Relationship between antipsychotic blood levels and treatment failure during the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study

Patterns of psychotropic drug use in veterans with epilepsy: Do drug interactions matter?

RATIONALE

Patients with epilepsy are likely to suffer from psychiatric comorbidities, including depression and anxiety. They often require treatment with multiple psychotropic drugs (PDs). While it is clear that CYP-inducing ASMs (EIASMs) can increase the oral clearance of multiple medications (thus lowering systemic exposure), it is less clear that all PK interactions are clinically meaningful (e.g. lower efficacy). As a first step in addressing this issue, this study sought to quantify the potential impact of ASM choice, whether EIASM or non-inducer (NIASM), on surrogate markers of suggestive of clinical use, including resultant antidepressant (AD) or antipsychotic (AP) dose, frequency of combination use of AD & AP, and number of multiple drug switches of PDs. Our hypothesis is that because of PK interactions, EIAED treatment would be associated with higher psychotropic drug doses, more frequent Rx adjustments and poly psychotropic comedication, all in order to optimize therapeutic response.

METHODS

Using VA pharmacy and national encounter databases, veterans with epilepsy were identified based on having a seizure diagnosis and being prescribed concomitantly an ASM and a psychotropic drug for at least 365 days between 10/1/2010 and 9/30/2014. Patients for whom psychotropic drugs were prescribed any time between beginning and end prescriptions dates of ASMs were considered. Among those, patients receiving both an EIASM + NEIASM concomitantly were categorized with the EIASM group. Patients were evaluated for AD only, AP only and both (AD & AP). To compute average drug doses per day, averages for each patient were computed and averaged again. Multiple drug switches were defined to be for patients who had been prescribed more than three psychotropic drugs during the observation period. Pearson's Chi-Square test was used to compare relative proportions of AD, AP and AD + AP in both groups.

RESULTS

In all, 16,188 patients were identified (57.0% on EIASM, 43.0% on NIASM) with a mean age of 58.7 years (91.2% male). A larger proportion of patients on EIASM received mono treatment with any psychotropic drug, as compared to NIASM (42.0% vs 36.1%). Among all, 59.6% received AD only, 6.5% received AP only, and 33.8% received both concurrently. Of EIASM, 62.5% were on AD, 5.9% on AP, and 31.7% on both AP & AD. For NIASM, 55.9% received AD, 7.4% AP, and 36.7% on AD & AP.Chi-square showed that the distribution of PD was statistically different between EIASM and NIASM groups. Z tests showed that each difference (AD, AP and both) in proportions was statistically significant (p values (4 tests, one Chi-square, 3 Z tests <0.001) between EIASM vs NIASM. Interestingly, mean doses of AD or AP did not appear to differ between ASM groups.

CONCLUSIONS

Concurrent psychotropic drug use is quite common in the VA population with epilepsy, and a large number of patients still receive enzyme-inducing ASMs that may complicate other medical therapies. Interestingly, in seeming contradiction to our hypothesis, mean daily doses of either AD or AP did not appear to differ between inducers vs non-inducers. Similarly, use of polytherapy, and/or multiple trials of various psychotropic drugs did not appear increased in the CYP-induced group. In fact, combination therapy of AD + AP was higher in NIASM than EIASM. These data suggest that perhaps these types of PK interactions may not in fact result in meaningful clinical differences. Since the present analyses did not include clinical psychiatric measures, future analyses examining direct clinical outcomes are clearly warranted.

Association between olanzapine concentration and metabolic dysfunction in drug-naive and chronic patients: similarities and differences

Second-generation antipsychotics are widely used to treat schizophrenia but their use could induce metabolic dysfunction. To balance efficacy and side effects, various guidelines recommend the use of therapeutic drug monitoring. Given the controversial relationship between olanzapine serum concentration and metabolic dysfunction, its use in clinical practice is still debated. To address this issue, we conducted a prospective cohort study to explore the associations in patients with schizophrenia. Specifically, first-episode drug-naive patients and patients with chronic schizophrenia were recruited. All participants received olanzapine monotherapy for 8 weeks. Anthropometric parameters and metabolic indices were tested at baseline and at week 8, and olanzapine serum concentration was tested at week 4. After 8 weeks of observation, body weight and BMI increased significantly in drug-naive patients. Moreover, triglycerides and LDL increased significantly in both drug-naive and chronic patients. Among chronic patients, those who have never used olanzapine/clozapine before had a significantly higher increase in weight and BMI than those who have previously used olanzapine/clozapine. Furthermore, olanzapine concentration was associated with changes in weight, BMI, and LDL levels in the drug-naive group and glucose, triglyceride and LDL levels in chronic patients who have not used olanzapine/clozapine previously. In conclusion, the metabolic dysfunction induced by olanzapine is more severe and dose-dependent in drug-naive patients but independent in patients with chronic schizophrenia. Future studies with a longer period of observation and a larger sample are warranted.

