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Patients with chronic myeloid leukemia and coronavirus disease 2019 in the Omicron era

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Abstract

To explore the prevalence and severity of COVID-19 and the mental health during the Omicron pandemic in patients with chronic myeloid leukemia (CML), a cross-sectional survey from 2609 respondents with CML was performed. A total of 1725 (66%) reported that they had COVID-19 during this period. Among them, 1621 (94%) were mild; 97 (6%), moderate; 7 (0.4%), severe; and 0, critical or death. Four hundred three (15%), 199 (8%), and 532 (20%) had moderate to severe depression, anxiety, and distress, respectively. Eight hundred ninety (34%), 667 (26%), and 573 (22%), avoidance, intrusion, and hyper-arousal, respectively. In multivariate analyses, longer TKI-therapy duration was significantly associated with a lower prevalence of COVID-19 (odds ratio [OR] = 0.98; 95% confidence interval [CI], 0.95, 0.99; p = 0.043); however, living in urban areas (OR = 1.6 [1.3, 2.0]; p < 0.001) and having family members with COVID-19 (OR = 18.6 [15.1, 22.8]; p < 0.001), a higher prevalence of COVID-19. Increasing age (OR = 1.2 [1.1, 1.4]; p = 0.009), comorbidity(ies) (OR = 1.7 [1.1, 2.7]; p = 0.010), and multi-TKI-resistant patients receiving 3rd-generation TKIs or investigational agents (OR = 2.2 [1.2, 4.2]; p = 0.010) were significantly associated with moderate or severe COVID-19. Female, comorbidity(ies), unvaccinated, and moderate or severe COVID-19 were significantly associated with almost all adverse mental health consequences; increasing age or forced TKI dose reduction because of various restriction during the pandemic, moderate to severe distress, avoidance, or intrusion; however, mild COVID-19, none or mild anxiety, distress, avoidance, or intrusion. In conclusion, shorter TKI-therapy duration, increasing age, comorbidity(ies), or multi-TKI-resistant patients receiving 3rd-generation TKIs or investigational agents had a higher prevalence of COVID-19 or higher risk of moderate or severe disease in patients with CML; increasing age, female, comorbidity(ies), forced TKI dose reduction due to the pandemic, moderate or severe COVID-19, unvaccinated, a higher likelihood of worse mental health.

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Data availability

The data of this study are available from the corresponding author upon reasonable request.

References

  1. El Chaer F, Auletta JJ, Chemaly RF (2022) How I treat and prevent COVID-19 in patients with hematologic malignancies and recipients of cellular therapies. Blood 140(7):673–684

    Article  PubMed  PubMed Central  Google Scholar 

  2. Lee LYW, Cazier JB, Starkey T, Briggs SEW, Arnold R, Bisht V et al (2020) 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 21(10):1309–1316

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Breccia M, Abruzzese E, Accurso V, Attolico I, Barulli S, Bergamaschi M et al (2022) COVID-19 infection in chronic myeloid leukaemia after one year of the pandemic in Italy. A Campus CML report. Br J Haematol 196(3):559–565

    Article  CAS  PubMed  Google Scholar 

  4. Claudiani S (2022) Is COVID-19 less severe in CML patients than in those with other haematological cancers? Br J Haematol 196(3):471–472

    Article  CAS  PubMed  Google Scholar 

  5. Ector G, Huijskens EGW, Blijlevens NMA, Westerweel PE (2020) Prevalence of COVID-19 diagnosis in Dutch CML patients during the 2020 SARS-CoV2 pandemic. A prospective cohort study. Leukemia 34(9):2533–2535

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Claudiani S, Rosadas C, McClure M, Khan M, Tedder RS, Innes AJ et al (2020) Prevalence of SARS-CoV-2 infection in patients with chronic myeloid leukemia. Blood 136:20

    Article  Google Scholar 

  7. Bonifacio M, Tiribelli M, Miggiano MC, Abruzzese E, Binotto G, Scaffidi L et al (2021) The serological prevalence of SARS-CoV-2 infection in patients with chronic myeloid leukemia is similar to that in the general population. Cancer Med 10(18):6310–6316

