A Systematic Framework to Rapidly Obtain Data on Patients with Cancer and COVID-19: CCC19 Governance, Protocol, and Quality Assurance

Abidi, Maheen Z.; Aboulafia, David M.; Accordino, Melissa K.; Acoba, Jared D.; Ahluwalia, Manmeet; Ahmad, Syed A.; Ajmera, Archana; Alimohamed, Saif; Altman, Jessica K.; Angevine, Anne H.; Bakouny, Ziad; Bär, Michael; Bardia, Aditya; Barnholtz‐Sloan, Jill S.; McCollough, Briana Barrow; Bashir, Babar; Batist, Gerald; Bekaii‐Saab, Tanios; Berg, Stephanie; Bernicker, Eric H.; Bhutani, Divaya; Bilen, Mehmet Asım; Bindal, Poorva; Bishnoi, Rohit; Blau, Sibel; Bohachek, Pamela; Boland, Genevieve M.; Bonnen, Mark; Bouchard, Gabrielle; Bouganim, Nathaniel; Bowles, Daniel W.; Busser, Fiona; Butt, Omar H.; Cabal, Angelo; Cabalona, Wilhelmina D.; Cabebe, Elwyn C.; Caimi, Paolo; Campian, Jian; Carducci, Theresa M.; Chen, James L.; Cheng, Alex; Chism, David D.; Choueiri, Toni K.; Clark, Melanie J.; Clément, Jessica; Connors, Jean M.; Cook, Erin; Curran, Catherine; Daher, Ahmad; Dailey, Mark; Davis, Elizabeth J.; Dawsey, Scott J.; Deeken, John F.; Prete, Salvatore A. Del; Demetri, George D.; Desai, Aakash; Doroshow, Deborah Blythe; Durbin, Eric B.; Egan, Pamela; Elias, Rawad; Elkrief, Arielle; Elms, Destry; Elshoury, Amro; Faller, Bryan A.; Farmakiotis, Dimitrios; Fecher, Leslie A.; Feldman, Lawrence E.; Ferrario, Cristiano; Fiala, Mark A.; Flora, Daniel B.; French, Benjamin; Friese, Christopher R.; Fu, Julie; Gadgeel, Shirish M.; Gainor, Justin F.; Galsky, Matthew D.; Gantt, Gerald; García, Jorge A.; Gartrell, Benjamin A.; Gatti‐Mays, Margaret E.; Gill, David; Gillaspie, Erin A.; Giordano, Antonio; Glace, Grace; Glover, Michael; Goel, Sanjay; Graber, Jerome; Griffiths, Elizabeth A.; Grivas, Petros; Grover, Punita; Gulati, Anthony P.; Gulati, Shuchi; Gupta, Shilpa; Gurley, Michael; Hafez, Navid; Halabi, Susan; Halfdanarson, Thorvardur R.; Halmos, Balázs; Hausrath, Daniel; Hawley, Jessica E.; Hennessy, Cassandra; Herbst, Roy S.; Hershman, Dawn L.; Hoppenot, Claire; Hoskins, Kent; Hoyo-Ulloa, Irma; Hsu, Emily; Hsu, Chih–Yuan; Hwang, Clara; Islam, Jessica Y.; Jabbour, Salma K.; Jani, Chinmay; Jha, Alokkumar; Jhawar, Sachin R.; Johnson, Douglas B.; Joshi, Monika; Kasi, Anup; Kelleher, Kaitlin M.; Kennecke, Hagen F.; Khaki, Ali Raza; Hina, Kazuyoshi; Khan, Mahir; Kharofa, Jordan; Kloecker, Goetz; Knoble, Jeanna; Kulkarni, Amit; Kumar, Vaibhav; Lammers, Philip E.; Leighton, John; Lemmon, Christopher A.; Lewis, Mark A.; Li, Ang; Li, Xuanyi; Liu, Stephen V.; Lo, K. M. Steve; Loaiza‐Bonilla, Arturo; Logan, Barbara; Loggers, Elizabeth T.; Lopes, Gilberto; Loree, Jonathan M.; LoRusso, Patricia; Low, Clarke A.; Lustberg, Maryam B.; Lyman, Gary H.; Lynch, Ryan C.; Madhavan, Subha; Mahadevan, Daruka; Mahmood, Sana; Mansoor, Abdul-Hai; Marcum, Michelle; Markham, Merry Jennifer; Mashru, Sandeep H.; Masters, Tyler; Mavromatis, Blanche H.; McKay, Rana