1. Medicine
  2. Cancer Biology

International multicenter study comparing COVID-19 in patients with cancer to patients without cancer: Impact of risk factors and treatment modalities on survivorship

  1. Issam I Raad
  2. Ray Hachem
  3. Nigo Masayuki
  4. Tarcila Datoguia
  5. Hiba Dagher
  6. Ying Jiang
  7. Vivek Subbiah
  8. Bilal Siddiqui
  9. Arnaud Bayle
  10. Robert Somer
  11. Ana Fernández Cruz
  12. Edward Gorak
  13. Arvinder Bhinder
  14. Nobuyoshi Mori
  15. Nelson Hamerschlak
  16. Samuel Shelanski
  17. Tomislav Dragovich
  18. Yee Elise Vong Kiat
  19. Suha Fakhreddine
  20. Abi Hanna Pierre
  21. Roy F Chemaly
  22. Victor Mulanovich
  23. Javier Adachi
  24. Jovan Borjan
  25. Fareed Khawaja
  26. Bruno Granwehr
  27. Teny John
  28. Eduardo Yepez Yepez
  29. Harrys A Torres
  30. Natraj Reddy Ammakkanavar
  31. Marcel Yibirin
  32. Cielito C Reyes-Gibby
  33. Mala Pande
  34. Noman Ali
  35. Raniv Dawey Rojo
  36. Shahnoor M Ali
  37. Rita E Deeba
  38. Patrick Chaftari
  39. Takahiro Matsuo
  40. Kazuhiro Ishikawa
  41. Ryo Hasegawa
  42. Ramón Aguado-Noya
  43. Alvaro Garcia García
  44. Cristina Traseira Puchol
  45. Dong Gun Lee
  46. Monica Slavin
  47. Benjamin Teh
  48. Cesar A Arias
  49. Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE) Team
  50. Dimitrios P Kontoyiannis
  51. Alexandre E Malek
  52. Anne-Marie Chaftari  Is a corresponding author
  1. Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, United States
  2. Division of Infectious Diseases, McGovern Medical School, The University of Texas Health Science Center at Houston, United States
  3. Médica Hematologista Hospital Israelita Albert Einstein, Brazil
  4. MD Anderson Cancer Network, UT MD Anderson Cancer Center, United States
  5. Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, United States
  6. Department of Hematology Oncology, Community Health Network, United States
  7. Department of Medical Oncology, Gustave Roussy, Université Paris-Saclay, France
  8. Cooper Medical School of Rowan University, Cooper University Health Care, United States
  9. Unidad de Enfermedades Infecciosas, Servicio de Medicina Interna, Hospital Universitario Puerta de Hierro, Spain
  10. Department of Hematology Oncology, Baptist Health, United States
  11. Department of Hematology/Oncology, Ohio Health Marion, United States
  12. Department of Infectious Diseases, St. Luke's International Hospital, Japan
  13. Banner MD Anderson Cancer Center – North Colorado, United States
  14. Division of Cancer Medicine, Banner MD Anderson Cancer Center, United States
  15. Department of Medical Oncology, Tan Tock Seng Hospital, Singapore
  16. Department of Infectious Diseases, Rafik Hariri University Hospital, Lebanon
  17. Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, United States
  18. Department of Gastroenterology, The University of Texas MD Anderson Cancer Center, United States
  19. Department of Hospital Medicine, The University of Texas MD Anderson Cancer Center, United States
  20. Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, United States
  21. Oncology Department, Hospital Universitario Puerta de Hierro-Majadahonda, Spain
  22. Hematology Department, Hospital Universitario Puerta de Hierro-Majadahonda, Spain
  23. Division of Infectious Diseases, Department of Internal Medicine, Vaccine Bio Research Institute, The Catholic University of Korea, Republic of Korea
  24. Department of Infectious Diseases and National Centre for Infections in Cancer, Peter MacCallum Cancer Centre, Australia
  25. Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE) Team at The University of Texas MD Anderson Cancer Center, United States
https://doi.org/10.7554/eLife.81127
Share this article
Cite this article
  1. Issam I Raad
  2. Ray Hachem
  3. Nigo Masayuki
  4. Tarcila Datoguia
  5. Hiba Dagher
  6. Ying Jiang
  7. Vivek Subbiah
  8. Bilal Siddiqui
  9. Arnaud Bayle
  10. Robert Somer
  11. Ana Fernández Cruz
  12. Edward Gorak
  13. Arvinder Bhinder
  14. Nobuyoshi Mori
  15. Nelson Hamerschlak
  16. Samuel Shelanski
  17. Tomislav Dragovich
  18. Yee Elise Vong Kiat
  19. Suha Fakhreddine
  20. Abi Hanna Pierre
  21. Roy F Chemaly
  22. Victor Mulanovich
  23. Javier Adachi
  24. Jovan Borjan
  25. Fareed Khawaja
  26. Bruno Granwehr
  27. Teny John
  28. Eduardo Yepez Yepez
  29. Harrys A Torres
  30. Natraj Reddy Ammakkanavar
  31. Marcel Yibirin
  32. Cielito C Reyes-Gibby
  33. Mala Pande
  34. Noman Ali
  35. Raniv Dawey Rojo
  36. Shahnoor M Ali
  37. Rita E Deeba
  38. Patrick Chaftari
  39. Takahiro Matsuo
  40. Kazuhiro Ishikawa
  41. Ryo Hasegawa
  42. Ramón Aguado-Noya
  43. Alvaro Garcia García
  44. Cristina Traseira Puchol
  45. Dong Gun Lee
  46. Monica Slavin
  47. Benjamin Teh
  48. Cesar A Arias
  49. Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE) Team
  50. Dimitrios P Kontoyiannis
  51. Alexandre E Malek
  52. Anne-Marie Chaftari
(2023)
International multicenter study comparing COVID-19 in patients with cancer to patients without cancer: Impact of risk factors and treatment modalities on survivorship
eLife 12:e81127.
https://doi.org/10.7554/eLife.81127
  2. Download BibTeX
  3. Download .RIS
1 figure, 4 tables and 3 additional files

