Abstract
Objective
A SARS-CoV-2 Omicron (BA.5.2) epidemic began in China in December, 2022 following stopping the zero COVID policy.
Methods
We studied features of the epidemic in 1,121 persons with chronic myeloid leukaemia (CML).
Results
1103 (98%) were in chronic, 10 in accelerated and 8 in acute phases. 834 (74%) became infected almost all of whom met criteria for COVID-19. The most common symptoms were fever (91%), cough (90%) and fatigue (82%). 42 infected persons were asymptomatic. Most people quarantined at home and self-medicated. 22 were hospitalized for COVID-19. At admission 5 had mild, 14, moderate and 3, severe/critical disease according to World Health Organization (WHO) criteria. 5 received respiratory assistance, 3 were admitted to the intensive care unit (ICU) and 1 in accelerated phase died from COVID-19. Co-variates associated with a risk of COVID-19 in SARS-CoV-2-infected subjects include age ≥ 65 years, higher education level and imatinib therapy.
Conclusion
In conclusion, most SARS-CoV-2 Omicron BA.5.2 infections in persons with CML resulted in COVID-19 most of which cases are mild with only 1 death.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00432-023-04995-6.
Keywords: Chronic myeloid leukaemia, COVID-19, SARS-CoV-2 Omicron, Omicron BA.5.2
Introduction
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic began in December 2019 and SARS-CoV-2 Omicron BA.5.2 first reported in November 2021. (Petersen et al. 2022) Soon thereafter China implemented a dynamic zero-COVID policy which was terminated in November, 2022 when SARS-CoV-2 Omicron BA.5.2 was the predominant stain. This was quickly followed by an epidemic of SARS-CoV-2 Omicron in China. This situation gave us a unique opportunity to study the impact of the epidemic on SARS-CoV-2 Omicron BA.5.2-infection and subsequent development of coronavirus disease-2019 (COVID-19) in 1121 persons with chronic myeloid leukaemia (CML) using an online questionnaire. We found most became infected but few developed COVID-19 most of which cases were mild with rare deaths.
Methods
Survey-design
Persons with CML from the Hubei and Henan provinces were recruited for a survey November 11, 2022 to January 31, 2023 based on registration in the Hubei or Henan Anti-Cancer Associations. Subjects or their guardians were asked to complete an online questionnaire which included 30 questions assessing demographics, education levels, co-morbidities, infection symptoms, Drugs and outcomes of COVID-19 and CML-related data including diagnosis, therapies (Supplement). Data on therapy response and outcomes were extracted from records of the Anti-Cancer Associations. The impact of SARS-CoV-2 Omicron infection and COVID-19 on CML management was also queried. Missing or ambiguous data were clarified by direct communication with the subject, guardians and/or health-care providers. The study was approved by the Institutional Ethics Committee of the Tongji Medical College, Huazhong University of Science and Technology (Wuhan, China; Approval. 2023 0065). The requirement for written informed consent was waived.
Diagnosis, monitoring, and response to TKI therapy
Diagnosis of CML disease phase, monitoring and response used 2020 European LeukemiaNet recommendations (Hochhaus et al. 2020). Although the 2022 WHO classification of CML deleted accelerated phase we retained the prior definition.
Criteria for SARS-CoV-2-infection and COVID-19
SARS-CoV-2 infection was based on subjects indicating a positive real time qualitative polymerase chain reaction (qRT-PCR) or antigen self-test on the questionnaire. COVID-19 severity at hospitalization was graded using World Health Organization (WHO) criteria (WHO 2022). Outcomes were defined as follows: (1) cured: 2 successive negative qRT-PCR tests ≥ 24 h apart and being asymptomatic; (2) in hospital: still hospitalized at the time of survey; or (3) death from COVID-19. Vaccinated subjects received inactivated COVID-19 vaccines such as Sinovac-CoronaVac COVID-19 vaccine, Sinopharm COVID-19 vaccine (Wuhan) and Sinopharm COVID-19 vaccine (Beijing).
Statistical analyses
Descriptive co-variants are presented as median (Interquartile Range; IQR) or number (percentage). Differences between cohorts were analyzed by the Pearson Chi-square or Fisher exact tests for categorical variables and the Mann–Whitney U or the Kruskal–Wallis test for continuous variables. Potential co-variates associated with SARS-CoV-2-infection were tested in uni-variable analyses and those with P < 0.20 are included in a muti-variable binary logistic regression analysis. P values < 0.05 were considered significant. Statistical analysis used SPSS statistical software version 25.0 (SPSS Inc., Chicago, IL, USA).
