Abstract
Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) in China at the end of 2019, the virus has spread rapidly across the globe leading to millions of infections and subsequent deaths. Although the virus infects those exposed indiscriminately, there are groups in society at an increased risk of severe infection, leading to increased morbidity. Patients suffering from hematological cancers, particularly leukemia, lymphoma, and myeloma, may be one such group and previous studies have suggested that they may be at a three to four times greater risk of severe COVID‐19 after SARS‐CoV‐2 infection, leading to admissions to ICU, mechanical ventilation, and death compared to those without such malignancies. Serological testing for IgG seroconversion has been extensively studied in the immunocompetent, but fewer publications have characterized this process in large series of immunocompromised patients. This study described 20 patients with hematological cancers who tested positive for SARS‐CoV‐2 via PCR with 12 of the patients receiving further serological testing. We found that of the 12 patients screened for SARS‐CoV‐2 IgG antibodies, only 2 (16.6%) were able to generate an immune response to the infection. Yet despite this low seroconversion rate in this cohort, none of these patients died or became particularly unwell with COVID‐19 or its related complications.
Keywords: immune responses, immunoglobulin, SARS coronavirus, virus classification
Highlights
Investigation into the immune response of haematology patients to SARS‐CoV‐2.
Although haematology patients are at a greater risk of infection they appear to be less susceptible to severe SARS‐CoV‐2 infections.
Suppression of the immune response could potentially confer some protection from severe COVID‐19.
1. BACKGROUND
Patients with hematological cancers are at increased risk of coronavirus disease (COVID‐19), in part due to their underlying malignancy, but also to their increased age (peak incident of cancer is 85–89 years) with any accompanying comorbidities. Of note is the increased production of angiotensin‐converting enzyme‐2 (a key enzyme for infectivity by coronaviruses) that occurs with advancing age. 1 , 2
Another aspect that can potentially increase the severity of COVID‐19 disease in cancer patients is a reduced ability to mount an adaptive immune response following the initial innate response. The situation becomes more complicated by patients on active cancer treatments, further impairing their immune response. 3 Initial data from China revealed a 3.5‐fold increase in COVID‐19 infections in patients with cancer requiring admission to ICU, mechanical ventilation, and death compared to those without cancer. 4 However, recent studies have revealed that patients with hematological cancers may be at a reduced risk of severe COVID‐19 due to their inability to produce an excessive, aberrant immune response which leads to acute respiratory distress syndrome and death in severe cases. 5 Rather, hematology patients with any of the other known high‐risk comorbidities for severe COVID‐19 (hypertension, diabetes, and other chronic diseases) could be the main driver behind any increase in deaths associated with COVID‐19, but larger studies are still required to confirm this. 6
Seroconversion for severe acute respiratory syndrome coronavirus 2 (SASR‐CoV‐2) IgG occurs after 10–12 days and SARS‐CoV‐2 IgM seroconversion after 11–13 days following infection with SARS‐CoV‐2 in immunocompetent patients. 7 However, there have been few publications detailing the serological responses and clinical outcomes to SARS‐CoV‐2 in hematology–oncology patients.
We present a case series of 20 hematology–oncology patients who tested positive for SARS‐CoV‐2, their symptoms, serological responses, and outcomes.
2. REPORT OF 20 HEMATOLOGY–ONCOLOGY CASES WITH COVID‐19
Twenty patients with hematological cancers who tested positive for COVID‐19 between March 3, 2020 and June 30, 2020 are reported here. A positive COVID‐19 result is defined as a nasopharyngeal swab that tested positive for SARS‐CoV‐2 RNA by reverse‐transcriptase polymerase‐chain‐reaction (RT‐PCR). The AusDiagnostics SARS‐CoV‐2 PCR assay (AusDiagnostics UK Ltd) was used for testing which targets the ORF1 and ORF8 genes, both targets were detected in all patient samples. Kit sensitivity and specificity have been reported as 97%–98% and 99%–100%, respectively, by the manufacturer and external sources. 8 Patient sera were tested using the DiaSorin Liaison SARS‐CoV‐2 S1/S2 assay IgG Kit with manufacturer sensitivity and specificity reported as 97% (86.8%–99.5%) and 98.9% (97.5%–99.2%), respectively.
Patient demographics and clinical characteristics have been displayed in Tables 1 and 2. The median age of patients was 77.20 (s.d: 11.45, range: 56–93), of which 14 were male (60%) and 6 were female, 18 of which required admission with an average length of 13 days (s.d: 11.8, range: 3–43).
