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.

Missed opportunities for treatment of inflammatory arthritis and factors associated with non-treatment: An observational cohort study in United States Veterans with rheumatoid arthritis, psoriatic arthritis, or ankylosing spondylitis.

OBJECTIVE: To identify factors associated with non-treatment with biologic and non-biologic disease modifying anti-rheumatic drugs (DMARDs) during the 12 months after initial inflammatory arthritis (IA) diagnosis. METHODS: We identified Veterans with incident IA diagnosed in 2007-2019. We assessed time to treatment with Kaplan-Meier curves. We identified associations between non-treatment and factors relating to patients, providers, and the health system with multivariate Generalized Estimation Equation (GEE) log-Poisson. Subgroup analyses included IA subtypes (rheumatoid arthritis [RA], psoriatic arthritis [PsA], and ankylosing spondylitis [AS]) and timeframes of the initial IA diagnosis (2007-11, 2012-15, and 2016-19). RESULTS: Of 18,318 study patients, 40.7 % did not receive treatment within 12 months after diagnosis. In all patients, factors associated with non-treatment included Black race (hazard ratio, 95 % confidence interval: 1.13, 1.08-1.19), Hispanic ethnicity (1.14, 1.07-1.22), Charlson Comorbidity Index ≥2, (1.15, 1.11-1.20), and opiate use (1.09, 1.05-1.13). Factors associated with higher frequency of DMARD treatment included married status (0.86, 0.81-0.91); erosion in joint imaging report (HR: 0.86, 0.81-0.91); female diagnosing provider (0.90, CI: 0.85-0.96), gender concordance between patient and provider (0.91, CI: 0.86-0.97), and diagnosing provider specialty of rheumatology (0.53, CI: 0.49-0.56). CONCLUSION: A high proportion of Veterans with IA were not treated with a biologic or non-biologic DMARD within one year after their initial diagnosis. A wide range of factors were associated with non-treatment of IA that may represent missed opportunities for improving the quality of care through early initiation of DMARDs.

Clinical and Economic Benefit of Achieving Disease Control in Psoriatic Arthritis and Ankylosing Spondylitis: A Retrospective Analysis from the OM1 Registry.

BACKGROUND: There is limited evidence on the clinical and economic benefit of achieving disease control in psoriatic arthritis (PsA) and ankylosing spondylitis (AS), thus we aimed to assess the impact of disease control on healthcare resource use (HCRU) and direct medical costs among US patients with PsA or AS over 1 year. METHODS: Data were derived from the US OM1 PsA/AS registries (PsA: 1/2013-12/2020; AS: 01/2013-4/2021) and the Optum Insight Clinformatics® Data Mart to identify adult patients with PsA or AS. Two cohorts were created: with disease control and without disease control. Disease control was defined as modified Disease Activity Index for Psoriatic Arthritis (DAPSA28) ≤ 4 for PsA and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) < 4 for AS. Outcomes were all-cause inpatient, outpatient, and emergency department (ED) visits and associated costs over a 1-year follow-up period. Mean costs per person per year (PPPY) were assessed descriptively and adjusted odds ratios (aOR) with 95% confidence intervals (CI) were estimated for the likelihood of HCRU by logistic regression. RESULTS: The study included 1235 PsA (with disease control: N = 217; without: N = 1018) and 581 AS patients (with disease control: N = 342; without: N = 239). Patients without disease control were more likely to have an inpatient (aOR [95% CI]; PsA: 3.0 [0.9, 10.1]; AS: 7.7 [2.3, 25.1]) or ED (PsA: 1.6 [0.6, 4.2]; AS: 3.5 [1.5, 8.3]) visit than those with disease control. Those without disease control, vs. those with disease control, had greater PPPY costs associated with inpatient (PsA: $1550 vs. $443), outpatient (PsA: $1789 vs. $1327; AS: $2498 vs. $2023), and ED (PsA: $114 vs. $57; AS: $316 vs. $50) visits. CONCLUSIONS: Findings from this study demonstrate lower disease activity among patients with PsA and AS is associated with less HCRU and lower costs over the following year.