R.; McNair, Christopher; McWeeney, Shannon K.; Menendez, Alvaro G.; Menon, Harry; Mesa, Ruben A.; Mico, Vasil; Miller, Chaim; Mishra, Sanjay; Monahan, Ryan; Morgans, Alicia K.; Mulcahy, Mary F.; Mundt, Daniel; Mushtaq, Sarah; Nagaraj, Gayathri; Nagle, Sarah; Nakasone, Elizabeth S.; Nakayama, John; Nelson, Heather H.; Nemecek, Eneida R.; Nguyen, Ruby H.N.; Nizam, Amanda; Nohria, Anju; Nuzzo, Pier Vitale; Ohri, Nitin; Olszewski, Adam J.; Owenby, Susie; Painter, Corrie; Palmer, Joshua D.; Panagiotou, Orestis A.; Park, Cathleen; Pasquinelli, Mary; Patel, Jaymin; Patel, Kanishka G.; Peddi, Prakash; Pennell, Nathan A.; Peters, Solange; Pilar, Christine; Pillainayagam, Clement; Puc, Matthew; Ramirez, Amelie G.; Rathmann, Joerg; Ravindranathan, Deepak; Reid, Sonya; Reuben, Daniel Y.; Revankar, Sanjay G.; Reynolds, Kerry L.; Rho, Young Soo; Rhodes, Terence Duane; Rice, Robert L.; Riess, Jonathan W.; Rini, Brian I.; Rink, Cameron; Rosen, L; Rosenstein, Lori J.; Rosovsky, Rachel; Routy, Bertrand; Rovito, Marc A.; Rubinstein, Samuel M.; Saif, Muhammad Wasif; Salazar, Mary; Dutra, Míriam Santos; Schapira, Lidia; Schmidt, Andrew; Schroeder, Brett; Schwartz, Gary K.; Schwartz, Candice; Schweizer, Michael T.; Serrano, Oscar K.; Shafer, Danielle; Shah, Pankil; Shah, Dimpy P.; Shah, Mansi; Shah, Sumit; Shah, Chintan; Shaw, Grace; Shaya, Justin; Shyr, Yu; Slosky, David A.; Smits, Melissa; Solórzano, Carmen C.; Stauffer, Karen; Stockerl-Goldstein, Keith; Stover, Daniel G.; Stratton, Jamie; Stratton, Catherine; Streckfuss, Mitrianna; Subbiah, Suki; Tachiki, Lisa; Tadesse, Eyob; Thompson, Michael A.; Topaloğlu, Ümit; Tucker, Matthew D.; Allen, Eliezer M. Van; Loon, Susan Van; Vega-Luna, Karen; Venepalli, Neeta K.; Verma, Amit; Vikas, Praveen; Vinayak, Shaveta; Vinh, Donald C.; Wagner, Michael J.; Wall, Sarah; Wang, Lucy Lu; Warner, Jeremy L.; Wehbe, Firas; Weinstein, Paul L.; Weiss, Matthias; Weissmann, Lisa B.; Wildes, Tanya M.; Williams, Nicole; Wise‐Draper, Trisha M.; Wood, William A.; Wu, Julie Tsu-Yu; Wulff‐Burchfield, Elizabeth; Xie, Zhuoer; Xu, Wenxin; Yeh, Albert C.; Yu, Irene S.; Yu, Peter Paul; Zacks, Rosemary; Zaman, Qamar U.; Zaren, Howard A.; Zhang, Tian; Zhou, Alice; Zhu, Huili; Zon, Rebecca L.; Zubiri, Leyre

doi:10.1016/j.ccell.2020.10.022

Cited by 27 publications

(33 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Adult patients with an active or previous diagnosis of cancer with a laboratory‐confirmed SARS‐CoV‐2 test from March 17, 2020 to November 30, 2020 were included in the current study. Patients were excluded if they did not reside within United States or Canada, did not have assessable thrombotic complication status within 90 days (13 weeks), were never hospitalized at baseline, had poor data quality (quality score ≥5, typically due to very high levels of missingness), 19 or had follow‐up less than 30 days (interval between the COVID‐19 diagnosis and the analysis data lock).…”

