Coadministration of fluconazole to boost subtherapeutic sirolimus concentrations: A case report

Individual sirolimus whole blood concentrations are highly variable, critically influenced by the concomitant use of cytochrome P450 (CYP) 3A inducers or inhibitors, and also modulated by food. Therapeutic drug monitoring is therefore recommended, especially at treatment start or in circumstances that can influence sirolimus exposure. In this case report, we highlight the challenge of achieving therapeutic sirolimus concentrations and present pragmatic solutions with regimen adaptions, pharmacokinetic enhancement (use of a drug-drug interaction), concentration monitoring, and subsequent modeling of population pharmacokinetics to support treatment decisions. In a 69-year-old female patient with allogeneic hematopoietic stem cell transplantation, tacrolimus concentrations were stable until she developed cerebral toxoplasmosis with tonic-clonic seizures. During treatment of this acute infection, tacrolimus concentrations dropped to subtherapeutic levels and remained largely unaffected by dose increases. Only the simultaneous administration of the CYP3A4 inhibitor fluconazole and a shortening of the sirolimus dosing intervals to a (non-approved) twice-daily administration led to successful control of the concentrations, which ultimately even made a dose reduction possible. This intervention resulted in an increase of sirolimus mean trough concentration to 5.85 ng/mL, i.e., into the desired target range. Additionally, a higher ratio of sirolimus trough levels/daily dose from 26.9 to 109 ng/mL/mg/kg/day was achieved with the initiation of fluconazole. Thus, this case report describes the use of clinical pharmacological concepts and pharmacokinetic modeling to optimize treatment strategies in an individual patient. This strategy could be generalized to other CYP inhibitors and other treatment regimens.

Effect of Tacrolimus Formulation (Prolonged-Release vs Immediate-Release) on Its Susceptibility to Drug-Drug Interactions with St. John's Wort

Tacrolimus is metabolized by cytochrome P450 3A (CYP3A) and is susceptible to interactions with the CYP3A and P-glycoprotein inducer St. John's Wort (SJW). CYP3A isozymes are predominantly expressed in the small intestine and liver. Prolonged-release tacrolimus (PR-Tac) is largely absorbed in distal intestinal segments and is less susceptible to CYP3A inhibition. The effect of induction by SJW is unknown. In this randomized, crossover trial, 18 healthy volunteers received single oral tacrolimus doses (immediate-release [IR]-Tac or PR-Tac, 5 mg each) alone and during induction by SJW. Concentrations were quantified using ultra-high performance liquid chromatography coupled with tandem mass spectrometry and non-compartmental pharmacokinetics were evaluated. SJW decreased IR-Tac exposure (area under the concentration-time curve) to 73% (95% confidence interval 60%-88%) and maximum concentration (Cmax ) to 61% (52%-73%), and PR-Tac exposure to 67% (55%-81%) and Cmax to 69% (58%-82%), with no statistical difference between the 2 formulations. The extent of interaction appeared to be less pronounced in volunteers with higher baseline CYP3A4 activity and in CYP3A5 expressors. In contrast to CYP3A inhibition, CYP3A induction by SJW showed a similar extent of interaction with both tacrolimus formulations. A higher metabolic baseline capacity appeared to attenuate the extent of induction by SJW.

Feasibility and Safety of Sildenafil to Repair Brain Injury Secondary to Birth Asphyxia (SANE-01): A Randomized, Double-blind, Placebo-controlled Phase Ib Clinical Trial

OBJECTIVE

To test feasibility and safety of administering sildenafil in neonates with neonatal encephalopathy (NE), developing brain injury despite therapeutic hypothermia (TH).

STUDY DESIGN

We performed a randomized, double-blind, placebo-controlled phase Ib clinical trial between 2016 and 2019 in neonates with moderate or severe NE, displaying brain injury on day-2 magnetic resonance imaging (MRI) despite TH. Neonates were randomized (2:1) to 7-day sildenafil or placebo (2 mg/kg/dose enterally every 12 hours, 14 doses). Outcomes included feasibility and safety (primary outcomes), pharmacokinetics (secondary), and day-30 neuroimaging and 18-month neurodevelopment assessments (exploratory).

RESULTS

Of the 24 enrolled neonates, 8 were randomized to sildenafil and 3 to placebo. A mild decrease in blood pressure was reported in 2 of the 8 neonates after initial dose, but not with subsequent doses. Sildenafil plasma steady-state concentration was rapidly reached, but decreased after TH discontinuation. Twelve percent of neonates (1/8) neonates died in the sildenafil group and 0% (0/3) in the placebo group. Among surviving neonates, partial recovery of injury, fewer cystic lesions, and less brain volume loss on day-30 magnetic resonance imaging were noted in 71% (5/7) of the sildenafil group and in 0% (0/3) of the placebo group. The rate of death or survival to 18 months with severe neurodevelopmental impairment was 57% (4/7) in the sildenafil group and 100% (3/3) in the placebo group.

CONCLUSIONS

Sildenafil was safe and well-absorbed in neonates with NE treated with TH. Optimal dosing needs to be established. Evaluation of a larger number of neonates through subsequent phases II and III trials is required to establish efficacy.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.govNCT02812433.

Influence of a Short Course of Ritonavir Used as Booster in Antiviral Therapies Against SARS-CoV-2 on the Exposure of Atorvastatin and Rosuvastatin

PURPOSE

Early antiviral treatment with nirmatrelvir/ritonavir is recommended for SARS-CoV-2-infected patients at high risk for severe courses. Such patients are usually chronically ill and susceptible to adverse drug interactions caused by ritonavir. We investigated the interactions of short-term low-dose ritonavir therapy with atorvastatin and rosuvastatin, two statins commonly used in this population.

METHOD

We assessed exposure changes (area under the concentration-time curve (AUC∞) and maximum concentration (Cmax)) of a single dose of 10 mg atorvastatin and 10 mg rosuvastatin before and on the fifth day of ritonavir treatment (2 × 100 mg/day) in healthy volunteers and developed a semi-mechanistic pharmacokinetic model to estimate dose adjustment of atorvastatin during ritonavir treatment.

RESULTS

By the fifth day of ritonavir treatment, the AUC∞ of atorvastatin increased 4.76-fold and Cmax 3.78-fold, and concurrently, the concentration of atorvastatin metabolites decreased to values below the lower limit of quantification. Pharmacokinetic modelling indicated that a stepwise reduction in atorvastatin dose during ritonavir treatment with a stepwise increase up to 4 days after ritonavir discontinuation can keep atorvastatin exposure within safe and effective margins. Rosuvastatin pharmacokinetics were only mildly modified; ritonavir significantly increased the Cmax 1.94-fold, while AUC∞ was unchanged.

CONCLUSION

Atorvastatin doses should likely be adjusted during nirmatrelvir/ritonavir treatment. For patients on a 20-mg dose, we recommend half of the original dose. In patients taking 40 mg or more, a quarter of the dose should be taken until 2 days after discontinuation of nirmatrelvir/ritonavir. Patients receiving rosuvastatin do not need to change their treatment regimen.

TRIAL REGISTRATION

EudraCT number: 2021-006634-39. DRKS00027838.

CYP3A and CYP2C19 Activity Determined by Microdosed Probe Drugs Accurately Predict Voriconazole Clearance in Healthy Adults

BACKGROUND AND OBJECTIVE

Voriconazole is an important broad-spectrum anti-fungal drug with nonlinear pharmacokinetics. The aim of this single centre fixed-sequence open-label drug-drug interaction trial in healthy participants (N = 17) was to determine whether microdosed probe drugs for CYP3A and CYP2C19 reliably predict voriconazole clearance (CLVRZ).

METHODS

At baseline, a single oral microdose of the paradigm substrates midazolam (CYP3A) and omeprazole (CYP2C19) were given to estimate their clearances (CL). Thereafter, a single oral dose of voriconazole was administered (50, 100, 200 or 400 mg), followed by the microdosed probe drugs.

