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Value in Health | 2010

Pms71 Indirect Treatment Comparisons of Biologic Therapies for Rheumatoid Arthritis

R. Alfonso; B. Devine; S.D. Sullivan

PMS71 INDIRECT TREATMENT COMPARISONS OF BIOLOGIC THERAPIES FOR RHEUMATOID ARTHRITIS Alfonso R, Devine B, Sullivan SD University of Washington, Seattle, WA, USA OBJECTIVES: To compare the efficacy results of biological therapies for rheumatoid arthritis (RA) using indirect treatment comparisons and meta-regression techniques. METHODS: We performed a literature search to identify the randomized clinical trials (RCTs) of biological therapies for RA. Using these studies we created a network and developed two random effects, logistic regression models (6and 12-months), using the ACR-50 as the primary outcome. We chose mean disease duration and mean baseline HAQ-DI score as meta-regression covariates, to account for heterogeneity between trials, as these have prognostic value in determining the effect of RA treatment. RESULTS: We included 18 RCTs in the 6-month analysis and 10 RCTs in the 12-month analysis. Eight biologic agents are included in the 6-month analysis and six in the 12-month. The results of the 6-month analysis suggest that the eight biologic agents are significantly more effective than the comparator (p < 0.05): Certulizumab (log odds ratio, median = 2.6), rituximab (1.7), adalimumab (1.6), infliximab (1.6), etanercept (1.4), golimumab (1.3), abatacept (1.2), and anakinra (1.0). The results also indicate that methotrexate (MTX) is significantly more effective than placebo (0.7). The parameter values for the 12-month analysis are similar, with the effectiveness of the biologics following the same order, but without golimumab and anakinra. CONCLUSIONS: Our results suggest that biologic treatments are more effective than MTX or placebo, but they may differ from one another. There are differences in the outcomes depending on whether we evaluate the ACR-50 at 6-months or 12-months. Biologic agents seem to be more effective with longer disease duration.


Value in Health | 2007

PHP10 ASSESSING PAYER AND EMPLOYER PERSPECTIVES RELATED TO VALUE IN HEALTH CARE

Brian W. Bresnahan; R Carlson; Louis P. Garrison; G Carpenter; Peter J. Neumann; S.D. Sullivan

PHP7 GENERIC-NAME PRESCRIPTION AND PERCEIVED QUALITY IN THE DEMAND FOR PHARMACEUTICALS IN ARGENTINA Maceira DA, Kurtzbart R Center for the Study of the State and Society, Buenos Aires, Argentina OBJECTIVES: Pharmaceutical markets are examples of imperfect competition, based on product differentiation associated to perceive quality under a patent scheme. In Argentina, the 25649 law in 2002 defined the “duty to prescribe medicines by the generic name of their active principle”, changing the prior normative that allow brand names in prescriptions. The aim of the initiative was to provide the opportunity for substitution based on prices of products therapeutically equivalent, triggering price reductions and higher access to pharmaceuticals. Considering pharmaceutical markets as an array of sub-markets with nonhomogeneous characteristics, this paper focuses on the analysis of two therapeutic classes: hypolipemiants and calcium blockers. The objective is to measure the impact of the normative on prices, by using a data set of monthly sales by firm and by brand for the period July 1999–June 2004. METHODS: By using a discrete choice model of product differentiation, the econometric implementation shows a panel data analysis where each firm’s market share is explained by price and non-price characteristics, plus a dummy variable that account for normative switch, corrected by macroeconomic variables (exchange rates and economic activity fluctuations). Among non-market characteristics, the estimations consider age of the product as a proxy or reputation builder, manufacturer position in the local market, and nature of the capital (local or multinational firm). RESULTS: Results show that product age is significant and positive explanation for market share in both classes studied, while foreign capital and industry leadership have the expected sign just for one of the markets considered. Additionally, price is negative and significant at 99%. CONCLUSION: However, price sensitivity to the price increased only about 0.9% and 0.3% for each market because of the normative change, which shows perceived quality as the main explanation for demand, and rejecting the hypothesis of truncated demand function based on loyalty.