Healthcare Costs of Not Achieving Remission in Patients with Rheumatoid Arthritis in the United States: A Retrospective Cohort Study.

INTRODUCTION: To compare all-cause and rheumatoid arthritis (RA)-related healthcare costs and resource use in patients with RA who do not achieve remission versus those who achieve remission, using clinical practice data. METHODS: Data were derived from Optum electronic health records linked to claims from commercial and Medicare Advantage health plans. Two cohorts were created: remission and non-remission. Remission was defined as Disease Activity Score 28-joint count with the C-reactive protein level or erythrocyte sedimentation rate (DAS28-CRP/ESR) < 2.6 or Routine Assessment of Patient Index Data 3 (RAPID3 ≤ 3.0). Outcomes were all-cause and RA-related costs and resource use during a 1-year follow-up period. A weighted generalized linear regression and negative binomial regression were used to estimate adjusted annual costs and resource use, respectively, controlling for confounding factors, including patient and socio-demographic characteristics. RESULTS: Data from 335 patients (remission: 125; non-remission: 210) were analyzed. Annual all-cause total costs were significantly less in the remission versus non-remission cohort ($30,427 vs. $38,645, respectively; cost ratio [CR] = 0.79; 95% CI 0.63, 0.99). All-cause resource use (mean number of visits) was less in the remission versus non-remission cohort: inpatient (0.23 vs. 0.63; visit ratio [VR] = 0.36; 95% CI 0.19, 0.70), emergency department (0.36 vs. 0.77; VR = 0.47; 95% CI 0.30, 0.74), and outpatient visits (20.7 vs. 28.5; VR = 0.73; 95% CI 0.62, 0.86). Annual RA-related total costs were similar in both cohorts; however, RA-related medical costs were numerically lower in the remission versus non-remission cohort ($8,594 vs. $10,002, respectively; CR = 0.86; 95% CI 0.59, 1.25). RA-related resource use was less in the remission versus non-remission cohort. CONCLUSIONS: Significant economic burden was associated with patients who did not achieve remission compared with those who did achieve remission.

Economic Benefit from Improvements in Quality of Life with Upadacitinib: Comparisons with Tofacitinib and Methotrexate in Patients with Rheumatoid Arthritis.

INTRODUCTION: To compare the economic benefit of upadacitinib combination therapy versus tofacitinib combination therapy and upadacitinib monotherapy versus methotrexate monotherapy from improvements in health-related quality of life (HRQOL) in patients with rheumatoid arthritis (RA). METHODS: Data were analyzed from two trials of upadacitinib (SELECT-NEXT and SELECT-MONOTHERAPY) and one trial of tofacitinib (ORAL-Standard) that collected HRQOL measurements using the Short Form 36 (SF-36) Health Survey in patients with RA. Direct medical costs per patient per month (PPPM) for patients receiving upadacitinib 15 mg once daily and methotrexate were derived from observed SF-36 Physical (PCS) and Mental Component Summary (MCS) scores in the SELECT trials using a regression algorithm. Direct medical costs PPPM for patients receiving tofacitinib 5 mg twice daily were obtained from a published analysis of SF-36 PCS and MCS scores observed in the ORAL-Standard trial. Short-term (12-14 weeks) and long-term (48 weeks) estimates of direct medical costs PPPM were compared between upadacitinib and tofacitinib and between upadacitinib and methotrexate. RESULTS: Over 12 weeks, direct medical costs PPPM were $252 lower (95% CI $72, $446) for upadacitinib-treated patients versus tofacitinib-treated patients. Medical costs PPPM at weeks 24 and 48 and cumulative costs over the entire 48-week period (difference $1759; 95% CI $1162, $2449) were significantly lower for upadacitinib than for tofacitinib. Over 14 weeks, direct medical costs PPPM were $399 lower (95% CI $158, $620) for patients treated with upadacitinib monotherapy compared with those treated with methotrexate alone. Direct medical costs at week 48 and cumulative costs over the entire 48-week period (difference $2044; 95% CI $1221, $2846) were significantly lower for upadacitinib monotherapy compared with methotrexate alone. CONCLUSION: In the short and long term, upadacitinib combination therapy versus tofacitinib combination therapy and upadacitinib monotherapy versus methotrexate monotherapy were associated with significantly lower direct medical costs for patients with RA. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02675426, NCT02706951, and NCT00853385.