Table 1.
Characteristic | Value |
---|---|
Patients (n = 20) | |
Patient age (years) | |
Mean ± SD | 77.20 ± 11.45 |
Range | 56–93 |
Sex, n (%) | |
Male | 14 (70) |
Female | 6 (30) |
Disease severity (%)a | |
0 | 6 (30) |
1 | 6 (30) |
2 | 4 (20) |
3 | 4 (20) |
Cancer (%) | |
Lymphoma | 6 (30) |
Leukemia | 7 (35) |
Myeloma | 7 (35) |
Symptoms (%) | |
Fever | 10 (50) |
Cough | 5 (25) |
SOB | 9 (45) |
Abdominal pain | 2 (10) |
Comorbidities (%) | |
Hypertension | 10 (50) |
Diabetes | 4 (20) |
Osteoporosis | 5 (25) |
Cognitive disorder | 2 (10) |
Alive/deceased (%) | |
Alive | 13 (65) |
Deceased | 7 (35) |
Abbreviations: SARS‐CoV‐2, severe acute respiratory syndrome coronavirus 2; SOB, shortness of breath.
Disease severity calculated by the number of symptoms.
Table 2.
Patient | Sex | Age on admission (years) | Length of admission (days) | Alive/deceased | COVID‐19 symptom score | Hematological disease | Cancer treatment | Clinical features | SARS‐CoV‐2 Swab PCR | Finds on chest X‐ray | Serology for anti‐SARS‐CoV‐2 IgG | Time between Symptom onset and PCR sample (days) | Time between symptom onset and serum sample (days) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | F | 89 | 12 | Alive | 6 | Myeloma | Lenalidomide and dexamethasone | SOB, cough, and fever | Positive | Patchy opacification of lower zones bilaterally | Negative | 11 | 11 |
2 | F | 86 | 6 | Deceased | 7 | Myeloma | Lenalidomide and dexamethasone | Asymptomatic | Positive | Linear atelectasis in both lowers but no focal consolidation | Negative | 0 | 18 |
3 | M | 70 | 3 | Alive | 6 | Lymphoma | Tirabutinib | Fever, cough, and SOB | Positive | Extensive peripheral subpleural ground‐glass opacities with consolidation | Negative | 8 | 8 |
4 | M | 79 | 4 | Alive | 3 | Lymphoma | Unknown | Asymptomatic | Positive | No lung parenchymal changes of COVID‐19 | Negative | 0 | 25 |
5 | M | 87 | 14 | Alive | 3 | Myeloma | Lenalidomide and dexamethasone | Asymptomatic | Positive | Bilateral peripheral ground‐glass opacities | Negative | 0 | 12 |
6 | M | 82 | 39 | Alive | 2 | Myeloma | Lenalidomide and dexamethasone | Fever | Positive | No convincing features to suggest COVID‐19 | Negative | 7 | 30 |
7 | M | 56 | 13 | Alive | 4 | Leukemia | Unknown | Fever and SOB | Positive | Unilateral consolidation | Positive | 6 | 19 |
8 | M | 74 | 27 | Alive | 4 | Leukemia | Cyatarbine venetoclax | Fever | Positive | Right side pleural effusion | Negative | 6 | 8 |
9 | M | 93 | 19 | Alive | 1 | Lymphoma | Unknown | Asymptomatic | Positive | No CXR results | Positive | 6 | 13 |
10 | M | 63 | 6 | Alive | 2 | Lymphoma | Pomalidomide, dexamethasone, and apixaban | Asymptomatic | Positive | Bilateral lower lobe pulmonary embolism | Not tested | 0 | – |
11 | M | 69 | 14 | Alive | 4 | Leukemia | Lenalidomide, dexamethasone, and daratumumab | Fever | Positive | Right‐side pleural effusion | Negative | 6 | 7 |
12 | M | 79 | 8 | Deceased | 7 | Myeloma | Pomalidomide and dexamethasone | Fever and SOB | Positive | No CXR results | Not tested | 0 | – |
13 | M | 77 | 5 | Alive | 3 | Lymphoma | Dexamethasone | Cough and SOB | Positive | No CXR results | Negative | 0 | 0 |
14 | M | 60 | 8 | Deceased | 9 | Leukemia | Not on treatment | Fever, cough, and SOB | Positive | Coarsened airspace shadowing in both lungs | Not tested | 0 | – |
15 | F | 86 | 8 | Deceased | 8 | Leukemia | Not on treatment | Abdominal pain | Positive | Left basal apical linear atelectasis | Not tested | 1 | – |
16 | F | 92 | 18 | Alive | 3 | Leukemia | Mycophenolate and prednisolone | Asymptomatic | Positive | Patchy bibasal consolidation | Not tested | 0 | – |
17 | M | 88 | 0 | Deceased | 8 | Leukemia | Radiotherapy | SOB | Positive | Patchy bilateral perihilar inflammatory changes | Not tested | 1 | – |
18 | F | 68 | 43 | Deceased | 8 | Lymphoma | Not on treatment | SOB | Positive | Bilateral patchy air space opacification | Not tested | 0 | – |
19 | F | 85 | 0 | Deceased | 9 | Lymphoma | Not on treatment | Fever and abdominal pain | Positive | Bibasal consolidation with bilateral pleural effusions | Not tested | 24 | – |
20 | M | 61 | 5 | Alive | 5 | Lymphoma | Atorvastatin | Fever, cough, and SOB | Positive | Bilateral air space shadowing | Negative | 0 | 2 |
Abbreviations: CXR, chest X‐ray; F, female; M, male; SARS‐CoV‐2, severe acute respiratory syndrome coronavirus 2; SOB, shortness of breath.
