Literature DB >> 33367546

Clinical features associated with COVID-19 outcome in multiple myeloma: first results from the International Myeloma Society data set.

Ajai Chari1, Mehmet Kemal Samur2,3, Joaquin Martinez-Lopez4,5, Gordon Cook6,7, Noa Biran8, Kwee Yong9, Vania Hungria10, Monika Engelhardt11,12,13, Francesca Gay14, Ana García Feria15, Stefania Oliva16, Rimke Oostvogels17, Alessandro Gozzetti18, Cara Rosenbaum19, Shaji Kumar20, Edward A Stadtmauer21, Hermann Einsele22, Meral Beksac23, Katja Weisel24, Kenneth C Anderson2,25, María-Victoria Mateos26, Philippe Moreau27,28, Jesus San-Miguel29,30,31,32, Nikhil C Munshi2,25,33, Hervé Avet-Loiseau28,34.   

Abstract

The primary cause of morbidity and mortality in patients with multiple myeloma (MM) is an infection. Therefore, there is great concern about susceptibility to the outcome of COVID-19-infected patients with MM. This retrospective study describes the baseline characteristics and outcome data of COVID-19 infection in 650 patients with plasma cell disorders, collected by the International Myeloma Society to understand the initial challenges faced by myeloma patients during the COVID-19 pandemic. Analyses were performed for hospitalized MM patients. Among hospitalized patients, the median age was 69 years, and nearly all patients (96%) had MM. Approximately 36% were recently diagnosed (2019-2020), and 54% of patients were receiving first-line therapy. Thirty-three percent of patients have died, with significant geographic variability, ranging from 27% to 57% of hospitalized patients. Univariate analysis identified age, International Staging System stage 3 (ISS3), high-risk disease, renal disease, suboptimal myeloma control (active or progressive disease), and 1 or more comorbidities as risk factors for higher rates of death. Neither history of transplant, including within a year of COVID-19 diagnosis, nor other anti-MM treatments were associated with outcomes. Multivariate analysis found that only age, high-risk MM, renal disease, and suboptimal MM control remained independent predictors of adverse outcome with COVID-19 infection. The management of MM in the era of COVID-19 requires careful consideration of patient- and disease-related factors to decrease the risk of acquiring COVID-19 infection, while not compromising disease control through appropriate MM treatment. This study provides initial data to develop recommendations for the management of MM patients with COVID-19 infection.

Entities:  

Mesh:

Year:  2020        PMID: 33367546      PMCID: PMC7759145          DOI: 10.1182/blood.2020008150

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


Introduction

In the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)[1] pandemic, known as COVID-19, cancer represents a major risk factor[2-4] for COVID-19–associated death. Cancer patients with COVID-19 represented 8.3% of deaths in the New York city area, and 7.6% of deaths from the Wuhan area in China.[5,6] An even higher fatality rate (20.3%) was observed in Italy.[7] A recent study aimed at identifying risk factors for death in cancer patients developing COVID-19 interestingly (but not surprisingly) reported age over 65 years as a risk factor. In this study, treatment with checkpoint inhibitors was a risk factor, but not ongoing chemotherapy.[5] Multiple myeloma (MM) is a hematological cancer involving plasma cells, mostly within the bone marrow.[8] Apart from the specific cancer-related symptoms, most patients display immunosuppression[9] involving both the B- and T-cell compartments. Infections are common disease complications,[10] and unfortunately remain a major cause of death. Furthermore, corticosteroids, and especially dexamethasone, are used as treatment throughout the disease course, usually at high doses.[11,12] This MM therapy may increase the immunosuppression observed in patients with MM, though low doses seem to improve mortality in hospitalized patients. MM usually affects the elderly population, a more vulnerable group of patients due to immunosenescence together with other comorbidities. In addition, younger MM patients are usually treated with high-dose chemotherapy followed by autologous stem cell transplant,[13] with high infection susceptibility during the 3-month period following transplant.[14] For all of these reasons, MM could theoretically represent a high risk factor for poor outcomes with COVID-19.[15] In this international study, we have collected data and investigated the risk and outcome of COVID-19 infection in MM patients globally, both to evaluate the death rate and to identify potential risk factors that could be modified to improve patient outcomes during the current pandemic and in the future. With this in mind, we have predominantly focused our analysis on patients requiring hospitalization for COVID-19 infection.