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Pagano L, Salmanton-García J, Marchesi F, Busca A, Corradini P, Hoenigl M et al (2021) COVID-19 infection in adult patients with hematological malignancies: a European Hematology Association Survey (EPICOVIDEHA). J Hematol Oncol 14(1):168

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Başcı S, Ata N, Altuntaş F, Yiğenoğlu TN, Dal MS, Korkmaz S et al (2020) Outcome of COVID-19 in patients with chronic myeloid leukemia receiving tyrosine kinase inhibitors. J Oncol Pharm Pract 26(7):1676–1682

    Article  PubMed  PubMed Central  Google Scholar 

  10. Graf I, Herndlhofer S, Kundi M, Greiner G, Sperr M, Hadzijusufovic E et al (2023) Incidence of symptomatic COVID-19 infections in patients with mastocytosis and chronic myeloid leukemia: a comparison with the general Austrian population. Eur J Haematol 110(1):67–76

    Article  CAS  PubMed  Google Scholar 

  11. Li W, Wang D, Guo J, Yuan G, Yang Z, Gale RP et al (2020) COVID-19 in persons with chronic myeloid leukaemia. Leukemia 34(7):1799–1804

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Arbore DR, Galdean SM, Dima D, Rus I, Kegyes D, Ababei RG et al (2022) COVID-19 impact on chronic myeloid leukemia patients. J Pers Med 12(11):1886

    Article  PubMed  PubMed Central  Google Scholar 

  13. Radich JP, Kok CH, Chelysheva EY, Cortes JE, Jiang Q, Mauro M et al (2022) A risk model for CML patients with COVID-19: importance of molecular response in the context of age, comorbidities and country income. Blood 140(Supplement 1):9617–9619

    Article  Google Scholar 

  14. Rea D, Mauro MJ, Cortes JE, Jiang Q, Pagnano KB, Ongondi M et al (2020) COVID-19 in patients (pts) with chronic myeloid leukemia (CML): results from the International CML Foundation (iCMLf) CML and COVID-19 (CANDID) study. Blood 136(Supplement 1):46–47

    Article  Google Scholar 

  15. Pagnano KB, Kok CH, Mauro MJ, Cortes JE, Evans N, Jiang Q et al (2021) COVID-19 in patients with chronic myeloid leukemia: poor outcomes for patients with comorbidities, older age, advanced phase disease, and those from low-income countries: an update of the Candid study. Blood 138(Supplement 1):634–634

    Article  CAS  Google Scholar 

  16. Galimberti S, Petrini M, Baratè C, Ricci F, Balducci S, Grassi S et al (2020) Tyrosine kinase inhibitors play an antiviral action in patients affected by chronic myeloid leukemia: a possible model supporting their use in the fight against SARS-CoV-2. Front Oncol 10:1428

    Article  PubMed  PubMed Central  Google Scholar 

  17. Lorenzo M, Bentancour F, Garrido G, Garrido D, Guidali C, Prado A et al (2022) Sub-analysis of patients with COVID-19 in chronic myeloid leukemia on TKI treatment: update from the International CML Foundation (iCMLf) CML and COVID19 (CANDID) study. In: The 24th John Goldman conference on chronic myeloid leukemia (CML): biology and therapy. European School of Haematology, Mandelieu-La Napoule

    Google Scholar 

  18. Bao M, Yang S, Gale RP, Zhang Y, Liu X, Zhu H et al (2021) Mental health in persons with chronic myeloid leukemia during the SARS-CoV-2 pandemic: the need for increased access to health care services. Front Psych 12:679932

    Article  Google Scholar 

  19. Zhou Y, Zhi H, Teng Y (2023) The outbreak of SARS-CoV-2 omicron lineages, immune escape, and vaccine effectivity. J Med Virol 95(1):e28138

