Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clinical trial timelines. To meet the planned trial recruitment, site selection strategies are used during clinical trial planning to identify research sites that are most likely to recruit a sufficiently high number of subjects within trial timelines. We developed a machine learning approach that outperforms baseline methods to rank research sites based on their expected recruitment in future studies. Indication level historical recruitment and real-world data are used in the machine learning approach to predict patient enrollment at site level. We define covariates based on published recruitment hypotheses and examine the effect of these covariates in predicting patient enrollment. We compare model performance of a linear and a non-linear machine learning model with common industry baselines that are constructed from historical recruitment data. Performance of the methodology is evaluated and reported for two disease indications, inflammatory bowel disease and multiple myeloma, both of which are actively being pursued in clinical development. We validate recruitment hypotheses by reviewing the covariates relationship with patient recruitment. For both indications, the non-linear model significantly outperforms the baselines and the linear model on the test set. In this paper, we present a machine learning approach to site selection that incorporates site-level recruitment and real-world patient data. The model ranks research sites by predicting the number of recruited patients and our results suggest that the model can improve site ranking compared to common industry baselines.

Impact of Immune Checkpoint Inhibitors on COVID-19 Severity in Patients with Cancer.

BACKGROUND: Amid continued uncertainty about the management of cancer patients during the pandemic, this study sought to obtain real-world data on the use of immune checkpoint inhibitors (ICIs) before COVID-19 diagnosis and its association with severity and survival outcomes in cancer patients who contracted COVID-19. METHODS: Cancer patients diagnosed with COVID-19 were identified from a large electronic health record database; those treated with ICIs before COVID-19+ diagnosis were matched in a 1:2 ratio to those not treated with ICIs, using a 2-step matching procedure. A descriptive analysis examined the difference in COVID-19 mortality (30-day and overall) and severity outcomes between the 2 cohorts, and overall survival was compared. RESULTS: Among 17 545 adults ≥18 years with cancer who tested positive for COVID-19 between February 20, 2020, and January 28, 2021, in the US, 228 ICI-treated patients were matched to 456 non-ICI-treated patients, comprising the 2 study cohorts. Clinical characteristics differed significantly between the 2 cohorts before matching, with metastatic disease, lung cancer, a history of smoking, and the presence of pulmonary comorbidities being more common in the ICI-treated cohort; after matching, the 2 cohorts were similar. There were no significant differences between the ICI-treated and non-ICI-treated cohorts for 30-day mortality (12.7% vs. 14.9%, P = .235), overall mortality (22.4% vs. 22.4%, P = 1.000), hospitalization (38.6% vs. 39.0%, P = .912), or emergency department visits (16.7% vs. 14.7%, P = .500). Overall survival was similar between the 2 cohorts. CONCLUSION: This analysis adds to the clinical evidence base that use of ICIs before SARS-CoV-2 infection does not affect COVID-19 severity or survival outcomes, supporting the continued use of ICIs in cancer patients during the pandemic.

Association of biological antirheumatic therapy with risk for type 2 diabetes: a retrospective cohort study in incident rheumatoid arthritis.

OBJECTIVE: To explore possible associations of treatment with biological disease-modifying antirheumatic drugs (bDMARDs), including T-cell-based and interleukin-6 inhibition (IL-6i)-based therapies, and the risk for type 2 diabetes mellitus (T2DM) in patients with rheumatoid arthritis (RA). STUDY DESIGN, SETTING AND PARTICIPANTS: Five treatment groups were selected from a United States Electronic Medical Records database of 283 756 patients with RA (mean follow-up, 5 years): never received bDMARD (No bDMARD, n=125 337), tumour necrosis factor inhibitors (TNFi, n=34 873), IL-6i (n=1884), T-cell inhibitors (n=5935) and IL-6i+T cell inhibitor abatacept (n=1213). Probability and risk for T2DM were estimated with adjustment for relevant confounders. RESULTS: In the cohort of 169 242 patients with a mean 4.5 years of follow-up and a mean 641 200 person years of follow-up, the adjusted probability of developing T2DM was significantly lower in the IL-6i (probability, 1%; 95% CI 0.6 to 2.0), T-cell inhibitor (probability, 3%; 95% CI 2.3 to 3.3) and IL-6i+T cell inhibitor (probability, 2%; 95% CI 0.1 to 2.9) groups than in the No bDMARD (probability, 5%; 95% CI 4.6 to 4.9) and TNFi (probability, 4%; 95% CI 3.7 to 4.7) groups. Compared with No bDMARD, the IL-6i and IL-6i+T cell inhibitor groups had 37% (95% CI of HR 0.42 to 0.96) and 34% (95% CI of HR 0.46 to 0.93) significantly lower risk for T2DM, respectively; there was no significant difference in risk in the TNFi (HR 0.99; 95% CI 0.93 to 1.06) and T-cell inhibitor (HR 0.96; 95% CI 0.82 to 1.12) groups. CONCLUSIONS: Treatment with IL-6i, with or without T-cell inhibitors, was associated with reduced risk for T2DM compared with TNFi or No bDMARDs; a less pronounced association was observed for the T-cell inhibitor abatacept.

