Evidence map›Paper›PMID 29954425›Full record

ReviewOrphanet journal of rare diseases2018

Using a meta-narrative literature review and focus groups with key stakeholders to identify perceived challenges and solutions for generating robust evidence on the effectiveness of treatments for rare diseases.

Kylie Tingley, Doug Coyle, Ian D Graham, Lindsey Sikora, Pranesh Chakraborty, Kumanan Wilson, John J Mitchell, Sylvia Stockler-Ipsiroglu, Beth K Potter, Canadian Inherited Metabolic Diseases Research Network

Open access · goldAbstract readReview
In one paragraph

Review in Orphanet journal of rare diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Review
  3. Fine-tuning large language models for rare disease concept normalization.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  4. Fine-tuning Large Language Models for Rare Disease Concept Normalization.bioRxiv : the preprint server for biology · 2024
    Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Observational
  16. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Kylie TingleySchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada.
Doug CoyleSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada.
Ian D GrahamSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada.
Lindsey SikoraHealth Sciences Library, University of Ottawa, Ottawa, ON, Canada.
Pranesh ChakrabortyMetabolics and Newborn Screening, Department of Pediatrics, Children's Hospital of Eastern Ontario, Ottawa, ON, Canada.
Kumanan WilsonSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada.
John J MitchellDepartment of Pediatrics and Department of Medical Genetics, McGill University Health Centre, Montreal, QC, Canada.
Sylvia Stockler-IpsirogluDivision of Biochemical Diseases, BC Children's Hospital, Vancouver, BC, Canada.
Beth K PotterSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada. bpotter@uottawa.ca.ORCID 0000-0001-8374-6542
Canadian Inherited Metabolic Diseases Research Network
University of Ottawa · CAMcGill University Health Centre · CAUniversity of British Columbia · CA

Funding

CIHR TR3-119195
6 · The paper itself

Abstract

introductionFor many rare diseases, strong analytic study designs for evaluating the efficacy and effectiveness of interventions are challenging to implement because of small, geographically dispersed patient populations and underlying clinical heterogeneity. The objective of this study was to integrate perspectives from published literature and key rare disease stakeholders to better understand the perceived challenges and proposed methodological approaches to research on clinical interventions for rare diseases.

methodsWe used a meta-narrative literature review and focus group interviews with key rare disease stakeholders to better understand the perceived challenges in generating and synthesizing treatment effectiveness evidence, and to describe various research methods for mitigating these identified challenges. Data from both components of this study were synthesized narratively according to research paradigms that emerged from our data.

resultsResults from our meta-narrative literature review and focus group interviews revealed three fundamental challenges in generating robust treatment effectiveness evidence for rare diseases: i) limitations in recruiting a sufficient sample size to achieve planned statistical power; ii) inability to account for clinical heterogeneity and assess treatment effects across a clinical spectrum; and iii) reliance on short-term, surrogate outcomes whose clinical relevance is often unclear. We mapped these challenges and associated solutions to three interrelated research paradigms: i) explanatory evidence generation; ii) comparative effectiveness/pragmatic evidence generation; and iii) patient-oriented evidence generation. Within each research paradigm, numerous criticisms and potential solutions have been described with respect to overcoming these challenges from a research study design perspective.

conclusionsOver time, discussions about clinical research for interventions for rare diseases have moved beyond methodological approaches to overcome challenges related to explanatory evidence generation, with increased recognition of the importance of pragmatic and patient-oriented evidence. Future directions for our work include developing a framework to expand current evidence synthesis practices to take into consideration many of the concepts discussed in this paper.

Indexed as

Rare DiseasesFocus GroupsHumansResearch DesignComparative effectivenessEvidence generationEvidence synthesisPatient-oriented outcomesRare diseasesResearch methods

Identifiers

PMID29954425
PMCPMC6022712
OpenAlexW2810528414

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.