Evidence map›Paper›PMID 35622321›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Minimal Residual Disease Analysis by Monitoring Immunoglobulin and T-Cell Receptor Gene Rearrangements by Quantitative PCR and Droplet Digital PCR.

Irene Della Starza, Cornelia Eckert, Daniela Drandi, Giovanni Cazzaniga, EuroMRD Consortium

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  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.

Irene Della StarzaHematology, Department of Translational and Precision Medicine, "Sapienza" University of Rome, Rome, Italy.
Cornelia EckertDepartment of Pediatric Oncology Hematology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Daniela DrandiHematology Division, Department of Molecular Biotechnology and Health sciences, University of Torino, Torino, Italy.
Giovanni CazzanigaCentro Ricerca Tettamanti, Fondazione Tettamanti, Centro Maria Letizia Verga, Monza, Italy. giovanni.cazzaniga@unimib.it.
EuroMRD Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analysis of immunoglobulin and T-cell receptor gene rearrangements by real-time quantitative polymerase chain reaction (RQ-PCR) is the gold standard for sensitive and accurate minimal residual disease (MRD) monitoring; it has been extensively standardized and guidelines have been developed within the EuroMRD consortium ( www.euromrd.org ). However, new generations of PCR-based methods are standing out as potential alternatives to RQ-PCR, such as digital PCR technology (dPCR), the third-generation implementation of conventional PCR, which has the potential to overcome some of the limitations of RQ-PCR such as allowing the absolute quantification of nucleic acid targets without the need for a calibration curve. During the last years, droplet digital PCR (ddPCR) technology has been compared to RQ-PCR in several hematologic malignancies showing its proficiency for MRD analysis. So far, no established guidelines for ddPCR MRD analysis and data interpretation have been defined and its potential is still under investigation. However, a major standardization effort is underway within the EuroMRD consortium ( www.euromrd.org ) for future application of ddPCR in standard clinical practice.

Indexed as

Gene RearrangementGenes, T-Cell ReceptorImmunoglobulinsNeoplasm, ResidualHumansReal-Time Polymerase Chain ReactionReference StandardsImmunoglobulinsddPCRImmunoglobulinMinimal residual diseaseRearrangementRQ-PCRT-cell receptor

Identifiers

PMID35622321
PMCPMC9761497

What Socratic holds

Textmetadata
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 Socratic graph.