دورية أكاديمية

Establishment 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.

التفاصيل البيبلوغرافية
العنوان: Establishment 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.
المؤلفون: Lee, R.J., Wysocki, O., Zhou, C., Shotton, R., Tivey, A., Lever, L., Woodcock, J., Albiges, L., Angelakas, A., Arnold, D., Aung, T., Banfill, K., Baxter, M., Barlesi, F., Bayle, A., Besse, B., Bhogal, T., Boyce, H., Britton, F., Calles, A., Castelo-Branco, L., Copson, E., Croitoru, A.E., Dani, S.S., Dickens, E., Eastlake, L., Fitzpatrick, P., Foulon, S., Frederiksen, H., Frost, H., Ganatra, S., Gennatas, S., Glenthøj, A., Gomes, F., Graham, D.M., Hague, C., Harrington, K., Harrison, M., Horsley, L., Hoskins, R., Huddar, P., Hudson, Z., Jakobsen, L.H., Joharatnam-Hogan, N., Khan, S., Khan, U.T., Khan, K., Massard, C., Maynard, A., McKenzie, H., Michielin, O., Mosenthal, A.C., Obispo, B., Patel, R., Pentheroudakis, G., Peters, S., Rieger-Christ, K., Robinson, T., Rogado, J., Romano, E., Rowe, M., Sekacheva, M., Sheehan, R., Stevenson, J., Stockdale, A., Thomas, A., Turtle, L., Viñal, D., Weaver, J., Williams, S., Wilson, C., Palmieri, C., Landers, D., Cooksley, T., Dive, C., Freitas, A., Armstrong, A.C.
المساهمون: ESMO Co-Care
المصدر: JCO clinical cancer informatics, vol. 6, pp. e2100177
سنة النشر: 2022
المجموعة: Université de Lausanne (UNIL): Serval - Serveur académique lausannois
مصطلحات موضوعية: Adolescent, Adult, Aged, 80 and over, COVID-19/complications, COVID-19/diagnosis, Child, Preschool, Female, Hospitals, Humans, Male, Middle Aged, Neoplasms/complications, Neoplasms/diagnosis, Neoplasms/therapy, Oxygen, SARS-CoV-2, Young Adult
الوصف: 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). 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 (O 2 ) 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. 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 ...
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
تدمد: 2473-4276
العلاقة: info:eu-repo/semantics/altIdentifier/pmid/35609228; info:eu-repo/semantics/altIdentifier/eissn/2473-4276; info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_A5BE25E8275C4; https://serval.unil.ch/notice/serval:BIB_A5BE25E8275CTest; urn:issn:2473-4276; https://serval.unil.ch/resource/serval:BIB_A5BE25E8275C.P001/REF.pdfTest; http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_A5BE25E8275C4Test
DOI: 10.1200/CCI.21.00177
الإتاحة: https://doi.org/10.1200/CCI.21.00177Test
https://serval.unil.ch/notice/serval:BIB_A5BE25E8275CTest
https://serval.unil.ch/resource/serval:BIB_A5BE25E8275C.P001/REF.pdfTest
http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_A5BE25E8275C4Test
حقوق: info:eu-repo/semantics/openAccess ; CC BY-NC-ND 4.0 ; https://creativecommons.org/licenses/by-nc-nd/4.0Test/
رقم الانضمام: edsbas.B8A5FAE8
قاعدة البيانات: BASE
الوصف
تدمد:24734276
DOI:10.1200/CCI.21.00177