Age-stratified comorbid and pharmacologic analysis of patients with glioblastoma

Background

Increased age is a strong and unfavorable prognostic factor for patients with glioblastoma (GBM). However, the relationships between stratified patient age, comorbidities, and medications have yet to be explored in GBM patient survival analyses.

Objective

To evaluate co-morbid conditions, tumor-related symptoms, medication prescriptions, and subject age for patients with GBM and to establish potential targets for prospective studies.

Methods

Electronic health records for 565 patients with IDHwt GBM were evaluated at a single center between January 1, 2000 and August 9, 2021 were retrospectively assessed. Data were stratified by MGMT promoter methylation status when available and were used to construct multivariable time-dependent cox models and intra-cohort hazards.

Results

Younger (<65 years of age) but not older (≥65 years) GBM patients demonstrated a worse prognosis with movement related disabilities (P < 0.0001), gait/balance difficulty (P = 0.04) and weakness (P = 0.007), as well as psychiatric conditions, mental health disorders (P = 0.002) and anxiety (P = 0.001). In contrast, older but not younger GBM patients demonstrated a worse prognosis with epilepsy (P = 0.039). Both groups had worse survival with confusion/altered mental status (P = 0.023 vs < 0.000) and an improved survival with a Temozolomide prescription. Older but not younger GBM patients experienced an improved hazard with a prescription of ace-inhibitor medications (P = 0.048).

Conclusion

Age-dependent novel associations between clinical symptoms and medications prescribed for co-morbid conditions were demonstrated in patients with GBM. The results of the current work support future mechanistic studies that investigate the negative relationship(s) between increased age, comorbidities, and drug therapies for differential clinical decision-making across the lifespan of patients with GBM.

Clinical associations with a polygenic predisposition to benign lower white blood cell counts

Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is uncharacterized. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio = 0.55 per standard deviation increase in PGSWBC [95%CI, 0.30-0.94], p = 0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n = 1724, hazard ratio [HR] = 0.78 [0.69-0.88], p = 4.0 × 10-5) or immunosuppressant (n = 354, HR = 0.61 [0.38-0.99], p = 0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n = 1,466, HR = 0.62 [0.44-0.87], p = 0.006). Collectively, these findings suggest that there are genetically predisposed individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit.

Risk factors affecting polygenic score performance across diverse cohorts

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGS BMI ) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R 2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R 2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGS BMI -covariate interaction effects, modifying PGS BMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R 2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R 2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGS BMI individuals have highest R 2 and increase in PGS effect. Using quantile regression, we show the effect of PGS BMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R 2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGS BMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R 2 (mean 23%) across datasets. Finally, creating PGS BMI directly from GxAge GWAS effects increased relative R 2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGS BMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Rapid identification of inflammatory arthritis and associated adverse events following immune checkpoint therapy: a machine learning approach

Introduction

Immune checkpoint inhibitor-induced inflammatory arthritis (ICI-IA) poses a major clinical challenge to ICI therapy for cancer, with 13% of cases halting ICI therapy and ICI-IA being difficult to identify for timely referral to a rheumatologist. The objective of this study was to rapidly identify ICI-IA patients in clinical data and assess associated immune-related adverse events (irAEs) and risk factors.

Methods

We conducted a retrospective study of the electronic health records (EHRs) of 89 patients who developed ICI-IA out of 2451 cancer patients who received ICI therapy at Northwestern University between March 2011 to January 2021. Logistic regression and random forest machine learning models were trained on all EHR diagnoses, labs, medications, and procedures to identify ICI-IA patients and EHR codes indicating ICI-IA. Multivariate logistic regression was then used to test associations between ICI-IA and cancer type, ICI regimen, and comorbid irAEs.

Results

Logistic regression and random forest models identified ICI-IA patients with accuracies of 0.79 and 0.80, respectively. Key EHR features from the random forest model included ICI-IA relevant features (joint pain, steroid prescription, rheumatoid factor tests) and features suggesting comorbid irAEs (thyroid function tests, pruritus, triamcinolone prescription). Compared to 871 adjudicated ICI patients who did not develop arthritis, ICI-IA patients had higher odds of developing cutaneous (odds ratio [OR]=2.66; 95% Confidence Interval [CI] 1.63-4.35), endocrine (OR=2.09; 95% CI 1.15-3.80), or gastrointestinal (OR=2.88; 95% CI 1.76-4.72) irAEs adjusting for demographics, cancer type, and ICI regimen. Melanoma (OR=1.99; 95% CI 1.08-3.65) and renal cell carcinoma (OR=2.03; 95% CI 1.06-3.84) patients were more likely to develop ICI-IA compared to lung cancer patients. Patients on nivolumab+ipilimumab were more likely to develop ICI-IA compared to patients on pembrolizumab (OR=1.86; 95% CI 1.01-3.43).

Discussion

Our machine learning models rapidly identified patients with ICI-IA in EHR data and elucidated clinical features indicative of comorbid irAEs. Patients with ICI-IA were significantly more likely to also develop cutaneous, endocrine, and gastrointestinal irAEs during their clinical course compared to ICI therapy patients without ICI-IA.

Detection of Personal and Family History of Suicidal Thoughts and Behaviors using Deep Learning and Natural Language Processing: A Multi-Site Study

Objective

Personal and family history of suicidal thoughts and behaviors (PSH and FSH, respectively) are significant risk factors associated with future suicide events. These are often captured in narrative clinical notes in electronic health records (EHRs). Collaboratively, Weill Cornell Medicine (WCM), Northwestern Medicine (NM), and the University of Florida (UF) developed and validated deep learning (DL)-based natural language processing (NLP) tools to detect PSH and FSH from such notes. The tool's performance was further benchmarked against a method relying exclusively on ICD-9/10 diagnosis codes.

Materials and Methods

We developed DL-based NLP tools utilizing pre-trained transformer models Bio_ClinicalBERT and GatorTron, and compared them with expert-informed, rule-based methods. The tools were initially developed and validated using manually annotated clinical notes at WCM. Their portability and performance were further evaluated using clinical notes at NM and UF.

Results

The DL tools outperformed the rule-based NLP tool in identifying PSH and FHS. For detecting PSH, the rule-based system obtained an F1-score of 0.75 ± 0.07, while the Bio_ClinicalBERT and GatorTron DL tools scored 0.83 ± 0.09 and 0.84 ± 0.07, respectively. For detecting FSH, the rule-based NLP tool's F1-score was 0.69 ± 0.11, compared to 0.89 ± 0.10 for Bio_ClinicalBERT and 0.92 ± 0.07 for GatorTron. For the gold standard corpora across the three sites, only 2.2% (WCM), 9.3% (NM), and 7.8% (UF) of patients reported to have an ICD-9/10 diagnosis code for suicidal thoughts and behaviors prior to the clinical notes report date. The best performing GatorTron DL tool identified 93.0% (WCM), 80.4% (NM), and 89.0% (UF) of patients with documented PSH, and 85.0%(WCM), 89.5%(NM), and 100%(UF) of patients with documented FSH in their notes.

