Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel

Risk of Anaphylaxis Among New Users of GLP-1 Receptor Agonists: A Cohort Study

OBJECTIVE

To assess risk of anaphylaxis among patients with type 2 diabetes mellitus who are initiating therapy with a glucagon-like peptide 1 receptor agonist (GLP-1 RA), with a focus on those starting lixisenatide therapy.

RESEARCH DESIGN AND METHODS

A cohort study was conducted in three large, U.S. claims databases (2017-2021). Adult (aged ≥18 years) new users of a GLP-1 RA who had type 2 diabetes mellitus and ≥6 months enrollment in the database before GLP-1 RA initiation (start of follow-up) were included. GLP-1 RAs evaluated were lixisenatide, an insulin glargine/lixisenatide fixed-ratio combination (FRC), exenatide, liraglutide or insulin degludec/liraglutide FRC, dulaglutide, and semaglutide (injectable and oral). The first anaphylaxis event during follow-up was identified using a validated algorithm. Incidence rates (IRs) and 95% CIs were calculated within each medication cohort. The unadjusted IR ratio (IRR) comparing anaphylaxis rates in the lixisenatide cohort with all other GLP-1 RAs combined was analyzed post hoc.

RESULTS

There were 696,089 new users with 456,612 person-years of exposure to GLP-1 RAs. Baseline demographics, comorbidities, and use of other prescription medications in the 6 months before the index date were similar across medication cohorts. IRs (95% CIs) per 10,000 person-years were 1.0 (0.0-5.6) for lixisenatide, 6.0 (3.6-9.4) for exenatide, 5.1 (3.7-7.0) for liraglutide, 3.9 (3.1-4.8) for dulaglutide, and 3.6 (2.6-4.9) for semaglutide. The IRR (95% CI) for the anaphylaxis rate for the lixisenatide cohort compared with the pooled other GLP-1 RA cohort was 0.24 (0.01-1.35).

CONCLUSIONS

Anaphylaxis is rare with GLP-1 RAs. Lixisenatide is unlikely to confer higher risk of anaphylaxis than other GLP-1 RAs.

An application of the Causal Roadmap in two safety monitoring case studies: Causal inference and outcome prediction using electronic health record data

Background

Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these settings, it is important to document analytic decisions transparently and objectively to assess and ensure that analyses meet their intended goals.

Methods

The Causal Roadmap is an established framework that can guide and document analytic decisions through each step of the analytic pipeline, which will help investigators generate high-quality real-world evidence.

Results

In this paper, we illustrate the utility of the Causal Roadmap using two case studies previously led by workgroups sponsored by the Sentinel Initiative - a program for actively monitoring the safety of regulated medical products. Each case example focuses on different aspects of the analytic pipeline for drug safety monitoring. The first case study shows how the Causal Roadmap encourages transparency, reproducibility, and objective decision-making for causal analyses. The second case study highlights how this framework can guide analytic decisions beyond inference on causal parameters, improving outcome ascertainment in clinical phenotyping.

Conclusion

These examples provide a structured framework for implementing the Causal Roadmap in safety surveillance and guide transparent, reproducible, and objective analysis.

Positive Predictive Values of Anaphylaxis Diagnosis in Claims Data: A Multi-Institutional Study in Taiwan

Real-world data sources can facilitate essential understanding of the epidemiological features of anaphylaxis. However, the accuracy of case-identifying definitions based on diagnosis codes for anaphylaxis in healthcare databases remains understudied. We conducted a cross-sectional study analyzing claims data from the largest multi-institutional healthcare system in Taiwan during 2017-2021. We included patients with incident anaphylaxis identified by either ICD-10-CM codes for anaphylaxis (Group 1) or ICD-10-CM codes for severe allergic or drug adverse events and additional modifier codes for acute allergy events (Group 2). We randomly selected 20% of the cases to determine the positive predictive value (PPV) of anaphylaxis case-identifying definitions in Groups 1 and 2 after review of electronic medical records by two physicians. From the original cohort (n = 2,176), we randomly selected 433 patients with either a diagnosis of anaphylaxis (Group 1), or a diagnosis of severe allergic and drug adverse events with additional modifier codes for acute allergy events (Group 2). In Group 1, we judged 135 / 170 patients as true anaphylaxis cases, giving a PPV of 79.4% (95% CI: 73.3-85.5). In Group 2, we judged 47 / 263 patients as true anaphylaxis cases, giving a PPV of 17.9% (95% CI: 13.3-22.5). In conclusion, acceptable PPVs were observed when anaphylaxis cases were identified by ICD-10-CM codes for anaphylaxis, but not by ICD-10-CM codes for severe allergic or drug adverse event with additional modifier codes for acute allergy events. Our multi-institutional findings could serve as a fundamental reference for further studies of anaphylaxis based on real-world healthcare databases.

Direct Versus Indirect Query Performance of ICD-9/-10 Coding to Identify Anaphylaxis

BACKGROUND

Anaphylaxis is an often under =diagnosed, severe allergic event for which epidemiological data are sporadic. Researchers have leveraged administrative and claims data algorithms to study large databases of anaphylactic events; however, little longitudinal data analysis is available after transition to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM).

OBJECTIVE

Study longitudinal trends in anaphylaxis incidence using direct and indirect query methods.

METHODS

Emergency department (ED) and inpatient data were analyzed from a large state health care administration database from 2011 to 2020. Incidence was calculated using direct queries of anaphylaxis ICD-9-CM and ICD-10-CM codes and indirect queries using a symptom-based ICD-9-CM algorithm and forward mapped ICD-10-CM version to identify undiagnosed anaphylaxis episodes and to assess algorithm performance at the population level.

RESULTS

An average of 2.4 million inpatient and 7.5 million ED observations/y were analyzed. Using the direct query method, annual ED anaphylaxis cases increased steadily from 1,454 (2011) to 4,029 (2019) then declined to 3,341 in 2020 during the coronavirus disease 2019 (COVID-19) pandemic. In contrast, inpatient cases remained relatively steady, with a slight decline after 2015 during the ICD version transition, until a significant drop occurred in 2020. Using the indirect queries, anaphylaxis cases increased markedly after the ICD transition year, especially involving drug-related anaphylaxis.

CONCLUSIONS

Nontypical drug associations with anaphylaxis episodes using the ICD-10-CM version of the algorithm suggest poor performance with drug-related codes. Further, the increased granularity of ICD-10-CM identified potential limitations of a previously validated symptom-based ICD-9-CM algorithm used to detect undiagnosed cases.

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning

We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance of automated health-care claims-based algorithms to identify anaphylaxis events using data on 516 patients with outpatient, emergency department, or inpatient anaphylaxis diagnosis codes during 2015-2019 in 2 integrated health-care institutions in the Northwest United States. We used one site's manually reviewed gold-standard outcomes data for model development and the other's for external validation based on cross-validated area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and sensitivity. In the development site 154 (64%) of 239 potential events met adjudication criteria for anaphylaxis compared with 180 (65%) of 277 in the validation site. Logistic regression models using only structured claims data achieved a cross-validated AUC of 0.58 (95% CI: 0.54, 0.63). Machine learning improved cross-validated AUC to 0.62 (0.58, 0.66); incorporating NLP-derived covariates further increased cross-validated AUCs to 0.70 (0.66, 0.75) in development and 0.67 (0.63, 0.71) in external validation data. A classification threshold with cross-validated PPV of 79% and cross-validated sensitivity of 66% in development data had cross-validated PPV of 78% and cross-validated sensitivity of 56% in external data. Machine learning and NLP-derived data improved identification of validated anaphylaxis events.