RESULTS

The clearances of midazolam (CLMDZ 790-2790 mL/min at baseline; 248-1316 mL/min during voriconazole) and omeprazole (CLOMZ 66.4-2710 mL/min at baseline; 30.1-1420 mL/min during voriconazole) were highly variable. CLMDZ [geometric mean ratio (GMR) 0.586 at 50 mg voriconazole decreasing to GMR 0.196 at 400 mg voriconazole] and CLOMZ (GMR 0.590 at 50 mg decreasing to GMR 0.166 at 400 mg) were reduced with higher voriconazole doses. CLMDZ was linearly correlated with CLVRZ (slope 1.458; adjusted R2 0.528) as was CLOMZ (slope 0.807; adjusted R2 0.898). Multiple linear regression resulted in an adjusted R2 of 0.997 for the relationship CLVRZ ~ log CLOMZ + log CLMDZ using data during voriconazole treatment and an adjusted R2 of 0.997 for the relationship CLVRZ ~ log CLOMZ + log CLMDZ + voriconazole dose, using baseline data for CLMDZ and CLOMZ.

CONCLUSION

Microdosed midazolam and omeprazole accurately described and predicted total CLVRZ TRIAL REGISTRATION: EudraCT No: 2020-001017-20, registered on March 5th, 2020. DRKS: DRKS00022547, registered on August 6th, 2020.

Mortality and Hospitalizations Among Patients Enrolled in an Interprofessional Medication Management Program

BACKGROUND

Measures for improving medication safety in outpatient care are often complex and involve medication reviews. Over the period 2016-2022 (with a preceeding one-year pilot phase), an interprofessional medication management program- the Medicines Initiative Saxony-Thuringia (Arzneimittelinitiative Sachsen-Thüringen, ARMIN)-was implemented in two German federal states. More than 5000 patients received a medication review by the end of 2019 by a team composed of physicians and pharmacists and were provided with joint, continuous care thereafter.

METHODS

In the framework of a retrospectively registered cohort study, the mortality and hospitalizations of this population (5033 patients) were studied using routine data from a statutory health insurer (observation period 2015-2019) and compared with those of a control group (10 039 patients) determined from the routine data by propensity score matching. Mortality was compared by survival analysis (Cox regression), and hospitalization rates were compared in terms of event probabilities within two years of enrollment in the medication management program. Robustness was tested in multiple sensitivity analyses.

RESULTS

Over the observation period, 9.3% of the ARMIN participants and 12.9% of persons in the control group died (hazard ratio of the adjusted Cox regression, 0.84; 95% confidence interval [0.76; 0.94], P = 0.001). In the first two years after inclusion, the ARMIN participants were hospitalized just as often as the persons in the control group (52.4% versus 53.4%; odds ratio from the adjusted model, 1.04 [0.96; 1.11], P = 0.347). The effects were consistent in sensitivity analyses.

CONCLUSION

In this retrospective cohort study, participation in the ARMIN program was associated with a lower risk of death. Exploratory analyses provide clues to the potential origin of this association.

Analysing and improving preoperative medication management in cardiac surgery

AIMS

The objective of this study was to analyse the preoperative medication management within the cardiac surgery patient population and measure the effectiveness of an interprofessional intervention in routine care.

METHODS

A jointly developed preoperative medication management was implemented in routine care on multiple levels (inclusion in admission letter to primary care, hotline for inquiries, pocket cards for physicians and correspondence with referring centres). The effectiveness was evaluated by analysing preoperative management before and after implementation. The primary endpoint was the number of drugs managed correctly according to the guidelines after implementation. Secondary endpoints consisted amongst others of bleeding on the intensive care unit, re-thoracotomy, postoperative infarction and cerebrovascular complications. Additionally, possible associations between the correct management and different variables were investigated by multivariate analysis.

RESULTS

After the implementation, the number of drugs managed correctly according to guidelines increased from 54.0 to 73.5% (P < .001). The effect was more prominent for direct oral anticoagulants and prophylactic aspirin where the guideline adherence increased from 29.2 to 74.5% and from 78.6 to 95.1%, respectively. No difference was seen for sodium-glucose transporter-2 inhibitors, metformin, vitamin-K antagonists and dual-antiplatelet therapy. Secondary endpoints showed no safety signals with regard to bleeding or thrombotic events. In multivariate analysis, the intervention was effective (odds ratio 2.17, 95% confidence interval [1.32-3.62]) after adjusting for possible confounders.

CONCLUSION

An interprofessional programme was effective to improve preoperative medication management in cardiac surgery patients. Sodium-glucose transporter-2 inhibitors, metformin and direct oral anticoagulants appear to be especially at risk for incorrect management before cardiac surgery with possible adverse events.

Effect of Clarithromycin, a Strong CYP3A and P-glycoprotein Inhibitor, on the Pharmacokinetics of Edoxaban in Healthy Volunteers and the Evaluation of the Drug Interaction with Other Oral Factor Xa Inhibitors by a Microdose Cocktail Approach

PURPOSE

We assessed the differential effect of clarithromycin, a strong inhibitor of cytochrome P450 (CYP) 3A4 and P-glycoprotein, on the pharmacokinetics of a regular dose of edoxaban and on a microdose cocktail of factor Xa inhibitors (FXaI). Concurrently, CYP3A activity was determined with a midazolam microdose.

METHODS

In an open-label fixed-sequence trial in 12 healthy volunteers, the pharmacokinetics of a microdosed FXaI cocktail (μ-FXaI; 25 μg apixaban, 50 μg edoxaban, and 25 μg rivaroxaban) and of 60 mg edoxaban before and during clarithromycin (2 x 500 mg/d) dosed to steady-state was evaluated. Plasma concentrations of study drugs were quantified using validated ultra-performance liquid chromatography-tandem mass spectrometry methods.

RESULTS

Therapeutic clarithromycin doses increased the exposure of a therapeutic 60 mg dose of edoxaban with a geometric mean ratio (GMR) of the area under the plasma concentration-time curve (AUC) of 1.53 (90 % CI: 1.37-1.70; p < 0.0001). Clarithromycin also increased the GMR (90% CI) of the exposure of microdosed FXaI apixaban to 1.38 (1.26-1.51), edoxaban to 2.03 (1.84-2.24), and rivaroxaban to 1.44 (1.27-1.63). AUC changes observed for the therapeutic edoxaban dose were significantly smaller than those observed with the microdose (p < 0.001).

CONCLUSION

Clarithromycin increases FXaI exposure. However, the magnitude of this drug interaction is not expected to be clinically relevant. The edoxaban microdose overestimates the extent of the drug interaction with the therapeutic dose, whereas AUC ratios for apixaban and rivaroxaban were comparable to the interaction with therapeutic doses as reported in the literature.

TRIAL REGISTRATION

EudraCT Number: 2018-002490-22.

Anticholinergic burden measures, symptoms, and fall-associated risk in older adults with polypharmacy: Development and validation of a prognostic model

BACKGROUND

Anticholinergic burden has been associated with adverse outcomes such as falls. To date, no gold standard measure has been identified to assess anticholinergic burden, and no conclusion has been drawn on which of the different measure algorithms best predicts falls in older patients from general practice. This study compared the ability of five measures of anticholinergic burden to predict falls. To account for patients' individual susceptibility to medications, the added predictive value of typical anticholinergic symptoms was further quantified in this context.

METHODS AND FINDINGS

To predict falls, models were developed and validated based on logistic regression models created using data from two German cluster-randomized controlled trials. The outcome was defined as "≥ 1 fall" vs. "no fall" within a 6-month follow-up period. Data from the RIME study (n = 1,197) were used in model development, and from PRIMUM (n = 502) for external validation. The models were developed step-wise in order to quantify the predictive ability of anticholinergic burden measures, and anticholinergic symptoms. In the development set, 1,015 patients had complete data and 188 (18.5%) experienced ≥ 1 fall within the 6-month follow-up period. The overall predictive value of the five anticholinergic measures was limited, with neither the employed anticholinergic variable (binary / count / burden), nor dose-dependent or dose-independent measures differing significantly in their ability to predict falls. The highest c-statistic was obtained using the German Anticholinergic Burden Score (0.73), whereby the optimism-corrected c-statistic was 0.71 after interval validation using bootstrapping and 0.63 in the external validation. Previous falls and dizziness / vertigo had the strongest prognostic value in all models.