Discussion

While PSH and FSH are significant risk factors for future suicide events, little effort has been made previously to identify individuals with these history. To address this, we developed a transformer based DL method and compared with conventional rule-based NLP approach. The varying effectiveness of the rule-based tools across sites suggests a need for improvement in its dictionary-based approach. In contrast, the performances of the DL tools were higher and comparable across sites. Furthermore, DL tools were fine-tuned using only small number of annotated notes at each site, underscores its greater adaptability to local documentation practices and lexical variations.

Conclusion

Variations in local documentation practices across health care systems pose challenges to rule-based NLP tools. In contrast, the developed DL tools can effectively extract PSH and FSH information from unstructured clinical notes. These tools will provide clinicians with crucial information for assessing and treating patients at elevated risk for suicide who are rarely been diagnosed.

Interventions and contextual factors to improve retention in care for patients with hypertension in primary care: Hermeneutic systematic review

BACKGROUND

Regular engagement over time in hypertension care, or retention, is a crucial but understudied step in optimizing patient outcomes. This systematic review leverages a hermeneutic methodology to identify, evaluate, and quantify the effects of interventions and contextual factors for improving retention for patients with hypertension.

METHODS

We searched for articles that were published between 2000 and 2022 from multiple electronic databases, including MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, clinicaltrials.gov, and WHO International Trials Registry. We followed the latest version of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guideline to report the findings for this review. We also synthesized the findings using a hermeneutic methodology for systematic reviews, which used an iterative process to review, integrate, analyze, and interpret evidence.

RESULTS

From 4686 screened titles and abstracts, 18 unique studies from 9 countries were identified, including 10 (56%) randomized controlled trials (RCTs), 3 (17%) cluster RCTs, and 5 (28%) non-RCT studies. The number of participants ranged from 76 to 1562. The overall mean age range was 41-67 years, and the proportion of female participants ranged from 0% to 100%. Most (n = 17, 94%) studies used non-physician personnel to implement the proposed interventions. Fourteen studies (78%) implemented multilevel combinations of interventions. Education and training, team-based care, consultation, and Short Message Service reminders were the most common interventions tested.

CONCLUSIONS

This review presents the most comprehensive findings on retention in hypertension care to date and fills the gaps in the literature, including the effectiveness of interventions, their components, and contextual factors. Adaptation of and implementing HIV care models, such differentiated service delivery, may be more effective and merit further study.

REGISTRATION

CRD42021291368.

PROTOCOL REGISTRATION

PROSPERO 2021 CRD42021291368. Available at: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=291368.

Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations

Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

Advanced Age in Humans and Mouse Models of Glioblastoma Show Decreased Survival from Extratumoral Influence

PURPOSE

Glioblastoma (GBM) is the most common aggressive primary malignant brain tumor in adults with a median age of onset of 68 to 70 years old. Although advanced age is often associated with poorer GBM patient survival, the predominant source(s) of maladaptive aging effects remains to be established. Here, we studied intratumoral and extratumoral relationships between adult patients with GBM and mice with brain tumors across the lifespan.

EXPERIMENTAL DESIGN

Electronic health records at Northwestern Medicine and the NCI SEER databases were evaluated for GBM patient age and overall survival. The commercial Tempus and Caris databases, as well as The Cancer Genome Atlas were profiled for gene expression, DNA methylation, and mutational changes with varying GBM patient age. In addition, gene expression analysis was performed on the extratumoral brain of younger and older adult mice with or without a brain tumor. The survival of young and old wild-type or transgenic (INK-ATTAC) mice with a brain tumor was evaluated after treatment with or without senolytics and/or immunotherapy.

RESULTS

Human patients with GBM ≥65 years of age had a significantly decreased survival compared with their younger counterparts. While the intra-GBM molecular profiles were similar between younger and older patients with GBM, non-tumor brain tissue had a significantly different gene expression profile between young and old mice with a brain tumor and the eradication of senescent cells improved immunotherapy-dependent survival of old but not young mice.

CONCLUSIONS

This work suggests a potential benefit for combining senolytics with immunotherapy in older patients with GBM.

Identification and assessment of classification criteria attributes for systemic lupus erythematosus in a regional medical record data network

OBJECTIVE

To assess the application and utility of algorithms designed to detect features of SLE in electronic health record (EHR) data in a multisite, urban data network.

METHODS

Using the Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN), a Clinical Data Research Network (CDRN) containing data from multiple healthcare sites, we identified patients with at least one positively identified criterion from three SLE classification criteria sets developed by the American College of Rheumatology (ACR) in 1997, the Systemic Lupus International Collaborating Clinics (SLICC) in 2012, and the European Alliance of Associations for Rheumatology and the ACR in 2019 using EHR-based algorithms. To measure the algorithms' performance in this data setting, we first evaluated whether the number of clinical encounters for SLE was associated with a greater quantity of positively identified criteria domains using Poisson regression. We next quantified the amount of SLE criteria identified at a single healthcare institution versus all sites to assess the amount of SLE-related information gained from implementing the algorithms in a CDRN.

RESULTS

Patients with three or more SLE encounters were estimated to have documented 2.77 (2.73 to 2.80) times the number of positive SLE attributes from the 2012 SLICC criteria set than patients without an SLE encounter via Poisson regression. Patients with three or more SLE-related encounters and with documented care from multiple institutions were identified with more SLICC criteria domains when data were included from all CAPriCORN sites compared with a single site (p<0.05).

CONCLUSIONS

The positive association observed between amount of SLE-related clinical encounters and the number of criteria domains detected suggests that the algorithms used in this study can be used to help describe SLE features in this data environment. This work also demonstrates the benefit of aggregating data across healthcare institutions for patients with fragmented care.

Rationale and design for Healthy Hearts for Michigan (HH4M): A pragmatic single-arm hybrid effectiveness-implementation study

Background

The burden of cardiovascular disease (CVD) is particularly high in several US states, which include the state of Michigan. Hypertension and smoking are two major risk factors for mortality due to CVD. Rural Michigan is disproportionally affected by CVD and by primary care shortages. The Healthy Hearts for Michigan (HH4M) study aims to promote hypertension management and smoking cessation through practice facilitation and quality improvement efforts and is part of the multi-state EvidenceNOW: Building State Capacity initiative to provide external support to primary care practices to improve care delivery.

Methods

Primary care practices in rural and underserved areas of Michigan were recruited to join HH4M, a pragmatic, single-arm hybrid Type 2 effectiveness-implementation study during which practice facilitation was delivered at the practice level for 12 months, followed by a 3-month maintenance period.

Results

Fifty-four practices were enrolled over a 12-month recruitment period. At baseline, the mean proportion (standard deviation) of patients at the practice level meeting the clinical quality measures were: blood pressure, 0.72 (0.12); tobacco screening, 0.80 (0.30); tobacco cessation intervention, 0.57 (0.28); tobacco screening and cessation intervention: 0.78 (0.26).

Conclusion

This three-year research program will evaluate the ability of rural and medically underserved primary care practices to implement the quality improvement model by identifying drivers of and barriers to sustainable implementation, and test whether the model improves (a) blood pressure control and (b) tobacco use screening and cessation.

Declining Participation in Primary Care Quality Improvement Research: A Qualitative Study

PURPOSE

There are numerous supportive quality improvement (QI) projects to facilitate the implementation of evidence-based practices in primary care, but recruiting physician practices to join these projects is challenging, costly, and time consuming. We aimed to identify factors leading primary care practices to decline participation in QI projects, and strategies to improve the feasibility and attractiveness of QI projects in the future.