Active Postlicensure Safety Surveillance for Recombinant Zoster Vaccine Using Electronic Health Record Data

Recombinant zoster vaccine (RZV) (Shingrix; GlaxoSmithKline, Brentford, United Kingdom) is an adjuvanted glycoprotein vaccine that was licensed in 2017 to prevent herpes zoster (shingles) and its complications in older adults. In this prospective, postlicensure Vaccine Safety Datalink study using electronic health records, we sequentially monitored a real-world population of adults aged ≥50 years who received care in multiple US Vaccine Safety Datalink health systems to identify potentially increased risks of 10 prespecified health outcomes, including stroke, anaphylaxis, and Guillain-Barré syndrome (GBS). Among 647,833 RZV doses administered from January 2018 through December 2019, we did not detect a sustained increased risk of any monitored outcome for RZV recipients relative to either historical (2013-2017) recipients of zoster vaccine live, a live attenuated virus vaccine (Zostavax; Merck & Co., Inc., Kenilworth, New Jersey), or contemporary non-RZV vaccine recipients who had an annual well-person visit during the 2018-2019 study period. We confirmed prelicensure trial findings of increased risks of systemic and local reactions following RZV. Our study provides additional reassurance about the overall safety of RZV. Despite a large sample, uncertainty remains regarding potential associations with GBS due to the limited number of confirmed GBS cases that were observed.

Glucagon-Like Peptide 1 Receptor Agonists and Risk of Anaphylactic Reaction Among Patients With Type 2 Diabetes: A Multisite Population-Based Cohort Study

Case reports and a pharmacovigilance analysis have linked glucagon-like peptide 1 receptor agonists (GLP-1 RAs) with anaphylactic reactions, but real-world evidence for this possible association is lacking. Using databases from the United Kingdom (Clinical Practice Research Datalink) and the United States (Medicare, Optum (Optum, Inc., Eden Prairie, Minnesota), and IBM MarketScan (IBM, Armonk, New York)), we employed a new-user, active comparator study design wherein initiators of GLP-1 RAs were compared with 2 different active comparator groups (initiators of dipeptidyl peptidase 4 (DPP-4) inhibitors and initiators of sodium-glucose cotransporter 2 (SGLT-2) inhibitors) between 2007 and 2019. Propensity score fine stratification weighted Cox proportional hazards models were fitted to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for an anaphylactic reaction. Database-specific HRs were pooled using random-effects models. Compared with the use of DPP-4 inhibitors (n = 1,641,520), use of GLP-1 RAs (n = 324,098) generated a modest increase in the HR for anaphylactic reaction, with a wide 95% CI (36.9 per 100,000 person-years vs. 32.1 per 100,000 person-years, respectively; HR = 1.15, 95% CI: 0.94, 1.42). Compared with SGLT-2 inhibitors (n = 366,067), GLP-1 RAs (n = 259,929) were associated with a 38% increased risk of anaphylactic reaction (40.7 per 100,000 person-years vs. 29.4 per 100,000 person-years, respectively; HR = 1.38, 95% CI: 1.02, 1.87). In this large, multisite population-based cohort study, GLP-1 RAs were associated with a modestly increased risk of anaphylactic reaction when compared with DPP-4 inhibitors and SGLT-2 inhibitors.

Anaphylaxis among elderly emergency department patients in a large health system in New York

BACKGROUND

Anaphylaxis in the elderly is poorly understood.

OBJECTIVE

To elucidate demographic, clinical, and management characteristics of older adults presenting to emergency departments (EDs) with National Institute of Allergy and Infectious Diseases (NIAID) criteria-confirmed anaphylaxis vs milder, non-anaphylactic acute allergic reactions (AARs).

METHODS

A retrospective analysis of ED patients more than or equal to 65 years was conducted, using anaphylaxis International Classification of Diseases, Ninth Revision (ICD-9) codes or ICD-9-based algorithms incorporating the NIAID diagnostic criteria. Descriptive statistics were generated, and the abovementioned characteristics were compared between cohorts.

RESULTS

Of 164 eligible visits, 71 (43.3%), 90 (54.9%), and 3 (1.8%) cases were identified by ICD-9 codes, the algorithms, or both, respectively. Only half fulfilled NIAID diagnostic criteria. Compared with the non-anaphylactic AAR group, criteria-confirmed anaphylaxis group had lower drug allergy rates (43.9% vs 61.0%, P = .03) but higher food allergy rates (26.8% vs 12.2%, P = .02). For the criteria-confirmed anaphylaxis group, presenting signs and symptoms in descending frequency were mucocutaneous, respiratory, cardiovascular, and gastrointestinal. Criteria-confirmed anaphylaxis group had higher rates of prior anaphylaxis (13.4% vs 2.4%, P = .009), pre-ED (12.2% vs 0.0%, P = .001) or ED (72.0% vs 4.9%, P < .001) epinephrine administration, and allergy referral (17.1% vs 2.4%, P = .002). Tryptase levels were rarely ordered, occurring once in the criteria-confirmed anaphylaxis group and never in the non-anaphylactic AAR group. Despite low mortality (n = 1), 64.6% of the criteria-confirmed anaphylaxis cohort required hospitalization, with 23.2% admitted to intensive care unit.

CONCLUSION

Diagnosis of elderly ED patients with anaphylaxis remains suboptimal. Identifying NIAID criteria-confirmed cases remain challenging, using the existing methods. Management of these patients poorly adheres to current guidelines.

Risks for Anaphylaxis With Intravenous Iron Formulations : A Retrospective Cohort Study

BACKGROUND

The risks for anaphylaxis among intravenous (IV) iron products currently in use have not been assessed.

OBJECTIVE

To compare risks for anaphylaxis among 5 IV iron products that are used frequently.

DESIGN

Retrospective cohort study using a target trial emulation framework.

SETTING

Medicare fee-for-service data with Part D coverage between July 2013 and December 2018.

PARTICIPANTS

Older adults receiving their first administration of IV iron.

MEASUREMENTS

The primary outcome was the occurrence of anaphylaxis within 1 day of IV iron administration, ascertained using a validated case definition. Analysis was adjusted for 40 baseline covariates using inverse probability of treatment weighting. The adjusted incidence rates (IRs) for anaphylaxis per 10 000 first administrations and odds ratios (ORs) were computed.

RESULTS

The adjusted IRs for anaphylaxis per 10 000 first administrations were 9.8 cases (95% CI, 6.2 to 15.3 cases) for iron dextran, 4.0 cases (CI, 2.5 to 6.6 cases) for ferumoxytol, 1.5 cases (CI, 0.3 to 6.6 cases) for ferric gluconate, 1.2 cases (CI, 0.6 to 2.5 cases) for iron sucrose, and 0.8 cases (CI, 0.3 to 2.6 cases) for ferric carboxymaltose. Using iron sucrose as the referent category, the adjusted ORs for anaphylaxis were 8.3 (CI, 3.5 to 19.8) for iron dextran and 3.4 (CI, 1.4 to 8.3) for ferumoxytol. When cohort entry was restricted to the period after withdrawal of high-molecular-weight iron dextran from the U.S. market in 2014, the risk for anaphylaxis associated with low-molecular-weight iron dextran (OR, 8.4 [CI, 2.8 to 24.7]) did not change appreciably. Anaphylactic reactions requiring hospitalizations were observed only among patients using iron dextran or ferumoxytol.

LIMITATION

Generalizability to non-Medicare populations.

CONCLUSION

The rates of anaphylaxis were very low with all IV iron products but were 3- to 8-fold greater for iron dextran and ferumoxytol than for iron sucrose.

PRIMARY FUNDING SOURCE

None.

Validity of hospital ICD-10-GM codes to identify anaphylaxis

PURPOSE

Anaphylaxis (ANA) is an important adverse drug reaction. We examined positive predictive values (PPV) and other test characteristics of ICD-10-GM code algorithms for detecting ANA as used in a multinational safety study (PASS).

METHODS

We performed a cross-sectional study on routine data from a German academic hospital (2004-2019, age ≥ 18). Chart review was used for case verification. Potential cases were identified from the hospital administration system. The main outcome required at least one of the following: any type of specific in-hospital code (T78.2, T88.6, and T80.5) OR specific outpatient code in combination with a symptom code OR in-hospital non-specific code (T78.4, T88.7, and Y57.9) in combination with two symptom codes. PPV were calculated with 95% confidence interval. Sensitivity analyses modified type of codes, unit of analysis, verification criteria and time period. The most specific algorithm used only primary codes for ANA (numbers added in brackets).

RESULTS

Four hundred and sixteen eligible cases were evaluated, and 78 (37) potential ANA cases were identified. PPV were 62.8% (95% CI 51.1-73.5) (main) and 77.4% (58.9-90.4) (most specific). PPV from all modifications ranged from 12.9% to 80.6%. The sensitivity of the main algorithm was 66.2%, specificity 91.5%, and negative predictive value 92.6%. Corresponding figures for the most specific algorithm were 32.4%, 98.0%, and 87.0%.

