Evidence map›Paper›PMID 31853234›Full record

ReviewDose-response : a publication of International Hormesis Society

Targeting Approaches of Nanomedicines in Acute Myeloid Leukemia.

Xiao Huang, Hai Lin, Feng Huang, Yuning Xie, Ka Hong Wong, Xiaoyu Chen, Dongyue Wu, Aiping Lu, Zhijun Yang

Abstract readReview
In one paragraph

Review in Dose-response : a publication of International Hormesis Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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

9 authors.

Xiao HuangSchool of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China.ORCID https://orcid.org/0000-0002-6144-2860
Hai LinDepartment of Traditional Chinese Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Feng HuangInstitute of Acupuncture & Moxibustion, China Academy of Chinese Medical Sciences, Beijing, China.
Yuning XieSchool of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China.
Ka Hong WongSchool of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China.
Xiaoyu ChenSchool of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China.
Dongyue WuDepartment of Traditional Chinese Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Aiping LuSchool of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China.
Zhijun YangSchool of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) is a hematological malignancy, which is commonly associated with high incidence and mortality among adult patients. The standard induction regimen for AML has been substantially unchanged over the past 40 years, for which novel nanomedicines have represented a promising strategy in AML therapies. Despite developments of multiple nanoparticles formulated with drugs or genes, less there is not much information available about approaches in AML is available. This review presents an overview of nanomedicines currently being evaluated in AML. First, it briefly summarized conventional chemotherapies in use. Second, nanomedicines presently ongoing in clinical trials or preclinical researches were classified and described, with illustrative examples from recent literatures. Finally, limitations and potential safety issues concerns in clinical translation of AML treatment were discussed as well.

Indexed as

acute myeloid leukemiacancer therapynanomedicinesnanoparticles

Identifiers

PMID31853234
PMCPMC6906351

What OpenQuestion holds

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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.