Background: Mexico and Central America have a high incidence of acute lymphoblastic leukemia (ALL) in adolescents and young adults (AYA). Chemotherapy with Hyper-CVAD has been widely used with poor outcomes, with a 3-year overall survival (OS) of 25.7% in this group of age. In low-and middle-income countries (LMIC), limitations in supportive care such as low access to neutrophil stimulant agents, antifungal prophylaxis and limited intensive care access, may increase treatment-related mortality. On the other hand, reports suggest that specific high-risk subgroups may be more frequent in Hispanic patients from Mexico and Central America. We hypothesize that the use of a less-myeloablative regimen, based on L-asparaginase could overcome the bad outcomes previously reported. Methods We modified the original CALGB 10403 based on local drug-access. We include patients with newly diagnosed Philadelphia-negative B- or T-cell ALL between 14-49 years from 4 centers in Mexico and one in Guatemala. We modified the regimen as following: replaced pegaspargase by E. Coli asparaginase, thioguanine by 6-mercapatopurine and incorporate rituximab 375mg/m2 for 6 doses in CD20 positive patients. After the first interim analysis (October 2019), we replaced the prednisone by dexamethasone during induction. Minimal residual disease (MRD) was assessed by flow cytometry after induction and after first consolidation. We considered high-risk karyotype if MLL-rearrangements, complex or hypodiploid and high-white blood cell count (WBC) if >30 x10 3/mcL for B-ALL or >100 x10 3/mcL for T-ALL. The main objective was to evaluate OS and as secondary objectives to evaluate complete response (CR) rate, relapse-free survival (RFS) and to assess the safety of this regimen. Results From January 2017 to December 2020, 95 patients have been enrolled with a median age of 23 years (range 14-49). One third (34.6%) had overweight and 11.7% were obese. The majority (92.6%) had a B-cell ALL and a normal karyotype (81.2%). The median WBC was 18.4 x10 3/mcL (0.2-427.7) and 40.9% had a high-WBC. During induction, adverse events (AE) included grade 3/4 elevated bilirubin (21.1%), transaminases (14.7%), hyperglycemia (14.7%), hypofibrinogenemia (44.2%), thrombosis (10.5%), hypersensitivity (2.2%) and pancreatitis (2.1%). During consolidation, AE included grade 3/4 hepatic toxicity (18.9%), hypertriglyceridemia (14.8%), thrombosis (5.3%) and pancreatitis (2.1%). Neutropenic fever occurred in 55.8% during induction (grade 4: 31.5%), and in 32.9% during consolidation (grade 4/5: 5.3%). A dose adjustment due to AE was required in 22.1% during induction and in 23.2% during consolidation. The induction related-mortality (IRM) rate was 7.4% The CR rate was 87.8%. After-induction, MRD was <0.01% in 39.1%, 0.01-0.1% in 39.1% and > 0.1% in 24.6%. Post-consolidation MRD was only measured in 43 patients and was <0.01% in 37.2%. During follow-up, 26.7% relapsed: 62.5% bone marrow (BM) relapses, 25.0% central nervous system (CNS) relapses and 12.5% CNS + BM relapses. Eight patients (8.4%) received an allogeneic-stem cell transplant (HSCT) as consolidation. The 2-year OS was 72.1%. The post-induction MRD <0.1% was associated with a better OS (figure 1A) (HR: 0.17 (95%CI: 0.06-0.55), p=0.003) and a high-WBC with an inferior OS (figure 1B) (HR: 4.13 (95%CI: 1.68-10.14), p=0.002). The 2-year RFS was 65.2%. The post-induction MRD <0.1% was associate with a better RFS (figure 1C) (HR: 0.19 (95%CI: 0.07-0.50), p=0.001) and a high-WBC and overweight / obesity with an inferior RFS (HR: 4.08 (95%CI: 1.71-9.73), p=0.001 and 2.50 (95%CI: 1.06-5.86), p=0.036 respectively) (figure 1D). Conclusions: The adoption of modified CALGB10403 regimen in Central America based on local resources is feasible. It is associated with a significant improvement in the OS and decrease in IRM when compared with previous reports. Despite a very high-rate of hepatic