ArticleJournal of current science and technology2021
Perspective on the treatment of non-small cell lung cancer in the context of potential SARS-CoV-2 infection during the pandemic.
Article in Journal of current science and technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
SARS-CoV-2 infections are rising at an alarming rate and various aspects of this pandemic must be quickly and adequately addressed in order to enhance effective healthcare delivery and protect at risk populations such as cancer patients. Preventing Covid-19 infection must be a top system wide priority to avoid mortality, and considerable financial and disease burden. Most cancer patients, and in particular those with tumors resistant to chemotherapy are particularly vulnerable to infection. In this review, we connect potential viral infection of patients with lung tumors that have somewhat quiescence the immune response in the tumor microenvironment and categorize target molecules in metabolism that may be used to identify at risk patients leading to more effective treatment regimens; keeping continuity of therapy and disease prevention during a very tumultuous period of time surrounding the pandemic.
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Registered trials
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.