper, we first aim to characterize the current landscape of available biobanks and to describe specific biobanks, including their place of origin, size, and data types. The development and accessibility of large-scale biorepositories provide the opportunity to accelerate agnostic searches, expedite discoveries, and conduct hypothesis-generating studies of disease-treatment, disease-exposure, and disease-gene associations. Rather than designing and implementing a single study focused on a few targeted hypotheses, researchers can potentially use biobanks' existing resources to answer an expanded selection of exploratory questions as quickly as they can analyze them. However, there are many obvious and subtle challenges with the design and analysis of biobank-based studies. Our second aim is to discuss statistical issues related to biobank research such as study design, sampling strategy, phenotype identification, and missing data. We focus our discussion on biobanks that are linked to electronic health records. Some of the analytic issues are illustrated using data from the Michigan Genomics Initiative and UK Biobank, two biobanks with two different recruitment mechanisms. We summarize the current body of literature for addressing these challenges and discuss some standing open problems. This work complements and extends recent reviews about biobank-based research and serves as a resource catalog with analytical and practical guidance for statisticians, epidemiologists, and other medical researchers pursuing research using biobanks.

A Review of Automatic Phenotyping Approaches using Electronic Health Records

Electronic Health Records (EHR) are a rich repository of valuable clinical information that exist in primary and secondary care databases. In order to utilize EHRs for medical observational research a range of algorithms for automatically identifying individuals with a specific phenotype have been developed. This review summarizes and offers a critical evaluation of the literature relating to studies conducted into the development of EHR phenotyping systems. This review describes phenotyping systems and techniques based on structured and unstructured EHR data. Articles published on PubMed and Google scholar between 2013 and 2017 have been reviewed, using search terms derived from Medical Subject Headings (MeSH). The popularity of using Natural Language Processing (NLP) techniques in extracting features from narrative text has increased. This increased attention is due to the availability of open source NLP algorithms, combined with accuracy improvement. In this review, Concept extraction is the most popular NLP technique since it has been used by more than 50% of the reviewed papers to extract features from EHR. High-throughput phenotyping systems using unsupervised machine learning techniques have gained more popularity due to their ability to efficiently and automatically extract a phenotype with minimal human effort.

The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature

Electronic health records (EHRs) have emerged among health information technology as "meaningful use" to improve the quality and efficiency of healthcare, and health disparities in population health. In other instances, they have also shown lack of interoperability, functionality and many medical errors. With proper implementation and training, are electronic health records a viable source in managing population health? The primary objective of this systematic review is to assess the relationship of electronic health records' use on population health through the identification and analysis of facilitators and barriers to its adoption for this purpose. Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE (PubMed), 10/02/2012-10/02/2017, core clinical/academic journals, MEDLINE full text, English only, human species and evaluated the articles that were germane to our research objective. Each article was analyzed by multiple reviewers. Group members recognized common facilitators and barriers associated with EHRs effect on population health. A final list of articles was selected by the group after three consensus meetings (n = 55). Among a total of 26 factors identified, 63% (147/232) of those were facilitators and 37% (85/232) barriers. About 70% of the facilitators consisted of productivity/efficiency in EHRs occurring 33 times, increased quality and data management each occurring 19 times, surveillance occurring 17 times, and preventative care occurring 15 times. About 70% of the barriers consisted of missing data occurring 24 times, no standards (interoperability) occurring 13 times, productivity loss occurring 12 times, and technology too complex occurring 10 times. The analysis identified more facilitators than barriers to the use of the EHR to support public health. Wider adoption of the EHR and more comprehensive standards for interoperability will only enhance the ability for the EHR to support this important area of surveillance and disease prevention. This review identifies more facilitators than barriers to using the EHR to support public health, which implies a certain level of usability and acceptance to use the EHR in this manner. The public-health industry should combine their efforts with the interoperability projects to make the EHR both fully adopted and fully interoperable. This will greatly increase the availability, accuracy, and comprehensiveness of data across the country, which will enhance benchmarking and disease surveillance/prevention capabilities.

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative

Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether polygenic risk scores (PRS) for common cancers are associated with multiple phenotypes in a phenome-wide association study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. There were 13,490 (47.7%) patients with at least one cancer diagnosis in this study sample. PRS exhibited strong association for several cancer traits they were designed for, including female breast cancer, prostate cancer, melanoma, basal cell carcinoma, squamous cell carcinoma, and thyroid cancer. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate PRS associations driven by the primary trait from associations arising through shared genetic risk profiles, the idea of "exclusion PRS PheWAS" was introduced. Further analysis of temporal order of the diagnoses improved our understanding of these secondary associations. This comprehensive PheWAS used PRS instead of a single variant.

Phenome-wide association study identifies marked increased in burden of comorbidities in African Americans with systemic lupus erythematosus

Background

African Americans with systemic lupus erythematosus (SLE) have increased renal disease compared to Caucasians, but differences in other comorbidities have not been well-described. We used an electronic health record (EHR) technique to test for differences in comorbidities in African Americans compared to Caucasians with SLE.

Methods

We used a de-identified EHR with 2.8 million subjects to identify SLE cases using a validated algorithm. We performed phenome-wide association studies (PheWAS) comparing African American to Caucasian SLE cases and African American SLE cases to matched non-SLE controls. Controls were age, sex, and race matched to SLE cases. For multiple testing, a false discovery rate (FDR) p value of 0.05 was used.

