Inactivated vaccine dosage and serum IgG levels correlate with persistent COVID-19 infections in hematologic malignancy patients during the Omicron Surge in China

Abstract

Purpose

The essence of this scholarly work was to carefully outline the key factors intensifying the virulence and protracted contagion of COVID-19, particularly among individuals afflicted with hematologic malignancies (HM), in an epoch predominantly governed by the Omicron variant.

Methods

Adults with HM diagnosed with COVID-19 from November 2022 to February 2023 were monitored in this retrospective study. Patient blood samples yielded biochemical data, and COVID-19 was confirmed through RNA or antigen testing. The factors affecting severity and infection duration were examined using both univariate and multivariate logistic regression analyses. For calculating the overall survival probabilities, the Kaplan–Meier product limit approach was employed.

Results

In the examined cohort, 133 individuals diagnosed with HM and concomitantly infected with COVID-19 were scrutinized. Of the participants, 29.3% (39 patients) were classified as Severe/Critical, while the other 70.7% (94 patients) were categorized as Non-severe. A significant difference was observed in vaccination status: 61.7% of patients in the Non-severe group had received at least a two-dose vaccine regimen, whereas 61.5% of the Severe/Critical group had either minimal or only one dose of vaccination. The data analysis revealed that elevated C-reactive protein levels (≥ 100 mg/L) significantly raised the risk of severe/critical conditions in HM patients with COVID-19, as determined by advanced multivariate logistic regression. The odds ratio was 3.415 with a 95% confidence interval of 1.294–9.012 (p = 0.013). Patients who continued to have positive nucleic acid tests and ongoing symptoms beyond 30 days were categorized as having a persistent infection, whereas those who achieved infection control within this timeframe were categorized as having infection recovery. Of the HM cohort, 11 did not survive beyond 30 days after diagnosis. The results from a competing risk model revealed that increased interleukin-6 levels (HR: 2.626, 95% CI: 1.361–5.075; p = 0.004) was significantly associated with persistent infection. Conversely, receiving more than two vaccine doses (HR: 0.366, 95% CI: 0.158–0.846; p = 0.019), and having high IgG levels (≥ 1000 mg/dl) (HR: 0.364, 95% CI: 0.167–0.791; p = 0.011), were associated with infection recovery. There was a notable disparity in survival rates between patients with persistent infections and infection recovery, with those in the non-persistent group demonstrating superior survival outcomes (P < 0.001).

Conclusions

In conclusion, the study determined that HM patients with COVID-19 and increased C-reactive protein levels had a higher likelihood of severe health outcomes. Persistent infection tended to be more prevalent in those with vaccine dosages (< 2 doses), lower IgG levels, and higher interleukin-6 levels.

Background

In March 2020, the World Health Organization declared COVID-19, caused by the SARS-CoV-2 virus, a global pandemic. Following the relaxation of quarantine measures in China in November 2022, a new development arose with the emergence of the Omicron variant. Studies suggest that individuals with myeloproliferative neoplasms, chronic lymphocytic leukemia, and lymphoma have a lower mortality risk in cases of Omicron infections [1–5]. Conversely, studies indicate that COVID-19 breakthrough infections in HM patients remain linked to high mortality risks, influenced by factors such as the patient’s health status and treatment regimen [6–11]. Chang A et al., in their study, observed negligible neutralization against Omicron in patients with B-cell malignancies treated with AZD7442 [12]. Moreover, HM patients receiving B-cell depletion therapy showed an extended average COVID-19 clearance time of 55.5 days [13]. This data implies that COVID-19 might manifest more severely and persistently in certain HM patients.

Kevin Boyd and colleagues showed that inactivated vaccines effectively protect against severe COVID-19 in the general population [14]. Recent studies indicate reduced immune responses to COVID-19 vaccines in individuals with chronic lymphocytic leukemia and multiple myeloma. Yair Herishanu and colleagues identified a heightened susceptibility to acute COVID-19 infections in patients with HM compared to those with solid neoplasms or healthy individuals. This vulnerability may be attributed to the immunocompromising nature of their diseases or treatments. Patients with HM are increasingly recognized as a high-risk group, with elevated chances of experiencing severe consequences from COVID-19, as detailed in studies [15–17]. Amidst the global challenge posed by the highly transmissible and mutationally adept Omicron variant, it is crucial to investigate the factors contributing to the severity and persistence of COVID-19 in patients with HM.

