Evidence map›Paper›PMID 33210442›Full record

ArticleThe oncologist2021

Cancer in Lockdown: Impact of the COVID-19 Pandemic on Patients with Cancer.

Harsha Moraliyage, Daswin De Silva, Weranja Ranasinghe, Achini Adikari, Damminda Alahakoon, Raj Prasad, Nathan Lawrentschuk, Damien Bolton

Abstract read
In one paragraph

Article in The oncologist, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 4 pooled it
–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

75 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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15 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

8 authors.

Harsha MoraliyageResearch Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia.ORCID 0000-0002-6212-8312
Daswin De SilvaResearch Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia.
Weranja RanasingheResearch Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia.
Achini AdikariResearch Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia.
Damminda AlahakoonResearch Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia.
Raj PrasadNational Health Service Trust, North Bristol, England, United Kingdom.
Nathan LawrentschukDepartment of Surgery, University of Melbourne and Olivia Newton-John Cancer Centre, Austin Hospital, Melbourne, Australia.
Damien BoltonDepartment of Surgery, University of Melbourne and Olivia Newton-John Cancer Centre, Austin Hospital, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lockdown measures of the ongoing COVID-19 pandemic have disengaged patients with cancer from formal health care settings, leading to an increased use of social media platforms to address unmet needs and expectations. Although remote health technologies have addressed some of the medical needs, the emotional and mental well-being of these patients remain underexplored and underreported. We used a validated artificial intelligence framework to conduct a comprehensive real-time analysis of two data sets of 2,469,822 tweets and 21,800 discussions by patients with cancer during this pandemic. Lung and breast cancer are most prominently discussed, and the most concerns were expressed regarding delayed diagnosis, cancellations, missed treatments, and weakened immunity. All patients expressed significant negative sentiment, with fear being the predominant emotion. Even as some lockdown measures ease, it is crucial that patients with cancer are engaged using social media platforms for real-time identification of issues and the provision of informational and emotional support.

Indexed as

Communicable Disease ControlCOVID-19Datasets as TopicFearHumansInformation DisseminationMedical OncologyMental HealthNeoplasmsPandemicsSARS-CoV-2Social MediaTelemedicine

Identifiers

PMID33210442
PMCPMC7753606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.