CONCLUSIONS

The ability of anticholinergic burden measures to predict falls does not appear to differ significantly, and the added value they contribute to risk classification in fall-prediction models is limited. Previous falls and dizziness / vertigo contributed most to model performance.

HIOPP-6 – a pilot study on the evaluation of an electronic tool to assess and reduce the complexity of drug treatment considering patients’ views

Background

A complex drug treatment might pose a barrier to safe and reliable drug administration for patients. Therefore, a novel tool automatically analyzes structured medication data for factors possibly contributing to complexity and subsequently personalizes the results by evaluating the relevance of each identified factor for the patient by means of key questions. Hence, tailor-made optimization measures can be proposed.

Methods

In this controlled, prospective, exploratory trial the tool was evaluated with nine general practitioners (GP) in three study groups: In the two intervention groups the tool was applied in a version with (G_{I_with}) and a version without (G_{I_without}) integrated key questions for the personalization of the analysis, while the control group (G_C) did not use any tools (routine care). Four to eight weeks after application of the tool, the benefits of the optimization measures to reduce or mitigate complexity of drug treatment were evaluated from the patient perspective.

Results

A total of 126 patients regularly using more than five drugs could be included for analysis. GP suggested 117 optimization measures in G_{I_with}, 83 in G_{I_without}, and 2 in G_C. Patients in G_{I_with} were more likely to rate an optimization measure as helpful than patients in G_{I_without} (IRR: 3.5; 95% CI: 1.2—10.3). Thereby, the number of optimization measures recommended by the GP had no significant influence (P = 0.167).

Conclusions

The study suggests that an automated analysis considering patient perspectives results in more helpful optimization measures than an automated analysis alone – a result which should be further assessed in confirmatory studies.

Trial registration

The trial was registered retrospectively at the German Clinical Trials register under DRKS-ID DRKS00025257 (17/05/2021).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01757-0.

A prediction model for nonpersistence or nonadherence to direct oral anticoagulants in hospitalized patients with atrial fibrillation

BACKGROUND: Medication adherence and persistence is fundamental for drug effectiveness, which is also true for the prevention of strokes in patients with atrial fibrillation (AF). Adherence to direct oral anticoagulants (DOACs) as first-line agents is often high in the early posthospital period. However, adherence often sharply declines (or eventually leads to nonpersistence) in the post-discharge ambulatory period, rendering stroke prevention ineffective. If patients at high risk of nonpersistence or nonadherence could be identified early, they could be offered early intervention measures to improve adherence and/or persistence. OBJECTIVE: To develop and internally validate a predictive model for medication nonadherence and nonpersistence to DOAC treatment in patients with AF after discharge using health insurance claims data. METHODS: We selected health insurance claims data between 2011 and 2016 from 8,055 patients with AF who were newly treated with rivaroxaban or apixaban after a hospital admission for stroke, transient ischemic attack, or AF. In the post-discharge ambulatory period, medication adherence was derived as the proportion of days covered, calculated from drug dispensation data. A maximum permissible 90-day gap between the end of a prescription and the next dispensation was used to estimate persistence. Candidate predictors were either derived from the index hospital admission or summarized from the previous year (eg, comorbidities or medication adherence to long-term treatments, such as ß-blockers, renin-angiotensin system inhibitors, statins, and thyroid hormones). A regularized logistic regression model was fitted using the least absolute shrinkage and selection operator in a split-sample approach (66.7% training data; 33.3% test data) to predict a composite of medication nonadherence/nonpersistence. Discrimination performance was assessed using the area under the receiver operating characteristic curve, the maximum sensitivity/specificity, and the scaled Brier score. A calibration curve fitted by linear regression was used to evaluate model calibration. RESULTS: The average age of the study participants was 79.7 years, 62% were female, and 3,515 patients (44%) were adherent and persistent (median follow-up of 185 days). Medication adherence to previous long-term treatments showed strong predictive properties. The developed model discriminated well (concordance statistic: 0.755), was well calibrated, and showed a scaled Brier score of 0.202 for identification of patients at risk. CONCLUSIONS: The model successfully predicted medication non-adherence/nonpersistence to DOAC treatment after discharge. Such a model could help ensure that targeted interventions are already in place at the time of hospital discharge, potentially preventing strokes and reducing costs. DISCLOSURES: Mr Wirbka is funded by the German Innovation Funds according to § 92a (2) Volume V of the Social Insurance Code (§ 92a Abs. 2, SGBV-Fünftes Buch Sozialgesetzbuch), grant number: 01VSF18019. Dr Haefeli received financial support from Daiichi-Sankyo, app development (https://www.easydoac.de/), and Bayer. He also received personal speaker fees from Bristol Myers-Squibb and Daiichi-Sankyo Online Seminar. Dr Meid is funded by the Physician-Scientist Programme of the Medical Faculty of Heidelberg University.

Prevalence and patient-rated relevance of complexity factors in medication regimens of community-dwelling patients with polypharmacy

Purpose

To describe the prevalence of complexity factors in the medication regimens of community-dwelling patients with more than five drugs and to evaluate the relevance of these factors for individual patients.

Methods

Data were derived from the HIOPP-6 trial, a controlled study conducted in 9 general practices which evaluated an electronic tool to detect and reduce complexity of drug treatment. The prevalence of complexity factors was based on the results of the automated analysis of 139 patients’ medication data. The relevance assessment was based on the patients’ rating of each factor in an interview (48 patients included for analysis).

Results

A median of 5 (range 0–21) complexity factors per medication regimen were detected and at least one factor was observed in 131 of 139 patients. Almost half of these patients found no complexity factor in their medication regimen relevant.

Conclusion

In most medication regimens, complexity factors could be identified automatically, yet less than 15% of factors were indeed relevant for patients as judged by themselves. When assessing complexity of medication regimens, one should especially consider factors that are both particularly frequent and often challenging for patients, such as use of inhalers or tablet splitting.

Trial registration

The HIOPP-6 trial was registered retrospectively on May 17, 2021, in the German Clinical Trials register under DRKS-ID DRKS00025257.

Supplementary information

The online version contains supplementary material available at 10.1007/s00228-022-03314-1.

Predicting Hospital Readmissions from Health Insurance Claims Data: A Modeling Study Targeting Potentially Inappropriate Prescribing

BACKGROUND

 Numerous prediction models for readmissions are developed from hospital data whose predictor variables are based on specific data fields that are often not transferable to other settings. In contrast, routine data from statutory health insurances (in Germany) are highly standardized, ubiquitously available, and would thus allow for automatic identification of readmission risks.

OBJECTIVES

 To develop and internally validate prediction models for readmissions based on potentially inappropriate prescribing (PIP) in six diseases from routine data.

METHODS

 In a large database of German statutory health insurance claims, we detected disease-specific readmissions after index admissions for acute myocardial infarction (AMI), heart failure (HF), a composite of stroke, transient ischemic attack or atrial fibrillation (S/AF), chronic obstructive pulmonary disease (COPD), type-2 diabetes mellitus (DM), and osteoporosis (OS). PIP at the index admission was determined by the STOPP/START criteria (Screening Tool of Older Persons' Prescriptions/Screening Tool to Alert doctors to the Right Treatment) which were candidate variables in regularized prediction models for specific readmission within 90 days. The risks from disease-specific models were combined ("stacked") to predict all-cause readmission within 90 days. Validation performance was measured by the c-statistics.