Economic burden of fatigue or morning stiffness among patients with rheumatoid arthritis: a retrospective analysis from real-world data.

Objective: Determine healthcare resource utilization (HCRU) and costs associated with fatigue and stiffness among patients with rheumatoid arthritis (RA).Methods: A retrospective claims analysis compared RA patients with fatigue or stiffness to matched RA control patients with neither. Claims from a large US commercial insurance database identified new cases of stiffness/fatigue among newly diagnosed patients. Study patients had ≥2 medical claims for RA ≥45 days apart, continuous insurance coverage ≥12 months before RA index (baseline period) and ≥12 months after fatigue/stiffness index (follow-up period). Controls had no diagnosis of fatigue or stiffness ≥12 months before index. Cases had ≥1 claim of fatigue/stiffness after RA index; the first such claim was the index date. Multivariate logistic regressions, adjusting for baseline demographics, comorbidities, medication use and HCRU, were used to predict the propensity of having a fatigue/stiffness diagnosis. Controls were propensity-score matched to cases. Generalized linear models estimated all-cause and RA-specific costs associated with resource use as well as prescription drugs, adjusting for any unbalanced covariates after propensity-score matching.Results: Approximately 32% of newly diagnosed RA patients suffer from fatigue/stiffness. Matched cohorts were analyzed: fatigue vs. control; stiffness vs. control; fatigue and stiffness vs. control. After RA diagnosis, hospitalizations increased: 83% for fatigue, 117% for stiffness and 148% for both; total office visits increased 63%, 113% and 135%, respectively. Greater HCRU yielded significantly greater (all p < .001) per-patient-per-year hospitalization costs vs. matched controls: fatigue ($2554 vs. $1293); stiffness ($2792 vs. $892); fatigue and stiffness ($3322 vs. $1033). Per-patient-per-year costs of office visits increased significantly (all p < .001) vs. matched controls: fatigue ($1373 vs. $908); stiffness ($1580 vs. $761); fatigue and stiffness ($1989 vs. $921).Conclusions: RA patients with fatigue and/or stiffness report more HCRU and incur significantly higher medical costs than RA patients without them.

Cost-utility analyses of targeted immunomodulators in rheumatoid arthritis: systematic review.

Aims: Cost-utility (CU) modeling is a common technique used to determine whether new treatments represent good value for money. As with any modeling exercise, findings are a direct result of methodology choices, which may vary widely. Several targeted immuno-modulators have been launched in recent years to treat moderate-to-severe rheumatoid arthritis (RA) which have been evaluated using CU methods. Our objectives were to identify common and innovative modeling choices in moderate-to-severe RA and to highlight their implications for future models in RA.Materials and methods: A systematic literature search was conducted to identify CU models in moderate-to-severe RA published from January 2013 to June 2019. Studies must have included an active comparator and used quality-adjusted life-years (QALYs) as the common measure of effectiveness. Modeling methods were characterized by stakeholder perspective, simulation type, mapping between parameters, and data sources.Results: Thirty-one published modeling studies were reviewed spanning 13 countries and 9 drugs, with common methodological choices and innovations observed among them. Over the evaluated time period, we observed common methods and assumptions that are becoming more prominent in the RA CU modeling landscape, including patient-level simulations, two-stage models combining trial results and real-world evidence, real-world treatment durations, long-term health consequences, and Health Assessment Questionnaire (HAQ)-related hospitalization costs. Models that consider the societal perspective are increasingly being developed as well.Limitations: This review did not consider studies that did not report QALYs as a utility measure, models published only as conference abstracts, or cost-consequence models that did not report an incremental CU ratio.Conclusions: CU modeling for RA increasingly reflects real-world conditions and patient experiences which are anticipated to provide better information in the assessment of health technologies. Future CU models in RA should consider applying the observed advances in modeling choices to optimize their CU predictions and simulation of real-world outcomes.