Methods

Patient cohort

The international MM COVID-19 data set created by the International Myeloma Society (IMS) has retrospectively collected data for 650 patients with a plasma cell disorder from 10 different countries and multiple centers. All patients in the study had confirmed positive SARS-CoV-2 tests, according to the protocols in their respective countries. A questionnaire created by IMS was shared with participant institutes/investigators, and all required information was collected by the participating investigators. Data cleaning, preprocessing, and quality control were completed before the data analysis. COVID-19 outcome is defined as recovery from the virus and discharge from hospital or death due to COVID-19. Those patients who required an ongoing treatment at the time of data collection, unknown COVID-19 outcomes, and not hospitalized, were excluded from the cohort for statistical analysis. The IMS COVID-19 data set is reviewed by the New England Institutional Review Board based on federal regulation 45 CFR 46 and associated guidance; it is determined to be human subjects research exempt and approved for a waiver of authorization. All data captured are deidentified and comply with Health Insurance Portability and Accountability Act (HIPAA) Safe Harbor regulations.

Statistical analysis

All statistical analyses were performed using R (www.r-project.org). Descriptive statistics for demographic information and clinical variables are reported. Parametric 2-group comparison was used for age, univariate logistic regression was used to evaluate the association between COVID-19 outcome and variables, and odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. Multivariate analysis was performed using only variables that were associated with the outcome on univariate analysis.

Results

Overall, 650 patients with a plasma cell disorder and COVID-19 infection are included in this study, with the majority of patients being from Spain (28.62%), France (28.46%), the United States (19.38%), and the United Kingdom (14.77%) (Table 1; Figure 1A; supplemental Table 1 [available on the Blood Web site]). Median age was 69 years (range, 34-92 years), and 58.5% of patients were male (Table 2). The vast majority of patients (95.5%) had MM, whereas 29 patients (4.5%) had another plasma cell disorder. The MM immunoglobulin subtype included 55% immunoglobulin G (IgG), 21% IgA, and 20% light chain (Table 2). Patients were equally distributed between International Staging System (ISS) stages 1 to 3, with 32.1% of patients having high-risk cytogenetics and 26.5% having renal dysfunction. Fifty-four percent of patients were receiving first-line therapy, whereas 23.5% of patients had 3 or more lines of therapy. Additional demographic data are presented in Table 1, Table 2, and supplemental Tables 1 and 2.
Table 1.

Total number of patients and their COVID-19 outcomes recorded in the IMS COVID-19 data set by country and diagnosis

All patients, n = 650HospitalizedHospitalized with invasive ventilation
n (%)Died (%)Died (%)Recovered (%)Unknown (%)TotalDied (%)Recovered (%)Unknown (%)Total
Country
 Total650 (100)222 (34.1)139 (31.10)300 (67.11)8 (1.79)44773 (80.22)16 (17.58)2 (2.20)91
 Spain186 (28.62)56 (30.1)46 (30.26)105 (69.08)1 (0.66)1529 (60.00)5 (33.33)1 (6.67)15
 France185 (28.46)69 (37.2)35 (26.52)97 (73.48)13231 (83.78)6 (16.22)(0.00)37
 USA126 (19.38)31 (24.6)11 (21.57)37 (72.55)3 (5.88)5117 (94.44)1 (5.56)(0.00)18
 UK96 (14.77)53 (55.2)44 (53.66)37 (45.12)1 (1.22)827 (100.00)(0.00)(0.00)7
 Other57 (8.77)13 (22.8)3 (10.00)24 (80.00)3 (10.00)309 (64.29)4 (28.57)1 (7.14)14
Diagnosis
 Total646 (100)222 (34.3)139 (31.24)295 (66.29)10 (2.25)44573 (80.22)16 (17.58)2 (2.20)91
 MM617 (95.51)212 (34.3)136 (31.85)283 (66.28)8 (1.87)42767 (78.82)16 (18.82)2 (2.35)85
 MGUS/SMM19 (2.94)5 (26.3)1 (8.33)9 (75.00)2 (16.67)123 (100)3
 Amyloid10 (1.55)5 (50)2 (33.33)4 (66.67)63 (100)3

All patients (n = 650) refers to all of the patients including, hospitalized patients and outpatients without any exclusion, in our data set.

MGUS, monoclonal gammopathy of undetermined significance; SMM, smoldering MM; UK, United Kingdom; USA, United States of America.

Figure 1.

Patient origin, mortality, and associated risk factors. (A) Number of patients in the IMS COVID-19 data set with plasma cell disorders. (B) Overall (outpatient and hospitalized) COVID-19 death rates in the data set by contributing countries. (C) Predicted COVID-19 outcome for MM patients by age. (D) A forest plot for risk factors for MM patients from univariate analysis. HR, high risk; LCL, lower confidence level; PD, progressive disease; UCL, upper confidence level; UK, United Kingdom; USA, United States of America.

Table 2.