    Article  CAS  PubMed  Google Scholar 

  20. Tian D, Sun Y, Xu H, Ye Q (2022) The emergence and epidemic characteristics of the highly mutated SARS-CoV-2 omicron variant. J Med Virol 94(6):2376–2383

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Ali EA, Khamees I, Abu-Tineh M, Qasim H, Alshurafa A, Ahmed K et al (2022) SARS-CoV-2 omicron variant in patients with chronic myeloid leukemia: a retrospective study. Cureus 14(4):e23863

    PubMed  PubMed Central  Google Scholar 

  22. Liu Y, Rocklöv J (2022) The effective reproductive number of the omicron variant of SARS-CoV-2 is several times relative to delta. J Travel Med 29(3):taac037

    Article  PubMed  PubMed Central  Google Scholar 

  23. Ulloa AC, Buchan SA, Daneman N, Brown KA (2022) Estimates of SARS-CoV-2 omicron variant severity in Ontario, Canada. Jama 327(13):1286–1288

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Sheikh A, Kerr S, Woolhouse M, McMenamin J, Robertson C (2022) Severity of omicron variant of concern and effectiveness of vaccine boosters against symptomatic disease in Scotland (EAVE II): a national cohort study with nested test-negative design. Lancet Infect Dis 22(7):959–966

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Bager P, Wohlfahrt J, Bhatt S, Stegger M, Legarth R, Møller CH et al (2022) Risk of hospitalisation associated with infection with SARS-CoV-2 omicron variant versus delta variant in Denmark: an observational cohort study. Lancet Infect Dis 22(7):967–976

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Nyberg T, Ferguson NM, Nash SG, Webster HH, Flaxman S, Andrews N et al (2022) Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study. Lancet 399(10332):1303–1312

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lewis D (2023) China’s COVID wave has probably peaked, model suggests. Nature 613(7944):424–425

    Article  CAS  PubMed  Google Scholar 

  28. Pan Y, Wang L, Feng Z, Xu H, Li F, Shen Y et al (2023) Characterisation of SARS-CoV-2 variants in Beijing during 2022: an epidemiological and phylogenetic analysis. Lancet 401(10377):664–672

    Article  PubMed  PubMed Central  Google Scholar 

  29. Manea L, Gilbody S, McMillan D (2012) Optimal cut-off score for diagnosing depression with the patient health questionnaire (PHQ-9): a meta-analysis. Cmaj 184(3):E191–E196

    Article  PubMed  PubMed Central  Google Scholar 

  30. Löwe B, Decker O, Müller S, Brähler E, Schellberg D, Herzog W et al (2008) Validation and standardization of the generalized anxiety disorder screener (GAD-7) in the general population. Med Care 46(3):266–274

    Article  PubMed  Google Scholar 

  31. Wu KK, Chan KS (2003) The development of the Chinese version of Impact of Event Scale – Revised (CIES-R). Soc Psychiatry Psychiatr Epidemiol 38(2):94–98

    Article  CAS  PubMed  Google Scholar 

  32. Spitzer RL, Kroenke K, JBW W, Löwe B (2006) A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 166(10):1092–1097

    Article  PubMed  Google Scholar 

  33. Hochhaus A, Baccarani M, Silver RT, Schiffer C, Apperley JF, Cervantes F et al (2020) European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia 34(4):966–984

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Guilhot J, Baccarani M, Clark RE, Cervantes F, Guilhot F, Hochhaus A et al (2012) Definitions, methodological and statistical issues for phase 3 clinical trials in chronic myeloid leukemia: a proposal by the European LeukemiaNet. Blood 119(25):5963–5971

    Article  CAS  PubMed  Google Scholar 

  35. Baccarani M, Deininger MW, Rosti G, Hochhaus A, Soverini S, Apperley JF et al (2013) European LeukemiaNet recommendations for the management of chronic myeloid leukemia: 2013. Blood J American Soc Hematol 122(6):872–884

