Evidence map›Paper›PMID 36356416›Full record

ArticleESMO open2022

Changes in anticancer treatment plans in patients with solid cancer hospitalized with COVID-19: analysis of the nationwide BSMO-COVID registry providing lessons for the future.

T Geukens, M Brandão, A Laenen, J Collignon, C Van Marcke, I Louviaux, W Demey, S Van Wambeke, D Schrijvers, S Lecomte and 18 more

Abstract read
In one paragraph

Article in ESMO open, 2022. 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. Article
  2. Article
  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

28 authors.

T GeukensLaboratory for Translational Breast Cancer Research, KU Leuven, Leuven. Electronic address: tatjana.geukens@kuleuven.be.
M BrandãoDepartment of Medical Oncology, Institut Jules Bordet and L'Université Libre de Bruxelles (U.L.B), Brussels.
A LaenenLeuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), KU Leuven, Leuven.
J CollignonDepartment of Medical Oncology, CHU Liège, Liège.
C Van MarckeDepartment of Medical Oncology, King Albert II Cancer Institute, Cliniques Universitaires Saint-Luc, Brussels; Institut de Recherche Expérimentale et Clinique (IREC), Pole of Medical Imaging, Radiotherapy and Oncology (MIRO), Université Catholique de Louvain (UCLouvain), Brussels.
I LouviauxDepartment of Medical Oncology, CHR Citadelle, Liège.
W DemeyDepartment of Medical Oncology, AZ Klina, Brasschaat.
S Van WambekeDepartment of Medical Oncology, Ziekenhuisnetwerk Antwerpen, Antwerp.
D SchrijversDepartment of Medical Oncology, Ziekenhuisnetwerk Antwerpen, Antwerp.
S LecomteDepartment of Medical Oncology, CHU Brugmann, Brussels.
J MebisDepartment of Medical Oncology, Jessa Hospital, Hasselt.
A RuttenDepartment of Medical Oncology, Ziekenhuizen Gasthuiszusters Antwerp, Antwerp.
C FontaineDepartment of Medical Oncology, UZ Brussels, Brussels.
W LybaertDepartment of Medical Oncology, VITAZ, Sint-Niklaas.
S AspeslaghDepartment of Medical Oncology, UZ Brussels, Brussels.
J-C GoeminneDepartment of Medical Oncology, CHU-UCL Namur, Namur.
H Van Den BulckDepartment of Medical Oncology, Imelda Hospital, Bonheiden.
E SerontDepartment of Medical Oncology, Hopital de Jolimont, Haine Saint Paul.
L De BackerDepartment of Medical Oncology, Sint-Andriesziekenhuis, Tielt.
W De RoockDepartment of Oncology-Hematology-Radiotherapy, Ziekenhuis Oost-Limburg and Limburgs Oncologisch Centrum, Genk.
M IgnatiadisDepartment of Medical Oncology, Institut Jules Bordet and L'Université Libre de Bruxelles (U.L.B), Brussels; Academic Trials Promoting Team (ATPT), Institut Jules Bordet, Brussels.
H PrenenDepartment of Oncology, University Hospital Antwerp, Edegem.
D Van BeckhovenDepartment of Epidemiology and Public Health, Sciensano, Brussels.
M HeijlenDepartment of General Medical Oncology and Multidisciplinary Breast Centre, Leuven Cancer Institute and University Hospitals Leuven, Leuven.
J VerheezenDepartment of Medical Oncology, St. Trudo Hospital, Sint-Truiden.
S RotteyDepartment of Medical Oncology, Ghent University Hospital, Ghent, Belgium.
K PunieDepartment of General Medical Oncology and Multidisciplinary Breast Centre, Leuven Cancer Institute and University Hospitals Leuven, Leuven.
E de AzambujaDepartment of Medical Oncology, Institut Jules Bordet and L'Université Libre de Bruxelles (U.L.B), Brussels.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSolid cancer is an independent prognostic factor for poor outcome with COVID-19. As guidelines for patient management in that setting depend on retrospective efforts, we here present the first analyses of a nationwide database of patients with cancer hospitalized with COVID-19 in Belgium, with a focus on changes in anticancer treatment plans at the time of SARS-CoV-2 infection.

methodsNineteen Belgian hospitals identified all patients with a history of solid cancer hospitalized with COVID-19 between March 2020 and February 2021. Demographic, cancer-specific and COVID-specific data were pseudonymously entered into a central Belgian Society of Medical Oncology (BSMO)-COVID database. The association between survival and primary cancer type was analyzed through multivariate multinomial logistic regression. Group comparisons for categorical variables were carried out through a Chi-square test.

resultsA total of 928 patients were registered in the database; most of them were aged ≥70 years (61.0%) and with poor performance scores [57.2% Eastern Cooperative Oncology Group (ECOG) ≥2]. Thirty-day COVID-related mortality was 19.8%. In multivariate analysis, a trend was seen for higher mortality in patients with lung cancer (27.6% versus 20.8%, P = 0.062) and lower mortality for patients with breast cancer (13.0% versus 23.3%, P = 0.052) compared with other tumour types. Non-curative treatment was associated with higher 30-day COVID-related mortality rates compared with curative or no active treatment (25.8% versus 14.3% versus 21.9%, respectively, P < 0.001). In 33% of patients under active treatment, the therapeutic plan was changed due to COVID-19 diagnosis, most frequently involving delays/interruptions in systemic treatments (18.6%). Thirty-day COVID-related mortality was not significantly different between patients with and without treatment modifications (21.4% versus 20.5%).

conclusionInterruption in anticancer treatments at the time of SARS-CoV-2 infection was not associated with a reduction in COVID-related mortality in our cohort of patients with solid cancer, highlighting that treatment continuation should be strived for, especially in the curative setting.

Indexed as

COVID-19Lung NeoplasmsBelgiumCOVID-19 TestingHumansMedical OncologyRegistriesRetrospective StudiesSARS-CoV-2cancerCOVID-19prognosissolid tumourstreatment changes

Identifiers

PMID36356416
PMCPMC9639795

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Registered trials

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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.