Patient characteristics for hospitalized MM patients and overall data set

MM hospitalized recovered, n = 299MM hospitalized died, n = 203All MM patients, n = 617
Age, y
 Median [min-max]70 [35-92]72 [47-92]69 [34-92]
Sex, n (%)
 Female126 (42.14)76 (37.43)270 (41.53)
Year of diagnosis, n (%)
 2020 and 2019114 (38.64)67 (33)226 (35.59)
 2018 and 2017 and 201686 (29.15)69 (34)200 (31.50)
 2015 or before95 (32.20)67 (33)209 (32.91)
MGUS/MM type, n (%)
 IgG127 (57.72)59 (47.96)255 (55.19)
 IgA50 (22.72)30 (24.39)100 (21.64)
 Light chain38 (17.27)34 (27.64)93 (20.12)
ISS stage
 ISS1/2164 (69.49)88 (61.53)331 (68.39)
 ISS372 (30.50)55 (38.46)153 (31.61)
High-risk disease by FISH [del 17p, t(4;14), amp 1q, or t(14;16)], n (%)
 Yes57 (23.36)47 (30.51)136 (32.07)
Renal disease, n (%)
 Yes43 (21.71)41 (35.65)113 (26.52)
Line of treatments, n (%)
 1 or less156 (54.74)101 (51.27)331 (54)
 263 (22.10)48 (24.36)138 (22.51)
 3 or more66 (23.16)48 (24.36)144 (23.49)
Patient receiving active treatment, n (%)
 Yes225 (87.20)131 (86.75)456 (83.57)
Prior transplant, n (%)
 Yes118 (40.54)60 (32.78)241 (39.12)
Disease status, n (%)
 Newly diagnosed134 (50.95)86 (44.55)282 (48.53)
MM status at COVID-19, n (%)
 Active or PD37 (14.57)34 (22.97)87 (16.66)
 Partial response143 (56.30)82 (55.40)290 (55.55)
 Complete response74 (29.13)32 (21.62)145 (27.77)

All MM patients includes hospitalized patients and outpatients regardless of their COVID-19–associated outcome.

FISH, fluorescence in situ hybridization; ISS, International Staging System; max, maximum; min, minimum. See Table 1 for expansion of other abbreviations.

Total number of patients and their COVID-19 outcomes recorded in the IMS COVID-19 data set by country and diagnosis All patients (n = 650) refers to all of the patients including, hospitalized patients and outpatients without any exclusion, in our data set. MGUS, monoclonal gammopathy of undetermined significance; SMM, smoldering MM; UK, United Kingdom; USA, United States of America. Patient origin, mortality, and associated risk factors. (A) Number of patients in the IMS COVID-19 data set with plasma cell disorders. (B) Overall (outpatient and hospitalized) COVID-19 death rates in the data set by contributing countries. (C) Predicted COVID-19 outcome for MM patients by age. (D) A forest plot for risk factors for MM patients from univariate analysis. HR, high risk; LCL, lower confidence level; PD, progressive disease; UCL, upper confidence level; UK, United Kingdom; USA, United States of America. Patient characteristics for hospitalized MM patients and overall data set All MM patients includes hospitalized patients and outpatients regardless of their COVID-19–associated outcome. FISH, fluorescence in situ hybridization; ISS, International Staging System; max, maximum; min, minimum. See Table 1 for expansion of other abbreviations. Thirty-three percent of patients died following COVID-19 diagnosis. The death rate increased from 4% for those who were outpatients to 31% for hospitalized patients not on ventilator support to 80% for patients on ventilator support (Table 1; supplemental Table 1). The variability in death rates across 4 major countries is shown in Figure 1B and Table 1. The death rate in patients with other plasma cell disorders was 31% (9 of 29). We have further focused on analyzing the hospitalized patients, for whom the mortality rates ranged from 27% in Germany, Italy, Brazil, The Netherlands, Portugal, and Turkey to 57% in the United Kingdom (Table 2). Age was significantly associated with COVID-19 outcome (P < .001). The estimated probability of death for 40-, 60-, and 80-year old patients was 17.76%, 31.43%, and 49.3%, respectively (Figure 1C). Forty percent of hospitalized patients were female, and in contrast to prior reports, sex was not associated with outcome. Of note, the mean age for male patients (69 years) was significantly lower than female patients (71.5 years) (P = .01). Of the patients with available data, those diagnosed with MM in 2019 or 2020 accounted for 35.6% of the cohort, and those with ≤1 line of therapy accounted for 54% of the cohort; 32.9% of patients were diagnosed on or before 2015. Neither time from diagnosis nor number of prior lines of treatment had any impact on outcome of COVID-19 infection. Immunoglobulin type distribution was similar to the general MM population, and isotypes were not associated with outcome. Univariate analysis identified ISS3 vs ISS1 (P = .04), high-risk disease [del 17p, t(4;14), amp 1q or t(14;16)] (P = .07), renal disease (P = .007), inadequate MM control (active disease or progressive disease [PD] vs complete response) (P = .01), and 1 or more comorbidities (P = .04) correlating with higher rates of death (Figure 1D). Eighty-seven percent of patients who had a known treatment status were on active MM therapy at the time of COVID-19 diagnosis, and 89% patients had their therapy held during COVID-19 diagnosis and management (Table 2; supplemental Table 2). A history of prior transplant or transplant within a year of COVID-19 diagnosis did not impact outcome. In fact, patients with a history of stem cell transplant within a year of COVID-19 diagnosis had a lower death rate; however, this difference was cofounded by a 10-year age difference between transplant and nontransplant patients, and was not observed when adjusted for age. Similarly, we did not observe any significant difference in outcome from COVID-19 infection whether patients underwent transplant within 6 months or >6 months before their COVID-19 diagnosis. Approximately 86% of patients had prior exposure to proteasome inhibitors (PIs), 80% to immunomodulatory (IMiD) agents, and 30% to anti-CD38 antibody. In univariate analysis, prior PI, IMiD, or anti-CD38 treatment was not associated with outcome. Although univariate analysis showed that patients who were receiving IMiD treatment at the time of COVID-19 diagnosis had decreased mortality compared with patients not on IMiDs, multivariate analysis failed to identify IMiD or any of these features as being related with outcome (Table 3). We did not observe any significant correlation between active PI, IMiD, anti-CD38 monoclonal antibody, alkylating agents, steroids, or other treatments (venetoclax, 96-hour infusional regimens, bispecific T-cell engagers, belantamab, chimeric antigen receptor T cell, elotuzumab, histone deacetylase) and the COVID-19 outcome.
Table 3.

