COVID-19 in multiple myeloma patients: frequencies and risk factors for hospitalization, ventilatory support, intensive care admission and mortality –cooperative registry from the Grupo Brasileiro de Mieloma Multiplo (GBRAM) (2024)

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COVID-19 in multiple myeloma patients: frequencies and risk factors for hospitalization, ventilatory support, intensive care admission and mortality –cooperative registry from the Grupo Brasileiro de Mieloma Multiplo (GBRAM) (1)

Hematology, Transfusion and Cell Therapy

Hematol Transfus Cell Ther. 2024 Apr-Jun; 46(2): 153–160.

Published online 2023 Sep 13. doi:10.1016/j.htct.2023.08.002

PMCID: PMC11150487

PMID: 37718131

Marcia Garnica,a,b, Edvan De Queiroz Crusoe,c Glaciano Ribeiro,d Rosane Bittencourt,e Roberto José Pessoa Magalhães,a Karla Richter Zanella,f Abrahão Elias Hallack Neto,g Juliana Souza Lima,h Caroline Bonamin Solo,i Emmanuella Graciott Souza,d Andre Magalhaes Fernandes,j Angelo Maiolino,a,k and Vania Hungrial,m

Author information Article notes Copyright and License information PMC Disclaimer

Abstract

Introduction

This study evaluated outcomes and risk factors for COVID-19 in 91 Brazilian multiple myeloma (MM) patients between April 2020 and January 2022.

Results

Of the 91 MM patients diagnosed with COVID-19, 64% had comorbidities and 66% required hospitalization due to COVID-19, with 44% needing ventilatory support and 37% intensive care. Age (OR 2.02; 95%CI 1.02 – 7.7) and hypertension OR 4.5; 95%CI 1.3 – 15.5) were independently associated with hospitalization and certain MM therapies (corticosteroids and monoclonal drugs) were associated with ventilatory support (OR 4.3; 95%CI 1.3 – 14 and OR 5.7; 95%CI 1.8 – 18, respectively), while corticosteroids and immunomodulatory drugs were linked to ICU admission (OR 5.1; 95% CI 1.4 – 18 and OR 3.4; 95%CI 1.1 – 10, respectively). The overall mortality rate was 30%, with the highest rate observed in the ICU (73%). Additionally, the ECOG performance status was linked to increased mortality (OR 11.5; 95%CI 1.9 – 69). The MM treatment was delayed in 63% of patients who recovered from COVID-19.

Conclusions

The findings highlight the need for preventing COVID-19 and prioritizing vaccination among MM patients, as they have high rates of severe outcomes in the event of COVID-19. It is also essential to monitor the potential clinical impacts of COVID-19 on MM patients in the long-term. Given the limited resources available in treating MM patients in Brazil during the COVID-19 pandemic, outcomes might be worse in this population.

Keywords: Multiple myeloma, SARS-Cov 2, COVID-19, Mortality, Infection

Introduction

Multiple myeloma is characterized by severe immunosuppression, leaving patients at high risk of infections and of developing severe and life-threatening complications. Infection risk often relates to disease-related immunoparesis, age, comorbidities and systemic therapy.1, 2, 3 The COVID-19 pandemic has impacted oncological care, including delays in diagnosis and treatments, but, additionally, regarding several cases of COVID-19 infections in this high-risk population.4 For patients in treatment for multiple myeloma, the same was observed.5 The MM patients showed a higher risk for the SARS-CoV-2 infection and a higher excess mortality in 2020 (difference in excess mortality) than non-MM patients.6 The outcome can be even worse in Brazil, where the scenario is of restricted resources to treat MM patients and large numbers of COVID-19 cases and related deaths.

In this cooperative study, we aimed to assess risk factors and outcomes of COVID-19 in Brazilian patients with MM and describe the impact of the infection on the MM treatment.

Methods

This was a cooperative retrospective multicenter study performed nationally by the “Grupo Brasileiro de Mieloma” (GBRAM). Patients with multiple myeloma followed at the participating centers and diagnosed with COVID-19 (SARS-CoV 2 polymerase chain reaction (PCR)- positive test) from April 2020 to Jan. 2022 were included in this study. The study included cases managed in and out of the hospital reported by 12 centers in 8 different states, representing 4 of the 5 Brazilian regions.

This research was conducted following the Declaration of Helsinki and was approved by the Ethical Committee of each center under CAAE number 30907420.1.0000.5455.

