Exploration, normalization, and summaries of high density oligonucleotide array probe level data.

SUMMARY In this paper we report exploratory analyses of high-density oligonucleotide array data from the Affymetrix GeneChip R system with the objective of improving upon currently used measures of gene expression. Our analyses make use of three data sets: a small experimental study consisting of five MGU74A mouse GeneChip R arrays, part of the data from an extensive spike-in study conducted by Gene Logic and Wyeth's Genetics Institute involving 95 HG-U95A human GeneChip R arrays; and part of a dilution study conducted by Gene Logic involving 75 HG-U95A GeneChip R arrays. We display some familiar features of the perfect match and mismatch probe (P M and M M) values of these data, and examine the variance-mean relationship with probe-level data from probes believed to be defective, and so delivering noise only. We explain why we need to normalize the arrays to one another using probe level intensities. We then examine the behavior of the P M and M M using spike-in data and assess three commonly used summary measures: Affymetrix's (i) average difference (AvDiff) and (ii) MAS 5.0 signal, and (iii) the Li and Wong multiplicative model-based expression index (MBEI). The exploratory data analyses of the probe level data motivate a new summary measure that is a robust multiarray average (RMA) of background-adjusted, normalized, and log-transformed P M values. We evaluate the four expression summary measures using the dilution study data, assessing their behavior in terms of bias, variance and (for MBEI and RMA) model fit. Finally, we evaluate the algorithms in terms of their ability to detect known levels of differential expression using the spike-in data. We conclude that there is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities

Developing a Nationwide Infrastructure for Therapeutic Drug Monitoring of Targeted Oral Anticancer Drugs: The ON-TARGET Study Protocol

Exposure-efficacy and/or exposure-toxicity relationships have been identified for up to 80% of oral anticancer drugs (OADs). Usually, OADs are administered at fixed doses despite their high interindividual pharmacokinetic variability resulting in large differences in drug exposure. Consequently, a substantial proportion of patients receive a suboptimal dose. Therapeutic Drug Monitoring (TDM), i.e., dosing based on measured drug concentrations, may be used to improve treatment outcomes. The prospective, multicenter, non-interventional ON-TARGET study (DRKS00025325) aims to investigate the potential of routine TDM to reduce adverse drug reactions in renal cell carcinoma patients receiving axitinib or cabozantinib. Furthermore, the feasibility of using volumetric absorptive microsampling (VAMS), a minimally invasive and easy to handle blood sampling technique, for sample collection is examined. During routine visits, blood samples are collected and sent to bioanalytical laboratories. Venous and VAMS blood samples are collected in the first study phase to facilitate home-based capillary blood sampling in the second study phase. Within one week, the drug plasma concentrations are measured, interpreted, and reported back to the physician. Patients report their drug intake and toxicity using PRO-CTCAE-based questionnaires in dedicated diaries. Ultimately, the ON-TARGET study aims to develop a nationwide infrastructure for TDM for oral anticancer drugs

Cardiovascular Mortality Can Be Predicted by Heart Rate Turbulence in Hemodialysis Patients

Background: Excess mortality in hemodialysis patients is mostly of cardiovascular origin. We examined the association of heart rate turbulence (HRT), a marker of baroreflex sensitivity, with cardiovascular mortality in hemodialysis patients. Methods: A population of 290 prevalent hemodialysis patients was followed up for a median of 3 years. HRT categories 0 (both turbulence onset [TO] and slope [TS] normal), 1 (TO or TS abnormal), and 2 (both TO and TS abnormal) were obtained from 24 h Holter recordings. The primary end-point was cardiovascular mortality. Associations of HRT categories with the endpoints were analyzed by multivariable Cox regression models including HRT, age, albumin, and the improved Charlson Comorbidity Index for hemodialysis patients. Multivariable linear regression analysis identified factors associated with TO and TS. Results: During the follow-up period, 20 patients died from cardiovascular causes. In patients with HRT categories 0, 1 and 2, cardiovascular mortality was 1, 10, and 22%, respectively. HRT category 2 showed the strongest independent association with cardiovascular mortality with a hazard ratio of 19.3 (95% confidence interval: 3.69-92.03;P < 0.001). Age, calcium phosphate product, and smoking status were associated with TO and TS. Diabetes mellitus and diastolic blood pressure were only associated with TS. Conclusion: Independent of known risk factors, HRT assessment allows identification of hemodialysis patients with low, intermediate, and high risk of cardiovascular mortality. Future prospective studies are needed to translate risk prediction into risk reduction in hemodialysis patients