METHODS

For this qualitative study, we contacted 109 representatives of practices that had declined participation in 1 of 4 Agency for Healthcare Research and Quality-funded EvidenceNOW projects. The representatives were invited to participate in a 15-minute interview or complete a 5-question questionnaire. Thematic analysis was used to organize and characterize findings.

RESULTS

Representatives from 31 practices (28.4% of those contacted) responded. Overwhelmingly, respondents indicated that staff turnover, staffing shortages, and general time constraints, exacerbated by the pandemic, prevented participation in the QI projects. Challenges with electronic health records, an expectation of greater financial compensation for participation, and confidence in the practices' current care practices were secondary reasons for declining participation. Tying participation to value-based programs and offering greater compensation were identified as strategies to facilitate recruitment. None of the respondents' recommendations, however, addressed the primary issues of staffing challenges and time constraints.

CONCLUSIONS

Staffing challenges and general time constraints, exacerbated by the pandemic, are compromising primary care practices' ability to engage in QI research projects. To encourage participation, policy makers should consider direct supports for primary care, which may also help to alleviate burnout.

Clinical consequences of a polygenic predisposition to benign lower white blood cell counts: Consequences of benign WBC count genetics

Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is undefined. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio=0.55 per standard deviation increase in PGSWBC [95%CI, 0.30 - 0.94], p=0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n=1,724, hazard ratio [HR]=0.78 [0.69 - 0.88], p=4.0×10-5) or immunosuppressant (n=354, HR=0.61 [0.38 - 0.99], p=0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n=1,466, HR=0.62 [0.44 - 0.87], p=0.006). Collectively, these findings suggest that a WBC count polygenic score identifies individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit.

Characterizing variability of electronic health record-driven phenotype definitions

OBJECTIVE

The aim of this study was to analyze a publicly available sample of rule-based phenotype definitions to characterize and evaluate the variability of logical constructs used.

MATERIALS AND METHODS

A sample of 33 preexisting phenotype definitions used in research that are represented using Fast Healthcare Interoperability Resources and Clinical Quality Language (CQL) was analyzed using automated analysis of the computable representation of the CQL libraries.

RESULTS

Most of the phenotype definitions include narrative descriptions and flowcharts, while few provide pseudocode or executable artifacts. Most use 4 or fewer medical terminologies. The number of codes used ranges from 5 to 6865, and value sets from 1 to 19. We found that the most common expressions used were literal, data, and logical expressions. Aggregate and arithmetic expressions are the least common. Expression depth ranges from 4 to 27.

DISCUSSION

Despite the range of conditions, we found that all of the phenotype definitions consisted of logical criteria, representing both clinical and operational logic, and tabular data, consisting of codes from standard terminologies and keywords for natural language processing. The total number and variety of expressions are low, which may be to simplify implementation, or authors may limit complexity due to data availability constraints.

CONCLUSIONS

The phenotype definitions analyzed show significant variation in specific logical, arithmetic, and other operators but are all composed of the same high-level components, namely tabular data and logical expressions. A standard representation for phenotype definitions should support these formats and be modular to support localization and shared logic.

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network

The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations.

Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits

Immunoglobulin A (IgA) mediates mucosal responses to food antigens and the intestinal microbiome and is involved in susceptibility to mucosal pathogens, celiac disease, inflammatory bowel disease, and IgA nephropathy. We performed a genome-wide association study of serum IgA levels in 41,263 individuals of diverse ancestries and identified 20 genome-wide significant loci, including 9 known and 11 novel loci. Co-localization analyses with expression QTLs prioritized candidate genes for 14 of 20 significant loci. Most loci encoded genes that produced immune defects and IgA abnormalities when genetically manipulated in mice. We also observed positive genetic correlations of serum IgA levels with IgA nephropathy, type 2 diabetes, and body mass index, and negative correlations with celiac disease, inflammatory bowel disease, and several infections. Mendelian randomization supported elevated serum IgA as a causal factor in IgA nephropathy. African ancestry was consistently associated with higher serum IgA levels and greater frequency of IgA-increasing alleles compared to other ancestries. Our findings provide novel insights into the genetic regulation of IgA levels and its potential role in human disease.

Multiancestral polygenic risk score for pediatric asthma

BACKGROUND

Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.

OBJECTIVES

This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.

METHODS

This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.

RESULTS

The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PFDR = 3.71 × 10-65) and related phenotypes.

CONCLUSIONS

A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

Predictive Modeling for Suicide-Related Outcomes and Risk Factors among Patients with Pain Conditions: A Systematic Review

Suicide is a leading cause of death in the US. Patients with pain conditions have higher suicidal risks. In a systematic review searching observational studies from multiple sources (e.g., MEDLINE) from 1 January 2000–12 September 2020, we evaluated existing suicide prediction models’ (SPMs) performance and identified risk factors and their derived data sources among patients with pain conditions. The suicide-related outcomes included suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors. Among the 87 studies included (with 8 SPM studies), 107 suicide risk factors (grouped into 27 categories) were identified. The most frequently occurring risk factor category was depression and their severity (33%). Approximately 20% of the risk factor categories would require identification from data sources beyond structured data (e.g., clinical notes). For 8 SPM studies (only 2 performing validation), the reported prediction metrics/performance varied: C-statistics (n = 3 studies) ranged 0.67–0.84, overall accuracy(n = 5): 0.78–0.96, sensitivity(n = 2): 0.65–0.91, and positive predictive values(n = 3): 0.01–0.43. Using the modified Quality in Prognosis Studies tool to assess the risk of biases, four SPM studies had moderate-to-high risk of biases. This systematic review identified a comprehensive list of risk factors that may improve predicting suicidal risks for patients with pain conditions. Future studies need to examine reasons for performance variations and SPM’s clinical utility.

Electronic health record data use in the assessment of quality indicators for glucocorticoid osteoporosis screening in systemic lupus erythematosus

OBJECTIVE

To determine whether electronic health record (EHR) data components could be identified and used to assess bone health quality indicators in patients with systemic lupus erythematosus as a foundation for population health management.

METHODS

We identified patients in our EHR system who had diagnosis codes for lupus from 2012 to 2017 and characterized them based on the frequency and dosage of prescribed glucocorticoid medications. The medical records of patients who received repeated high-dose glucocorticoid orders were further reviewed for osteoporosis, osteoporotic fractures, receipt of appropriate preventive screening, and orders for protective medications based on established quality indicators. Descriptive statistics were calculated to summarize results.

RESULTS

We identified 617 patients with a lupus diagnosis; 414 received glucocorticoid prescriptions, 189 received chronic, high-dose; and 83 received chronic, low-dose prescription orders. Of those with chronic high-dose glucocorticoid prescriptions, 14% had an osteoporosis diagnosis, 3% had an osteoporotic fracture, 51% received a prescription for calcium/vitamin D, 43% had bone mineral density screening orders, 20% received a spine radiograph order, 29% had a documented T-score, 12% received a prescription for osteoporosis medication, and 6% had a documented osteoporosis screening. We were able to identify data elements in the EHR for all nine components of the osteoporosis management quality indicator.

