Many studies have shown that the efficacy and risk of side effects of drug treatment is influenced by genetic variants. Evidence based guidelines are essential for implementing pharmacogenetic knowledge in daily clinical practice to optimize pharmacotherapy of individual patients. A literature search was performed to select committees developing guidelines with recommendations being published in English. The Dutch Pharmacogenetics Working Group (DPWG), the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and the French National Network (Réseau) of Pharmacogenetics (RNPGx) were selected. Their guidelines were compared with regard to the methodology of development, translation of genotypes to predicted phenotypes, pharmacotherapeutic recommendations and recommendations on genotyping. A detailed overview of all recommendations for gene-drug combinations is given. The committees have similar methodologies of guideline development. However, the objectives differed at the start of their projects, which have led to unique profiles and strengths of their guidelines. DPWG and CPIC have a main focus on pharmacotherapeutic recommendations for a large number of drugs in combination with a patient’s genotype or predicted phenotype. DPWG, CPNDS and RNPGx also recommend on performing genetic testing in daily clinical practice, with RNPGx even describing specific clinical settings or medical conditions for which genotyping is recommended. Discordances exist, however committees also initiated harmonizing projects. The outcome of a consensus project was to rename “extensive metabolizer (EM)” to “normal metabolizer (NM)”. It was decided to translate a CYP2D6 genotype with one nonfunctional allele (activity score 1.0) into the predicted phenotype of intermediate metabolizer (IM). Differences in recommendations are the result of the methodologies used, such as assessment of dose adjustments of tricyclic antidepressants. In some cases, indication or dose specific recommendations are given for example for clopidogrel, codeine, irinotecan. The following drugs have recommendations on genetic testing with the highest level: abacavir (HLA), clopidogrel (CYP2C19), fluoropyrimidines (DPYD), thiopurines (TPMT), irinotecan (UGT1A1), codeine (CYP2D6), and cisplatin (TPMT). The guidelines cover many drugs and genes, genotypes, or predicted phenotypes. Because of this and their unique features, considering the totality of guidelines are of added value. In conclusion, many evidence based pharmacogenetics guidelines with clear recommendations are available for clinical decision making by healthcare professionals, patients and other stakeholders.

Background: Chemotherapy‐induced toxicities frequently occur in non‐small cell lung cancer (NSCLC) patients treated with platinum‐based chemotherapy. Low skeletal muscle mass (SMM) has been associated with a higher incidence of toxicities for several types of cancers and cytostatics. The aim of this study was to evaluate the association between skeletal muscle measures and chemotherapy‐induced toxicity in a large cohort of NSCLC patients.Methods: A multicentre prospective follow‐up study (PGxLUNG, NTR number NL5373610015) in NSCLC patients was conducted. Included were patients diagnosed with NSCLC (stage II–IV) treated with first‐line platinum‐based (cisplatin or carboplatin) chemotherapy of whom pretreatment imaging was available. Skeletal muscle area (SMA) segmentation was performed on abdominal imaging at the level of the third lumbar vertebra (L3). SMA at the level of L3 was corrected for squared height (m²) to yield the lumbar skeletal muscle mass index (LSMI). Skeletal muscle density (SMD) was calculated as the mean Hounsfield Unit (HU) of the segmented SMA. SMM and SMD were categorized as low, intermediate, and high, based on LSMI and mean HU tertiles, respectively. Chemotherapy‐induced toxicity was scored using CTCAE v4.03 and categorized into haematological (anaemia, leukocytopenia, neutropenia, and thrombocytopenia), non‐haematological (nephrotoxicity, neurotoxicity, and esophagitis), and dose‐limiting toxicity (DLT) (treatment switch, delay, de‐escalation, discontinuation, or hospitalization). The relationship between SMM, SMD, and toxicities was assessed with logistic regression modelling taking into account potential confounders like gender and body mass index (BMI).Results: In total, 297 patients (male n = 167, median age 64 years) were included. Haematological toxicity grade 3/4 was experienced in 36.6% (n = 108) of the patients, 24.6% (n = 73) experienced any non‐haematological toxicity grade ≥2, and 55.6% (n = 165) any DLT. Multivariate logistic regression analysis showed that low SMM (ORadj 2.41, 95% CI 1.31–4.45, P = 0.005) and age at diagnosis >65 years (ORadj 1.76, 95% CI 1.07–2.90, P = 0.025) were statistically significantly associated with overall haematological toxicity grade 3/4. No statistically significant associations were found between low SMM or low SMD and non‐haematological toxicities. Low SMM (ORadj 2.23, 95% CI 1.23–4.04, P = 0.008) and high SMD (ORadj 0.41, 95% CI 0.23–0.74, P = 0.003) were statistically significantly associated with a higher respectively lower risk of DLT.Conclusions: Non‐small cell lung cancer patients with pretreatment low SMM are at significant higher risk for haematological toxicities grade 3/4 and DLT. NSCLC patients with high SMD are at significant lower risk for DLT. Further studies should be aimed to investigate whether platinum dosing based on skeletal muscle measurements and/or improvement of pretreatment SMM/SMD could reduce the risk of toxicity without compromising efficacy.

