Evidence map›Paper›PMID 28346419›Full record

ReviewBone marrow transplantation2017

Evolving concepts in prognostic scoring of chronic GvHD.

A Lazaryan, M Arora

Open access · bronzeAbstract readReview
PubMed Publisher
In one paragraph

Review in Bone marrow transplantation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. 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

2 authors at 1 institution in 1 country.

A LazaryanDepartment of Medicine, Division of Hematology, Oncology and Transplantation, University of Minnesota Medical Center, Minneapolis, MN, USA.
M AroraDepartment of Medicine, Division of Hematology, Oncology and Transplantation, University of Minnesota Medical Center, Minneapolis, MN, USA.
University of Minnesota Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic GvHD (cGvHD) remains one of the most complex and challenging complications after allogeneic hematopoietic cell transplantation. Emerging knowledge about the clinical manifestations and associated organ involvement of cGvHD has led to the establishment of prognostic parameters for post-transplant survival among affected allograft recipients. Studies employing the pre-National Institutes of Health (NIH) consensus data on cGvHD incidence and its risks have led to development of the CIBMTR's cGvHD risk stratification, which serves as the most refined and validated prognostic tool for estimating survival of patients with cGvHD. However, cGvHD global severity scoring has recently evolved as a powerful prognostic tool for patient survival in the post-NIH consensus era. Current use of the substantially redefined NIH criteria of cGvHD diagnosis and measurements of its severity makes it challenging to interpret prognostic scoring systems generated in the pre-NIH era. Some of the pre-NIH prognostic parameters, however, appear to retain their significance in predicting survival independently from the NIH global severity score. Thus, future analyses of prospective cohorts of patients with cGvHD defined by NIH consensus criteria will be critical in reconciling and integrating various prognostic scoring systems of cGvHD.

Indexed as

Graft vs Host DiseaseHematopoietic Stem Cell TransplantationSeverity of Illness IndexAllograftsBiomarkersChronic DiseaseDisease-Free SurvivalHumansSurvival RateBiomarkers

Identifiers

PMID28346419
OpenAlexW2597600170

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.