Incidence of venous and arterial thromboembolic events reported in the tofacitinib rheumatoid arthritis, psoriasis and psoriatic arthritis development programmes and from real-world data.

OBJECTIVES: Tofacitinib is a Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ulcerative colitis, and has been investigated in psoriasis (PsO). Routine pharmacovigilance of an ongoing, open-label, blinded-endpoint, tofacitinib RA trial (Study A3921133; NCT02092467) in patients aged ≥50 years and with ≥1 cardiovascular risk factor identified a higher frequency of pulmonary embolism (PE) and all-cause mortality for patients receiving tofacitinib 10 mg twice daily versus those receiving tumour necrosis factor inhibitors and resulted in identification of a safety signal for tofacitinib. Here, we report the incidence of deep vein thrombosis (DVT), PE, venous thromboembolism (VTE; DVT or PE) and arterial thromboembolism (ATE) from the tofacitinib RA (excluding Study A3921133), PsA and PsO development programmes and observational studies. Data from an ad hoc safety analysis of Study A3921133 are reported separately within. METHODS: This post-hoc analysis used data from separate tofacitinib RA, PsO and PsA programmes. Incidence rates (IRs; patients with events per 100 patient-years' exposure) were calculated for DVT, PE, VTE and ATE, including for populations stratified by defined baseline cardiovascular or VTE risk factors. Observational data from the US Corrona registries (including cardiovascular risk factor stratification), IBM MarketScan research database and the US FDA Adverse Event Reporting System (FAERS) database were analysed. RESULTS: 12 410 tofacitinib-treated patients from the development programmes (RA: n=7964; PsO: n=3663; PsA: n=783) were included. IRs (95% CI) of thromboembolic events among the all tofacitinib cohorts' average tofacitinib 5 mg and 10 mg twice daily treated patients for RA, respectively, were: DVT (0.17 (0.09-0.27) and 0.15 (0.09-0.22)); PE (0.12 (0.06-0.22) and 0.13 (0.08-0.21)); ATE (0.32 (0.22-0.46) and 0.38 (0.28-0.49)). Among PsO patients, IRs were: DVT (0.06 (0.00-0.36) and 0.06 (0.02-0.15)); PE (0.13 (0.02-0.47) and 0.09 (0.04-0.19)); ATE (0.52 (0.22-1.02) and 0.22 (0.13-0.35)). Among PsA patients, IRs were: DVT (0.00 (0.00-0.28) and 0.13 (0.00-0.70)); PE (0.08 (0.00-0.43) and 0.00 (0.00-0.46)); ATE (0.31 (0.08-0.79) and 0.38 (0.08-1.11)). IRs were similar between tofacitinib doses and generally higher in patients with baseline cardiovascular or VTE risk factors. IRs from the overall Corrona populations and in Corrona RA patients (including tofacitinib-naïve/biologic disease-modifying antirheumatic drug-treated and tofacitinib-treated) with baseline cardiovascular risk factors were similar to IRs observed among the corresponding patients in the tofacitinib development programme. No signals of disproportionate reporting of DVT, PE or ATE with tofacitinib were identified in the FAERS database. CONCLUSIONS: DVT, PE and ATE IRs in the tofacitinib RA, PsO and PsA programmes were similar across tofacitinib doses, and generally consistent with observational data and published IRs of other treatments. As expected, IRs of thromboembolic events were elevated in patients with versus without baseline cardiovascular or VTE risk factors, and were broadly consistent with those observed in the Study A3921133 ad hoc safety analysis data, although the IR (95% CI) for PE was greater in patients treated with tofacitinib 10 mg twice daily in Study A3921133 (0.54 (0.32-0.87)), versus patients with baseline cardiovascular risk factors treated with tofacitinib 10 mg twice daily in the RA programme (0.24 (0.13-0.41)).

Evaluating the Effectiveness of New York City Health Policy Initiatives in Reducing Cardiovascular Disease Mortality, 1990-2011.

