Peripheral T-cell lymphomas (PTCLs) are a heterogeneous group of haematological cancers with generally poor clinical outcomes. However, a subset of patients experience durable disease control, and ...little is known regarding long-term outcomes. The International T-cell Lymphoma Project (ITCLP) is the largest prospectively collected cohort of patients with PTCLs, providing insight into clinical outcomes at academic medical centres globally. We performed a long-term outcome analysis on patients from the ITCLP with available 10-year follow-up data (n = 735). The overall response rate to first-line therapy was 68%, while 5- and 10-year overall survival estimates were 49% and 40% respectively. Most deaths occurred prior to 5 years, and for patients alive at 5 years, the chance of surviving to 10 years was 84%. However, lymphoma remained the leading cause of death in the 5- to 10-year period (67%). Low-risk International Prognostic Index and Prognostic Index for T-cell lymphoma scores both identified patients with improved survival, while in multivariate analysis, age >60 years and Eastern Cooperative Oncology Group performance status 2-4 were associated with inferior outcomes. The favourable survival seen in patients achieving durable initial disease control emphasizes the unmet need for optimal front-line therapeutic approaches in PTCLs.
The introduction of agents such as thalidomide, lenalidomide, and bortezomib has changed the management of patients with multiple myeloma who are not eligible for autologous transplantation, many of ...whom are elderly. We sought to compare three thalidomide-based oral regimens among such patients in Latin America. We randomized patients with newly diagnosed multiple myeloma with measurable disease to one of the following regimens: melphalan, prednisone, and thalidomide (MPT); cyclophosphamide, thalidomide, and dexamethasone (CTD); and thalidomide and dexamethasone (TD). The TD arm was closed prematurely and was analyzed only descriptively. The primary endpoint was the overall response rate (ORR), whereas progression-free survival (PFS) and overall survival (OS) were secondary endpoints. The accrual rate was slower than expected, and the study was terminated after 82 patients had been randomized. The ORRs were 67.9 % with MPT, 89.7 % with CTD, and 68.7 % with TD (
p
= 0.056 for the comparison between MPT and CTD). The median PFS was 24.1 months for MPT, 25.9 months for CTD, and 21.5 months for TD. There were no statistically significant differences in PFS or OS between MPT and CTD. In an unplanned logistic regression analysis, ORR was significantly associated with treatment with CTD (
p
= 0.046) and with performance status of 0 or 1 (
p
= 0.035). Based on the current results, no definitive recommendations can be made regarding the comparative merit of the regimens tested. Nevertheless and until the results of further studies become available, we recommend either CTD or MPT as suitable frontline regimens for patients with multiple myeloma who are not candidates to transplantation in settings where lenalidomide and bortezomib are not available.
Background
Accurate prediction of stem cell yield is important for planning leukapheresis procedures. A formula has been published (Pierelli et al., Vox Sang 2006;91:126‐34) to estimate the CD34+ ...dose collected on the first day of leukapheresis that was based on the preapheresis peripheral blood (PB) CD34+ counts, the blood volume processed, and the donor's weight. The aim of this study was to assess the predictive value of this formula.
Study Design and Methods
Data were retrospectively collected on 1126 consecutive PB stem cell harvests conducted at five institutions. Information on age, sex, diagnosis, weight, preapheresis absolute peripheral CD34+ count, total blood volume processed, and CD34+ cells harvested per kilogram of body weight on the first day of apheresis was collected.
Results
Among donors at least 18 years old, Pearson's correlation coefficient (r) between actual yield (AY) and predicted yield (PY) was 0.76. To characterize this correlation, AY and PY were classified as being within the conventionally acceptable CD34+ doses (>2 × 106‐5 × 106 cells/kg), below this range (≤2 × 106 cells/kg), or above it (>5 × 106 cells/kg). The positive predictive value (PPV) of PY was estimated considering the distribution of AY as the “gold standard.” PPV was relatively high for PY of more than 5 × 106 cells/kg (85%), moderate for PY of not more than 2 × 106 cells/kg (72%), and low for PY more than 2 × 106 to 5 × 106 cells/kg (56%). A consistent pattern was observed within institutions.
Conclusion
The formula of Pierelli et al. is associated with a PPV that is high, moderate, and relatively low for the corresponding predicted CD34+ doses.
Background: The Checklist During Multidisciplinary Visits for Reduction of Mortality in Intensive Care Units (Checklist- ICU) trial is a pragmatic, two-arm, cluster-randomised trial involving 118 ...intensive care units in Brazil, with the primary objective of determining if a multifaceted qualityimprovement intervention with a daily checklist, definition of daily care goals during multidisciplinary daily rounds and clinician prompts can reduce inhospital mortality.
Objective: To describe our trial statistical analysis plan (SAP).
Methods: This is an ongoing trial conducted in two phases. In the preparatory observational phase, we collect three sets of baseline data: ICU characteristics; patient characteristics, processes of care and outcomes; and completed safety attitudes questionnaires (SAQs). In the randomised phase, ICUs are assigned to the experimental or control arms and we collect patient data and repeat the SAQ.
Results: Our SAP includes the prespecified model for the primary and secondary outcome analyses, which account for the cluster-randomised design and availability of baseline data. We also detail the multiple mediation models that we will use to assess our secondary hypothesis (that the effect of the intervention on inhospital mortality is mediated not only through care processes targeted by the checklist, but also through changes in safety culture). We describe our approach to sensitivity and subgroup analyses and missing data.
Conclusion: We report our SAP before closing our study database and starting analysis. We anticipate that this should prevent analysis bias and enhance the utility of results.
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