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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2022
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2022
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2022
Data sources: Datacite
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Dataset related to article "Impact of active cancer on COVID-19 survival: a matchedanalysis on 557 consecutive patients at an Academic Hospital in Lombardy, Italy"

Authors: Bertuzzi, Alexia F.; Ciccarelli, Michele; Marrari, Andrea; Gennaro, Nicolò; Dipasquale, Andrea; Giordano, Laura; Cariboni, Umberto; +3 Authors

Dataset related to article "Impact of active cancer on COVID-19 survival: a matchedanalysis on 557 consecutive patients at an Academic Hospital in Lombardy, Italy"

Abstract

This record contains raw data related to article "Impact of active cancer on COVID-19 survival: a matchedanalysis on 557 consecutive patients at an Academic Hospital in Lombardy, Italy" Background: The impact of active cancer in COVID-19 patients is poorly defined; however, most studies showed a poorer outcome in cancer patients compared to the general population. Methods: We analysed clinical data from 557 consecutive COVID-19 patients. Uni-multivariable analysis was performed to identify prognostic factors of COVID-19 survival; propensity score matching was used to estimate the impact of cancer. Results: Of 557 consecutive COVID-19 patients, 46 had active cancer (8%). Comorbidities included diabetes (n = 137, 25%), hypertension (n = 284, 51%), coronary artery disease (n = 114, 20%) and dyslipidaemia (n = 122, 22%). Oncologic patients were older (mean age 71 vs 65, p = 0.012), more often smokers (20% vs 8%, p = 0.009), with higher neutrophil-to-lymphocyte ratio (13.3 vs 8.2, p = 0.046). Fatality rate was 50% (CI 95%: 34.9;65.1) in cancer patients and 20.2% (CI 95%: 16.8;23.9) in the non-oncologic population. Multivariable analysis showed active cancer (HRactive: 2.26, p = 0.001), age (HRage>65years: 1.08, p < 0.001), as well as lactate dehydrogenase (HRLDH>248mU/mL: 2.42, p = 0.007), PaO2/FiO2 (HRcontinuous: 1.00, p < 0.001), procalcitonin (HRPCT>0.5ng/mL: 2.21, p < 0.001), coronary artery disease (HRyes: 1.67, p = 0.010), cigarette smoking (HRyes: 1.65, p = 0.041) to be independent statistically significant predictors of outcome. Propensity score matching showed a 1.92× risk of death in active cancer patients compared to non-oncologic patients (p = 0.013), adjusted for ICU-related bias. We observed a median OS of 14 days for cancer patients vs 35 days for other patients. Conclusion: A near-doubled death rate between cancer and non-cancer COVID-19 patients was reported. Active cancer has a negative impact on clinical outcome regardless of pre-existing clinical comorbidities.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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Cancer Research