The COVID-19 & Cancer Consortium (CCC19) and Opportunities for Radiation Oncology
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".