CONCLUSIONS

The PPV of the main algorithm seems of acceptable validity for use in comparative safety research but will underestimate absolute risks by about a third. Restriction to primary discharge codes markedly improves PPV to the expense of reducing sensitivity.

ICD-10 anaphylaxis algorithm and the estimate of vaccine-attributable anaphylaxis incidence in Medicare

BACKGROUND

Anaphylaxis is a rare, serious allergic reaction. Its identification in large healthcare databases can help better characterize this risk.

OBJECTIVE

To create an ICD-10 anaphylaxis algorithm, estimate its positive predictive values (PPVs) in a post-vaccination risk window, and estimate vaccination-attributable anaphylaxis rates in the Medicare Fee For Service (FFS) population.

METHODS

An anaphylaxis algorithm with core and extended portions was constructed analyzing ICD-10 anaphylaxis claims data in Medicare FFS from 2015 to 2017. Cases of post-vaccination anaphylaxis among Medicare FFS beneficiaries were then identified from October 1, 2015 to February 28, 2019 utilizing vaccine relevant anaphylaxis ICD-10 codes. Information from medical records was used to determine true anaphylaxis cases based on the Brighton Collaboration's anaphylaxis case definition. PPVs were estimated for incident anaphylaxis and the subset of vaccine-attributable anaphylaxis within a 2-day post-vaccination risk window. Vaccine-attributable anaphylaxis rates in Medicare FFS were also estimated.

RESULTS

The study recorded 66,572,128 vaccinations among 21,685,119 unique Medicare FFS beneficiaries. The algorithm identified a total of 190 suspected anaphylaxis cases within the 2-day post-vaccination window; of these 117 (62%) satisfied the core algorithm, and 73 (38%) additional cases satisfied the extended algorithm. The core algorithm's PPV was 66% (95% CI [56%, 76%]) for identifying incident anaphylaxis and 44% (95% CI [34%, 56%]) for vaccine-attributable anaphylaxis. The vaccine-attributable anaphylaxis incidence rate after any vaccination was 0.88 per million doses (95% CI [0.67, 1.16]).

CONCLUSION

The ICD-10 claims algorithm for anaphylaxis allows the assessment of anaphylaxis risk in real-world data. The algorithm revealed vaccine-attributable anaphylaxis is rare among vaccinated Medicare FFS beneficiaries.

Use of intravenous iron and risk of anaphylaxis: A multinational observational post-authorisation safety study in Europe

PURPOSE

This post-authorisation safety study estimated the risk of anaphylaxis in patients receiving intravenous (IV) iron in Europe, with interest in iron dextran and iron non-dextrans. Studies conducted in the United States have reported risk of anaphylaxis to IV iron ranging from 2.0 to 6.8 per 10 000 first treatments.

METHODS

Cohort study of IV iron new users, captured mostly through pharmacy ambulatory dispensing, from populations covered by health and administrative data sources in five European countries from 1999 to 2017. Anaphylaxis events were identified through an algorithm that used parenteral penicillin as a positive control.

RESULTS

A total of 304 210 patients with a first IV iron treatment (6367 iron dextran), among whom 13-16 anaphylaxis cases were identified and reported as a range to comply with data protection regulations. The pooled unadjusted incidence proportion (IP) ranged from 0.4 (95% confidence interval [CI], 0.2-0.9) to 0.5 (95% CI, 0.3-1.0) per 10 000 first treatments. No events were identified at first dextran treatments. There were 231 294 first penicillin treatments with 30 potential cases of anaphylaxis (IP = 1.2; 95% CI, 0.8-1.7 per 10 000 treatments).

CONCLUSION

We found an IP of anaphylaxis from 0.4 to 0.5 per 10 000 first IV iron treatments. The study captured only a fraction of IV iron treatments administered in hospitals, where most first treatments are likely to happen. Due to this limitation, the study could not exclude a differential risk of anaphylaxis between iron dextran and iron non-dextrans. The IP of anaphylaxis in users of penicillin was consistent with incidences reported in the literature.

Identification and Validation of Anaphylaxis Using Electronic Health Data in a Population-based Setting

BACKGROUND

Anaphylaxis is a life-threatening allergic reaction that is difficult to identify accurately with administrative data. We conducted a population-based validation study to assess the accuracy of ICD-10 diagnosis codes for anaphylaxis in outpatient, emergency department, and inpatient settings.

METHODS

In an integrated healthcare system in Washington State, we obtained medical records from healthcare encounters with anaphylaxis diagnosis codes (potential events) from October 2015 to December 2018. To capture events missed by anaphylaxis diagnosis codes, we also obtained records on a sample of serious allergic and drug reactions. Two physicians determined whether potential events met established clinical criteria for anaphylaxis (validated events).

RESULTS

Out of 239 potential events with anaphylaxis diagnosis codes, the overall positive predictive value (PPV) for validated events was 64% (95% CI = 58 to 70). The PPV decreased with increasing age. Common precipitants for anaphylaxis were food (39%), medications (35%), and insect bite or sting (12%). The sensitivity of emergency department and inpatient anaphylaxis diagnosis codes for all validated events was 58% (95% CI = 51 to 65), but sensitivity increased to 95% (95% CI = 74 to 99) when outpatient diagnosis codes were included. Using information from all validated events and sampling weights, the incidence rate for anaphylaxis was 3.6 events per 10,000 person-years (95% CI = 3.1 to 4.0).

CONCLUSIONS

In this population-based setting, ICD-10 diagnosis codes for anaphylaxis from emergency department and inpatient settings had moderate PPV and sensitivity for validated events. These findings have implications for epidemiologic studies that seek to estimate risks of anaphylaxis using electronic health data.

Development and validation of a predictive model algorithm to identify anaphylaxis in adults with type 2 diabetes in U.S. administrative claims data

PURPOSE

To use medical record adjudication and predictive modeling methods to develop and validate an algorithm to identify anaphylaxis among adults with type 2 diabetes (T2D) in administrative claims.

METHODS

A conventional screening algorithm that prioritized sensitivity to identify potential anaphylaxis cases was developed and consisted of diagnosis codes for anaphylaxis or relevant signs and symptoms. This algorithm was applied to adults with T2D in the HealthCore Integrated Research Database (HIRD) from 2016 to 2018. Clinical experts adjudicated anaphylaxis case status from redacted medical records. We used confirmed case status as an outcome for predictive models developed using lasso regression with 10-fold cross-validation to identify predictors and estimate the probability of confirmed anaphylaxis.

RESULTS

Clinical adjudicators reviewed medical records with sufficient information from 272 adults identified by the anaphylaxis screening algorithm, which had an estimated Positive Predictive Value (PPV) of 65% (95% confidence interval [CI]: 60%-71%). The predictive model algorithm had a c-statistic of 0.95. The model's probability threshold of 0.60 excluded 89% (84/94) of false positives identified by the screening algorithm, with a PPV of 94% (95% CI: 91%-98%). The model excluded very few true positives (15 of 178), and identified 92% (95% CI: 87%-96%) of the cases selected by the screening algorithm.

CONCLUSIONS

Predictive modeling techniques yielded an accurate algorithm with high PPV and sensitivity for identifying anaphylaxis in administrative claims. This algorithm could be considered in future safety studies using similar claims data to reduce potential outcome misclassification.

Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM

PURPOSE

Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data.

METHODS

We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated.

RESULTS

We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL.

CONCLUSIONS

Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

Trends in Emergency Department Visits and Hospitalizations for Acute Allergic Reactions and Anaphylaxis Among US Older Adults: 2006-2014

BACKGROUND

The US older adult population (age ≥65 years) is increasing and may be at increased risk for severe anaphylaxis. Little is known about the health care use for acute allergic reactions (AAR), including anaphylaxis, among older adults.

OBJECTIVE

To characterize trends in emergency department (ED) visits and hospitalizations for AAR and anaphylaxis among US older adults from 2006 to 2014 and examine factors associated with severe anaphylaxis.