This study aims to clarify the inter-relations between the dosage of inactivated vaccines, serum IgG concentrations, and the duration of COVID-19 infections in individuals afflicted with HM. By examining these interconnections, the study aims to uncover key factors that influence the severity and duration of COVID-19 within this vulnerable cohort. Such findings are crucial for guiding targeted medical interventions and optimizing vaccination strategies, with the ultimate goal of mitigating the impact of the Omicron variant on these highly vulnerable individuals.

Patients and methods

Patients

The Ethical Oversight Committee of the First Affiliated Hospital, Zhejiang University School of Medicine, approved this study. It incorporated subjects hospitalized with HM, as delineated by the World Health Organization, manifesting symptomatic presentation and laboratory-validated COVID-19 contagion from November 2022 to February 2023. The COVID-19 diagnosis conformed to the Sino guidelines for the diagnosis and treatment of the disease, encompassing parameters for severe morbidity (such as SpO2 < 94% in an ambient atmosphere at the sea level, PaO2/FiO2 ratio < 300 mmHg, respiratory frequency > 30 respirations/min, or pulmonary infiltrates > 50%) and critical pathology (inclusive of respiratory insufficiency, septic shock, and/or multi-organ dysfunction syndrome) [18]. In this study, a prolonged infection was defined as a COVID-19 infection lasting more than 30 days.

Methods

Treatment principles

Minimizing exposure to COVID-19 for both patients and staff, while still providing optimal care, is a critical focus. This can be accomplished by implementing less intensive treatment methods, reducing the frequency of patient visits, and fostering collaboration with local healthcare facilities. Prior to initiating any anti-tumor treatments, all HM patients were required to undergo COVID-19 screening, including a basic, contrast-free chest CT scan. For HM patients in the initial stages or with active disease, as well as those with controlled or stable disease, all anti-tumor treatments were paused for a minimum of 14 days following a COVID-19 diagnosis. During this hiatus, antiviral and supportive treatments were administered. For patients with HM experiencing disease progression, physicians were responsible for identifying the most appropriate treatments to reduce the tumor burden. For those in remission or with controlled and stable disease, it was advised to postpone consolidation therapies when feasible. Treatment plans, including antiviral therapy, symptomatic relief, and supportive care, were customized based on the severity of the COVID-19 infection.

Follow-up

The terminal surveillance of this investigation concluded in October 2023, culminating in a median observational tenure of 303 days, with a 95% confidence interval spanning from 301 to 305 days. The aggregate survival duration was ascertained from the juncture of COVID-19 diagnosis to either the event of demise from any etiology or the epoch of the ultimate follow-up. All datasets were censored as of the concluding follow-up date.

Statistical analysis

The Kolmogorov–Smirnov (K–S) test was employed to assess the distribution of continuous variables. For data that did not conform to a Gaussian (normal) distribution, descriptive statistics were reported using the median and interquartile range (IQR). In contrast, categorical variables were presented as percentages. The analysis of categorical variables utilized the χ2 test or Fisher’s exact test for small sample sizes. Student’s t-test was applied to analyze continuous variables. Univariate logistic regression was used to identify relevant factors, while multivariate logistic regression was employed to identify independent predictors of outcomes. Survival curves were generated using Kaplan–Meier analysis and compared using the log-rank test. A competing risk model was used to identify independent predictors of persistent infection. All statistical analyses were conducted using SPSS version 22.0 and R version 4.3.2. Statistical significance was defined as a P-value below 0.05. Importantly, all analyses were two-tailed to ensure a complete evaluation.

