Evidence map›Paper›PMID 28670436›Full record

ArticleHematology reports2017

Bridging-to-transplant with Azacitidine for Myelodysplastic Syndrome and Acute Myeloid Leukemia, Reduces the Incidence of Acute Graft-

Koichi Murakami, Hironori Ueno, Takashi Okabe, Toshiya Kagoo, Saigen Boku, Takahiro Yano, Akihiro Yokoyama

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Hematology reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

7 authors at 2 institutions in 1 country.

Koichi MurakamiDivision of Hematology, Department of Internal Medicine, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
Hironori UenoDivision of Hematology, Department of Internal Medicine, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
Takashi OkabeDivision of Hematology, Department of Internal Medicine, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
Toshiya KagooDivision of Hematology, Department of Internal Medicine, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
Saigen BokuDivision of Hematology, Department of Internal Medicine, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
Takahiro YanoDivision of Hematology, Department of Internal Medicine, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
Akihiro YokoyamaDivision of Hematology, Department of Internal Medicine, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
National Hospital Organization · JPTokyo Medical Center · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allogeneic stem cell transplantation (allo-SCT) is the only curative option for myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Azacitidine (AZA) has a good toxicity profile compared with intensive chemotherapy and can be considered a pre-transplant regimen in elderly patients and in patients with comorbidities. To investigate the impact of pre-transplant AZA on patient outcome after allo-SCT, we conducted a retrospective analysis of AZA pre-treatment followed by allo-SCT in patients with high-risk MDS and AML. Twenty patients who were divided into two groups according to AZA treatment given prior to allo-SCT (AZA

Indexed as

acute GVHDazacitidinebridging to transplanimmunomodulater

Identifiers

PMID28670436
PMCPMC5477469
OpenAlexW2626291518

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.