Figures

Figure 1
Download asset Open asset
Consort diagram of patient attrition.

Tables

Table 1
Comparing COVID-19 patients with and without cancer.
CharacteristicWithout cancer (n=2851)
N (%)
With cancer
(n=1115)
N (%)
p-value
Demographic and baseline clinical characteristics
Age (years), median (range)50 (18–100)61 (18–100)<0.0001
Sex, male1335 (47)506 (45)0.41
Race/ethnicity<0.0001
White720/2674 (27)534/916 (58)
Black517/2674 (19)155/916 (17)
Hispanic547/2674 (20)178/916 (19)
Asian275/2674 (10)33/916 (4)
Middle Eastern63/2674 (2)3/916 (0.3)
Other552/2674 (21)13/916 (1)
Prior pulmonary disorders431/2064 (21)275/1017 (27)<0.001
COPD/bronchiolitis obliterans175/2054 (9)75 (7)0.07
Asthma178 (6)106 (10)<0.001
Obstructive sleep apnea98/2054 (5)89/948 (9)<0.0001
History of heart failure240/2036 (12)85/1098 (8)<0.001
History of ischemic heart disease226/2830 (8)94/1101 (9)0.57
History of hypertension1020/2837 (36)546/1110 (49)<0.0001
History of diabetes mellitus659/2837 (23)299/1104 (27)0.01
Current or previous smoker348/2055 (17)409/1066 (38)<0.0001
Corticosteroid treatment within 2wk prior to COVID-19 diagnosis40/1041 (4)189/1097 (17)<0.0001
Presenting symptoms981/1061 (92)813/1102 (74)<0.0001
Cough685/1061 (65)505/1102 (46)<0.0001
Fever698/1061 (66)498/1102 (45)<0.0001
Shortness of breath508/1061 (48)387/1102 (35)<0.0001
Chest pain100/1061 (9)66/1102 (6)0.003
Headache133/1061 (13)80/1102 (7)<0.0001
Gastrointestinal symptoms148/1061 (14)104/1102 (9)0.001
Loss of smell84/1061 (8)58/1102 (5)0.013
Loss of taste78/1061 (7)55/1102 (5)0.022
ICU admission225/1846 (12)141/1100 (13)0.62
Abnormal laboratory values
ANC <0.5K/μl2/1434 (0.1)30/419 (7)<0.0001
ALC <0.5K/μl487/1537 (32)225/463 (49)<0.0001
Platelet count<100K/μl187/1446 (13)151/387 (39)<0.0001
Hemoglobin<10g/dL437/1533 (29)283/601 (47)<0.0001
D-dimer, median (range), μg/ml1.51 (0.04–735.0)1.95 (0.25–93.24)0.013
Ferritin, median (range), ng/ml823 (1.10–89672)1015 (1.5–100001)<0.0001
Procalcitonin, median (range), ng/ml0.21 (0.009–163.5)0.25 (0–101.8)0.008
IL-6, median (range), pg/ml61 (0–5001)44 (0–7525)0.13
Imaging findings
New infiltrates151/622 (24)138/424 (33)0.003
Ground-glass opacities487/622 (78)287/425 (68)<0.0001
Peripheral distribution of infiltrates253/622 (41)60/347 (17)<0.0001