Results

Patient characteristics

The majority of the cohort were men, comprising 75 individuals, which constituted 56.4% of the study population (Table 1). The median age of the patients was 61 years, with an IQR of 52 to 68 years. The majority of patients were diagnosed with B cell lymphoma/leukemia, representing 50.4% of the group (n = 67), followed by 21.0% (n = 28) with acute myeloid leukemia. In terms of comorbidities, 54.1% of the patients (n = 72) had at least one additional health condition. This encompassed hypertension in 27 patients, pulmonary disease in 22, diabetes in 17, and obesity in 13 patients. At the time of contracting COVID-19, 53.4% of the patients (n = 71) had their malignant tumors in a controlled or stable condition, while 46.4% (n = 62) were experiencing onset/active disease states. Regarding treatment history before contracting COVID-19, 77.4% of the patients (n = 103) had undergone some form of therapy. The administered treatments varied and included anti-CD20 combinations in 38 patients, bcl-2 combinations in 18, conventional chemotherapy in 12, and combinations of immunomodulating agents in 7 patients (Fig. 1). In this group of 133 patients, 39 cases (29.3%) were categorized as severe. Among these severe cases, a significant portion, 24 patients (61.5%), either had not been vaccinated or had received only one dose of the vaccine. In contrast, the remaining 94 patients (70.7%) exhibited mild or moderate symptoms. Notably, within this latter group, the majority of 58 patients (61.7%) had received at least two doses of the vaccine (Fig. 1).

Table 1.

Patient characteristics

	N (%)
Total number of patients	133 (100%)
Median age at the time of diagnosis (IQR: years)	61 (52–68)
Female / Male	58/75
Median BMI (IQR)	22.5 (20.5–24.8)
Hematologic malignancy
Acute myeloid leukemia	28 (21.0%)
MDS/MPN	15 (11.3%)
B cell lymphoma/leukemia	67 (50.4%)
T cell lymphoma	9 (6.8%)
Others	14 (10.5%)
Comorbidities before COVID-19
No comorbidities	59 (44.4%)
One comorbidity	37 (27.8%)
Two or more comorbidities	35 (26.3%)
Malignancy status at diagnosis
Controlled/stable malignancy	71 (53.4%)
Onset/active malignancy	62 (46.6%)
Time from last treatment to COVID diagnosis
Untreated	30 (22.6%)
In the last month	59 (44.4%)
In the last 3 months />3 months	44 (33.1%)
Severity of COVID-19 infections
Mild	31 (23.3%)
Moderate	63 (47.4%)
Severe/critical	39 (29.3%)
Number of vaccine doses
Unvaccinated/ One dose	60 (45.1%)
Two doses	27 (20.3%)
Three/four doses	46 (34.6%)
Neutrophils (IQR)	2.5 (1.1–4.1)
Lymphocytes (IQR)	0.6 (0.3–1.1)
COVID-19 treatment
Antivirus ± corticosteroids ± Immunoglobulin ± JAK inhibitor	55 (41.4%)
Corticosteroids ± Immunoglobulin ± JAK inhibitor	47 (35.3%)
Others (Immunoglobulin ± JAK inhibitor, plasma)	31 (23.3%)

IQR = Inter-Quartile Range; BMI = Body Mass Index; MDS/MPN = Myelodysplastic syndromes/Myeloproliferative neoplasms; Others = Plasma cell disorders, Castleman disease, NK lymphoma, HD, EBV-LPD; JAK = Janus Kinase;

Fig. 1.

The pie chart presenting the last anti-neoplastic treatment for hematological malignancies before COVID-19 diagnosis; The bar graph presenting the distribution of vaccine doses for different severity levels of COVID-19 infections

Univariate and multivariate logistic regression analyses for severe/critical COVID-19 infections in HM patients

Significant differences were noted between patients with severe/critical infections (n = 39) and those with non-severe infections (n = 94) in terms of median age, duration from last treatment to COVID diagnosis, number of vaccine doses received, median lymphocyte count, and C-reactive protein levels. Thirty-nine patients (29.3%) experienced severe/critical infections, with a median age (IQR) of 65 (57 − 71) years. Among them, 24 individuals (61.5%) had not received or had only received a single dose of the vaccine, and 22 individuals (56.4%) had undergone tumor treatment in the last one month preceding the diagnosis of COVID-19. Concurrently, the C-response protein level (mg/L) in patients with severe infections was 58 (14–149) and the lymphocyte count (×10⁹/L) was 0.5 (0.1–1.0). A total of 94 patients (70.7%) were classified as non-severe, with a median age (IQR) of 60 (49–67) years. Among them, 58 individuals (61.7%) had received at least two doses of the vaccine, and 36 individuals (38.3%) had undergone tumor treatment in the last one month preceding the diagnosis of COVID-19. In contrast, the C-response protein level (mg/L) in patients with non-severe infections was 32 (10–66), and the lymphocyte count (×10⁹/L) was 0.7 (0.4–1.2) (Table 2).