Rituximab utilization for approved and off-label nononcology indications and patients' experiences with the Patient Alert Card.

This study used retrospective chart review and survey data to evaluate: (1) off-label use of rituximab (MabThera®/Rituxan®) in autoimmune conditions and (2) patients' receipt and knowledge of the Patient Alert Card (PAC), a risk minimization measure for progressive multifocal leukoencephalopathy (PML) and serious infections. Anonymized patient data were collected from infusion centers in Europe from December 2015 to July 2017. Adults receiving rituximab in the same centers were provided a self-administered survey. Outcomes included patterns of off-label rituximab use for nononcology indications, and evaluation of patients' receipt and knowledge of the PAC and its impact. Of 1012 patients in the retrospective chart review, 70.2% received rituximab for rheumatoid arthritis or granulomatosis with polyangiitis/microscopic polyangiitis, and 29.8% received rituximab off label. Among 524 survey participants, 32.8% reported receiving the PAC, 59.3% reported not receiving the PAC and 7.9% did not know whether they received the PAC. A total of 72.4% of patients reported that they were unaware that some patients receiving rituximab experience PML. A higher proportion of PAC recipients identified PML as a potential risk of rituximab than nonrecipients (37.8% vs 19.9%); 58.3% of PAC recipients had poor awareness of PML. Most PAC recipients (90.0%) and nonrecipients (85.5%) correctly answered that they should seek medical attention for infection symptoms. In conclusion, approximately 30% of patients received off-label rituximab. Most patients reported not receiving the PAC or having knowledge of PML but demonstrated understanding of the recommended action in the event of infection symptoms, regardless of PAC receipt.

Characterizing Disease Manifestations and Treatment Patterns Among Adults with Systemic Sclerosis: A Retrospective Analysis of a US Healthcare Claims Population.

INTRODUCTION: Real-world use of immunomodulating therapy (IMT) in patients with systemic sclerosis (SSc) was investigated for the first time in a descriptive, retrospective cohort analysis of claims made in a healthcare insurance database to characterize treatment patterns and their alignment with SSc disease manifestations. METHODS: Treatment patterns and disease manifestations, symptoms, complications, and comorbidities were assessed in patients with SSc enrolled in a US healthcare claims database who received treatment between January 2006 and December 2013 and for whom data were available 6 months before and 12 months after SSc diagnosis. RESULTS: Among 7812 eligible patients, 6852 received treatments of interest for SSc and 2404 (30.8%) received IMT during the first year after SSc diagnosis. In the first year after diagnosis, the most common claims were for antibiotics (61.7%), opioids (50.6%), glucocorticoids (46.5%), and proton pump inhibitors (35.4%); the most common organs involved with complications among patients with SSc were lung (30.5%), heart (17.4%), and gastrointestinal tract (22.4%); the most common signs or symptoms were musculoskeletal (16.1%) and fatigue (10.5%); 1035 patients (15.1%) had infections and 14 (0.2%) had malignancies. Among patients who received IMT, 43.8% received at least hydroxychloroquine and 21.1% received at least methotrexate; 460 patients switched to a second IMT, 23.0% to at least methotrexate and 22.8% to at least mycophenolate mofetil. The most common comorbidities reported with first IMT were in lung (11.8%), overlap syndrome (8.4%), heart (5.3%), and gastrointestinal (6.8%) categories. CONCLUSION: One-third of patients with SSc in the healthcare claims population received IMTs during the first year after diagnosis. However, patients who received IMTs had disease manifestations similar to those of the overall SSc healthcare claims population.

