Evidence map›Paper›PMID 41312229›Full record

SynthesisOntario health technology assessment series2025

DNA Methylation-Based Classification for Central Nervous System Tumours: A Health Technology Assessment.

Ontario Health (Quality)

Abstract readSystematic Review
In one paragraph

Synthesis in Ontario health technology assessment series, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. 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

1 author.

Ontario Health (Quality)

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Central nervous system (CNS) tumours occur when abnormal cells form in the tissues of the brain and/or spinal cord. Conventional testing for CNS tumour classification involves histopathological evaluation and molecular markers. More recently, DNA methylation-based classifier tests are being used as an adjunct tool in addition to conventional tests to help with CNS tumour classification. We conducted a health technology assessment of DNA methylation-based classifier tests for CNS tumours, which included an evaluation of effectiveness, cost-effectiveness, and budget impact of publicly funding DNA methylation-based classifier tests for CNS tumours. After considering the likely effects of testing on the patient experience, we determined not to perform an analysis of patient preferences and values. Methods: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria.We performed a systematic economic literature search and developed a decision-analytic model to evaluate the cost-effectiveness of using DNA methylation-based classifier tests. We also analyzed the budget impact of publicly funding DNA methylation-based classifier tests. All costs were expressed in 2024 CAD. Results: We included 38 studies in the clinical evidence review. Compared with conventional testing alone, DNA methylation-based classifier tests are an adjunct tool that may improve CNS tumour classification (GRADE: Moderate). The tests may improve downstream patient outcomes, although the evidence is very uncertain (GRADE: Very low). Unclassifiable test results may increase time to treatment, but the evidence is very uncertain (GRADE: Very low).We did not identify any studies that met the inclusion criteria for our economic literature review. We estimated that there were about 716 patients with challenging diagnostic primary CNS tumours in Ontario each year. The cost of clinical-based DNA methylation profiling for CNS tumours was $1,500 per patient. The annual incremental costs of second-tier DNA methylation classifier tests (after the use of conventional test) would be $1,074,738 for all challenging diagnostic cases, and DNA methylation-based classifier tests improved the diagnosis for 195 patients. The incremental cost-effectiveness ratio (ICER; i.e., the incremental cost per case with an improvement in primary CNS tumour classification) was $5,521. Scenario analyses showed that for children aged 0 to 14 years, the ICER was reduced to $2,683. Publicly funding second-tier DNA methylation-based classifier testing for challenging diagnostic cases of primary CNS tumours would result in a budget increase of about $1 million per year, with total additional costs of about $5.4 million over 5 years to test 3,600 patients. The budget increase for funding subgroup populations (e.g., children, patients with malignant tumours) would be smaller. If DNA methylation-based classifiers are used as first-tier tests for all patients with newly diagnosed primary CNS tumours, the additional funding costs would be about $4 million per year, with total additional funding costs of about $21 million over the initial 5-year period. Conclusions: DNA methylation-based classifier tests are an adjunct tool that may improve CNS tumour classification compared with conventional testing alone. Given that there are no empirical willingness-to-pay thresholds for an improvement in primary CNS tumour classification, the cost-effectiveness of DNA methylation-based classifier cannot be determined. Publicly funding second-tier DNA methylation-based classifier tests for challenging diagnostic primary CNS tumours would result in a total budget increase of about $5.4 million over 5 years. Public funding DNA methylation-based classifiers as first-tier tests for all patients with newly diagnosed primary CNS tumours would result in total budget increase of around $21 million over the next 5 years.

Indexed as

Central Nervous System NeoplasmsDNA MethylationTechnology Assessment, BiomedicalBiomarkers, TumorCost-Benefit AnalysisHumansBiomarkers, Tumor

Identifiers

PMID41312229
PMCPMC12647934

What OpenQuestion holds

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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.