Beginning in 2002, New York City (NYC) implemented numerous policies and programs targeting cardiovascular disease (CVD) risk factors. Using death certificates, we analyzed trends in NYC-specific and US mortality rates from 1990 to 2011 for all causes, any CVD, atherosclerotic CVD (ACVD), coronary artery disease (CAD), and stroke. Joinpoint analyses quantified annual percent change (APC) and evaluated whether decreases in CVD mortality accelerated after 2002 in either NYC or the total US population. Our analyses included 1,149,217 NYC decedents. The rates of decline in mortality from all causes, any CVD, and stroke in NYC did not change after 2002. Among men, the decline in ACVD mortality accelerated during 2002-2011 (APC = -4.8%, 95% confidence interval (CI): -6.1, -3.4) relative to 1990-2001 (APC = -2.3%, 95% CI: -3.1, -1.5). Among women, ACVD rates began declining more rapidly in 1993 (APC = -3.2%, 95% CI: -3.8, -2.7) and again in 2006 (APC = -6.6%, 95% CI: -8.9, -4.3) as compared with 1990-1992 (APC = 1.6%, 95% CI: -2.7, 6.0). In the US population, no acceleration of mortality decline was observed in either ACVD or CAD mortality rates after 2002. Relative to 1990-2001, atherosclerotic CVD and CAD rates began to decline more rapidly during the 2002-2011 period in both men and women-a pattern not observed in the total US population, suggesting that NYC initiatives might have had a measurable influence on delaying or reducing ACVD mortality.

Implications for Improving Fetal Death Vital Statistics: Connecting Reporters' Self-Identified Practices and Barriers to Third Trimester Fetal Death Data Quality in New York City.

OBJECTIVES: Perinatal mortality prevention strategies that target fetal deaths often utilize vital records data sets shown to contain critical quality deficiencies. To understand the causes of deficient data, we linked survey responses of fetal death reporters with facility fetal death data quality indicators. METHODS: In 2011, we surveyed the person most responsible for fetal death reporting at New York City healthcare facilities on their attitudes, barriers, and practices regarding reporting. We compared responses by 2 facility data quality indicators (data completeness and ill-defined cause of fetal death) for third trimester fetal death registrations using Chi squared tests. RESULTS: Thirty-nine of 50 facilities completed full questionnaires (78 % response rate); responding facilities reported 84 % (n = 11,891) of all 2011 fetal deaths, including 329 third trimester fetal deaths. Facilities citing ≥1 reporting barrier were approximately five times more likely to have incomplete third trimester registrations than facilities citing no substantial barriers (37.5 vs 7.9 %; RR 4.7; 95 % CI [1.6-14.2]). Reported barriers included onerous reporting requirements (n = 10; 26 %) and competing physician priorities (n = 11; 28 %). Facilities citing difficulty involving physicians in reporting were more likely to report fetal deaths with nonspecific cause-of-death information (70.9 vs 56.6 %; RR 1.3; 95 % CI [1.1-1.5]). CONCLUSIONS: Self-reported challenges correlate with completeness and accuracy of reported fetal death data, suggesting that such barriers are likely contributing to low quality data. We identified several improvement opportunities, including in-depth training and reducing the information collected, especially for early fetal deaths (<20 weeks' gestation), the majority of events reported.

Evaluating the Use of an Electronic Death Registration System for Mortality Surveillance During and After Hurricane Sandy: New York City, 2012.

OBJECTIVES: We evaluated the use of New York City's (NYC's) electronic death registration system (EDRS) to conduct mortality surveillance during and after Hurricane Sandy. METHODS: We used Centers for Disease Control and Prevention guidelines for surveillance system evaluation to gather evidence on usefulness, flexibility, stability, timeliness, and quality. We assessed system components, interviewed NYC Health Department staff, and analyzed 2010 to 2012 death records. RESULTS: Despite widespread disruptions, NYC's EDRS was stable and collected timely mortality data that were adapted to provide storm surveillance with minimal additional resources. Direct-injury fatalities and trends in excess all-cause mortality were rapidly identified, providing useful information for response; however, the time and burden of establishing reports, adapting the system, and identifying indirect deaths limited surveillance. CONCLUSIONS: The NYC Health Department successfully adapted its EDRS for near real-time disaster-related mortality surveillance. Retrospective assessment of deaths, advanced methods for case identification and analysis, standardized reports, and system enhancements will further improve surveillance. Local, state, and federal partners would benefit from partnering with vital records to develop EDRSs for surveillance and to promote ongoing evaluation.

