Evidence map›Paper›PMID 30578743›Full record

ArticleEuropean journal of haematology2019

Treatment patterns and healthcare resource utilization in patients with FLT3-mutated and wild-type acute myeloid leukemia: A medical chart study.

James D Griffin, Hongbo Yang, Yan Song, David Kinrich, Manasee V Shah, Cat N Bui

Open access · hybridAbstract read
In one paragraph

Article in European journal of haematology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Treatment Patterns andTherapeutics and clinical risk management · 2024
    Article
  3. Article
  4. Article
  5. Cost-effectiveness of gilteritinib for relapsed/refractoryJournal of managed care & specialty pharmacy · 2021
    Article
  6. Review
  7. 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

6 authors at 3 institutions in 1 country.

James D GriffinDana-Farber Cancer Institute, Boston, Massachusetts.
Hongbo YangAnalysis Group, Inc., Boston, Massachusetts.
Yan SongAnalysis Group, Inc., Boston, Massachusetts.
David KinrichAnalysis Group, Inc., Boston, Massachusetts.
Manasee V ShahAstellas Pharma US, Inc., Northbrook, Illinois.
Cat N BuiAstellas Pharma US, Inc., Northbrook, Illinois.
Analysis Group (United States) · USAstellas Pharma (United States) · USDana-Farber Cancer Institute · US

Funding

TYROSINE KINASE ONCOGENESIS IN MYELOID LEUKEMIAP01CA066996 · NCI · DANA-FARBER CANCER INSTITUTE · PI SCOTT A ARMSTRONG · 1996 to 2026
$52.5M
Astellas Pharma USNCI NIH HHS P01 CA066996
6 · The paper itself

Abstract

objectivesTo assess real-world treatment patterns and healthcare resource utilization (HRU) among patients with FLT3-mutated (FLT3

methodsData were abstracted from medical charts of patients with AML from 10 countries. Patients were grouped based on their FLT3 mutation status, age (18-64 or ≥65), and whether they were newly diagnosed (ND) or relapsed/refractory (R/R).

resultsCharts of 1027 AML patients were included (183 FLT3

conclusionsTreatment patterns of AML were heterogeneous and FLT3

Indexed as

MutationPatient Acceptance of Health CarePractice Patterns, Physicians'AdultAgedAllelesCombined Modality TherapyComorbidityDisease ManagementDrug Resistance, NeoplasmFemalefms-Like Tyrosine Kinase 3Health Care SurveysHealth ResourcesHumansLeukemia, Myeloid, AcuteFLT3 protein, humanfms-Like Tyrosine Kinase 3acute myeloid leukemiaFLT3 mutationhealthcare resource utilizationtreatment patterns

Identifiers

PMID30578743
PMCPMC6850763
OpenAlexW2906408484

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.