Table 2.

Patient characteristics between those with severe/critical and non-severe infections

	Severe/critical (n = 39)	Non-severe (n = 94)	p-value
Sex, Male/Female	18/21	57/37	0.578
Median age (IQR; years)	65 (57–71)	60 (49–67)	0.032*
Median BMI (IQR)	22.6 (20.7–24.3)	22.5 (20.4–25.0)	0.959
Disease classification			0.983
Acute myeloid leukemia	8	20
B cell lymphoma/leukemia (indolent/aggressive)	19	48
Malignancy status at COVID-19 diagnosis			0.282
Onset/Active	21	41
Controlled/Stable	18	53
Time from last treatment to COVID diagnosis			0.040*
Untreated	10	20
In the last one month	22	36
In the last 3 months or>3 months	7	38
Number of vaccine doses (< 2 / ≥2)	24/15	36/58	0.014*
Neutrophil count (IQR; ×109/L)	2.8 (1.2–5.4)	2.1 (1.1–3.8)	0.230
Lymphocyte count (IQR; ×109/L))	0.5 (0.1–1.0)	0.7 (0.4–1.2)	0.037*
Platelet count (IQR; g/L)	87 (33–128)	105 (48–174)	0.155
IgG level (mg/dl)	1205 (867–1580)	1010 (650–1370)	0.060
C-response protein (mg/L)	58 (14–149)	32 (10–66)	0.030*
Ferritin (ng/ml)	1396 (523–2662)	980 (306–2240)	0.080
IL-6 level (pg/ml)	14.7 (8.1–54.8)	11 (5.2–30)	0.118
Interleukin-10 level (pg/ml)	5.9 (4.7–12.6)	4.9 (3.2–9.6)	0.056

IQR = Inter-Quartile Range; BMI = Body Mass Index; IgG = Immunoglobulin G; IL-6 = Interleukin-6; *p<0.05

Univariate analysis revealed that severe/critical infections correlated with age at diagnosis (>50 years) (p = 0.046), vaccine doses (< 2 doses) (p = 0.016), lymphocyte count (≤ 0.2 × 10⁹/L) (p = 0.017), and C-reactive protein levels (≥ 100 mg/L) (p = 0.001). After adjusting for these factors, higher C-reactive protein levels (≥ 100 mg/L) remained significantly associated with severe/critical infections (odds ratio [OR]: 3.415, 95% confidence interval [CI]: 1.294–9.012; p = 0.013) (Table 3).

Table 3.

Univariable and multivariable analyses of factors associated with severe/critical COVID-19 infections in patients

Variables	Univariable analysis		Multivariable analysis
	odds ratio (95%CI)	p-value	odds ratio (95%CI)	p-value
Age at diagnosis (>50 years)	3.170 (1.023–9.825)	0.046	2.161 (0.632–7.391)	0.219
vaccines dose (≥ 2 doses)	0.388 (0.180–0.836)	0.016	0.503 (0.211–1.197)	0.120
Lymphocytes (>0.2 × 109/L)	0.329 (0.132–0.819)	0.017	0.575 (0.207–1.602)	0.290
C-response protein (≥ 100 mg/L)	4.587 (1.842–11.418)	0.001	3.415 (1.294–9.012)	0.013*

