Evidence map›Paper›PMID 33159569›Full record

ArticleAnnals of hematology2021

COVID-19 in cancer patients: clinical characteristics and outcome-an analysis of the LEOSS registry.

Maria Madeleine Rüthrich, C Giessen-Jung, S Borgmann, A Y Classen, S Dolff, B Grüner, F Hanses, N Isberner, P Köhler, J Lanznaster and 12 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of hematology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
107citing papers in PubMed, 10 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

107 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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  13. Impact of COVID-19 vaccination on cancer patients: safety, efficacy, and long-term effects.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
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47 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

22 authors.

Maria Madeleine RüthrichDepartment of Internal Medicine II, Hematology and Medical Oncology, University Hospital Jena, Am Klinikum 1, 07747, Jena, Germany. maria.ruethrich@med.uni-jena.de.ORCID http://orcid.org/0000-0001-7577-181X
C Giessen-JungDepartment of Internal Medicine III, Ludwig Maximilian University, Munich, Germany.
S BorgmannDepartment of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany.
A Y ClassenDepartment I for Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
S DolffDepartment of Infectious Diseases, University Hospital Essen, University Duisburg Essen, Essen, Germany.
B GrünerSection Clinical Infectiology, University Hospital Ulm, Ulm, Germany.
F HansesEmergency Department, University Hospital Regensburg, Regensburg, Germany.
N IsbernerDepartment of Internal Medicine II, Division of Infectious Diseases, University Hospital Würzburg, Würzburg, Germany.
P KöhlerCologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany.
J LanznasterDepartment of Internal Medicine II, Passau Hospital, Passau, Germany.
U MerleDepartment of Internal Medicine IV, University Hospital Heidelberg, Heidelberg, Germany.
S NadalinDepartment of General, Visceral and Transplant Surgery, University Hospital Tübingen, Tübingen, Germany.
C PiepelHospital Bremen-Center, Bremen, Germany.
J SchneiderDepartment of Internal Medicine II, Technical University of Munich, School of Medicine, University hospital rechts der Isar, Munich, Germany.
M SchonsDepartment I for Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
R StraussMedical Clinic I, University Hospital Erlangen, Erlangen, Germany.
L TomettenDepartment of Gastroenterology and Infectiology, Hospital Ernst-von-Bergmann, Potsdam, Germany.
J J VehreschildDepartment I for Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
M von Lilienfeld-ToalDepartment of Internal Medicine II, Hematology and Medical Oncology, University Hospital Jena, Am Klinikum 1, 07747, Jena, Germany.
G BeutelDepartment of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany.
K WilleUniversity of Bochum, University Clinic for Hematology, Oncology, Hemostaseology and Palliative Care, Minden, Germany.
LEOSS Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSince the early SARS-CoV-2 pandemic, cancer patients have been assumed to be at higher risk for severe COVID-19. Here, we present an analysis of cancer patients from the LEOSS (Lean European Open Survey on SARS-CoV-2 Infected Patients) registry to determine whether cancer patients are at higher risk. PATIENTS AND

methodsWe retrospectively analyzed a cohort of 435 cancer patients and 2636 non-cancer patients with confirmed SARS-CoV-2 infection, enrolled between March 16 and August 31, 2020. Data on socio-demographics, comorbidities, cancer-related features and infection course were collected. Age-, sex- and comorbidity-adjusted analysis was performed. Primary endpoint was COVID-19-related mortality.

resultsIn total, 435 cancer patients were included in our analysis. Commonest age category was 76-85 years (36.5%), and 40.5% were female. Solid tumors were seen in 59% and lymphoma and leukemia in 17.5% and 11% of patients. Of these, 54% had an active malignancy, and 22% had recently received anti-cancer treatments. At detection of SARS-CoV-2, the majority (62.5%) presented with mild symptoms. Progression to severe COVID-19 was seen in 55% and ICU admission in 27.5%. COVID-19-related mortality rate was 22.5%. Male sex, advanced age, and active malignancy were associated with higher death rates. Comparing cancer and non-cancer patients, age distribution and comorbidity differed significantly, as did mortality (14% vs 22.5%, p value < 0.001). After adjustments for other risk factors, mortality was comparable.

conclusionComparing cancer and non-cancer patients, outcome of COVID-19 was comparable after adjusting for age, sex, and comorbidity. However, our results emphasize that cancer patients as a group are at higher risk due to advanced age and pre-existing conditions.

Indexed as

AdolescentAdultAgedAged, 80 and overComorbidityCOVID-19EuropeFemaleHospitalizationHospital MortalityHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasmsOutcome Assessment, Health CareAdjusted analysisCancer patientsCohort studyCOVID-19LEOSSPandemicSARS-CoV-2

Identifiers

PMID33159569
PMCPMC7648543

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LicenceCC BY
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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.