The medical records of the patients were used to collect the following baseline characteristics: time from diagnosis to COVID-19 infection, age at COVID-19 event, ECOG performance status, comorbidities and myeloma International Staging System (ISS) at MM diagnosis. The current MM therapy and previous stem cell transplant data were also collected. 44

Regarding COVID infection, we collect data concerning symptoms of infection onset and COVID-19 vaccination status.

Clinical features and risk factors were analyzed with the severity of COVID-19 and the following outcomes: hospital admissions, intensive care unit (ICU) admission, ventilatory support, and death. MM treatment modification due to COVID-19 was also accessed.

Statistical analyses

Categorical and continuous numeric variables were explored using the chi-square or Fisher exact test, Wilcoxon rank-sum test, or Spearman correlation test; the results were expressed as frequencies and medians. Crude and adjusted odds ratios (OR) were estimated with logistic regression analysis for the outcomes. A p-value lower than 5% was considered significant. All analyses were performed with the IBM SPSS statistical package (SPSS Statistics for MAC, Version 27, IBM Corp).

Results

The characteristics of the 91 MM patients were reported in Table 1. There was 50% male with a median age of 62 (33 – 84) years and 30% ISS III at diagnosis. At least one comorbidity was present in 52 (64%) patients: most frequently hypertension and diabetes (52% and 23%). Twenty-eight (35%) patients had more than one comorbidity.

Table 1

Baseline patients characteristics.

n = 91
Age, median, years62 (33 – 84)
Age group, n (%), in 83
< 65y46 (55)
65 - 7527 (33)
> 7510 (12)
Unknown/not documented8
Gender, n (%) in 89
Male45 (51)
Female43 (49)
Unknown/not documented3
ISS stage (ISS), n (%), in 76
Stage I30 (39)
Stage II23 (30)
Stage III23 (30)
Unknown/not documented15
ECOG status, n (%), in 76
0 – 167 (88)
2 - 49 (12)
Unknown/not documented15
Comorbidities, n (%) in 81
None29 (36)
At least one52 (64)
More than one28 (35)
Unknown/not documented10
Hypertension42 (52)
Diabetes19 (23)
Cardiac Disease12 (15)
Renal Disease8 (10)
Pulmonary disease6 (7)
Obesity4 (5)
MM status at COVID, n (%) in 88
Remission (CR, VGPR, PR)65 (74)
Stable disease18 (20)
Progression5 (6)
Unknown/not documented3
Previous SCT, n (%) in 88
Yes35 (40)
No56 (64)
Unknown/not documented3
Lines of therapy before COVID, n (%) in 88
154 (61)
216 (7)
> 318 (20)
Unknown/not documented3
Current Treatment at COVID, n (%)
Corticosteroids57 (63)
Immunomodulatory drugs51 (55)
Proteasome inhibitors38 (42)
Monoclonals25 (27)
Alkylating agents19 (21)
COVID-19 vaccine status, n (%) in 89
Non-vaccinated in the event66 (74)
Vaccinated before COVID event23 (26)
Unknown/not documented2
COVID-19 clinical features
Clinical severity, n (%)
Mild31 (34)
Moderate-Severe26 (29)
Critical34 (37)
Symptoms at diagnosis
Fever55 (61)
High respiratory tract33 (37)
Low respiratory tract47 (52)
COVID Management
Hospitalization60 (66)
Ventilatory support40 (44)
Intensive care34 (37)
Outcomes, n (%) in 86
Recovered60 (70)
Death26 (30)
Ongoing/ Unknown/not documented5

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Note: percentages of valid cases.

During the COVID episode, 23 (26%) patients had an active or progressing disease, and 37% received at least two prior lines of treatment.

Corticosteroids were the class of MM therapy most frequent used (n=57, 63%), followed by immunomodulatory drugs (n=51, 55%) at the onset of COVID.

COVID-19 infections were classified as at least moderate in (n=60) 66%, and the event management required hospitalization in 60 (66%), ventilatory support in 40 (44%), and ICU admission in 34 (37%). As the cohort started in 2021, most events (74%) occurred in patients not exposed to COVID-19 vaccines.