Out of the 20 patients, 7 had a lymphoma (35%), 7 had leukemia (35%), and 6 had myeloma (30%). Many patients had coexisting medical conditions: hypertension (50%), osteoporosis (25%), diabetes (20%), and a cognitive disorder (10%). The most common symptoms were fever (50%), shortness of breath (45%), cough (25%), and abdominal pain (2%).
Patient symptom severity was assessed using a COVID‐19 symptom score (CSS) ranging from 1 to 15 (1–3 = low, 4–6 = medium, and >7 = severe) with individual symptoms each scoring 1, >65 years of age scoring 1, coexisting medical conditions scoring 1, chest X‐rays consistent with COVID‐19 scoring 2, ICU admission scoring 3, and death with COVID‐19 scoring 4 (Table 2).
The CSS assessment revealed that 7/20 (35%) presented with low severity, 6/20 (30%) presented with medium severity, and 7/20 (35%) presented with severe symptoms. All patients with low or medium CSS survived their infections (13/20, 11 male, 2 female); while all patients with severe CSS scores died with the infection (7/20, 3 male, 4 female). All surviving patients will continue with their follow‐up appointments as part of their care pathway.
Seventeen of the cohort had chest X‐rays performed (Table 2) with 15 reported to have features consistent with infection (88%). The median time from symptom onset to a PCR test was 3.8 days (s.d: 5.9, range: 0–24) while the median time from symptom onset to serum sample collection was 13 days (s.d: 9, range: 0–30; Table 2).
Thirteen of the patients presented here (65%) survived while the remaining seven patients (35%) died with the SARS‐CoV‐2 infection. Of the seven deceased patients, four were female (median age: 81.15, s.d: 8.84, range: 68–86) and three were male (median age: 75.66, s.d: 14.3, range: 60–88). In terms of hematological cancer and mortality, two had myelomas, three had leukemias, and two had lymphomas. Note that for the patients who died with SARS‐CoV‐2 infection, we cannot be certain that this was the definitive cause of their death without additional post‐mortem investigations.
Out of the 20 patients included in this case series, 12 were tested for SARS‐CoV‐2 IgG seroconversion from stored serum samples with two patients successfully seroconverting (16.6%; Table 2). The two patients (Cases 7 and 9) positive for SARS‐CoV‐2 IgG had a mean time for onset of symptoms to serum testing of 16 days (s.d.: 4.2, range: 13–19), while for negative anti‐SARS‐CoV‐2 patients the meantime between symptoms and serum testing was 12.1 days (s.d: 10.1, range: 0–30).
3. DISCUSSION
The median age for our cohort was 77.20 with a range of 56–93 years, which correlates well with the increased incidence of cancer and cases of COVID‐19 with advancing age. 1 , 2 Our cohort was predominately male (60%) but of those who died with COVID‐19 (SARS‐CoV‐2 infection), the majority were female (57.1%). Studies on otherwise immunocompetent patients with COVID‐19 have found that male patients tend to have more severe disease and higher mortality. 5
The hematological cancers among our cohort were evenly distributed with similar numbers of patients with lymphoma, leukemia, and myeloma. This even distribution was also seen in the patients who died (two lymphoma, three leukemia, and two myeloma cases).
