ArticleCancer2022
COVID-19 and patients with cancer: Investigating treatment impact, information sources, and COVID-19-related knowledge, attitudes, and practices.
Article in Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Patient Perspectives on Virtual vs In-Person Posttreatment Care for Brain Metastases.Advances in radiation oncology · 2025Article
- Identifying predictors of COVID-related delays in cancer-specific medical care.Cancer medicine · 2024Article
- Efficacy, safety, and molecular response predictors of oral ixazomib and short-course rituximab in untreated iNHL.Blood advances · 2023Article
- Article
- COVID-19 and Cancer Patients in the Second Year of the Pandemic: Investigating Treatment Impact, Information Sources, and COVID-19-Related Knowledge, Attitudes and Practices.Current oncology (Toronto, Ont.) · 2022Article
- Cancer Patients' Experiences with Telehealth before and during the COVID-19 Pandemic in British Columbia.Current oncology (Toronto, Ont.) · 2022Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundThe coronavirus disease 2019 (COVID-19) pandemic has caused enormous strain on public health. Patients with cancer are particularly susceptible to the disease, and their treatment plans have been threatened by public health restrictions designed to contain the spread.
methodsThis study examined the effects of the pandemic on cancer patients' psychology, knowledge, attitudes, and practices concerning COVID-19 as well as their perceptions of the impact of COVID-19 on their cancer health care services. A survey was sent to 5800 patients at a cancer center in Toronto, Canada. Descriptive results were summarized. Qualitative feedback was coded and summarized. To examine for potential associations, regression models were tested for the outcomes of patient psychological well-being, knowledge, attitudes, and practices, and they accounted for several demographic, health literacy, and disease variables.
resultsA total of 1631 surveys were completed. Most patients saw their appointments shifted to virtual visits, and for a substantial minority, there was no change. A majority of the patients (62%) expressed fears about contracting the virus. There were no independent predictors of COVID-19-related knowledge. Fears were more pronounced among patients who did not speak English and those who used social media more often. Female participants, those who scored higher on knowledge questions, and those who used cancer center materials were more likely to take preventative measures against infection.
conclusionsThis study provides a snapshot of the state of cancer patient treatment and the knowledge, attitudes, and practices of patients between the first 2 waves of the pandemic. The study's results can inform our understanding of adaptation to conditions during and after the outbreak.
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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.