Value in Health | 2005

Php27 Quality of Economic Models in Dossiers Submitted Undertheamcp Format

F Colmenero; S.D. Sullivan; John B. Watkins; Peter J. Neumann

variable is per capita pharmaceutical and other medical nondurable expenditures. Explanatory variables investigated include per capita GDP (Gross Domestic Product), % of elderly population (65+ years), % of population with higher education (college+), school expectancy, calorie intake per capita per day, alcohol consumption in liters per capita (age 15+), % of expenditures on pharmaceuticals and other medical non-durables financed by the public sector, number of practicing physicians, % of population with public health care coverage, number of doctor consultations per capita and % urbanized. All monetary values were converted into US dollars based on GDP purchasing power parity. A log-linear (constant elasticity) regression model was used. RESULTS: The final model included 6 explanatory variables with an adjusted R2 = 0.744. The White test was used to correct heteroskedasticity. The natural log of GDP per capita (b = 0.455, p = 0.003), percent of elderly population (b = 0.039, p = 0.01), number of doctor consultations (b = 0.028, p = 0.008), and calories intake (b = 0.0003, p = 0.002) had positive, statistically significant effects on pharmaceutical expenditures at á < 0.01. Percent of population with higher education (b = 0.012, p = 0.22) and public financing (b = -0.001, p = 0.43) were not significant. Alcohol consumption (another indicator of lifestyle behaviors); number of physicians and public health care coverage (indicators of relative size of the health care system); urbanization (indicator of development); and school expectancy (another indicator of educational development) did not contribute to the model. CONCLUSIONS: OECD countries with more wealth, more elderly people, more doctor consultations, and more calorie intake tend to spend more on pharmaceuticals and other medical non-durables. Size of the health care system and financing methods do not explain differences in pharmaceutical expenditures.


Value in Health | 2001

PID1: EFFICACY OF ZINC LOZENGES ON THE DURATION OF COMMON COLD SYMPTOMS: A META-ANALYSIS REVISITED

Nathorn Chaiyakunapruk; David L. Veenstra; S.D. Sullivan; Sanjay Saint; S Bent


Value in Health | 2012

PRS18 A Dynamic Cohort Model of Chronic Obstructive Pulmonary Disease and Its Treatments

Ryan N. Hansen; X. Xu; S.D. Sullivan


Value in Health | 2011

PHP146 Current Status and Trends in Performance-Based Schemes Between Health Care Payers and Manufacturers

Josh J. Carlson; Katharine S. Gries; S.D. Sullivan; Louis P. Garrison


Value in Health | 2001

HP3: INCORPORATING CLINICAL OUTCOMES AND ECONOMIC CONSEQUENCES INTO DRUG FORMULARY DECISIONS: EVALUATION OF 30 MONTHS OF EXPERIENCE

De Atherly; S.D. Sullivan; Ds Fullerton; Ll Sturm


Value in Health | 2009

PHP64 LINKING PAYMENT AND HEALTH OUTCOMES: A SYSTEMATIC REVIEW AND TAXONOMY OF PERFORMANCE-BASED HEALTH OUTCOMES AGREEMENTS BETWEEN HEALTH CARE PAYERS AND MANUFACTURERS

Josh J. Carlson; S.D. Sullivan; Louis P. Garrison; Peter J. Neumann; David L. Veenstra


Annals of Oncology | 2017

263PSurvival gains from advances in first-line systemic therapy for HER2-positive metastatic breast cancer in the U.S., 1995-2015

J. Roth; P. Bajaj; S.D. Sullivan; C. Reyes; V. Antao; Alisha Stein; R. Mahtani; S. Ramsey


Value in Health | 2014

Incentivizing Value In Managed Care Drug Formularies: Design, Implementation, And First-Year Outcomes Of A Value-Based Formulary

J. Watkins; S.D. Sullivan; K. Yeung; Scott D. Ramsey; Louis P. Garrison; E. Wong; C. Murphy; D. Danielson; Dl. Veenstra; C. Vogeler; Wylie Burke; R. McGee

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Scott D. Ramsey

Fred Hutchinson Cancer Research Center

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Ryan N. Hansen

University of Washington

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B. Seal

Bayer HealthCare Pharmaceuticals

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Carl V. Asche

University of Illinois at Chicago

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