Cost-effectiveness modelling of biological treatment sequences in moderate to severe rheumatoid arthritis in France

Objectives. Modern treatment of RA includes the use of biologics. Their cost is high and comparison between different treatment strategies is needed. Method. Direct medical costs of RA in France were evaluated based on expert opinion. Then, simulation-decision analytical models were developed to assess four biologic treatment sequences over 2 years in patients failing to respond to at least one anti-TNF agent. Effectiveness was expressed in theoretical expected number of days (TEND) in remission or low disease activity [low disease activity score (LDAS)] based on DAS-28 scores. Results. Direct medical costs of RA in France (excluding the cost of biologics) were estimated at €905 (s.d. 263) for 6 months and €696 (s.d. 240) for each subsequent 6 months (P < 0.001) for patients achieving LDAS and €1215 for 6 months (s.d. 405) for patients not achieving LDAS. Based on LDAS criteria, using abatacept after an inadequate response to the first anti-TNF agent (etanercept) appeared significantly (P < 0.01) more efficacious over a 2-year period (102 TEND) compared with using rituximab at a 6-month re-treatment interval (82 TEND). Mean cost-effectiveness ratios showed significantly lower costs (P < 0.01) per TEND with abatacept as second biologic agent (€278) compared with rituximab (€303). After an inadequate response to two anti-TNF agents, using abatacept also appeared significantly more efficacious than an anti-TNF agent (P < 0.01). All comparisons were confirmed when using remission criteria instead of LDAS. Conclusion. Advanced simulation models based on clinical evidence and medical practice appear to be a promising approach for comparing cost-effectiveness of biologic strategies in R

Quantitative monitoring of tamoxifen in human plasma extended to 40 metabolites using liquid-chromatography high-resolution mass spectrometry: new investigation capabilities for clinical pharmacology

Liquid-chromatography (LC) high-resolution (HR) mass spectrometry (MS) analysis can record HR full scans, a technique of detection that shows comparable selectivity and sensitivity to ion transitions (SRM) performed with triple-quadrupole (TQ)-MS but that allows de facto determination of "all” ions including drug metabolites. This could be of potential utility in in vivo drug metabolism and pharmacovigilance studies in order to have a more comprehensive insight in drug biotransformation profile differences in patients. This simultaneous quantitative and qualitative (Quan/Qual) approach has been tested with 20 patients chronically treated with tamoxifen (TAM). The absolute quantification of TAM and three metabolites in plasma was realized using HR- and TQ-MS and compared. The same LC-HR-MS analysis allowed the identification and relative quantification of 37 additional TAM metabolites. A number of new metabolites were detected in patients' plasma including metabolites identified as didemethyl-trihydroxy-TAM-glucoside and didemethyl-tetrahydroxy-TAM-glucoside conjugates corresponding to TAM with six and seven biotransformation steps, respectively. Multivariate analysis allowed relevant patterns of metabolites and ratios to be associated with TAM administration and CYP2D6 genotype. Two hydroxylated metabolites, α-OH-TAM and 4′-OH-TAM, were newly identified as putative CYP2D6 substrates. The relative quantification was precise (<20%), and the semiquantitative estimation suggests that metabolite levels are non-negligible. Metabolites could play an important role in drug toxicity, but their impact on drug-related side effects has been partially neglected due to the tremendous effort needed with previous MS technologies. Using present HR-MS, this situation should evolve with the straightforward determination of drug metabolites, enlarging the possibilities in studying inter- and intra-patients drug metabolism variability and related effects. Figure

COST-EFFECTIVENESS SIMULATION MODEL OF ABATACEPT VERSUS RITUXIMAB IN RHEUMATOID ARTHRITIS IN FRANCE

International audienc

Cost-effectiveness simulation model of abatacept versus anti-TNF treatment strategies in rheumatoid arthritis in France

International audienc

Cost-effectiveness modelling of biological treatment sequences in moderate to severe rheumatoid arthritis in France.

International audienceModern treatment of RA includes the use of biologics. Their cost is high and comparison between different treatment strategies is needed. Direct medical costs of RA in France were evaluated based on expert opinion. Then, simulation-decision analytical models were developed to assess four biologic treatment sequences over 2 years in patients failing to respond to at least one anti-TNF agent. Effectiveness was expressed in theoretical expected number of days (TEND) in remission or low disease activity [low disease activity score (LDAS)] based on DAS-28 scores. Direct medical costs of RA in France (excluding the cost of biologics) were estimated at euro 905 (s.d. 263) for 6 months and euro 696 (s.d. 240) for each subsequent 6 months (P < 0.001) for patients achieving LDAS and euro 1215 for 6 months (s.d. 405) for patients not achieving LDAS. Based on LDAS criteria, using abatacept after an inadequate response to the first anti-TNF agent (etanercept) appeared significantly (P < 0.01) more efficacious over a 2-year period (102 TEND) compared with using rituximab at a 6-month re-treatment interval (82 TEND). Mean cost-effectiveness ratios showed significantly lower costs (P < 0.01) per TEND with abatacept as second biologic agent (euro 278) compared with rituximab (euro 303). After an inadequate response to two anti-TNF agents, using abatacept also appeared significantly more efficacious than an anti-TNF agent (P < 0.01). All comparisons were confirmed when using remission criteria instead of LDAS. Advanced simulation models based on clinical evidence and medical practice appear to be a promising approach for comparing cost-effectiveness of biologic strategies in RA