Results
Baseline co-variates
We sent electronic questionnaires to 1442 persons with CML registered in the Hubei and Henan Anti-Cancer Associations (Fig. 1). 1390 (96%) responded. We excluded questionnaires from 196 nonresidents. 21 lacking complete data were also excluded. Another 52 subjects had irregular response monitoring and/or were lost to follow-up. Baseline co-variates are displayed in Table 1. There were 658 males (59%). Median age was 43 years (Interquartile Range [IQR] 33–53 years); 125 (11%) were ≥ 60 years old. 397 (35%) had a college degree or higher educational qualification. 348 (31%) reported ≥ 1 co-morbidity. 714 (64%) reported having received a prior SARS-CoV-2 vaccination. In the context of CML 1103 (98%) were in chronic phase, 10 in accelerated phase and 8 in blast phase. 334 (30%) were receiving imatinib, 283 (25%) dasatinib, 249 (22%) nilotinib, 156 (14%), flumatinib, 21, olverembatinib and 7, ponatinib. 8 were receiving investigational TKIs. Median duration of TKI-therapy before SARS-CoV-2-infection was 5.2 years (IQR 2.5–8.8 years). In 20 the best response before infection was a complete haematologic response (CHR), 65 had a complete cytogenetic response (CCyR), 74, a major molecular response (MMR) and 899 (80%), a deep molecular response (DMR). 596 subjects (53%) received their 1st TKI, 392 (35%), their 2nd TKI and 133 (12%), their 3rd TKI. 221 (20%) were receiving a reduced TKIs dose and 63 were in therapy-free remission (TFR).
Fig. 1.
CONSORT flow diagram
Table 1.
Baseline co-variates
| N = 1121 | |
|---|---|
| Male n (%) | 658 (59) |
| Age (y; range) | 43 (5–90) |
| TKI-therapy duration (y; IQR) | 5.2 (2.5–8.8) |
| Education | |
| Primary school | 131 (12) |
| Middle school | 326 (29) |
| High school/secondary specialized school | 267 (24) |
| Junior college | 148 (13) |
| Undergraduate | 218 (19) |
| Postgraduate | 31 |
| Co-morbidity | |
| Hypertension | 60 |
| Diabetes | 26 |
| Cardio-vascular diseases | 38 |
| Thyroid disease | 42 |
| Hepatitis B | 28 |
| Gastrointestinal diseases | 57 |
| Kidney disease | 10 |
| Respiratory disease | 11 |
| Other cancer | 31 |
| Other | 45 |
| Vaccination | 714 (64) |
| TKI-therapy | |
| Branded imatinib | 127 (11) |
| Generic imatinib | 127 (11) |
| Branded dasatinib | 207 (18) |
| Generic dasatinib | 57 |
| Branded nilotinib | 226 (20) |
| Flumatinib | 249 (22) |
| Ponatinib | 156 (14) |
| Olverembatinib | 7 |
| Clinical trials | 21 |
| 8 | |
| Disease phase | |
| Chronic | 1103 (98) |
| Accelerated | 10 |
| Blast | 8 |
| Response | |
| CHR | 20 |
| CCYR | 65 |
| MMR | 74 |
| DMR | 899 (80) |
| TFR | 63 |
| Line of TKI | |
| 1st | 596 (53) |
| 2nd | 392 (35) |
| 3rd | 133 (12) |
| Reduced dose | 221 (20) |
TKI tyrosine kinase-inhibitor, CHR complete haematologic response, CCyR complete cytogenetic response, MMR major molecular response, DMR deep molecular response, TFR treatment-free remission
SARS-CoV-2-infection and COVID-19
834 (74%) were infected with SARS-CoV-2, an incidence lower than the official rates reported in Hubei (> 80%) and Henan provinces (89%). In 617 (55%) of cases infection was attributed to family aggregation (Table S1). The most common symptoms were fever (91%), cough (90%) and fatigue (82%). 42 SARS-CoV-2-infected subjects were asymptomatic (Table S2). Median symptom duration was 7 days (IQR 3–15 days). Most persons with COVID-19 self-quarantined and -treated with non-prescription drugs (Table S3).
During the epidemic frequencies of out-patient visits and molecular monitoring decreased in 534 subjects (48%). 104 (9%) self-decided to reduce their TKI dose and 23 decided to stop TKI-therapy. 26 subjects had an increase in BCR::ABL1 transcript concentrations when they had COVID-19.
COVID-19 severity
At the time of infection 743 subjects (89%) had mild, 46 moderate and 3, severe/critical disease according to the WHO classification.
Co-variates associated with risk of SARS-CoV-2-infection
Results of uni-variable analyses are displayed in Table 2. Co-variates significantly associated with risk of SARS-CoV-2-infection in multi-variable analyses age ≥ 65 years (Hazard Ratio [HR] = 1.74 [1.38, 2.33]; P = 0.05), higher education level (HR = 3.08 [1.0, 8.62]; P < 0.001), and imatinib therapy (HR = 1.53 [1.07, 2.38]; P = 0.02) (Table 2). There was no correlation between vaccination to SARS-CoV-2 and risk of infection.
