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dc.contributor.authorLee, RJ
dc.contributor.authorWysocki, O
dc.contributor.authorZhou, C
dc.contributor.authorShotton, R
dc.contributor.authorTivey, A
dc.contributor.authorLever, L
dc.contributor.authorWoodcock, J
dc.contributor.authorAlbiges, L
dc.contributor.authorAngelakas, A
dc.contributor.authorArnold, D
dc.contributor.authorAung, T
dc.contributor.authorBanfill, K
dc.contributor.authorBaxter, M
dc.contributor.authorBarlesi, F
dc.contributor.authorBayle, A
dc.contributor.authorBesse, B
dc.contributor.authorBhogal, T
dc.contributor.authorBoyce, H
dc.contributor.authorBritton, F
dc.contributor.authorCalles, A
dc.contributor.authorCastelo-Branco, L
dc.contributor.authorCopson, E
dc.contributor.authorCroitoru, AE
dc.contributor.authorDani, SS
dc.contributor.authorDickens, E
dc.contributor.authorEastlake, L
dc.contributor.authorFitzpatrick, P
dc.contributor.authorFoulon, S
dc.contributor.authorFrederiksen, H
dc.contributor.authorFrost, H
dc.contributor.authorGanatra, S
dc.contributor.authorGennatas, S
dc.contributor.authorGlenthøj, A
dc.contributor.authorGomes, F
dc.contributor.authorGraham, DM
dc.contributor.authorHague, C
dc.contributor.authorHarrington, K
dc.contributor.authorHarrison, M
dc.contributor.authorHorsley, L
dc.contributor.authorHoskins, R
dc.contributor.authorHuddar, P
dc.contributor.authorHudson, Z
dc.contributor.authorJakobsen, LH
dc.contributor.authorJoharatnam-Hogan, N
dc.contributor.authorKhan, S
dc.contributor.authorKhan, UT
dc.contributor.authorKhan, K
dc.contributor.authorMassard, C
dc.contributor.authorMaynard, A
dc.contributor.authorMcKenzie, H
dc.contributor.authorMichielin, O
dc.contributor.authorMosenthal, AC
dc.contributor.authorObispo, B
dc.contributor.authorPatel, R
dc.contributor.authorPentheroudakis, G
dc.contributor.authorPeters, S
dc.contributor.authorRieger-Christ, K
dc.contributor.authorRobinson, T
dc.contributor.authorRogado, J
dc.contributor.authorRomano, E
dc.contributor.authorRowe, M
dc.contributor.authorSekacheva, M
dc.contributor.authorSheehan, R
dc.contributor.authorStevenson, J
dc.contributor.authorStockdale, A
dc.contributor.authorThomas, A
dc.contributor.authorTurtle, L
dc.contributor.authorViñal, D
dc.contributor.authorWeaver, J
dc.contributor.authorWilliams, S
dc.contributor.authorWilson, C
dc.contributor.authorPalmieri, C
dc.contributor.authorLanders, D
dc.contributor.authorCooksley, T
dc.contributor.authorESMO Co-Care
dc.contributor.authorDive, C
dc.contributor.authorFreitas, A
dc.contributor.authorArmstrong, AC
dc.coverage.spatialUnited States
dc.date.accessioned2022-07-13T14:27:56Z
dc.date.available2022-07-13T14:27:56Z
dc.date.issued2022-05-01
dc.identifier.citationJCO Clinical Cancer Informatics, 2022, 6 (6), pp. e2100177 -en_US
dc.identifier.issn2473-4276
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/5229
dc.identifier.eissn2473-4276
dc.identifier.eissn2473-4276
dc.identifier.doi10.1200/CCI.21.00177
dc.identifier.doi10.1200/CCI.21.00177
dc.description.abstractPURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.
dc.formatPrint
dc.format.extente2100177 -
dc.languageeng
dc.language.isoengen_US
dc.publisherLIPPINCOTT WILLIAMS & WILKINSen_US
dc.relation.ispartofJCO Clinical Cancer Informatics
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectAdolescent
dc.subjectAdult
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectCOVID-19
dc.subjectChild
dc.subjectChild, Preschool
dc.subjectFemale
dc.subjectHospitals
dc.subjectHumans
dc.subjectMale
dc.subjectMiddle Aged
dc.subjectNeoplasms
dc.subjectOxygen
dc.subjectSARS-CoV-2
dc.subjectYoung Adult
dc.titleEstablishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital.en_US
dc.typeJournal Article
dcterms.dateAccepted2022-04-11
dc.date.updated2022-07-13T14:23:04Z
rioxxterms.versionVoRen_US
rioxxterms.versionofrecord10.1200/CCI.21.00177en_US
rioxxterms.licenseref.startdate2022-05-01
rioxxterms.typeJournal Article/Reviewen_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/35609228
pubs.issue6
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Biology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Biology/Targeted Therapy
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Targeted Therapy
pubs.organisational-group/ICR/ImmNet
pubs.publication-statusPublished
pubs.volume6
icr.researchteamTargeted Therapyen_US
dc.contributor.icrauthorHarrington, Kevin
icr.provenanceDeposited by Mr Arek Surman on 2022-07-13. Deposit type is initial. No. of files: 1. Files: Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Ris.pdf


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