Evidence map›Paper›PMID 33486624›Full record

ArticleInternational journal of clinical oncology2021

The mortality rate of COVID-19 was high in cancer patients: a retrospective single-center study.

Gulcin Sahingoz Erdal, Ozlem Polat, Gokmen Umut Erdem, Ramazan Korkusuz, Fehmi Hindilerden, Mesut Yilmaz, Kadriye Kart Yasar, Nilgun Isiksacan, Deniz Tural

Open access · bronzeAbstract read
In one paragraph

Article in International journal of clinical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 3 pooled it
3.9field-weighted citation impact, top 4% of its field
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

26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 47 citations in OpenAlex.

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  11. Determinants of COVID-19 cases and deaths in OECD countries.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2023
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  12. Cancer Patients during COVID-19 Pandemic: A Mini-Review.Healthcare (Basel, Switzerland) · 2023
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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

9 authors at 2 institutions in 3 countries.

Gulcin Sahingoz ErdalDepartment of Oncology, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, dr. Tevfik Saglam Street No: 11, 34147, Istanbul, Turkey. gulcinctf@hotmail.com.ORCID http://orcid.org/0000-0001-5815-5847
Ozlem PolatDepartment of Family Medicine, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Gokmen Umut ErdemDepartment of Oncology, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, dr. Tevfik Saglam Street No: 11, 34147, Istanbul, Turkey.
Ramazan KorkusuzDepartment of Infectious Diseases and Clinical Microbiology, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Fehmi HindilerdenDepartment of Hematology, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Mesut YilmazDepartment of Oncology, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, dr. Tevfik Saglam Street No: 11, 34147, Istanbul, Turkey.
Kadriye Kart YasarDepartment of Infectious Diseases and Clinical Microbiology, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Nilgun IsiksacanDepartment of Biochemistry, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Deniz TuralDepartment of Oncology, Bakırköy dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, dr. Tevfik Saglam Street No: 11, 34147, Istanbul, Turkey.
Bakırköy Dr.Sadi Konuk Eğitim ve Araştırma Hastanesi · TRUniversity of Health Science · KH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) has quickly turned into a global pandemic with close to 5 million cases and more than 320,000 deaths. Cancer patients constitute a group that is expected to be at risk and poor prognosis in COVID pandemic. We aimed to investigate how cancer patients are affected by COVID-19 infection, its clinical course and the factors affecting mortality.

methodsIn our single-center retrospective study, we included cancer patients with laboratory confirmed COVID-19 in our hospital. Demographic, clinical, treatment, and laboratory data were obtained from electronic medical records. Logistic regression methods were used to investigate risk factors associated with in-hospital death.

resultsIn the hospital, 4489 patients were hospitalized with COVID infection and 77 were cancer patients. The mean age of cancer patients was 61.9 ± 10.9 and 44 of them were male (62%). While the mortality rate in non-cancer patients was 1.51% (n = 68), this rate was significantly higher in cancer patients, 23.9% (n = 17). The stage of the disease, receiving chemotherapy in the last 30 days also lymphopenia, elevated troponin I, D-dimer, CRP, and CT findings were associated with severe disease and mortality. Severe lung involvement (OR = 22.9, p = 0.01) and lymphopenia (OR = 0.99, p = 0.04) are the most important factors influencing survival in logistic regression.

conclusionsThe disease is more severe in cancer patients and mortality is significantly higher than non-cancer patients. These data show that it may be beneficial to develop dynamic prevention, early diagnosis and treatment strategies for this vulnerable group of patients who are affected by the infection so much.

Indexed as

CancerCOVID-19Mortality rateRetrospective case study

Identifiers

PMID33486624
PMCPMC7826293
OpenAlexW3122483479

What OpenQuestion holds

Textmetadata
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.