Evidence map›Paper›PMID 39739296›Full record

ArticleApplied health economics and health policy2025

Exome Sequencing in the Diagnostic Pathway for Suspected Rare Genetic Diseases: Does the Order of Testing Affect its Cost-Effectiveness?

Koen Degeling, Toni Tagimacruz, Karen V MacDonald, Trevor A Seeger, Katharine Fooks, Viji Venkataramanan, Kym M Boycott, Francois P Bernier, Roberto Mendoza-Londono, Taila Hartley and 3 more

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Article in Applied health economics and health policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Koen Degeling *Cancer Health Services Research, Centre for Health Policy and Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia.
Toni Tagimacruz *Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Karen V MacDonaldDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Trevor A SeegerDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Katharine FooksChild Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Viji VenkataramananChild Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Kym M BoycottChildren's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada.
Francois P BernierDepartment of Medical Genetics, University of Calgary, Calgary, AB, Canada.
Roberto Mendoza-LondonoDivision of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
Taila HartleyChildren's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada.
Robin Z Hayeems *Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Deborah A Marshall *Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada. damarsha@ucalgary.ca.ORCID http://orcid.org/0000-0002-8467-8008
Care4Rare Canada

Funding

Genome Canada OGI-147Ontario Genomics Institute OGI-147
6 · The paper itself

Abstract

backgroundPatients with suspected rare diseases often experience lengthy and uncertain diagnostic pathways. This study aimed to estimate the cost-effectiveness of exome sequencing (ES) in different positions in the diagnostic pathway for patients suspected of having a rare genetic disease.

methodsData collected retrospectively from 305 patients suspected of having a rare genetic disease (RGD), who received clinical-grade ES and participated in the Canadian multicentre Care4Rare-SOLVE study, informed a discrete event simulation of the diagnostic pathway. We distinguished between tests that can lead to the diagnosis of a specific RGD ('indicator tests') and more routine non-RGD diagnostic tests ('non-indicator tests'). Five strategies were considered: no-ES, and ES as 1st, 2nd, 3rd, or 4th test (Tier 1, Tier 2, Tier 3, and Tier 4, respectively), where ES was the final test in the diagnostic pathway if included. Outcomes included the diagnostic yield, time-to-diagnosis, time on the diagnostic pathway, and test costs for each strategy. The cost-effectiveness analysis from a Canadian healthcare system perspective was conducted with diagnostic yield as the primary outcome of interest. Probabilistic analyses and expert-defined scenario analyses quantified uncertainty.

resultsImplementing ES increases the diagnostic yield by 16 percentage points from 20% with no-ES to 36%. Exome sequencing, as the first test (Tier 1), resulted in the shortest time to a diagnosis and the lowest testing cost. Mean testing costs per patient were CAD4347 (95% CI 3925, 4788) for no-ES, CAD2458 (95% CI 2406, 2512) for Tier 1, CAD3851 (95% CI 3684, 4021) for Tier 2, CAD5246 (95% CI 4956, 5551) for Tier 3 and CAD6422 (95% CI 5954, 6909) for Tier 4, with Tier 1 having the highest diagnostic yield at the lowest cost. The scenario analyses yielded results consistent with those of the base case.

conclusionsImplementing ES to diagnose patients suspected of having a RGD can result in a higher diagnostic yield. Although a limitation of our study was that the yield for the non-ES indicator tests was estimated using expert opinion due to a lack of available data, the results underscore the value of ES as a first-line diagnostic test, offering reduced time to diagnosis and lower overall testing costs.

Indexed as

Exome SequencingGenetic TestingRare DiseasesAdultCanadaCost-Benefit AnalysisFemaleHumansMaleMiddle AgedRetrospective Studies

Identifiers

PMID39739296

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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.