    CAS  Google Scholar 

  36. Baccarani M, Saglio G, Goldman J, Hochhaus A, Simonsson B, Appelbaum F et al (2006) Evolving concepts in the management of chronic myeloid leukemia: recommendations from an expert panel on behalf of the European LeukemiaNet. Blood 108(6):1809–1820

    Article  CAS  PubMed  Google Scholar 

  37. Zhang XS, Gale RP, Huang XJ, Jiang Q (2022) Is the Sokal or EUTOS long-term survival (ELTS) score a better predictor of responses and outcomes in persons with chronic myeloid leukemia receiving tyrosine-kinase inhibitors? Leukemia 36(2):482–491

    Article  PubMed  Google Scholar 

  38. Zhang XS, Gale RP, Zhang MJ, Huang XJ, Jiang Q (2022) A predictive scoring system for therapy-failure in persons with chronic myeloid leukemia receiving initial imatinib therapy. Leukemia 36(5):1336–1342

    Article  CAS  PubMed  Google Scholar 

  39. Yang S, Zhang XS, Gale RP, Huang XJ, Jiang Q (2022) Co-variates associated with outcomes of tyrosine kinase-inhibitor therapy in persons with chronic myeloid leukaemia initially presenting in accelerated phase. Leukemia 36(7):1818–1824

    Article  CAS  PubMed  Google Scholar 

  40. Zhang XS, Gale RP, Li ZY, Zhang MY, Huang XJ, Jiang Q (2022) Predictive scoring systems for molecular responses in persons with chronic phase chronic myeloid leukemia receiving initial imatinib therapy. Leukemia 36(8):2042–2049

    Article  CAS  PubMed  Google Scholar 

  41. Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N et al (2020) Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Netw Open 3(3):e203976

    Article  PubMed  PubMed Central  Google Scholar 

  42. Wu Q, Wang H, Cai J, Ai J, Li Y, Zhang H et al (2023) Vaccination effects on post-infection outcomes in the omicron BA.2 outbreak in Shanghai. Emerg Microbes Infect 12(1):e2169197

    Article  PubMed  PubMed Central  Google Scholar 

  43. McMenamin ME, Nealon J, Lin Y, Wong JY, Cheung JK, Lau EH et al (2022) Vaccine effectiveness of one, two, and three doses of BNT162b2 and CoronaVac against COVID-19 in Hong Kong: a population-based observational study. Lancet Infect Dis 22(10):1435–1443

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Mefsin YM, Chen D, Bond HS, Lin Y, Cheung JK, Wong JY et al (2022) Epidemiology of infections with SARS-CoV-2 omicron BA.2 variant, Hong Kong, January-March 2022. Emerg Infect Dis 28(9):1856–1858

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Petrone D, Mateo-Urdiales A, Sacco C, Riccardo F, Bella A, Ambrosio L et al (2023) Reduction of the risk of severe COVID-19 due to omicron compared to delta variant in Italy (November 2021-February 2022). Int J Infect Dis 129:135–141

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Chadeau-Hyam M, Tang D, Eales O, Bodinier B, Wang H, Jonnerby J et al (2022) Omicron SARS-CoV-2 epidemic in England during February 2022: a series of cross-sectional community surveys. Lancet Reg Health Eur 21:100462

    Article  PubMed  PubMed Central  Google Scholar 

  47. Boucau J, Marino C, Regan J, Uddin R, Choudhary MC, Flynn JP et al (2022) Duration of shedding of culturable virus in SARS-CoV-2 omicron (BA.1) infection. N Engl J Med 387(3):275–277

    Article  PubMed  Google Scholar 

  48. Asif M, Amir M, Hussain A, Achakzai NM, Natesan Pushparaj P, Rasool M (2022) Role of tyrosine kinase inhibitor in chronic myeloid leukemia patients with SARS-CoV-2 infection: a narrative review. Medicine (Baltimore) 101(26):e29660

    Article  CAS  PubMed  Google Scholar 

  49. Coleman CM, Sisk JM, Mingo RM, Nelson EA, White JM, Frieman MB (2016) Abelson Kinase inhibitors are potent inhibitors of severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus fusion. J Virol 90(19):8924–8933

