Evidence map›Paper›PMID 36661708›Full record

ArticleCurrent oncology (Toronto, Ont.)2023

Impact of COVID-19 Pandemic on Non-Small Cell Lung Cancer Care.

YiYuan Zhai, Pooja Chopra, David Kang, Nicholas J Robert, Wei Zhang

Abstract read
In one paragraph

Article in Current oncology (Toronto, Ont.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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

5 authors.

YiYuan ZhaiOntada, 6555 State Highway 161, Irving, TX 75039, USA.
Pooja ChopraOntada, 6555 State Highway 161, Irving, TX 75039, USA.
David KangOntada, 6555 State Highway 161, Irving, TX 75039, USA.
Nicholas J RobertOntada, 6555 State Highway 161, Irving, TX 75039, USA.
Wei ZhangOntada, 6555 State Highway 161, Irving, TX 75039, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We assessed the impact of COVID-19 on healthcare visits, timing of stage IV NSCLC diagnosis and immunotherapy initiation, and rates of switching to extended dosing schedules of immunotherapies among patients with stage IV NSCLC. This retrospective study examined electronic health record data of adult patients receiving treatment for stage IV NSCLC within The US Oncology Network and Onmark. Endpoints were compared for February-July 2019 (before COVID) vs. February-July 2020 (during COVID). The study found rapid decreases in numbers of patients with clinic/vital visits, immunotherapy initiations, and new diagnoses of stage IV NSCLC during April-May 2020 vs. April-May 2019. The rate of delays of immunotherapy administrations and proportions of patients with such delays increased from February to March of 2020. These patterns may have resulted from the increase in COVID-19 cases during this period and the corresponding quarantine and lockdowns. However, when comparing pre COVID-19 and during COVID-19 for May and after, the differences in delay of immuno-oncology administrations became less marked, likely due to lifting of lockdowns. The rate of switching from shorter to longer dosing schedules increased from May-July 2020. This was mainly attributed to pembrolizumab, likely due to FDA approval of the pembrolizumab 6W dosing schedule in April 2020.

Indexed as

Carcinoma, Non-Small-Cell LungCOVID-19Lung NeoplasmsAdultCommunicable Disease ControlHumansPandemicsRetrospective Studiescancer diagnosis delaycancer screening delaycancer treatment delayCOVID-19 impact on cancer careimmunotherapy dosing schedulenon-small cell lung cancer

Identifiers

PMID36661708
PMCPMC9858327

What OpenQuestion holds

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LicenceCC BY
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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.