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Background Patients with lymphoid malignancies are at risk for poor coronavirus disease 2019 (COVID-19)-related outcomes and have reduced vaccine-induced immune responses. Currently, a 3-dose primary regimen of mRNA vaccines is recommended in the United States for immunocompromised hosts. Methods A prospective cohort study of healthy adults (n  = 27) and patients with lymphoid malignancies (n  = 94) was conducted, with longitudinal follow-up through completion of a 2- or 3-dose primary mRNA COVID vaccine series, respectively. Humoral responses were assessed in all participants, and cellular immunity was assessed in a subset of participants. Results The rate of seroconversion (68.1% vs 100%) and the magnitude of peak anti-S immunoglobulin G (IgG) titer (median anti-S IgG = 32.4, IQR = 0.48–75.0 vs median anti-S IgG = 72.6, IQR 51.1–100.1; P  = .0202) were both significantly lower in patients with lymphoid malignancies compared to the healthy cohort. However, peak titers of patients with lymphoid malignancies who responded to vaccination were similar to healthy cohort titers (median anti-S IgG = 64.3; IQR, 23.7–161.5; P  = .7424). The third dose seroconverted 7 of 41 (17.1%) patients who were seronegative after the first 2 doses. Although most patients with lymphoid malignancies produced vaccine-induced T-cell responses in the subset studied, B-cell frequencies were low with minimal memory cell formation. Conclusions A 3-dose primary mRNA series enhanced anti-S IgG responses to titers equivalent to healthy adults in patients with lymphoid malignancies who were seropositive after the first 2 doses and seroconverted 17.1% who were seronegative after the first 2 doses. T-cell responses were present, raising the possibility that the vaccines may confer some cell-based protection even if not measurable by anti-S IgG. [ABSTRACT FROM AUTHOR]

Correctly allocating times to the main activities of a manager is a crucial task that directly affects the possibility of success for any company. Decision support based on state-of-the-art methods can lead to better performance in this activity. However, allocating times to managerial activities is not straightforward; the decision support should provide a flexible recommendation so the manager can make a final decision while ensuring robustness. This paper describes and assesses a novel approach where a search for the best distribution of the manager's time is performed by an intelligent decision support system. The approach consists of eliciting manager preferences to define the value of the manager's main activities and, by using a portfolio-like optimization based on differential evolution, obtaining the best time allocation. Aiming at applicability in practical scenarios, the approach can deal with many activities, group decisions, cope with imprecision, vagueness, ill-determination, and other types of uncertainty. We present evidence of the approach's applicability exploiting a real case study with the participation of several managers. The approach is assessed through the satisfaction level of each manager. [ABSTRACT FROM AUTHOR]