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REG call for research!

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The call for research ideas has now closed.  The REG collaborators are currently reviewing all ideas and will advise on outcome in due course.  Please visit us in 2015 to submit your new ideas for consideration.
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The REG research needs aims to generate or strengthen the evidence base for real-life research, including the important area of comparative effective research.
The research priorities were set out at The Arch Summit by REG’s Management Committee – a dynamic list designed to enhance international collaboration and to: promote and support the development of strong analytical method; set best practice benchmarks in this emerging field; answer important clinical and cost-effectiveness questions; shape and direct the activities of the Respiratory Effectiveness Group and its collaborators.

 

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The REG research needs statement complements and adds to those outlined by:

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Standards and Quality Assurance

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There is a need to:
  • Develop registries and networks:
    • Set up a registry for real-life study (pragmatic trials and observational studies) that will set minimum protocol registration criteria and provide a central repository of real-life studies that will optimise sharing of best practice.
    • Develop a network for real-life research to facilitate collaboration between international experts best placed to answer questions relating to these, and other, research needs
  • Standardise observational study methods:
    • Define (and communicate) standard definitions for (i) real-life study designs (e.g. dataset analyses, implementation studies, pragmatic trials); (ii) meaningful endpoints (iii) observational study populations.
    • Validate real-life study endpoints against existing “gold standard”, e.g. asthma control, as evaluated in observational studies against the ACQ, ACT, AQLA, GINA-defined control categories.
    • Standardise dataset interrogation, including application of: codes (clinical, diagnostic, etc) and algorithms used to interpret the data.
    • Establish a minimum data criteria for datasets and database analyses — “a checklist”— that can serve as a quality marker that can guide reviewers when seeking to differentiate between high and low quality real-life research.
  • Develop tools to visualise and evaluate the quality of real-life data:
    • Tools that will complement the GRADE approach, but that will recognise other quality domains (e.g. applicability domain) and that will recognise the quality of non-randomised controlled trial study designs when they are better placed to answer a research questions
    • Holistic, visual representation and means of combining  drug risks and benefits (e.g. summing over different risk and benefit domains, such as: effect on FEV1, impact on comorbidities, indirect physiological measures, impact on patient-reported outcomes). Such approaches could be utilised by guideline bodies.
    • Representations of the “applicability domain” (diagrammatic, analytic) to illustrate the proportion of the true patient population represented by different studies and their applicability to the general populous.
  • Evaluate the predictive power of different types of study designs:
    • randomised controlled trials, observational studies, indirect comaparison modelling can return vastly differing results. Little work has been done to evaluate which study design best predicts future outcomes to help guide study design selection for future research. [/three_fourth_last]

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    Patient-centric research

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    There is a need to bring the patients and carers, as a key stakeholders, more closely into research, to ensure research is relevant and meaningful to those affected.
  • Meaningful research
    • Undertake a Delphi process to understand the disease-related terminology used by patients. Separate projects are required for each country as, even among countries with common languages, idiomatic and colloquial use of language and terminology may vary.
  • Relevant research
    • Work with patients and patient groups to understand the research questions most relevant to those living with respiratory conditions
    • Include patients at research meetings and within study steering groups.

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    Clinical research

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    There are questions in respiratory research that cannot be answered by randomised controlled trials due to the necessary tight inclusion criteria and design of RCTs. These include questions around optimum use (and safety) of therapies in different patient subgroups (e.g. ethnic groups, those with comorbidities), over the long-term, in sub-optimal compliance settings and with real-life contact with healthcare professionals.
    The following is a dynamic list of research needs in respiratory research, those where RCTs have not, or are unable, to provide complete answers:

COPD

  • Utilize real-life longitudinal data to map treatment pathways and response rates for different therapies to offer guidance on potential sequential treatment options.
  • Evaluate the interaction of treatment outcomes and ethnicity
  • Evaluate the interaction of treatment outcomes and COPD phenotype
  • Evaluate the effect of prior asthma diagnosis on COPD treatment outcomes
  • Explore how best to identify severe COPD without using the BODE index
  • Evaluate which COPD index (BODE, ADO, DOSE) is most predictive and whether combining computer tomography with the different indices improves their predictive power
  • Evaluate the true prevalence of comorbidities in COPD (and by COPD phenotype), and prevalence of “disease clusters”  (validate in multiple international datasets to evaluate national differences)
  • Characterise the disease pattern, severity & treatment response for COPD patients who are non-smokers vs (smoker) controls.
  • Understand the safety (and mortality risk) associated with different treatment options for patients with COPD and other comorbidities (e.g. COPD and cardiovascular disease).

Asthma 

  • Explore the concept of risk in asthma and patient characteristics (modifiable and innate) that may be associated with increased exacerbation risk. To date:
    • ATS 2014: An abstract has been submitted to the 2014 ATS looking at risk predictors for increased asthma exacerbations
    • AAAAI 2014: A late-breaking abstract has been submitted to the 2014 AAAAI on risk predictors for increased asthma hospitalisations.
  • Evaluate different routine management approaches post exacerbation
  • Utilise real-life longitudinal data to map treatment pathways and response rates for different therapies to offer guidance on potential sequential treatment options
  • Evaluate the real-life response rate to inhaled corticosteroids, by ICS molecule and particle size
  • Paediatric asthma
    • Explore the real-life pattern of respiratory disease in children ≤5 years and the potential frequency of (seasonal) viral wheeze being misdiagnosed as asthma.
    • Evaluate the real-life effectiveness of different step-up options in paediatric asthma.

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Cost

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There is a need to bring the patients and carers, as a key stakeholders, more closely into research, to ensure research is relevant and meaningful to those affected.
  • Cost efficacy vs cost effectiveness:
    • Cost effectiveness is commonly in place of cost efficacy. There is a lack of data evaluating and comparing the difference between true cost efficacy and cost effectiveness of therapies
    • Cost of disease to the patient is calculated via summation of different unit costs captured within insurance claims records and/or clinical records. Little work has been done around the true cost to the patient using anonymised tax records.
    • “Which real world?”: cost perspectives vary globally, yet that the majority of cost effectiveness studies are performed from a Western perspective and by Western companies. The applicability and relevance of cost evaluations (and to which countries) needs to be explored.

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Safety and regulatory

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There is a need to work with regulatory bodies to:
    • Appropriate use: Establish the appropriate role and position of real-life research in the pre and post-marketing phase of drug development.
    • Reduce barriers to independent research: Ensure indpendent, investigator-led studies are not hampered by an inability to access placebos to conduct valuable safety and effectiveness research.

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E-Health

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There is a need to utilise smart phone and tablet technologies to access new types of real-life data to shed light on previously unanswerable research questions.
  • Point prevalence disease evaluations
    • True disease state: Use Apps to reach out to patients and conduct real-life point prevalence assessments
  • Smart-phone push technologies: Apps download to mobile phones collect information without active involvement from the patient, enabling:
    • Accelerometers Apps: Assessment of mobility and lifestyle impairment of diseases
    • Geo-positioning Apps linked to clinical data: Explore geographical triggersmap disease severity and outcomes by location and proximity to potential environmental triggers (e.g. motorways, industrial centres.[/three_fourth_last]

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