[Polymedication and oral antitumour therapies - which drug interactions should be considered?]

INTRODUCTION: Oral anticancer therapies offer various advantages but also entail risks due to their toxicity and narrow therapeutic ranges. Since these drugs are increasingly prescribed in patients with existing polypharmacy, identifying and assessing potential drug interactions is of great importance for safe and effective therapy. This article provides an overview of the most common pharmacokinetic and pharmacodynamic drug-drug interactions of targeted anticancer therapies, with focus on protein kinase inhibitors.

Pre-treatment comorbidities, C-reactive protein and eosinophil count, and immune-related adverse events as predictors of survival with checkpoint inhibition for multiple tumour entities.

BACKGROUND: The development of immune-related adverse events (irAEs) may be associated with clinical efficacy of checkpoint inhibitors (CPIs) in patients with cancer. We therefore investigated the effect of irAEs and pre-treatment parameters on outcome in a large, real-life patient cohort. METHODS: We performed a single-centre, retrospective, observational study including patients who received CPIs from 2011 to 2018 and followed until 2021. The primary outcome was overall survival, and the secondary outcome was the development of irAEs. RESULTS: In total, 229 patients with different tumour entities (41% non-small cell lung cancer [NSCLC], 29% melanoma) received a total of 282 CPI treatment courses (ipilimumab, nivolumab, pembrolizumab or atezolizumab). Thirty-four percent of patients developed irAEs (of these 17% had CTCAE Grade ≥3). Factors independently associated with mortality were pre-treatment CRP ≥10 mg/L (hazard ratio [HR] 2.064, p = 0.0003), comorbidity measured by Charlson comorbidity index (HR 1.149, p = 0.014) and irAEs (HR 0.644, p = 0.036) (age-adjusted, n = 216). Baseline eosinophil count ≤0.2 × 109 /L was a further independent predictor of mortality (age-, CRP-, CCI- and irAE-adjusted HR = 2.252, p = 0.002, n = 166). Anti-CTLA-4 use (p < 0.001), and pre-treatment CRP <10 mg/L were independently associated with irAE occurrence (p = 0.037). CONCLUSIONS: We found an independent association between irAE occurrence and improved overall survival in a real-life cohort spanning multiple tumour entities and treatment regimens. Pre-treatment comorbidities, CRP and eosinophil count represent potential markers for predicting treatment response.

Disease-Drug Interactions Requiring Special Attention.

This short review addresses disease-drug interactions requiring special attention, namely interactions between common conditions and over-the-counter medication and interactions between rare conditions and drugs that are absolutely contraindicated. We specifically examine over-the-counter analgesics, antiemetics and drugs used to treat allergy symptoms and underlying disease conditions they can exacerbate. Resources for avoiding disease-drug interactions in patients with rare conditions, such as myasthenia gravis, glucose-6-phosphate deficiency, mitochondriopathies and long QT-syndrome are given. We also discuss methods for avoiding disease-drug interactions in clinical practice. These include awareness, regular diagnosis- and drug-history taking, consulting the product information, good communication between healthcare providers and patient education. Furthermore, pharmacovigilance activities help in the early identification and characterization of adverse drug reactions resulting from disease-drug interactions.

Gastrointestinal bleeding during anticoagulation with direct oral anticoagulants compared to vitamin K antagonists.

Aim: Patients receiving oral anticoagulants with vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs) have an increased risk of gastrointestinal bleeding (GIB). We compared cases of GIB associated with VKAs and DOACs in terms of risk factors, scores, timing, location, severity, and outcome. Methods: Data from patients treated at a university hospital in Switzerland for GIB under VKA and DOACs between 2012 and 2018 were analyzed in this investigator-driven, retrospective, single-center study. Results: A total of 248 patients (110 males; median age, 80 years; 134 VKA, 114 DOAC) were included. No significant differences in age, weight or sex were observed. The propensity of the VKA group for risk factors such as comorbidities, interacting medications, or a high risk for bleeding (HAS-BLED score) was higher than that of the DOAC group. 56% of the VKA-treated patients had a supratherapeutic INR, and 25% in the DOAC group received an unlicensed dose. Significantly more patients in the DOAC group were not formally overdosed with OAC whilst receiving amiodarone compared to the VKA group (57% vs. 18%, respectively, p = 0.03). Latency between the documented start of oral anticoagulation and GIB was shorter in the DOAC group (median 3 months) than in the VKA group (median 23.5 months, p¡0.001). There were no differences in terms of location and severity of the GIB, length of hospitalization, or mortality. Conclusion: Patients taking VKAs displayed more risk factors for GIB than those taking DOACs. Treatment with DOACs was associated with early GIB and calls for increased vigilance during the first months after commencement. Co-medication with amiodarone appeared to be a risk factor for GIB in patients taking DOACs.

Activity-based costing methodology as tool for costing in hematopathology laboratory.

BACKGROUND: Cost analysis in laboratories represents a necessary phase in their scientific progression. AIM: To calculate indirect cost and thus total cost per sample of various tests at Hematopathology laboratory (HPL). SETTINGS AND DESIGN: Activity-based costing (ABC) method is used to calculate per cost test of the hematopathology laboratory. MATERIAL AND METHODS: Information is collected from registers, purchase orders, annual maintenance contracts (AMCs), payrolls, account books, hospital bills and registers along with informal interviews with hospital staff. RESULTS: Cost per test decreases as total number of samples increases. Maximum annual expense at the HPL is on reagents and consumables followed by manpower. Cost per test is higher for specialized tests which interpret morphological or flow data and are done by a pathologist. CONCLUSIONS: Despite several limitations and assumptions, this was an attempt to understand how the resources are consumed in a large size government-run laboratory. The rate structure needs to be revised for most of the tests, mainly for complete blood counts (CBC), bone marrow examination, coagulation tests and Immunophenotyping. This costing exercise is laboratory specific and each laboratory needs to do its own costing. Such an exercise may help a laboratory redesign its costing structure or at least understand the economics involved in the laboratory management.