Estimated COVID-19 outcome predictors based on multivariate analysis and their ORs for MM patients

VariablePOR (95% CI)
Age.0061.04 (1.01-1.08)
ISS3.8991.05 (0.49-2.22)
High-risk disease.0132.35 (1.20-4.66)
Renal disease.0142.71 (1.23-6.08)
Active disease or PD.0631.91 (0.96-3.81)
Comorbidities.7110.88 (0.44-1.75)
Prior anti-CD38.5580.77 (0.31-1.85)
Active anti-CD38.2621.68 (0.68-4.21)
Active IMiD.7691.10 (0.59-2.07)

OR for age is calculated by increments of 1 year. High-risk disease includes patients with del 17p, t(4;14), amp 1q or t(14;16) alterations detected by FISH. Renal disease is defined as creatinine clearance <40 mL/min, creatinine >2 mg/dL, or on dialysis. Active disease or PD refers to newly diagnosed or relapsed patients whose MM was not responsive to any treatment or not controlled at the time of COVID-19 diagnosis. Comorbidities refers to 1 or more condition associated with cardiac, neurological, pulmonary, or renal disease, diabetes, and/or hypertension. Prior anti-CD38 refers to anti-CD38 monoclonal antibody usage any time before COVID-19 diagnosis. Active anti-CD38 and active-IMiD refer to using these treatments at the time of COVID-19 diagnosis. Variables with P < .1 were considered statistically significant and are shown in bold.

See Table 2 for expansion of abbreviations.

Estimated COVID-19 outcome predictors based on multivariate analysis and their ORs for MM patients OR for age is calculated by increments of 1 year. High-risk disease includes patients with del 17p, t(4;14), amp 1q or t(14;16) alterations detected by FISH. Renal disease is defined as creatinine clearance <40 mL/min, creatinine >2 mg/dL, or on dialysis. Active disease or PD refers to newly diagnosed or relapsed patients whose MM was not responsive to any treatment or not controlled at the time of COVID-19 diagnosis. Comorbidities refers to 1 or more condition associated with cardiac, neurological, pulmonary, or renal disease, diabetes, and/or hypertension. Prior anti-CD38 refers to anti-CD38 monoclonal antibody usage any time before COVID-19 diagnosis. Active anti-CD38 and active-IMiD refer to using these treatments at the time of COVID-19 diagnosis. Variables with P < .1 were considered statistically significant and are shown in bold. See Table 2 for expansion of abbreviations. The treatments of COVID-19 were very heterogeneous, with the most frequent therapies including combination strategies (70%), antibiotics (14%), and hydroxychloroquine (10%). No therapies for COVID-19 appeared to be protective or associated with worse outcomes. Of the aforementioned variables that were associated with an increased risk of death by univariate analysis, only age (OR = 1.04; 95% CI, 1.01-1.08), high-risk MM [del 17p, t(4;14), amp 1q or t(14;16)] (OR = 2.35; 95% CI, 1.20-4.66), renal disease (OR = 2.71; 95% CI, 1.23-6.08), and active or progressive MM (OR = 1.91; 95% CI, 0.96-3.81) remained as independent predictors of adverse outcome on multivariate analysis (Table 3).

