To describe the cumulative incidences of adverse drug reactions (ADRs) associated with disease-modifying anti-rheumatic drugs (DMARDs) in rheumatoid arthritis (RA) patients from real-world data (RW...

Aims: Sunitinib exhibits considerable interindividual variability in exposure. While the target total plasma concentration of sunitinib and its active metabolite is 50–87.5 ng/mL for the intermittent dosing schedule, ~10–21% of patients experience higher exposures (>87.5 ng/mL), correlated with an increased risk for toxicity. Previous research identified single nucleotide variants (SNVs) in genes from the sunitinib pharmacokinetic pathway to be associated with efficacy and toxicity. However, significant interindividual variability in exposure remains unexplained. Our aim was to identify genetic variants associated with supratherapeutic exposure of sunitinib.Methods: This was a genome‐wide association study. Cases were identified during routine therapeutic drug monitoring and consisted of patients with dose‐normalized sunitinib plasma concentrations >87.5 ng/mL (intermittent dosing) or >75 ng/mL (continuous dosing). Controls were sampled from the historical cohort EuroTARGET who tolerated the standard dose of 50 mg in an intermittent schedule. SNVs were tested for an association with sunitinib exposure. A P‐value ≤5 × 10⁻⁸ was considered significant and a P‐value between 5 × 10⁻⁸ and 5 × 10⁻⁶ was considered suggestive.Results: Sixty‐nine cases and 345 controls were included for association analysis. One SNV (rs6923761), located on the gene glucagon‐like peptide 1 receptor, was significantly associated with increased sunitinib exposure (P = 7.86 × 10⁻¹⁹). Twelve SNVs were suggestive for an association with sunitinib exposure (P ≤ 5 × 10⁻⁶).Conclusions: While rs6923761 is associated with high sunitinib exposure, the underlying mechanism is not yet clarified and warrants further investigation. [Corrections made on 23 September 2024, after first online publication: In the preceding sentence, identifier rs6923671 has been changed to rs6923761 in this version.] We could not confirm the earlier found associations between SNVs in candidate genes involved in the pharmacokinetic pathway of sunitinib and its efficacy and toxicity.

Aims: With the rising number of oral targeted oncolytics and growing awareness of the benefits of therapeutic drug monitoring (TDM) within the field of oncology, it is expected that the requests for quantifying concentrations of these drugs will increase. It is important to (cross‐)validate available assays and ensure its quality, as results may lead to altered dosing recommendations. Therefore, we aimed to evaluate the performance of laboratories measuring concentrations of targeted oral oncolytics in a one‐time international quality control (QC) programme.Methods: Participating laboratories received a set of plasma samples containing low, medium and high concentrations of imatinib, sunitinib, desethylsunitinib, pazopanib, cabozantinib, olaparib, enzalutamide, desmethylenzalutamide and abiraterone, with the request to report their results back within five weeks after shipment. Accuracy was defined acceptable if measurements where within 85%–115% from the weighed‐in reference concentrations. Besides descriptive statistics, an exploratory ANOVA was performed.Results: Seventeen laboratories from six countries reported 243 results. Overall, 80.7% of all measurements were within the predefined range of acceptable accuracy. Laboratories performed best in quantifying imatinib and poorest in quantifying desethylsunitinib (median absolute inaccuracy respectively 4.0% (interquartile range (IQR) 1.8%–6.5%) and 15.5% (IQR 8.8%–34.9%)). The poorest performance of desethylsunitinib might be caused by using the stable‐isotope‐labelled sunitinib instead of desethylsunitinib as an internal standard, or due to the light‐induced cis(Z)/trans(E) isomerization of (desethyl)sunitinib. Overall, drug substance and performing laboratory seemed to influence the absolute inaccuracy (F = 16.4; p < 0.001 and F = 35.5; p < 0.001, respectively).Conclusion: Considering this is the first evaluation of an international QC programme for oral targeted oncolytics, an impressive high percentage of measurements were within the predefined range of accuracy. Cross‐validation of assays that are used for dose optimization of oncolytics will secure the performance and will protect patients from incorrect advices.

Imatinib plasma trough concentrations are associated with efficacy for patients treated for advanced or metastatic KIT-positive gastrointestinal stromal tumours (GISTs). This relationship has not been studied for patients treated in the neoadjuvant setting, let alone its correlation with tumour drug concentrations. In this exploratory study we aimed to determine the correlation between plasma and tumour imatinib concentrations in the neoadjuvant setting, investigate tumour imatinib distribution patterns within GISTs, and analyse its correlation with pathological response. Imatinib concentrations were measured in both plasma and in three regions of the resected primary tumour: the core, middle part, and periphery. Twenty-four tumour samples derived from the primary tumours of eight patients were included in the analyses. Imatinib tumour concentrations were higher compared to plasma concentrations. No correlation was observed between plasma and tumour concentrations. Interpatient variability in tumour concentrations was high compared to interindividual variability in plasma concentrations. Although imatinib accumulates in tumour tissue, no distribution pattern of imatinib in tumour tissue could be identified. There was no correlation between imatinib concentrations in tumour tissue and pathological treatment response.

Pazopanib is an oral tyrosine kinase inhibitor used in patients with either metastatic renal cell carcinoma or soft tissue sarcoma. Pazopanib has a high interindividual variability in pharmacokinetics and pharmacodynamics and a well‐established exposure–response relationship. Therefore, therapeutic drug monitoring is recommended to improve the efficacy–toxicity balance. Intra‐patient variability in pazopanib pharmacokinetics is moderate with a mean of 24.7%. In other fields, such as transplantation medicine, a high intra‐patient variability of immunosuppressive drugs has previously been associated with worse outcomes. Whether this also applies to therapeutic modalities in oncology is unknown. The aim of this study was to explore the relationship between pazopanib intra‐patient variability and clinical outcomes. Data from patients diagnosed with either metastatic renal cell carcinoma or soft tissue sarcoma treated with pazopanib guided by routine therapeutic drug monitoring with at least three available pazopanib trough concentrations were retrieved. Non‐dose corrected estimated trough concentrations were used to calculate intra‐patient variability. Among 144 patients, median intra‐patient variability was 30.2%. The high intra‐patient variability group (intra‐patient variability > 30.2%) was at risk for worse progression‐free survival (HR 1.42; 95% CI 0.85–2.35) and overall survival (HR 2.17; 95% CI 1.10–4.29) in patients with renal cell carcinoma. No association between a high intra‐patient variability and clinical outcomes for patients with soft tissue sarcoma could be established. Our results show that high intra‐patient variability is associated with poorer treatment outcomes. A high intra‐patient variability urges the treating clinician to address therapy adherence, drug–drug and food–drug interactions, and improve chances for optimal treatment outcome.