How well do birth records serve maternal and child health programs? Birth registration system evaluation, New York City, 2008-2011.

National birth registration guidelines were revised in 2003 to improve data quality; however, few studies have evaluated the impact on local jurisdictions and their data users. In New York City (NYC), approximately 125,000 births are registered annually with the NYC Department of Health and Mental Hygiene, and data are used routinely by the department's maternal and child health (MCH) programs. In order to better meet MCH program needs, we used Centers for Disease Control and Prevention guidelines to assess birth data usefulness, simplicity, data quality, timeliness and representativeness. We interviewed birth registration and MCH program staff, reviewed a 2009 survey of birth registrars (n = 39), and analyzed 2008-2011 birth records for timeliness and completeness (n = 502,274). Thirteen MCH programs use birth registration data for eligibility determination, needs assessment, program evaluation, and surveillance. Demographic variables are used frequently, nearly 100 % complete, and considered the gold standard by programs; in contrast, medical variables' use and validity varies widely. Seventy-seven percent of surveyed birth registrars reported ≥1 problematic items in the system; 64.1 % requested further training. During 2008-2011, the median interval between birth and registration was 5 days (range 0-260 days); 11/13 programs were satisfied with timeliness. The NYC birth registration system provides local MCH programs useful, timely, and representative data. However, some medical items are difficult to collect, of low quality, and rarely used. We recommend enhancing training for birth registrars, continuing quality improvement efforts, increasing collaboration with program users, and removing consistently low-quality and low-use variables.

Reliability of Reported Maternal Smoking: Comparing the Birth Certificate to Maternal Worksheets and Prenatal and Hospital Medical Records, New York City and Vermont, 2009.

Maternal smoking is captured on the 2003 US Standard Birth Certificate based on self-reported tobacco use before and during pregnancy collected on post-delivery maternal worksheets. Study objectives were to compare smoking reported on the birth certificate to maternal worksheets and prenatal and hospital medical records. The authors analyzed a sample of New York City (NYC) and Vermont women (n = 1,037) with a live birth from January to August 2009 whose responses to the Pregnancy Risk Assessment Monitoring System survey were linked with birth certificates and abstracted medical records and maternal worksheets. We calculated smoking prevalence and agreement (kappa) between sources overall and by maternal and hospital characteristics. Smoking before and during pregnancy was 13.7 and 10.4% using birth certificates, 15.2 and 10.7% using maternal worksheets, 18.1 and 14.1% using medical records, and 20.5 and 15.0% using either maternal worksheets or medical records. Birth certificates had "almost perfect" agreement with maternal worksheets for smoking before and during pregnancy (κ = 0.92 and 0.89) and "substantial" agreement with medical records (κ = 0.70 and 0.74), with variation by education, insurance, and parity. Smoking information on NYC and Vermont birth certificates closely agreed with maternal worksheets but was underestimated compared with medical records, with variation by select maternal characteristics. Opportunities exist to improve birth certificate smoking data, such as reducing the stigma of smoking, and improving the collection, transcription, and source of information.

Effect of cause-of-death training on agreement between hospital discharge diagnoses and cause of death reported, inpatient hospital deaths, New York City, 2008-2010.