CI = confidence interval; *p<0.05

Competing risk model for HM patients with COVID-19 persistent infection

Of the adult HM patients diagnosed with COVID-19, 11 did not survive beyond 30 days after diagnosis. A total of 47 patients had persistent infections, as indicated by positive nucleic acid tests and ongoing symptoms lasting more than 30 days. In contrast, 75 patients recovered from the infection within 30 days. Significant differences were noted between patients with persistent infections (n = 47) and those with infection recovery (n = 75) (Table 4) in terms of disease classification, duration from last treatment to COVID diagnosis, number of vaccine doses received, median neutrophil count, serum immunoglobulin G (IgG) level, and Interleukin-6 level. Patients with persistent infection had a median age (IQR) of 64 (52–71) years. The majority of the patients had B cell lymphoma/leukemia (n = 27, 57.5%). Among them, 26 individuals (55.3%) had not received or had only received a single dose of the vaccine, and 19 individuals (40.4%) had undergone tumor treatment in the last one month preceding the diagnosis of COVID-19. Concurrently, the neutrophil count (×10⁹/L) in patients with persistent infection was 2.8 (1.2–4.5), IgG level (mg/dl) was 833 (828–1070), and Interleukin-6 level (pg/ml) was 15.2 (7.4–47). Patients with infection recovery had a median age (IQR) of 60 (50–66) years. The majority of the patients had B cell lymphoma/leukemia (n = 33, 44%) Among these, 51 individuals (68%) had received at least two doses of the vaccine, and 34 individuals (45.3%) had undergone tumor treatment in the last one month preceding the diagnosis of COVID-19. In contrast, the neutrophil count (×10⁹/L) in patients with infection recovery was 1.7 (0.6–3.4), IgG level (mg/dl) was 1188 (637–1421), and Interleukin-6 level (pg/ml) was 8.2 (4.7–28.8).

Table 4.

Clinical characteristics between 47 patients with persistent infections and 75 patients with infection recovery

	Persistent infections (n = 47)	Infection recovery (n = 75)	p-value
Sex, Male/Female	23/24	44/31	0.293
Median age (IQR; years)	64 (52–71)	60 (50–66)	0.094
Median BMI (IQR)	22.1(20.8–24.5)	23(20.7–25.6)	0.447
Disease classification			0.023*
Acute myeloid leukemia	5	21
B cell lymphoma/leukemia (indolent/aggressive)	27	33
Malignancy status at COVID-19 diagnosis			0.270
Onset/Active	19	38
Controlled/Stable	28	37
Time from last treatment to COVID diagnosis			0.026*
Untreated	5	20
In the last one month	19	34
In the last 3 months or>3 months	23	21
Number of vaccine doses (< 2 / ≥2)	26/21	24/51	0.011*
Neutrophil count (IQR; ×109/L)	2.8 (1.2–4.5)	1.7 (0.6–3.4)	0.043*
Lymphocyte count (IQR; ×109/L))	0.5 (0.3–1.1)	0.7 (0.4–1.2)	0.247
Platelet count (IQR; g/L)	110 (44–174)	113 (42–174)	0.689
IgG level (mg/dl)	833 (828–1070)	1188 (637–1421)	0.006*
C-response protein (mg/L)	38 (13–77)	26 (7–83)	0.319
Ferritin (ng/ml)	982 (275–2017)	1064 (359–2339)	0.471
IL-6 level (pg/ml)	15.2 (7.4–47)	8.2 (4.7–28.8)	0.042*
Interleukin-10 level (pg/ml)	5.7 (3.9–9.6)	4.7 (3.2–9.8)	0.434

Persistent infection is defined as a COVID-19 infection characterized by positive nucleic acid tests or ongoing symptoms lasting more than 30 days; infection recovery is defined as a controlled infection within 30 days; IQR = Inter-Quartile Range; BMI = Body Mass Index; IgG = Immunoglobulin G; IL-6 = Interleukin-6; *p<0.05

We conducted a competing risk model that considered 30-day mortality as a competing endpoint to identify the factors influencing persistent infection. Univariate analysis indicated a higher likelihood of persistent infection was associated with factors such as age over 65 (p = 0.024), less than two vaccine doses (p < 0.001), lower IgG levels (< 1000 mg/dl, p < 0.001), and heightened Interleukin-6 levels (≥ 12 pg/ml, p = 0.005). After controlling for these variables, increased interleukin-6 levels (HR: 2.626, 95% CI: 1.361–5.075; p = 0.004) was significantly associated with persistent infection. Conversely, receiving more than two vaccine doses (HR: 0.366, 95% CI: 0.158–0.846; p = 0.019), and having high IgG levels (≥ 1000 mg/dl) (HR: 0.364, 95% CI: 0.167–0.791; p = 0.011), were associated with infection recovery (Table 5).

Table 5.