and metabolic toxicities, these were manageable. As reported by other groups, MRD, high-WBC and overweight/obesity are associated with poor outcomes. Despite being encouraging results, a significant number of patients persist with positive MRD and the main cause of dead is disease progression. Access to cellular therapies, and BiTes is cost restricted in LMIC. Hence, we should generate strategies to intensify treatment in MRD positive patients and expand transplant access to overcome outcomes. Figure 1 Figure 1. Disclosures Rangel-Patiño: Bristol: Consultancy; Abbvie: Speakers Bureau. Ceniceros: Amgen: Speakers Bureau. Espinosa: Amgen: Speakers Bureau; Janssen: Consultancy; Pfizer: Consultancy. Amador: Abbvie: Consultancy, Speakers Bureau; Bristol: Consultancy. Cabrero Garcia: Takeda: Speakers Bureau; Abbvie: Speakers Bureau; Roche: Speakers Bureau; Janssen: Speakers Bureau; Astellas: Consultancy; BD: Speakers Bureau. Inclan-Alarcon: Janssen: Speakers Bureau; Boehringer: Speakers Bureau. Neme Yunes: Janssen: Consultancy, Speakers Bureau; Bristol: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Bristol: Consultancy, Speakers Bureau; Abbvie: Consultancy, Speakers Bureau; Abbvie: Speakers Bureau. Meillon-García: Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Roche: Speakers Bureau; Astellas: Consultancy. Apodaca: Sanofi: Consultancy; Asofarma: Consultancy, Speakers Bureau; Abbvie: Speakers Bureau. Demichelis: Bristol/Celgene: Consultancy, Speakers Bureau; Astellas: Consultancy; Gilead: Consultancy; ASH: Research Funding; Abbvie: Consultancy, Speakers Bureau; AMGEN: Consultancy, Speakers Bureau; Novartis: Consultancy, Research Funding, Speakers Bureau; Jazz: Consultancy.
Background Understanding non-epidemiological factors is essential for the surveillance and prevention of infectious diseases, and the factors are likely to vary spatially and temporally as the disease progresses. However, the impacts of these influencing factors were primarily assumed to be stationary over time and space in the existing literature. The spatiotemporal impacts of mobility-related and social-demographic factors on disease dynamics remain to be explored. Methods Taking daily cases data during the coronavirus disease 2019 (COVID-19) outbreak in the US as a case study, we develop a mobility-augmented geographically and temporally weighted regression (M-GTWR) model to quantify the spatiotemporal impacts of social-demographic factors and human activities on the COVID-19 dynamics. Different from the base GTWR model, the proposed M-GTWR model incorporates a mobility-adjusted distance weight matrix where travel mobility is used in addition to the spatial adjacency to capture the correlations among local observations. Results The results reveal that the impacts of social-demographic and human activity variables present significant spatiotemporal heterogeneity. In particular, a 1% increase in population density may lead to 0.63% more daily cases, and a 1% increase in the mean commuting time may result in 0.22% increases in daily cases. Although increased human activities will, in general, intensify the disease outbreak, we report that the effects of grocery and pharmacy-related activities are insignificant in areas with high population density. And activities at the workplace and public transit are found to either increase or decrease the number of cases, depending on particular locations. Conclusions Through a mobility-augmented spatiotemporal modeling approach, we could quantify the time and space varying impacts of non-epidemiological factors on COVID-19 cases. The results suggest that the effects of population density, socio-demographic attributes, and travel-related attributes will differ significantly depending on the time of the pandemic and the underlying location. Moreover, policy restrictions on human contact are not universally effective in preventing the spread of diseases.
