Abstract: Introduction In the first weeks of the Covid-19 pandemic when healthcare systems in many areas were overstretched, we documented that hospital mortality in multiple myeloma (MM) patients infected by Sars-Cov-2 was 50% higher than in age matched Covid-19 patients without cancer. In the following months, the pressure on healthcare systems in Spain continued although it did not reach the extreme levels of the first weeks of the pandemic. In this study, we proposed to determine if the severity of Covid-19 outcomes in MM patients has changed over the first year of the pandemic. Patients and methods The Spanish MM Collaborative Group (Pethema-GEM) conducted a survey at national level on plasma cell disorder patients infected by SARS-Cov-2 between March 2020 and February 2021. Sixty-six (69%) out of 96 contacted healthcare centers, from all 17 regions in Spain, reported 502 patients. Data on Covid-19 acute and post-acute phase outcomes (hospitalization, oxygen requirements, severity of symptoms and mortality) were reported first in May 2020 (Martinez-Lopez et al, BCJ 2021) and updated in February 2021. In this study, we compared outcome occurrence between two study periods: P1, a period of extreme stress for the healthcare system in Spain, from March to mid-June 2020; and a second period, P2, up to mid-February 2021 with a sustained but lower burden on the national health care system. Results Among the 451 patients with plasma cell disorders and a Sars-Cov-2 infection documented with an rRT-PCR positive test, 377 (84%) were MM patients, 15 SMM (3%), 40 MGUS (9%) and 19 amyloidosis (4%). The number of MM weekly reported cases was 57% (95%CI, 48-65) lower in P2 (188 cases in 35 weeks) compared to P1 (189 cases in 15 weeks), p & lt;0.001. The mean (SD) age and the proportion of men did not differ between P1 and P2, respectively 69.8 (10.9) vs 68.6 (11.0) years, p=0.6, and 53.3% vs 59.6%, p=0.2. MM patients with active or progressive disease at time of Covid-19 diagnosis were 24% in P1 and 34% in P2, p=0.05; patients on active treatment were more frequent in P1, 89%, than in P2, 79%, p=0.01. MM treatment was withheld in 78% and 82% of patients, p=0.4. Covid-19 treatment changed over time: MM inpatients received more remdesivir and corticoids in the second period (3% vs 31% p & lt;0.001, and 49% vs 73%, p & lt;0.001, respectively). In P1, 90% of the reported MM patients were hospitalized compared to 71% in P2, p & lt;0.001. Thirty-one and 41% of patients did not require oxygen support during P1 and P2, respectively; non-invasive ventilation in 19% and 14%, and mechanical ventilation in 7% and 8%, p=0.12. Overall, acute clinical Covid-19 severity was reduced from P1 to P2: 75% to 51%, p & lt;0.001: moderate/severe pneumonia was reduced from 68% to 36%, p & lt;0.001 but severe distress syndrome increased from 7% to 15%, p=0.03. However, mortality in all reported patients was 30.7% in P1 vs 26.1% in P2, p=0.3; and no differences in mortality were observed in hospitalized patients, 32.2% in P1 and 35.3% in P2, p=0.6. We performed a multivariable adjustment with the predictors identified in our previous study (BCJ 2021) and confirmed that inpatient mortality was similar in both study periods, odds ratio (OR) 0.99 (95%CI 0.59-1.66). Independently of the study period, an increased mortality was observed in men (OR 1.81, 1.08-3.05), patients over 65 (OR 2.40, 1.33-4.36), and patients with active or progressive disease (OR 2.12, 1.24-3.62). The severity of Covid-19 clinical outcomes -besides mortality, was associated with increased age but not with active or progressive disease. Conclusions Although COVID-19 clinical severity has decreased over the first year of the pandemic in multiple myeloma patients, mortality remains high with no change between the initial weeks of the pandemic and the following months. Prevention and vaccination strategies should be strengthened in this vulnerable population, particularly in patients with active or progressive disease at time of Covid-19 diagnosis. Disclosures Martínez-López: Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy; Roche, Novartis, Incyte, Astellas, BMS: Research Funding. Mateos: Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria. López-Muñoz: Amgen: Consultancy. Sureda: GSK: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Other: Support for attending meetings and/or travel; Mundipharma: Consultancy; Bluebird: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite, a Gilead Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Research Funding, Speakers Bureau. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Lahuerta: Celgene, Takeda, Amgen, Janssen and Sanofi: Consultancy; Celgene: Other: Travel accomodations and expenses. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, Takeda: Consultancy, Other: Advisory board.

