Assessment of the change of antiemetic prophylaxis from double to triple combination in patients with high dose carboplatin chemotherapy.

INTRODUCTION: Chemotherapy-induced nausea and vomiting (CINV) is one of the adverse events that most affects oncologic patients' quality of life. Carboplatin AUC ≥ 4 belongs to agents with high emetic risk (moderate risk in ASCO guidelines). We aimed to compare the effectiveness of netupitant/palonosetron and dexamethasone triple combination (TC) therapy versus ondansetron and dexamethasone double combination (DC) therapy as antiemetic prophylaxis in patients with carboplatin AUC ≥ 4. As a secondary endpoint, in TC group we evaluated the effectiveness of changing NEPA administration timing from 1 h to 15 min before chemotherapy. METHODS: Open-label prospective study conducted in a tertiary-care hospital in patients receiving carboplatin AUC ≥ 4. CINV was evaluated using MASCC antiemetic tool, in acute (<24 h) and delayed phase (24-120 h). Results were analyzed using χ2 test. RESULTS: Two-hundred four completed questionnaires (CQ) were analyzed (76 in DC and 128 in TC). The proportion of patients who remained emesis-free was superior for TC-treated group compared to DC, either in acute (99.2% vs 92.1%, p = 0.0115) and delayed phase (97.6% vs 90.7%, p = 0.043). Likewise, a higher proportion of TC-treated patients compared to DC remained nausea-free for the first 24 h after treatment (90.6% vs 71%, p = 0.0004) and between 24 and 120 h (82.3% vs 62.7%, p = 0.0025). The change of NEPA administration time showed similar effectiveness in terms of CINV control (81.6% vs 74.5%, p = 0.70). CONCLUSIONS: TC showed superiority in early and delayed CINV control in carboplatin AUC ≥ 4 regimens, with no significant differences among cancer types. Change in NEPA administration timing has beneficial implications; it allows NEPA to be administered at hospitals before chemotherapy session.

Real-world data of the use and experience of caplacizumab for the treatment of acquired thrombotic thrombocytopenic purpura: Case series.

PURPOSE: Caplacizumab was licensed for acquired thrombotic thrombocytopenic purpura (aTTP) based on prospective controlled trials. Real-world evidence is crucial in rare diseases. We aim to describe a patient population with aTTP, receiving caplacizumab in a real-world setting, reporting their outcomes, including safety and tolerability, and contrasting them with a historical cohort from our center. METHODS: We describe data collected retrospectively from 2012 to 2022 for 16 patients with aTTP (8 received caplacizumab and 8 the historical standard-of-care). Patients' characteristics and outcomes were compared between groups. RESULTS: Patients' demographic and baseline characteristics were similar in both groups. Caplacizumab led to a rapid normalization of the platelet count of 3.5 (IQR, 2-6) versus 16 (IQR, 9.5-23.5) days in the historical cohort: (p = .002). The median number of plasma exchanges and the length of days requiring them, between the caplacizumab group versus the historical cohort, was 6 (IQR, 6-10) versus 19.5 (IQR, 12.5-29.5) plasma exchanges (p = .006); and 9 (IQR, 8.5-13.5) versus 22 (15-31) days (p = .049), respectively. There were no refractory cases in the caplacizumab group in comparison with 37.5 % in the historical cohort. None of patients treated with caplacizumab experienced a recurrence after 1081 (IQR, 511-3125) days of follow-up. Safety was in line with data reported in clinical trials, with mild adverse events (mostly grade≤2). CONCLUSION: We provided real-world evidence in the treatment of aTTP, confirming the results obtained in clinical trials. Caplacizumab reduced the time to platelet count recovery and the number and length of plasma exchanges.

Robotic chemotherapy compounding: A multicenter productivity approach.

INTRODUCTION: The aim of this study is to compare productivity of the KIRO Oncology compounding robot in three hospital pharmacy departments and identify the key factors to predict and optimize automatic compounding time. METHODS: The study was conducted in three hospitals. Each hospital compounding workload and workflow were analyzed. Data from the robotic compounding cycles from August 2017 to July 2018 were retrospectively obtained. Nine cycle specific parameters and five productivity indicators were analysed in each site. One-to-one differences between hospitals were evaluated. Next, a correlation analysis between cycle specific factors and productivity indicators was conducted; the factors presenting a highest correlation to automatic compounding time were used to develop a multiple regression model (afterwards validated) to predict the automatic compounding time. RESULTS: A total of 2795 cycles (16367 preparations) were analysed. Automatic compounding time showed a relevant positive correlation (ǀrs|>0.40) with the number of preparations, number of vials and total volume per cycle. Therefore, these cycle specific parameters were chosen as independent variables for the mathematical model. Considering cycles lasting 40 minutes or less, predictability of the model was high for all three hospitals (R2:0.81; 0.79; 0.72). CONCLUSION: Workflow differences have a remarkable incidence in the global productivity of the automated process. Total volume dosed for all preparations in a cycle is one of the variables with greater influence in automatic compounding time. Algorithms to predict automatic compounding time can be useful to help users in order to plan the cycles launched in KIRO Oncology.

Drug interactions with oral antineoplastic drugs: The role of the pharmacist.

The main objective of the study is to determine the pharmacist detection of drug-drug and drug-food interactions in patients receiving oral antineoplastic drugs (OADs). Descriptive, prospective study in a tertiary-care teaching hospital. The study population included patients who received OADs from the Outpatient Pharmacy of the hospital. The study population was attended by a pharmacist who checked potential interactions. The severity of interactions was evaluated using the summary of product characteristics of each drug and three different databases. We included 219 patients with a total of 736 concomitant medications. A total of 34 drug-drug or food-drug interactions were recorded. The most common interaction detected was between erlotinib and ranitidine (major interaction). In 19 of the 34 interactions detected in the experimental group, the pharmacist prevented them from reaching the patient. Interactions were resolved by drug suspensions, drug changes, or changes in schedules always according to the attending physician or the patient. In the remaining 15 interactions, the doctor was not contacted because the interactions were considered to be of little relevance or because they only required surveillance. Hospital pharmacist can improve the patient's safety and the efficiency of oral cytostatic treatment by detecting and preventing drug-drug and drug-food interactions.