In terms of CSS and symptoms, our cohort again reflected those of other studies with the most common symptom being fever, followed by breathlessness, then cough, and finally abdominal pain (Table 1). 9 , 10 However, within our cohort females presented with higher CSS scores than males and a higher death rate, which differs from the findings of other studies involving non‐hematology patients. 5 , 11
Immunological responses to SARS‐CoV‐2 in immunocompetent patients have been investigated by several research groups, all giving a range of seroconversion rates for IgG and IgM of 11–20 days. 7 , 12 , 13 The average time between symptom onset and serum sample was 13 days (range: 0–30) which is adequate time for an immunological response in most immunocompetent patients. 7 The SARS‐CoV‐2 IgG seroconversion rates vary widely with some studies stating seroconversion rates of 44% to as high as 89%. 13 , 14 In our cohort, we report a seroconversion rate of 2/12 (16.6%), far below the average for immunocompetent patients, which may not be unexpected for immunocompromised hosts, particularly in this hematology patients cohort where some were on anti‐CD‐20 therapies that will reduce antibody responses to such viral infections. 3 , 4 This lack of immune response could, paradoxically, give increased protection to hematology patients from SARS‐CoV‐2 due to a decrease in the interleukin 6 production, a key interleukin in the hyperinflammatory phase of the COVID‐19 disease. 15
Of our cohort that was tested for SARS‐CoV‐2 IgG, 6/12 (50%) were less than 14 days post‐symptom onset (Table 2). This included nine patients who were tested positive 13 days post‐symptom onset. Therefore, it is feasible that the remaining patients, given more time, could have developed an immunological response. There are relatively few studies investigating the antibody response in cancer patients, and in those published, they generally exclude patients who are less than 21 days post‐symptom onset due to their delayed immune responses, while some studies have waited up to 50 days before serological testing. 10 , 16 , 17
Earlier data from China demonstrated a 3.5‐fold increase in COVID‐19 infections amongst patients with cancer who eventually required ICU admission. 4 However, of the seven patients within our cohort who died with COVID‐19 infection, four (Cases 14, 15, 18, 19) were not on any form of immunosuppressive treatment (57%). Therefore, it is feasible that due to the cessation of anticancer therapy their partially reconstituted host immune response may have contributed to their more severe COVID‐19 presentation, increasing their risk of severe disease and death. 18
In contrast, two independent studies on large hematology case series from the United Kingdom have advocated the continuation of anticancer therapy in such patients, as the impact of COVID‐19 on these cancer cases was deemed to be less of a risk than their underlying malignancy progressing. 19 , 20
4. CONCLUSION
This retrospective study demonstrates the possibility of more severe clinical outcomes in hematological patients with COVID‐19. However, other studies with contrasting findings and recommendations 4 , 19 , 20 demonstrate the need for further studies into how the severity of COVID‐19 and clinical outcomes correlates to the varied immunological response of this group—which may vary substantially between individual cases.
Hematological patients who have been off chemotherapy or have been on minimum immunosuppression for some time, allowing partial host immune reconstitution may manifest stronger and potentially more aberrant immune responses that may impact on their clinical severity and outcomes of COVID‐19. In contrast, patients already on chemotherapy to suppress the progression of their underlying malignancy may need to continue these even in the presence of COVID‐19, the clinical impact of which may be blunted due to the continuing immunosuppression from such therapies.
CONFLICT OF INTERESTS
The authors have no conflict of interests to declare. All coauthors have seen and agree with the contents of the manuscript and there is no financial interest to report. We certify that the submission is original work and is not under review at any other publication.
AUTHOR CONTRIBUTIONS
Julian W.‐T. Tang conceived the presented idea. Ben Kennedy, Sapna Ladani, and Julian W.‐T. Tang identified relevant patients. Paul W. Bird performed all testing of samples. Paul W. Bird and Vinay Badhwar collated the patient data and performed the data analysis. Paul W. Bird, Vinay Badhwar, and Julian W.‐T. Tang drafted the manuscript. All authors reviewed the manuscript and made amendments before submission.