A competing risk model to predict the factors associated with persistent infection

Variables	Univariable analysis		Multivariable analysis
	Hazard ratio (95%CI)	p value	Hazard ratio (95%CI)	p value
Age at COVID diagnosis (≥ 65 years)	1.770(1.079–2.890)	0.024	1.161(0.565–2.381)	0.680
Vaccines dose (≥ 2 doses)	0.429(0.266–0.690)	<0.001*	0.366(0.158–0.846)	0.019*
IgG level (≥ 1000 mg/dl)	0.378(0.221–0.645)	<0.001*	0.364(0.167–0.791)	0.011*
IL-6 level (≥ 12pg/ml)	2.460(1.316–4.587)	0.005*	2.626(1.361–5.075)	0.004*

The outcome event is persistent infection lasting more than 30 days, while the competing event is the 30-day mortality. CI = confidence interval; IgG = immunoglobulin G; IL-6 = Interleukin-6; *p<0.05

Survival analysis

Throughout the study cohort, the median follow-up duration was 303 days, with a 95% confidence interval (CI) ranging from 301 to 305 days. During this period, 5 patients were lost to follow-up, including 2 from the positive group and 3 from the negative group. In the study, the overall mortality rate was 30.8%, which equated to 41 patients. Specifically, the mortality rate at 30 days was 9.8%, accounting for 13 patients. The primary causes of death among these patients were infections, severe bleeding events, and multiple organ failure. A notable finding was the significant difference in survival rates between the cohorts with persistent infection and infection recovery (P < 0.001). The data revealed that individuals with infection recovery exhibited a higher survival rate compared to those with persist infection, highlighting the substantial impact of the duration of infections on patient outcomes (Fig. 2).

Fig. 2.

Kaplan-Meier survival curves showing the OS of patients with non-persistent or persistent COVID-19 infections

Discussion

The COVID-19 pandemic, initiated by the severe respiratory pathogen SARS-CoV-2, poses a significant global health threat. Among the various comorbid conditions identified as predisposing individuals to severe forms of COVID-19, neoplastic disorders are particularly concerning [19]. This emphasizes the critical need for extensive research into the factors that heighten the susceptibility of these patients to severe COVID-19.

During the period when the Delta variant was predominant, elevated levels of C-reactive protein were noted as key laboratory markers indicative of COVID-19 severity [20–22]. Moreover, in the subsequent phase dominated by the Omicron variant, C-reactive protein levels were pinpointed as an independent prognostic factor, as indicated [23–25]. In support of these findings, our analysis indicates that individuals with hematologic malignancies infected with the Omicron variant and high levels of C-reactive protein are 3.415 times more likely to experience severe disease (OR: 3.415, 95% CI: 1.294–9.012; p = 0.013). This correlation might be attributed to ongoing inflammation and a compromised immune response highlighting the crucial role of inflammation in the severity of COVID-19 among this vulnerable patient group [26]. Sepsis triggers hyperactivity of immune cells, followed by immune paralysis days later, which is associated with poor patient outcomes [27]. Qiurong Ruan carried out a study on 150 confirmed cases of new coronavirus pneumonia in Wuhan, China [28]. The results of the study highlight the significance of elevated inflammatory markers in the bloodstream as predictors of potentially fatal outcomes in COVID-19 cases. It was discernibly observed that the concentrations of CRP and IL-6 were markedly elevated in patients who were discharged as opposed to those who succumbed (P < 0.001). This suggests the potential utility of these biomarkers in prognosticating the severity of the ailment.

Further, the study suggests a possible association between COVID-19 mortality and the development of a virally induced “cytokine storm syndrome” or fulminant myocarditis. Consistent with these findings, our study also identified high levels of interleukin-6 (≥ 12pg/ml) as a significant independent factor influencing persistent infection in adult patients with HM diagnosed with COVID-19 (HR: 2.626, 95% CI: 1.361–5.075; p = 0.004) by the analysis of the competing risk model. The findings of this study align with those of Qiurong Ruan et al. Regarding Tocilizumab, an IL-6 receptor antagonist, these findings have prompted the approval of a multicenter randomized controlled trial in China to investigate its effects on patients with COVID-19 who exhibit elevated levels of this cytokine. Another possible strategy for treating COVID-19, particularly in instances of hyperinflammation, is to inhibit Janus kinase (JAK), which affects inflammatory responses and viral entry into cells. This highlights the potential benefit of immunosuppression in managing the hyperinflammatory condition associated with severe COVID-19 infections.

