Evidence map›Paper›PMID 31174574›Full record

ArticleOrphanet journal of rare diseases2019

Factors associated with positive and negative recommendations for cancer and non-cancer drugs for rare diseases in Canada.

Fernanda Naomi Inagaki Nagase, Tania Stafinski, Jian Sun, Gian Jhangri, Devidas Menon

Open access · goldAbstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 9% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
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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

5 authors at 1 institution in 1 country.

Fernanda Naomi Inagaki NagaseHealth Technology & Policy Unit, School of Public Health, University of Alberta, Edmonton, AB, Canada. fnagase@ualberta.ca.ORCID 0000-0002-1138-3452
Tania StafinskiHealth Technology & Policy Unit, School of Public Health, University of Alberta, Edmonton, AB, Canada.
Jian SunHealth Technology & Policy Unit, School of Public Health, University of Alberta, Edmonton, AB, Canada.
Gian JhangriSchool of Public Health, University of Alberta, Edmonton, AB, Canada.
Devidas MenonHealth Technology & Policy Unit, School of Public Health, University of Alberta, Edmonton, AB, Canada.
University of Alberta · CA

Funding

CIHR
6 · The paper itself

Abstract

backgroundIn Canada, reimbursement recommendations on drugs for common and rare diseases are overseen by the Canadian Agency for Drugs and Technologies in Health (CADTH) and made through the pan-Canadian Oncology Drug Review (pCODR) and the Common Drug Review (CDR). While the agency specifies information requirements for the review of drug submissions, how that information is used by each process to formulate final reimbursement recommendations, particularly on drugs for rare diseases (DRDs) in which per patient treatment costs are often high, is unclear. The purpose of this study was to determine which factors contribute to recommendation type for DRDs.

methodsInformation was extracted from CDR and pCODR recommendations on drugs for diseases with a prevalence < 1 in 2000 from January 2012 to April 2018. Data were tabulated and multiple logistic regression was applied to explore the association between recommendation type and the following factors: condition/review process (cancer vs non-cancer), year, prevalence, clinical effectiveness (improvements in surrogate, clinical and patient reported outcomes), safety, quality of evidence (availability of comparative data, consistency between population in trial and indication, and bias), clinical need, treatment cost, and incremental cost-effective ratio (ICER). Two-way interactions were also explored.

resultsA total of 103 recommendations were included. Eleven were resubmissions, all of which received a positive recommendation. Among new submissions (n = 92), DRDs that were safe or offered improvements in clinical or patient reported outcomes were more likely to receive positive reimbursement recommendations. No associations between recommendation type and daily treatment cost, cost-effectiveness, or condition (cancer or non-cancer) were found.

conclusionsClinical effectiveness, as opposed to economic considerations or whether the drug is indicated for cancer or non-cancer, determine the type of reimbursement recommendation.

Indexed as

CanadaCost-Benefit AnalysisHumansLogistic ModelsNeoplasmsOrphan Drug ProductionRare DiseasesOrphan drugsRare diseasesReimbursement review

Identifiers

PMID31174574
PMCPMC6555917
OpenAlexW2948368473

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.