Evidence map›Paper›PMID 32570729›Full record

ReviewCancers2020

Nanomedicine in Non-Small Cell Lung Cancer: From Conventional Treatments to Immunotherapy.

Coral García-Fernández, Cristina Fornaguera, Salvador Borrós

Abstract readReview
In one paragraph

Review in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Review
  2. Article
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  13. Article
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  15. Article
  16. Efficacy analysis of targeted nanodrug for non-small cell lung cancer therapy.Frontiers in bioengineering and biotechnology · 2022
    Article
  17. Review
  18. Review
  19. Review
  20. The Nanosystems Involved in Treating Lung Cancer.Life (Basel, Switzerland) · 2021
    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

3 authors.

Coral García-FernándezGrup d'Enginyeria de Materials (GEMAT), Institut Químic de Sarrià (IQS), Universitat Ramon Llull (URL), 08022 Barcelona, Spain.ORCID 0000-0001-5788-2727
Cristina FornagueraGrup d'Enginyeria de Materials (GEMAT), Institut Químic de Sarrià (IQS), Universitat Ramon Llull (URL), 08022 Barcelona, Spain.ORCID 0000-0002-7014-3213
Salvador BorrósGrup d'Enginyeria de Materials (GEMAT), Institut Químic de Sarrià (IQS), Universitat Ramon Llull (URL), 08022 Barcelona, Spain.ORCID 0000-0002-4003-0381

Funding

Agència de Gestió d'Ajuts Universitaris i de Recerca SGR 2017 1559Ministerio de Ciencia, Innovación y Universidades RTI2018-094734-B-C22
6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC) remains the most common cause of cancer-related mortality. The heterogeneous nature of this disease hinders its diagnosis and treatment, requiring continuous advances in research aiming to understand its intricate nature. Consequently, the retrospective analysis of conventional therapies has allowed the introduction of novel tools provided by nanotechnology, leading to considerable improvements in clinical outcomes. Furthermore, the development of novel immunotherapies based on the recently understood interaction of the immune system with the tumor highlights the real possibility of definitively treating NSCLC from its early stages. Novel engineering approaches in nanomedicine will enable to overcome the intrinsic limits of conventional and emerging therapies regarding off-site cytotoxicity, specificity, resistance mechanisms, and administration issues. The convergence point of these therapies with nanotechnology lays the foundation for achieving currently unmet needs.

Indexed as

cancer vaccinechemotherapyimmunotherapiesnanomedicinenon-small cell lung cancer

Identifiers

PMID32570729
PMCPMC7352459

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.