Evidence map›Paper›PMID 40590881›Full record

ArticleBlood advances2025

From CyBorD to dara-CyBorD, ASCT utilization trends in AL amyloidosis: a 15-year analysis.

Eli Muchtar, Angela Dispenzieri, Francis K Buadi, Prashant Kapoor, David Dingli, Taxiarchis V Kourelis, Wilson Gonsalves, Nelson Leung, Suzanne R Hayman, Martha Q Lacy and 10 more

Abstract read
In one paragraph

Article in Blood advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. [Clinical features and pathological scoring analysis of hepatic amyloidosis].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026
    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

20 authors.

Eli MuchtarDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0003-2210-2174
Angela DispenzieriDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0001-8780-9512
Francis K BuadiDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0003-3214-0203
Prashant KapoorDivision of Hematology, Mayo Clinic, Rochester, MN.
David DingliDivision of Hematology, Mayo Clinic, Rochester, MN.
Taxiarchis V KourelisDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0001-8573-9434
Wilson GonsalvesDivision of Hematology, Mayo Clinic, Rochester, MN.
Nelson LeungDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0002-5651-1411
Suzanne R HaymanDivision of Hematology, Mayo Clinic, Rochester, MN.
Martha Q LacyDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0003-1193-1559
Mustaqeem SiddiquiDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0002-4640-7311
Joselle CookDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0001-5335-9533
Nadine AbdallahDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0001-9195-1589
Moritz BinderDivision of Hematology, Mayo Clinic, Rochester, MN.
Saurabh ZanwarDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0001-5074-8453
William HoganDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0002-5841-4105
Rahma WarsameDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0003-0240-0326
S Vincent RajkumarDivision of Hematology, Mayo Clinic, Rochester, MN.
Shaji K KumarDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0001-5392-9284
Morie A GertzDivision of Hematology, Mayo Clinic, Rochester, MN.ORCID 0000-0002-3853-5196

Funding

Project 4: Targeting Resistance to T-Cell Directed Therapy in Multiple MyelomaP50CA186781 · NCI · MAYO CLINIC ARIZONA · PI Peter Leif Bergsagel · 2015 to 2026
$25.5M
NCI NIH HHS P50 CA186781
6 · The paper itself

Abstract

abstractThis retrospective analysis examined 15 years of autologous stem cell transplantation (ASCT) for light chain (AL) amyloidosis at the Mayo Clinic (2010-2024). We aimed to assess ASCT utilization trends, factors influencing practice changes, and current indications amid newer therapies. Four hundred and forty-one ASCTs were divided into cohort 1 (2010-2019) and cohort 2 (2020-2024), revealing a significant ASCT reduction in cohort 2 (385 vs 56, average 71% annual decrease). Cohort 2 patients were older, more likely to have relapsed/refractory disease, and had higher baseline bone marrow plasma cell burden compared to cohort 1. Pre-ASCT induction was more frequent in cohort 2 (89.3% vs 56.4%), with daratumumab (Dara)-cyclophosphamide-bortezomib-dexamethasone (CyBorD) replacing CyBorD as the predominant induction regimen. Lymphoma-based regimens were also more common in cohort 2 (15.1% vs 5.3%, P = .02). Day-100 satisfactory hematological response improved in cohort 2 (91.1% vs 72.7%, P = .001), although hematological complete response rates did not significantly differ (50.9% vs 38.8%, P = .09). In summary, there is a decrease in the utilization of ASCT in AL amyloidosis. This procedure is primarily reserved for patients with suboptimal responses, relapsed/refractory disease, lymphoplasmacytic clones (predominantly immunoglobulin M amyloidosis), or high bone marrow plasma cell burden (myeloma phenotype). This study underscores a significant shift in ASCT practice, driven by novel therapies, emphasizing more personalized management in AL amyloidosis.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsHematopoietic Stem Cell TransplantationImmunoglobulin Light-chain AmyloidosisAdultAgedAntibodies, MonoclonalBortezomibCyclophosphamideDexamethasoneFemaleHumansMaleMiddle AgedRetrospective StudiesTransplantation, AutologousTreatment OutcomeAntibodies, MonoclonalBortezomibCyclophosphamidedaratumumabDexamethasone

Identifiers

PMID40590881
PMCPMC12395166

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.