Table 2.
Risk factors for SARS-CoV-2-infection
| Uni-variable HR (95% CI) | P value | Multi-variable HR (95% CI) | P value | |
|---|---|---|---|---|
| Age (y, < 65 y ref) | ||||
| ≥ 65 y | 1.64 (1.46, 2.78) | 0.04 | 1.74 (1.38, 2.33) | 0.05 |
| Sex (female ref) | ||||
| Male | 1.18 (0.90,1.54) | |||
| Duration TKI-therapy at infection | 1.0 (0.98,1.02) | 0.95 | ||
| Duration TKI-therapy at infection (< 5 y ref) | ||||
| ≥ 5 y | 1.03 (0.79, 1.35) | 0.81 | ||
| Education level (primary school, ref) | 0.002 | |||
| Middle school | 1.90 (1.24, 2.91) | 0.02 | 1.73 (1.11, 2.69) | 0.03 |
| High school/secondary specialized school | 1.98 (1.19, 3.29) | 0.01 | 1.66 (1.06, 2.62) | 0.02 |
| Junior college | 1.75 (1.13, 2.72) | 0.01 | 1.79 (1.06, 3.02) | 0.03 |
| Undergraduate | 3.33 (2.02, 5.49) | 0.003 | 3.0 (1.79, 5.01) | 0.01 |
| Postgraduate | 3.43 (1.24, 9.84) | < 0.001 | 3.08 (1.0, 8.62) | < 0.001 |
| Disease phase at infection (chronic phase, ref) | 0.42 | |||
| Accelerated | 3.11 (0.39, 24.63) | 0.28 | ||
| Blast | 0.58 (0.14, 2.42) | 0.45 | ||
| Response at infection (MMR, ref) | ||||
| < MMR | 1.13 (0.67,1.90) | 0.65 | ||
| Reduction of TKI dose (standard dose, ref) | 0.93 (0.66,1.30) | 0.66 | ||
| TKI line at infection (1st ref) | 0.01 | 0.04 | ||
| 2nd | 0.75(0.56,1.01) | 0.05 | 0.80 (0.59, 1.08) | 0.15 |
| 3rd | 0.57 (0.38, 0.85) | 0.01 | 0.59 (0.39, 0.91) | 0.02 |
| TKI at infection (Imatinib, ref) | 0.19 | 0.24 | ||
| 2nd generation | 0.75 (0.22, 2.57) | 0.65 | 0.82 (0.23, 2.90) | 0.62 |
| 3rd generationa | 0.69 (0.23, 2.09) | 0.52 | 0.69 (0.22, 2.12) | 0.26 |
| TFR | 1.50 (0.41, 5.52) | 0.54 | 1.40 (0.37, 5.24) | 0.62 |
TKI tyrosine kinase-inhibitor, TFR therapy-free remission
aPonatinib and olverembatinib
Hospitalization
Twenty-two subjects were hospitalized including 5 with mild disease, 14 with moderate disease and 3 with severe/critical disease at admission. Five received respiratory assistance and three were admitted to an intensive care unit (ICU). At the time of the survey two persons remained hospitalized because of adverse events to TKIs, including thrombocytopenia (N = 1) and pulmonary hypertension (N = 1). One subject in accelerated phase died from COVID-19 (Table S4).
Co-variates associated with an increased risk of hospitalization in uni-variable analyses included age ≥ 65 years (HR = 1.61 [1.14, 2.67]; P = 0.01), ≥ 1 co-morbidity (HR = 3.20 [1.35, 7.55]; P = 0.01), blast phase (HR = 19.02 [3.60, 100.35]; P < 0.001), < MMR (HR = 4.84 [1.84, 12.73]; P < 0.001) and 3rd-line TKI therapy (HR = 5.34 [1.90, 15.0]; P < 0.001). Several of these co-variates are confounded but there were too few events for multi-variable analyses (Table 3).
Table 3.