Patients who required hospitalization were older and had more frequent comorbidities. (Table 2) Previous stem cell transplants were less frequent in patients who required hospitalization (30 vs. 55%; p=0.025) compared with controls. The frequency of treatment with immunomodulatory and monoclonals was more frequent in patients who required hospitalization (66 vs. 45%, p=0.07; and 37% vs. 13%, p=0.025) respectively. Ventilatory support was more frequent in older patients (> 75 years) (p=0.02); receiving corticosteroids (p=0.03), immunomodulatory (p=0.03), or monoclonal drugs (p=0.002). (Table 3) Admission in ICU was associated with age (p=0.003), MM treatment including corticosteroids (p=0.006), immunomodulatory (p=0.008), or monoclonal drugs (p=0.015). (Table 4)

Table 2

Characteristics of patients who required or not hospitalization for COVID care.

Hospitalized
n = 60
Non-Hospitalized
n = 31
p-value
Age group, n (%)0.008
< 65y24 (44)22 (76)
65 - 7520 (37)7 (24)
> 7510 (18)0
GenderNS
Male30 (51)15 (52)
Female29 (49)14 (48)
ISS stage (ISS), n (%)NS
Stage I18 (37.5)12 (43)
Stage II14 (29)9 (32)
Stage III16 (37)7 (25)
ECOG statusNS
0 – 140 (83)27 (96)
2 - 48 (17)1 (4)
Comorbidities0.010
None15 (26)14 (58)
At least one42 (74)10 (42)
More than one25 (44)3 (12.5)0.010
Hypertension35 (61)7 (29)0.014
Diabetes16 (28)3 (12)NS
Cardiac Disease10 (17.5)2 (8)NS
Renal Disease8 (14)0NS
Pulmonary disease5 (9)1 (4)NS
Obesity
MM status at COVIDNS
Remission (CR, VGPR, PR)41 (72)24 (77)
Stable disease12 (21)6 (19)
Progression4 (7)1 (3)
Previous SCT0.025
Yes18 (30)17 (55)
No42 (70)14 (45)
Lines of therapy before COVIDNS
136 (62)18 (60)
29 (15.5)7 (23)
> 313 (22)5 (17)
Current Treatment at COVID
Corticosteroids41 (71)16 (52)NS
Immunomodulatory drugs37 (66)14 (45)0.07
Proteasome inhibitors25 (44)13 (42)NS
Monoclonals21 (37)4 (13)0.025
Alkylating agents
COVID-19 vaccine status
Non-vaccinated in the event42 (72)24 (77)NS
Vaccinated before COVID event16 (28)7 (23)
Symptoms at diagnosis
Fever42 (71)13 (42)0.012
High respiratory tract23 (39)10 (32)NS
Low respiratory tract37 (63)10 (32)0.008

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Note: percentages and statistics including only valid cases; NS: not statistically significant.

Table 3

Characteristics of patients who required or not (Controls) ventilatory support for COVID care.

Ventilatory support
n = 40
Controls
n = 51
p-value
Age group, n (%)0.023
< 65y20 (56)26 (55)
65 - 758 (22)19 (40)
>758 (22)2 (4)
GenderNS
Male23 (59)22 (45)
Female16 (41)27 (55)
ISS stage (ISS), n (%)NS
Stage I14 (47)16 (35)
Stage II8 (27)15 (33)
Stage III8 (37)15 (33)
ECOG statusNS
0 – 126 (81)41 (93)
2 - 46 (19)3 (7)
ComorbiditiesNS
None12 (32)17 (39)
At least one25 (68)27 (61)
More than one16 (43)12 (27)0.16
Hypertension20 (54)22 (50)NS
Diabetes10 (27)9 (20)NS
Cardiac Disease8 (22)4 (9)NS
Renal Disease4 (11)4 (9)NS
Pulmonary disease4 (11)2 (4)NS
Obesity3 (8)1 (2)NS
MM status at COVIDNS
Remission (CR, VGPR, PR)32 (82)33 (67)
Stable disease5 (13)13 (26.5)
Progression2 (5)3 (6)
Previous SCTNS
Yes12 (30)23 (45)
No28 (70)28 (55)
Lines of therapy before COVIDNS
123 (60)31 (62)
26 (16)10 (20)
> 39 (24)9 (18)
Current Treatment at COVID
Corticosteroids30 (77)27 (54)0.028
Immunomodulatory drugs27 (73)24 (48)0.028
Proteasome inhibitors19 (50)19 (38)NS
Monoclonals18 (46)7 (14)0.002
Alkylating agents
COVID-19 vaccine status
Non-vaccinated in the event27 (69)39 (78)NS
Vaccinated before COVID event12 (31)11 (22)
Symptoms at diagnosis
Fever28 (72)27 (53)0.08
High respiratory tract19 (49)14 (37)0.048
Low respiratory tract23 (59)24 (47)NS

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Note: Percentages and statistics including only valid cases; NS: not statistically significant.