Abstract: Assessing measurable residual disease (MRD) has become standard with many tumors, but the clinical meaning of MRD in multiple myeloma (MM) remains uncertain, particularly when assessed by next-generation flow (NGF) cytometry. Thus, we aimed to determine the applicability and sensitivity of the flow MRD-negative criterion defined by the International Myeloma Working Group (IMWG). PATIENTS AND METHODS In the PETHEMA/GEM2012MENOS65 trial, 458 patients with newly diagnosed MM had longitudinal assessment of MRD after six induction cycles with bortezomib, lenalidomide, and dexamethasone (VRD), autologous transplantation, and two consolidation courses with VRD. MRD was assessed in 1,100 bone marrow samples from 397 patients; the 61 patients without MRD data discontinued treatment during induction and were considered MRD positive for intent-to-treat analysis. The median limit of detection achieved by NGF was 2.9 × 10 −6 . Patients received maintenance (lenalidomide ± ixazomib) according to the companion PETHEMA/GEM2014MAIN trial. RESULTS Overall, 205 (45%) of 458 patients had undetectable MRD after consolidation, and only 14 of them (7%) have experienced progression thus far; seven of these 14 displayed extraosseous plasmacytomas at diagnosis and/or relapse. Using time-dependent analysis, patients with undetectable MRD had an 82% reduction in the risk of progression or death (hazard ratio, 0.18; 95% CI, 0.11 to 0.30; P 〈 .001) and an 88% reduction in the risk of death (hazard ratio, 0.12; 95% CI, 0.05 to 0.29; P 〈 .001). Timing of undetectable MRD (after induction v intensification) had no impact on patient survival. Attaining undetectable MRD overcame poor prognostic features at diagnosis, including high-risk cytogenetics. By contrast, patients with Revised International Staging System III status and positive MRD had dismal progression-free and overall survivals (median, 14 and 17 months, respectively). Maintenance increased the rate of undetectable MRD by 17%. CONCLUSION The IMWG flow MRD-negative response criterion is highly applicable and sensitive to evaluate treatment efficacy in MM.

Abstract: Patients with cancer have been shown to have a higher risk of clinical severity and mortality compared to non-cancer patients with COVID-19. Patients with hematologic malignancies typically are known to have higher levels of immunosuppression and may develop more severe respiratory viral infections than patients with solid tumors. Data on COVID-19 in patients with hematologic malignancies are limited. Here we characterize disease severity and mortality and evaluate potential prognostic factors for mortality. Methods In this population-based registry study, we collected de-identified data on clinical characteristics, treatment and outcomes in adult patients with hematologic malignancies and confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection within the Madrid region of Spain. Our case series included all patients admitted to 22 regional health service hospitals and 5 private healthcare centers between February 28 and May 25, 2020. The primary study outcome was all-cause mortality. We assessed the association between mortality and potential prognostic factors using Cox regression analyses adjusted for age, sex, comorbidities, hematologic malignancy and recent active cancer therapy. Results Of 833 patients reported, 697 were included in the analyses. Median age was 72 years (IQR 60–79), 413 (60%) patients were male and 479 (69%) and 218 (31%) had lymphoid and myeloid malignancies, respectively. Clinical severity of COVID-19 was severe/critical in 429 (62%) patients. At data cutoff, 230 (33%) patients had died. Age ≥ 60 years (hazard ratios 3.17–10.1 vs  〈  50 years),  〉  2 comorbidities (1.41 vs ≤ 2), acute myeloid leukemia (2.22 vs non-Hodgkin lymphoma) and active antineoplastic treatment with monoclonal antibodies (2·02) were associated with increased mortality; conventional chemotherapy showed borderline significance (1.50 vs no active therapy). Conversely, Ph-negative myeloproliferative neoplasms (0.33) and active treatment with hypomethylating agents (0.47) were associated with lower mortality. Overall, 574 (82%) patients received antiviral therapy. Mortality with severe/critical COVID-19 was higher with no therapy vs any antiviral combination therapy (2.20). Conclusions In this series of patients with hematologic malignancies and COVID-19, mortality was associated with higher age, more comorbidities, type of hematological malignancy and type of antineoplastic therapy. Further studies and long-term follow-up are required to validate these criteria for risk stratification.