Risk of malignancy associated with use of tocilizumab versus other biologics in patients with rheumatoid arthritis: A multi-database cohort study.

OBJECTIVES: To examine the rate of incident malignancies excluding non-melanoma skin cancer (NMSC) in patients with rheumatoid arthritis (RA) newly treated with tocilizumab versus other biologic drugs. METHODS: We conducted a cohort study using data from 3 U.S. insurance claims databases - Medicare (2010-2015), 'IMS' PharMetrics Plus (2011-2015) and Truven 'MarketScan' (2011-2015). Adults with RA who newly started tocilizumab or a TNF inhibitor (TNFi) after failing a different TNFi, abatacept or tofacitinib were included. The primary outcome was development of any malignancies excluding NMSC. For confounding control, tocilizumab starters were propensity score (PS)-matched to TNFi starters with a variable ratio of 1:3 within each database. Hazard ratios (HR) from the 3 PS-matched cohorts were combined by an inverse variance-weighted, fixed-effects model. We conducted a secondary analysis where we compared tocilizumab initiators with abatacept initiators. RESULTS: We included 13,102 tocilizumab initiators PS-matched to 26,727 TNFi initiators in all three databases. The incidence rate of malignancies per 1,000 person-years ranged from 8.27 (IMS) to 23.18 (Medicare) in the tocilizumab group and from 9.64 (MarketScan) to 21.46 (Medicare) in the TNFi group. The risk of incident malignancies was similar between tocilizumab and TNFi initiators across all three databases, with a combined HR of 0.98 (95%CI 0.80-1.19) in tocilizumab versus TNFi. The secondary analysis comparing tocilizumab versus abatacept showed similar results (combined HR 0.97, 95%CI 0.74-1.27). CONCLUSIONS: This large multi-database cohort study found no difference in the risk of malignancies excluding NMSC in RA patients who newly started tocilizumab compared with TNFi or abatacept.

Adverse Events in Giant Cell Arteritis and Rheumatoid Arthritis Patient Populations: Analyses of Tocilizumab Clinical Trials and Claims Data.

INTRODUCTION: The safety profile of tocilizumab (TCZ) in patients with rheumatoid arthritis (RA) is well established. TCZ was approved to treat giant cell arteritis (GCA) in 2017 in the USA and Europe, and its safety profile in patients with GCA continues to be defined. The objective of this analysis was to examine incidence rates (IRs) of adverse events of special interest (AESI) occurring during the TCZ clinical development program and in healthcare claims data in patients with GCA or RA. METHODS: TCZ-naïve patients with GCA or RA were identified in the MarketScan administrative healthcare claims database. TCZ-treated patients with GCA from the GiACTA trial and TCZ-treated patients with RA from pooled clinical trial data were analyzed. The IRs of AESI (AESI IRs) were calculated for all cohorts. In the claims cohorts, risks of AESI were estimated using Poisson regression. RESULTS: TCZ-naïve claims cohorts comprised 4804 patients with GCA [mean (standard deviation) age 73.4 (9.8) years; follow-up 3.9 (3.1) years] and 15,164 patients with RA [age 60.3 (8.2) years; follow-up, 4.5 (2.8) years]. TCZ-treated clinical trial cohorts comprised 149 patients with GCA [age 69.5 (8.4) years; exposure approx. 138 patient-years (PY)] and 7647 with RA [age 52 (12.6) years; exposure approx. 22,394 PY]. The IRs of infections, stroke, malignancies, myocardial infarction, and gastrointestinal perforations in the GCA claims cohort exceeded those in the RA claims cohort; the risk of AESI (adjusted for age and glucocorticoid use) was higher in patients with GCA than in those with RA. Similar patterns to the claims cohorts in terms of the AESI IRs were observed in clinical trial cohorts, although the number of events was limited in the GCA trial cohort. CONCLUSION: Higher IRs of AESI were observed in patients with GCA versus those with RA in both TCZ-naïve and -treated cohorts. Differences in underlying disease, age, and glucocorticoid use may influence AESI incidence, irrespective of intervention. FUNDING: This study was funded by F. Hoffmann-La Roche Ltd and Genentech, Inc. Article processing charges were funded by F. Hoffmann-La Roche Ltd. Plain language summary is available for this article.