Table 4

Characteristics of patients who required (ICU) or not (Controls) Intensive Care for COVID care.

ICU
n = 34
Controls
n = 57
p-value
Age group, n (%)0.003
< 65y17 (57)29 (55)
65 - 755 (17)22 (41)
> 758 (27)2 (4)
GenderNS
Male18 (54)27 (49)
Female15 (46)28 (51)
ISS stage (ISS), n (%)NS
Stage I13 (52)17 (35)
Stage II6 (24)17 (33)
Stage III6 (24)17 (33)
ECOG statusNS
0 – 123 (82)44 (92)
2 - 45 (18)4 (8)
ComorbiditiesNS
None11 (34)18 (37)
At least one21 (66)31 (63)
More than one14 (44)14 (29)NS
Hypertension17 (53)25 (51)NS
Diabetes8 (25)11 (22)NS
Cardiac Disease6 (26)6 (12)NS
Renal Disease4 (12)4 (8)NS
Pulmonary disease2 (6)4 (8)NS
Obesity3 (9)1 (2)NS
MM status at COVIDNS
Remission (CR, VGPR, PR)27 (82)38 (69)
Stable disease4 (12)14 (25.5)
Progression2 (6)3 (5.5)
Previous SCTNS
Yes10 (29)25 (44)
No24 (71)32 (56)
Lines of therapy before COVIDNS
120 (61)34 (62)
25 (15)11 (20)
> 38 (24)10 (18)
Current Treatment at COVID
Corticosteroids26 (82)29 (52)0.006
Immunomodulatory drugs26 (73)25 (45)0.008
Proteasome inhibitors17 (51)21 (38)NS
Monoclonals15 (44)10 (18)0.015
Alkylating agents
COVID-19 vaccine status
Non-vaccinated in the event24 (73)42 (75)NS
Vaccinated before COVID event9 (27)14 (25)
Symptoms at diagnosis
Fever23 (70)32 (56)NS
High respiratory tract17 (51)16 (28)0.040
Low respiratory tract20 (61)27 (47)NS

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Note: Percentages and statistics including only valid cases; NS: not statistically significant.

By adjusted multivariate analysis, age and hypertension (p=0.05 and p=0.02), respectively, were independently associated with hospitalization; MM therapy, including corticosteroids and monoclonal drugs (p=0.02 and p<0.01), was related to ventilatory support; treatment with corticosteroids and immunomodulatory drugs (p=0.01 and p=0.03) were associated with ICU admission. (Table 6)

Table 6

Multivariate analysis of clinical outcomes.

HospitalizationVentilatory SupportICUDeath
Univariate p-valueMultivariate p-value (OR; 95%CI)Univariate (p-value)Multivariate p-value (OR; 95%CI)Univariate (p-value)Multivariate p-value (OR; 95%CI)Univariate (p-value)Multivariate p-value (OR; 95%CI)
Age group, n (%)0.0080.045 (2.02; 1.02 – 7.7)0.023NS0.003NS0.028NS
ECOG status---0.0050.008 (11.5; 1.9 – 69)
Hypertension0.0140.016 (4.5; 1.3 – 15.5)---
Previous SCT0.025NS---
Corticosteroids*0.0280.015 (4.3; 1.3 – 14)0.0060.011 (5.1; 1.4 – 18)0.015NS
Immunomodulatory drugs*0.07NS0.028NS0.0080.031 (3.4; 1.1 – 10)0.09NS
Monoclonals *0.025NS0.0020.003 (5.7; 1.8 – 18)0.015NS

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Myeloma treatment at COVID-19 event; ICU: intensive care unit; OR: odds ratio; 95%CI: 95% confidence interval; NS: not statistically significant.

The overall mortality was 30%. Mortality rates were 45%, 67%, and 73% in hospitalized, ventilatory support, and ICU patients. (Figure 1) By univariate analysis, age (p=0.028), ECOG performance status (p=0.005), and MM therapy, including corticosteroids (p=0.015), were associated with increased mortality. (Table 5) By multivariate model, only ECOG performance status (OR 11.5; 95% CI 1.9 – 69) remained associated with mortality. (Table 6)

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Figure 1

Mortality rates per supportive care requirement.

