Evidence map›Paper›PMID 41682677›Full record

ReviewJournal of clinical medicine2026

Ultra-Sensitive Mutation Detection Technology in Myeloid Neoplasms: New Tools for Patient Monitoring.

Alessandro Ferrando, Valentina Bonuomo, Arianna Savi, Daniela Cilloni

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2026. 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

4 authors.

Alessandro FerrandoDepartment of Clinical and Biological Sciences, University of Turin, 10124 Orbassano, Italy.ORCID 0009-0000-6304-9782
Valentina BonuomoDepartment of Clinical and Biological Sciences, University of Turin, 10124 Orbassano, Italy.ORCID 0000-0001-6491-8337
Arianna SaviDepartment of Clinical and Biological Sciences, University of Turin, 10124 Orbassano, Italy.
Daniela CilloniDepartment of Clinical and Biological Sciences, University of Turin, 10124 Orbassano, Italy.ORCID 0000-0001-6346-4791

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The clinical management of myeloid neoplasms increasingly relies on the accurate detection and longitudinal monitoring of disease-defining genetic alterations. Many clinically relevant mutations are often present at very low variant allele frequencies, below the detection limits of conventional approaches routinely used in diagnostic workflows. In recent years, a growing number of ultra-sensitive molecular technologies have been developed to overcome these limitations, enabling the detection of rare variants with unprecedented precision, offering complementary strengths in terms of sensitivity, quantification, throughput, and clinical applicability. This review provides a comprehensive overview of established and emerging ultra-sensitive technologies for the diagnosis and molecular monitoring of myeloid neoplasms, discussing their technical principles, advantages, and limitations.

Indexed as

diagnosismyeloid neoplasmspatient monitoringpersonalized medicinesensitivity

Identifiers

PMID41682677
PMCPMC12897794

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.