Incidence of Serious Infections and Design of Utilization and Safety Studies for Biologic and Biosimilar Surveillance.

BACKGROUND: There is a need for postmarketing evidence generation for novel biologics and biosimilars. OBJECTIVE: To assess the feasibility, strengths, and limitations of the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) Distributed Research Network (DRN) to examine the utilization and comparative safety of immune-modulating agents among patients with autoimmune diseases. METHODS: We conducted a retrospective cohort study among patients enrolled in health insurance plans participating in the BBCIC DRN between January 1, 2006, and September 30, 2015. Eligible patients were adult (≥18 years) new users of a disease-modifying nonbiologic and/or biologic agent with a prior diagnosis of rheumatoid arthritis (RA), other inflammatory conditions (psoriasis, psoriatic arthritis, ankylosing spondylitis), or inflammatory bowel disease (IBD). Follow-up started at treatment initiation and ended at the earliest of outcome occurrence (serious infection); treatment discontinuation; or switching, death, disenrollment, or end of study period. The study leveraged the FDA Sentinel System infrastructure for data management and analysis; descriptive statistics of patient characteristics and unadjusted incidence rates of study outcomes during follow-up were calculated. RESULTS: Eligible patient drug episodes included 111,611 with RA (75% female), 61,050 with other inflammatory conditions (51% female), and 30,628 with IBD (52% female). Across all 3 cohorts, approximately half of the patient drug episodes initiated a biologic (50% in RA; 60% in psoriasis, psoriatic arthritis, ankylosing spondylitis; and 55% in IBD). The crude incidence rate of serious infection was 9.8 (9.5-10.0) cases per 100 person-years in RA, 7.1 (6.8-7.5) in other inflammatory conditions, and 14.2 (13.6-14.8) in IBD patients. CONCLUSIONS: This study successfully identified large numbers of new users of biologics and produced results that were consistent with those from earlier published studies. The BBCIC DRN is a potential resource for surveillance of biologics. DISCLOSURES: This study was funded by the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC). HealthCore conducted this study in collaboration with Harvard Pilgrim Health Care. Zhang and Sridhar were employed by HealthCore at the time of this study. Haynes is employed by HealthCore funded by PCORI, the NIH, and the FDA. Barr and Eichelberger were employed by AMCP at the time of this study. Lockhart is employed by the BBCIC. Holmes and Clewell are employed by AbbVie. Accrott is an employee of and shareholder in Amgen. Marshall and Brown are employed by Harvard Pilgrim Health Care. Barr is a shareholder in Roche/Genentech. Curtis has received research grants from and consults with the following: Amgen, AbbVie, BMS, CORRONA, Lilly, Janssen, Myriad, Pfizer, Roche, Regeneron, and UCB. Brown has received research grants from GSK and Pfizer and consulting fees from Bayer, Roche, and Jazz Pharmaceuticals, along with funding from the Reagan-Udall Foundation for the FDA to conduct studies for medical product manufacturers, including Eli Lilly, Novartis, Abbvie, and Merck. Brown is also funded by PCORI, the NIH, and the FDA. McMahill-Walraven subcontracts with Harvard Pilgrim Health Care Institute for public health and safety surveillance distributed data network activtities and with the FDA, GSK, and Pfizer. She also reports fees from Reagan Udall Foundation for the FDA and the Patient Centered Outcomes Research Institute.

Case-control analysis of ambulance, emergency room, or inpatient hospital events for epilepsy and antiepileptic drug formulation changes.