Risk of serious infections in tocilizumab versus other biologic drugs in patients with rheumatoid arthritis: a multidatabase cohort study.

OBJECTIVE: To investigate the rate of serious bacterial, viral or opportunistic infection in patients with rheumatoid arthritis (RA) starting tocilizumab (TCZ) versus tumour necrosis factor inhibitors (TNFi) or abatacept. METHODS: Using claims data from US Medicare from 2010 to 2015, and IMS and MarketScan from 2011 to 2015, we identified adults with RA who initiated TCZ or TNFi (primary comparator)/abatacept (secondary comparator) with prior use of ≥1 different biologic drug or tofacitinib. The primary outcome was hospitalised serious infection (SI), including bacterial, viral or opportunistic infection. To control for >70 confounders, TCZ initiators were propensity score (PS)-matched to TNFi or abatacept initiators. Database-specific HRs were combined by a meta-analysis. RESULTS: The primary cohort included 16 074 TCZ PS-matched to 33 109 TNFi initiators. The risk of composite SI was not different between TCZ and TNFi initiators (combined HR 1.05, 95% CI 0.95 to 1.16). However, TCZ was associated with an increased risk of serious bacterial infection (HR 1.19, 95% CI 1.07 to 1.33), skin and soft tissue infections (HR 2.38, 95% CI 1.47 to 3.86), and diverticulitis (HR 2.34, 95% CI 1.64 to 3.34) versus TNFi. An increased risk of composite SI, serious bacterial infection, diverticulitis, pneumonia/upper respiratory tract infection and septicaemia/bacteraemia was observed in TCZ versus abatacept users. CONCLUSIONS: This large multidatabase cohort study found no difference in composite SI risk in patients with RA initiating TCZ versus TNFi after failing ≥1 biologic drug or tofacitinib. However, the risk of serious bacterial infection, skin and soft tissue infections, and diverticulitis was higher in TCZ versus TNFi initiators. The risk of composite SI was higher in TCZ initiators versus abatacept.

Comparative effectiveness of tocilizumab versus TNF inhibitors as monotherapy or in combination with conventional synthetic disease-modifying antirheumatic drugs in patients with rheumatoid arthritis after the use of at least one biologic disease-modifying antirheumatic drug: analyses from the pan-European TOCERRA register collaboration.

OBJECTIVE: To compare the effectiveness of tocilizumab (TCZ) and tumour necrosis factor (TNF) inhibitors (TNFi) as monotherapy or in combination with conventional synthetic disease-modifying antirheumatic drugs (DMARDs) in patients with rheumatoid arthritis (RA) after the use of at least one biologic DMARD (bDMARD). METHODS: We included patients with RA having used at least one bDMARD from 10 European registries. We compared drug retention using Kaplan-Meier and Cox models and Clinical Disease Activity Index (CDAI) change over time with mixed-effects models for longitudinal data. The proportions of CDAI remission and low disease activity (LDA) at 1 year were compared using LUNDEX correction. RESULTS: 771 patients on TCZ as monotherapy (TCZ mono), 1773 in combination therapy (TCZ combo), 1404 on TNFi as monotherapy (TNFi mono) and 4660 in combination therapy (TNFi combo) were retrieved. Crude median retention was higher for TCZ mono (2.31 years, 95% CI 2.07 to 2.61) and TCZ combo (1.98 years, 95% CI 1.83 to 2.11) than TNFi combo (1.37 years, 95% CI 1.30 to 1.45) and TNFi mono (1.31 years, 95% CI 1.18 to 1.47). In a country and year of treatment initiation-stratified, covariate-adjusted analysis, hazards of discontinuation were significantly lower among patients on TCZ mono or combo compared with patients on TNFi mono or combo, and TNFi combo compared with TNFi mono, but similar between TCZ mono and combo. Average adjusted CDAI change was similar between groups. CDAI remission and LDA rates were comparable between groups. CONCLUSION: With significantly longer drug retention and similar efficacy to TNFi combo, TCZ mono or combo are reasonable therapeutic options in patients with inadequate response to at least one bDMARD.

