Evidence map›Paper›PMID 38845982›Full record

ArticleHeliyon2024

A telomere-related gene risk model for predicting prognosis and treatment response in acute myeloid leukemia.

Hui-Zhong Shi, Ming-Wei Wang, Yu-Song Huang, Zhong Liu, Ling Li, Li-Ping Wan

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Hui-Zhong ShiDepartment of Hematology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Shanghai, 200080, China.
Ming-Wei WangInstitute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu 610052, China.
Yu-Song HuangDepartment of Cardiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhong LiuInstitute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu 610052, China.
Ling LiDepartment of Blood Transfusion, The Third People's Hospital of Chengdu, College of Medicine, Southwest Jiaotong University, Chengdu 610031, China.
Li-Ping WanDepartment of Hematology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Shanghai, 200080, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) is a prevalent hematological malignancy among adults. Recent studies suggest that the length of telomeres could significantly affect both the risk of developing AML and the overall survival (OS). Despite the limited focus on the prognostic value of telomere-related genes (TRGs) in AML, our study aims at addressing this gap by compiling a list of TRGs from TelNet, as well as collecting clinical information and TRGs expression data through the Gene Expression Omnibus (GEO) database. The GSE37642 dataset, sourced from GEO and based on the GPL96 platform, was divided into training and validation sets at a 6:4 ratio. Additionally, the GSE71014 dataset (based on the GPL10558 platform), GSE12417 dataset (based on the GPL96 and GPL570 platforms), and another portion of the GSE37642 dataset (based on the GPL570 platform) were designated as external testing sets. Univariate Cox regression analysis identified 96 TRGs significantly associated with OS. Subsequent Lasso-Cox stepwise regression analysis pinpointed eight TRGs (MCPH1, SLC25A6, STK19, PSAT1, KCTD15, DNMT3B, PSMD5, and TAF2) exhibiting robust predictive potential for patient survival. Both univariate and multivariate survival analyses unveiled TRG risk scores and age as independent prognostic variables. To refine the accuracy of survival prognosis, we developed both a nomogram integrating clinical parameters and a predictive risk score model based on TRGs. In subsequent investigations, associations were emphasized not solely regarding the TRG risk score and immune infiltration patterns but also concerning the response to immune-checkpoint inhibitor (ICI) therapy. In summary, the establishment of a telomere-associated genetic risk model offers a valuable tool for prognosticating AML outcomes, thereby facilitating informed treatment decisions.

Indexed as

Acute myeloid leukemiaImmunotherapyPrognostic modelSurvival analysisTelomere

Identifiers

PMID38845982
PMCPMC11153201

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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.