Evidence map›Paper›PMID 34953042›Full record

Trial reportCancer medicine2022

The added value of multi-state modelling in a randomized controlled trial: The HOVON 102 study re-analyzed.

Katerina Bakunina, Hein Putter, Jurjen Versluis, Eva A S Koster, Bronno van der Holt, Markus G Manz, Dimitri A Breems, Bjorn T Gjertsen, Jacqueline Cloos, Peter J M Valk and 6 more

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 25% of its field
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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Observational
  6. 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

16 authors at 9 institutions in 4 countries.

Katerina BakuninaDepartment of Hematology, HOVON Data Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.ORCID 0000-0003-3737-7971
Hein PutterDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Jurjen VersluisDepartment of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands.
Eva A S KosterDepartment of Hematology, Leiden University Medical Center, Leiden, The Netherlands.ORCID 0000-0002-8446-5133
Bronno van der HoltDepartment of Hematology, HOVON Data Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Markus G ManzDepartment of Medical Oncology and Hematology, University Hospital Zurich, Zurich, Switzerland.
Dimitri A BreemsDepartment of Hematology, Hospital Network Antwerp Stuivenberg/Middelheim, Antwerp, Belgium.
Bjorn T GjertsenDepartment of Internal Medicine, Hematology section, Haukeland University Hospital, Bergen, Norway.
Jacqueline CloosDepartment of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Peter J M ValkDepartment of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands.
Jakob PasswegDepartment of Hematology, University Hospital Basel, Basel, Switzerland.
Thomas PabstDepartment of Medical Oncology, University Hospital/Inselspital, Bern, Switzerland.
Gert J OssenkoppeleDepartment of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Bob LöwenbergDepartment of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands.
Jan J CornelissenDepartment of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands.
Liesbeth C de WreedeDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Erasmus MC · NLLeiden University Medical Center · NLCancer Center Amsterdam · NLErasmus MC Cancer Institute · NLHaukeland University Hospital · NOUniversity Hospital of Basel · CHUniversity Hospital of Bern · CHUniversity Hospital of Zurich · CHZNA Middelheim Hospital · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clofarabine is an active antileukemic drug for subgroups of patients with acute myeloid leukemia (AML). Multi-state models can provide additional insights to supplement the original intention-to-treat analysis of randomized controlled trials (RCT). We re-analyzed the HOVON102/SAKK30/09 phase III RCT for newly diagnosed AML patients, which randomized between standard induction chemotherapy with or without clofarabine. Using multi-state models, we evaluated the effects of induction chemotherapy outcomes (complete remission [CR], measurable residual disease [MRD]), and post-remission therapy with allogeneic stem cell transplantation [alloSCT] on relapse and death. Through the latter a consistent reduction in the hazard of relapse in the clofarabine arm compared to the standard arm was found, which occurred irrespective of MRD status or post-remission treatment with alloSCT, demonstrating a strong and persistent antileukemic effect of clofarabine. During the time period between achieving CR and possible post-remission treatment with alloSCT, non-relapse mortality was higher in patients receiving clofarabine. An overall net benefit of treatment with clofarabine was identified using the composite endpoint current leukemia-free survival (CLFS). In conclusion, these results enforce and extend the earlier reported beneficial effect of clofarabine in AML and show that multi-state models further detail the effect of treatment on competing and series of events.

Indexed as

Hematopoietic Stem Cell TransplantationLeukemia, Myeloid, AcuteClofarabineHumansRecurrenceRemission InductionTreatment OutcomeClofarabineAMLclofarabinecurrent leukemia-free survivalHSCTmulti-state modelRCT

Identifiers

PMID34953042
PMCPMC8817075
OpenAlexW4200293057

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.