Evidence map›Paper›PMID 38098254›Full record

ArticleCancer medicine2023

Assessment of 2022 European LeukemiaNet risk classification system in real-world cohort from China.

Enbo Chen, Changqing Jiao, Jian Yu, Yu Gong, Duo Jin, Xiaoyu Ma, Jianling Cui, Zhonghui Wu, Junjie Zhou, Haixia Wang and 2 more

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 7% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

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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

12 authors at 1 institution in 1 country.

Enbo ChenDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Changqing JiaoDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Jian YuDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Yu GongDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Duo JinDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Xiaoyu MaDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Jianling CuiDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Zhonghui WuDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Junjie ZhouDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Haixia WangDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Bobing SuDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Jian GeDepartment of Hematology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.ORCID 0000-0002-6963-287X
Anhui Medical University · CN

Funding

National Natural Science Foundation of China 81200371National Natural Science Foundation of China 82370175Postgraduate Innovation Research and Practice Program of Anhui Medical University YJS20230016Research Foundation of Anhui Medical University 2020xkj166Research Foundation of Anhui Provincial Institute of Translational Medicine 2021zhyx-C32
6 · The paper itself

Abstract

backgroundThe European LeukemiaNet (ELN) risk classification system for acute myeloid leukemia (AML) patients has been used worldwide. In 2022, the ELN risk classification system modified risk genes including CEBPA mutation status, myelodysplasia-related (MR) gene mutations and internal tandem duplications of FLT3 (FLT3-ITD).

methodsWe include newly diagnosed de novo AML patients at our center from January 2017 to December 2021, regardless of the further treatment received. Clinical data and date of survival were included. Survival analysis were performed using the Kaplan-Meier method, and the log-rank test was used to compare survival between different risk groups.

resultsWe include 363 newly diagnosed de novo AML patients from 2017 to 2021 to assess the accuracy of the ELN risk classification system. Their survival results show that the ELN-2022 risk classification system is not superior to the ELN-2017 version; for patients with FLT3-ITD mutations but without FLT3 inhibitor treatment, their survival is similar to the ELN-2022 adverse risk group. The ELN-2022 risk classification system cannot accurately clarify ECOG performance status (PS) 2-4 patients, especially in the ELN-2022 favorable risk group.

conclusionThe ELN-2022 risk stratification system may not be appropriate for patients unable to receive intensive therapy or FLT3 inhibitor; more real-world data is needed to straify patients with worse ECOG PS and inferior intensive therapy.

Indexed as

Leukemia, Myeloid, AcuteNucleophosminHumansMutationPrognosisRisk AssessmentRisk FactorsSurvival AnalysisNucleophosminacute myeloid leukemiaEuropean LeukemiaNetFLT3-ITD mutationsreal-worldrisk classifications

Identifiers

PMID38098254
PMCPMC10757130
OpenAlexW4389790197

What OpenQuestion holds

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LicenceCC BY
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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.