Evidence map›Paper›PMID 29456860›Full record

ReviewBiomarker research2018

Protein kinase inhibitors for acute leukemia.

Yuan Ling, Qing Xie, Zikang Zhang, Hua Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Biomarker research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

24 citing papers in PubMed, 36 citations in OpenAlex.

  1. Review
  2. Article
  3. Kinase Inhibitors in Genetic Diseases.International journal of molecular sciences · 2023
    Review
  4. Article
  5. Article
  6. Review
  7. Recent Advances in Molecular Diagnosis and Prognosis of Childhood B Cell Lineage Acute Lymphoblastic Leukemia (B-ALL).Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion · 2021
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Cancer biomarkers for targeted therapy.Biomarker research · 2019
    Article
  18. Article
  19. Review
  20. 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

4 authors at 1 institution in 1 country.

Yuan LingGuangdong Provincial Key Laboratory of Medical Molecular Diagnostics, Institute of Laboratory Medicine, Guangdong Medical University, Dongguan, 523808 China.
Qing XieGuangdong Provincial Key Laboratory of Medical Molecular Diagnostics, Institute of Laboratory Medicine, Guangdong Medical University, Dongguan, 523808 China.
Zikang ZhangGuangdong Provincial Key Laboratory of Medical Molecular Diagnostics, Institute of Laboratory Medicine, Guangdong Medical University, Dongguan, 523808 China.
Hua ZhangGuangdong Provincial Key Laboratory of Medical Molecular Diagnostics, Institute of Laboratory Medicine, Guangdong Medical University, Dongguan, 523808 China.
Guangdong Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional treatments for acute leukemia include chemotherapy, radiation therapy, and intensive combined treatments (including bone marrow transplant or stem cell transplants). Novel treatment approaches are in active development. Recently, protein kinase inhibitors are on clinical trials and offer hope as new drugs for acute leukemia treatment. This review will provide a brief summary of the protein kinase inhibitors in clinical applications for acute leukemia treatment.

Indexed as

Acute lymphocyte leukemiaAcute myeloid leukemiaProtein kinase inhibitor

Identifiers

PMID29456860
PMCPMC5809833
OpenAlexW2795669086

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.