Evidence map›Paper›PMID 29700386›Full record

ArticleLeukemia2018

Minimal residual disease analysis in chronic lymphocytic leukemia: a way for achieving more personalized treatments.

Paolo Ghia, Andy Rawstron

Abstract read
PubMed Publisher
In one paragraph

Article in Leukemia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Measurable Residual Disease.Methods in molecular biology (Clifton, N.J.) · 2027
    Article
  3. Review
  4. Review
  5. 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

2 authors.

Paolo GhiaUniversità Vita-Salute San Raffaele and IRCCS Istituto Scientifico San Raffaele, Milano, Italy. ghia.paolo@hsr.it.ORCID http://orcid.org/0000-0003-3750-7342
Andy RawstronHaematological Malignancy Diagnostic Service (HMDS), Leeds Teaching Hospitals NHS Trust, Leeds and Department of Health Sciences, University of York, York, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Therapeutic approaches for chronic lymphocytic leukemia (CLL) have dramatically changed over the recent past. In parallel, quantification of minimal residual disease (MRD) proved to be an independent prognostic factor for progression-free and overall survival. The European Research Initiative on CLL (ERIC) in collaboration with American and Australasian partners developed harmonised assays that could be applied reproducibly to compare the efficacy of different treatments. The potential for MRD analysis to identify the most effective treatments prior to reaching survival endpoints was recognised by regulatory agencies and approved as an intermediate endpoint for licensure in randomized studies, in Europe. More recently treatment approaches have evolved, in particular with BCL2-pathway inhibitors, so that MRD analysis may be informative for most patients and clinical trials, potentially becoming a tool for managing CLL patients in clinical practice. In the recent past the importance of the type of MRD assay used, the most appropriate timing and compartment to assess for different treatment types have been learnt as we move towards eradicating residual disease beyond the guideline threshold of one cell in ten thousand. Nowadays, MRD assessment in CLL has quickly become an indispensable tool for clinical research and development that promise to change the way we manage our patients in the future.

Indexed as

High-Throughput Nucleotide SequencingHumansLeukemia, Lymphocytic, Chronic, B-CellNeoplasm, ResidualPrecision MedicineProtein Kinase InhibitorsProtein Kinase Inhibitors

Identifiers

What OpenQuestion 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 OpenQuestion graph.