Immunoglobulin plays a crucial role in the immune system by combating bacteria and viruses. The serum IgG level could be associated with disease classification, treatment, and patient age. In some HM patients, low levels of IgG in the serum could lead to antibody immunodeficiency, impairing viral clearance. Haggenburg S et al. demonstrated that patients receiving or shortly after anti-CD20 therapy experienced B cell impairment, leading to a diminished or unresponsive immune response to the third mRNA vaccination [29]. In a phase II study conducted by Raman RS et al., intravenous immunoglobulin was found to shorten the median time for the virus to become undetectable [30]. Our study also revealed that a higher IgG level (≥ 1000 mg/dl) was associated with infection recovery within 30 days. Conducting a long-term longitudinal study is essential to comprehensively understand the dynamic relationship between inactivated vaccine dosage, serum IgG levels, and the duration of COVID-19 infections. This will aid in capturing trends and identifying influencing factors that evolve over time.

The accumulating body of evidence strongly supports widespread immunization of oncology patients as a critical strategy to reduce COVID-19-related morbidity and mortality [31–34]. Prior to the emergence of the Omicron variant, research by Chien et al. found that vaccination (≥ 2 doses) in HM patients significantly reduced hospitalization risk compared to those who were unvaccinated [35]. Azar JH et al. observed that B cell-targeting therapies primarily impact the production of new antibodies rather than affecting existing ones, emphasizing the importance of mRNA vaccination before initiating cancer therapy [36]. Following anti-CD20 therapy (within a year before vaccination), the count of circulating B cells was a crucial predictor of vaccine response [37]. The efficacy of vaccines is also associated with the number of doses received [29, 38, 39]. Currently, inactivated vaccines are predominantly authorized for use in China. A study by Yu et al. indicated that a booster dose of an inactivated vaccine could enhance protective immunity [40]. Consistent with these findings, our study also found that severe COVID-19 cases among HM patients were more likely to have received fewer vaccine doses, whereas non-severe cases were more likely to have received more than two doses. Moreover, receiving ≥ 2 doses of an inactivated vaccine emerged as an independent protective factor against the Omicron variant.

Our analyses have several limitations. First, the relatively small sample population may introduce information bias and affect the accuracy of the results. Second, reliance on existing retrospective data could lead to incomplete or inaccurate findings, resulting in a less comprehensive assessment. These limitations have prompted us to consider conducting a larger, prospective study to further investigate these results.

Conclusion

In conclusion, this study highlights C-reactive protein levels as a critical factor influencing the severity of COVID-19 infections in patients with HM. Additionally, the effective clearance of the Omicron variant in these patients was associated with receiving ≥ 2 doses of inactivated vaccines and higher levels of IgG and lower levels of IL-6. The inactivated vaccine appears to enhance viral clearance. These insights could play a crucial role in shaping COVID-19 interventions for adult patients with HM, potentially improving their prognosis.

Author contributions

H.T. and L.Y. designed the study. L.Y. and Y.Y wrote the manuscript. L.Y. and X.Z. analyzed and arranged the data. X.Z., L.W., L.Z., X.L., Y.Z., X.Z., X.Z., Y.R., L.M., G.X., C.Y., H.W., D.Z., M.Y., X.Y. J.W., W.Y., J.Q., Y.L., W.X. J.H., H.M., and J.J. provided patient samples and data. H.T. guided the project design and article modification. We sincerely thank the sample donors and clinical investigators who participated in this study.

Funding

This work was supported by The National Natural Science Foundation of China grants (82270146).

Data availability

There was no data sharing plan set out at the start of this study. All data and materials are available from the corresponding author (tonghongyan@zju.edu.cn).

Declarations

Ethics approval and consent to participate

Ethical approval for the present study was obtained from the ethics committee of the First Affiliated Hospital, Zhejiang University School of Medicine (IIT20231213A), in accordance with the Second Declaration of Helsinki. All the interviewed people were informed about this survey, and a written. Informed consent to participate was obtained from all of the participants in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.