Self-Report for Measuring and Predicting Medication Adherence: Experts' Experience in Predicting Adherence in Stable Psychiatric Outpatients and in Pharmacokinetics

Exploring low clozapine C/D ratios, inverted clozapine-norclozapine ratios and undetectable concentrations as measures of non-adherence in clozapine patients: A literature review and a case series of 17 patients from 3 studies

BACKGROUND

Up to 1/2 of outpatients prescribed clozapine may be partially/fully non-adherent, based on therapeutic drug monitoring (TDM). Three indices for measuring partial/full non-adherence are proposed a: 1) clozapine concentration/dose (C/D) ratio which drops to half or more of what is expected in the patient; 2) clozapine/norclozapine ratio that becomes inverted; and 3) clozapine concentration that becomes non-detectable.

METHODS

These 3 proposed indices are based on a literature review and 17 cases of possible non-adherence from 3 samples: 1) an inpatient study in a Chinese hospital, 2) an inpatient randomized clinical trial in a United States hospital, and 3) and a Uruguayan outpatient study.

RESULTS

The first index of non-adherence is a clozapine C/D ratio which is less than half the ratio corresponding to the patient's specific ancestry group and sex-smoking subgroup. Knowing the minimum therapeutic dose of the patient based on repeated TDM makes it much easier to establish non-adherence. The second index is inverted clozapine/norclozapine ratios in the absence of alternative explanations. The third index is undetectable concentrations. By using half-lives, the chronology of the 3 indices of non-adherence was modeled in two patients: 1) the clozapine C/D ratio dropped to ≥1/2 of what is expected from the patient (around day 2); 2) the clozapine/norclozapine ratio became inverted (around day 3); and 3) the clozapine concentration became undetectable by the laboratory (around days 9-11).

CONCLUSION

Prospective studies should further explore these proposed clozapine indices in average patients, poor metabolizers (3 presented) and ultrarapid metabolizers (2 presented).

Adherence to Background Antipsychotic and Pimavanserin in Patients with Schizophrenia: Post Hoc Analyses from the ENHANCE and ADVANCE Studies

Background

In patients with schizophrenia, study design to optimize adherence and objective measurement of adherence is critical for interpreting results. Two randomized, double-blind studies evaluating adjunctive pimavanserin in patients with schizophrenia who received stable antipsychotic treatment included measures to encourage and assess treatment adherence.

Objective

This post hoc analysis evaluated adherence levels achieved in the Phase III ENHANCE study (NCT02970292) and the Phase II ADVANCE study (NCT02970305).

Methods

Blood levels of participants receiving adjunctive treatment with pimavanserin or placebo added to their ongoing antipsychotic medication were tested and evaluated regularly throughout both studies. For both the background antipsychotic and pimavanserin, treatment adherence was defined as a blood sample test result above the lower limit of quantification.

Results

Overall, 392 of 633 screened patients and 403 of 608 screened patients were in the safety populations in ENHANCE and ADVANCE, respectively. In ENHANCE, at weeks 1, 3, and 6/early termination (ET), the adherence rates remained ≥ 95.1% for the background antipsychotic in both pimavanserin and placebo treatment groups and ≥ 96.8% for pimavanserin. In ADVANCE, high adherence rates (≥90.6%) with the background antipsychotic (for both treatment groups) and pimavanserin (≥95.0%) were observed at weeks 2, 8, 14, and 26/ET.

Conclusion

Rigorous screening was performed to exclude patients not adherent to their background antipsychotic before enrollment and to pimavanserin during study visits by using regular blood sampling. Mandatory caregiver participation further supported adherence to study treatment and procedures. These efforts may have contributed to the high levels of adherence to both background antipsychotic and pimavanserin reported in ENHANCE and ADVANCE.

Optimization of Therapy in Patients with Epilepsy and Psychiatric Comorbidities: Key Points

Psychiatric disorder comorbidity in patients with epilepsy (PWE) is very frequent with a mean percentage prevalence of up to 50% and even higher. Such a high frequency suggests that epilepsy and psychiatric disorders might share common pathological pathways. Various aspects contribute in making the matter very complex from a therapeutic point of view. Some antiseizure medications (ASMs), namely valproic acid, carbamazepine, and lamotrigine, have mood-stabilising effects and are routinely used for the treatment of bipolar disorder in patients who do not have epilepsy. Pregabalin and, to a lesser extent, gabapentin, exerts anxiolytic effects. However, several ASMs, in particular levetiracetam, topiramate, and perampanel, may contribute to psychiatric disorders, including depression, aggressive behaviour, and even psychosis. If these ASMs are prescribed, the patient should be monitored closely. A careful selection should be made also with psychotropic drugs. Although most of these can be safely used at therapeutic doses, bupropion, some tricyclic antidepressants, maprotiline, and clozapine may alter seizure threshold and facilitate epileptic seizures. Interactions between ASMs and psychotropic medication may make it difficult to predict individual response. Pharmacokinetic interactions can be assessed with drug monitoring and are consequently much better documented than pharmacodynamic interactions. Another aspect that needs a careful evaluation is patient adherence to treatment. Prevalence of non-adherence in PWE and psychiatric comorbidities is reported to reach values even higher than 70%. A careful evaluation of all these aspects contributes in optimizing therapy with a positive impact on seizure control, psychiatric wellbeing, and quality of life.