CONCLUSIONS

It is possible to identify data in the EHR for all attributes of the quality indicator for osteoporosis in lupus patients who receive chronic high-dose glucocorticoids. However, missing data and need to extract data from text-based notes may make development of population management tools challenging.

Considerations Before Selecting a Stepped-Wedge Cluster Randomized Trial Design for a Practice Improvement Study

PURPOSE

Despite the growing popularity of stepped-wedge cluster randomized trials (SW-CRTs) for practice-based research, the design's advantages and challenges are not well documented. The objective of this study was to identify the advantages and challenges of the SW-CRT design for large-scale intervention implementations in primary care settings.

METHODS

The EvidenceNOW: Advancing Heart Health initiative, funded by the Agency for Healthcare Research and Quality, included a large collection of SW-CRTs. We conducted qualitative interviews with 17 key informants from EvidenceNOW grantees to identify the advantages and challenges of using SW-CRT design.

RESULTS

All interviewees reported that SW-CRT can be an effective study design for large-scale intervention implementations. Advantages included (1) incentivized recruitment, (2) staggered resource allocation, and (3) statistical power. Challenges included (1) time-sensitive recruitment, (2) retention, (3) randomization requirements and practice preferences, (4) achieving treatment schedule fidelity, (5) intensive data collection, (6) the Hawthorne effect, and (7) temporal trends.

CONCLUSIONS

The challenges experienced by EvidenceNOW grantees suggest that certain favorable real-world conditions constitute a context that increases the odds of a successful SW-CRT. An existing infrastructure can support the recruitment of many practices. Strong retention plans are needed to continue to engage sites waiting to start the intervention. Finally, study outcomes should be ones already captured in routine practice; otherwise, funders and investigators should assess the feasibility and cost of data collection.VISUAL ABSTRACT.

Many Medicare Beneficiaries Do Not Fill High-Price Specialty Drug Prescriptions

For high-price drugs, Medicare Part D beneficiaries who do not receive a low-income subsidy must pay a percentage of the drug's price for each medication fill. Without that subsidy, which lowers out-of-pocket spending, beneficiaries typically pay hundreds or thousands of dollars for a single fill. We estimated the proportion of Part D beneficiaries in fee-for-service Medicare, with and without a subsidy, who do not initiate treatment (that is, do not fill a new prescription) with high-price Part D drugs newly prescribed for four conditions. Examining 17,076 new prescriptions issued between 2012 and 2018 for Part D beneficiaries from eleven geographically diverse health systems, we found that beneficiaries receiving subsidies were nearly twice as likely to obtain the prescribed drug within ninety days as those without subsidies. Among beneficiaries without subsidies, we observed noninitiation for 30 percent of prescriptions written for anticancer drugs, 22 percent for hepatitis C treatments, and more than 50 percent for disease-modifying therapies for either immune system disorders or hypercholesterolemia. Our findings support current legislative efforts to increase the accessibility of high-price medications by reducing out-of-pocket expenses under Medicare Part D, particularly for beneficiaries without low-income subsidies.

Development of preclinical and clinical models for immune-related adverse events following checkpoint immunotherapy: a perspective from SITC and AACR

Recent advances in cancer immunotherapy have completely revolutionized cancer treatment strategies. Nonetheless, the increasing incidence of immune-related adverse events (irAEs) is now limiting the overall benefits of these treatments. irAEs are well-recognized side effects of some of the most effective cancer immunotherapy agents, including antibody blockade of the cytotoxic T-lymphocyte-associated protein 4 and programmed death protein 1/programmed-death ligand 1 pathways. To develop an action plan on the key elements needed to unravel and understand the key mechanisms driving irAEs, the Society for Immunotherapy for Cancer and the American Association for Cancer Research partnered to bring together research and clinical experts in cancer immunotherapy, autoimmunity, immune regulation, genetics and informatics who are investigating irAEs using animal models, clinical data and patient specimens to discuss current strategies and identify the critical next steps needed to create breakthroughs in our understanding of these toxicities. The genetic and environmental risk factors, immune cell subsets and other key immunological mediators and the unique clinical presentations of irAEs across the different organ systems were the foundation for identifying key opportunities and future directions described in this report. These include the pressing need for significantly improved preclinical model systems, broader collection of biospecimens with standardized collection and clinical annotation made available for research and integration of electronic health record and multiomic data with harmonized and standardized methods, definitions and terminologies to further our understanding of irAE pathogenesis. Based on these needs, this report makes a set of recommendations to advance our understanding of irAE mechanisms, which will be crucial to prevent their occurrence and improve their treatment.

Pleiotropy of systemic lupus erythematosus risk alleles and cardiometabolic disorders: A phenome-wide association study and inverse-variance weighted meta-analysis

OBJECTIVES

To test the hypothesis that genetic predisposition to systemic lupus erythematosus (SLE) increases the risk of cardiometabolic disorders.

METHODS

Using 41 single nucleotide polymorphisms (SNPs) associated with SLE, we calculated a weighted genetic risk score (wGRS) for SLE. In a large biobank we tested the association between this wGRS and 9 cardiometabolic phenotypes previously associated with SLE: atrial fibrillation, ischemic stroke, coronary artery disease, type 1 and type 2 diabetes, obesity, chronic kidney disease, hypertension, and hypercholesterolemia. Additionally, we performed a phenome-wide association analysis (pheWAS) to discover novel clinical associations with a genetic predisposition to SLE. Findings were replicated in the Electronic Medical Records and Genomics (eMERGE) Network. To further define the association between SLE-related risk alleles and the selected cardiometabolic phenotypes, we performed an inverse variance weighted regression (IVWR) meta-analysis.

RESULTS

The wGRS for SLE was calculated in 74,759 individuals of European ancestry. Among the pre-selected phenotypes, the wGRS was significantly associated with type 1 diabetes (OR [95%CI] =1.11 [1.06, 1.17], P-value = 1.05x10-5). In the PheWAS, the wGRS was associated with several autoimmune phenotypes, kidney disorders, and skin neoplasm; but only the associations with autoimmune phenotypes were replicated. In the IVWR meta-analysis, SLE-related risk alleles were nominally associated with type 1 diabetes (P = 0.048) but the associations were heterogeneous and did not meet the adjusted significance threshold.

CONCLUSION

A weighted GRS for SLE was associated with an increased risk of several autoimmune-related phenotypes including type I diabetes but not with cardiometabolic disorders.

Remdesivir Versus Standard-of-Care for Severe Coronavirus Disease 2019 Infection: An Analysis of 28-Day Mortality

Background

Remdesivir is approved by the US Food and Drug Administration for the treatment of patients hospitalized with coronavirus disease 2019 (COVID-19) and has been shown to shorten time to recovery and improve clinical outcomes in randomized trials.

Methods

This was the final day 28 comparative analysis of data from a phase 3, randomized, open-label study comparing 2 remdesivir regimens (5 vs 10 days, combined for this analysis [remdesivir cohort]) and a real-world retrospective longitudinal cohort study of patients receiving standard-of-care treatment (nonremdesivir cohort). Eligible patients, aged ≥18 years, had confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), oxygen saturation ≤94% on room air or required supplemental oxygen, with pulmonary infiltrates. Propensity score matching (up to 1:10 ratio) was used to ensure comparable populations. We assessed day 14 clinical recovery (determined using a 7-point ordinal scale) and day 28 all-cause mortality (coprimary endpoints).