Cardiovascular Safety of Tocilizumab Versus Tumor Necrosis Factor Inhibitors in Patients With Rheumatoid Arthritis: A Multi-Database Cohort Study.

OBJECTIVE: While tocilizumab (TCZ) is known to increase low-density lipoprotein (LDL) cholesterol levels, it is unclear whether TCZ increases cardiovascular risk in patients with rheumatoid arthritis (RA). This study was undertaken to compare the cardiovascular risk associated with receiving TCZ versus tumor necrosis factor inhibitors (TNFi). METHODS: To examine comparative cardiovascular safety, we conducted a cohort study of RA patients who newly started TCZ or TNFi using claims data from Medicare, IMS PharMetrics, and MarketScan. All patients were required to have previously used a different TNFi, abatacept, or tofacitinib. The primary outcome measure was a composite cardiovascular end point of hospitalization for myocardial infarction or stroke. TCZ initiators were propensity score matched to TNFi initiators with a variable ratio of 1:3 within each database, controlling for >65 baseline characteristics. A fixed-effects model combined database-specific hazard ratios (HRs). RESULTS: We included 9,218 TCZ initiators propensity score matched to 18,810 TNFi initiators across all 3 databases. The mean age was 72 years in Medicare, 51 in PharMetrics, and 53 in MarketScan. Cardiovascular disease was present at baseline in 14.3% of TCZ initiators and 13.5% of TNFi initiators. During the study period (mean ± SD 0.9 ± 0.7 years; maximum 4.5 years), 125 composite cardiovascular events occurred, resulting in an incidence rate of 0.52 per 100 person-years for TCZ initiators and 0.59 per 100 person-years for TNFi initiators. The risk of cardiovascular events associated with TCZ use versus TNFi use was similar across all 3 databases, with a combined HR of 0.84 (95% confidence interval 0.56-1.26). CONCLUSION: This multi-database population-based cohort study showed no evidence of an increased cardiovascular risk among RA patients who switched from a different biologic drug or tofacitinib to TCZ versus to a TNFi.

Incidence of Gastrointestinal Perforations in Patients with Rheumatoid Arthritis Treated with Tocilizumab from Clinical Trial, Postmarketing, and Real-World Data Sources.

INTRODUCTION: The aim of this study was to use multiple data sources to update information on gastrointestinal perforations (GIPs) during tocilizumab (TCZ) treatment in patients with rheumatoid arthritis (RA). METHODS: Reporting rates of GIP events were estimated from three distinct patient data sets: a TCZ-IV RA clinical trial all-exposure population, a global TCZ postmarketing safety database population, and a US healthcare claims database population of patients with RA, including patients who received TCZ, anti-tumor necrosis factor (aTNF) agents, or abatacept. RESULTS: The clinical trial, global postmarketing, and healthcare claims populations provided 17,906, 382,621, and 3268 patient-years (PYs) of TCZ exposure, respectively. GIP incidence rates [95% confidence interval (CI)] were 1.9 (1.3-2.7), 1.2 (1.1-1.3), and 1.8 (0.7-4.0; specific definition) to 2.8 (1.3-5.2; sensitive definition) per 1000 PYs for the clinical trial, postmarketing, and healthcare claims populations, respectively. The GIP incidence rate (95% CI) for the comparator aTNF healthcare claims population ranged from 0.6 (0.3-1.2) to 0.9 (0.5-1.5) per 1000 PYs, for an absolute rate difference between TCZ and aTNFs of 1.2 (-0.3 to 2.5) to 1.9 (0.0-3.7) per 1000 PYs, corresponding to a number needed to harm between 533 and 828. CONCLUSION: The TCZ GIP event rates from multiple data sources were consistent with previously reported rates, did not increase over time, and were significantly associated with the number of prior biologics. Comparison of GIP incidence rates among patients with prior biologic exposure suggests that, for every 1000 patients treated with TCZ per year, an additional 1-2 GIP events might occur compared with patients treated with aTNFs. FUNDING: Roche.