Steroid profiles in both blood serum and seminal plasma are not correlated and do not reflect sperm quality: Study on the male reproductive health of fifty young Swiss men

Steroids play an important role in sperm production and quality. These hormones have been extensively studied in blood, but poorly investigated in semen. The purpose of our study was to evaluate the relationship between sperm quality and steroid profiles in blood and semen in a small cohort of young Swiss men. Another objective was to determine whether the presence of xenobiotics or drugs could influence these profiles. Semen analysis was performed according to WHO guidelines, and steroid profiles in blood serum and seminal plasma were determined by two complementary approaches: a targeted investigation involving the quantification of a limited number of relevant steroids for testing putative correlations with sperm parameters and a global "steroidomic" analysis highlighting their complex metabolic relationship. Results showed that steroid profiles are distinct within blood and seminal fluid. No significant correlation was found between individual steroids measured in blood and in semen, demonstrating the relevance of assessing hormone levels in both fluids. Moreover, testosterone and androstenedione levels were significantly correlated in semen but not in blood. None of the evaluated spermiogram parameters was linked to steroid levels measured in any medium. The steroidomic analyses confirmed that the steroids present in both fluids are different and that there is no correlation with spermiogram parameters. Finally, upon toxicological screening, we observed that all the three samples positive for tetrahydrocannabinol, which is known to act as an endocrine disruptor, displayed low seminal testosterone concentrations. In conclusion, we did not find any evidence suggesting using steroid profiles, neither in blood nor in semen, as surrogates for sperm analyses. However, steroid profiles could be useful biomarkers of individual exposure to endocrine disruptors

Steroid profiles in both blood serum and seminal plasma are not correlated and do not reflect sperm quality: Study on the male reproductive health of fifty young Swiss men

Steroids play an important role in sperm production and quality. These hormones have been extensively studied in blood, but poorly investigated in semen. The purpose of our study was to evaluate the relationship between sperm quality and steroid profiles in blood and semen in a small cohort of young Swiss men. Another objective was to determine whether the presence of xenobiotics or drugs could influence these profiles. Semen analysis was performed according to WHO guidelines, and steroid profiles in blood serum and seminal plasma were determined by two complementary approaches: a targeted investigation involving the quantification of a limited number of relevant steroids for testing putative correlations with sperm parameters and a global "steroidomic" analysis highlighting their complex metabolic relationship. Results showed that steroid profiles are distinct within blood and seminal fluid. No significant correlation was found between individual steroids measured in blood and in semen, demonstrating the relevance of assessing hormone levels in both fluids. Moreover, testosterone and androstenedione levels were significantly correlated in semen but not in blood. None of the evaluated spermiogram parameters was linked to steroid levels measured in any medium. The steroidomic analyses confirmed that the steroids present in both fluids are different and that there is no correlation with spermiogram parameters. Finally, upon toxicological screening, we observed that all the three samples positive for tetrahydrocannabinol, which is known to act as an endocrine disruptor, displayed low seminal testosterone concentrations. In conclusion, we did not find any evidence suggesting using steroid profiles, neither in blood nor in semen, as surrogates for sperm analyses. However, steroid profiles could be useful biomarkers of individual exposure to endocrine disruptors

Near infrared spectroscopy as a screening technique for the quality control of antiretroviral drugs for HIV treatment in Swiss prisons