PURPOSE: Although antiepileptic drugs (AEDs) with multisource generic alternatives are becoming more prevalent, no case-control studies have been published examining multisource medication use and epilepsy-related outcomes. This study evaluated the association between inpatient/emergency epilepsy care and the occurrence of a recent switch in AED formulation. METHODS: A case-control analysis was conducted utilizing the Ingenix LabRx Database. Eligible patients were 12-64 years of age, received >or=145 days of AEDs in the preindex period, had continuous eligibility for 6 months preindex, and no prior inpatient/emergency care. Cases received care between 7/1/2006 and 12/31/2006 in an ambulance, emergency room, or inpatient hospital with a primary epilepsy diagnosis. Controls had a primary epilepsy diagnosis in a physician's office during the same period. The index date was the earliest occurrence of care in each respective setting. Cases and controls were matched 1:3 by epilepsy diagnosis and age. Odds of a switch between "A-rated" AEDs within 6 months prior to index were calculated. RESULTS: Cases (n = 416) had 81% greater odds of having had an A-rated AED formulation switch [odds ratio (OR) = 1.81; 95% confidence interval (CI) = 1.25 to 2.63] relative to controls (n = 1248). There were no significant differences between groups regarding demographics or diagnosis. Significant differences were found with regard to medical coverage type (case Medicaid = 4.6%, control Medicaid = 1.8%, p = 0.002). Post hoc analysis results excluding Medicaid recipients remained significant and concordant with the original analysis. DISCUSSION: This analysis found an association between patients receiving epilepsy care in an emergency or inpatient setting and the recent occurrence of AED formulation switching involving A-rated generics.

Direct medical costs for patients seeking emergency care for losses of epilepsy control in a U.S. managed care setting.

The objective of this retrospective claims database study was to compare the costs of care from a U.S. payer perspective before and after epilepsy treatment in emergent care settings and, secondarily, to describe the frequency of toxic effects and physical injuries occurring on the date of the emergent care. Nine and four-tenths percent of patients receiving emergent care for epilepsy (114/1213) had an injury or adverse antiepileptic drug effect on the same date. The majority of incidents were superficial injuries and contusions (28%), fractures (21%), open wounds or injury to blood vessels (19%), intracranial injury (10%), and/or medication toxicity (10%). Both non-epilepsy-related (US$12,745.56) and epilepsy-related (US$2013.62) direct medical costs of care pre-index were significantly different from those post-index (US$15,274.95 and US$7087.53, respectively). The cost of care for possible reestablishment of epilepsy control and treatment of co-occurring injuries is significant when compared with that for the period prior to seizure.

Economic Burden of Switching to Different Biologic Therapies Among Tumor Necrosis Factor Inhibitor-Experienced Patients with Psoriatic Arthritis.

INTRODUCTION: Patients with psoriatic arthritis (PsA) who receive an initial tumor necrosis factor inhibitor (TNFi) may switch to another TNFi or a non-TNFi biologic therapy. This study compared the healthcare resource use (HRU), expenditures, and time to discontinuation among TNFi-experienced patients with PsA who switched to different biologic therapies in the United States (US). METHODS: Adults with PsA who discontinued an initial TNFi (adalimumab, etanercept, infliximab, golimumab, or certolizumab pegol) and switched to another TNFi or a non-TNFi (ustekinumab or secukinumab) were identified in the Symphony Health Solutions database [Quarter (Q)1 2010-Q2 2017]. Eligible patients had claims data activity for ≥ 12 months before (baseline) and after (study period) the switching date. All-cause HRU, costs (2017 US dollars), and time to discontinuation during the study period were compared between patients switching to another TNFi vs. a non-TNFi (index drug). Multivariable regression models adjusted for baseline covariates (index year, age, sex, initial TNFi, comorbidities, baseline HRU, and PsA-related treatment history). RESULTS: Of 2107 patients switching to another TNFi and 253 switching to a non-TNFi, adalimumab and etanercept were the most common initial TNFi in both cohorts. During the study period, patients switching to another TNFi had significantly fewer dermatologists visits (0.43; p < 0.01) but more rheumatologist visits (1.56, p < 0.01) than patients switching to a non-TNFi. Patients switching to another TNFi vs. a non-TNFi incurred significantly lower total average healthcare expenditures (adjusted difference: $17,625; p < 0.01), driven by lower prescription drug (adjusted difference: $17,172; p < 0.01) and hospitalization expenditures (adjusted difference: $5772; p = 0.04). Patients who switched to another TNFi vs. a non-TNFi continued on their index therapy significantly longer (median time to discontinuation: 8.31 vs. 5.68 months; log-rank p < 0.01). CONCLUSIONS: Patients with PsA who switched to another TNFi had lower total healthcare expenditures and longer persistence compared with patients who switched to a non-TNFi biologic. FUNDING: AbbVie.