METHODS

We performed cross-sectional analyses of trends in ED visits and hospitalizations among older adults using data from the Nationwide Emergency Department Sample and the National (Nationwide) Inpatient Sample in 2006 to 2014. We used International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes to identify visits for AAR, including anaphylaxis. Multivariable logistic regression modeling was used to identify factors associated with severe anaphylaxis (cardiac arrest, intubation, and death).

RESULTS

In 2006 to 2014, older adults experienced approximately 1,019,967 AAR-related ED visits, 173,844 AAR-related hospitalizations, 93,795 anaphylaxis-related ED visits, and 72,677 anaphylaxis-related hospitalizations. Whereas AAR-related ED visit and hospitalization rates remained stable (P = .28 and .16, respectively), anaphylaxis-related ED visit and hospitalization rates increased significantly over time (37 visits/100,000 in 2006 to 51 in 2014, P < .001; and from 13 hospitalizations/100,000 in 2006 to 23 in 2014, P < .001), especially hospitalization rates for drug-related anaphylaxis (47 hospitalizations/100,000 in 2006 to 85 in 2014; P < .001). Risk factors for anaphylaxis-related death included older age and drug-related trigger.

CONCLUSIONS

In a nationally representative sample of US older adults, the rate of anaphylaxis-related ED visits and hospitalizations increased over time. Drug-related triggers represented a substantial portion of increased health care use and are a growing risk in this vulnerable population.

Examining the effects of pre-pregnancy weight and gestational weight gain on allergic disease development in offspring: a protocol for a population-based study using health administrative databases in Ontario, Canada

INTRODUCTION

Over the last 20 years, excess maternal pre-pregnancy weight (overweight and obesity) and gestational weight gain have become the most common morbidities in pregnancy. These morbidities may pose a threat to fetal immunological development through associated metabolic dysfunction and inflammation and, as such, may partly explain the concurrent rise of paediatric allergic disease. We will examine the effect of maternal pre-pregnancy weight and gestational weight gain during pregnancy on the incidence of allergic diseases among offspring in Canada's most populous province.

METHODS AND ANALYSIS

We will conduct a retrospective, population-based cohort study of all singleton live births to residents of Ontario, Canada in 2012-2013 and 2013-2014. The study population will be defined using maternal-newborn records from the provincial birth registry, which captures information on maternal pre-pregnancy weight and gestational weight gain. The cohort will be linked with provincial health administrative databases, allowing for follow-up of neonates through early childhood until 2019 (5-7 years of age). Allergic disease development (asthma, rhinitis, atopic dermatitis and anaphylaxis) will be ascertained using diagnostic codes from healthcare encounters. Potential confounders have been identified a priori through a directed acyclic graph. Cox proportional hazards regression models will be employed to assess the associations between maternal pre-pregnancy weight, gestational weight gain and incident paediatric allergic disease. Several preplanned sensitivity analyses will be conducted, including a probabilistic bias analysis of outcome misclassification.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Research Ethics Board of the Children's Hospital of Eastern Ontario and the ICES Privacy Office. Findings will be disseminated in scientific conference presentations and peer-reviewed publications.

Real-world patterns of pegloticase use for treatment of gout: descriptive multidatabase cohort study

OBJECTIVE

Pegloticase is used in severe refractory gout or in cases of intolerance to other urate-lowering therapies. We sought to evaluate the patterns of pegloticase use in the USA and the incidence of safety outcomes.

METHODS

We conducted a retrospective descriptive study using data from two US commercial insurance claims databases (2010-2018). We identified new initiators of pegloticase with ≥1 gout diagnosis code in the 365-day baseline period prior to pegloticase initiation. We measured the number and duration of pegloticase infusions. We assessed the risk of anaphylaxis or anaphylactoid reactions, cardiovascular events, including myocardial infarction or stroke, and hospitalisation for heart failure (new onset or exacerbations) while undergoing pegloticase therapy.

RESULTS

Among 2.9 million patients with ≥1 diagnosis of gout, we identified only 483 (179 in Optum and 304 in MarketScan) pegloticase initiators. The mean age and % female was 55.6 years, 10.9% for MarketScan and 60.6 years and 17.3% for Optum. Hypertension was present in up to 85%, diabetes mellitus in 38%, chronic kidney disease in 46% and heart failure in 21% of the patients. The median number of infusions was four and the duration of therapy was 3 months. During the mean 0.5-year follow-up time on pegloticase, there were 3 (0.6%) anaphylaxis, 7 (1.4%) composite cardiovascular, 31 (6.4%) heart failure hospitalisations and 3 (0.6%) deaths.

CONCLUSION

Pegloticase is rarely used in gout, and the median duration of pegloticase therapy was 3 months. There were few anaphylaxis events captured in this claims-based study, while heart failure hospitalisations were common.

Incidence of and risk factors for perioperative or periprocedural anaphylaxis in the United States from 2005 to 2014

BACKGROUND

The estimated worldwide incidence of perioperative or periprocedural anaphylaxis (PA) is between 1 in 1250 and 1 in 20,000 procedures.

OBJECTIVE

To evaluate the incidence of PA in the United States and compare patient characteristics and underlying risk factors using a large national database.

METHODS

Using deidentified data from the nationwide inpatient sample from 2005 to 2014, we identified cases of PA through the International Classification of Diseases, Ninth Revision, Clinical Modification codes and conducted a retrospective analysis.

RESULTS

Among 35,647,347 surgeries and procedures, there were 5458 (0.015%) PA cases identified. The incidence of PA was 15.3 cases per 100,000 procedures. When compared with controls, PA cases had an increased mortality (3.4% vs 1.4%; P < .001), median length of stay (5 vs 3 days; P < .001), and median hospital cost ($45,155 vs $24,734; P < .001). The age group between 18 and 34 years (odds ratio [OR], 1.34; 95% confidence interval [CI], 1.13-1.58; P < .001) and female sex (OR, 1.40; 95% CI, 1.31-1.49; P < .001) were associated with increased odds of PA. Transplant (OR, 3.35; 95% CI, 2.59-4.34; P < .001), hematologic (OR, 1.63; 95% CI, 1.30-2.05; P < .001), vascular (OR, 1.49; 95% CI, 1.30-1.67; P < .001), and cardiac (OR, 1.47; 95% CI, 1.30-1.67; P < .001) procedures were at increased risk for PA. Several comorbidities were associated with PA including chronic pulmonary disease (OR, 1.41; 95% CI, 1.31-1.51; P < .001).

CONCLUSION

The incidence of PA is 1 in 6531 procedures, with a mortality of 1 in 191,652 procedures. PA has worsening outcomes compared with controls. The risk factors of PA include age, sex, procedure type, and comorbidities.

A Comprehensive Methodology to Systematically Identify Drug Hypersensitivity and Anaphylactic Reactions in Clinical Trial Databases

BACKGROUND

The incidence of drug hypersensitivity or anaphylactic reactions in clinical trial databases is thought to be underestimated due to variable clinical presentations and lack of clear definitions.

OBJECTIVE

Our objective was to develop a more comprehensive, systematic methodology for retrospectively identifying potential hypersensitivity or anaphylactic reactions reported in patients treated with investigational drugs in clinical trials and to accurately assess and characterise the risk.

METHODS

A three-step approach was developed to identify hypersensitivity or anaphylactic reactions: clinical trial database search, medical review, and adjudication to confirm or rule out cases. The database search strategy consisted of the narrow search for Standardized MedDRA Query (SMQ) Hypersensitivity, a modified MedDRA query based on SMQ Anaphylactic reaction, and pyrexia-related MedDRA Preferred Terms. The cases identified from the search were further medically reviewed taking into consideration the temporal relationship, seriousness, severity, course, and management of the events, action taken, and outcomes of adverse events. Those cases deemed to have potentially drug-related hypersensitivity were then adjudicated to be confirmed or ruled out.

RESULTS

The method was applied to a clinical trial database containing safety data for 421 patients treated with an investigational drug. Application of the methodology led to 19 hypersensitivity cases being identified. Of these, 12 were classified as immediate reactions and 7 as non-immediate reactions.

CONCLUSION

This three-step method provided a thorough and robust way to identify hypersensitivity reactions, including anaphylaxis, in a clinical trial database. This method could be applied to investigational drugs to improve early detection and monitoring of potential safety concerns, subsequent patient safety management strategies, and potentially programme-wide drug development decisions. Algorithmic tools and narrow and/or broad SMQs should be considered when evaluating safety concerns. The authors also recommend a revision of the MedDRA SMQ of Anaphylactic reaction.