INTRODUCTION: Accurate cause-of-death reporting is required for mortality data to validly inform public health programming and evaluation. Research demonstrates overreporting of heart disease on New York City death certificates. We describe changes in reported causes of death following a New York City health department training conducted in 2009 to improve accuracy of cause-of-death reporting at 8 hospitals. The objective of our study was to assess the degree to which death certificates citing heart disease as cause of death agreed with hospital discharge data and the degree to which training improved accuracy of reporting. METHODS: We analyzed 74,373 death certificates for 2008 through 2010 that were linked with hospital discharge records for New York City inpatient deaths and calculated the proportion of discordant deaths, that is, death certificates reporting an underlying cause of heart disease with no corresponding discharge record diagnosis. We also summarized top principal diagnoses among discordant reports and calculated the proportion of inpatient deaths reporting sepsis, a condition underreported in New York City, to assess whether documentation practices changed in response to clarifications made during the intervention. RESULTS: Citywide discordance between death certificates and discharge data decreased from 14.9% in 2008 to 9.6% in 2010 (P < .001), driven by a decrease in discordance at intervention hospitals (20.2% in 2008 to 8.9% in 2010; P < .001). At intervention hospitals, reporting of sepsis increased from 3.7% of inpatient deaths in 2008 to 20.6% in 2010 (P < .001). CONCLUSION: Overreporting of heart disease as cause of death declined at intervention hospitals, driving a citywide decline, and sepsis reporting practices changed in accordance with health department training. Researchers should consider the effect of overreporting and data-quality changes when analyzing New York City heart disease mortality trends. Other vital records jurisdictions should employ similar interventions to improve cause-of-death reporting and use linked discharge data to monitor data quality.

Understanding perinatal death: a systematic analysis of New York City fetal and neonatal death vital record data and implications for improvement, 2007-2011.

We aimed to compare demographic, medical, and cause-of-death information reported for third-trimester fetal and neonatal death vital records collected in New York City (NYC) before and after implementation of the revised fetal death certificate to identify: (1) the limitations of combining fetal and neonatal death records for the purpose of perinatal death prevention; and (2) improvement opportunities for fetal death vital records registration. Using Chi squared tests, we compared data completeness and cause-of-death information between third-trimester NYC fetal (n = 1,930) and neonatal deaths (n = 735) from 2007 to 2011. We also compared fetal death data before and after the 2011 implementation of the 2003 United States (US) Standard Report of Fetal Death and an electronic reporting system. Compared with neonatal deaths, fetal death data were generally less complete (P < 0.0001). Fetal death data much more frequently reported an ill-defined cause of death (67 vs. 5 %). Most ill-defined reported causes of fetal death (73 %) were attributed to stillbirth synonyms (e.g., "fetal demise"). Ill-defined causes of fetal death decreased from 68 to 61 % (P < 0.01) after 2011. Both data completeness and ill-defined causes of death varied widely by hospital. In NYC, fetal deaths lack demographic, medical, and cause-of-death information compared with neonatal deaths, with implications for research that uses combined perinatal mortality data sets. Electronic implementation of the US Standard Report of Fetal Death minimally improved cause-of-death information. Substantial variability by hospital suggests opportunities for improvement exist.

Test of an electronic program to query clinicians about nonspecific causes reported for pneumonia deaths, New York City, 2012.

We tested an electronic cause-of-death query system at a hospital in New York City to evaluate clinicians' reporting of cause of death. We used the system to query clinicians about all deaths assigned International Classification of Disease code J189 (pneumonia, unspecified) as the underlying cause of death. Of 29 death certificates that generated queries, 28 were updated with additional information, which led to revisions in the underlying cause of 27 deaths. The electronic system for querying reported cause of death was feasible and enabled quicker than usual responses; however, follow-up with clinicians to ensure timely, accurate, and complete responses was labor-intensive. Educating clinicians and enforcing reporting standards would reduce the time and effort required to ensure accurate and timely cause-of-death reporting.

Evaluating New York City's abortion reporting system: insights for public health data collection systems.

