EVERSANA to present at the Virtual ISPOR 2020

Analyze, Deliver, Measure and Communicate Value at Every Stage of the Product Lifecycle.

Join our experts LIVE during one of the 4 presentations to get a deeper understanding of key issues impacting our value-driven healthcare environment.

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PANEL: ARE EXISTING REGULATORY EVIDENCE STANDARDS ADEQUATE FOR INFORMING DECISIONS ON MEDICAL DEVICE ADOPTION BY U.S. HEALTHCARE PROVIDERS/HOSPITALS?
Virtual ISPOR 2020 | MONDAY, May 18th, 2020 | 11:00 AM ET

MODERATOR: Nicole Ferko, MSC, Value & Evidence Division, Marketing and Market Access, EVERSANA, Burlington, ON, Canada

PANELISTS: Barbara Strain, MA, CVAHP, Association of Healthcare Value Analysis Professionals (AHVAP), Albany, NY, USA; Gloria Graham, DNP RN, CVAHP, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA; Paul Delatore, MBA, Alcon, Fort Worth, TX, USA>

ISSUE: With cost containment pressures and the need to optimize health and healthcare delivery, U.S. healthcare providers/hospitals must consider economic value, in addition to clinical evidence and feasibility of adoption, to inform medical device adoption decisions. As the majority of devices do not receive additional reimbursement by payers, providers often need to absorb the costs within operating budgets. Adoption decisions are frequently deliberated by hospital Value Analysis (VA) Committees which evaluate how a device may address a current problem, what evidence exists to demonstrate efficacy and safety, cost, and feasibility of integration to justify adoption. There are no guidelines to inform such evidence development needs, and requirements can vary considerably across institutions. Traditional HEOR methods may be important sources of data; however, hospital decision-makers may not be trained in such methods and may perceive bias in evidence provided by manufacturers. There is a need for clear guidance to consolidate the type of evidence required to support provider decision-making.

OVERVIEW: This panel will debate the evidence requirements for informing VA decisions by setting and device categories, with a focus on medical devices that do not achieve incremental reimbursement.


PODIUM: METHODOLOGICAL CHALLENGES WITH CONDUCTING NETWORK META-ANALYSES ASSESSING LONG-TERM COMPARATIVE EFFICACY IN PSORIASIS- A CRITIQUE OF ASSUMPTIONS UNDERPINNING RECENT INDIRECT TREATMENT COMPARISONS
Virtual ISPOR 2020 | TUESDAY, May 19th, 2020 | 5:30-5:45 PM ET

Disher T1Peterson S2, Eaton K1, Nair S3, Villacorta R2, Hutton B4, Cameron C5, Jansen JP3
1EVERSANA, Burlington, ON, Canada, 2Janssen Immunology Global Commercial Strategy Organization, Horsham, PA, USA, 3Janssen R&D BE, Beerse, Belgium, 4Ottawa Hospital Research Institute, Ottawa, ON, Canada, 5EVERSANA, Sydney , NS, Canada
OBJECTIVES: In network meta-analysis (NMA) of psoriasis trials, cross-over after an initial placebo-controlled period limits the connectivity of long-term evidence networks. We illustrate the challenges with conducting NMAs assessing efficacy beyond cross-over in psoriasis by critically appraising the assumptions underpinning recent long-term NMAs.
METHODS: We compared three recent NMA studies (Armstrong et al. 2019, Sawyer et al. 2018, and Diels et al. 2017) assessing long-term (beyond 16 to 24 weeks) comparative efficacy in psoriasis and investigated how the three studies derived comparative efficacy estimates in the absence of a connected network. While each of the review methods address a slightly different research question, we assumed the underlying goal was to approximate the results from a standard connected network. The purpose of the study was therefore to assess the assumptions required for each approach that would provide unbiased estimates of the comparative effectiveness of included agents.
RESULTS: Armstrong et al. did not analyze comparative RCT data but instead removed placebo arms with cross-over, pooled individual active arms from 23 RCTs, and conducted naïve indirect comparisons between pooled arms (which assumes that all trials are equivalent in terms of prognostic factors, an unlikely assumption). Sawyer et al. analyzed a largely disconnected network with four comparative RCTs, as well as a larger network that was connected through 17 comparisons that assumed placebo response rates observed during induction period were maintained to week 52. Diels et al. only included comparative RCTs in their NMA and constructed a network of 11 RCTs by assuming a class-effect among TNFα inhibitors (i.e., all TNFα inhibitors have similar efficacy).
CONCLUSIONS: Recent analyses assessing long-term comparative efficacy in psoriasis have methodological limitations and should be interpreted with caution. Future studies should consider the assumptions underpinning NMAs and assess how alternative NMA methods can be leveraged to yield more rigorous long-term indirect treatment comparisons.