RESULTS

 While the prevalence of START criteria was higher than for STOPP criteria, more single STOPP criteria were selected into models for specific readmissions. Performance in validation samples was the highest for DM (c-statistics: 0.68 [95% confidence interval (CI): 0.66-0.70]), followed by COPD (c-statistics: 0.65 [95% CI: 0.64-0.67]), S/AF (c-statistics: 0.65 [95% CI: 0.63-0.66]), HF (c-statistics: 0.61 [95% CI: 0.60-0.62]), AMI (c-statistics: 0.58 [95% CI: 0.56-0.60]), and OS (c-statistics: 0.51 [95% CI: 0.47-0.56]). Integrating risks from disease-specific models to a combined model for all-cause readmission yielded a c-statistics of 0.63 [95% CI: 0.63-0.64].

CONCLUSION

 PIP successfully predicted readmissions for most diseases, opening the possibility for interventions to improve these modifiable risk factors. Machine-learning methods appear promising for future modeling of PIP predictors in complex older patients with many underlying diseases.

Low Exposure to Direct Oral Anticoagulants Is Associated with Ischemic Stroke and Its Severity

Background and purpose

In acute stroke patients, plasma concentrations of direct oral anticoagulants (DOAC) at hospital admission only poorly mirror DOAC exposure or the coagulation status at the time of the event. Here, we evaluated whether DOAC exposure and DOAC plasma concentration at the time of transient ischemic attacks (TIA) and ischemic strokes correlate with their likelihood of occurrence.

Methods

Prospectively, consecutive DOAC patients with acute ischemic stroke or TIA were included. Admission DOAC plasma concentrations were measured by ultraperformance liquid chromatography– tandem mass spectrometry. Individual DOAC exposure (area under the curve) and DOAC concentrations at event onset were derived from population pharmacokinetic analyses.

Results

DOAC exposure was successfully modeled in 211 patients (ischemic stroke 74.4%, TIA 25.6%). Compared to published values, 63.0% had relatively lower DOAC exposure and they more often received lower DOAC doses than recommended (odds ratio [OR], 2.125; 95% confidence interval [CI], 1.039 to 4.560; P=0.044). These patients more likely suffered ischemic strokes than TIA (OR, 2.411; 95% CI, 1.254 to 4.638; P=0.008) and their strokes were more severe (slope, 3.161; 95% CI, 0.741 to 5.58; P=0.011). Low relative DOAC concentrations at event onset were likewise associated with ischemic strokes (OR, 4.123; 95% CI, 1.834 to 9.268; P=0.001), but not to stroke severity (P=0.272). DOAC exposure had a higher explanatory value for stroke severity than concentrations at event.

Conclusions

Low DOAC exposure is strongly associated to ischemic stroke and its severity. By monitoring DOAC plasma concentrations, patients prone to ischemic stroke might be identified.

Quantification of the Time Course of CYP3A Inhibition, Activation, and Induction Using a Population Pharmacokinetic Model of Microdosed Midazolam Continuous Infusion

BACKGROUND

Cytochrome P450 (CYP) 3A contributes to the metabolism of many approved drugs. CYP3A perpetrator drugs can profoundly alter the exposure of CYP3A substrates. However, effects of such drug-drug interactions are usually reported as maximum effects rather than studied as time-dependent processes. Identification of the time course of CYP3A modulation can provide insight into when significant changes to CYP3A activity occurs, help better design drug-drug interaction studies, and manage drug-drug interactions in clinical practice.

OBJECTIVE

We aimed to quantify the time course and extent of the in vivo modulation of different CYP3A perpetrator drugs on hepatic CYP3A activity and distinguish different modulatory mechanisms by their time of onset, using pharmacologically inactive intravenous microgram doses of the CYP3A-specific substrate midazolam, as a marker of CYP3A activity.

METHODS

Twenty-four healthy individuals received an intravenous midazolam bolus followed by a continuous infusion for 10 or 36 h. Individuals were randomized into four arms: within each arm, two individuals served as a placebo control and, 2 h after start of the midazolam infusion, four individuals received the CYP3A perpetrator drug: voriconazole (inhibitor, orally or intravenously), rifampicin (inducer, orally), or efavirenz (activator, orally). After midazolam bolus administration, blood samples were taken every hour (rifampicin arm) or every 15 min (remaining study arms) until the end of midazolam infusion. A total of 1858 concentrations were equally divided between midazolam and its metabolite, 1'-hydroxymidazolam. A nonlinear mixed-effects population pharmacokinetic model of both compounds was developed using NONMEM^®. CYP3A activity modulation was quantified over time, as the relative change of midazolam clearance encountered by the perpetrator drug, compared to the corresponding clearance value in the placebo arm.

RESULTS

Time course of CYP3A modulation and magnitude of maximum effect were identified for each perpetrator drug. While efavirenz CYP3A activation was relatively fast and short, reaching a maximum after approximately 2-3 h, the induction effect of rifampicin could only be observed after 22 h, with a maximum after approximately 28-30 h followed by a steep drop to almost baseline within 1-2 h. In contrast, the inhibitory impact of both oral and intravenous voriconazole was prolonged with a steady inhibition of CYP3A activity followed by a gradual increase in the inhibitory effect until the end of sampling at 8 h. Relative maximum clearance changes were +59.1%, +46.7%, -70.6%, and -61.1% for efavirenz, rifampicin, oral voriconazole, and intravenous voriconazole, respectively.

CONCLUSIONS

We could distinguish between different mechanisms of CYP3A modulation by the time of onset. Identification of the time at which clearance significantly changes, per perpetrator drug, can guide the design of an optimal sampling schedule for future drug-drug interaction studies. The impact of a short-term combination of different perpetrator drugs on the paradigm CYP3A substrate midazolam was characterized and can define combination intervals in which no relevant interaction is to be expected.

CLINICAL TRIAL REGISTRATION

The trial was registered at the European Union Drug Regulating Authorities for Clinical Trials (EudraCT-No. 2013-004869-14).

Can Machine Learning from Real-World Data Support Drug Treatment Decisions? A Prediction Modeling Case for Direct Oral Anticoagulants

BACKGROUND

Decision making for the "best" treatment is particularly challenging in situations in which individual patient response to drugs can largely differ from average treatment effects. By estimating individual treatment effects (ITEs), we aimed to demonstrate how strokes, major bleeding events, and a composite of both could be reduced by model-assisted recommendations for a particular direct oral anticoagulant (DOAC).

METHODS

In German claims data for the calendar years 2014-2018, we selected 29 901 new users of the DOACs rivaroxaban and apixaban. Random forests considered binary events within 1 y to estimate ITEs under each DOAC according to the X-learner algorithm with 29 potential effect modifiers; treatment recommendations were based on these estimated ITEs. Model performance was evaluated by the c-for-benefit statistics, absolute risk reduction (ARR), and absolute risk difference (ARD) by trial emulation.

RESULTS

A significant proportion of patients would be recommended a different treatment option than they actually received. The stroke model significantly discriminated patients for higher benefit and thus indicated improved decisions by reduced outcomes (c-for-benefit: 0.56; 95% confidence interval [0.52; 0.60]). In the group with apixaban recommendation, the model also improved the composite endpoint (ARR: 1.69 % [0.39; 2.97]). In trial emulations, model-assisted recommendations significantly reduced the composite event rate (ARD: -0.78 % [-1.40; -0.03]).

CONCLUSIONS

If prescribers are undecided about the potential benefits of different treatment options, ITEs can support decision making, especially if evidence is inconclusive, risk-benefit profiles of therapeutic alternatives differ significantly, and the patients' complexity deviates from "typical" study populations. In the exemplary case for DOACs and potentially in other situations, the significant impact could also become practically relevant if recommendations were available in an automated way as part of decision making.HighlightsIt was possible to calculate individual treatment effects (ITEs) from routine claims data for rivaroxaban and apixaban, and the characteristics between the groups with recommendation for one or the other option differed significantly.ITEs resulted in recommendations that were significantly superior to usual (observed) treatment allocations in terms of absolute risk reduction, both separately for stroke and in the composite endpoint of stroke and major bleeding.When similar patients from routine data were selected (precision cohorts) for patients with a strong recommendation for one option or the other, those similar patients under the respective recommendation showed a significantly better prognosis compared with the alternative option.Many steps may still be needed on the way to clinical practice, but the principle of decision support developed from routine data may point the way toward future decision-making processes.

