Evidence map›Paper›PMID 41437818›Full record

ReviewHaematologica2026

Translocation t(11;14) and BCL2-inhibition in multiple myeloma.

Shirlene Sim, Binod Dhakal, Hang Quach

Abstract readReview
In one paragraph

Review in Haematologica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shirlene SimClinical Haematology Department, St Vincent's Hospital Melbourne, Fitzroy, Victoria 3065, Australia; Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3065. Shirlene.Sim@svha.org.au.
Binod DhakalBone Marrow Transplantation and Cell Therapy, Division of Haematology and Oncology, Medical College of Wisconsin, Milwaukee, WI 53226.
Hang QuachClinical Haematology Department, St Vincent's Hospital Melbourne, Fitzroy, Victoria 3065, Australia; Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3065.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma is an increasingly treatable disease with improved survival, although characterized by multiple subclones that drive heterogeneity and variable clinical outcomes between patients. A biomarker-driven approach can help to tailor treatment and improve patient outcomes. Translocation t(11;14), a primary cytogenetic abnormality present in 15-20% of myeloma patients at diagnosis, is currently the most prominent targetable lesion in myeloma. In the era of induction with proteasome inhibitors and/or immunomodulatory drugs, t(11;14) has been associated with poorer outcomes compared to other standard-risk subgroups, with shorter progression-free and overall survival. The presence of t(11;14) in myeloma cells confers increased dependence on the pro-survival BCL2 protein, thus driving its ability to evade apoptosis, and is the main biomarker predicting response to BCL2-inhibitors. This review examines the pathogenesis and prognostic significance of t(11;14) in myeloma and the impact of concurrent high-risk cytogenetics, the mechanism of action of BCL2-inhibitors, cumulative evidence supporting their use, and proposed mechanisms of resistance. The review also presents potential future directions regarding BCL2-inhibitor-based regimens and how best to position these drugs to optimize patient outcomes.

Indexed as

Chromosomes, Human, Pair 11Chromosomes, Human, Pair 14Multiple MyelomaProto-Oncogene Proteins c-bcl-2Translocation, GeneticDrug Resistance, NeoplasmHumansPrognosisBCL2 protein, humanProto-Oncogene Proteins c-bcl-2

Identifiers

PMID41437818
PMCPMC13482237

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Registered trials

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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.