Latest Trends in Design of Pivotal Clinical Trials for Huntington’s Disease

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person change in scale scores and effect size (mean change divided by standard deviation of baseline score) between baseline and 3mo in relation to change in clinical status, as measured by SLEDAI-2K scores, categorized as “improved”, “no change”, or “worsened”, and test-retest reliability was assessed by Pearson correlation coefficient (r) comparing baseline and 3mo scores among those with “no change” in SLEDAI-2K scores.  Results: Within person change/effect size among the Improved group(n= 54): LAST= -6.4/-0.537; C-LAST= -5.6/-0.536); TLAS= -1.7/0.234; SIMPLE= -4.1/-0.359; PhGA(scale:0-10)= -1.3/-0.655; PhGA(scale:0-3)= -0.7/0.915. No change(n= 55): LAST= -0.7/-0.055; C-LAST: -0.5 /-0.049; TLAS: 1.7/0.159; SIMPLE: -1.3/-0.114; PhGA(scale:0-10): -0.2/-0.080; PhGA(scale:0-3): -0.02/0.025. Worsened(n= 40): LAST= 4.1/0.323; C-LAST= 2.9/0.265; TLAS= 4.8/0.449; SIMPLE= 1.9/0.170; PhGA(scale:0-10)= 1.0/0.495; PhGA(scale:0-3)= 0.4/0.480. Test-retest reliability (r; all p< .0001): LAST= 0.694; CLAST= 0.659; TLAST= 0.761; SIMPLE= 0.621; PhGA(scale:0-10)= 0.663, PhGA(scale:0-3)= 0.515).  Conclusions: Test-retest reliability showed moderate-to-strong correlations between baseline and 3mo assessments. For the “improved” and “worsened” groups (per SLEDAI-2K change), effect sizes indicated a small to medium effect, whereas the “no change” group had effect sizes indicative of no change; mean within-person change scores were directionally responsive to clinical change. PRM33 Accounting for Rater Severity/Leniency in Endpoint Measures in Adults with Severe TBI Mallinson T1, Pape T2, Guernon A2 1The George Washington University, Washington, DC, USA, 2Edward Hines Jr. Veterans Affairs Hospital, Hines, IL, USA

Objectives: To examine impact of rater severity/leniency on measures of neurobehavioral functioning. Observed performance, where a clinician observes and then rates patient’s performance, is required when assessing patients with severe traumatic brain injury (TBI). When some raters are more severe or lenient in how they assign scores measurement treatment effectiveness will be under- or overestimated.  Methods: Prospective, observational, cohort study. 57 clinicians administered Disorders of Consciouness Scale (DOCS) to 174 patients with severe TBI who were vegetative or minimally conscious at time of study enrollment and within 180 days of injury. To complete the DOCS, clinicians present 25 sensory stimuli to patients and rate the elicited response on a 3-point rating scale. Data were analyzed using the multi-faceted Rasch model (MFRM). A facet is any factor that contributes to making a patient appear to have more or less of a trait than they actually do. MFRM is an extension of the Rasch model that enables patient measures to be adjusted for rater severity/leniency.  Results: Overall, mean DOCS measure was 50.8 units unadjusted and was 51.7 units after adjusting for rater severity; t= -2.25, P= .03. However, 35% of individual DOCS measures differed more than the established minimally detectable change of 5 units; some patient measures differed by as much as 37 units; a minimally clinically important difference (MCID) for the DOCS is 7 units. 28 patients were rated too severely (IQR 5.6 - 9.9 units too severely) and 13 were patients rated too leniently (IQR 7.0 - 14.0 units too leniently).  Conclusions: Accounting for rater severity/leniency is important for all endpoints in which a rater observes, and then judges, patient behavior/response. Raters can introduce unwanted variation that threatens the interpretation of clinical trial endpoints. By adjusting for rater severity/leniency accurate change in endpoints across time can be established, despite data being collected by different raters. PRM34 The Diffusion of Indirect Comparison Meta-Analytic Methods in the Study of Drugs: A Systematic Review and Co-Authorship Network Analysis Ban JK, Tadrous M, Cicinelli EA, Dubins DN, Cadarette SM Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada

Objectives: Utilizing indirect evidence to compare the relative effects between two or more comparators in meta-analysis was first introduced in 1997. Refined methods were published in 2002 (network meta-analysis) and 2004 (mixed-treatment comparisons). We sought to characterize the diffusion of indirect comparison meta-analytic methods in the study of drugs over time.  Methods: We completed a systematic keyword (Cochrane, EMBASE, and MEDLINE) and citation (Web of Science and SCOPUS) search to identify papers that utilized indirect comparison meta-analytic methods to study drugs. The number of papers was plotted by year and type (methodological contribution, review, or empirical application), and sociograms were created to visualize the co-authorship network and identify social clusters (components). Countries affiliated with the first and last authors of each empirical application were used to ascribe regional credit to each application.  Results: We identified 477 studies (74 methodological contributions, 42 reviews, and 361 empirical applications) by 1,689 distinct authors published from 1997 to 2013. Prior to 2011, only 147 (31%) empirical applications were published. A rapid increase in use was noted since 2011, with 330 (69%) applications published in only 3 years. The co-authorship network consisted of 129 components, yet 90 (70%) included only a single paper. Overall, 49% of papers were from Europe (22% United Kingdom, 27% other), 37% were from North America (26% USA, 11% Canada), and 15% were from other regions (Africa, Australasia, South America). Of the 361 empirical applications, 259 (72%) used a single term to describe the meta-analytic methods. Network meta-analysis was most commonly used (31%).  Conclusions: Indirect comparison meta-analysis is an important innovation in drug safety and effectiveness research. While Europe has the most publications, there has been wide diffusion worldwide, and significant variation in the terminology used to describe these meta-analytic methods. Developing naming standards may facilitate identification, comprehension, and application of these methods. PRM35 Latest Trends in Design of Pivotal Clinical Trials for Huntington’s Disease