Treatment
Hydroxychloroquine475/2054 (23)196/1114 (18)<0.001
Azithromycin972/2054 (47)201/1114 (18)<0.0001
Remdesivir338 (12)97 (9)0.004
Tocilizumab75/2054 (4)67 (6)0.002
Convalescent plasma253/2054 (12)61/948 (6)<0.0001
Steroids879/2054 (43)192/1114 (17)<0.0001
Others*166/2054 (8)124/953 (13)<0.0001
Outcomes
Co-infection after COVID-19 diagnosis158/1994 (8)116/1066 (11)0.006
Multi-organ failure130/1052 (12)135/1096 (12)0.98
Thrombotic complication56/1048 (5)48/1072 (5)0.36
Discharged on supplemental oxygen among hospitalized90/776 (12)75/438 (17)0.007
patients
Hospital re-admission within 30 days of COVID-19 diagnosis<0.0001
No667/806 (83)318/481 (66)
Yes60/806 (7)63/481 (13)
Stayed in hospital (throughout 30 days)79/806 (10)100/481 (21)
Death within 30 days of COVID-19 diagnosis226 (8)122 (11)0.003

  1. Note:*Other treatment included chloroquine, favipiravir, lopinavir-ritonavir, anakina, baricitinib, type 1 interferons, and immunoglobulin.

  2. Note: If a variable had missing data then the number of patients evaluable for this variable is added as denominator in its analysis result.

  3. COPD = Chronic obstructive pulmonary disease; ANC = Absolute neutrophil count; ALC = Absolute lymphocyte count; IL-1=interleukin 1; IL-6=Interleukin 6; NA = Not applicable.

Table 2
Country-adjusted multivariars of 30 day mortality among all patients.
Independent predictorComplete Case (CC)Multiple imputation (MI)
(N=2349)(N=3966)
aOR95%CIp-valueaOR95%CIp-value
Age ≥65y4.47(3.27, 6.11)<0.00014.73(3.54, 6.32)<0.0001
Prior COPD/bronchiolitis obliterans1.95(1.33, 2.85)<0.0011.73(1.21, 2.48)0.003
History of heart failure1.61(1.13, 2.28)0.0081.64(1.17, 2.29)0.004
History of hypertension1.44(1.03, 2.01)0.0361.52(1.11, 2.07)0.008
Cancer1.30(0.89, 1.90)0.181.23(0.87, 1.75)0.24
Hypoxia at diagnosis4.58(2.92, 7.19)<0.00015.74(3.91, 8.45)<0.0001
Mechanical ventilation/intubation at diagnosis2.20(1.23, 3.93)0.0082.23(1.30, 3.84)0.004
ALC at diagnosis <0.5K/µl1.86(1.30, 2.64)<0.0011.79(1.27, 2.51)<0.001
Creatinine at diagnosis >1.5mg/dl1.68(1.21, 2.31)0.0021.70(1.22, 2.38)0.002
Hemoglobin at diagnosis <10g/dl1.54(1.06, 2.25)0.0241.67(1.18, 2.38)0.004
Coinfection after diagnosis1.83(1.25, 2.68)0.0021.79(1.25, 2.56)0.001
Remdesivir treatment0.64(0.42, 0.97)0.036

