Evidence map›Paper›PMID 34980048›Full record

ArticleBMC pediatrics2022

Clinical and economic impact of molecular testing for BRAF fusion in pediatric low-grade Glioma.

Juan David Rios, Russanthy Velummailum, Julie Bennett, Liana Nobre, Derek S Tsang, Eric Bouffet, Cynthia Hawkins, Uri Tabori, Avram Denburg, Petros Pechlivanoglou

Open access · goldAbstract read
In one paragraph

Article in BMC pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
0.3field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. 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 5 institutions in 1 country.

Juan David RiosChild Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, 686 Bay Street, 11th Floor - L4 East, Toronto, ON, M5G 0A4, Canada.
Russanthy VelummailumChild Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, 686 Bay Street, 11th Floor - L4 East, Toronto, ON, M5G 0A4, Canada.
Julie BennettDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.
Liana NobreDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.
Derek S TsangDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.
Eric BouffetDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.
Cynthia HawkinsDepartment of Pathology, Hospital for Sick Children, Toronto, ON, Canada.
Uri TaboriDivision of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada.
Avram Denburg *Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, 686 Bay Street, 11th Floor - L4 East, Toronto, ON, M5G 0A4, Canada.
Petros Pechlivanoglou *Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, 686 Bay Street, 11th Floor - L4 East, Toronto, ON, M5G 0A4, Canada. petros.pechlivanoglou@sickkids.ca.
Hospital for Sick Children · CASickKids Foundation · CAInstitute for Clinical Evaluative Sciences · CAUniversity Health Network · CAUniversity of Toronto · CA

Funding

The Canadian Institutes for Health Research 159805
6 · The paper itself

Abstract

backgroundTreatment personalization via tumor molecular testing holds promise for improving outcomes for patients with pediatric low-grade glioma (PLGG). We evaluate the health economic impact of employing tumor molecular testing to guide treatment for patients diagnosed with PLGG, particularly the avoidance of radiation therapy (RT) for patients with BRAF-fusion.

methodsWe performed a model-based cost-utility analysis comparing two strategies: molecular testing to determine BRAF fusion status at diagnosis against no molecular testing. We developed a microsimulation to model the lifetime health and cost outcomes (in quality-adjusted life years (QALYs) and 2018 CAD, respectively) for a simulated cohort of 100,000 patients newly diagnosed with PLGG after their initial surgery.

resultsThe life expectancy after diagnosis for individuals who did not receive molecular testing was 39.01 (95% Confidence Intervals (CI): 32.94;44.38) years and 40.08 (95% CI: 33.19;45.76) years for those who received testing. Our findings indicate that patients who received molecular testing at diagnosis experienced a 0.38 (95% CI: 0.08;0.77) gain in QALYs and $1384 (95% CI: $-3486; $1204) reduction in costs over their lifetime. Cost and QALY benefits were driven primarily by the avoidance of long-term adverse events (stroke, secondary neoplasms) associated with unnecessary use of radiation.

conclusionsWe demonstrate the clinical benefit and cost-effectiveness of molecular testing in guiding the decision to provide RT in PLGG. While our results do not consider the impact of targeted therapies, this work is an example of the value of simulation modeling in assessing the long-term costs and benefits of precision oncology interventions for childhood cancer, which can aid decision-making about health system reimbursement.

Indexed as

GliomaProto-Oncogene Proteins B-rafChildCost-Benefit AnalysisHumansMolecular Diagnostic TechniquesPrecision MedicineQuality-Adjusted Life YearsBRAF protein, humanProto-Oncogene Proteins B-rafCost-effectivenessHealth economicsHealth technology evaluationMolecular testingPediatric low-grade GliomaPediatric oncologyPrecision medicine

Identifiers

PMID34980048
PMCPMC8722113
OpenAlexW4206739470

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.