Discussion

The COVID-19 infection has affected patients globally, with high incidence in Europe and the Americas. The disease has involved patients of all age groups; however, heterogeneity in outcome of COVID-19 infection has been observed to be associated with comorbidities, racial differences, as well as individual characteristics such as smoking.[16-18] Of note, the presence of comorbidities has been extensively studied to identify patients at greater risk of infection and those with worse outcome. In this regard, our current study focuses on a single type of cancer, MM, to understand both impact and outcome of patients when they develop COVID-19 infection. As MM patients have hallmark immunosuppression, it is of great interest to understand the impact of both the disease and its treatment, that is, the immunosuppressive effects of high-dose therapy with autologous transplantation, as well as novel targeted therapies. Here, we report data primarily from 4 countries (Spain, France, the United Kingdom, and the United States) having a high prevalence of COVID-19 infection and with the highest frequencies of COVID-19 in MM patients. Differing access to testing likely led to the majority of outpatients (55%) coming from the United States. Interestingly, recent data from institutions in New York City showed that ∼19% of 127 patients with COVID-19 actually had MM precursor conditions (plasmacytoma, monoclonal gammopathy of undetermined significance, smoldering MM).[19] Based on the fact that data collection was feasible predominantly in patients who were hospitalized, our study has focused on hospitalized patients and their outcomes, and is unable to provide insight into a question regarding susceptibility and outcome of COVID-19 in patients with MM precursor conditions. According to Surveillance, Epidemiology, and End Results Program (SEER) data, 22% of the patients with myeloma had their diagnosis of MM in 2019 or 2020. In our cohort, 36% of the patients with COVID-19 infection were diagnosed with MM in 2019 or 20, suggesting higher susceptibility even in earlier stages of the disease. Even if we account for variability in diagnosis and selection of cases, there seems to be no evidence of increased hospitalizations in advanced multiply relapsed MM, as was initially postulated. However, differing access to COVID-19 testing or care between newly diagnosed and established patients at academic hospitals collaborating with the IMS may impact these results. Of note, a prior report noted that hypogammaglobulinemia (IgG < 700 mg/dL) was not associated with outcomes of COVID-19 infection, but severe hypogammaglobulinemia (IgG < 400 mg/dL) was associated with death.[20] The impact of disease stage and clinical immunoparesis is being evaluated in prospective studies. The sex distribution in this analysis was similar to the general incidence of MM, and thus suggests a similar susceptibility to COVID-19 infection between male and female patients with MM. A clear association between age and outcome was confirmed in these patients, as is true in other settings. The differences reported here between various countries reflects, at least in part, differing diagnostic and management practices, as well as the resources available and used in management of COVID-19 at the height of the pandemic, as well as referral patterns. Health system differences between countries may influence the ability to seek or obtain SARS-CoV-2 testing and health care, including admission to hospital. Health care providers should always consider local COVID-19 prevalence and local guidelines, and recommendations made here should only be used as a reference. For example, the number of patients who received ventilator support differed from 7% to 31%, and there are also differences in outpatient management vs hospitalization. Nonetheless, hospitalized patients can be considered to have more severe COVID-19–related complications requiring more intensive support. Our data suggest higher mortality in hospitalized patients with MM and COVID-19 infection than nonmyeloma patients. A recent study from Spain found a higher mortality rate in MM patients with COVID-19 (34%) compared with age- and sex-matched non-MM patients with COVID-19 (23%).[21] A recent publication from France confirmed overall mortality in all hospitalized patients with COVID-19 to be 16%, which is significantly lower than mortality observed in hospitalized MM patients in France (39%).[22] Our data clearly suggest a lack of relationship between prior lines of therapy or prior type of therapy, or those receiving active MM therapy at the time of diagnosis with COVID-19 and outcome. Interestingly, neither past nor recent high-dose therapy had significant impact on outcome. These data indicate that postponing indicated MM therapies, including high-dose therapy, may not be necessary during the COVID-19 pandemic. Within the limitation of our sample size and retrospective nature of the study, there is no clear suggestion for the need to avoid any specific MM treatment. Importantly, patients with good MM control (complete response) had superior outcome compared with those with relapsed disease or partial response. A similar finding was observed in a study of 928 cancer patients with COVID-19, in which patients with active cancer (progressing vs remission) had an adjusted OR of 5.2 for 30-day mortality, but there was no association with recent noncytotoxic therapy nor recent cytotoxic systemic chemotherapy.[2] As most patients receive dexamethasone as part of combination therapy, judging its independent impact on outcome was not possible, which is important because a recent report suggests superior survival for those COVID-19 patients given dexamethasone as part of their COVID-19 therapy.[23] Our multivariate model identifies age, high-risk or progressive MM, and presence of renal disease as indicators of poor outcome. MM therapy to achieve deep response may therefore also protect patients from adverse outcome from COVID-19 infection. Although little is known about the recovery of patients with MM from COVID-19 infection, Wang et al found that the median time to polymerase chain reaction (PCR) negativity was 43 days (range, 19-68 days) from initial positive PCR.[20] Interestingly, 96% of MM patients (22 of 23) developed antibodies to SARS-CoV-2 at a median of 32 days after initial diagnosis. Based on the observations reported here, young patients with high-risk and/or active MM need to receive therapies to control their disease, which will also improve their outcome if infected with COVID-19. For elderly patients with a higher death rate from COVID-19, disease control is also beneficial, but may be achieved using regimens that decrease frequency of office visits (eg, oral drug) in order to avoid exposure to the virus. Importantly, continued therapy including steroids and high-dose therapy are not contraindicated, and in fact should be continued to achieve better MM control, which is associated with improved outcome even with COVID-19 infection. In conclusion, this collaborative international effort provides the first large-scale analysis and initial IMS suggestions on the management of, and outcomes for, patients with MM during the current COVID-19 pandemic (Table 4). As the pandemic and data accumulation rapidly increase, we need prospective studies on treatment options and additional patient characteristics to further understand the variables associated with COVID-19–associated death in MM patients. The high mortality noted in MM patients highlights the critical importance of measures to prevent contracting COVID-19, such as social distancing and wearing masks, in patients with MM.
Table 4.