Section: Methodsmentioning

confidence: 99%

The CoVID‐TE risk assessment model for venous thromboembolism in hospitalized patients with cancer and COVID‐19

Kuderer

Hsu

et al. 2021

Journal of Thrombosis and Haemostasis

Self Cite

View full text Add to dashboard Cite

Background Hospitalized patients with COVID‐19 have increased risks of venous (VTE) and arterial thromboembolism (ATE). Active cancer diagnosis and treatment are well‐known risk factors; however, a risk assessment model (RAM) for VTE in patients with both cancer and COVID‐19 is lacking. Objectives To assess the incidence of and risk factors for thrombosis in hospitalized patients with cancer and COVID‐19. Methods Among patients with cancer in the COVID‐19 and Cancer Consortium registry (CCC19) cohort study, we assessed the incidence of VTE and ATE within 90 days of COVID‐19–associated hospitalization. A multivariable logistic regression model specifically for VTE was built using a priori determined clinical risk factors. A simplified RAM was derived and internally validated using bootstrap. Results From March 17, 2020 to November 30, 2020, 2804 hospitalized patients were analyzed. The incidence of VTE and ATE was 7.6% and 3.9%, respectively. The incidence of VTE, but not ATE, was higher in patients receiving recent anti‐cancer therapy. A simplified RAM for VTE was derived and named CoVID‐TE ( C ancer subtype high to very‐high risk by o riginal Khorana score +1, V TE history +2, I CU admission +2, D ‐dimer elevation +1, recent systemic anti‐cancer T herapy +1, and non‐Hispanic E thnicity +1). The RAM stratified patients into two cohorts (low‐risk, 0–2 points, n = 1423 vs. high‐risk, 3+ points, n = 1034) where VTE occurred in 4.1% low‐risk and 11.3% high‐risk patients (c statistic 0.67, 95% confidence interval 0.63–0.71). The RAM performed similarly well in subgroups of patients not on anticoagulant prior to admission and moderately ill patients not requiring direct ICU admission. Conclusions Hospitalized patients with cancer and COVID‐19 have elevated thrombotic risks. The CoVID‐TE RAM for VTE prediction may help real‐time data‐driven decisions in this vulnerable population.

show abstract

Section: Methodsmentioning

confidence: 99%

The CoVID‐TE risk assessment model for venous thromboembolism in hospitalized patients with cancer and COVID‐19

Kuderer

Hsu

et al. 2021

Journal of Thrombosis and Haemostasis

Self Cite

View full text Add to dashboard Cite

show abstract

“…The methods for CCC19 have been described and published previously. 13 We analyzed data from hospitalized US adults with a current or past diagnosis of hematologic cancers diagnosed with confirmed or suspected SARS-CoV-2 infection in 2020 and reported from March 17, 2020, to January 21, 2021 (full list of contributors is in the eAppendix in Supplement 1 ). Treatment exposure was defined as receiving convalescent plasma at any time during the COVID-19 illness.…”

Section: Methodsmentioning

confidence: 99%

Association of Convalescent Plasma Therapy With Survival in Patients With Hematologic Cancers and COVID-19