New York State cases of anaphylaxis in elderly patients from 2000 to 2010

BACKGROUND

Limited information is available on the effect of anaphylaxis, a severe, potentially life-threatening allergic reaction, in the elderly population.

OBJECTIVE

To elucidate the frequency of anaphylaxis and the demographic characteristics of elderly patients admitted to New York hospitals from 2000 to 2010.

METHODS

A retrospective analysis of hospitalized patients aged 65 years and older in New York from 2000 to 2010 was conducted using the Statewide Planning and Research Cooperative System, a statewide administrative database. Cases were identified using anaphylaxis International Classification of Diseases, Ninth Revision (ICD-9) codes or an ICD-9-based diagnostic algorithm incorporating the National Institutes of Allergy and Infectious Disease diagnostic criteria. The χ² test was used to measure the association between demographic characteristics and group membership. Regression was used to model group and age as a function of hospital rates.

RESULTS

A total of 3673 hospitalizations were analyzed. Anaphylaxis ICD-9 codes identified 1790 cases (48.7%), the algorithms identified 1701 cases (46.3.%), and 182 cases (5.0%) were identified by both. Hospitalization rates increased significantly during this period (P < .001). Women comprised 61.5% and people of white race comprised 69.8% of the sample. Distribution by age differed by ascertainment method (ICD-9 vs algorithm) among the early-old group (65-74 years of age; 53.8% vs 41.8%) and among the late-old group (≥85 years of age; 11.2% vs 19.3%).

CONCLUSION

Hospitalization rates and anaphylaxis cases increased during the study period among the hospitalized elderly population of New York. Relying on anaphylaxis ICD-9 codes alone missed approximately half of possible cases. The identification and possibly the effect of anaphylaxis among the elderly population may differ, depending on age, race, payer, New York County, and disposition.

Evaluation of Use of Technologies to Facilitate Medical Chart Review

INTRODUCTION

While medical chart review remains the gold standard to validate health conditions or events identified in administrative claims and electronic health record databases, it is time consuming, expensive and can involve subjective decisions.

AIM

The aim of this study was to describe the landscape of technology-enhanced approaches that could be used to facilitate medical chart review within and across distributed data networks.

METHOD

We conducted a semi-structured survey regarding processes for medical chart review with organizations that either routinely do medical chart review or use technologies that could facilitate chart review.

RESULTS

Fifteen out of 17 interviewed organizations used optical character recognition (OCR) or natural language processing (NLP) in their chart review process. None used handwriting recognition software. While these organizations found OCR and NLP to be useful for expediting extraction of useful information from medical charts, they also mentioned several challenges. Quality of medical scans can be variable, interfering with the accuracy of OCR. Additionally, linguistic complexity in medical notes and heterogeneity in reporting templates used by different healthcare systems can reduce the transportability of NLP-based algorithms to diverse healthcare settings.

CONCLUSION

New technologies including OCR and NLP are currently in use by various organizations involved in medical chart review. While technology-enhanced approaches could scale up capacity to validate key variables and make information about important clinical variables from medical records more generally available for research purposes, they often require considerable customization when employed in a distributed data environment with multiple, diverse healthcare settings.

Identifying monoclonal gammopathy of undetermined significance in electronic health data

PURPOSE

Monoclonal gammopathy of undetermined significance (MGUS) is a prevalent yet largely asymptomatic precursor to multiple myeloma. Patients with MGUS must undergo regular surveillance and testing, with few known predictors of progression. We developed an algorithm to identify MGUS patients in electronic health data to facilitate large-scale, population-based studies of this premalignant condition.

METHODS

We developed a four-step algorithm using electronic health record and health claims data from men and women aged 50 years or older receiving care from a large, multispecialty medical group between 2007 and 2015. The case definition required patients to have at least two MGUS ICD-9 diagnosis codes within 12 months, at least one serum and/or urine protein electrophoresis and one immunofixation test, and at least one in-office hematology/oncology visit. Medical charts for selected cases were abstracted then adjudicated independently by two physicians. We assessed algorithm validity by positive predictive value (PPV).

RESULTS

We identified 833 people with at least two MGUS diagnosis codes; 429 (52%) met all four algorithm criteria. We randomly selected 252 charts for review, including 206 from patients meeting all four algorithm criteria. The PPV for the 206 algorithm-identified charts was 76% (95% CI, 70%-82%). Among the 49 cases deemed to be false positives (24%), 33 were judged to have multiple myeloma or another lymphoproliferative condition, such as lymphoma.

CONCLUSIONS

We developed a simple algorithm that identified MGUS cases in electronic health data with reasonable accuracy. Inclusion of additional steps to eliminate cases with malignant disease may improve algorithm performance.

Capturing anaphylaxis through medical records: Are ICD and CPT codes sufficient?

OBJECTIVE

The identification of anaphylaxis cases is imperative for optimal clinicalprovider knowledge deficiencies in diagnosis and treatment and the efficacy of reimbursement codes, such as International Classification of Diseases (ICD) and current procedural terminology (CPT) codes, in detecting anaphylaxis.

DATA SOURCES

Pubmed.

STUDY SELECTIONS

Recent and clinically relevant literature on anaphylaxis and provider knowledge, ICD, CPT, Healthcare Common Procedural Coding System (HCPCS), and E-codes were selected and reviewed.

RESULTS

Reimbursement codes are used to detect anaphylaxis in administrative claims databases. Inaccurate recognition of the diagnosis by providers, underreporting, and cause identification are challenges faced by health researchers using reimbursement codes for anaphylaxis case identification. Anaphylactic shock-specific ICD codes were noted to have a positive predictive value (PPV) of 52% to 53% of anaphylaxis events compared with physician chart review, which was improved to 63% to 67.3% when used in conjunction with anaphylaxis symptom-specific ICD, CPT, HCPCS, and E-codes 31, 34, and 35.

CONCLUSION

Education of providers to properly diagnose and treat anaphylaxis requires systematic and educational investments. The ICD codes specific to anaphylactic shock have suboptimal PPV to identify anaphylaxis in administrative claims databases. Use of algorithms incorporating other reimbursement codes improve the PPV, but they are limited by inaccurate diagnoses and underreporting of anaphylaxis. Future ICD-11 reclassification may improve anaphylaxis detection by reimbursement codes.

Methodologic considerations for noninterventional studies of switching from reference biologic to biosimilars

PURPOSE

As more biosimilars become available in the United States, postapproval noninterventional studies describing biosimilar switching and comparing effectiveness and/or safety between switchers and nonswitchers will play a key role in generating real-world evidence to inform clinical practices and policy decisions. Ensuring sound methodology is critical for making valid inferences from these studies.

METHODS

The Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) convened a workgroup consisting of academic researchers, industry scientists, and practicing clinicians to establish best practice recommendations for the conduct of noninterventional studies of biosimilar and reference biologic switching. The workgroup members participated in eight teleconferences between August 2017 and February 2018 to discuss specific topics and build consensus.

RESULTS

This report provides workgroup recommendations covering five main considerations relating to noninterventional studies describing reference biologic to biosimilar switching and comparing reference biologic to biosimilars for safety and effectiveness in the presence of switching at treatment initiation and during follow-up: (a) selecting appropriate data sources from a range of available options including insurance claims, electronic health records, and registries; (b) study designs; (c) outcomes of interest including health care utilization and clinical endpoints; (d) analytic approaches including propensity scores, disease risk scores, and instrumental variables; and (e) special considerations including avoiding designs that ignore history of biologic use, avoiding immortal time bias, exposure misclassification, and accounting for postindex switching.

CONCLUSION

Recommendations provided in this report provide a framework that may be helpful in designing and critically evaluating postapproval noninterventional studies involving reference biologic to biosimilar switching.

Anaphylaxis in Pregnancy in the United States: Risk Factors and Temporal Trends Using National Routinely Collected Data

Background

Anaphylaxis in pregnancy is an understudied, rare, and severe complication of pregnancy.

Objective

To describe the incidence and temporal trends, and to identify potential risk factors for anaphylaxis-related hospitalizations while pregnant in the United States.