1 Introduction Human immunodeficiency virus (HIV) infection remains one of the major public health challenges over the world. In 2018, according to the Joint United Nations Program on HIV/AIDS, nearly 37.9 million people are living with HIV [1]. Antiretroviral therapy has shown a great effectiveness in reducing mortality and morbidity related to AIDS and has thus allowed AIDS to evolve from a deadly disease to a chronic one [2]. However, most of the antiretroviral drugs are still under patent protection, and therefore their price is a major barrier to their access in low- and middle-income countries. In this context, the “Doha Declaration” was adopted in 2001 allowing these countries to produce certain patented drugs, by giving them contractual licenses. These “unapproved generic drugs” present the same active principal ingredients (APIs), galenic form and dosage, but can differ in used excipients or additives [3]. In Switzerland, people living in prison (PLP) are often not covered by compulsory insurance and their access to treatment is therefore limited. In this context, Swiss Buyer’s clubs have been created with the aim of importing “unapproved generic drugs” via recognized suppliers based in low- and middle-income countries. Consequently, quality control tests have to be performed in order to guarantee the quality and safety of these pharmaceutical products [2, 3, 4]. Separation techniques, such as liquid chromatography (LC) and capillary electrophoresis (CE), remain the gold standard to determine the API content in pharmaceutical formulations quantitatively. However, they provide only limited information about other components of the sample, such as excipients and additives. Furthermore, as a sample preparation is required before analysis, their use implies the sacrifice of at least one sample, that is undesirable for expensive samples, or when a limited number of tablets is available. Therefore, near infrared spectroscopy (NIR) can offer relevant advantages allowing fast direct analysis of the samples without prior preparation [5]. The goal of this project is the evaluation of NIR spectroscopy as a screening tool to confirm the identity of tablets coming from different selected manufacturers. 2 Material and methods Drug samples were obtained from the Medical Direction Geneva University Hospitals. Handheld NIR-S-G1 (Tellspec, Canada) was used to perform NIR analyses. The wavelength range was from 900 to 1700 nm (11111 – 5882 cm-1). Matlab R2018a software (The MathWorks, Massachusetts) and PLS toolbox® (version 8.6.2, Eigenvector Research, Washington) were used for data treatment and computation. 3 Results and discussion Six patented anti-HIV drugs and their respective generic formulations have been selected for this study and analysed by NIR spectroscopy: Truvada® (emtricitabine, enofovir disoproxil), Descovy® (emtricitabine, tenofovir alafenamide), Atripla® (emtricitabine, tenofovir disoproxil, efevirenz), Isentress® (raltegravir), Tivicay® (dolutegravir), Triumeq® (dolutregavir, abacavir, lamivudine). Some of them present one or more API(s) in common. When building the data set, inter- and intra- batch variabilities were taken into consideration by selecting different batches. Ten tablets were selected from each batch and one spectrum was acquired on each sample. Before modeling, various types of preprocessing were tested in order to better exploit the spectral information. Patented drugs often showed relevant spectral differences from their generic formulations. Since NIR spectroscopy allows obtaining information about both chemical and physical properties of samples, small differences in the formulations permitted to easily differentiate between the two. Data-driven soft independent modelling of class analogy (DD-SIMCA) models were chosen as one-class classification technique and a model was built for each patented and generic drug. Based on a calibration set, this chemometric tool allows the evaluation of a critical distance, which has been used to define the acceptance area limits for future identifications (α = 0.05). In fact, all the spectra falling within this area can be associated to the modelled class and then to a specific pharmaceutical drug. 4 Conclusion NIR spectroscopy shows great potential as screening technique for the quality control of antiretroviral drugs for HIV treatment in Swiss prisons. In fact, a proper chemometric model could be used to assess the identity and then the conformity of drugs before performing further tests, if required. 5 References [1] Global HIV & AIDS statistics – 2019 fact sheet. [cited 2019 Nov 27]. Available from: https://www.unaids.org/en/resources/fact-sheet [2] WHO, UNAIDS, UNDP. Using TRIPS flexibilities to improve access to HIV treatment, 2011. [cited 2019 Nov 27] Available from: http://files.unaids.org/en/media/unaids/contentassets/documents/unaidspublication/2011/JC2049_PolicyBrief_TRIPS_en.pdf [3] WTO Ministerial conferences – Doha 4th Ministerial – TRIPS declaration. [cited 2019 Nov 2019] Available from: https://www.wto.org/english/thewto_e/minist_e/min01_e/min01_e.htm [4] Vernaz, N., Calmy, A., Hurst, S., Jackson, Y., Negro, F., Perrier, A., Wolf, H. A buyers’ club to improve access to hepatitis C treatment for vulnerable populations. Swiss Med Wkly. 2018 [5] Deidda, R., Sacré, P.-Y., Clavaud, M., Coïc, L., Avohou, H., Hubert, Ph., Ziemons, E. Vibrational spectroscopy in analysis of pharmaceuticals: Critical review of innovative portable and handheld NIR and Raman spectrophotometers. Trends Anal. Chem. 114, 251 – 259, 2019

Metabotypes of Pseudomonas aeruginosa Correlate with Antibiotic Resistance, Virulence and Clinical Outcome in Cystic Fibrosis Chronic Infections

Pseudomonas aeruginosa (P.a) is one of the most critical antibiotic resistant bacteria in the world and is the most prevalent pathogen in cystic fibrosis (CF), causing chronic lung infections that are considered one of the major causes of mortality in CF patients. Although several studies have contributed to understanding P.a within-host adaptive evolution at a genomic level, it is still difficult to establish direct relationships between the observed mutations, expression of clinically relevant phenotypes, and clinical outcomes. Here, we performed a comparative untargeted LC/HRMS-based metabolomics analysis of sequential isolates from chronically infected CF patients to obtain a functional view of P.a adaptation. Metabolic profiles were integrated with expression of bacterial phenotypes and clinical measurements following multiscale analysis methods. Our results highlighted significant associations between P.a "metabotypes", expression of antibiotic resistance and virulence phenotypes, and frequency of clinical exacerbations, thus identifying promising biomarkers and therapeutic targets for difficult-to-treat P.a infections