Results

A total of 368 (remdesivir) and 1399 (nonremdesivir) patients were included in the matched analysis. The day 14 clinical recovery rate was significantly higher among the remdesivir versus the nonremdesivir cohort (65.2% vs 57.1%; odds ratio [OR], 1.49; 95% confidence interval [CI], 1.16–1.90; P = 0.002). The day 28 mortality rate was significantly lower in the remdesivir cohort versus the nonremdesivir cohort (12.0% vs 16.2%; OR, 0.67; 95% CI, 0.47–.95; P = .03).

Conclusions

Remdesivir was associated with significantly higher rates of day 14 clinical recovery, and lower day 28 mortality, compared with standard-of-care treatment in hospitalized patients with COVID-19. These data, taken together, support the use of remdesivir to improve clinical recovery and decrease mortality from SARS-CoV-2 infection.

Evaluation of structured data from electronic health records to identify clinical classification criteria attributes for systemic lupus erythematosus

Objective

Our objective was to develop algorithms to identify lupus clinical classification criteria attributes using structured data found in the electronic health record (EHR) and determine whether they could be used to describe a cohort of people with lupus and discriminate them from a defined healthy control cohort.

Methods

We created gold standard lupus and healthy patient cohorts that were fully adjudicated for the American College of Rheumatology (ACR), Systemic Lupus International Collaborating Clinics (SLICC) and European League Against Rheumatism/ACR (EULAR/ACR) classification criteria and had matched EHR data. We implemented rule-based algorithms using structured data within the EHR system for each attribute of the three classification criteria. Individual criteria attribute and classification criteria algorithms as a whole were assessed over our combined cohorts and the overall performance of the algorithms was measured through sensitivity and specificity.

Results

Individual classification criteria attributes had a wide range of sensitivities, 7% (oral ulcers) to 97% (haematological disorders) and specificities, 56% (haematological disorders) to 98% (photosensitivity), but all could be identified in EHR data. In general, algorithms based on laboratory results performed better than those primarily based on diagnosis codes. All three classification criteria systems effectively distinguished members of our case and control cohorts, but the SLICC criteria-based algorithm had the highest overall performance (76% sensitivity, 99% specificity).

Conclusions

It is possible to characterise disease manifestations in people with lupus using classification criteria-based algorithms that assess structured EHR data. These algorithms may reduce chart review burden and are a foundation for identifying subpopulations of patients with lupus based on disease presentation to support precision medicine applications.

Does coaching matter? Examining the impact of specific practice facilitation strategies on implementation of quality improvement interventions in the Healthy Hearts in the Heartland study

BACKGROUND

Practice facilitation is a multicomponent implementation strategy used to improve the capacity for practices to address care quality and implementation gaps. We sought to assess whether practice facilitators use of coaching strategies aimed at improving self-sufficiency were associated with improved implementation of quality improvement (QI) interventions in the Healthy Hearts in the Heartland Study.

METHODS

We mapped 27 practice facilitation activities to a framework that classifies practice facilitation strategies by the degree to which the practice develops its own process expertise (Doing Tasks, Project Management, Consulting, Teaching, and Coaching) and then used regression tree analysis to group practices by facilitation strategies experienced. Kruskal-Wallis tests were used to assess whether practice groups identified by regression tree analysis were associated with successful implementation of QI interventions and practice and study context variables.

RESULTS

There was no association between number of strategies performed by practice facilitators and number of QI interventions implemented. Regression tree analysis identified 4 distinct practice groups based on the number of Project Management and Coaching strategies performed. The median number of interventions increased across the groups. Practices receiving > 4 project management and > 6 coaching activities implemented a median of 17 of 35 interventions. Groups did not differ significantly by practice size, association with a healthcare network, or practice type. Statistically significant differences in practice location, number and duration of facilitator visits, and early study termination emerged among the groups, compared to the overall practice population.

CONCLUSIONS

Practices that engage in more coaching-based strategies with practice facilitators are more likely to implement more QI interventions, and practice receptivity to these strategies was not dependent on basic practice demographics.

Remdesivir for Severe COVID-19 versus a Cohort Receiving Standard of Care

Background

We compared the efficacy of the antiviral agent, remdesivir, versus standard-of-care treatment in adults with severe coronavirus disease 2019 (COVID-19) using data from a phase 3 remdesivir trial and a retrospective cohort of patients with severe COVID-19 treated with standard of care.

Methods

GS-US-540–5773 is an ongoing phase 3, randomized, open-label trial comparing two courses of remdesivir (remdesivir-cohort). GS-US-540–5807 is an ongoing real-world, retrospective cohort study of clinical outcomes in patients receiving standard-of-care treatment (non-remdesivir-cohort). Inclusion criteria were similar between studies: patients had confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, were hospitalized, had oxygen saturation ≤94% on room air or required supplemental oxygen, and had pulmonary infiltrates. Stabilized inverse probability of treatment weighted multivariable logistic regression was used to estimate the treatment effect of remdesivir versus standard of care. The primary endpoint was the proportion of patients with recovery on day 14, dichotomized from a 7-point clinical status ordinal scale. A key secondary endpoint was mortality.

Results

After the inverse probability of treatment weighting procedure, 312 and 818 patients were counted in the remdesivir- and non-remdesivir-cohorts, respectively. At day 14, 74.4% of patients in the remdesivir-cohort had recovered versus 59.0% in the non-remdesivir-cohort (adjusted odds ratio [aOR] 2.03: 95% confidence interval [CI]: 1.34–3.08, P < .001). At day 14, 7.6% of patients in the remdesivir-cohort had died versus 12.5% in the non-remdesivir-cohort (aOR 0.38, 95% CI: .22–.68, P = .001).

Conclusions

In this comparative analysis, by day 14, remdesivir was associated with significantly greater recovery and 62% reduced odds of death versus standard-of-care treatment in patients with severe COVID-19.

Clinical Trials Registration

NCT04292899 and EUPAS34303.

A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies

CONTEXT

As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated to be unidentified in clinical practice.

OBJECTIVE

Utilizing polygenic risk prediction, we aim to identify the phenome-wide comorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventive treatment.

DESIGN, PATIENTS, AND METHODS

Leveraging the electronic health records (EHRs) of 124 852 individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores (PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). We evaluated its predictive capability across different ancestries and perform a PRS-based phenome-wide association study (PheWAS) to assess the phenomic expression of the heightened risk of PCOS.

RESULTS

The integrated polygenic prediction improved the average performance (pseudo-R2) for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null model across European, African, and multi-ancestry participants respectively. The subsequent PRS-powered PheWAS identified a high level of shared biology between PCOS and a range of metabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity", "type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension", and "sleep apnea" reaching phenome-wide significance.

CONCLUSIONS

Our study has expanded the methodological utility of PRS in patient stratification and risk prediction, especially in a multifactorial condition like PCOS, across different genetic origins. By utilizing the individual genome-phenome data available from the EHR, our approach also demonstrates that polygenic prediction by PRS can provide valuable opportunities to discover the pleiotropic phenomic network associated with PCOS pathogenesis.