Teaching reproducible research for medical students and postgraduate pharmaceutical scientists

In medicine and other academic settings, (doctoral) students often work in interdisciplinary teams together with researchers of pharmaceutical sciences, natural sciences in general, or biostatistics. They should be fundamentally taught good research practices, especially in terms of statistical analysis. This includes reproducibility as a central aspect. Acknowledging that even experienced researchers and supervisors might be unfamiliar with necessary aspects of a perfectly reproducible workflow, a lecture series on reproducible research (RR) was developed for young scientists in clinical pharmacology. The pilot series highlighted definitions of RR, reasons for RR, potential merits of RR, and ways to work accordingly. In trying to actually reproduce a published analysis, several practical obstacles arose. In this article, reproduction of a working example is commented to emphasize the manifold facets of RR, to provide possible explanations for difficulties and solutions, and to argue that harmonized curricula for (quantitative) clinical researchers should include RR principles. These experiences should raise awareness among educators and students, supervisors and young scientists. RR working habits are not only beneficial for ourselves or our students, but also for other researchers within an institution, for scientific partners, for the scientific community, and eventually for the public profiting from research findings.

The impact of a computerized physician order entry system implementation on 20 different criteria of medication documentation-a before-and-after study

Background

The medication process is complex and error-prone. To avoid medication errors, a medication order should fulfil certain criteria, such as good readability and comprehensiveness. In this context, a computerized physician order entry (CPOE) system can be helpful. This study aims to investigate the distinct effects on the quality of prescription documentation of a CPOE system implemented on general wards in a large tertiary care hospital.

Methods

In a retrospective analysis, the prescriptions of two groups of 160 patients each were evaluated, with data collected before and after the introduction of a CPOE system. According to nationally available recommendations on prescription documentation, it was assessed whether each prescription fulfilled the established 20 criteria for a safe, complete, and actionable prescription. The resulting fulfilment scores (prescription-Fscores) were compared between the pre-implementation and the post-implementation group and a multivariable analysis was performed to identify the effects of further covariates, i.e., the prescription category, the ward, and the number of concurrently prescribed drugs. Additionally, the fulfilment of the 20 criteria was assessed at an individual criterion-level (denoted criteria-Fscores).

Results

The overall mean prescription-Fscore increased from 57.4% ± 12.0% (n = 1850 prescriptions) before to 89.8% ± 7.2% (n = 1592 prescriptions) after the implementation (p < 0.001). At the level of individual criteria, criteria-Fscores significantly improved in most criteria (n = 14), with 6 criteria reaching a total score of 100% after CPOE implementation. Four criteria showed no statistically significant difference and in two criteria, criteria-Fscores deteriorated significantly. A multivariable analysis confirmed the large impact of the CPOE implementation on prescription-Fscores which was consistent when adjusting for the confounding potential of further covariates.

Conclusions

While the quality of prescription documentation generally increases with implementation of a CPOE system, certain criteria are difficult to fulfil even with the help of a CPOE system. This highlights the need to accompany a CPOE implementation with a thorough evaluation that can provide important information on possible improvements of the software, training needs of prescribers, or the necessity of modifying the underlying clinical processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01607-6.

Renal Safety of Hydroxyethyl starch 130/0.42 After Cardiac Surgery: A Retrospective Cohort Analysis

Introduction

The risk for renal complications from hydroxyethyl starch 130/0.42 (HES) impacts treatment decisions in patients after cardiac surgery.

Objective

The objective of this study was to determine the impact of postoperatively administered HES on renal function and 90-day mortality compared to sole crystalloid administration in patients after elective cardiac surgery.

Methods

Using electronic health records from a university hospital, confounding-adjusted models analyzed the associations between postoperative HES administration and the occurrence of postoperative acute kidney injury. In addition, 90-day mortality was evaluated. The impact of HES dosage and timing on renal function on trajectories of estimated glomerular filtration rates over the postoperative period was investigated using linear mixed-effects models.

Results

Overall 1009 patients (45.0%) experienced acute kidney injury. Less acute kidney injury occurred in patients receiving HES compared with patients receiving only crystalloids for fluid resuscitation (43.7% vs 51.2%, p = 0.008). In multivariate acute kidney injury models, HES had a protective association (odds ratio: 0.89; 95% confidence interval 0.82–0.96). Crystalloids were not as protective as HES (odds ratio: 0.98; 95% confidence interval 0.95–1.00). There was no association between HES and 90-day mortality (odds ratio: 1.05; 95% confidence interval 0.88–1.25). Renal function trajectories were dose dependent and biphasic, HES appeared to slow down the late postoperative decline.

Conclusions

This study showed no association between HES and the postoperative occurrence of acute kidney injury and thus further closes the evidence gap on HES safety in cardiac surgery patients. Although this was a retrospective cohort study, the results indicated that HES might be safely administered to cardiac surgery patients with regard to renal outcomes, especially if it was administered early and dosed appropriately.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01116-5.

Comparison of Five Lists to Identify Potentially Inappropriate Use of Non-Steroidal Anti-Inflammatory Drugs in Older Adults

OBJECTIVE

To compare the prevalence of potentially inappropriate non-steroidal anti-inflammatory drugs (NSAIDs) among NSAIDs users defined with frequently used potentially inappropriate medication (PIM) lists and to identify the determinants of their use.

DESIGN AND SETTING

Cross-sectional survey among community-dwelling older adults from Germany.

SUBJECTS

N = 284 NSAIDs users aged 65-89 years.

METHODS

All currently regularly or as-needed used drugs were recorded during a home visit. Multivariate logistic regression models were applied to assess the potential determinants of potentially inappropriate NSAIDs use.

RESULTS

Prevalence of potentially inappropriate NSAIDs use was 54.2%, 45.4%, 29.9%, 20.4%, and 3.5% when applying the STOPP, 2019 Beers, EU(7)-PIM, FORTA, and PRISCUS list, respectively. No study participant was identified as a potentially inappropriate NSAIDs user by all five lists simultaneously. The majority (68%) were identified only by one or two lists. Merely the STOPP and Beers criteria had a moderate inter-instrument agreement. Lower pain severity, gout, peptic ulcer (PU), cardiovascular disease (CVD), and chronic kidney disease (CKD) were statistically significantly associated with potentially inappropriate NSAIDs use defined by the STOPP criteria and the latter three conditions also with the 2019 Beers criteria.

CONCLUSIONS

The STOPP and Beers criteria may be superior to the other lists because they more frequently identify potentially inappropriate NSAIDs use in conditions implying a high risk for NSAIDs' adverse events (i.e., PUD, CKD and CVD). We developed a harmonized, country-independent PIM list for NSAIDs with the same advantages as observed for the STOOP and 2019 Beers criteria and recommended its use.

Disease-dependent variations in the timing and causes of readmissions in Germany: A claims data analysis for six different conditions

BACKGROUND

Hospital readmissions place a major burden on patients and health care systems worldwide, but little is known about patterns and timing of readmissions in Germany.

METHODS

We used German health insurance claims (AOK, 2011-2016) of patients ≥ 65 years hospitalized for acute myocardial infarction (AMI), heart failure (HF), a composite of stroke, transient ischemic attack, or atrial fibrillation (S/AF), chronic obstructive pulmonary disease (COPD), type 2 diabetes mellitus, or osteoporosis to identify hospital readmissions within 30 or 90 days. Readmissions were classified into all-cause, specific, and non-specific and their characteristics were analyzed.

RESULTS

Within 30 and 90 days, about 14-22% and 27-41% index admissions were readmitted for any reason, respectively. HF and S/AF contributed most index cases, and HF and COPD accounted for most all-cause readmissions. Distributions and ratios of specific to non-specific readmissions were disease-specific with highest specific readmissions rates among COPD and AMI.