  1. The model was adjusted for country, tocilizumb treatment, and convalescent plasma treatment.

  2. The significant difference between the models by CC analysis and by MI analysis was shown in the gray area - remdesivir treatment was an independent predictor of 30 day mortality in the multivariable model by CC analysis but not in the model by MI analysis.

  3. COPD=Chronic obstructive pulmonary disease; ALC=Absolute lymphocyte count.

Table 3
Country-adjusted multivariable logistic regression analysis of independent predictors of 30 day mortality among different patients.
A) Patients with cancer
Independent predictorComplete case (CC)Multiple imputation (MI)
(N=557)(N=1115)
aOR95%CIp-valueaOR95%CIp-value
Age ≥65y6.64(3.51, 12.55)<0.00014.22(2.51, 7.07)<0.0001
History of heart failure2.29(1.19, 4.42)0.014
Hypoxia at diagnosis2.52(1.18, 5.35)0.0172.46(1.17, 5.17)0.017
Non-invasive ventilation at diagnosis2.13(1.01, 4.53)0.0492.67(1.28, 5.57)0.009
ALC at diagnosis <0.5K/µl2.10(1.16, 3.79)0.0141.98(1.14, 3.45)0.017
Hemoglobin at diagnosis <10g/dl2.40(1.30, 4.44)0.0051.74(0.98, 3.08)0.056
Platelet at diagnosis <100K/µl2.21(1.15, 4.24)0.017
LRTI at diagnosis or progression to LRTI3.70(1.94, 7.08)<.00014.16(1.95, 8.82)<0.001
Remdesivir treatment0.44(0.20, 0.96)0.040.45(0.21, 0.98)0.04
B) Patients without cancer
Independent predictorComplete Case (CC)Multiple Imputation (MI)
(N=1777)(N=2851)
aOR95%CIp-valueaOR95%CIp-value
Age ≥65y4.91(3.39, 7.13)<.00014.96(3.46, 7.10)<0.0001
Prior COPD/bronchiolitis obliterans1.81(1.16, 2.83)0.0091.84(1.19, 2.84)0.006
History of ishemic heart disease1.68(1.10, 2.56)0.0171.69(1.12, 2.56)0.013
History of hypertension1.98(1.30, 3.03)0.0022.15(1.42, 3.24)<0.001
Hypoxia at diagnosis7.53(3.72, 15.26)<0.00017.91(4.22, 14.86)<0.0001
Mechanical ventilation/intubation2.38(1.22, 4.62)0.0112.15(1.13, 4.08)0.019
At diagnosis
ALC at diagnosis <0.5K/µl1.62(1.01, 2.59)0.044
Creatinine at diagnosis >1.5mg/dL1.96(1.35, 2.84)<0.0011.95(1.32, 2.87)<0.001
Coinfection after diagnosis3.03(1.87, 4.89)<0.00012.83(1.79, 4.48)<0.0001

  1. ALC=Absolute lymphocyte count; LRTI=Lower respiratory tract infection; COPD=Chronic obstructive pulmonary disease.

  2. The model was adjusted for country and tocilizumb treatment.

  3. The significant differences between the models by CC analysis and by MI analysis were shown in the gray area - (a) History of heart failure and platelet level at diagnosis were independent predictors of 30 day mortality in the multivariable model by MI analysis, but not in the model by CC analysis; (b) Hemoglobin level at diagnosis was an independent predictor of 30 day mortality in the multivariable model by CC analysis, but not in the model by MI analysis.

