Evidence map›Paper›PMID 42455913›Full record

ArticleCancer2026

Longitudinal analysis of tyrosine kinase inhibitor therapy outcomes and BCR-ABL1 transcript decline velocity in chronic myeloid leukemia: A 16-year real-world study.

Moaath K Mustafa Ali, Emily C Zabor, Kamilla Abdurakhmanov, Hadil Zureigat, Ahmed N Mohamed, Muaz Alsabbagh Alchirazi, Aastha Dhakal, Ali Mushtaq, Naveen Rehman, Ameed Bawwab and 12 more

Abstract read
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Article in Cancer, 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
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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

22 authors.

Moaath K Mustafa AliDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0003-3289-2333
Emily C ZaborDepartment of Quantitative Health Sciences, Cleveland Clinic Lerner Research Institute, Cleveland, Ohio, USA.
Kamilla AbdurakhmanovDepartment of Quantitative Health Sciences, Cleveland Clinic Lerner Research Institute, Cleveland, Ohio, USA.ORCID https://orcid.org/0009-0004-9643-6438
Hadil ZureigatDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Ahmed N MohamedDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0001-9605-1539
Muaz Alsabbagh AlchiraziDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Aastha DhakalDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Ali MushtaqDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Naveen RehmanDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Ameed BawwabDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Bryan BerubeDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Lana KhatibDepartment of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
Akriti G JainDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0002-7238-9241
John C MolinaDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Sophia BaldermanDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Abhay SinghDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Aaron T GerdsDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Ronald SobecksDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Anjali S AdvaniDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Hetty E CarrawayDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Matt KalaycioDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.
Sudipto MukherjeeDepartment of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNo large, randomized trials have compared three or more tyrosine kinase inhibitors (TKIs) in a single chronic myeloid leukemia (CML) cohort. Most studies are two-arm comparisons versus imatinib, or rely on indirect methods.

methodsA retrospective cohort study was conducted of 349 patients with chronic- and accelerated-phase CML treated between 2007 and 2023 at Cleveland Clinic centers in Northeast Ohio. Overall survival (OS), event-free survival (EFS), 12-month therapeutic milestone achievement, and BCR-ABL1 transcript decline velocity across first-, second-, and third-line TKIs were compared. Baseline demographics, comorbidities, cytogenetics, and hematologic parameters were collected. Multivariable regression and time-dependent Cox models were adjusted for confounders and varying therapy initiation times.

resultsFirst-line TKIs included imatinib (53%), dasatinib (30%), nilotinib (15%), and bosutinib (2%). Median age ranged from 52 to 60 years, most patients were White, and high-risk cytogenetics were rare. Five-year OS ranged from 78% for dasatinib to 90% for nilotinib, with nilotinib associated with improved OS (hazard ratio [HR], 0.43) and EFS (HR, 0.48) and the fastest BCR-ABL1 decline (β = -8.3%) versus imatinib. In second- (n = 181) and third-line therapy (n = 91), no significant differences in outcomes were observed. Across all lines, time-dependent modeling showed improved EFS only for nilotinib (HR, 0.61). Unadjusted OS was higher in patients starting treatment in 2007-2010 versus later periods but differences disappeared after adjustment.

conclusionsReal-world data indicate that imatinib achieves comparable response rates to newer TKIs, with durable survival. Nilotinib consistently shows faster BCR-ABL1 decline and improved EFS overall, consistent with prior network meta-analyses. Lack of improvement in OS over time suggests the need to investigate factors influencing long-term outcomes in CML.

Indexed as

Fusion Proteins, bcr-ablLeukemia, Myelogenous, Chronic, BCR-ABL PositiveProtein Kinase InhibitorsAniline CompoundsDasatinibFemaleHumansImatinib MesylateLongitudinal StudiesMaleMiddle AgedNitrilesPyrimidinesQuinolinesRetrospective StudiesTreatment OutcomeAniline CompoundsBCR-ABL1 fusion protein, humanbosutinibDasatinibFusion Proteins, bcr-ablImatinib MesylatenilotinibNitrilesProtein Kinase InhibitorsPyrimidinesQuinolinesBCR‐ABL1 kineticschronic myeloid leukemiaevent‐free survivaloverall survivaltyrosine kinase inhibitors

Identifiers

PMID42455913
PMCPMC13372233

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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.