Weekly telephone mood monitoring is associated with decreased suicidality and improved sleep quality in a clinical sample

Sleep disturbances and suicidality are common presentations of mood and anxiety disorders. If not closely monitored post-discharge, patients may be at an increased risk of symptom worsening and completed suicide. We explored the associations between telephone mood monitoring, suicidality, and sleep quality in a clinical sample. Fifty inpatients (mean age = 39.49, SD = 11.17; female = 74%) with a mood and/or anxiety disorder were telephonically monitored weekly post-discharge for16 weeks for depression and mania. Suicidality and sleep quality were assessed at intake (pre-discharge), and at weeks 4, 8, 12, and 16 post-discharge. ANOVA indicated that suicidality significantly decreased, and sleep quality improved over 16 weeks. Linear regression analysis indicated that depression severity at week 1 post-discharge significantly predicted suicidality and sleep quality at week 16. Mania severity at week 1 post-discharge predicted sleep quality, but not suicidality, at week 16. Participants generally had positive experiences of the monitoring and perceived it as helpful. Monitoring of mood state, suicidality, and sleep quality post-discharge may allow for early detection of relapse when initiated at 1-week post-discharge. This is a potentially cost-effective intervention and may relieve the burden on the mental healthcare system, especially when face-to-face consultations are not possible.

Healthcare Provider Engagement with a Novel Dashboard for Tracking Medication Ingestion: Impact on Treatment Decisions and Clinical Assessments for Adults with Schizophrenia

Purpose

Schizophrenia is a severe, chronic condition accounting for disproportionate healthcare utilization. Antipsychotics can reduce relapse rates, but the characteristics of schizophrenia may hinder medication adherence. A phase 3b open-label clinical trial used aripiprazole tablets with sensor (AS; includes pills with ingestible event-marker, wearable sensor patches and smartphone application) in adults with schizophrenia. This post hoc analysis explored how healthcare providers' (HCPs) usage of a dashboard that provided medication ingestion information impacted treatment decisions and clinical assessments.

Patients and Methods

Participants used AS for 3-6 months. HCPs were instructed to check the dashboard regularly, identify features used, and report impact on treatment decisions. After stratifying HCPs by frequency of dashboard checks and resulting treatment decisions, changes from baseline were calculated for Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression (CGI)-Severity of Illness and CGI-Improvement (CGI-I), and Personal and Social Performance (PSP), and compared using Mann-Whitney U-tests and rank-biserial correlation coefficient (r) effect sizes.

Results

To ensure sufficient opportunity for AS engagement, 113 participants who completed ≥3 months on study were analyzed. HCPs most often accessed dashboard data regarding medication ingestion and missed doses. HCPs recommended adherence counseling and participant education most often. Participants whose HCPs used the dashboard more and recommended adherence counseling and participant education (n=61) improved significantly more than participants with less dashboard-active HCPs (n=49) in CGI-I mean score (2.9 versus 3.4 [p=0.004]), total PANSS (mean change: -9.2 versus -3.1 [p=0.0002]), PANSS positive subscale (-3.2 versus -1.5 [p=0.003]), PANSS general subscale (-4.3 versus -1.2 [p=0.02]), and Marder factor for negative symptoms (-1.9 versus 0.0 [p=0.03]). Most HCPs found the dashboard easy to use (74%) and helpful for improving conversations with participants about their treatment plan and progress (78%).

Conclusion

This provider dashboard may facilitate discussions with patients about regular medication-taking, which can improve patient outcomes.

Effect of necessity-concern framework and polypharmacy on treatment adherence in psychiatric patients. Comparing an Argentinian with a Spanish sample

OBJECTIVE

We aimed to replicate a prior Spanish study of medication adherence where logistic regression models provided highly significant odds ratios (ORs) for three continuous scores: necessity, concern and the necessity-concern differential, and a dichotomous variable: skeptical attitude. Adherence ORs in the necessity-concern framework were very strong in patients taking five or six medications.

METHODS

The sample comprised consecutive adult psychiatric outpatients in Mendoza, Argentina. The necessity-concerns framework was assessed using a subscale of the Beliefs about Medicines Questionnaire. Adherence (yes/no) to prescribed psychiatric medications was assessed by the Sidorkiewicz adherence tool.

RESULTS

When compared with the Spanish sample, the Argentinian group (508 patients with 875 medications) was characterized by: (1) significantly stronger adherence ORs with the necessity-concern framework, (2) significantly lower number of medications per patient and percentage of patients with marked psychiatric polypharmacy (≥4 medications), (3) though a higher number of medications still was significantly associated with poor adherence.

CONCLUSIONS

The Argentinian sample replicated the previous finding that patient beliefs regarding necessity and concern were associated with poor adherence to prescribed medications. Polypharmacy had an additive role decreasing adherence in both samples. In both samples, when prescribed ≥4 psychiatric medications, patients reported adherence to only two-third of the medications.