Introduction The COVID-19 pandemic has affected the entire world. Health systems have been affected in such a way that patients with diseases other than COVID-19 have suffered serious consequences. In Latin America, the disease has emerged in a fragile system with more disparities, making our patients more vulnerable. Acute leukemia patients have a high risk of severe COVID-19 disease. Various expert recommendations have emerged with the aim of minimizing the risk of COVID-19 without affecting leukemia-related outcomes. However, multiple logistical issues tangentially associated with the pandemic have also appeared, potentially limiting the quality of management of these patients. The objective of this study was to register treatment modifications associated with the COVID-19 pandemic and its short-term consequences in Latin American countries. Methods We included patients older than 14 years, from 14 centers of 4 Latin American countries (Mexico, Peru, Guatemala and Panama), with the diagnosis of acute leukemia, who were on active treatment since the first case of COVID-19 was documented in each country. We documented their baseline characteristics and followed the patients prospectively until July 15, were data-cutoff for this pre-planned analysis was performed. The primary outcome was the incidence of COVID-19 disease and its complications. Secondary outcomes included treatment and consult modifications, and cause of death during the study period. Logistic regression was performed to determine factors associated with COVID-19 and all-cause mortality. Results We recorded the information of 635 patients: 58.1% Ph-negative ALL, 25.7% AML, 9% APL and 7.2% Ph+ALL. The median age was 35 years (14-90 years); 58.8% were consideredf high-risk patients. The majority were on CR (68.3%) receiving consolidation or maintenance therapy, while 14.5% were newly diagnosed and 17.2% with relapsed/refractory disease. The majority (91.8%) were treated in centers that were also receiving COVID-19 patients, 40.2% in centers were patients could not be electively hospitalized for leukemia treatment because of the COVID-19 pandemic. The COVID-pandemic led to treatment-modifications in 40.8% of the cases. Reasons for modifications were associated with logistical issues (22.4%), medical decisions (15.1%) or patient choice (3.3%). The most frequent modification was chemotherapy delay (17.3%) followed by regimen modification (13.4%) and dose-reductions (10.1%). (Figure 1) 83 patients (13.1%) developed COVID-19 disease, the majority mild-moderate disease (54.2%), 27.7% severe disease and 18.1% critically ill; 27.7% required mechanical ventilation and 37.7% died from COVID-19 disease, representing 4.9% of the entire cohort. We identify as risk factors for COVID-19 disease the presence of active leukemia (newly diagnosed or relapsed) (OR 3.46 [95% CI: 2.16-5.5], p<0.001), high-risk leukemia (OR 1.63 [95% CI: 1.54-4.52], p<0.001) and being treated in a center were elective hospitalization was possible (OR 2.17 [95% CI 1.29-3.67], p=0.004). Treatment modifications, appointment prolongations or the use of virtual consultation were not associated with a reduction in the risk of COVID-19. On the other hand, 16.7% of patients died during period analyzed due to leukemia (57.5%), COVID-19 (29.2%) or treatment related-mortality (13.2%). Independent factors associated with mortality were AML vs. ALL (OR 1.89 [95% CI: 1.12-3.18], p=0.016), relapsed-refractory disease (OR 8.34 [95% CI: 4.83-14.41], p<0.001), induction/consolidation vs. maintenance therapy (OR 2.20 [95% CI: 1.25-3.18], p<0.001) and the use of virtual consultation (OR 0.35 [95% CI: 0.13-0.94] p=0.037). (Table 1) Discussion/Conclusions The COVID-19 pandemic led to significant modifications in the standard of care treatment of patients with acute leukemia. The incidence of COVID-19 disease in acute leukemia patients was considerable and more than a third of the patients with acute leukemia and COVID-19 disease died. Despite a short-follow up, 16.7% of the patients died and leukemia-related deaths were the most frequent. In low- and middle-income countries with fragile health systems, the collateral damage for patients with acute leukemia may be just as important as the direct consequences of COVID-19. Disclosures Alvarado: Roche: Speakers Bureau; Novartis: Speakers Bureau; Amgen: Speakers Bureau; Celgene: Speakers Bureau; Alexion: Speakers Bureau. De la Peña-Celaya:Amgen: Speakers Bureau; Janssen: Speakers Bureau; Novartis: Speakers Bureau. Perez:Roche: Speakers Bureau; Celgene: Speakers Bureau; Novartis: Speakers Bureau. Gomez-Almaguer:Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.