Table 5

Characteristics of deceased or recovered patients.

Deceased
n = 26
Recovered
n = 60
p-value
Age group, n (%)0.028
< 65y11 (52)32 (56)
65 - 754 (19)21 (37)
> 756 (27)4 (7)
GenderNS
Male13 (52)29 (50)
Female12 (48)29 (50)
ISS stage (ISS), n (%)NS
Stage I8 (42)21 (40)
Stage II6 (32)16 (30)
Stage III5 (26)16 (30)
ECOG status0.005
0 – 114 (70)30 (96)
2 - 46 (30)2 (4)
ComorbiditiesNS
None8 (35)19 (36)
At least one15 (65)34 (64)
More than one10 (43)16 (30)NS
Hypertension14 (61)26 (49)NS
Diabetes5 (22)13 (24)NS
Cardiac Disease4 (17)8 (15)NS
Renal Disease2 (9)5 (9)NS
Pulmonary disease2 (9)4 (7.5)NS
Obesity1 (4)2 (4)NS
MM status at COVIDNS
Remission (CR, VGPR, PR)21 (84)41 (71)
Stable disease3 (12)14 (24)
Progression1 (4)3 (5)
Previous SCTNS
Yes8 (31)26 (43)
No18 (69)34 (57)
Lines of therapy before COVIDNS
112 (50)37 (63)
24 (17)12 (20)
> 38 (33)10 (17)
Current Treatment at COVID
Corticosteroids21 (84)32 (54)0.015
Immunomodulatory drugs18 (72)28 (49)0.09
Proteasome inhibitors13 (54)22 (37)NS
Monoclonals9 (36)14 (24)NS
Alkylating agents
COVID-19 vaccine status
Non-vaccinated in the event20 (80)45 (76)NS
Vaccinated before COVID event5 (20)14 (24)
Symptoms at diagnosis
Fever16 (64)36 (60)NS
High respiratory tract11 (44)19 (32)NS
Low respiratory tract16 (64)28 (47)NS

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Note: Percentages and statistics including only valid cases; NS: not statistically significant.

Regarding the 60 patients who recovered from COVID, 38 (63%) had the current MM treatment delayed. Patients who did not require hospitalization had a delay in MM treatment in 55% of cases. Those who recovered after hospitalization, ventilatory support, or ICU support had 68%, 91%, and 100% of treatment delays.

Discussion

In this series, MM patients diagnosed with COVID-19 had a very high frequency of hospitalization, ventilatory support requirements, ICU admission, and deaths. Although not associated with increased mortality, the therapy regimen was associated with severity condition. There was a high frequency of MM treatment delay in COVID-19 recovered patients.

MM is a disease with severely impaired immunity, including B-cell dysfunction leading to hypogammaglobulinemia, T-cell, dendritic cell, and NK cell abnormalities.7 Infection complications are frequent at diagnosis and remain clinically significant during all phases of treatment.1,2,8

A significant impact of the COVID-19 pandemic on MM patients had been expected since the first report of cases, as viral infections constitute most infections in patients with MM, and the respiratory tract is the most common site.9

The Spain Cooperative Group provided the outcomes of a large national cohort of MM patients hospitalized with confirmed SARS-CoV-2 infection. Regarding their data, MM patients had mortality rates 50% higher than noncancer patients with COVID-19.10 In a report from a single center, including patients with COVID-19 managed as in and out-patient, the infection course was most moderate or severe, with 56% requiring hospitalizations, 20% of intensive care, and 18% of deaths.11 The in-patient mortality of both studies was around 30%-35%. Our patients required more often hospitalization and a significantly higher in-patient mortality rate (45%); three in four cases requiring ICU support were deceased in our cohort.

ECOG performance status was our cohort's most critical risk factor for mortality. ECOG performance status is a validated fragility score and an outcome predictor in cancer patients, independent of age and comorbidities index. The other COVID cohorts in MM patients had also addressed age, renal disease, and active/progressive disease as predictors of COVID outcome.11,12

Although none of the prior MM treatments significantly influenced the mortality rate in our cohort, they were associated with the severity of the infection. Corticosteroids and monoclonal antibodies increased rates of ventilatory support, and corticosteroids and immunomodulatory drugs were associated with ICU admission.