CONCLUSION

German claims are well-suited to investigate readmission causes if longer periods than 30 days are evaluated. Conditions closely related with the primary disease are the most frequent readmission causes, but multiple comorbidities among readmitted cases suggest that a multidisciplinary care approach should be implemented vigorously addressing comorbidities already during the index hospitalization.

Predicting negative health outcomes in older general practice patients with chronic illness: Rationale and development of the PROPERmed harmonized individual participant data database

The prevalence of multimorbidity and polypharmacy increases significantly with age and are associated with negative health consequences. However, most current interventions to optimize medication have failed to show significant effects on patient-relevant outcomes. This may be due to ineffectiveness of interventions themselves but may also reflect other factors: insufficient sample sizes, heterogeneity of population. To address this issue, the international PROPERmed collaboration was set up to obtain/synthesize individual participant data (IPD) from five cluster-randomized trials. The trials took place in Germany and The Netherlands and aimed to optimize medication in older general practice patients with chronic illness. PROPERmed is the first database of IPD to be drawn from multiple trials in this patient population and setting. It offers the opportunity to derive prognostic models with increased statistical power for prediction of patient-relevant outcomes resulting from the interplay of multimorbidity and polypharmacy. This may help patients from this heterogeneous group to be stratified according to risk and enable clinicians to identify patients that are likely to benefit most from resource/time-intensive interventions. The aim of this manuscript is to describe the rationale behind PROPERmed collaboration, characteristics of the included studies/participants, development of the harmonized IPD database and challenges faced during this process.

Are Anticholinergic Symptoms a Risk Factor for Falls in Older General Practice Patients With Polypharmacy? Study Protocol for the Development and Validation of a Prognostic Model

Background: Cumulative anticholinergic exposure, also known as anticholinergic burden, is associated with a variety of adverse outcomes. However, studies show that anticholinergic effects tend to be underestimated by prescribers, and anticholinergics are the most frequently prescribed potentially inappropriate medication in older patients. The grading systems and drugs included in existing scales to quantify anticholinergic burden differ considerably and do not adequately account for patients’ susceptibility to medications. Furthermore, their ability to link anticholinergic burden with adverse outcomes such as falls is unclear. This study aims to develop a prognostic model that predicts falls in older general practice patients, to assess the performance of several anticholinergic burden scales, and to quantify the added predictive value of anticholinergic symptoms in this context.

Methods: Data from two cluster-randomized controlled trials investigating medication optimization in older general practice patients in Germany will be used. One trial (RIME, n = 1,197) will be used for the model development and the other trial (PRIMUM, n = 502) will be used to externally validate the model. A priori, candidate predictors will be selected based on a literature search, predictor availability, and clinical reasoning. Candidate predictors will include socio-demographics (e.g. age, sex), morbidity (e.g. single conditions), medication (e.g. polypharmacy, anticholinergic burden as defined by scales), and well-being (e.g. quality of life, physical function). A prognostic model including sociodemographic and lifestyle-related factors, as well as variables on morbidity, medication, health status, and well-being, will be developed, whereby the prognostic value of extending the model to include additional patient-reported symptoms will be also assessed. Logistic regression will be used for the binary outcome, which will be defined as “no falls” vs. “≥1 fall” within six months of baseline, as reported in patient interviews.

Discussion: As the ability of different anticholinergic burden scales to predict falls in older patients is unclear, this study may provide insights into their relative importance as well as into the overall contribution of anticholinergic symptoms and other patient characteristics. The results may support general practitioners in their clinical decision-making and in prescribing fewer medications with anticholinergic properties.

Using the Causal Inference Framework to Support Individualized Drug Treatment Decisions Based on Observational Healthcare Data

When healthcare professionals have the choice between several drug treatments for their patients, they often experience considerable decision uncertainty because many decisions simply have no single “best” choice. The challenges are manifold and include that guideline recommendations focus on randomized controlled trials whose populations do not necessarily correspond to specific patients in everyday treatment. Further reasons may be insufficient evidence on outcomes, lack of direct comparison of distinct options, and the need to individually balance benefits and risks. All these situations will occur in routine care, its outcomes will be mirrored in routine data, and could thus be used to guide decisions. We propose a concept to facilitate decision-making by exploiting this wealth of information. Our working example for illustration assumes that the response to a particular (drug) treatment can substantially differ between individual patients depending on their characteristics (heterogeneous treatment effects, HTE), and that decisions will be more precise if they are based on real-world evidence of HTE considering this information. However, such methods must account for confounding by indication and effect measure modification, eg, by adequately using machine learning methods or parametric regressions to estimate individual responses to pharmacological treatments. The better a model assesses the underlying HTE, the more accurate are predicted probabilities of treatment response. After probabilities for treatment-related benefit and harm have been calculated, decision rules can be applied and patient preferences can be considered to provide individual recommendations. Emulated trials in observational data are a straightforward technique to predict the effects of such decision rules when applied in routine care. Prediction-based decision rules from routine data have the potential to efficiently supplement clinical guidelines and support healthcare professionals in creating personalized treatment plans using decision support tools.

Pain severity and analgesics use in the community-dwelling older population: a drug utilization study from Germany

Purpose

Chronic pain is common in the older population and a significant public health concern. However, comprehensive studies on analgesics use in this age group from Germany are scarce. This study aims to give a comprehensive overview on the use of the most common therapeutic groups of analgesics in community-dwelling older adults from Germany.

Methods

A cross-sectional study was carried out using data from a German cohort of 2038 community-dwelling adults aged 63–89 years. Descriptive statistics and logistic regression models were applied to assess the utilization of analgesics by age, sex, pain severity, pain duration, and locations.

Results

One out of four study participants was suffering from high-intensity or disabling pain. Approximately half of those taking analgesics still reported to suffer from high-intensity or disabling pain. Among analgesics users, occasional non-steroidal anti-inflammatory drugs (NSAIDs) use was the most frequent pain therapy (in 43.6% of users), followed by metamizole (dipyrone) use (16.1%), regular NSAIDs use (12.9%), strong opioids use (12.7%), and weak opioids use (12.0%). In multivariate logistic regression models, higher age, higher pain severity, longer pain duration, abdominal pain, and back pain were statistically significantly associated with opioids use. Metamizole use was also statistically significantly associated with higher pain severity but inversely associated with pain duration.

Conclusions

A significant number of older German adults are affected by high-intensity and disabling chronic pain despite receiving analgesics. Long-term studies are needed to compare the effectiveness and safety of different treatments for chronic pain in older adults.

Electronic supplementary material

The online version of this article (10.1007/s00228-020-02954-5) contains supplementary material, which is available to authorized users.

A framework to build similarity-based cohorts for personalized treatment advice - a standardized, but flexible workflow with the R package SimBaCo

Along with increasing amounts of big data sources and increasing computer performance, real-world evidence from such sources likewise gains in importance. While this mostly applies to population averaged results from analyses based on the all available data, it is also possible to conduct so-called personalized analyses based on a data subset whose observations resemble a particular patient for whom a decision is to be made. Claims data from statutory health insurance companies could provide necessary information for such personalized analyses. To derive treatment recommendations from them for a particular patient in everyday care, an automated, reproducible and efficiently programmed workflow would be required. We introduce the R-package SimBaCo (Similarity-Based Cohort generation) offering a simple, but modular, and intuitive framework for this task. With the six built-in R-functions, this framework allows the user to create similarity cohorts tailored to the characteristics of particular patients. An exemplary workflow illustrates the distinct steps beginning with an initial cohort selection according to inclusion and exclusion criteria. A plotting function facilitates investigating a particular patient’s characteristics relative to their distribution in a reference cohort, for example the initial cohort or the precision cohort after the data has been trimmed in accordance with chosen variables for similarity finding. Such precision cohorts allow any form of personalized analysis, for example personalized analyses of comparative effectiveness or customized prediction models developed from precision cohorts. In our exemplary workflow, we provide such a treatment comparison whereupon a treatment decision for a particular patient could be made. This is only one field of application where personalized results can directly support the process of clinical reasoning by leveraging information from individual patient data. With this modular package at hand, personalized studies can efficiently weight benefits and risks of treatment options of particular patients.

