Association between olanzapine plasma concentrations and treatment response: A systematic review, meta-analysis and individual participant data meta-analysis.

AIMS: By meta-analysing pooled studies and available individual participant data, we aim to provide new insight on olanzapine therapeutic drug monitoring in schizophrenia. METHOD: We conducted a computerized search of bibliographic databases (Pubmed, Cochrane library, Web of Science and PsycINFO) to identify studies that assessed the relationship between olanzapine plasma concentration and the change in patients' clinical scores. We investigated this relationship with olanzapine plasma level 12h00 post-intake using a random-effects model. RESULTS: 7 studies were included in the pooled data analysis (781 patients). We found no difference in oral dose between responders and non-responders but a significantly higher concentration of 4.50 µg/L in responders (p < 0.01). Olanzapine concentration above the thresholds identified in each study was associated with response (odd ratio = 3.50, p = 0.0007). We identified that non-responder patients showed greater inter-individual variability than responders. In the individual data analysis (159 patients), we found no relationship between dose and clinical response but an association between plasma level and response in the shape of a parabolic curve. The Receiver Operating Characteristic curve found a threshold of 22.07 µg/L to identify responders (96% sensitivity, 86% specificity) and a threshold of 56.47 µg/L to identify a decreased probability of response. CONCLUSION: In contrast to oral dose, our work confirmed that plasma olanzapine levels are associated with clinical response and should therefore be used to optimise treatment. We determined a treatment response threshold of 22.07 µg/L and suggest that a concentration above the therapeutic window may result in a decreased response.

Simultaneous quantification of 55 psychotropic drugs and metabolites in human plasma with a fast UPLC-MS/MS method.

OBJECTIVES: Therapeutic drug monitoring is strongly recommended for psychotropic drugs, which present a strong inter- and intra-individual variability due to multiple factors like inflammatory state, smoking, diet, drug interactions due to polypharmacy, and genetic profile. The aim of this study was to develop and validate a fast, simple, and sensitive method allowing the simultaneous quantification of a large number of psychotropic drugs. METHODS: After a simple sample preparation with a one-step protein precipitation, a total of 55 compounds, including 22 antidepressants, 18 antipsychotics, 2 other psychotropic drugs (bupropion and nefopam), and their metabolites, was separated on a Waters Acquity HSS T3 ultra-performance liquid chromatography column, and subsequently detected and quantified by a triple quadrupole Quantis mass spectrometer with electrospray ionization operated in positive mode. RESULTS: Total run time was only 5.7 min. Limits of detection ranged from 0.01 to 0.18 µg/L depending on compound. Measuring ranges were from 0.195 to 1000 µg/L depending on compound, and were defined according to therapeutic ranges. Inter- and intra-assay precisions values were less than 15 %. After validation, this method was successfully applied in daily practice for therapeutic drug monitoring of polymedicated psychiatric patients. CONCLUSION: We developed and validated one of the most sensitive and complete UPLC-MS/MS methods in psychopharmacology, allowing the simultaneous determination of 55 psychotropic drugs in only 5.7 min after a simple sample preparation. This method has been successfully used in daily practice for therapeutic drug monitoring of psychiatric patients and is especially useful in polymedicated patients.

Statins and immune-mediated necrotizing myopathy: Variability in the risk.

INTRODUCTION: Immune-mediated necrotizing myopathy (IMNM) is a form of statin myopathy characterized by the presence of antibodies against 3-hydroxy-3-methylglutaryl-coenzyme A reductase (anti HMGCR). OBJECTIVES: The aim of this study was to investigate the relationship between the different statins and the risk of IMNM. METHODS: A two-time approach was used. First, we performed a descriptive analysis of the French national pharmacovigilance database (FNPV) for the period from 1985 to december2020. To identify relevant cases, we used Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs) related to IMNM. We performed a quantitative and qualitative review of individual case safety reports (ICSRs) recorded in the french vigilance spontaneous reporting system. In a second time, we performed a comparative analysis with the World Health Organization global individual case safety reports database (Vigibase). The association between IMNM and statins exposure was assessed by calculating the reporting odds ratio (ROR) and its 95% confidence interval. RESULTS: After analysis, a total of 25 ICSRs were related to IMNM in the FNPV. The suspected statins were atorvastatin (n=21), simvastatin (n=2), pravastatin (n=1) and rosuvastatin (n=1). In Vigibase, 567 notifications were identified. A significant ROR value was found for atorvastatin, pitavastatin, simvastatin, pravastatin and rosuvastatin. CONCLUSION: Atorvastatin presents the highest risk of IMNM. Our data suggest that the occurrence of IMNM is a class effect.