PODIUM: APPLICATION OF PROPENSITY SCORE MATCHING AND BAYESIAN HIERARCHICAL DESIGN METHODS TO INTEGRATE SINGLE-ARM STUDIES INTO NETWORK META-ANALYSES (NMAS)
Virtual ISPOR 2020 | TUESDAY, May 19th, 2020 | 5:45-6:00 PM ET

Qadeer R1, Ghosh S2, Clymer JW2, Wright G1, Ferko N1, Cameron C3
1EVERSANA, Burlington, ON, Canada, 2Ethicon Inc., Cincinnati, OH, USA, 3EVERSANA, Sydney , NS, Canada
OBJECTIVES : Network meta-analyses (NMAs) generally include direct comparative evidence from randomized controlled trials (RCTs) and/or comparative observational studies; however, comparative evidence is limited in many disease/treatment areas. The objective of this analysis was to discuss opportunities and pitfalls associated with incorporating single-arm studies into NMAs, illustrated in a case study assessing the effectiveness of ablation/radiation therapies in lung cancer.
METHODS : A systematic literature review was conducted to identify RCTs, comparative observational studies, and single-arm studies assessing ablation/radiation therapies among adults with lung cancer. The outcomes were local tumor recurrence, overall survival, and complications. First, Bayesian hierarchical NMAs using direct comparative studies, down-weighting lower quality evidence, were conducted. Second, simulated comparative studies were obtained by matching relevant single-arm studies using optimal 1:1 matching; propensity scores were estimated by fitting a logistic regression model that included age, sex, tumor type, tumor size, and average number of tumors as covariates. Third, Bayesian hierarchical NMAs using both comparative and simulated comparative studies, down-weighting lower quality evidence, were conducted.
RESULTS : One RCT, 10 comparative observational studies, and 147 single-arm studies were identified. Seven to 22 simulated comparative studies were incorporated within each NMA, depending on the outcome. The conclusions of the Bayesian hierarchical NMAs were aligned between analyses using comparative or comparative and simulated comparative studies; however, differences in effect estimate magnitudes (0% – 44%) and treatment rankings were sometimes observed. Limitations of this analysis included sub-optimal reporting of covariates among single-arm studies limiting the ability to sufficiently match for cross-study differences and poor matching where cross-study differences existed.
CONCLUSIONS : Thoughtful integration of single-arm studies in NMAs may offer opportunities to utilize all available evidence and be especially useful in disease/treatment areas with many single-arm studies and limited direct comparative evidence or incomplete evidence networks. However, studies should clearly state the methodological limitations and present results stratified by study design.

WORKSHOP: DEVELOPING AND IMPLEMENTING AN INDIRECT TREATMENT COMPARISON (ITC) STRATEGY TO SUPPORT GLOBAL HEALTH TECHNOLOGY ASSESSMENT (HTA) AND REIMBURSEMENT SUBMISSIONS
Virtual ISPOR 2020 | WEDNESDAY, May 20th, 2020 | 10:00 AM ET

DISCUSSION LEADERS: Chris Cameron, Ph.D., EVERSANA, Sydney, NS, Canada; Sandhya Bair, Ph.D., Janssen Pharmaceitical NV, Beerse, Belgium; Steven Peterson, MBA, Janssen Immunology Global Commercial Strategy Organization, Horshan, PA, USA.

PURPOSE: This interactive workshop will examine the various indirect comparison methodologies that are available. Commonly used ITC methods such as network meta-analysis (NMA) and matching-adjusted indirect comparisons (MAIC) will be discussed using real-world case studies. Discussion leaders and international experts in ITC from Canada, US and Europe will describe methods to develop and implement global ITC strategies to support HTA and reimbursement submissions. The workshop will also provide guidance on selecting the appropriate ITC method to align with analytic objectives as well as data availability. It will also discuss which methodologies are commonly accepted by HTA agencies, and under what scenarios. The strengths and weaknesses of ITC approaches will also be highlighted by the panelists using real-world case studies.

DESCRIPTION: Indirect treatment comparisons are increasingly used to support healthcare decision making. Guidelines for conduct and transparent reporting of ITCs have been published but fail to discuss strategic considerations regarding selection of the most appropriate indirect comparison method to align with analytic objectives and in considering the types of data available to the research team. This workshop will describe how to develop and implement a global indirect treatment comparisons strategy to support health technology assessment and reimbursement submissions. We will present a matrix of relevant ITC methodologies geared toward guiding users to select the most appropriate ITC methodology for their technology assessment scenario based upon the number of treatments to be compared and the granularity of clinical data available (aggregate versus patient level). Commonly used indirect comparison methods such as NMA and MAIC are plotted within this schematic. Additional considerations of relevance including heterogeneity/inconsistency, feasibility of meta-regression analysis and limitations of clinical trial data will also be discussed. The strengths and weaknesses of using ITC approaches will also be highlighted by the panelists using real-world case studies, together with suggestions for future research.


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