CONTEXT: New York City (NYC) mandates reporting of all abortion procedures. These reports enable tracking of abortion incidence and underpin programs, policy, and research. Since January 2011, the majority of abortion facilities must report electronically. OBJECTIVES: We conducted an evaluation of NYC's abortion reporting system and its transition to electronic reporting. We summarize the evaluation methodology and results and draw lessons relevant to other vital statistics and public health reporting systems. DESIGN: The evaluation followed Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems. We interviewed key stakeholders and conducted a data provider survey. In addition, we compared the system's abortion counts with external estimates and calculated the proportion of missing and invalid values for each variable on the report form. Finally, we assessed the process for changing the report form and estimated system costs. SETTING: NYC Health Department's Bureau of Vital Statistics. MAIN OUTCOME MEASURES: Usefulness, simplicity, flexibility, data quality, acceptability, sensitivity, timeliness, and stability of the abortion reporting system. RESULTS: Ninety-five percent of abortion data providers considered abortion reporting important; 52% requested training regarding the report form. Thirty percent reported problems with electronic biometric fingerprint certification, and 18% reported problems with the electronic system's stability. Estimated system sensitivity was 88%. Of 17 variables, education and ancestry had more than 5% missing values in 2010. Changing the electronic reporting module was costly and time-consuming. System operating costs were estimated at $80 136 to $89 057 annually. CONCLUSIONS: The NYC abortion reporting system is sensitive and provides high-quality data, but opportunities for improvement include facilitating biometric certification, increasing electronic platform stability, and conducting ongoing outreach and training for data providers. This evaluation will help data users determine the degree of confidence that should be placed on abortion data. In addition, the evaluation results are applicable to other vital statistics reporting and surveillance systems.

A case study of the impact of inaccurate cause-of-death reporting on health disparity tracking: New York City premature cardiovascular mortality.

OBJECTIVES: Heart disease death overreporting is problematic in New York City (NYC) and other US jurisdictions. We examined whether overreporting affects the premature (< 65 years) heart disease death rate disparity between non-Hispanic Blacks and non-Hispanic Whites in NYC. METHODS: We identified overreporting hospitals and used counts of premature heart disease deaths at reference hospitals to estimate corrected counts. We then corrected citywide, age-adjusted premature heart disease death rates among Blacks and Whites and a White-Black premature heart disease death disparity. RESULTS: At overreporting hospitals, 51% of the decedents were White compared with 25% at reference hospitals. Correcting the heart disease death counts at overreporting hospitals decreased the age-adjusted premature heart disease death rate 10.1% (from 41.5 to 37.3 per 100,000) among Whites compared with 4.2% (from 66.2 to 63.4 per 100,000) among Blacks. Correction increased the White-Black disparity 6.1% (from 24.6 to 26.1 per 100,000). CONCLUSIONS: In 2008, NYC's White-Black premature heart disease death disparity was underestimated because of overreporting by hospitals serving larger proportions of Whites. Efforts to reduce overreporting may increase the observed disparity, potentially obscuring any programmatic or policy-driven advances.

Programmatic impact of 5 years of mortality surveillance of New York City homeless populations.

A homeless mortality surveillance system identifies emerging trends in the health of the homeless population and provides this information to key stakeholders in a timely and ongoing manner to effect evidence-based, programmatic change. We describe the first 5 years of the New York City homeless mortality surveillance system and, for the first time in peer-reviewed literature, illustrate the impact of key elements of sustained surveillance (i.e., timely dissemination of aggregate mortality data and real-time sharing of information on individual homeless decedents) on the programs of New York City's Department of Homeless Services. These key elements had a positive impact on the department's programs that target sleep-related infant deaths and hypothermia, drug overdose, and alcohol-related deaths among homeless persons.

Impact of a hospital-level intervention to reduce heart disease overreporting on leading causes of death.