Methods

All hospitalizations while pregnant and any anaphylactic reactions were identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes from the National Inpatient Sample, United States, over the period 2004 to 2014. Annual incidence rates of anaphylaxis during pregnancy were calculated. Logistic regression models assessed risk factors for anaphylaxis during pregnancy, presented as odds ratios (ORs) and 95% CIs.

Results

During the period 2004 to 2014, the incidence of anaphylaxis during pregnancy was 3.8 (95% CI, 3.4-4.2) per 100,000 hospitalizations while pregnant. The incidence did not statistically differ during the period 2004 to 2014. After adjustment, there were 3 factors that increased the odds of anaphylaxis during pregnancy: cesarean delivery (adjusted OR [aOR], 4.19; 95% CI, 3.28-5.35) compared with noncesarean delivery; history of an allergic reaction (aOR, 4.05; 95% CI, 2.64-6.23) compared with no history; and a black race (aOR, 1.57; 95% CI, 1.15-2.15) and other race (aOR, 1.69; 95% CI, 1.08-2.63) compared with white race.

Conclusions

Despite increased rates of cesarean delivery in the United States and consequent drug administration, there was no evidence of an increasing trend in anaphylaxis. Cesarean delivery and history of an allergic reaction allow the identification of women at risk of anaphylaxis. Not all women had clear risk factors, and preparations should always be in place to ensure timely management if this uncommon event occurs.

Validity of Privacy-Protecting Analytical Methods That Use Only Aggregate-Level Information to Conduct Multivariable-Adjusted Analysis in Distributed Data Networks

Distributed data networks enable large-scale epidemiologic studies, but protecting privacy while adequately adjusting for a large number of covariates continues to pose methodological challenges. Using 2 empirical examples within a 3-site distributed data network, we tested combinations of 3 aggregate-level data-sharing approaches (risk-set, summary-table, and effect-estimate), 4 confounding adjustment methods (matching, stratification, inverse probability weighting, and matching weighting), and 2 summary scores (propensity score and disease risk score) for binary and time-to-event outcomes. We assessed the performance of combinations of these data-sharing and adjustment methods by comparing their results with results from the corresponding pooled individual-level data analysis (reference analysis). For both types of outcomes, the method combinations examined yielded results identical or comparable to the reference results in most scenarios. Within each data-sharing approach, comparability between aggregate- and individual-level data analysis depended on adjustment method; for example, risk-set data-sharing with matched or stratified analysis of summary scores produced identical results, while weighted analysis showed some discrepancies. Across the adjustment methods examined, risk-set data-sharing generally performed better, while summary-table and effect-estimate data-sharing more often produced discrepancies in settings with rare outcomes and small sample sizes. Valid multivariable-adjusted analysis can be performed in distributed data networks without sharing of individual-level data.

Identifying Patients With Relapsing-Remitting Multiple Sclerosis Using Algorithms Applied to US Integrated Delivery Network Healthcare Data

BACKGROUND

Relapsing-remitting multiple sclerosis (RRMS) has a major impact on affected patients; therefore, improved understanding of RRMS is important, particularly in the context of real-world evidence.

OBJECTIVES

To develop and validate algorithms for identifying patients with RRMS in both unstructured clinical notes found in electronic health records (EHRs) and structured/coded health care claims data.

METHODS

US Integrated Delivery Network data (2010-2014) were queried for study inclusion criteria (possible multiple sclerosis [MS] base cohort): one or more MS diagnosis code, patients aged 18 years or older, 1 year or more baseline history, and no other demyelinating diseases. Sets of algorithms were developed to search narrative text of unstructured clinical notes (EHR clinical notes-based algorithms) and structured/coded data (claims-based algorithms) to identify adult patients with RRMS, excluding patients with evidence of progressive MS. Medical records were reviewed manually for algorithm validation. Positive predictive value was calculated for both EHR clinical notes-based and claims-based algorithms.

RESULTS

From a sample of 5308 patients with possible MS, 837 patients with RRMS were identified using only the EHR clinical notes-based algorithms and 2271 patients were identified using only the claims-based algorithms; 779 patients were identified using both algorithms. The positive predictive value was 99.1% (95% confidence interval [CI], 94.2%-100%) for the EHR clinical notes-based algorithms and 94.6% (95% CI, 89.1%-97.8%) to 94.9% (95% CI, 89.8%-97.9%) for the claims-based algorithms.

CONCLUSIONS

The algorithms evaluated in this study identified a real-world cohort of patients with RRMS without evidence of progressive MS that can be studied in clinical research with confidence.

Use of epinephrine in emergency department depends on anaphylaxis severity in children

Despite multiple recommendations, intramuscular epinephrine is poorly prescribed in emergency department receiving pediatric anaphylaxis. To evaluate the role of severity symptoms on this use, we included all admissions for a diagnosis linked to possible allergy in the two pediatric emergency departments of our institution between January 2010 and December 2015. Selection and analysis were restricted to children under 18 years fulfilling Sampson's criteria for anaphylaxis. We retrospectively ranked these admissions with the Ring and Messmer anaphylaxis severity score and compared the use of epinephrine according to this classification. Among 422,483 admissions, 204 (0.05%) fulfilled the anaphylaxis criteria (170 (83.3%) grade II anaphylaxis, and 34 (16.7%) grade III; mean age 7.9 years). Previous allergy, anaphylaxis, and asthma were found in respectively 60.8%, 36.8%, and 35.1%. Food allergy was the main suspected causal trigger. Epinephrine was used in 32.7% (n = 65/199), before admission (11.4% (n = 23/201)) or in the emergency department (22.2% (n = 45/202)). Epinephrine was more frequently prescribed in grade III than in grade II anaphylaxis (84.8% vs 22.3%, p < 0.001; OR = 19.05 [7.05-54.10]). Upon discharge, epinephrine auto-injectors prescription and allergy referral were rare (31.7% and 44.2%).Conclusion: Pediatricians intuitively adapt their epinephrine use to the severity of the anaphylaxis and contribute to epinephrine underuse in pediatric anaphylaxis. What is known: • Intramuscular epinephrine is the recommended treatment for pediatric anaphylaxis. However, most of the European and North-American studies show a low prescription rate of epinephrine in both prehospital and pediatric emergency department management. • Reasons for such a low prescription rate are unknown. What is new: • This study confirms that intramuscular epinephrine is poorly prescribed in pediatric anaphylaxis (about one case among 10 before admission and one among 5 in pediatric emergency departments). • Despite recommendations, pediatricians intuitively adapt their prescription to the clinical severity of anaphylaxis, with a fourfold increase prescription in grade III compared to grade II anaphylaxis. This medical behavior ascertainment may be in part explained by the delay between the ED admission/management and the anaphylactic episode onset.

Epidemiologic patterns of in-hospital anaphylaxis in pediatric surgical patients

The incidence of in-hospital anaphylaxis in pediatric surgical patients has more than doubled between 2003 and 2012. Patients with hematological and myeloproliferative disorders, particularly when admitted for bone marrow transplant, are at especially heightened risk.

Identification of perioperative pulmonary aspiration in children using quality assurance and hospital administrative billing data

BACKGROUND

Perioperative aspiration is a rare but potentially devastating complication, occurring in 1-10 per 10 000 anesthetics based on studies of quality assurance databases. Quality assurance reporting is known to underestimate the incidence of adverse outcomes, but few large studies use supplementary data sources. This study aims to identify the incidence of and risk factors for perioperative aspiration in children using quality assurance data supplemented by administrative billing records, and to examine the utility of billing data as a supplementary data source.

METHODS

Aspiration events for children receiving anesthesia at a tertiary care pediatric hospital between 2008 and 2014 were identified using (i) a perioperative quality assurance database and (ii) hospital administrative billing records with International Classification of Diseases, Ninth Revision Clinical Modification coded diagnoses of aspiration. Records were subject to review by pediatric anesthesiologists. Following identification of all aspiration events, the incidence of perioperative aspiration was calculated and risk factors were assessed.