Aggarwal S1, Kumar S2, Topaloglu H1 1NOVEL Health Strategies, Chevy Chase, MD, USA, 2Institute for Global Policy Research, Washington, DC, USA

Objectives: Huntington’s disease (HD) is a rare but devastating neurodegenerative disorder characterized by jerky and involuntary movements, impairment in voluntary motor function, behavioral changes, and dementia. The objective of this study was to review the trends in design of pivotal clinical trials for Huntington’s Disease.  Methods: Systematic review was conducted to identify new and on-going pivotal clinical for Huntington’s Disease. The inclusion criteria were the indication of Huntington’s Disease, Phase 3 status and study completion date of 2014 or after. The data field extracted were study title, intervention, sponsor, age subgroups, planned enrollment, study type, study design, completion date and outcome measures.  Results: Overall, 6 clinical studies with total planned enrollment of 1652 patients were identified. The median enrollment for the studies was 149 patients. Five of the six studies were for drugs and 1 study was for a dietary supplement. Each trial had entirely different primary outcome measures. Primary outcome measures included: Rate of caudate atrophy, Change in total functional capacity, the Independence scale and Total Maximal Chorea Score (TMC) and Change in Total Functional Capacity. The secondary outcomes also significantly varied across trials. The UHDRS (Unified Huntington Disease Rating Scale) was the most common measure across these trials. Other outcomes included: Patient Global Impression of Change (PGIC), SF-36 physical component, Clinical Global Impression of Change (CGIC), BARS, HADS, ESS, C-SSR, MoCA and cost.  Conclusions: Lack of consistent primary and secondary outcomes across Huntington’s Disease trials might pose some challenges in demonstrating comparative value of new treatments to various stakeholders.

RESEARCH ON METHODS – Cost Methods PRM36 Economic And Productivity Consequences Associated With Rheumatoid Arthritis Among Non-Institutionalized Individuals In The United States Gaitonde P 1, Shaya F T 2 of Maryland, Baltimore, MD, USA, 2University of Maryland School of Pharmacy, Baltimore, MD, USA .

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Objectives: Based on a previous study (2008), the direct incremental medical cost associated with rheumatoid arthritis (RA) was $73.4 billion, equivalent to 0.5% of the gross domestic product (GDP). Therefore, using the most up-to-date data, this study investigates the direct medical cost and productivity losses attributable to rheumatoid arthritis (RA).  Methods: This is a pooled cross-sectional study that used the Medical Expenditure Panel Survey (MEPS) data for years 2010 - 2013. We identified RA patients using the clinical classification code – ‘202’. We measured direct medical cost as total annual healthcare expenditure by individuals in MEPS. Impact on productivity was measured as wage income loss and days absent from work (absenteeism). The study aims were analyzed using log-linear regression. Estimates were weighted to account for complex survey design.  Results: The prevalence of RA in the U.S is 1.94% (24.2 million) with 70.5% females and 47.8% belonging to the age group of 45 – 65 years. Mean total healthcare expenditure among RA versus non-RA was $ 12,203 (± 20,771) and $3,237 (± 12,598) respectively. Mean wage earned was $10,984 (± 22,409) and $16,844 (±28,563) while mean absenteeism was 9.5 days (±22.5) and 3.8 days (±13.6) respectively among patients with versus without RA. A 72% increase in direct medical expenditure (p< 0.0001) was observed among patients with versus without RA, after adjusting for demographics, comorbidities and health status. In addition to above variables, after adjusting for education, occupation and mental health status, 3.6% wage income loss (p< 0.0001) and 17.8% increase in absenteeism (p< 0.0001) was noted among patients with versus without RA.  Conclusions: RA has a substantial impact on both direct medical costs and productivity as measured in the current study. Further studies will assess the economic consequences attributable to RA overtime and the explore impact of RA treatment regimens on productivity and physical function. PRM37 A Case For Market-Based Costs In Determining Cost Effectiveness: The Hepatitis C Example Leinwand B 1, Hughes K E 2, Sorenson C 1, Johnsrud M 2 Health, Washington, DC, USA, 2Avalere Health LLC, Washington, DC, USA .

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Objectives: To summarize results of recently published HCV cost-effectiveness studies assessing new direct-acting antivirals (DAAs) from the payer perspective, and determine the extent to which the models integrated established methodological guidelines for utilizing market-based pricing (rather than list pricing).  Methods: We conducted a structured search of the health economic literature to identify studies, abstracts, and health technology assessments (HTAs) that report cost-effectiveness of novel HCV therapies.  Results: We identified seven peer-reviewed articles , conference abstracts, and HTAs that assessed cost-effectiveness from a payer perspective on a US population. Six of the seven studies evaluated patients with genotype 1, one study also evaluated genotypes 2-4, and one study exclusively evaluated genotypes 2 and 3. While sofosbuvir-based regimens were the most common novel DAAs assessed, paritaprevir/ritonavir/ombitasvir, dasabuvir, and daclatasvir were also examined. The results of our review indicate a general trend of cost-effectiveness for the novel HCV treatments within generally accepted thresholds, which translates into value for payers. However, we found the majority of models utilized medication list pricing (e.g., wholesale acquisition price) and did not consider employing market-based pricing as suggested by ISPOR guidelines.  Conclusions: The current body of U.S. literature assessing cost-effectiveness of novel DAAs from the payer perspective suggests they provide good value for money. Because many of the models utilize medications’ list prices, results can be interpreted as conservative estimates; their true value to payers is likely greater.