Recommendations for management of MM patients in the era of a global COVID-19 pandemic

Recommendations for management of MM patients in the COVID-19 era
• Measures to prevent contracting COVID-19 including social distancing, wearing masks, and personal hygiene are critically important for MM patients
• COVID-19 PCR testing should be considered once in all newly diagnosed MM patients before starting therapy and also in patients prior to high-dose or cellular therapies; however, the testing of other MM patients as well as the frequency of repeat testing should be guided by symptoms and prevalence of COVID-19 in the environs
• MM patients diagnosed with COVID-19 and having any of the following characteristics: age >60 y, high-risk cytogenetics, active disease or PD, or renal disease should be monitored more closely for COVID-19 complications
• Currently, there are no data to support avoiding any specific MM treatments, including corticosteroids and high-dose therapy; this is particularly important in those patients with active disease or PD
• The risk/benefit of MM therapy should be weighed against an individual’s risk factors for COVID-19 complications and the prevalence of COVID-19 at a given time
 o Young patients, especially those with high-risk and/or active MM, should receive optimal MM therapies to control their disease
 o MM disease control is also important for elderly patients; however, consideration should be given to using regimens that result in decreased frequency of office visits to decrease the risk of COVID-19 exposure
• Data regarding the safety of continuing MM therapy in COVID-19 PCR+ patients are lacking; as with any MM patient with an active infection, the risks/benefit of MM therapy must be weighed carefully, and consideration should be given to at least ensuring clinical stability
Recommendations for management of MM patients in the era of a global COVID-19 pandemic

Supplementary Material

The online version of this article contains a data supplement. Click here for additional data file.
  19 in total

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Review 3.  Latest advances and current challenges in the treatment of multiple myeloma.

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4.  Infectious Complications in Patients With Multiple Myeloma After High-Dose Chemotherapy Followed by Autologous Stem Cell Transplant: Nationwide Study of the Infectious Complications Study Group of the Polish Adult Leukemia Group.

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Journal:  Transplant Proc       Date:  2020-03-23       Impact factor: 1.066

5.  Estimating the burden of SARS-CoV-2 in France.

Authors:  Henrik Salje; Cécile Tran Kiem; Noémie Lefrancq; Noémie Courtejoie; Paolo Bosetti; Juliette Paireau; Alessio Andronico; Nathanaël Hozé; Jehanne Richet; Claire-Lise Dubost; Yann Le Strat; Justin Lessler; Daniel Levy-Bruhl; Arnaud Fontanet; Lulla Opatowski; Pierre-Yves Boelle; Simon Cauchemez
Journal:  Science       Date:  2020-05-13       Impact factor: 47.728

6.  Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study.

Authors:  Andrew Clark; Mark Jit; Charlotte Warren-Gash; Bruce Guthrie; Harry H X Wang; Stewart W Mercer; Colin Sanderson; Martin McKee; Christopher Troeger; Kanyin L Ong; Francesco Checchi; Pablo Perel; Sarah Joseph; Hamish P Gibbs; Amitava Banerjee; Rosalind M Eggo
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7.  COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study.