Treatment Patterns with Disease-Modifying Antirheumatic Drugs in U.S. Veterans with Newly Diagnosed Rheumatoid Arthritis, Psoriatic Arthritis, or Ankylosing Spondylitis.

BACKGROUND: Delays in treatment for inflammatory arthritis (IA) are associated with unfavorable outcomes, including impaired quality of life, irreversible joint damage, and disability. OBJECTIVE: To characterize treatment initiation patterns in veterans with newly diagnosed rheumatoid arthritis (RA), psoriatic arthritis (PsA), or ankylosing spondylitis (AS). METHODS: ICD-9/10-CM codes and natural language processing were used to identify incident cases of RA, PsA, or AS between January 1, 2007, and December 31, 2015, in patients enrolled in the Veterans Health Administration. Patterns of treatment initiation and nontreatment with disease-modifying antirheumatic drugs (DMARDs) were assessed in the 12-month follow-up period after the incident diagnosis. Outcomes included the percentage of veterans treated with a DMARD, the mean time to the initial DMARD after diagnosis, and the percentage of veterans who accessed rheumatology care before DMARD initiation. To assess outcomes over time, veterans were grouped by year of initial IA diagnosis. Additionally, outcomes were compared between nonbiologic and biologic DMARDs and among IA subtypes (RA, PsA, and AS). Groups were statistically compared with 95% confidence intervals. RESULTS: The population consisted of 12,118 IA veterans (9,711 RA, 1,472 PsA, and 935 AS), with 91.3% males and a mean age of 63.7 years. The percentage of veterans treated with ≥ 1 DMARD (nonbiologic or biologic) during the 12-month follow-up period increased from 48.8% in 2007 to 66.4% in 2015. In veterans diagnosed with IA in 2015, DMARD treatment was more common for PsA patients (72.9%) and RA patients (68.6%) than for AS patients (28.9%). In the subset treated with a DMARD within 12 months after diagnosis, the mean time to the initial DMARD after diagnosis did not change throughout the observation period (35.5 days for RA, 43.9 days for PsA, and 59.5 days for AS). Rheumatology specialty care was accessed by 87.4% of veterans treated with a nonbiologic DMARD and 92.2% of veterans treated with a biologic DMARD, in patients diagnosed in 2015. CONCLUSIONS: DMARD treatment rates during the initial 12 months after diagnosis increased between 2007 and 2015, but nontreatment remained common, particularly in veterans with AS. The time to treatment after diagnosis was stable over time; it was shortest for RA, intermediate for PsA, and longest for AS. DMARD treatment was uncommon in veterans who did not access rheumatology specialty care. DISCLOSURES: AbbVie Pharmaceuticals and Marriott Daughters Foundation funded this study via investigator-initiated grants. Data analyses were completed by investigators independent of AbbVie and Marriott Daughters Foundation. Walker, Clewell, and Douglas are employed by, and stockholders in, Abbvie. Halwani reports grants from BMS, Kyowa Hakko Kirin, Seattle Genetics, Roche-Genentech, Miragen, Immunedesign, Takeda, Amgen, Pharmacyclics, and Abbvie. The other authors have nothing to disclose.

Risk of treatment-emergent diabetes mellitus in patients receiving antipsychotics.