Using Electronic Health Records to Measure Quality Improvement Efforts: Findings from a Large Practice Facilitation Initiative

BACKGROUND

Federal incentives for electronic health record (EHR) use typically require quality measure reporting over calendar year or 90-day periods. However, required reporting periods may not align with time frames of real-world quality improvement (QI) efforts. This study described primary care practices' ability to obtain measures with reporting periods aligning with a large QI initiative.

METHODS

Researchers conducted a substudy of a randomized trial testing practice facilitation strategies for preventive cardiovascular care. Three quality measures (aspirin for ischemic vascular disease; blood pressure control for hypertension; smoking screening/cessation) were collected quarterly over one year. The primary outcome was a binary indicator of whether a practice facilitator obtained all three measures with "rolling 12-month" reporting periods (that is, the year preceding each study quarter).

RESULTS

The study included 107 practices, 63 (58.9%) of which met the primary outcome of obtaining all measures with rolling 12-month reporting periods. Smaller practices were less likely to meet the primary outcome (p < 0.001). Practices used 11 different EHRs, 3 of which were unable to consistently produce rolling 12-month measures; at 33 practices (30.8%) using these 3 EHRs, facilitators met a secondary outcome of obtaining prior calendar year and rolling 3-month measures. Facilitators reported barriers to data collection such as practices lacking optional EHR features, and EHRs' inability to produce reporting periods across two calendar years.

CONCLUSION

EHR vendors' compliance with federal reporting requirements is not necessarily sufficient to support real-world QI work. Improvements are needed in the flexibility and usability of EHRs' quality measurement functions, particularly for smaller practices.

Challenges to electronic clinical quality measurement using third-party platforms in primary care practices: the healthy hearts in the heartland experience

Third-party platforms have emerged to support small primary care practices for calculating and reporting electronic clinical quality measures (eCQM) for federal programs like The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) and Merit-based Incentive Payment System (MIPS). Yet little is known about the capabilities and limitations of electronic health record systems (EHRs) to enable data access for these programs. We connected 116 small- to medium-sized practices with seven different EHRs to popHealth, an open-source eCQM platform. We identified the prevalence of following problems with eCQM data for data extraction in seven different EHRs: (1) Lack of coded data in five of seven; (2) Incorrectly categorized data in four of seven; (3) Isosemantic data (data within the incorrect context) in four of seven; (4) Coding that could not be directly evaluated in six of seven; (5) Errors in date assignment and labeled as historical values in five of seven; and (6) Inadequate data to assign the correct code in two of seven. We recommend specific enhancements to EHR systems that can promote effective eCQM implementation and reporting to MACRA and MIPS.

Assessing the Concordance of Clinical Classification Criteria for Lupus Between Electronic Health Records and a Physician Curated Registry

We developed a computable phenotype for systemic lupus erythematosus (SLE) based on the Systemic Lupus International Collaborative Clinics clinical classification criteria set for SLE. We evaluated the phenotype over registry and EHR data for the same patient population to determine concordance of criteria detected in both datasets and to assess which types of structured data detected individual classification criteria. We identified a concordance of 68% between registry and EHR data relying solely on structured data.

Engaging Primary Care Practices in Studies of Improvement: Did You Budget Enough for Practice Recruitment?

PURPOSE

The methods and costs to enroll small primary care practices in large, regional quality improvement initiatives are unknown. We describe the recruitment approach, cost, and resources required to recruit and enroll 500 practices in the Northwest and Midwest regional cooperatives participating in the Agency for Healthcare Research and Quality (AHRQ)-funded initiative, EvidenceNOW: Advancing Heart Health in Primary Care.

METHODS

The project management team of each cooperative tracked data on recruitment methods used for identifying and connecting with practices. We developed a cost-of-recruitment template and used it to record personnel time and associated costs of travel and communication materials.

RESULTS

A total of 3,669 practices were contacted during the 14- to 18-month recruitment period, resulting in 484 enrolled practices across the 6 states served by the 2 cooperatives. The average number of interactions per enrolled practice was 7, with a total of 29,100 hours and a total cost of $2.675 million, or $5,529 per enrolled practice. Prior partnerships predicted recruiting almost 1 in 3 of these practices as contrasted to 1 in 20 practices without a previous relationship or warm hand-off.

CONCLUSIONS

Recruitment of practices for large-scale practice quality improvement transformation initiatives is difficult and costly. The cost of recruiting practices without existing partnerships is expensive, costing 7 times more than reaching out to familiar practices. Investigators initiating and studying practice quality improvement initiatives should budget adequate funds to support high-touch recruitment strategies, including building trusted relationships over a long time frame, for a year or more.

Practice Facilitators' and Leaders' Perspectives on a Facilitated Quality Improvement Program

PURPOSE

Practice facilitation is a promising approach to helping practices implement quality improvements. Our purpose was to describe practice facilitators' and practice leaders' perspectives on implementation of a practice facilitator-supported quality improvement program and describe where their perspectives aligned and diverged.

METHODS

We conducted interviews with practice leaders and practice facilitators who participated in a program that included 35 improvement strategies aimed at the ABCS of heart health (aspirin use in high-risk individuals, blood pressure control, cholesterol management, and smoking cessation). Rapid qualitative analysis was used to collect, organize, and analyze the data.

RESULTS

We interviewed 17 of the 33 eligible practice leaders, and the 10 practice facilitators assigned to those practices. Practice leaders and practice facilitators both reported value in the program's ability to bring needed, high-quality resources to practices. Practice leaders appreciated being able to set the schedule for facilitation and select among the 35 interventions. According to practice facilitators, however, relying on practice leaders to set the pace of the intervention resulted in a lower level of program intensity than intended. Practice leaders preferred targeted assistance, particularly electronic health record documentation guidance and linkages to state smoking cessation programs. Practice facilitators reported that the easiest interventions were those that did not alter care practices.

CONCLUSIONS

The dual perspectives of practice leaders and practice facilitators provide a more holistic picture of enablers and barriers to program implementation. There may be greater opportunities to assist small practices through simple, targeted practice facilitator-supported efforts rather than larger, comprehensive quality improvement projects.

Disease Outcomes and Care Fragmentation Among Patients With Systemic Lupus Erythematosus

OBJECTIVE

To examine the impact of care fragmentation across multiple health care institutions on disease outcomes in patients with systemic lupus erythematosus (SLE).

METHODS

Using the Chicago HealthLNK Data Repository, an assembly of electronic health records from 6 institutions, we identified patients with SLE, using International Classification of Diseases, Ninth Revision (ICD-9) codes, whose care was delivered at more than 1 organization. We examined whether patients had severe infections or comorbidities (ICD-9 code defined) that indicated SLE-induced damage. T-tests and chi-square tests were used to examine differences between fragmentation groups. Logistic regression was used to assess factors contributing to the occurrence of disease outcomes.

RESULTS

We identified 4,276 patients with SLE. A total of 856 (20%) received care from more than 1 health care institution. African American patients and patients with public insurance were more likely to experience care fragmentation compared to white and private insurance patients (odds ratio [OR] 1.66, 95% confidence interval [95% CI] 1.44-1.97 and OR 1.63, 95% CI 1.42-1.95). We identified increased risk of infections (OR 1.57, 95% CI 1.30-1.88), cardiovascular disease (OR 1.51, 95% CI 1.23-1.86), end-stage renal disease (OR 1.34, 95% CI 1.05-1.70), nephritis (OR 1.28, 95% CI 1.07-1.54), and stroke (OR 1.28, 95% CI 1.01-1.62) among patients with fragmented care, adjusted for age, sex, race, insurance status, length of followup time, and total visit count.