Authors:  Lennard Yw Lee; Jean-Baptiste Cazier; Vasileios Angelis; Roland Arnold; Vartika Bisht; Naomi A Campton; Julia Chackathayil; Vinton Wt Cheng; Helen M Curley; Matthew W Fittall; Luke Freeman-Mills; Spyridon Gennatas; Anshita Goel; Simon Hartley; Daniel J Hughes; David Kerr; Alvin Jx Lee; Rebecca J Lee; Sophie E McGrath; Christopher P Middleton; Nirupa Murugaesu; Thomas Newsom-Davis; Alicia Fc Okines; Anna C Olsson-Brown; Claire Palles; Yi Pan; Ruth Pettengell; Thomas Powles; Emily A Protheroe; Karin Purshouse; Archana Sharma-Oates; Shivan Sivakumar; Ashley J Smith; Thomas Starkey; Chris D Turnbull; Csilla Várnai; Nadia Yousaf; Rachel Kerr; Gary Middleton
Journal:  Lancet       Date:  2020-05-28       Impact factor: 79.321

8.  Multiple myeloma and SARS-CoV-2 infection: clinical characteristics and prognostic factors of inpatient mortality.

Authors:  Joaquín Martínez-López; María-Victoria Mateos; Cristina Encinas; Anna Sureda; José Ángel Hernández-Rivas; Ana Lopez de la Guía; Diego Conde; Isabel Krsnik; Elena Prieto; Rosalía Riaza Grau; Mercedes Gironella; María Jesús Blanchard; Nerea Caminos; Carlos Fernández de Larrea; María Alicia Senin; Fernando Escalante; José Enrique de la Puerta; Eugenio Giménez; Pilar Martínez-Barranco; Juan José Mateos; Luis Felipe Casado; Joan Bladé; Juan José Lahuerta; Javier de la Cruz; Jesús San-Miguel
Journal:  Blood Cancer J       Date:  2020-10-19       Impact factor: 11.037

9.  Early relapse after autologous transplant for myeloma is associated with poor survival regardless of cytogenetic risk.

Authors:  Jill Corre; Lydia Montes; Elodie Martin; Aurore Perrot; Denis Caillot; Xavier Leleu; Karim Belhadj; Thierry Facon; Cyrille Hulin; Mohamad Mohty; Jean Fontan; Margaret Macro; Sabine Brechignac; Arnaud Jaccard; Anne-Marie Stoppa; Frederique Orsini-Piocelle; Didier Adiko; Laurent Voillat; Faiza Keddar; Marly Barry; Helene Demarquette; Marie-Noelle Certain; Isabelle Plantier; Murielle Roussel; Benjamin Hébraud; Thomas Filleron; Michel Attal; Hervé Avet-Loiseau
Journal:  Haematologica       Date:  2020-09-01       Impact factor: 9.941

10.  Risk factors for death in 1859 subjects with COVID-19.

Authors:  Lei Chen; Jianming Yu; Wenjuan He; Li Chen; Guolin Yuan; Fang Dong; Wenlan Chen; Yulin Cao; Jingyan Yang; Liling Cai; Di Wu; Qijie Ran; Lei Li; Qiaomei Liu; Wenxiang Ren; Fei Gao; Hongxiang Wang; Zhichao Chen; Robert Peter Gale; Qiubai Li; Yu Hu
Journal:  Leukemia       Date:  2020-06-16       Impact factor: 12.883

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  60 in total

1.  Disease- and Therapy-Specific Impact on Humoral Immune Responses to COVID-19 Vaccination in Hematologic Malignancies.

Authors:  Santosha A Vardhana; David A Knorr; David J Chung; Gunjan L Shah; Sean M Devlin; Lakshmi V Ramanathan; Sital Doddi; Melissa S Pessin; Elizabeth Hoover; LeeAnn T Marcello; Jennifer C Young; Sawsan R Boutemine; Edith Serrano; Saumya Sharan; Saddia Momotaj; Lauren Margetich; Christina D Bravo; Genovefa A Papanicolaou; Mini Kamboj; Anthony R Mato; Lindsey E Roeker; Malin Hultcrantz; Sham Mailankody; Alexander M Lesokhin
Journal:  Blood Cancer Discov       Date:  2021-09-13

2.  [Experts' consensus on severe acute respiratory syndrome coronavirus-2 vaccination in adult patients with hematological diseases in China (2022)].

Authors: 
Journal:  Zhonghua Xue Ye Xue Za Zhi       Date:  2022-05-14

Review 3.  Clinical Considerations for Immunoparesis in Multiple Myeloma.

