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Enregistrement W3114384989 · doi:10.1016/j.adro.2020.10.026

The COVID-19 & Cancer Consortium (CCC19) and Opportunities for Radiation Oncology

2020· article· en· W3114384989 sur OpenAlexaboutno aff
Sachin R. Jhawar, Joshua D. Palmer, Shang-Jui Wang, Danielle S. Bitterman, Brett Klamer, Minh Phuong Huynh-Le, Caroline Chung, Nitin Ohri, Daniel G. Stover, Maryam B. Lustberg, Sanjay Mishra, Jeremy L. Warner, Salma K. Jabbour, Sharad Goyal

Notice bibliographique

RevueAdvances in Radiation Oncology · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueCOVID-19 and healthcare impacts
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineAsymptomaticPublic healthPandemicDiseaseCoronavirus disease 2019 (COVID-19)CoronavirusViral sheddingInternal medicineInfectious disease (medical specialty)Intensive care medicineVirologyVirusPathology

Résumé

récupéré en direct d'OpenAlex

To date, there are more than 38,000,000 confirmed cases of coronavirus disease 2019 (COVID-19) worldwide, with over 1,000,000 deaths.1World Health OrganizationWorld Health Organization Coronavirus Disease (COVID-19) Dashboard.https://covid19.who.int/Date accessed: October 16, 2020Google Scholar In the United States, there have been over 14,100,000 confirmed cases, with over 276,000 deaths.1World Health OrganizationWorld Health Organization Coronavirus Disease (COVID-19) Dashboard.https://covid19.who.int/Date accessed: October 16, 2020Google Scholar This disease is highly infectious, especially because asymptomatic and symptomatic individuals can transmit the virus.2Lee S. Kim T. Lee E. et al.Clinical course and molecular viral shedding among asymptomatic and symptomatic patients with SARS-CoV-2 infection in a community treatment center in the republic of korea.JAMA Intern Med. 2020; 180: 1447-1452Crossref PubMed Scopus (322) Google Scholar,3SohnY Jeong S.J. Chng W.S. et al.Assessing viral shedding and infectivity of asymptomatic or mildly symptomatic patients with COVID-19 in a later phase.J Clin Med. 2020; 9: 2924Crossref Scopus (42) Google Scholar During the pandemic, extensive public health measures have been taken to limit exposure of both staff and patients to the severe acute respiratory syndrome coronavirus-2, including physical distancing and quarantine. Due to these public health measures, there is concern that access to radiation treatment may be limited, or treatment plans may be interrupted or changed due to severe acute respiratory syndrome coronavirus-2 infection. Despite the lack of data, multiple clinical practice guidelines have been released recommending changes in dose fractionation schedules for patients undergoing radiation therapy during the pandemic.4Thomson D.J. Yom S.S. Saeed H. et al.Radiation fractionation schedules published during the COVID-19 pandemic: A systematic review of the quality of evidence and recommendations for future development.Int J Radiat Oncol Biol Phys. 2020; 108: 379-389Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar The short- and long-term clinical effects of these changes on patient outcomes are unknown. The COVID-19 & Cancer Consortium (CCC19) is an international collection of 120 institutions from the United States, European Union, Argentina, Canada, Mexico, and the United Kingdom. The purpose of the CCC19 is to collect detailed information on patients with cancer diagnosed with COVID-19 at scale across the globe. In the CCC19 cohort study, the 30-day all-cause mortality was 13% among 928 patients in the United States with active cancer or previous history of cancer and confirmed COVID-19.5Kuderer N.M. Choueiri T.K. Shah D.P. et al.Clinical impact of COVID-19 on patients with cancer (CCC19): Acohort study.Lancet. 2020; 395: 1907-1918Abstract Full Text Full Text PDF PubMed Scopus (1192) Google Scholar Independent factors associated with increased 30-day mortality were increased age, male sex, smoking history, number of comorbidities, Eastern Cooperative Oncology Group performance status of 2 or higher, active cancer, receipt of azithromycin plus hydroxychloroquine, and residence in the Northeastern United States. Of note, active anticancer therapy was not associated with increased 30-day mortality.5Kuderer N.M. Choueiri T.K. Shah D.P. et al.Clinical impact of COVID-19 on patients with cancer (CCC19): Acohort study.Lancet. 2020; 395: 1907-1918Abstract Full Text Full Text PDF PubMed Scopus (1192) Google Scholar In the UK Coronavirus Cancer Monitoring Project study consisting of 800 patients with cancer and symptomatic COVID-19, the risk of death was significantly associated with advanced age, male sex, and comorbidities. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19.6Lee L.Y.W. Cazier J.-B. Starkey T. et al.COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: A prospective cohort study.Lancet Oncol. 2020; 21: 1309-1316Abstract Full Text Full Text PDF PubMed Scopus (410) Google Scholar Several other studies have similarly shown no statistically significant relationship between the use of chemotherapy and adverse outcomes.7Jee J. Foote M.B. Lumish M. et al.Chemotherapy and COVID-19 outcomes in patients with cancer.J Clin Oncol. 2020; (p. Jco2001307)Crossref PubMed Scopus (168) Google Scholar,8Vuagnat P. Frelaut M. Ramtohul T. et al.COVID-19 in breast cancer patients: A cohort at the Institut Curie hospitals in the Paris area.Breast Cancer Res. 2020; 22: 55Crossref PubMed Scopus (86) Google Scholar Specific to radiation therapy, in 59 patients with breast cancer with positive viral RNA testing or typical radiology signs for COVID-19 who were actively treated for early or metastatic disease during the last 4 months at the Institut Curie Parisian, no association was found between prior radiation therapy (RT) fields or RT sequelae and the extent of COVID-19 lung lesions. The 4 patients who died had significant noncancer comorbidities, and in univariate analysis, hypertension and age > 70 years were 2 factors associated with a higher risk of intensive care unit admission and/or death.8Vuagnat P. Frelaut M. Ramtohul T. et al.COVID-19 in breast cancer patients: A cohort at the Institut Curie hospitals in the Paris area.Breast Cancer Res. 2020; 22: 55Crossref PubMed Scopus (86) Google Scholar In Wuhan, China, the largest radiation therapy data set reported to-date provided insight into the radiation treatment courses of 209 patients9Xie C. Wang X. Liu H. et al.Outcomes in radiotherapy-treated patients with cancer during the COVID-19 outbreak in Wuhan, China.JAMA Oncol. 2020; 6: 1457-1459Crossref PubMed Scopus (18) Google Scholar with a 10-fold decrease in clinical caseload due to the lock down. Beyond these reports, there have been no large studies addressing the effect of COVID-19 related delays to start RT, changes in radiation treatment dose and fractionations, or unexpected interruptions or delays in completing treatment, which could have long-lasting effects on overall cancer outcomes. The CCC19 have an exceptionally detailed system of data collection on cancer-related variables for over 6000 patients (Fig 1). Currently, the consortium lacks important details of radiation treatment and timing. We aim to increase the collection and availability of radiation- specific variables to allow a more granular analysis of radiation decision making and the effect of radiation treatment during the COVID-19 era. We hope to call attention to the members of the American Society for Radiation Oncology to join the CCC19 and help accrue additional patients with radiation-specific details. The CCC19 will help to better understand the use of radiation treatment during the COVID-19 pandemic, the effect on cancer and COVID-19 outcomes in general, and help prepare our field for any future pandemic.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,969
Score d'incertitude au seuil0,630

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,218
Tête enseignante GPT0,510
Écart entre enseignants0,292 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2020
Routes d'admission1
Résumé présentoui

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