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Sisk JM, Frieman MB, Machamer CE (2018) Coronavirus S protein-induced fusion is blocked prior to hemifusion by Abl kinase inhibitors. J Gen Virol 99(5):619–630

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Delgado N, Torres A (2022) What do we currently know about chronic myeloid leukemia (CML) and COVID-19? Curr Oncol Rep 24(5):645–650

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Zumla A, Chan JF, Azhar EI, Hui DS, Yuen KY (2016) Coronaviruses - drug discovery and therapeutic options. Nat Rev Drug Discov 15(5):327–347

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Chan M, Holland EC, Gujral TS (2022) Olverembatinib inhibits SARS-CoV-2-omicron variant-mediated cytokine release in human peripheral blood mononuclear cells. EMBO Mol Med 14(6):e15919

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Hughes A, Clarson J, Tang C, Vidovic L, White DL, Hughes TP et al (2017) CML patients with deep molecular responses to TKI have restored immune effectors and decreased PD-1 and immune suppressors. Blood 129(9):1166–1176

    Article  CAS  PubMed  Google Scholar 

  55. Organization WH (2021) Interim recommendations for use of the inactivated COVID-19 vaccine, CoronaVac, developed by Sinovac: interim guidance, 24 May 2021. World Health Organization

    Google Scholar 

  56. Feikin DR, Higdon MM, Abu-Raddad LJ, Andrews N, Araos R, Goldberg Y et al (2022) Duration of effectiveness of vaccines against SARS-CoV-2 infection and COVID-19 disease: results of a systematic review and meta-regression. The Lancet

  57. Hossain MM, Tasnim S, Sultana A, Faizah F, Mazumder H, Zou L et al (2020) Epidemiology of mental health problems in COVID-19: a review. F1000Res 9:636

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Mojtabai R (2022) COVID-19 vaccination and mental health distress. J Gen Intern Med 37(4):1020–1021

    Article  PubMed  PubMed Central  Google Scholar 

  59. Pierce M, Hope H, Ford T, Hatch S, Hotopf M, John A et al (2020) Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. Lancet Psychiatry 7(10):883–892

    Article  PubMed  PubMed Central  Google Scholar 

  60. Wang Y, Di Y, Ye J, Wei W (2021) Study on the public psychological states and its related factors during the outbreak of coronavirus disease 2019 (COVID-19) in some regions of China. Psychol Health Med 26(1):13–22

    Article  PubMed  Google Scholar 

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Acknowledgements

QJ acknowledges support from the National Natural Science Foundation of China (No. 81970140). We thank American Journal Experts (AJE) for its linguistic assistance during the preparation of this manuscript.

Funding

Funded by the National Nature Science Foundation of China (No. 81970140).

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Author notes

  1. Feiyang Qi, Mei Bao, and Hanlin Gao contributed equally to this work.

Authors and Affiliations

  1. Peking University People’s Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, No. 11 Xizhimen South St, Beijing, 100044, China

    Feiyang Qi, Mei Bao, Hanlin Gao, Xiaoshuai Zhang & Qian Jiang

  2. Peking University People’s Hospital, Qingdao, China

    Shasha Zhao, Chenglei Wang, Wenwen Li & Qian Jiang

  3. Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China

    Qian Jiang

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Contributions

QJ designed the study. MB helped to design the questionnaire. QJ, FYQ, MB, HLG, SSZ, CLW, and WWL delivered and collected the questionnaires. QJ, FYQ, MB, HLG, and XSZ analyzed the data. QJ, FYQ, MB, and HLG prepared the typescript. All authors approved the final typescript, take responsibility for the content, and agree to submit for publication.

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Correspondence to Qian Jiang.

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Qi, F., Bao, M., Gao, H. et al. Patients with chronic myeloid leukemia and coronavirus disease 2019 in the Omicron era. Ann Hematol 102, 2707–2716 (2023). https://doi.org/10.1007/s00277-023-05413-0

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