RESULTS

47 272 anesthetic cases were evaluated over 7 years. The quality assurance database identified 20 cases of perioperative aspiration occurring in surgical inpatients, same-day admissions, and outpatients. Using hospital administrative data (which excludes outpatients with shorter than a 24-hour stay), 9 cases of perioperative aspiration were identified of which 6 had not been found through quality assurance data. Overall, International Classification of Diseases, Ninth Revision coding demonstrated a positive predictive value of 94.5% for any aspiration event; however, positive predictive value was <4% for perioperative aspiration. A total incidence of 5.5 perioperative aspirations per 10 000 (95% CI: 3.7-8.0 per 10 000) anesthetics was found.

CONCLUSION

Quality assurance data offer an efficient way to measure the incidence of rare events, but may underestimate perioperative complications. International Classification of Diseases, Ninth Revision codes for aspiration used as a secondary data source were nonspecific for perioperative aspiration, but when combined with record review yielded a 30% increase in identified cases of aspiration over quality assurance data alone. The use of administrative data therefore holds potential for supplementing quality assurance studies of rare complications.

Development and validation of an algorithm to identify drug-induced anaphylaxis in the Beijing Pharmacovigilance Database

Background Pharmacovigilance databases are utilized to identify serious adverse drug events (ADEs). In China, very few studies have evaluated the validity of using pharmacovigilance databases to identify drug-induced anaphylaxis (DIA). Objective We aimed to develop and validate an algorithm to identify DIA using the Beijing Pharmacovigilance Database (BPD). Setting ADEs from the BPD mainly spontaneously reported from 94 hospitals in Beijing, China. Method Using the diagnoses, we developed an algorithm to identify potential DIAs from the BPD between January 2004 and December 2014. A sample of 500 patients was randomly selected for chart abstraction. Two physician adjudicators assessed whether DIA occurred using the published clinical criteria as the gold standard. Main outcome measure Positive predictive values (PPVs) and 95% confidence intervals of the algorithm and algorithm criteria components were calculated. Results 500 patients (53.2% female; the mean age 48.2 years) with potential DIA were selected using the algorithm. 444 were adjudicated as having anaphylaxis by physicians. The PPV of the overall algorithm was 88.8% (95% CI 86.0-91.6%). PPV for the algorithm only using specific diagnoses of "anaphylactic shock", "anaphylactic reaction", and "anaphylactoid reaction [severe]" was 89.6% (95% CI 86.6-92.4%); this partial algorithm identified 387 (87.2%) DIAs. The diagnosis that identified the most DIAs (83.8%) was "anaphylactic shock", with a PPV of 91.6% (95% CI 88.9-94.3%). Conclusion The overall algorithm identified a greater number of DIAs than the algorithm that only used specific diagnoses; however, its PPV was slightly lower. We were able to identify DIAs with the algorithm we developed.

Risk of Hypersensitivity to Biologic Agents Among Medicare Patients With Rheumatoid Arthritis

BACKGROUND

Hypersensitivity reactions (HSRs) can occur with any of the available biologic agents used to treat rheumatoid arthritis (RA). We compared drug-specific risks for HSRs among RA patients enrolled in the US Medicare program.

METHODS

Using Medicare data, we identified new users of infused infliximab, abatacept, rituximab, tocilizumab, golimumab, and injected biologic agents. After identifying HSRs using validated algorithms, for each biologic agent, we calculated the cumulative incidence over 6 months and the incidence rates (IRs) in 0-1, 2-14, and 15-30 days of administration. For each biologic agent administration, followup started on the infusion/injection date and ended at HSR, subsequent biologic agent administration, death, coverage loss, 30-day followup, or December 31, 2013, whichever occurred first. Adjusted robust Poisson regression was used to compare the HSR risks across biologic agents. A sensitivity analysis was conducted using a nested case-crossover design.

RESULTS

We identified 725,591 biologic agent administrations and 248 HSRs among 80,587 new users of biologic agents. Of these, 26.9% occurred in users of intravenous abatacept, 4.6% in rituximab, 5.8% in intravenous tocilizumab, 22.9% in infliximab, and 39.7% in injectable anti-tumor necrosis factor inhibitors (anti-TNFi). The cumulative incidence of HSRs over 6 months for all biologic agents was low (<1%).The IRs for HSRs ranged from 2.4 (abatacept) to 239.5 (rituximab) per 10⁶ person-days. After adjustment, and using injectable anti-TNFi over 0-30 days as the referent, rituximab, infliximab, abatacept, and tocilizumab infusions were associated with a statistically significant higher risk of HSR. The sensitivity analysis yielded similar results.

CONCLUSION

Among RA patients taking biologic agents, rituximab and infliximab were most strongly associated with HSRs. The absolute IRs of HSR events for all biologic agent exposures were low.

Single-reviewer electronic phenotyping validation in operational settings: Comparison of strategies and recommendations

OBJECTIVE

Develop evidence-based recommendations for single-reviewer validation of electronic phenotyping results in operational settings.

MATERIAL AND METHODS

We conducted a randomized controlled study to evaluate whether electronic phenotyping results should be used to support manual chart review during single-reviewer electronic phenotyping validation (N=3104). We evaluated the accuracy, duration and cost of manual chart review with and without the availability of electronic phenotyping results, including relevant patient-specific details. The cost of identification of an erroneous electronic phenotyping result was calculated based on the personnel time required for the initial chart review and subsequent adjudication of discrepancies between manual chart review results and electronic phenotype determinations.

RESULTS

Providing electronic phenotyping results (vs not providing those results) was associated with improved overall accuracy of manual chart review (98.90% vs 92.46%, p<0.001), decreased review duration per test case (62.43 vs 76.78s, p<0.001), and insignificantly reduced estimated marginal costs of identification of an erroneous electronic phenotyping result ($48.54 vs $63.56, p=0.16). The agreement between chart review and electronic phenotyping results was higher when the phenotyping results were provided (Cohen's kappa 0.98 vs 0.88, p<0.001). As a result, while accuracy improved when initial electronic phenotyping results were correct (99.74% vs 92.67%, N=3049, p<0.001), there was a trend towards decreased accuracy when initial electronic phenotyping results were erroneous (56.67% vs 80.00%, N=55, p=0.07). Electronic phenotyping results provided the greatest benefit for the accurate identification of rare exclusion criteria.

DISCUSSION

Single-reviewer chart review of electronic phenotyping can be conducted more accurately, quickly, and at lower cost when supported by electronic phenotyping results. However, human reviewers tend to agree with electronic phenotyping results even when those results are wrong. Thus, the value of providing electronic phenotyping results depends on the accuracy of the underlying electronic phenotyping algorithm.

CONCLUSION

We recommend using a mix of phenotyping validation strategies, with the balance of strategies based on the anticipated electronic phenotyping error rate, the tolerance for missed electronic phenotyping errors, as well as the expertise, cost, and availability of personnel involved in chart review and discrepancy adjudication.

Distributed data networks: a blueprint for Big Data sharing and healthcare analytics

This paper defines the attributes of distributed data networks and outlines the data and analytic infrastructure needed to build and maintain a successful network. We use examples from one successful implementation of a large-scale, multisite, healthcare-related distributed data network, the U.S. Food and Drug Administration-sponsored Sentinel Initiative. Analytic infrastructure-development concepts are discussed from the perspective of promoting six pillars of analytic infrastructure: consistency, reusability, flexibility, scalability, transparency, and reproducibility. This paper also introduces one use case for machine learning algorithm development to fully utilize and advance the portfolio of population health analytics, particularly those using multisite administrative data sources.

Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods

OBJECTIVE

The combination of phenomic data from electronic health records (EHR) and clinical data repositories with dense biological data has enabled genomic and pharmacogenomic discovery, a first step toward precision medicine. Computational methods for the identification of clinical phenotypes from EHR data will advance our understanding of disease risk and drug response, and support the practice of precision medicine on a national scale.

METHODS

Based on our experience within three national research networks, we summarize the broad approaches to clinical phenotyping and highlight the important role of these networks in the progression of high-throughput phenotyping and precision medicine. We provide supporting literature in the form of a non-systematic review.

RESULTS

The practice of clinical phenotyping is evolving to meet the growing demand for scalable, portable, and data driven methods and tools. The resources required for traditional phenotyping algorithms from expert defined rules are significant. In contrast, machine learning approaches that rely on data patterns will require fewer clinical domain experts and resources.

CONCLUSIONS

Machine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, derived from data rather than experts. Research networks and phenotype developers should cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and truly modernize biomedical research and precision medicine.