CONCLUSION

In this cross-site cohort of SLE patients, care fragmentation is associated with increased risk of severe infection and comorbidities. These results suggest that improved health information exchange could positively impact outcomes for SLE patients.

Design and implementation of a privacy preserving electronic health record linkage tool in Chicago

OBJECTIVE

To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical research.

METHODS

The authors developed and distributed a software application that performs standardized data cleaning, preprocessing, and hashing of patient identifiers to remove all protected health information. The application creates seeded hash code combinations of patient identifiers using a Health Insurance Portability and Accountability Act compliant SHA-512 algorithm that minimizes re-identification risk. The authors subsequently linked individual records using a central honest broker with an algorithm that assigns weights to hash combinations in order to generate high specificity matches.

RESULTS

The software application successfully linked and de-duplicated 7 million records across 6 institutions, resulting in a cohort of 5 million unique records. Using a manually reconciled set of 11 292 patients as a gold standard, the software achieved a sensitivity of 96% and a specificity of 100%, with a majority of the missed matches accounted for by patients with both a missing social security number and last name change. Using 3 disease examples, it is demonstrated that the software can reduce duplication of patient records across sites by as much as 28%.

CONCLUSIONS

Software that standardizes the assignment of a unique seeded hash identifier merged through an agreed upon third-party honest broker can enable large-scale secure linkage of EHR data for epidemiologic and public health research. The software algorithm can improve future epidemiologic research by providing more comprehensive data given that patients may make use of multiple healthcare systems.

The genetic basis of laboratory adaptation in Caulobacter crescentus

The dimorphic bacterium Caulobacter crescentus has evolved marked phenotypic changes during its 50-year history of culture in the laboratory environment, providing an excellent system for the study of natural selection and phenotypic microevolution in prokaryotes. Combining whole-genome sequencing with classical molecular genetic tools, we have comprehensively mapped a set of polymorphisms underlying multiple derived phenotypes, several of which arose independently in separate strain lineages. The genetic basis of phenotypic differences in growth rate, mucoidy, adhesion, sedimentation, phage susceptibility, and stationary-phase survival between C. crescentus strain CB15 and its derivative NA1000 is determined by coding, regulatory, and insertion/deletion polymorphisms at five chromosomal loci. This study evidences multiple genetic mechanisms of bacterial evolution as driven by selection for growth and survival in a new selective environment and identifies a common polymorphic locus, zwf, between lab-adapted C. crescentus and clinical isolates of Pseudomonas aeruginosa that have adapted to a human host during chronic infection.

Draft sequencing and comparative genomics of Xylella fastidiosa strains reveal novel biological insights

Draft sequencing is a rapid and efficient method for determining the near-complete sequence of microbial genomes. Here we report a comparative analysis of one complete and two draft genome sequences of the phytopathogenic bacterium, Xylella fastidiosa, which causes serious disease in plants, including citrus, almond, and oleander. We present highlights of an in silico analysis based on a comparison of reconstructions of core biological subsystems. Cellular pathway reconstructions have been used to identify a small number of genes, which are likely to reside within the draft genomes but are not captured in the draft assembly. These represented only a small fraction of all genes and were predominantly large and small ribosomal subunit protein components. By using this approach, some of the inherent limitations of draft sequence can be significantly reduced. Despite the incomplete nature of the draft genomes, it is possible to identify several phage-related genes, which appear to be absent from the draft genomes and not the result of insufficient sequence sampling. This region may therefore identify potential host-specific functions. Based on this first functional reconstruction of a phytopathogenic microbe, we spotlight an unusual respiration machinery as a potential target for biological control. We also predicted and developed a new defined growth medium for Xylella.

Whole-genome comparative analysis of three phytopathogenic Xylella fastidiosa strains

Xylella fastidiosa (Xf) causes wilt disease in plants and is responsible for major economic and crop losses globally. Owing to the public importance of this phytopathogen we embarked on a comparative analysis of the complete genome of Xf pv citrus and the partial genomes of two recently sequenced strains of this species: Xf pv almond and Xf pv oleander, which cause leaf scorch in almond and oleander plants, respectively. We report a reanalysis of the previously sequenced Xf 9a5c (CVC, citrus) strain and the two "gapped" Xf genomes revealing ORFs encoding critical functions in pathogenicity and conjugative transfer. Second, a detailed whole-genome functional comparison was based on the three sequenced Xf strains, identifying the unique genes present in each strain, in addition to those shared between strains. Third, an "in silico" cellular reconstruction of these organisms was made, based on a comparison of their core functional subsystems that led to a characterization of their conjugative transfer machinery, identification of potential differences in their adhesion mechanisms, and highlighting of the absence of a classical quorum-sensing mechanism. This study demonstrates the effectiveness of comparative analysis strategies in the interpretation of genomes that are closely related.

Cutting edge: the Ets1 transcription factor is required for the development of NK T cells in mice

Ets1-deficient mice develop B and T cells but display a severe defect in the development of the NK cell lineage. In this report, we demonstrate that Ets1 is also required for the development of NK1.1+ T (NK T) cells. We observed significantly decreased numbers of NK T cells in the thymus, spleen, and liver of Ets1-deficient mice. These organs also contained markedly decreased levels of the canonical Valpha14-Jalpha281 TCRalpha transcript seen in NK T cells. Unlike wild-type NK T cells, Ets1-deficient thymocytes failed to produce detectable levels of IL-4 following anti-CD3 stimulation. The absence of NK T cells in the Ets1-deficient mice was not associated with defective expression of CD1, an MHC class I molecule required for NK T cell development. We conclude that Ets1 defines a novel transcriptional regulatory pathway that is required for the development of both the NK and NK T cell lineages.

The Ets-1 transcription factor is required for the development of natural killer cells in mice

In this report we have investigated the role of the Ets-1 transcription factor in the differentiation of the NK cell lineage in mice. Splenic NK cells express high levels of Ets-1. Ets-1-deficient mice produced by gene targeting developed mature erythrocytes, monocytes, neutrophils, and T and B lymphocytes. However, spleens from the Ets-1-deficient mice contained significantly reduced numbers of natural killer (NK) cells, and splenocytes from these mice lacked detectable cytolytic activity against NK cell targets in vitro. Moreover, unlike wild-type animals, Ets-1-deficient mice developed tumors following subcutaneous injection of NK-susceptible RMA-S cells. These NK cell defects could not be correlated with defects in the expression of IL-12, IL-15, and IL-18 or the IL-2 or IL-15 receptors. Thus, Ets-1 defines a novel transcriptional pathway that is required for the development of the NK cell lineage in mice.