New Insights Into the Pharmacokinetics of Vancomycin After Oral and Intravenous Administration: An Investigation in Beagle Dogs

Intestinal absorption of orally administered peptides is often negligible because one or more key requirements for successful absorption (water solubility, peptic resistance, mucosal permeation) are not met. Due to its high water solubility and stability in the gastro-intestinal tract, vancomycin is an ideal model peptide for evaluating the factors influencing the critical step of mucosal permeation. Therefore, to support formulation development for the systemic oral delivery of peptide therapeutics, we investigated the pharmacokinetics of vancomycin in beagle dogs after intravenous and oral administration comparing enteric encapsulated drug to the drug in solution, which revealed mean absolute bioavailabilities of 0.27% and 1.66%, respectively. Additionally, in depth pharmacokinetic analyses of intravenously administered vancomycin revealed a deep compartment slowly releasing the compound over many hours into the blood.

Phase I/II intra-patient dose escalation study of vorinostat in children with relapsed solid tumor, lymphoma, or leukemia

Background

Until today, adult and pediatric clinical trials investigating single-agent or combinatorial HDAC inhibitors including vorinostat in solid tumors have largely failed to demonstrate efficacy. These results may in part be explained by data from preclinical models showing significant activity only at higher concentrations compared to those achieved with current dosing regimens. In the current pediatric trial, we applied an intra-patient dose escalation design.

The purpose of this trial was to determine a safe dose recommendation (SDR) of single-agent vorinostat for intra-patient dose escalation, pharmacokinetic analyses (PK), and activity evaluation in children (3–18 years) with relapsed or therapy-refractory malignancies.

Results

A phase I intra-patient dose (de)escalation was performed until individual maximum tolerated dose (MTD). The starting dose was 180 mg/m²/day with weekly dose escalations of 50 mg/m² until DLT/maximum dose. After MTD determination, patients seamlessly continued in phase II with disease assessments every 3 months. PK and plasma cytokine profiles were determined. Fifty of 52 patients received treatment. n = 27/50 (54%) completed the intra-patient (de)escalation and entered phase II. An SDR of 130 mg/m²/day was determined (maximum, 580 mg/m²/day). n = 46/50 (92%) patients experienced treatment-related AEs which were mostly reversible and included thrombocytopenia, fatigue, nausea, diarrhea, anemia, and vomiting. n = 6/50 (12%) had treatment-related SAEs. No treatment-related deaths occurred. Higher dose levels resulted in higher C_max. Five patients achieved prolonged disease control (> 12 months) and showed a higher C_max (> 270 ng/mL) and MTDs. Best overall response (combining PR and SD, no CR observed) rate in phase II was 6/27 (22%) with a median PFS and OS of 5.3 and 22.4 months. Low levels of baseline cytokine expression were significantly correlated with favorable outcome.

Conclusion

An SDR of 130 mg/m²/day for individual dose escalation was determined. Higher drug exposure was associated with responses and long-term disease stabilization with manageable toxicity. Patients with low expression of plasma cytokine levels at baseline were able to tolerate higher doses of vorinostat and benefited from treatment. Baseline cytokine profile is a promising potential predictive biomarker.

Trial registration

ClinicalTrials.gov, NCT01422499. Registered 24 August 2011,

Evidence for underuse and overuse of antidepressants in older adults: Results of a large population-based study

OBJECTIVES

Depression is common among elderly people. However, diagnosis and adequate treatment is frequently difficult. Research on underuse and overuse of antidepressants in elderly persons is scarce. This study investigates the utilization and appropriateness of pharmacological and psychological depression treatment in a large cohort of community-dwelling adults.

METHODS

A subsample of 3117 participants (aged 55-85 y) of the third follow-up (2008-2010) of the large population-based German ESTHER study was included. Depression was assessed using the eight-item Patient Health Questionnaire (PHQ-8). In the course of a home visit, study doctors collected complete information on medication. Logistic regression analyses were conducted to determine the relationship of depression with both underuse and overuse of antidepressants. The analyses were then adjusted for socioeconomic variables, psychosomatic comorbidities, and motivation to seek help.

RESULTS

One hundred sixty-three participants (5.2%; 95% confidence interval [CI], 4.5-6.1) fulfilled the criteria for major depression. Underuse of antidepressants was present in 126 depressed participants (77.3%; 70.1-83.5). Persons who were motivated to seek help, who had an established depression diagnosis, or who were taking more than five different medications had lower odds of underuse. Anxiety was associated with higher odds for underuse. Overuse of antidepressants (prescription without clinical indication) was found in 96 cases (41.7%; 35.3-48.4) of all antidepressant prescriptions.

CONCLUSIONS

Depression treatment in older adults is frequently insufficient; it appears to depend on diagnosis as well as the patients' motivation to seek help. Education regarding the diagnosis of depression in the elderly as well as guidelines for appropriate treatment is needed.

The Role of Adherence Thresholds for Development and Performance Aspects of a Prediction Model for Direct Oral Anticoagulation Adherence

Patients who do not sufficiently adhere to their dosing regimens will, ultimately, do not get the full benefit of their medication. For example, if direct oral anticoagulants (DOAC) are not taken continuously, an intervention to improve adherence or maintain persistence will show direct effects on clinical outcomes. Usually, adherent patients are defined by taking ≥80% of their medication. The resulting binary adherence status from this threshold can as well be used for predictive classification. Thus, the threshold can determine the prediction model’s performance to identify patients at risk for poor adherence by this binary adherence status. In this perspective, we propose a plan for model development and performance considering the threshold’s role. Concerning development demands, we extracted predictors from a systematic literature search on DOAC adherence to be used as a core set of candidate predictors. Independently, we investigated how well a future model would technically have to perform by modeling drug intake and thromboembolic events based on a rivaroxaban pharmacokinetic-pharmacodynamic model. Using this simulation framework for different thresholds, we projected the impact of an imperfectly predicted adherence status on the event risk, and how imperfect sensitivity and specificity affect the cost balance if a supporting intervention was offered to patients classified as non-adherent. Our simulation results suggest applying a rather high threshold (90%) for discrimination between patients at low or high risk for non-adherence by a prediction model in order to assure cost-efficient implementation.

[Management of chronic pain using extended release tilidine : Quality of life and implication of comedication on tilidine metabolism]

BACKGROUND AND OBJECTIVES

The synthetic opioid tilidine is often used in chronic pain treatment. However, the activation via metabolism in patients with concomitant medication and reduced liver or kidney function is not thoroughly investigated. We therefore studied pain treatment efficacy, health-related quality of live and the metabolism of tilidine in patients with chronic pain.

METHODS AND MATERIALS

In all, 48 patients, who were on a stable dose of oral prolonged release tilidine for at least 7 days, were included in this observational multicenter study. Liver and kidney function were assessed in routine blood samples, concentrations of tilidine, nortilidine and bisnortilidine were determined using a validated LC/MS/MS method. Comedication was registered and patients experience with regard to quality of life, pain, gastrointestinal symptoms and adverse events was assessed in standardised questionnaires.

RESULTS

On average a daily dose of 180 mg tilidine was taken. Dose normalized plasma concentrations of the active metabolite nortilidine ranged between 1.6 ng/ml and 76.5 ng/ml (mean 29.2 ± 25.1 ng/ml). Ratios between tilidine and nortilidine were on average 0.28 (median = 0.13, standard deviation = 0.67). Patients were on 1 to 14 different concomitant medications. About 66% of the patients had sufficient pain treatment. Almost no opioid-induced constipation was observed. Only few patients had decreased kidney or liver function which did not result in elevated nortilidine concentrations.