Current Status of Therapeutic Drug Monitoring in Mental Health Treatment: A Review

Therapeutic drug monitoring (TDM) receives growing interest in different psychiatric clinical settings (emergency, inpatient, and outpatient services). Despite its usefulness, TDM remains underemployed in mental health. This is partly due to the need for evidence about the relationship between drug serum concentration and efficacy and tolerability, both in the general population and even more in subpopulations with atypical pharmacokinetics. This work aims at reviewing the scientific literature published after 2017, when the most recent guidelines about the use of TDM in mental health were written. We found 164 pertinent records that we included in the review. Some promising studies highlighted the possibility of correlating early drug serum concentration and clinical efficacy and safety, especially for antipsychotics, potentially enabling clinicians to make decisions on early laboratory findings and not proceeding by trial and error. About populations with pharmacokinetic peculiarities, the latest studies confirmed very common alterations in drug blood levels in pregnant women, generally with a progressive decrease over pregnancy and a very relevant dose-adjusted concentration increase in the elderly. For adolescents also, several drugs result in having different dose-related concentration values compared to adults. These findings stress the recommendation to use TDM in these populations to ensure a safe and effective treatment. Moreover, the integration of TDM with pharmacogenetic analyses may allow clinicians to adopt precise treatments, addressing therapy on an individual pharmacometabolic basis. Mini-invasive TDM procedures that may be easily performed at home or in a point-of-care are very promising and may represent a turning point toward an extensive real-world TDM application. Although the highlighted recent evidence, research efforts have to be carried on: further studies, especially prospective and fixed-dose, are needed to replicate present findings and provide clearer knowledge on relationships between dose, serum concentration, and efficacy/safety.

An Integrated Pharmacokinetic-Pharmacodynamic-Pharmacoeconomic Modeling Method to Evaluate Treatments for Adults with Schizophrenia

INTRODUCTION

Schizophrenia is a chronic mental disorder that worsens with each relapse. Long-acting injectable (LAI) antipsychotics may prevent the exacerbation of symptoms and occurrence of relapses through improved continuity of care. Different dose regimens are available for the LAIs aripiprazole monohydrate (AM) and aripiprazole lauroxil (AL), but their cost effectiveness is unclear.

OBJECTIVES

The study aim was to compare costs and effects (relapses) of the different aripiprazole LAI dose regimens to inform clinical and US payer decisions.

METHODS

A state-transition model calculated the outcomes of eight LAI dose regimens based on their relapse rates. As effectiveness data from randomized controlled trials were unavailable, relapse rates were modeled using pharmacokinetic and pharmacodynamic evidence. These described blood plasma levels of aripiprazole as a function of AM and AL dose regimens and described the probability of relapse as a function of aripiprazole blood plasma levels. The analysis had a time horizon of 1 year and took the US healthcare payer perspective. The incremental cost per relapse avoided and the probability of cost effectiveness were calculated in deterministic and probabilistic analyses. Scenario analyses explored the model's main assumptions, and results were validated against external data and other cost-effectiveness analyses.

RESULTS

Monthly administration of AM 400 mg consistently yielded the lowest predicted number of relapses across deterministic, probabilistic, and scenario analyses. The costs of treatment and relapses were projected to be the lowest with a monthly administration of AL 441 mg. The incremental cost per relapse avoided with AM 400 mg ranged from AM 400 mg being dominant to $US83,300. From willingness-to-pay thresholds of $US30,000 per relapse avoided, the probability of cost effectiveness was highest for AM 400 mg. The validation showed alignment with external data.

CONCLUSION

The analysis highlighted the robustness of the novel framework based on pharmacokinetic and pharmacodynamic evidence and demonstrated an application in a postmarketing setting.

A Receiver Operating Characteristic Framework for Non-adherence Detection Using Drug Concentration Thresholds-Application to Simulated Risperidone Data in Schizophrenic Patients

Non-adherence to antipsychotic medication is a primary factor in disease relapse in schizophrenic patients. We sought to evaluate if plasma concentrations of the antipsychotic risperidone can be used as a predictor of treatment adherence and to identify the optimal plasma concentration threshold to reliably distinguish between adherent and non-adherent patients. A population pharmacokinetic model was used to simulate plasma risperidone steady-state trough concentrations in 1000 virtual patients, where 60% of the patients were 100% adherent to their medication, while 40% of the patients were non-adherent to their medication. The probability of adherence was assessed by receiver operating characteristic (ROC) analysis on C_trough. The area under the ROC curve (AUC_ROC) was used to identify the optimal C_trough threshold. Single vs multiple C_trough at steady state was also evaluated. After a single risperidone C_trough measurement, the AUC_ROC (95% CI) was estimated to be 0.71 (0.69-0.72) and the optimal C_trough threshold accounting for the lowest number of adherent and non-adherent misclassifications was estimated to be 11.9 ng/mL. After multiple C_trough measurements, the AUC_ROC (95% CI) increased up to 0.85 (0.84-0.87) for three C_trough measurements. The optimal probability threshold to reliably discriminate between adherent and non-adherent patients was estimated to be 0.51. Using this model which is reflective of typical adherence to antipsychotic medication, we found that three consecutive steady-state C_trough measurements are needed for an accurate and precise diagnostic test to discriminate between patients who are adherent or non-adherent to treatment.