INTRODUCTION: The quality of cause-of-death reporting on death certificates affects the usefulness of vital statistics for public health action. Heart disease deaths are overreported in the United States. We evaluated the impact of an intervention to reduce heart disease overreporting on other leading causes of death. METHODS: A multicomponent intervention comprising training and communication with hospital staff was implemented during July through December 2009 at 8 New York City hospitals reporting excessive heart disease deaths. We compared crude, age-adjusted, and race/ethnicity-adjusted proportions of leading, underlying causes of death reported during death certification by intervention and nonintervention hospitals during preintervention (January-June 2009) and postintervention (January-June 2010) periods. We also examined trends in leading causes of death for 2000 through 2010. RESULTS: At intervention hospitals, heart disease deaths declined by 54% postintervention; other leading causes of death (ie, malignant neoplasms, influenza and pneumonia, cerebrovascular disease, and chronic lower respiratory diseases) increased by 48% to 232%. Leading causes of death at nonintervention hospitals changed by 6% or less. In the preintervention period, differences in leading causes of death between intervention and nonintervention hospitals persisted after controlling for race/ethnicity and age; in the postintervention period, age accounted for most differences observed between intervention and nonintervention hospitals. Postintervention, malignant neoplasms became the leading cause of premature death (ie, deaths among patients aged 35-74 y) at intervention hospitals. CONCLUSION: A hospital-level intervention to reduce heart disease overreporting led to substantial changes to other leading causes of death, changing the leading cause of premature death. Heart disease overreporting is likely obscuring the true levels of cause-specific mortality.

Causal models for investigating complex disease: I. A primer.

BACKGROUND/AIMS: To illustrate the utility of causal models for research in genetic epidemiology and statistical genetics. Causal models are increasingly applied in risk factor epidemiology, economics, and health policy, but seldom used in statistical genetics or genetic epidemiology. Unlike the statistical models usually used in genetic epidemiology, causal models are explicitly formulated in terms of cause and effect relationships occurring at the individual level. METHODS: We describe two causal models, the sufficient component cause model and the potential outcomes model, and show how key concepts in genetic epidemiology, including penetrance, phenocopies, genetic heterogeneity, etiologic heterogeneity, gene-gene interaction, and gene-environment interaction, can be framed in terms of these causal models. We also illustrate how potential outcomes models can provide insight into the potential for confounding and bias in the measurement of causal effects in genetic studies. RESULTS: Our analysis illustrates how causal models can elucidate the relationships among underlying causal mechanisms and measures obtained from statistical analysis of observed data. CONCLUSION: Causal models can enhance research aimed at identifying causal genes.

Causal models for investigating complex genetic disease: II. what causal models can tell us about penetrance for additive, heterogeneity, and multiplicative two-locus models.

BACKGROUND/AIMS: Statistical geneticists commonly use certain two-locus penetrance models because these models are familiar and mathematically tractable. We investigate whether and under what circumstances these two-locus penetrance models correspond to models of causation. METHODS: We describe a sufficient component cause model for a hypothetical disease with two genetic causes. We then use the potential outcomes framework to determine the expected two-locus penetrances from this causal model and contrast them with commonly used two-locus penetrance models (additive, heterogeneity, and multiplicative penetrance models, as formulated by Risch [Am J Hum Genet 1990;46:222-228]). RESULTS: Conventional additive and multiplicative models can correspond to any two-locus causal model only when certain very specific algebraic relationships hold. The heterogeneity model corresponds to a two-locus causal model only if the model stipulates that no disease cases are caused by the combined presence of the causal genotypes at both loci (i.e. only when there is no causal gene-gene interaction). Hence the heterogeneity model provides a valid test of the null hypothesis of no gene-gene interaction, whereas the additive and multiplicative models do not. CONCLUSION: We suggest that causal principles should provide the basis for statistical modeling in genetics.

An intervention to improve cause-of-death reporting in New York City hospitals, 2009-2010.