Serious Adverse Drug Reactions in Children and Adolescents Treated On- and Off-Label with Antidepressants and Antipsychotics in Clinical Practice

Introduction: Despite the growing evidence base for psychotropic drug treatment in pediatric patients, knowledge about the benefit-risk ratio in clinical practice remains limited. The 'Therapeutic Drug Monitoring (TDM)-VIGIL' study aimed to evaluate serious adverse drug reactions (ADRs) in children and adolescents treated with antidepressants and/or antipsychotics in approved ('on-label'), and off-label use in clinical practice. Methods: Psychiatric pediatric patients aged 6-18 years treated with antidepressants and/or antipsychotics either on-label or off-label were prospectively followed between October 2014 and December 2018 within a multicenter trial. Follow-up included standardized assessments of response, serious ADRs and therapeutic drug monitoring. Results: 710 youth (age=14.6±2.2 years, female=66.6%) were observed for 5.5 months on average; 76.3% received antidepressants, 47.5% antipsychotics, and 25.2% both. Altogether, 55.2% of the treatment episodes with antidepressants and 80.7% with antipsychotics were off-label. Serious ADRs occurred in 8.3% (95%CI=6.4-10.6%) of patients, mainly being psychiatric adverse reactions (77.4%), predominantly suicidal ideation and behavior. The risk of serious ADRs was not significantly different between patients using psychotropics off-label and on-label (antidepressants: 8.1% vs. 11.3%, p=0.16; antipsychotics: 8.7% vs 7.5%, p=0.67). Serious ADRs occurred in 16.6% of patients who were suicidal at enrollment versus 5.6% of patients who were not suicidal (relative risk 3.0, 95%CI=1.9-4.9). Conclusion: Off-label use of antidepressants and antipsychotics in youth was not a risk factor for the occurrence of serious ADRs in a closely monitored clinical setting. Results from large naturalistic trials like ours can contribute to bridging the gap between knowledge from randomized controlled trials and real-world clinical settings

Therapeutic drug monitoring of sertraline in children and adolescents: A naturalistic study with insights into the clinical response and treatment of obsessive-compulsive disorder.

BACKGROUND Sertraline is a selective serotonin reuptake inhibitor with specific indications in child and adolescent psychiatry. Notwithstanding its frequent use and clinical benefits, the relationship between pharmacokinetics, pharmacodynamics, efficacy, and tolerability of sertraline across indications, particularly in non-adult patients, is not fully understood. METHOD This naturalistic therapeutic drug monitoring (TDM) study was conducted in a transdiagnostic sample of children and adolescents treated with sertraline (n = 78; mean age, 14.22 ± 2.39; range, 7-18 years) within the prospective multicenter "TDM-VIGIL" project. Associations between dose, serum concentration, and medication-specific therapeutic and side effects based on the Clinical Global Impression scale were examined. Tolerability was measured qualitatively with the 56-item Pediatric Adverse Event Rating Scale. RESULTS A strong linear positive dose-serum concentration relationship (with dose explaining 45% of the variance in concentration) and significant effects of weight and co-medication were found. Neither dose nor serum concentration were associated with side effects. An overall mild-to-moderate tolerability profile of sertraline was observed. In contrast with the transdiagnostic analysis that did not indicate an effect of concentration, when split into depression (MDD) and obsessive-compulsive disorder (OCD) diagnoses, the probability of clinical improvement significantly increased as both dose and concentration increased for OCD, but not for MDD. CONCLUSIONS This TDM-flexible-dose study revealed a significant diagnosis-specific effect between sertraline serum concentration and clinical efficacy for pediatric OCD. While TDM already guides clinical decision-making regarding compliance, dose calibration, and drug-drug interactions, combining TDM with other methods, such as pharmacogenetics, may facilitate a personalized medicine approach in psychiatry

Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential

BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control