Abstract: Mortality rates for COVID-19 have declined over time in the general population, but data in patients with hematologic malignancies are contradictory. We identified independent prognostic factors for COVID-19 severity and survival in unvaccinated patients with hematologic malignancies, compared mortality rates over time and versus non-cancer inpatients, and investigated post COVID-19 condition. Data were analyzed from 1166 consecutive, eligible patients with hematologic malignancies from the population-based HEMATO-MADRID registry, Spain, with COVID-19 prior to vaccination roll-out, stratified into early (February–June 2020; n = 769 (66%)) and later (July 2020–February 2021; n = 397 (34%)) cohorts. Propensity-score matched non-cancer patients were identified from the SEMI-COVID registry. A lower proportion of patients were hospitalized in the later waves (54.2%) compared to the earlier (88.6%), OR 0.15, 95%CI 0.11–0.20. The proportion of hospitalized patients admitted to the ICU was higher in the later cohort (103/215, 47.9%) compared with the early cohort (170/681, 25.0%, 2.77; 2.01–3.82). The reduced 30-day mortality between early and later cohorts of non-cancer inpatients (29.6% vs. 12.6%, OR 0.34; 0.22–0.53) was not paralleled in inpatients with hematologic malignancies (32.3% vs. 34.8%, OR 1.12; 0.81–1.5). Among evaluable patients, 27.3% had post COVID-19 condition. These findings will help inform evidence-based preventive and therapeutic strategies for patients with hematologic malignancies and COVID-19 diagnosis.

Abstract: The existence of patients with multiple myeloma (MM) and light-chain (AL) amyloidosis who present with a monoclonal gammopathy of undetermined significance (MGUS)–like phenotype has been hypothesized, but methods to identify this subgroup are not standardized and its clinical significance is not properly validated. PATIENTS AND METHODS An algorithm to identify patients having MGUS-like phenotype was developed on the basis of the percentages of total bone marrow (BM) plasma cells (PC) and of clonal PC within the BM PC compartment, determined at diagnosis using flow cytometry in 548 patients with MGUS and 2,011 patients with active MM. The clinical significance of the algorithm was tested and validated in 488 patients with smoldering MM, 3,870 patients with active MM and 211 patients with AL amyloidosis. RESULTS Patients with smoldering MM with MGUS-like phenotype showed significantly lower rates of disease progression (4.5% and 0% at 2 years in two independent series). There were no statistically significant differences in time to progression between treatment versus observation in these patients. In active newly diagnosed MM, MGUS-like phenotype retained independent prognostic value in multivariate analyses of progression-free survival (PFS; hazard ratio [HR], 0.49; P = .001) and overall survival (OS; HR, 0.56; P = .039), together with International Staging System, lactate dehydrogenase, cytogenetic risk, transplant eligibility, and complete remission status. Transplant-eligible patients with active MM with MGUS-like phenotype showed PFS and OS rates at 5 years of 79% and 96%, respectively. In this subgroup, there were no differences in PFS and OS according to complete remission and measurable residual disease status. Application of the algorithm in two independent series of patients with AL predicted for different survival. CONCLUSION We developed an open-access algorithm for the identification of MGUS-like patients with distinct clinical outcomes. This phenotypic classification could become part of the diagnostic workup of MM and AL amyloidosis.

Abstract: There is limited information on the characteristics, prognostic factors, and outcomes of patients with multiple myeloma (MM) hospitalized with COVID-19. This retrospective case series investigated 167 patients reported from 73 hospitals within the Spanish Myeloma Collaborative Group network in March and April, 2020. Outcomes were compared with 167 randomly selected, contemporary, age-/sex-matched noncancer patients with COVID-19 admitted at six participating hospitals. Among MM and noncancer patients, median age was 71 years, and 57% of patients were male; 75 and 77% of patients, respectively, had at least one comorbidity. COVID-19 clinical severity was moderate–severe in 77 and 89% of patients and critical in 8 and 4%, respectively. Supplemental oxygen was required by 47 and 55% of MM and noncancer patients, respectively, and 21%/9% vs 8%/6% required noninvasive/invasive ventilation. Inpatient mortality was 34 and 23% in MM and noncancer patients, respectively. Among MM patients, inpatient mortality was 41% in males, 42% in patients aged 〉 65 years, 49% in patients with active/progressive MM at hospitalization, and 59% in patients with comorbid renal disease at hospitalization, which were independent prognostic factors on adjusted multivariate analysis. This case series demonstrates the increased risk and identifies predictors of inpatient mortality among MM patients hospitalized with COVID-19.