A Simple Allergist-Led Intervention Improves Resident Training in Anaphylaxis

Physicians underrecognize and undertreat anaphylaxis. Effective interventions are needed to improve physician knowledge and competency regarding evidence-based anaphylaxis diagnosis and management (ADAM). We designed and evaluated an educational program to improve ADAM in pediatrics, internal medicine, and emergency medicine residents from two academic medical centers. Anonymous questionnaires queried participants' demographics, prior ADAM clinical experience, competency, and comfort. A pretest assessing baseline knowledge preceded a 45-minute allergist-led evidence-based presentation, including practice with epinephrine autoinjectors, immediately followed by a posttest. A follow-up test assessed long-term knowledge retention twelve weeks later. 159 residents participated in the pretest, 152 participated in the posttest, and 86 participated in the follow-up test. There were no significant differences by specialty or site. With a possible score of 10, the mean pretest score (7.31 ± 1.50) was lower than the posttest score (8.79 ± 1.29) and follow-up score (8.17 ± 1.72) (P < 0.001 for both). Although participants' perceived confidence in diagnosing or managing anaphylaxis improved from baseline to follow-up (P < 0.001 for both), participants' self-reported clinical experience with ADAM or autoinjector use was unchanged. Allergist-led face-to-face educational intervention improves residents' short-term knowledge and perceived confidence in ADAM. Limited clinical experience or reinforcement contributes to the observed decreased knowledge.

Epidemiology of anaphylaxis

Knowledge about the epidemiology of anaphylaxis is based on data from various sources: clinical practice, large secondary clinical and administrative databases of primary care or hospitalized patients, and recent surveys with representative samples of the general population. As several similar results are often reported in several publications and populations, such findings are highly like to be robust. One such finding is that the incidence and prevalence of anaphylaxis are higher than previously thought. Publications from the last 5 years reveal an incidence of between 50 and 112 episodes per 100 000 person-years; estimated prevalence is 0.3-5.1% depending on the rigour of the definitions used. Figures are higher in children, especially those aged 0-4 years. Publications from various geographical areas based on clinical and administrative data on hospitalized patients suggest that the frequency of admissions due to anaphylaxis has increased (5-7-fold in the last 10-15 years). Other publications point to a geographic gradient in the incidence of anaphylaxis, with higher frequencies recorded in areas with few hours of sunlight. However, these trends could be the result of factors other than a real change in the incidence of anaphylaxis, such as changes in disease coding and in the care provided. Based on data from the records of voluntary declarations of death by physicians and from large national databases, death from anaphylaxis remains very infrequent and stands at 0.35-1.06 deaths per million people per year, with no increases observed in the last 10-15 years. Although anaphylaxis can be fatal, recurrence of anaphylaxis--especially that associated with atopic diseases and hymenoptera stings--affects 26.5-54% of patients.

Prospective influenza vaccine safety surveillance using fresh data in the Sentinel System

Purpose

To develop the infrastructure to conduct timely active surveillance for safety of influenza vaccines and other medical countermeasures in the Sentinel System (formerly the Mini‐Sentinel Pilot), a Food and Drug Administration‐sponsored national surveillance system that typically relies on data that are mature, settled, and updated quarterly.

Methods

Three Data Partners provided their earliest available (“fresh”) cumulative claims data on influenza vaccination and health outcomes 3–4 times on a staggered basis during the 2013–2014 influenza season, collectively producing 10 data updates. We monitored anaphylaxis in the entire population using a cohort design and seizures in children ≤4 years of age using both a self‐controlled risk interval design (primary) and a cohort design (secondary). After each data update, we conducted sequential analysis for inactivated (IIV) and live (LAIV) influenza vaccines using the Maximized Sequential Probability Ratio Test, adjusting for data‐lag.

Results

Most of the 10 sequential analyses were conducted within 6 weeks of the last care‐date in the cumulative dataset. A total of 6 682 336 doses of IIV and 782 125 doses of LAIV were captured. The primary analyses did not identify any statistical signals following IIV or LAIV. In secondary analysis, the risk of seizures was higher following concomitant IIV and PCV13 than historically after IIV in 6‐ to 23‐month‐olds (relative risk = 2.7), which requires further investigation.

Conclusions

The Sentinel System can implement a sequential analysis system that uses fresh data for medical product safety surveillance. Active surveillance using sequential analysis of fresh data holds promise for detecting clinically significant health risks early. Limitations of employing fresh data for surveillance include cost and the need for careful scrutiny of signals. © 2015 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Increased incidence of admissions for anaphylaxis in Spain 1998-2011

We report on trends in anaphylaxis admissions in the Spanish hospital system during the period 1998-2011. Data on admissions for anaphylaxis were obtained from the Spanish Information System for Hospital Data for the period 1998-2011. Patients were selected using the codes for anaphylaxis in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). Poisson regression models were used to estimate incidence rate ratios. We recorded a 1.89-fold increase in admissions for anaphylaxis in Spanish hospitals during the study period, particularly in patients aged 0-14 years (1.65- to 3.22-fold until 2009 and 4.09- to 12.59-fold until 2011) and in food anaphylaxis in all age groups (2.78-fold until 2009 and 8.74-fold until 2011). The incidence of anaphylaxis is perceived as having increased in recent years, especially anaphylaxis caused by food and anaphylaxis affecting the pediatric population.

A comparison of active adverse event surveillance systems worldwide

Post-marketing drug surveillance for adverse drug events (ADEs) has typically relied on spontaneous reporting. Recently, regulatory agencies have turned their attention to more preemptive approaches that use existing data for surveillance. We conducted an environmental scan to identify active surveillance systems worldwide that use existing data for the detection of ADEs. We extracted data about the systems' structures, data, and functions. We synthesized the information across systems to identify common features of these systems. We identified nine active surveillance systems. Two systems are US based-the FDA Sentinel Initiative (including both the Mini-Sentinel Initiative and the Federal Partner Collaboration) and the Vaccine Safety Datalink (VSD); two are Canadian-the Canadian Network for Observational Drug Effect Studies (CNODES) and the Vaccine and Immunization Surveillance in Ontario (VISION); and two are European-the Exploring and Understanding Adverse Drug Reactions by Integrative Mining of Clinical Records and Biomedical Knowledge (EU-ADR) Alliance and the Vaccine Adverse Event Surveillance and Communication (VAESCO). Additionally, there is the Asian Pharmacoepidemiology Network (AsPEN) and the Shanghai Drug Monitoring and Evaluative System (SDMES). We identified two systems in the UK-the Vigilance and Risk Management of Medicines (VRMM) Division and the Drug Safety Research Unit (DSRU), an independent academic unit. These surveillance systems mostly use administrative claims or electronic medical records; most conduct pharmacovigilance on behalf of a regulatory agency. Either a common data model or a centralized model is used to access existing data. The systems have been built using national data alone or via partnership with other countries. However, active surveillance systems using existing data remain rare. North America and Europe have the most population coverage; with Asian countries making good advances.

Minimizing signal detection time in postmarket sequential analysis: balancing positive predictive value and sensitivity

PURPOSE

Outcome misclassification in retrospective epidemiologic analyses has been well-studied, but little is known about such misclassification with respect to sequential statistical analysis during surveillance of medical product-associated risks, a planned capability of the US Food and Drug Administration's Sentinel System.

METHODS

Using a vaccine example, we model and simulate sequential database surveillance in an observational data network using a variety of outcome detection algorithms. We consider how these algorithms, as characterized by sensitivity and positive predictive value, impact the length of surveillance and timeliness of safety signal detection. We show investigators/users of these networks how they can perform preparatory study design calculations that consider outcome misclassification in sequential database surveillance.

RESULTS

Non-differential outcome misclassification generates longer surveillance times and less timely safety signal detection as compared with the case of no misclassification. Inclusive algorithms characterized by high sensitivity but low positive predictive value outperform more narrow algorithms when detecting rare outcomes. This decision calculus may change considerably if medical chart validation procedures were required.

CONCLUSIONS

These findings raise important questions regarding the design of observational data networks used for pharmacovigilance. Specifically, there are tradeoffs involved when choosing to populate such networks with component databases that are large as compared with smaller integrated delivery system databases that can more easily access laboratory or clinical data and perform medical chart validation.