  4. Hemoglobin level at diagnosis was kept in the final model by MI analysis due to its confounding effect despite its non-significant p-value.

  5. The model was adjusted for country and convalescent plasma treatment.

  6. The significant difference between the models by CC analysis and by MI analysis was shown in the gray area - ALC level at diagnosis was an independent predictor of 30 day mortality in the multivariable model by MI analysis, but not in the model by CC analysis.

Table 4
30 day mortality among different groups of COVID-19 patients with cancer.
Patient groupNo. of patientsNo. (%) who died within 30 days†
Hematological malignancy28337 (13)
Transplant within 1y of COVID-19 diagnosis152 (13)
Lymphoma or myeloma16419 (12)
Lymphocytic leukemia (ALL/CLL)446 (14)
Myelocytic leukemia628 (13)
Solid tumor*63247 (7)
Lung cancer6414 (22)
Metastatic non-lung cancer solid tumor26117 (7)
Non-metastatic non-lung cancer solid tumor30716 (5)
  1. *

    Patients with missing metastasis data were excluded from the analysis.

  2. †

    30 day mortality comparisons for the groups below. (1) Lung cancer vs metastatic non-lung cancer solid tumor: p< 0.001; (2) Lung cancer vs non-metastatic non-lung cancer solid tumor: p< 0.0001; (3) Hematological malignancy vs lung cancer: p=0.07; (4) Hematological malignancy vs non-lung cancer solid tumor: p< 0.001; (5) None of the above significant differences detected remained significant in multivariable analysis of 30 d mortality in cancer patients.

Additional files

Supplementary file 1

Comparing mortality in patients treated with remdesivir alone or with steroids for COVID-19.

https://cdn.elifesciences.org/articles/81127/elife-81127-supp1-v2.docx
Supplementary file 2

Timing of administration of corticosteroids as COVID-19 treatment and 30 d mortality.

https://cdn.elifesciences.org/articles/81127/elife-81127-supp2-v2.docx
MDAR checklist
https://cdn.elifesciences.org/articles/81127/elife-81127-mdarchecklist1-v2.docx

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Issam I Raad
  2. Ray Hachem
  3. Nigo Masayuki
  4. Tarcila Datoguia
  5. Hiba Dagher
  6. Ying Jiang
  7. Vivek Subbiah
  8. Bilal Siddiqui
  9. Arnaud Bayle
  10. Robert Somer
  11. Ana Fernández Cruz
  12. Edward Gorak
  13. Arvinder Bhinder
  14. Nobuyoshi Mori
  15. Nelson Hamerschlak
  16. Samuel Shelanski
  17. Tomislav Dragovich
  18. Yee Elise Vong Kiat
  19. Suha Fakhreddine
  20. Abi Hanna Pierre
  21. Roy F Chemaly
  22. Victor Mulanovich
  23. Javier Adachi
  24. Jovan Borjan
  25. Fareed Khawaja
  26. Bruno Granwehr
  27. Teny John
  28. Eduardo Yepez Yepez
  29. Harrys A Torres
  30. Natraj Reddy Ammakkanavar
  31. Marcel Yibirin
  32. Cielito C Reyes-Gibby
  33. Mala Pande
  34. Noman Ali
  35. Raniv Dawey Rojo
  36. Shahnoor M Ali
  37. Rita E Deeba
  38. Patrick Chaftari
  39. Takahiro Matsuo
  40. Kazuhiro Ishikawa
  41. Ryo Hasegawa
  42. Ramón Aguado-Noya
  43. Alvaro Garcia García
  44. Cristina Traseira Puchol
  45. Dong Gun Lee
  46. Monica Slavin
  47. Benjamin Teh
  48. Cesar A Arias
  49. Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE) Team
  50. Dimitrios P Kontoyiannis
  51. Alexandre E Malek
  52. Anne-Marie Chaftari
(2023)
International multicenter study comparing COVID-19 in patients with cancer to patients without cancer: Impact of risk factors and treatment modalities on survivorship
eLife 12:e81127.
https://doi.org/10.7554/eLife.81127