INTRODUCTION: Poor-quality cause-of-death reporting reduces reliability of mortality statistics used to direct public health efforts. Overreporting of heart disease has been documented in New York City (NYC) and nationwide. Our objective was to evaluate the immediate and longer-term effects of a cause-of-death (COD) educational program that NYC's health department conducted at 8 hospitals on heart disease reporting and on average conditions per certificate, which are indicators of the quality of COD reporting. METHODS: From June 2009 through January 2010, we intervened at 8 hospitals that overreported heart disease deaths in 2008. We shared hospital-specific data on COD reporting, held conference calls with key hospital staff, and conducted in-service training. For deaths reported from January 2009 through June 2011, we compared the proportion of heart disease deaths and average number of conditions per death certificate before and after the intervention at both intervention and nonintervention hospitals. RESULTS: At intervention hospitals, the proportion of death certificates that reported heart disease as the cause of death decreased from 68.8% preintervention to 32.4% postintervention (P < .001). Individual hospital proportions ranged from 58.9% to 79.5% preintervention and 25.9% to 45.0% postintervention. At intervention hospitals the average number of conditions per death certificate increased from 2.4 conditions preintervention to 3.4 conditions postintervention (P < .001) and remained at 3.4 conditions a year later. At nonintervention hospitals, these measures remained relatively consistent across the intervention and postintervention period. CONCLUSION: This NYC health department's hospital-level intervention led to durable changes in COD reporting.

Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design.

Interest in real-world data (RWD) and real-world evidence (RWE) to expedite and enrich the development of new biopharmaceutical products has proliferated in recent years, spurred by the 21st Century Cures Act in the United States and similar policy efforts in other countries, willingness by regulators to consider RWE in their decisions, demands from third-party payers, and growing concerns about the limitations of traditional clinical trials. Although much of the recent literature on RWE has focused on potential regulatory uses (e.g., product approvals in oncology or rare diseases based on single-arm trials with external control arms), this article reviews how biopharmaceutical companies can leverage RWE to inform internal decisions made throughout the product development process. Specifically, this article will review use of RWD to guide pipeline and portfolio strategy; use of novel sources of RWD to inform product development, use of RWD to inform clinical development, use of advanced analytics to harness "big" RWD, and considerations when using RWD to inform internal decisions. Topics discussed will include the use of molecular, clinicogenomic, medical imaging, radiomic, and patient-derived xenograft data to augment traditional sources of RWE, the use of RWD to inform clinical trial eligibility criteria, enrich trial population based on predicted response, select endpoints, estimate sample size, understand disease progression, and enhance diversity of participants, the growing use of data tokenization and advanced analytical techniques based on artificial intelligence in RWE, as well as the importance of data quality and methodological transparency in RWE.

Characteristics, Comorbidities, and Outcomes of SARS-CoV-2 Infection in Patients With Autoimmune Conditions Treated With Systemic Therapies: A Population-based Study.

OBJECTIVE: To describe characteristics and coronavirus disease 2019 (COVID-19) clinical outcomes of patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), or ulcerative colitis (UC) receiving systemic therapies vs the general population. METHODS: This descriptive retrospective cohort study used data from the United States Optum deidentified COVID-19 electronic health record dataset (2007-2020). Adults with COVID-19 were stratified into 3 disease cohorts (patients with RA, PsA, or UC who had received systemic therapy) and a comparator cohort not meeting these criteria. Incidence proportions of hospitalization and clinical manifestations of interest were calculated. Using logistic regression analyses, risk of endpoints was estimated, adjusting for demographics and demographics plus comorbidities. RESULTS: This analysis (February 1 to December 9, 2020) included 315,101 patients with COVID-19. Adjusting for demographics, COVID-19 patients with RA (n = 2306) had an increased risk of hospitalization (OR 1.54, 95% CI 1.39-1.70) and in-hospital death (OR 1.61, 95% CI 1.30-2.00) compared with the comparator cohort (n = 311,563). The increased risk was also observed when adjusted for demographics plus comorbidities (hospitalization OR 1.25, 95% CI 1.13-1.39 and in-hospital death OR 1.35, 95% CI 1.09-1.68]). The risk of hospitalization was lower in COVID-19 patients with RA receiving tumor necrosis factor inhibitors (TNFi) vs non-TNFi biologics (OR 0.32, 95% CI 0.20-0.53) and the comparator cohort (OR 0.77, 95% CI 0.51-1.17). The risk of hospitalization due to COVID-19 was similar between patients receiving tofacitinib and the comparator cohort. CONCLUSION: Compared with the comparator cohort, patients with RA were at a higher risk of more severe or critical COVID-19 and, except for non-TNFi biologics, systemic therapies did not further increase the risk. (ENCePP; registration no. EU PAS 35384).

