Evidence map›Paper›PMID 27419369›Full record

ArticleOncotarget2016

Somatic mutations predict outcomes of hypomethylating therapy in patients with myelodysplastic syndrome.

Seung-Hyun Jung, Yoo-Jin Kim, Seon-Hee Yim, Hye-Jung Kim, Yong-Rim Kwon, Eun-Hye Hur, Bon-Kwan Goo, Yun-Suk Choi, Sug Hyung Lee, Yeun-Jun Chung and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 4 pooled it
7.3field-weighted citation impact, top 2% 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

42 citing papers in PubMed, 4 syntheses or guidelines pooled it, 68 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

11 authors at 4 institutions in 1 country.

Seung-Hyun JungIntegrated Research Center for Genome Polymorphism, Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Yoo-Jin KimCatholic Blood and Marrow Transplantation Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Seon-Hee YimIntegrated Research Center for Genome Polymorphism, Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Hye-Jung KimCatholic Blood and Marrow Transplantation Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Yong-Rim KwonCatholic Blood and Marrow Transplantation Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Eun-Hye HurDepartment of Hematology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Bon-Kwan GooDepartment of Hematology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Yun-Suk ChoiDepartment of Hematology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Sug Hyung LeeDepartment of Pathology, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Yeun-Jun ChungIntegrated Research Center for Genome Polymorphism, Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Je-Hwan LeeDepartment of Hematology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Catholic University of Korea · KRUlsan College · KRUniversity of Ulsan · KRSeoul St. Mary's Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although hypomethylating therapy (HMT) is the first line therapy in higher-risk myelodysplastic syndromes (MDS), predicting response to HMT remains an unresolved issue. We aimed to identify mutations associated with response to HMT and survival in MDS. A total of 107 Korean patients with MDS who underwent HMT (57 responders and 50 non-responders) were enrolled. Targeted deep sequencing (median depth of coverage 1,623X) was performed for 26 candidate MDS genes. In multivariate analysis, no mutation was significantly associated with response to HMT, but a lower hemoglobin level (<10g/dL, OR 3.56, 95% CI 1.22-10.33) and low platelet count (<50,000/μL, OR 2.49, 95% CI 1.05-5.93) were independent markers of poor response to HMT. In the subgroup analysis by type of HMT agents, U2AF1 mutation was significantly associated with non-response to azacitidine, which was consistent in multivariate analysis (OR 14.96, 95% CI 1.67-134.18). Regarding overall survival, mutations in DNMT1 (P=0.031), DNMT3A (P=0.006), RAS (P=0.043), and TP53 (P=0.008), and two clinical variables (male-gender, P=0.002; IPSS-R H/VH, P=0.026) were independent predicting factors of poor prognosis. For AML-free survival, mutations in DNMT3A (P<0.001), RAS (P=0.001), and TP53 (P=0.047), and two clinical variables (male-gender, P=0.024; IPSS-R H/VH, P=0.005) were independent predicting factors of poor prognosis. By combining these mutations and clinical predictors, we developed a quantitative scoring model for response to azacitidine, overall- and AML-free survival. Response to azacitidine and survival rates became worse significantly with increasing risk-scores. This scoring model can make prognosis prediction more reliable and clinically applicable.

Indexed as

MutationAdultAgedAzacitidineDioxygenasesDNA-Binding ProteinsDNA (Cytosine-5-)-MethyltransferasesDNA MethylationDNA Methyltransferase 3AFemaleGenes, p53Genes, rasHumansMaleMiddle AgedMyelodysplastic SyndromesAzacitidineDioxygenasesDNA-Binding ProteinsDNA (Cytosine-5-)-MethyltransferasesDNA Methyltransferase 3ADNMT3A protein, humanProto-Oncogene ProteinsSplicing Factor U2AFTET2 protein, humanU2AF1 protein, humanhypomethylating therapymutationmyelodysplastic syndrometargeted sequencing

Identifiers

PMID27419369
PMCPMC5342416
OpenAlexW2469280064

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.