BACKGROUND: Type 2 diabetes mellitus has been reported during antipsychotic treatment. OBJECTIVE: To quantify the potential risk of treatment-emergent diabetes mellitus among patients receiving antipsychotic medications. METHODS: The MEDLINE and Psychinfo databases were searched using the key words antipsychotic (including individual drug names), diabetes, risk, and incidence for all English-language articles published between 1966 and 2005. Risk calculations were performed using data obtained from pharmacoepidemiologic studies that met the following criteria: (1) cohort design, (2) determination of preexisting diabetes, (3) inclusion of antipsychotic monotherapy as an exposure variable, and (4) comparison with exposure to first-generation antipsychotics. Studies meeting these criteria were used to calculate incidence, attributable risk between agents, and number needed to harm. RESULTS: A total of 25 observational pharmacoepidemiologic studies were found comparing antipsychotics on the outcome of diabetes mellitus. Sufficient information was provided in 15 of the reports to be able to estimate attributable risk. Attributable risk for individual second-generation antipsychotics relative to first-generation antipsychotics ranged from 53 more to 46 fewer new cases of diabetes per 1000 patients. Little observable difference was noted between the individual second-generation antipsychotics versus first-generation antipsychotics on this outcome. However, few of the studies controlled for body weight, race or ethnicity, or the presence of diabetogenic medications. None adjusted for familial history of diabetes, levels of physical activity, or diet, as this information is not usually available in the databases used in pharmacoepidemiologic studies. CONCLUSIONS: Based on the published pharmacoepidemiologic reports reviewed, the avoidance of diabetes as an outcome cannot be predictably achieved with precision by choice of a second-versus a first-generation antipsychotic. Risk management for new-onset diabetes requires the assessment of established risk factors such as family history, advancing age, non-white ethnicity, diet, central obesity, and level of physical activity.

The impact of patient support programs on adherence, clinical, humanistic, and economic patient outcomes: a targeted systematic review.

BACKGROUND: Patient support programs (PSPs), including medication management and counseling, have the potential to improve care in chronic disease states with complex therapies. Little is known about the program's effects on improving clinical, adherence, humanistic, and cost outcomes. PURPOSE: To conduct a targeted review describing medical conditions in which PSPs have been implemented; support delivery components (eg, face-to-face, phone, mail, and internet); and outcomes associated with implementation. DATA SOURCES: MEDLINE - 10 years through March 2015 with supplemental handsearching of reference lists. STUDY SELECTION: English-language trials and observational studies of PSPs providing at minimum, counseling for medication management, measurement of ≥1 clinical outcome, and a 3-month follow-up period during which outcomes were measured. DATA EXTRACTION: Program characteristics and related clinical, adherence, humanistic, and cost outcomes were abstracted. Study quality and the overall strength of evidence were reviewed using standard criteria. DATA SYNTHESIS: Of 2,239 citations, 64 studies met inclusion criteria. All targeted chronic disease processes and the majority (48 [75%]) of programs offered in-clinic, face-to-face support. All but 9 (14.1%) were overseen by allied health care professionals (eg, nurses, pharmacists, paraprofessionals). Forty-one (64.1%) reported at least one significantly positive clinical outcome. The most frequent clinical outcome impacted was adherence, where 27 of 41 (66%) reported a positive outcome. Of 42 studies measuring humanistic outcomes (eg, quality of life, functional status), 27 (64%) reported significantly positive outcomes. Only 15 (23.4%) programs reported cost or utilization-related outcomes, and, of these, 12 reported positive impacts. CONCLUSION: The preponderance of evidence suggests a positive impact of PSPs on adherence, clinical and humanistic outcomes. Although less often measured, health care utilization and costs are also reduced following PSP implementation. Further research is needed to better quantify which support programs, delivery methods, and components offer the greatest value for any particular medical condition.

Consistency of quality attributes for the glycosylated monoclonal antibody Humira® (adalimumab).

Humira® (adalimumab) is a recombinant human IgG1 monoclonal antibody (mAb) glycoprotein consisting of 1330 amino acids that is specific for human tumor necrosis factor (TNF). The biological activity and clinical profile of mAb therapeutics, including adalimumab, is influenced by their protein structure and glycosylation patterns, which can be affected by the expression system, cell culture conditions and purification process methodology. While clinical outcome cannot yet be attributed to many of the individual structural features that constitute a mAb, it is evident that detailed structural attribute analysis is necessary if structural contributions to function are to be comprehensively defined. Adalimumab product quality data generated from over a decade of manufacturing across multiple production sites and through a series of manufacturing scale changes are presented here. These data reveal a consistent and tightly controlled profile for the product.