Authors:  Michael Chahin; Zachery Branham; Ashley Fox; Christian Leurinda; Amany R Keruakous
Journal:  Cancers (Basel)       Date:  2022-05-03       Impact factor: 6.575

Review 4.  Facts and Hopes in Multiple Myeloma Immunotherapy.

Authors:  Adam S Sperling; Kenneth C Anderson
Journal:  Clin Cancer Res       Date:  2021-03-26       Impact factor: 12.531

Review 5.  Hematopoietic stem cell transplantation for autoimmune diseases in the time of COVID-19: EBMT guidelines and recommendations.

Authors:  Raffaella Greco; Tobias Alexander; Joachim Burman; Nicoletta Del Papa; Jeska de Vries-Bouwstra; Dominique Farge; Jörg Henes; Majid Kazmi; Kirill Kirgizov; Paolo A Muraro; Elena Ricart; Montserrat Rovira; Riccardo Saccardi; Basil Sharrack; Emilian Snarski; Barbara Withers; Helen Jessop; Claudia Boglione; Ellen Kramer; Manuela Badoglio; Myriam Labopin; Kim Orchard; Selim Corbacioglu; Per Ljungman; Malgorzata Mikulska; Rafael De la Camara; John A Snowden
Journal:  Bone Marrow Transplant       Date:  2021-05-24       Impact factor: 5.483

Review 6.  COVID-19 and Cancer: A Review of the Registry-Based Pandemic Response.

Authors:  Aakash Desai; Turab J Mohammed; Narjust Duma; Marina C Garassino; Lisa K Hicks; Nicole M Kuderer; Gary H Lyman; Sanjay Mishra; David J Pinato; Brian I Rini; Solange Peters; Jeremy L Warner; Jennifer G Whisenant; William A Wood; Michael A Thompson
Journal:  JAMA Oncol       Date:  2021-12-01       Impact factor: 31.777

7.  CD8+ T cells contribute to survival in patients with COVID-19 and hematologic cancer.

Authors:  Erin M Bange; Nicholas A Han; Paul Wileyto; Justin Y Kim; Sigrid Gouma; James Robinson; Allison R Greenplate; Madeline A Hwee; Florence Porterfield; Olutosin Owoyemi; Karan Naik; Cathy Zheng; Michael Galantino; Ariel R Weisman; Caroline A G Ittner; Emily M Kugler; Amy E Baxter; Olutwatosin Oniyide; Roseline S Agyekum; Thomas G Dunn; Tiffanie K Jones; Heather M Giannini; Madison E Weirick; Christopher M McAllister; N Esther Babady; Anita Kumar; Adam J Widman; Susan DeWolf; Sawsan R Boutemine; Charlotte Roberts; Krista R Budzik; Susan Tollett; Carla Wright; Tara Perloff; Lova Sun; Divij Mathew; Josephine R Giles; Derek A Oldridge; Jennifer E Wu; Cécile Alanio; Sharon Adamski; Alfred L Garfall; Laura A Vella; Samuel J Kerr; Justine V Cohen; Randall A Oyer; Ryan Massa; Ivan P Maillard; Kara N Maxwell; John P Reilly; Peter G Maslak; Robert H Vonderheide; Jedd D Wolchok; Scott E Hensley; E John Wherry; Nuala J Meyer; Angela M DeMichele; Santosha A Vardhana; Ronac Mamtani; Alexander C Huang
Journal:  Nat Med       Date:  2021-05-20       Impact factor: 87.241

8.  Characterization of Metal-Bound Benzimidazole Derivatives, Effects on Tumor Cells of Lung Cancer.

Authors:  Anita Raducka; Agnieszka Czylkowska; Katarzyna Gobis; Kamila Czarnecka; Paweł Szymański; Marcin Świątkowski
Journal:  Materials (Basel)       Date:  2021-05-30       Impact factor: 3.623

9.  Antibody Response After Initial Vaccination for SARS-CoV-2 in Patients With Amyloidosis.

Authors:  Efstathios Kastritis; Evangelos Terpos; Aimilia Sklirou; Foteini Theodorakakou; Despina Fotiou; Eleni-Dimitra Papanagnou; Tina Bagratuni; Nikolaos Kanellias; Maria Gavriatopoulou; Ioannis P Trougakos; Meletios A Dimopoulos
Journal:  Hemasphere       Date:  2021-07-15

Review 10.  COVID-19 in immunocompromised populations: implications for prognosis and repurposing of immunotherapies.

Authors:  Jason D Goldman; Philip C Robinson; Thomas S Uldrick; Per Ljungman
Journal:  J Immunother Cancer       Date:  2021-06       Impact factor: 13.751

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