Results

We identified 270 African Americans and 715 Caucasians with SLE and 1425 matched African American controls. Compared to Caucasians with SLE adjusting for age and sex, African Americans with SLE had more comorbidities in every organ system. The most striking included hypertension odds ratio (OR) = 4.25, FDR p = 5.49 × 10^{− 15}; renal dialysis OR = 10.90, FDR p = 8.75 × 10^{− 14}; and pneumonia OR = 3.57, FDR p = 2.32 × 10^{− 8}. Compared to the African American matched controls without SLE, African Americans with SLE were more likely to have comorbidities in every organ system. The most significant codes were renal and cardiac, and included renal failure (OR = 9.55, FDR p = 2.26 × 10^{− 40}) and hypertensive heart and renal disease (OR = 8.08, FDR p = 1.78 × 10^{− 22}). Adjusting for race, age, and sex in a model including both African American and Caucasian SLE cases and controls, SLE was independently associated with renal, cardiovascular, and infectious diseases (all p < 0.01).

Conclusions

African Americans with SLE have an increased comorbidity burden compared to Caucasians with SLE and matched controls. This increase in comorbidities in African Americans with SLE highlights the need to monitor for cardiovascular and infectious complications.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1561-8) contains supplementary material, which is available to authorized users.

Series: Pragmatic trials and real world evidence: Paper 6. Outcome measures in the real world

Results from pragmatic trials should reflect the comparative treatment effects encountered in patients in real-life clinical practice to guide treatment decisions. Therefore, pragmatic trials should focus on outcomes that are relevant to patients, clinical practice, and treatment choices. This sixth article in the series (see Box) discusses different types of outcomes and their suitability for pragmatic trials, design choices for measuring these outcomes, and their implications and challenges. Measuring outcomes in pragmatic trials should not interfere with real-world clinical practice to ensure generalizability of trial results, and routinely collected outcomes should be prioritized. Typical outcomes include mortality, morbidity, functional status, well-being, and resource use. Surrogate endpoints are typically avoided as primary outcome. It is important to measure outcomes over a relevant time horizon and obtain valid and precise results. As pragmatic trials are often open label, a less subjective outcome can reduce bias. Methods that decrease bias or enhance precision of the results, such as standardization and blinding of outcome assessment, should be considered when a high risk of bias or high variability is expected. The selection of outcomes in pragmatic trials should be relevant for decision making and feasible in terms of executing the trial in the context of interest. Therefore, this should be discussed with all stakeholders as early as feasible to ensure the relevance of study results for decision making in clinical practice and the ability to perform the study.

Development of an Inflammatory Bowel Disease Research Registry Derived from Observational Electronic Health Record Data for Comprehensive Clinical Phenotyping

BACKGROUND

Inflammatory bowel disease (IBD) is a heterogeneous collection of chronic inflammatory disorders of the digestive tract. Clinical, genetic, and pathological heterogeneity makes it increasingly difficult to translate efficacy studies into real-world practice. Our objective was to develop a comprehensive natural history registry derived from multi-year observational data to facilitate effectiveness and clinical phenotypic research in IBD.

METHODS

A longitudinal, consented registry with prospectively collected data was developed at UPMC. All adult IBD patients receiving care at the tertiary care center of UPMC are eligible for enrollment. Detailed data in the electronic health record are accessible for registry research purposes. Data are exported directly from the electronic health record and temporally organized for research.

RESULTS

To date, there are over 2565 patients participating in the IBD research registry. All patients have demographic data, clinical disease characteristics, and disease course data including healthcare utilization, laboratory values, health-related questionnaires quantifying disease activity and quality of life, and analytical information on treatment, temporally organized for 6 years (2009-2015). The data have resulted in a detailed definition of clinical phenotypes suitable for association studies with parameters of disease outcomes and treatment response. We have established the infrastructure required to examine the effectiveness of treatment and disease course in the real-world setting of IBD.

CONCLUSIONS

The IBD research registry offers a unique opportunity to investigate clinical research questions regarding the natural course of the disease, phenotype association studies, effectiveness of treatment, and quality of care research.

Comparative Effectiveness of Infliximab and Adalimumab in Crohn's Disease and Ulcerative Colitis

BACKGROUND

The availability of monoclonal antibodies to tumor necrosis factor α has revolutionized management of Crohn's disease (CD) and ulcerative colitis. However, limited data exist regarding comparative effectiveness of these agents to inform clinical practice.

METHODS

This study consisted of patients with CD or ulcerative colitis initiation either infliximab (IFX) or adalimumab (ADA) between 1998 and 2010. A validated likelihood of nonresponse classification score using frequency of narrative mentions of relevant symptoms in the electronic health record was applied to assess comparative effectiveness at 1 year. Inflammatory bowel disease-related surgery, hospitalization, and use of steroids were determined during this period.

RESULTS

Our final cohort included 1060 new initiations of IFX (68% for CD) and 391 of ADA (79% for CD). In CD, the likelihood of nonresponse was higher in ADA than IFX (odds ratio, 1.62 and 95% CI, 1.21-2.17). Similar differences favoring efficacy of IFX were observed for the individual symptoms of diarrhea, pain, bleeding, and fatigue. However, there was no difference in inflammatory bowel disease-related surgery, hospitalizations, or prednisone use within 1 year after initiation of IFX or ADA in CD. There was no difference in narrative or codified outcomes between the 2 agents in ulcerative colitis.

CONCLUSIONS

We identified a modestly higher likelihood of symptomatic nonresponse at 1 year for ADA compared with IFX in patients with CD. However, there were no differences in inflammatory bowel disease-related surgery or hospitalizations, suggesting these treatments are broadly comparable in effectiveness in routine clinical practice.