Incidence and complications of interstitial lung disease in users of tocilizumab, rituximab, abatacept and anti-tumor necrosis factor α agents, a retrospective cohort study.

INTRODUCTION: Interstitial lung disease (ILD) is a common extra-articular condition in rheumatoid arthritis (RA), but few studies have systematically investigated its incidence and risk factors in patients receiving anti-tumor necrosis factor-alpha (anti-TNFα) agents or alternate mechanisms of action (MOAs) (e.g., T-cell, B-cell, and interleukin-6 inhibitors). METHODS: RA patients at least 18 years old were selected from the MarketScan databases (2010-2012) if they had at least one prescription/administration of abatacept, rituximab, tocilizumab, or anti-TNF after having discontinued a different biologic agent and meeting enrollment criteria. Cox models estimated the risk of incident ILD and ILD-related hospitalization. Sensitivity analyses used an alternate ILD case definition. RESULTS: We identified 13,795 episodes of biologic exposure in 11,219 patients. Mean (standard deviation) follow-up was 0.7 (0.5) years. Patients receiving alternate MOA agents were more likely to have had recent exposure to steroids, prior exposure to a greater number of biologics, and history of ILD, anemia, chronic obstructive pulmonary disease, and other pulmonary conditions. When the sensitive definition was used, unadjusted ILD incidence rates (95% confidence interval, or CI) ranged from 4.0 (1.6-8.2, abatacept) to 12.2 (5.6-23.2, infliximab) per 1000 person-years. Being older (hazard ratio (HR) 3.5; 95% CI 2.1-6.0), being male (HR 3.1; 95% CI 1.2-8.4), and having another pulmonary condition (HR 4.8; 95% CI 1.7-13.7) were associated with increased ILD incidence in either sensitive and/or specific models. There were no significant differences by biologic class. Hospitalization rates (95% CI) when the sensitive definition was used ranged from 55.6 (6.7-200.7, tocilizumab) to 262.5 (71.5-672.2, infliximab). In Cox models, recent methotrexate exposure was associated with reduced ILD hospitalization (HR 0.16; 95% CI 0.06-0.46), whereas being male (HR 2.5; 95% CI 1.3-4.8) and having had a hospitalization for asthma (HR 3.4; 95% CI 1.2-9.8) or ILD/pneumonia (HR 2.3; 95% CI 1.1-4.7) in the 12 months prior to index were associated with increased hospitalization risk. CONCLUSIONS: There were no significant differences in the risk of ILD and its related complications between RA patients receiving anti-TNFα agents and those receiving alternate MOA agents. Further studies are needed that account for differences in baseline characteristics in order to fully evaluate the risk of ILD and its complications.

The role of the FcGRIIIa polymorphism in modifying the association between treatment and outcome in patients with rheumatoid arthritis treated with rituximab versus TNF-α antagonist therapies.

OBJECTIVES: There is an association between the FcGRIIIa polymorphism and the development of rheumatoid arthritis (RA). Studies in non-Hodgkin lymphoma demonstrated a relationship between the FcGRIIIa polymorphism and response to anti-CD20 therapies. However, there are currently no published studies evaluating the relationship between this polymorphism and therapeutic response to treatment with anti-CD20 agents such as rituximab in RA. We conducted a study to identify if the FcGRIIIa polymorphism is associated with rituximab efficacy in patients with RA. METHODS: Subjects with RA treated with rituximab (cases, n=158) or TNF-α antagonist (controls, n=390) were recruited from the Consortium of Rheumatology Researchers of North America. The FcGRIIIa variant was genotyped for all subjects and longitudinal patient outcomes were assessed using the clinical disease activity index (CDAI). We used a linear regression random effects model to estimate CDAI scores over time with multiple time points nested within patient. RESULTS: Similar changes in CDAI were observed across the three FcGRIIIa genotypes for the rituximab treated group (VV [4.56, SD 14.5]), VF (7.44, SD 14.9) and FF (4.75, SD 10.8) (p >0.05)] and the TNF-α antagonist therapy treated group [VV (5.12, SD 14.6), VF (6.77, SD 15.9), and FF (4.36, SD 18.2) (p >0.05). Overall, there were similar changes in CDAI at 6 months for rituximab (-5.91, SD 14.1) and anti-TNFs (-5.77, SD 15.5) (p >0.05). The FcGRIIIa genotype was not significantly associated (p=0.86) with treatment response in rituximab treated RA patients compared with TNF-α antagonist therapy treated patients. Baseline CDAI and number of prior biologics were significant predictors of clinical response over time. CONCLUSIONS: Our finding emphasises the idea that determinants of response to treatment are complex and may be dependent upon genetic and phenotypic interactions. Future studies should analyse the interaction between the FcGRIIIa gene, other neighbouring polymorphisms and other phenotypic and environmental factors.

