Evidence map›Paper›PMID 33549060›Full record

ArticleBMC cancer2021

A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS.

Siyu Gu, Jingya Xia, Yulu Tian, Jie Zi, Zheng Ge

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. P53 IHC Result as a Prognostic Tool in MDS.Iranian journal of pathology · 2023
    Article
  4. New investigational combinations for higher-risk MDS.Hematology. American Society of Hematology. Education Program · 2022
    Article
  5. Article
  6. Review
  7. Review
  8. Molecular Targeted Therapy and Immunotherapy for Myelodysplastic Syndrome.International journal of molecular sciences · 2021
    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

5 authors at 1 institution in 1 country.

Siyu GuDepartment of Hematology, Zhongda Hospital, School of Medicine, Southeast University, Institute of Hematology Southeast University, Nanjing, 210009, China.
Jingya XiaDepartment of Hematology, Zhongda Hospital, School of Medicine, Southeast University, Institute of Hematology Southeast University, Nanjing, 210009, China.
Yulu TianDepartment of Hematology, Zhongda Hospital, School of Medicine, Southeast University, Institute of Hematology Southeast University, Nanjing, 210009, China.
Jie ZiDepartment of Hematology, Zhongda Hospital, School of Medicine, Southeast University, Institute of Hematology Southeast University, Nanjing, 210009, China.
Zheng GeDepartment of Hematology, Zhongda Hospital, School of Medicine, Southeast University, Institute of Hematology Southeast University, Nanjing, 210009, China. Janege879@hotmail.com.ORCID http://orcid.org/0000-0001-8028-1612
Zhongda Hospital Southeast University · CN

Funding

Fundamental Research Funds for the Central Universities 2242019K3DZ02Jiangsu Province "333" project BRA2019103Jiangsu Provincial Special Program of Medical Science BE2017747Key Medical of Jiangsu Province ZDXKB2016020Milstein Medical Asian American Partnership (MMAAP) Foundation Research Project Award in Hematology 2017National Natural Science Foundation of China (CN) 81770172
6 · The paper itself

Abstract

backgroundThe treatment strategies for Myelodysplastic Syndromes (MDS) are usually based on the risk stratification system. However, few risk signatures which integrate the revised international prognostic scoring system (IPSS-R) with gene mutations can be easily applied in the real world.

methodsThe training cohort of 63 MDS patients was conducted at Zhongda Hospital of Southeast University from January 2013 to April 2020. The validation cohort of 141 MDS patients was obtained from GSE129828. The mutation scoring system was based on the number of mutations and a unique favorable prognostic factor, which is SF3B1 mutation. Univariate Cox, multivariate Cox, and LASSO regression analyses were used to determine the significant factors that influenced the overall survival. The receiver operating characteristic curve (ROC) was used to evaluate the efficiency of the prognostic model.

resultsA novel risk scoring system we named "mutation combined with revised international prognostic scoring system (MIPSS-R)" was developed based on the results derived from multivariate analysis which assigned points to the IPSS-R and the mutation scores according to their relative statistical weight. Based on the quintile of the new scores, patients were divided into five risk levels. The Kaplan-Meier curves showed the superiority of MIPSS-R in separating patients from different groups, comparing with IPSS-R both in the training cohort (p = 1.71e-08 vs. p = 1.363e-04) and validation cohort (p = 1.788e-04 vs. p = 2.757e-03). The area under the ROC of MIPSS-R was 0.79 in the training cohort and 0.62 in the validation cohort. The retrospective analysis of our house patients showed that the risk levels of 57.41% of patients would adjust according to MIPSS-R. After changing risk levels, 38.71% of patients would benefit from treatment strategies that MIPSS-R recommends.

conclusionA mutation scoring system was conducted based on the number of mutations and a unique favorable prognostic factor. MIPSS-R, the novel integral risk stratification system was developed by integrating IPSS-R and the mutation scores, which is more effective on prognosis and treatment guidance for MDS patients.

Indexed as

MutationAdultAgedAged, 80 and overArea Under CurveDioxygenasesDNA-Binding ProteinsFemaleGenes, p53HumansKaplan-Meier EstimateMaleMiddle AgedMyelodysplastic SyndromesPhosphoproteinsPrognosisASXL1 protein, humanDioxygenasesDNA-Binding ProteinsPhosphoproteinsProto-Oncogene ProteinsRepressor ProteinsRNA Splicing FactorsSerine-Arginine Splicing FactorsSF3B1 protein, humanSRSF2 protein, humanTET2 protein, humanMolecular abnormalitiesMyelodysplastic syndromePrognostic factorsReal-world study

Identifiers

PMID33549060
PMCPMC7866647
OpenAlexW3127754785

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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.