Co-variates associated with risk of hospitalization
| Uni-variable HR (95% CI) | P value | |
|---|---|---|
| Age (y, ref < 65 y) | ||
| ≥ 65 y | 1.61 (1.14, 2.66) | 0.01 |
| Co-morbidity (ref none) | 3.20 (1.35, 7.55) | 0.01 |
| Disease phase at infection (Chronic, ref) | < 0.001 | |
| Accelerated | 6.34 (0.77, 52.56) | 0.01 |
| Blast | 19.02 (3.60, 100.35) | < 0.001 |
| Response at infection (MMR, ref) | ||
| < MMR | 4.84 (1.84,12.73) | < 0.001 |
| TKI line at infection (1st ref) | 0.003 | |
| 2nd | 1.30 (0.43, 3.89) | 0.64 |
| 3rd | 5.34 (1.90, 15.0) | < 0.001 |
See abbreviations Table 2
Discussion
Our data indicate a 74% infection rate with SARS-CoV-2 Omicron BA.5.2 in persons with CML in an epidemic in China. Most infections resulted in COVID-19; most cases are mild and deaths rare. We also identified co-variates associated with increased risk of SARS-CoV-2-infection, including age ≥ 65 years, higher education level and receiving imatinib rather than other TKIs. We were unable to identify co-variates associated with risk of developing COVID-19 because 96% of infected persons developed it or of hospitalization or death because of few events.
Previous studies reported persons with haematological cancers were at increased risk of SARS-CoV-2-infection and severe COVID-19. Several of these studies included persons with CML. (Başcı et al. 2020; Breccia et al. 2022) A survey of 530 persons with CML in Hubei province during the SARS-CoV-2 pandemic in 2020 reported a lower incidence in persons with CML compared with other haematological cancers (Li et al. 2020). Similar data are reported by others (Passamonti et al. 2020). However, these studies were done before the SARS-CoV-2 Omicron BA.5.2 variant emerged.
Although some associations we report are expected such as with age. It was surprising to find high rather than low education level was associated with an increased risk of developing COVID-19 in SARS-CoV-2-infected persons. More highly educated people are more likely to have access to medical care and to reported signs and symptoms of SARS-CoV-2-infection.
We were also surprised to find receiving imatinib rather than other TKIs was associated with an increase infection risk. Especially as several studies reported a protective effect of TKIs against SARS-CoV‑2-infection. However, there may be differences between TKIs. For example, dasatinib and nilotinib are more effective in vitro in blocking SARS-CoV-infection and/or modulating effects of cytokine release syndrome (CRS) compared with imatinib (Dyall et al. 2014; Banerjee et al. 2021).
Molecular epidemiological data from Hubei and Henan provinces indicate the epidemic we analyzed was caused by SARS-CoV-2 Omicron BA.5.2. Several reports indicate the Omicron variant is less infectious and causes less severe COVID-19 compared with other variants reflecting our observations in subjects with CML. (Lewnard et al. 2022; Menni et al. 2022).
Our study has limitations. First, there is the possibility of selection biases in subjects returning the questionnaire and in recall bias. Second, there are possible inaccuracies in data reporting such as those related to TKI-therapy and response in the Hubei or Henan Anti-Cancer Association registries. Third, we assume our subjects with SARS-CoV-2-infection had the Omicron BA.5.2 variant based on molecular epidemiological data from Hubei and Henan provinces but we did not test this directly. Lastly, cancellation of region-wide testing for SARS-CoV-2-infection during the epidemic in China may have resulted in our missing some asymptomatic subjects resulting in an under-estimated the infection rates.
In conclusion, we found most SARS-CoV-2 Omicron BA.5.2 infections in persons with CML result in mild COVID-19 with rare deaths.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
RPG acknowledges support from the National Institute of Health Research (NIHR) Biomedical Research Centre and the Ministry of Science and Technology of China (84000-51200002).
Author contributions
M-WL, L-YZ, and QB-L designed the study and provided subjects. FC, HX, SY-C, JQ, and HG collected and analyzed the data. M-WL, L-YZ, RPG, SY-C, JQ, HG and FC prepared the typescript. All authors approved the final typescript, take responsibility, for the content and agreed to submit for publication.
Funding
This study is funded by National Institute of Health Research (NIHR) Biomedical Research Centre and the Ministry of Science and Technology of China (84000-51200002).
Data availability
All data are included in the typescript. Inquiries should be directed to the corresponding authors.
Declarations
Conflict of interest
RPG is a consultant to Antengene Biotech LLC, Ascentage Pharma Group and NexImmune Inc.; Medical Director, FFF Enterprises Inc.; Board of Directors: Russian Foundation for Cancer Research Support; and Scientific Advisory Boards, Nanexa AB and StemRad Ltd.
Ethics statement
The study was approved by the Institutional Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology (Wuhan, China) ([2023] 0065). The requirement for written informed consent was waived.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Fang Cheng and Hang Xiang have contributed equally to this work.
Contributor Information
Qiubai Li, Email: qiubaili@hust.edu.cn.
Yanli Zhang, Email: 13203729690@163.com.
Weiming Li, Email: lee937@126.com.
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Associated Data
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Supplementary Materials
Data Availability Statement
All data are included in the typescript. Inquiries should be directed to the corresponding authors.