Evidence map›Paper›PMID 29191057›Full record

ReviewDrug delivery2017

Co-delivery nanoparticles of anti-cancer drugs for improving chemotherapy efficacy.

Shan-Shan Qi, Jia-Hui Sun, Hao-Han Yu, Shu-Qin Yu

Open access · goldAbstract readReview
In one paragraph

Review in Drug delivery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

67 citing papers in PubMed, 204 citations in OpenAlex.

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7 more citing papers are in PubMed but not listed here.

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.

Shan-Shan Qia Jiangsu Province Key Laboratory for Molecular and Medical Biotechnology , College of Life Sciences, Nanjing Normal University , Nanjing , The People's Republic of China.
Jia-Hui Suna Jiangsu Province Key Laboratory for Molecular and Medical Biotechnology , College of Life Sciences, Nanjing Normal University , Nanjing , The People's Republic of China.
Hao-Han Yuc Nanjing DeBioChem Inc , Nanjing , The People's Republic of China.
Shu-Qin Yua Jiangsu Province Key Laboratory for Molecular and Medical Biotechnology , College of Life Sciences, Nanjing Normal University , Nanjing , The People's Republic of China.ORCID http://orcid.org/0000-0002-2824-4651
Nanjing Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To achieve superior therapeutic efficacy, the combination chemotherapy using two or more anticancer drugs in clinical practice has been generally accepted as a feasible strategy. On account of the concept of combination chemotherapy, co-delivery of anticancer drugs with nanotechnology gradually becomes a desired strategy and one of the research frontiers on modern drug delivery. In recent years, nano drug co-delivery system (NDCDS), which loads at least two anticancer drugs with different physicochemical and pharmacological properties into a combination delivery system, has achieved rapid development. NDCDS synergistically inhibited the growth of the tumor compared with the free drugs. In this review, we highlighted the current state of co-delivery nanoparticles and the most commonly used nanomaterial, discussed challenges and strategies, and prospect future development.

Indexed as

AnimalsAntineoplastic AgentsDrug Delivery SystemsHumansNanoparticlesNanotechnologyNeoplasmsAntineoplastic AgentsCombination chemotherapydrug delivery materialsmultidrug resistance (MDR)nano drug co-delivery system (NDCDS)targeting nanoparticles

Identifiers

PMID29191057
PMCPMC8241150
OpenAlexW2772878912

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.