The MM treatment plays a role in the risk of overall infection, and patients with at more lines of therapy have an increased risk of infection due to cumulative immunosuppression.8,9 Corticosteroids increase the risk of all types of infections through various mechanisms, and the risk of infection is directly proportional to the dose of glucocorticoid use. In our cohort, patients treated with combinations including corticosteroids required more ventilatory support and intensive care.

Monoclonal antibodies, in our cases, represented by Daratumumab (anti CD38 monoclonal antibody), are associated with the reactivation of latent viral infections, neutropenia, and pneumonia. Some studies reported high frequencies of severe COVID-19 in MM patients under anti-CD38 treatments.13,14 Its mechanism of action can explain the association with the severity of COVID in our cohort.

At last, immunomodulatory drugs were associated with ICU admission in our cohort. IMiDs downregulate the transcription factor PU.1, which disrupts granulocyte differentiation and induces neutropenia, resulting in an increased risk of severe infection at all stages of treatment.8,15 Another critical point is the association between thrombosis and IMiDs. As in COVID patients, thrombosis is a concern, and special attention is required.

There were a limited number of breakthrough infections after COVID-19 vaccination in our study. However, as the cohort started before a massive vaccination program in Brazil, no associations can be made. Vaccination is crucial in this population, but seroconversion is lower in MM patients compared to the general population and patients remain at risk of breakthrough infections even after complete vaccination.16, 17, 18

Our results showed that more than half of patients who did not required hospitalization had delayed MM treatment. The rate increases to 100% if the patients recover after ICU admission. An extended follow-up is necessary to evaluate if it could modify the outcome of these patients who survived.

A recent study evaluated the potential changes of the COVID pandemic in the treatment course of MM patients. Analyzing MM patients from more than 280 cancer centers in the US, they noted that patients with MM diagnosis performed during COVID were less likely to initiate treatment than those diagnosed before the pandemic.5 Studies in other cancer patients' subgroups also reported modifications in the patient's care during COVID.10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23

Our study has several limitations. Due to the unequal access to healthcare in our country, which was intensified by the pandemic, our cases may not be representative of the national reality since only cases reported by GBRAM centers were included. Patients from other centers could have had worse outcomes than those reported. Additionally, none of our patients received antiviral drugs such as remdesivir, Paxlovid, or molnulpiravir, despite their approval by the Brazilian regulatory agency (Remdesivir was approved in 2021, and others in 2022). Until now, access to treatment has been challenging, even for immunocompromised patients.

On the other hand, the incorporation of various COVID-19 vaccines with different platforms into the national immunization program in Brazil has led to a massive vaccination, and most patients having heterologous vaccine schedules. This variability makes assessing immune status more challenging.

The COVID-19 pandemic has dramatically impacted health care globally, but its impact on managing hematologic malignancies in low-income nations is an even higher challenge. We found that our patients were at the most significant risk of mortality from COVID-19 compared with MM patients from other reports. The increase in mortality among our patients was associated with performance status, but the treatment regimen was associated with disease severity. Most cases had the MM treatment at least delayed, and it needs special attention as it can result in long-term prognosis. These data are not surprising and emphasize the frailty of MM patients in Brazil. To limit severe events in this myeloma setting, close monitoring, optimal vaccination strategies, and access to treatment remains highly required, particularly in elderly patients with co-morbidities.

Authors' contribution

MG, EQC, GR, AM, and VH were responsible for the conception and design of the study, conducting the search, analysis, and interpretation of data, and drafting the article. EQC, GR, VH, RB, RJPM, KRZ, AEN, JSL, CBS, EGS, and AMF were responsible for data acquisition and provided feedback on the manuscript. All authors reviewed and approved the version to be submitted.

Conflicts of interest

None of the authors has any conflicts of interest (direct or indirect) concerning the manuscript's contents.

Funding

None.

Acknowledgments

We thank all clinical researchers from GBRAM for their support in collecting data.

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Articles from Hematology, Transfusion and Cell Therapy are provided here courtesy of Sociedade Brasileira de Hematologia e Hemoterapia

COVID-19 in multiple myeloma patients: frequencies and risk factors for hospitalization, ventilatory support, intensive care admission and mortality –cooperative registry from the Grupo Brasileiro de Mieloma Multiplo (GBRAM) (2024)

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