Thompson

Henderson

Shah³

et al. 2021

JAMA Oncol

Self Cite

164

View full text Add to dashboard Cite

IMPORTANCE COVID-19 is a life-threatening illness for many patients. Prior studies have established hematologic cancers as a risk factor associated with particularly poor outcomes from COVID-19. To our knowledge, no studies have established a beneficial role for anti-COVID-19 interventions in this at-risk population. Convalescent plasma therapy may benefit immunocompromised individuals with COVID-19, including those with hematologic cancers.OBJECTIVE To evaluate the association of convalescent plasma treatment with 30-day mortality in hospitalized adults with hematologic cancers and COVID-19 from a multi-institutional cohort. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study using data from the COVID-19 and Cancer Consortium registry with propensity score matching evaluated patients with hematologic cancers who were hospitalized for COVID-19. Data were collected between

show abstract

“…For propensity matching, patients without prostate cancer and those with 2 or more malignant neoplasms (synchronous or metachronous) were excluded. Reports with low-quality data (quality score >4 using our previously defined metric 23 ) or incomplete outcome ascertainment resulting in unknown status of the primary outcome were also excluded. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline 24 and was approved by local institutional review boards at participating sites per institutional policy.…”

Section: Methodsmentioning

confidence: 99%

Association Between Androgen Deprivation Therapy and Mortality Among Patients With Prostate Cancer and COVID-19

et al. 2021

Self Cite

View full text Add to dashboard Cite

IMPORTANCEAndrogen deprivation therapy (ADT) has been theorized to decrease the severity of SARS-CoV-2 infection in patients with prostate cancer owing to a potential decrease in the tissuebased expression of the SARS-CoV-2 coreceptor transmembrane protease, serine 2 (TMPRSS2). OBJECTIVE To examine whether ADT is associated with a decreased rate of 30-day mortality from SARS-CoV-2 infection among patients with prostate cancer. DESIGN, SETTING, AND PARTICIPANTS This cohort study analyzed patient data recorded in the COVID-19 and Cancer Consortium registry between March 17, 2020, and February 11, 2021. The consortium maintains a centralized multi-institution registry of patients with a current or past diagnosis of cancer who developed COVID-19. Data were collected and managed using REDCap software hosted at Vanderbilt University Medical Center in Nashville, Tennessee. Initially, 1228patients aged 18 years or older with prostate cancer listed as their primary malignant neoplasm were included; 122 patients with a second malignant neoplasm, insufficient follow-up, or low-quality data were excluded. Propensity matching was performed using the nearest-neighbor method with a 1:3 ratio of treated units to control units, adjusted for age, body mass index, race and ethnicity, Eastern Cooperative Oncology Group performance status score, smoking status, comorbidities (cardiovascular, pulmonary, kidney disease, and diabetes), cancer status, baseline steroid use, COVID-19 treatment, and presence of metastatic disease. EXPOSURES Androgen deprivation therapy use was defined as prior bilateral orchiectomy or pharmacologic ADT administered within the prior 3 months of presentation with COVID-19. MAIN OUTCOMES AND MEASURESThe primary outcome was the rate of all-cause 30-day mortality after COVID-19 diagnosis for patients receiving ADT compared with patients not receiving ADT after propensity matching. RESULTSAfter exclusions, 1106 patients with prostate cancer (before propensity score matching: median age, 73 years [IQR, 65-79 years]; 561 (51%) self-identified as non-Hispanic White) were included for analysis. Of these patients, 477 were included for propensity score matching (169 who received ADT and 308 who did not receive ADT). After propensity matching, there was no significant difference in the primary end point of the rate of all-cause 30-day mortality (OR, 0.77; 95% CI, 0.42-1.42).

show abstract

A Systematic Framework to Rapidly Obtain Data on Patients with Cancer and COVID-19: CCC19 Governance, Protocol, and Quality Assurance

Cited by 27 publications

References 14 publications

The CoVID‐TE risk assessment model for venous thromboembolism in hospitalized patients with cancer and COVID‐19

The CoVID‐TE risk assessment model for venous thromboembolism in hospitalized patients with cancer and COVID‐19

Association of Convalescent Plasma Therapy With Survival in Patients With Hematologic Cancers and COVID-19

Association Between Androgen Deprivation Therapy and Mortality Among Patients With Prostate Cancer and COVID-19

Contact Info

Product

Resources

About