Factors predicting change in frequency of heavy drinking days among alcohol-dependent participants in the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC).

AIMS: To discover the predictors of change in the frequency of heavy drinking (HD) over a 4-year period in alcohol dependent (AD)-individuals identified in the general population, namely, among participants of the US National Epidemiologic Survey on Alcohol and Related Conditions interviewed at Wave 1 (2001-2002) and at Wave 2 (2004-2005). METHODS: The study cohort included subjects meeting DSM-IV criteria for AD in the past year at Wave 1 (n = 1484), who were present at Wave 2 (n = 1172) and had complete data on factors of interest (n = 1123). Frequency of HD was defined as the number of HD days (HDD) (≥5 drinks per day for men and ≥4 for women). Change in frequency of HDD from baseline (Wave 1) to ~3 years later (Wave 2) was determined. An analysis of covariance model (ANCOVA), adjusting for baseline HDD, was used to examine individual factors associated with change in frequency of HDD, while a multivariable regression model was employed to assess factors associated with change in frequency of HDD simultaneously. RESULTS: Overall, there was a decrease in mean (SE) HDD [from 119.4 (1.8) at Wave 1 to 82.5 (2.1) at Wave 2, P < 0.0001]. Compared with smokers, non-smokers had a mean (SE) HDD reduction of 13.4 (6.7), P < 0.05. AD criteria of tolerance was significantly associated (P < 0.05) with less reduction in HDD. Change in depression/dysthymia status was associated with greater reduction in HDD in the ANCOVA model, but not the fully adjusted multivariable model. CONCLUSION: Findings from this study suggest that smoking and AD criteria of tolerance are important factors for long-term follow-up of AD patients and they should influence the selection of the kinds of interventions required for AD patients to achieve maximal therapeutic benefit.

Biologic disease-modifying drug treatment patterns and associated costs for patients with rheumatoid Arthritis.

OBJECTIVE: To assess the influence of biologic treatment patterns on healthcare costs for patients with rheumatoid arthritis (RA) initiating tumor necrosis factor-α (TNF-α) antagonist therapy. METHODS: Patients with 2 RA diagnoses (International Classification of Diseases, 9th ed, 714.xx), and without psoriasis or Crohn's disease, were identified in a US employer-based insurance claims database. A sample of 2545 was constructed based on an index event of initiating TNF-α antagonist therapy and 30 months of continuous enrollment. Baseline characteristics were assessed in the 6-month pre-index period and treatment patterns were determined during the 12-month post-index period. Medical service and prescription drug costs were analyzed for Months 13-24 using multivariate regression analysis to control for baseline characteristics and time-varying confounding associated with treatment and disease severity. RESULTS: In the first year after TNF-α initiation, 89% used a single TNF-α antagonist; only 9% and 2% had switched TNF-α antagonists or received non-TNF biologic disease-modifying antirheumatic drugs, respectively. Descriptive analyses revealed pairwise differences between groups (p < 0.05) in baseline characteristics (comorbidities, RA-related procedure use, and prescription drug use). Controlling for observed baseline characteristics, costs were greater for those treated with multiple vs single TNF-α antagonists: annual RA-related prescription drug costs ($8,340 vs $7,058; p = 0.012), RA-related healthcare costs ($15,048 vs $13,312; p = 0.008), and total healthcare costs ($26,697 vs $21,381; p < 0.001). CONCLUSION: In this sample, the majority of patients with RA were treated with a single TNF-α antagonist over the first year on therapy. For those who switched therapy, Year 2 RA-related and total direct healthcare costs were higher, adjusting for claims-based measures of RA disease severity.