Abstract: Traumatic brain injury (TBI) represents a large health and economic burden. Because of the inability of previous randomized controlled trials (RCTs) on TBI to demonstrate the expected benefit of reducing unfavorable outcomes, the IMPACT (International Mission on Prognosis and Analysis of Clinical Trials in TBI) and CRASH (Corticosteroid Randomisation After Significant Head Injury) studies provided new methods for performing prognostic studies of TBI. This study aimed to develop and externally validate a prognostic model for early death (within 48 hours). The secondary aim was to identify patients who were more likely to succumb to an early death to limit their inclusion in RCTs and to improve the efficiency of RCTs. Methods The derivation cohort was recruited at 1 center, Hospital 12 de Octubre, Madrid (1990–2003, 925 patients). The validation cohort was recruited in 2004–2006 from 7 study centers (374 patients). The eligible patients had suffered closed severe TBIs. The study outcome was early death (within 48 hours post-TBI). The predictors were selected using logistic regression modeling with bootstrapping techniques, and a penalized reduction was used. A risk score was developed based on the regression coefficients of the variables included in the final model. Results In the validation set, the final model showed a predictive ability of 50% (Nagelkerke R 2 ), with an area under the receiver operating characteristic curve of 89% and an acceptable calibration (goodness-of-fit test, p = 0.32). The final model included 7 variables, and it was used to develop a risk score with a range from 0 to 20 points. Age provided 0, 1, 2, or 3 points depending on the age group; motor score provided 0 points, 2 (untestable), or 3 (no response); pupillary reactivity, 0, 2 (1 pupil reacted), or 6 (no pupil reacted); shock, 0 (no) or 2 (yes); subarachnoid hemorrhage, 0 or 1 (severe deposit); cisternal status, 0 or 3 (compressed/absent); and epidural hematoma, 0 (yes) or 2 (no). Based on the risk of early death estimated with the model, 4 risk of early death groups were established: low risk, sum score 0–3 ( 〈 1% predicted mortality); moderate risk, sum score 4–8 (predicted mortality between 1% and 10%); high risk, sum score 9–12 (probability of early death between 10% and 50%); and very high risk, sum score 13–20 (early mortality probability 〉 50%). This score could be used for selecting patients for clinical studies. For example, if patients with very high risk scores were excluded from our study sample, the patients included (eligibility score 〈 13) would represent 80% of the original sample and only 23% of the patients who died early. Conclusions The combination of Glasgow Coma Scale score, CT scanning results, and secondary insult data into a prognostic score improved the prediction of early death and the classification of TBI patients.

Abstract: Patients with multiple myeloma (MM) may show patchy bone marrow (BM) infiltration and extramedullary disease. Notwithstanding, quantification of plasma cells (PCs) continues to be performed in BM since the clinical translation of circulating tumor cells (CTCs) remains undefined. PATIENTS AND METHODS CTCs were measured in peripheral blood (PB) of 374 patients with newly diagnosed MM enrolled in the GEM2012MENOS65 and GEM2014MAIN trials. Treatment included bortezomib, lenalidomide, and dexamethasone induction followed by autologous transplant, consolidation, and maintenance. Next-generation flow cytometry was used to evaluate CTCs in PB at diagnosis and measurable residual disease (MRD) in BM throughout treatment. RESULTS CTCs were detected in 92% (344 of 374) of patients with newly diagnosed MM. The correlation between the percentages of CTCs and BM PCs was modest. Increasing logarithmic percentages of CTCs were associated with inferior progression-free survival (PFS). A cutoff of 0.01% CTCs showed an independent prognostic value (hazard ratio: 2.02; 95% CI, 1.3 to 3.1; P = .001) in multivariable PFS analysis including the International Staging System, lactate dehydrogenase levels, and cytogenetics. The combination of the four prognostic factors significantly improved risk stratification. Outcomes according to the percentage of CTCs and depth of response to treatment showed that patients with undetectable CTCs had exceptional PFS regardless of complete remission and MRD status. In all other cases with detectable CTCs, only achieving MRD negativity (and not complete remission) demonstrated a statistically significant increase in PFS. CONCLUSION Evaluation of CTCs in PB outperformed quantification of BM PCs. The detection of ≥ 0.01% CTCs could be a new risk factor in novel staging systems for patients with transplant-eligible MM.

