Evidence map›Paper›PMID 32027746›Full record

ArticleBlood advances2020

Genomic context and TP53 allele frequency define clinical outcomes in TP53-mutated myelodysplastic syndromes.

Guillermo Montalban-Bravo, Rashmi Kanagal-Shamanna, Christopher B Benton, Caleb A Class, Kelly S Chien, Koji Sasaki, Kiran Naqvi, Yesid Alvarado, Tapan M Kadia, Farhad Ravandi and 12 more

Open access · goldAbstract read
In one paragraph

Article in Blood advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed
11.1field-weighted citation impact, top 1% 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

76 citing papers in PubMed, 127 citations in OpenAlex.

  1. Eprenetapopt Plus Azacitidine inJournal of clinical oncology : official journal of the American Society of Clinical Oncology · 2021
    Trial
  2. Eprenetapopt (APR-246) and Azacitidine inJournal of clinical oncology : official journal of the American Society of Clinical Oncology · 2021
    Trial
  3. Trial
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  13. Pandora's Box of AML: HowBiomedicines · 2025
    Review
  14. Article
  15. Article
  16. Prognostic and Therapeutic Implications ofbioRxiv : the preprint server for biology · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Review

16 more citing papers are in PubMed but not listed here.

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

22 authors at 1 institution in 1 country.

Guillermo Montalban-BravoDepartment of Leukemia.
Rashmi Kanagal-ShamannaDepartment of Hematopathology, and.
Christopher B BentonDepartment of Leukemia.
Caleb A ClassDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
Kelly S ChienDepartment of Leukemia.
Koji SasakiDepartment of Leukemia.
Kiran NaqviDepartment of Leukemia.
Yesid AlvaradoDepartment of Leukemia.
Tapan M KadiaDepartment of Leukemia.
Farhad RavandiDepartment of Leukemia.
Naval DaverDepartment of Leukemia.
Koichi TakahashiDepartment of Leukemia.
Elias JabbourDepartment of Leukemia.
Gautham BorthakurDepartment of Leukemia.
Naveen PemmarajuDepartment of Leukemia.
Marina KonoplevaDepartment of Leukemia.
Kelly A SoltysiakDepartment of Leukemia.
Sherry R PierceDepartment of Leukemia.
Carlos E Bueso-RamosDepartment of Hematopathology, and.
Keyur P PatelDepartment of Hematopathology, and.
Hagop KantarjianDepartment of Leukemia.
Guillermo Garcia-ManeroDepartment of Leukemia.
The University of Texas MD Anderson Cancer Center · US

Funding

TRAINING FOR ACADEMIC ONCOLOGY/HEMATOLOGYT32CA009666 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Michael Davies, Courtney DiNardo · 1994 to 2026
$9.8M
NCI NIH HHS T32 CA009666
6 · The paper itself

Abstract

TP53 mutations are associated with adverse outcomes and shorter response to hypomethylating agents (HMAs) in myelodysplastic syndrome (MDS). Limited data have evaluated the impact of the type, number, and patterns of TP53 mutations in response outcomes and prognosis of MDS. We evaluated the clinicopathologic characteristics, outcomes, and response to therapy of 261 patients with MDS and TP53 mutations. Median age was 68 years (range, 18-80 years). A total of 217 patients (83%) had a complex karyotype. TP53 mutations were detected at a median variant allele frequency (VAF) of 0.39 (range, 0.01-0.94). TP53 deletion was associated with lower overall response rate (ORR) (odds ratio, 0.3; P = .021), and lower TP53 VAF correlated with higher ORR to HMAs. Increase in TP53 VAF at the time of transformation was observed in 13 patients (61%), and previously undetectable mutations were observed in 15 patients (65%). TP53 VAF was associated with worse prognosis (hazard ratio, 1.02 per 1% VAF increase; 95% confidence interval, 1.01-1.03; P < .001). Integration of TP53 VAF and karyotypic complexity identified prognostic subgroups within TP53-mutant MDS. We developed a multivariable model for overall survival that included the revised International Prognostic Scoring System (IPSS-R) categories and TP53 VAF. Total score for each patient was calculated as follows: VAF TP53 + 13 × IPSS-R blast score + 16 × IPSS-R cytogenetic score + 28 × IPSS-R hemoglobin score + 46 × IPSS-R platelet score. Use of this model identified 4 prognostic subgroups with median survival times of not reached, 42.2, 21.9, and 9.2 months. These data suggest that outcomes of patients with TP53-mutated MDS are heterogeneous and that transformation may be driven not only by TP53 but also by other factors.

Indexed as

Myelodysplastic SyndromesTumor Suppressor Protein p53AdolescentAdultAgedAged, 80 and overGene FrequencyGenomicsHumansMiddle AgedMutationPrognosisYoung AdultTP53 protein, humanTumor Suppressor Protein p53

Identifiers

PMID32027746
PMCPMC7013259
OpenAlexW3005329625

What OpenQuestion holds

Textmetadata
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.