Bird PW, Badhwar V, Kennedy B, Ladani S, Tang JWT. Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) seroconversion in hematology–oncology patients. J Med Virol. 2021;93:4585–4591. 10.1002/jmv.26886
REFERENCES
- 1. Office for National Statistics . Cancer registration statistics, England, 2013. Stat. Bull. 2015.1–15. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases#publications. [Google Scholar]
- 2. Ciotti M, Angeletti S, Minieri M, et al. COVID‐19 outbreak: an overview. Chemotherapy. 2020;64:215‐223. 10.1159/000507423 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Sica A, Casale D, Rossi G, et al. The impact of the SARS‐CoV‐2 infection, with special reference to the hematological setting. J Med Virol. 2020;93:223‐233. 10.1002/jmv.26197 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Liang W, Guan W, Chen R, et al. Cancer patients in SARS‐CoV‐2 infection: a nationwide analysis in China. Lancet Oncol. 2020;21:335‐337. 10.1016/S1470-2045(20)30096-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Perrotta F, Corbi G, Mazzeo G, et al. COVID‐19 and the elderly: insights into pathogenesis and clinical decision‐making. Aging Clin Exp Res. 2020;32:1599‐1608. 10.1007/s40520-020-01631-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Wood WA, Neuberg DS, Thompson JC, et al. Outcomes of patients with hematologic malignancies and COVID‐19: a report from the ASH Research Collaborative Data Hub. Blood Adv. 2020;4:5966‐5975. 10.1182/bloodadvances.2020003170 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Hsueh PR, Huang LM, Chen PJ, Kao CL, Yang PC. Chronological evolution of IgM, IgA, IgG and neutralisation antibodies after infection with SARS‐associated coronavirus. Clin Microbiol Infect. 2004;10:1062‐1066. 10.1111/j.1469-0691.2004.01009.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Dhakal B, D'Souza A, Chhabra S, Hari P. Multiple myeloma and COVID‐19. Leukemia. 2020;34:1961‐1963. 10.1038/s41375-020-0879-9 [DOI] [PubMed] [Google Scholar]
- 9. Macera M, De Angelis G, Sagnelli C, Coppola N. Clinical presentation of covid‐19: case series and review of the literature. Int J Environ Res Public Health. 2020;17:5062. 10.3390/ijerph17145062 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Luciani M, Bentivegna E, Spuntarelli V, et al. Recurrent COVID‐19 pneumonia in the course of chemotherapy: consequence of a weakened immune system? J Med Virol. 2021;93(4):1882‐1884. 10.1002/jmv.26701 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Yuan X, Huang W, Ye B, et al. Changes of hematological and immunological parameters in COVID‐19 patients. Int J Hematol. 2020;112:553‐559. 10.1007/s12185-020-02930-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Long QX, Liu BZ, Deng HJ, et al. Antibody responses to SARS‐CoV‐2 in patients with COVID‐19. Nat Med. 2020;26:845‐848. 10.1038/s41591-020-0897-1 [DOI] [PubMed] [Google Scholar]
- 13. Lou B, Li TD, Zheng SF, et al. Serology characteristics of SARS‐CoV‐2 infection after exposure and post‐symptom onset. Eur Respir J. 2020;56:2000763. 10.1183/13993003.00763-2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Wajnberg A, Mansour M, Leven E, et al. Humoral response and PCR positivity in patients with COVID‐19 in the New York City region, USA: an observational study. Lancet Microbe. 2020;1:e283‐e289. 10.1016/s2666-5247(20)30120-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Zhong J, Tang J, Ye C, Dong L. The immunology of COVID‐19: is immune modulation an option for treatment? Lancet Rheumatol. 2020;2:e428‐e436. 10.1016/S2665-9913(20)30120-X [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Solodky ML, Galvez C, Russias B, et al. Lower detection rates of SARS‐COV2 antibodies in cancer patients versus health care workers after symptomatic COVID‐19. Ann Oncol. 2020;31:1087‐1088. 10.1016/j.annonc.2020.04.475 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Liu T, Zeng G, Tao H, et al. Low prevalence of IgG antibodies to SARS‐CoV‐2 in cancer patients with COVID‐19. Int J Cancer. 2020;147:3267‐3269. 10.1002/ijc.33148 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Saini KS, Lanza C, Romano M, et al. Repurposing anticancer drugs for COVID‐19‐induced inflammation, immune dysfunction, and coagulopathy. Br J Cancer. 2020;123:694‐697. 10.1038/s41416-020-0948-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Fox TA, Troy‐Barnes E, Kirkwood AA, et al. Clinical outcomes and risk factors for severe COVID‐19 in patients with haematological disorders receiving chemo‐ or immunotherapy. Br J Haematol. 2020;191:194‐206. 10.1111/bjh.17027 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Morrissey H, Ball P, Mandal A, et al. COVID‐19 in haematology patients: a multicentre West Midlands clinical outcomes analysis on behalf of the West Midlands Research Consortium. Br J Haematol. 2021;192(1):e11‐e14. 10.1111/bjh.17136 [DOI] [PubMed] [Google Scholar]