Abstract: Introduction: The severity of acute clinical outcomes and mortality in hematologic malignancy (HM) patients infected by SARS-CoV-2 was exhaustively documented in the first weeks of the pandemic. A consistent increased mortality compared to non-cancer patients was observed across studies. In this study we aimed to estimate survival in COVID-19 HM patients by type of malignancy, to describe acute and post-acute clinical outcomes, and to compare outcomes in early and later pandemic periods. Methods: In this population-based registry study sponsored by the Madrid Society of Hematology (Asociación Madrileña de Hematología y Hemoterapia), we collected de-identified data on clinical characteristics, treatment and acute and post-acute outcomes in adult patients with hematologic malignancies and confirmed SARS-CoV-2 infection within the Madrid region of Spain. Our case series included all eligible patients admitted to 26 regional health service hospitals and 5 private healthcare centers between February 28, 2020 and February 18, 2021 with a coverage of 98% on a population of 6.6 million inhabitants. The study outcomes were all-cause mortality, severity of disease (WHO), oxygen support, ICU admission, and follow-up symptoms and signs and complications. Survival probabilities were estimated with the actuarial method and reported overall and stratified by type of malignancy and for two study periods (early cohort,-COVID-19 diagnosis from February 28 to 31 May, 2020, and later cohort, up to February 18, 2021). Results: Of the 1408 patients reported to the HEMATO-MADRID COVID-19 registry, 1166 were included in the present analyses; 839 (72%) had a lymphoid malignancy, including 325 (28%) with non-Hodgkin lymphoma, 50 (4%) with Hodgkin lymphoma and 263 (23%) with multiple myeloma; and 327 (28%) had a myeloid malignancy, including 115 (10%) with myelodysplastic syndrome, 92 (8%) with acute myeloid leukemia (AML) and 87 (7%) with Philadelphia chromosome (Ph)-negative myeloproliferative neoplasms. Overall COVID-19 clinical severity was classified as critical in 19% of patients, severe in 36%, moderate in 22%, and mild in 22%; 10% were admitted to an ICU; 8% were on mechanical ventilation and 19% on noninvasive ventilation. Mild disease increased between early and later period from 15% to 38% of patients; severe disease decreased from 42% to 24%, p & lt;0.001. COVID-19 treatment with steroids increased from 38% to 59%, p & lt;0.001. At follow-up, 22% reported persistent symptoms related to COVID-19 at 2 months, 16% at 4 months and 14% at 6 months. 381 of 1166 (33%) patients died. Overall 30-day survival was 68%; 2 and 3-month overall survival probabilities were 56% and 53%, respectively. Survival was more favorable for patients with myeloproliferative neoplasms (82%, 69% and 65% at 30-days, 2 and 3 months, respectively) than for those with lymphoid malignancies (68%, 56% and 54%) or myelodysplastic syndrome/acute myeloid leukemia (61%, 51%, 46%), p=001. 285 (37%) patients died in the early period vs 96 (24%) in the later, p & lt;0.001, but median (interquartile range) follow-up time was much higher in the early vs later, 45 (20-116) days vs. 26 (11-86), respectively. Overall survival was not different between periods, p=0.5 (hazard ratio [95%C], 0.93 [0.73-1.17] ). In the later cohort, 30 and 60-day survival probabilities were 71% and 56% vs. 67% and 56% in the early cohort Conclusions. A population-based registry in Spain provided strong evidence that although COVID-19 severity decreased over year 1 of the pandemic, mortality remained high, and survival was stable over time in the group of patients with hematological malignancy infected by SARS-Coc-2. A relevant proportion of the infected patients (1 in 6) referred persistent symptoms attributable to COVID-19. The improved clinical management of severe COVID-19 in non-cancer patients that followed the dissemination of evidence-based recommendations did not translate in more favorable survival in patients with hematological malignancies. Research is needed to address the specific characteristics and improve the clinical management of this vulnerable population. Disclosures Martinez-Lopez: Novartis: Consultancy, Speakers Bureau; BMS: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Incyte: Consultancy, Research Funding, Speakers Bureau; Roche: Consultancy, Research Funding, Speakers Bureau; Astellas: Research Funding, Speakers Bureau. Jiménez-Yuste: Pfizer: Consultancy, Honoraria, Research Funding; Grifols: Consultancy, Honoraria, Research Funding; CSL Behring: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; Bayer: Consultancy, Honoraria, Research Funding; NovoNordisk: Consultancy, Honoraria, Research Funding; BioMarin: Consultancy; Sobi: Consultancy, Honoraria, Research Funding; Octapharma: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding. Kwon: Gilead: Honoraria.