CTLA-4 regulates tolerance induction and T cell differentiation in vivo

Cytotoxic T lymphocyte Ag-4 (CTLA-4; CD152) is an important T cell regulatory molecule. In vitro experiments have shown that the blockade of signals through CTLA-4 augments T cell expansion, while CTLA-4 cross-linking results in decreased T cell proliferation due to decreased IL-2 production. However, less is known about the role of CTLA-4 in regulating an ongoing immune response. In this study, we examined the role of CTLA-4 in the expansion, decline, tolerization, and differentiation of T cells following treatment with staphylococcal enterotoxin B (SEB). Anti-CTLA-4 treatment resulted in increased numbers of SEB-reactive T cells and blockade of subsequent tolerance induction. Further examination of the SEB-reactive cells from anti-CTLA-4-treated mice demonstrated that both the CD4+ and CD8+ Vbeta8+ T cells produced IL-4, providing evidence that not only do signals through CTLA-4 regulate T cell-tolerizing events, but they also play an important role in the differentiation of T cells in vivo.

CTLA-4 Regulates Tolerance Induction and T Cell Differentiation In Vivo

Cytotoxic T lymphocyte Ag-4 (CTLA-4; CD152) is an important T cell regulatory molecule. In vitro experiments have shown that the blockade of signals through CTLA-4 augments T cell expansion, while CTLA-4 cross-linking results in decreased T cell proliferation due to decreased IL-2 production. However, less is known about the role of CTLA-4 in regulating an ongoing immune response. In this study, we examined the role of CTLA-4 in the expansion, decline, tolerization, and differentiation of T cells following treatment with staphylococcal enterotoxin B (SEB). Anti-CTLA-4 treatment resulted in increased numbers of SEB-reactive T cells and blockade of subsequent tolerance induction. Further examination of the SEB-reactive cells from anti-CTLA-4-treated mice demonstrated that both the CD4+ and CD8+ Vβ8+ T cells produced IL-4, providing evidence that not only do signals through CTLA-4 regulate T cell-tolerizing events, but they also play an important role in the differentiation of T cells in vivo.

CTLA-4: a negative regulator of autoimmune disease

CTLA-4, a CD28 homologue expressed on activated T cells, binds with high affinity to the CD28 ligands, B7-1 (CD80) and B7-2 (CD86). This study was designed to examine the role of CTLA-4 in regulating autoimmune disease. Murine relapsing-remitting experimental autoimmune encephalomyelitis (R-EAE) is a demyelinating disease mediated by PLP139-151-specific CD4+ T cells in SJL/J mice. Anti-CTLA-4 mAbs (or their F(ab) fragments) enhanced in vitro proliferation and pro-inflammatory cytokine production by PLP139-151-primed lymph node cells. Addition of either reagent to in vitro activation cultures potentiated the ability of T cells to adoptively transfer disease to naive recipients. In vivo administration of anti-CTLA-4 mAb to recipients of PLP139-151-specific T cells resulted in accelerated and exacerbated disease. Finally, anti-CTLA-4 treatment of mice during disease remission resulted in the exacerbation of relapses. Collectively, these results suggest that CTLA-4 mediates the downregulation of ongoing immune responses and plays a major role in regulating autoimmunity.

CTLA-4 ligation blocks CD28-dependent T cell activation

CTLA-4 is a CD28 homologue believed to be a negative regulator of T cell function. However, the mechanism of this downregulatory activity is not well understood. The present study was designed to examine the effect of CTLA-4 ligation on cytokine production, cell survival, and cell cycle progression. The results demonstrate that the primary effect of CTLA-4 ligation is not the induction of apoptosis. Instead, CTLA-4 signaling blocks IL-2 production, IL-2 receptor expression, and cell cycle progression of activated T cells. Moreover, the effect of CTLA-4 signaling was manifested after initial T cell activation. Inhibition of IL-2 receptor expression and cell cycle progression was more pronounced at late (72 h) time points after initial activation. The effects of anti-CTLA-4 mAbs were most apparent in the presence of optimal CD28-mediated costimulation consistent with the finding that CTLA-4 upregulation was CD28-dependent. Finally, the addition of exogenous IL-2 to the cultures restored IL-2 receptor expression and T cell proliferation. These results suggest that CTLA-4 signaling does not regulate cell survival or responsiveness to IL-2, but does inhibit CD28-dependent IL-2 production.

CD28/B7 system of T cell costimulation

T cells play a central role in the initiation and regulation of the immune response to antigen. Both the engagement of the TCR with MHC/Ag and a second signal are needed for the complete activation of the T cell. The CD28/B7 receptor/ligand system is one of the dominant costimulatory pathways. Interruption of this signaling pathway with CD28 antagonists not only results in the suppression of the immune response, but in some cases induces antigen-specific tolerance. However, the CD28/B7 system is increasingly complex due to the identification of multiple receptors and ligands with positive and negative signaling activities. This review summarizes the state of CD28/B7 immunobiology both in vitro and in vivo; summarizes the many experiments that have led to our current understanding of the participants in this complex receptor/ligand system; and illustrates the current models for CD28/B7-mediated T cell and B cell regulation. It is our hope and expectation that this review will provoke additional research that will unravel this important, yet complex, signaling pathway.

CD28 expression is not essential for positive and negative selection of thymocytes or peripheral T cell tolerance

Thymocyte development requires positive selection of clones that can recognize Ag presented by MHC molecules and negative selection of clones that are self-reactive. However, the costimulatory signals required for negative selection and cell death, or positive selection and the transition to the peripheral lymphoid system, are not well understood. Many molecular interactions that are important for T cell activation have also been found to play a role in thymocyte development. The importance of the CD28/B7 interaction in the activation of mature T cells and recent observations that CD28 may play a role negative selection of developing CD4+CD8+ thymocytes suggest that CD28 may also be involved in development and maintenance of T cell tolerance. CD28-deficient mice were crossed to alpha beta and gamma delta TCR transgenic as well as H-2k Mlsc-bearing animals and were used to address the role of CD28 in positive and negative selection of developing T cells. The CD28-deficient animals demonstrated no obvious deficiency in either positive or negative selection of developing thymocytes. However, when mixed bone marrow chimeras were created with cells derived from both CD28-deficient and wild-type mice, the CD28+ T cells had a selective advantage over the CD28-deficient T cells. Therefore, it appears that CD28, although not essential for the selection of T cells during development, may allow for additional signals that increase the efficiency of selection and/or expansion of peripheral T cell populations.

CD28 expression is not essential for positive and negative selection of thymocytes or peripheral T cell tolerance

Thymocyte development requires positive selection of clones that can recognize Ag presented by MHC molecules and negative selection of clones that are self-reactive. However, the costimulatory signals required for negative selection and cell death, or positive selection and the transition to the peripheral lymphoid system, are not well understood. Many molecular interactions that are important for T cell activation have also been found to play a role in thymocyte development. The importance of the CD28/B7 interaction in the activation of mature T cells and recent observations that CD28 may play a role negative selection of developing CD4+CD8+ thymocytes suggest that CD28 may also be involved in development and maintenance of T cell tolerance. CD28-deficient mice were crossed to alpha beta and gamma delta TCR transgenic as well as H-2k Mlsc-bearing animals and were used to address the role of CD28 in positive and negative selection of developing T cells. The CD28-deficient animals demonstrated no obvious deficiency in either positive or negative selection of developing thymocytes. However, when mixed bone marrow chimeras were created with cells derived from both CD28-deficient and wild-type mice, the CD28+ T cells had a selective advantage over the CD28-deficient T cells. Therefore, it appears that CD28, although not essential for the selection of T cells during development, may allow for additional signals that increase the efficiency of selection and/or expansion of peripheral T cell populations.