Adverse events of special interest in clinical trials of rheumatoid arthritis, psoriatic arthritis, ulcerative colitis and psoriasis with 37 066 patient-years of tofacitinib exposure.

OBJECTIVES: To analyse adverse events (AEs) of special interest across tofacitinib clinical programmes in rheumatoid arthritis (RA), psoriatic arthritis (PsA), ulcerative colitis (UC) and psoriasis (PsO), and to determine whether the incidence rates (IRs; unique patients with events per 100 patient-years) of these events are consistent across diseases. METHODS: The analysis included data from patients exposed to ≥1 dose of tofacitinib in phase 1, 2, 3 or 3b/4 clinical trials and long-term extension (LTE) studies (38 trials) in RA (23 trials), PsA (3 trials), UC (5 trials) and PsO (7 trials). All studies were completed by or before July 2019, except for one ongoing UC LTE study (data cut-off May 2019). IRs were obtained for AEs of special interest. RESULTS: 13 567 patients were included in the analysis (RA: n=7964; PsA: n=783; UC: n=1157; PsO: n=3663), representing 37 066 patient-years of exposure. Maximum duration of exposure was 10.5 years (RA). AEs within the 'infections and infestations' System Organ Class were the most common in all diseases. Among AEs of special interest, IRs were highest for herpes zoster (non-serious and serious; 3.6, 1.8, 3.5 and 2.4 for RA, PsA, UC and PsO, respectively) and serious infections (2.5, 1.2, 1.7 and 1.3 for RA, PsA, UC and PsO, respectively). Age-adjusted and sex-adjusted mortality ratios (weighted for country) were ≤0.2 across cohorts. CONCLUSIONS: The tofacitinib safety profile in this analysis was generally consistent across diseases and with longer term follow-up compared with previous analyses.

Postapproval Comparative Safety Study of Tofacitinib and Biological Disease-Modifying Antirheumatic Drugs: 5-Year Results from a United States-Based Rheumatoid Arthritis Registry.

OBJECTIVE: Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). We compared 5-year adverse event (AE) incidence rates (IRs) between patients initiating tofacitinib and those initiating new biological disease-modifying antirheumatic drugs (bDMARDs) within the United States (US) Corrona RA registry. METHODS: IRs (number of first events/100 patient-years) of major adverse cardiovascular events (MACE), serious infection events (SIEs), herpes zoster (HZ), malignancies, and death were estimated among tofacitinib and bDMARD initiators, regardless of dose/schedule, between November 6, 2012 (US Food and Drug Administration tofacitinib approval), and July 31, 2018 (follow-up through January 31, 2019). Propensity score (PS) methods were used to control for nonrandom prescribing practices. Hazard ratios (HRs) were calculated to compare rates using multivariable-adjusted Cox regression. Different risk windows were used for acute (MACE, SIEs, HZ, and venous thromboembolic events [VTEs]) and long-term (malignancy and death) events. VTEs were assessed descriptively. RESULTS: For MACE, SIEs, and HZ, 1999 (3152.1 patient-years) and 8358 (12 869.4 years) tofacitinib and bDMARD initiators were included, respectively; for malignancy/death, 1999 (4505.6 patient-years) and 6354 (16 670.8 patient-years) initiators were included, respectively. AE rates were similar across cohorts, except for HZ, which was significantly higher with tofacitinib versus bDMARDs (PS-trimmed adjusted HR 2.32; 95% confidence interval [CI] 1.43-3.75). There were 45 (zero serious) and 88 (five serious) HZ events with tofacitinib and bDMARDs, respectively. Sensitivity analyses demonstrated similar results. VTE IRs (95% CI) were 0.29 (0.13-0.54) and 0.33 (0.24-0.45) for tofacitinib and bDMARDs, respectively. CONCLUSION: In this registry analysis, both cohorts had similar MACE, SIE, malignancy, death, and VTE rates; HZ rates were higher for tofacitinib initaitors than for bDMARD initiators.