Background: In addition to radiological evaluation, biomarkers may be useful in providing early information on the response to treatment, and supporting clinical decision‐making. The objective of this study was to investigate carcinoembryonic antigen (CEA) and lactate dehydrogenase (LDH) as biomarkers for early assessment of response in patients with advanced non‐small cell lung cancer (NSCLC) treated with platinum‐based chemotherapy.Methods: A retrospective follow‐up study was conducted from 2012 to 2017 among 593 consecutive patients with advanced NSCLC treated with first‐line platinum‐based chemotherapy in a large teaching hospital in the Netherlands. Pretreatment biomarker levels and changes from pretreatment levels were studied for association with radiologic response (partial response [PR] or complete response [CR], according to RECIST 1.1) using multivariate logistic regression, and with overall survival using COX proportional hazard modeling. Patient and disease characteristics such as age and disease stage were taken into account as potential confounding factors.Results: Decreases in CEA and LDH (≥ 20%), particularly early in treatment, were significantly associated with better radiological response. Increases in these biomarkers (≥ 20%) and high pretreatment LDH levels (≥ 247 U/L) were significantly associated with lower overall survival.Conclusions: Our results support determination of CEA and LDH levels for earlier assessment of response to platinum‐based chemotherapy in patients with advanced NSCLC. Hence, routine determination and evaluation of CEA and LDH levels, prior to each cycle of platinum‐based chemotherapy in advanced NSCLC, should be considered as part of daily clinical practice.Key points: Significant findings of the study: Serum biomarkers in monitoring of treatment in advanced NSCLC would be useful. CEA and LDH decrease (≥ 20%) is favorable for achieving radiological response. High LDH levels and CEA/LDH increase (≥ 20%) is associated with reduced survival. What this study adds: Monitoring of CEA seems to be particularly relevant in early stage of treatment. CEA and LDH determination should be considered as part of daily clinical practice.

Aim: A tailored antiplatelet strategy based on CYP2C19 genotype may reduce atherothrombotic and bleeding events. We describe our experience with CYP2C19 genotyping, using on-site TaqMan or Spartan genotyping or shipment to a central laboratory. Methodology: Data from two ongoing projects were used: Popular Risk Score project (non-urgent percutaneous coronary intervention patients) and the Popular Genetics study (ST-segment elevation myocardial infarction patients). For both projects, the time to genotyping result was calculated. Results: In the Popular Risk Score project (n = 2556), median time from blood collection to genotyping result was 4:04 h. In the Popular Genetics study (n = 1038), median time from randomization to genotyping result was 2:24 h. Conclusion: CYP2C19 genotyping is feasible in everyday clinical practice, both in the acute and non-acute settings.

Introduction: Preventing side effects is important to ensure optimal psychopharmacotherapy and therapeutic adherence among psychiatric patients. Obtaining the pharmacogenetic profile of CYP2C19 and CYP2D6 can play an important role in this. When the genotype-predicted phenotype shifts because of the use of co-medication, this is called phenoconversion. The aim was to study the influence of the pharmacogenetic (PGx) profile and phenoconversion on side effects experienced by psychiatric patients.Methods: A retrospective cohort study was performed using data from 117 patients from a psychiatric outpatient clinic. Patients were genotyped with a psychiatric PGx panel and side effects were evaluated using the Udvalg for Kliniske Undersølgelser side effects rating scale (UKU).Results: Of all patients, 10.3% and 9.4% underwent phenoconversion (any shift in predicted phenotype) for CYP2C19 and CYP2D6 respectively. No significant associations were found between the phenotype and UKU-score. 75% of the patients with an Intermediate metabolizer (IM) or Poor metabolizer (PM) phenoconverted phenotype of CYP2C19 experienced nausea and vomiting compared to 9.1% of the Normal metabolizer (NM) and Ultrarapid metabolizer (UM) patients (p = 0.033). 64% of the patients with an IM or PM phenoconverted phenotype of CYP2D6 experienced the side effect depression compared to 30.4% NMs and UMs (p = 0.020). CYP2D6 IM and PM patients had a higher concentration-dose ratio than NM patients (p < 0.05).Discussion: This study underlines the importance to consider phenoconversion when looking at a patient’s genotype. This is important for a better prediction of the phenotype and preventing possible side effects under a specific psychopharmacotherapy.