CONCLUSION

Pain treatment using tilidine resulted in variable nortilidine concentrations which are obviously not strongly influenced by comedication or reduced liver or kidney function. Only a few side effects were observed with almost no opioid-induced constipation.

Prediction of Drug-Related Risks Using Clinical Context Information in Longitudinal Claims Data

OBJECTIVES

To develop and internally validate prediction models for medication-related risks arising from overuse, misuse, and underuse that utilize clinical context information and are suitable for routine risk assessment in claims data (i.e., medication-based models predicting the risk for hospital admission apparent in routine claims data or MEDI-RADAR).

METHODS

Based on nationwide claims from health-insured persons in Germany between 2010 and 2012, we drew a random sample of people aged ≥65 years (N = 22,500 randomly allocated to training set, N = 7500 to validation set). Individual duration of drug supply was estimated from prescription patterns to yield time-varying drug exposure windows. Together with concurrent medical conditions (ICD-10 diagnoses), exposure to the STOPP/START (screening tool of older persons' potentially inappropriate prescriptions/screening tool to alert doctors to the right treatment) criteria was derived. These were tested as time-dependent covariates together with time-constant covariates (patient demographics, baseline comorbidities) in regularized Cox regression models.

RESULTS

STOPP/START variables were iteratively refined and selected by regularization to include 2 up to 11 START variables and 8 up to 31 STOPP variables in parsimonious and liberal selections in the prediction modeling. The models discriminated well between patients with and without all-cause hospitalizations, potentially drug-induced hospitalizations, and mortality (parsimonious model c-indices with 95% confidence intervals: 0.63 [0.62-0.64], 0.67 [0.65-0.68], and 0.78 [0.76-0.80]).

CONCLUSIONS

The STOPP/START criteria proved to efficiently predict medication-related risk in models possessing good performance. Timely detection of such risks by routine monitoring in claims data can support tailored interventions targeting these modifiable risk factors. Their impact on older peoples' medication safety and effectiveness can now be explored in future implementation studies.

Rivaroxaban and macitentan can be coadministered without dose adjustment but the combination of rivaroxaban and St John's wort should be avoided

AIMS

We assessed the potential mutual interaction of oral macitentan (cytochrome P450 (CYP) 3A4 substrate) at steady-state with single-dose oral rivaroxaban (CYP3A4 and P-glycoprotein substrate) and evaluated the effect of the CYP3A and P-glycoprotein inducer St John's wort (SJW) on the pharmacokinetics of these drugs in healthy volunteers.

METHODS

Twelve healthy volunteers completed this open-label, monocentre, two-period, one-sequence phase I clinical trial. The pharmacokinetics of macitentan (10 mg) was assessed on study days 3 (single dose), 15 (steady-state), 16 (impact of rivaroxaban) and 29 (after induction by oral SJW), and of rivaroxaban on days 2 (single dose), 16 (impact of macitentan at steady-state) and 29 (after induction by SJW). Concurrently, we quantified changes of CYP3A activity using oral microdoses of midazolam (30 μg).

RESULTS

Rivaroxaban and macitentan did not significantly change the pharmacokinetics of each other. After induction with SJW, CYP3A activity increased by 272% and geometric mean ratios of macitentan AUC decreased by 48% and of C_max by 45%. Concurrently, also geometric mean ratios of rivaroxaban AUC and C_max decreased by 25%.

CONCLUSIONS

There is no evidence for a relevant pharmacokinetic interaction between macitentan and rivaroxaban suggesting that these two drugs can be combined without dose adjustment. SJW strongly increased CYP3A activity and substantially reduced rivaroxaban and macitentan exposure while estimated net endothelin antagonism only decreased by 20%, which is considered clinically irrelevant. The combination of SJW with rivaroxaban should be avoided.

The impact of potentially inappropriate medication on the development of health care costs and its moderation by the number of prescribed substances. Results of a retrospective matched cohort study

Background

In the growing population of the elderly, drug-related problems are considered an important health care safety issue. One aspect of this is the prescription of potentially inappropriate medication (PIM) which is considered to increase health care costs.

Objective

Using data from the Health Economics of Potentially Inappropriate Medication (HEPIME) study, we aimed to analyze how the number of prescribed substances moderates the association of PIM use as defined by the German PRISCUS list and health care costs applying a longitudinal perspective.

Methods

An initial number of 6,849,622 insurants aged 65+ of a large German health insurance company were included in a retrospective matched cohort study. Based on longitudinal claims data from the four separate quarters of a 12-month pre-period, 3,860,842 individuals with no exposure to PIM in 2011 were matched to 508,212 exposed individuals. Exposure effects of PIM use on health care costs and the number of prescribed substances were measured based on longitudinal claims data from the four separate quarters of the 12-month post-period.

Results

After successful balancing for the development of numerous matching variables during the four quarters of the pre-period, exposed individuals consumed 2.1 additional prescribed substances and had higher total health care costs of 1,237 € when compared to non-exposed individuals in the 1st quarter of the post-period. Controlling for the number of prescribed substances, the difference in total health care costs between both study groups was 401 €. The average effect of one additionally prescribed substance (other than PIM) on total health care costs was increased by an amount of 137 € for those being exposed to a PIM. In quarters 2–4 of the post-period, the differences between both study groups tended to decrease sequentially.

Conclusions

PIM use has an increasing effect on the development of health care costs. This cost-increasing effect of PIM use is moderated by the number of prescribed substances.

Changes in prescribed medicines in older patients with multimorbidity and polypharmacy in general practice

Background

Treatment complexity rises in line with the number of drugs, single doses, and administration methods, thereby threatening patient adherence. Patients with multimorbidity often need flexible, individualised treatment regimens, but alterations during the course of treatment may further increase complexity. The objective of our study was to explore medication changes in older patients with multimorbidity and polypharmacy in general practice.

Methods

We retrospectively analysed data from the cluster-randomised PRIMUM trial (PRIoritisation of MUltimedication in Multimorbidity) conducted in 72 general practices. We developed an algorithm for active pharmaceutical ingredients (API), strength, dosage, and administration method to assess changes in physician-reported medication data during two intervals (baseline to six-months: ∆₁; six- to nine-months: ∆₂), analysed them descriptively at prescription and patient levels, and checked for intervention effects.

Results

Of 502 patients (median age 72 years, 52% female), 464 completed the study. Changes occurred in 98.6% of patients (changes were 19% more likely in the intervention group): API changes during ∆₁ and ∆₂ occurred in 414 (82.5%) and 338 (67.3%) of patients, dosage alterations in 372 (74.1%) and 296 (59.2%), and changes in API strength in 158 (31.5%) and 138 (27.5%) respectively. Administration method changed in 79 (16%) of patients in both ∆₁ and ∆₂. Simvastatin, metformin and aspirin were most frequently subject to alterations.

Conclusion

Medication regimens in older patients with multimorbidity and polypharmacy changed frequently. These are mostly due to discontinuations and dosage alterations, followed by additions and restarts. These findings cast doubt on the effectiveness of cross-sectional assessments of medication and support longitudinal assessments where possible.

Trial registration.

1. Prospective registration: Trial registration number: NCT01171339; Name of registry: ClinicalTrials.gov; Date of registration: July 27, 2010; Date of enrolment of the first participant to the trial: August 12, 2010.

2. Peer reviewed trial registration: Trial registration number: ISRCTN99526053; Name of registry: Controlled Trials; Date of registration: August 31, 2010; Date of enrolment of the first participant to the trial: August 12, 2010.

Electronic supplementary material

The online version of this article (10.1186/s12875-018-0825-3) contains supplementary material, which is available to authorized users.

Combinations of QTc-prolonging drugs: towards disentangling pharmacokinetic and pharmacodynamic effects in their potentially additive nature

BACKGROUND

Whether arrhythmia risks will increase if drugs with electrocardiographic (ECG) QT-prolonging properties are combined is generally supposed but not well studied. Based on available evidence, the Arizona Center for Education and Research on Therapeutics (AZCERT) classification defines the risk of QT prolongation for exposure to single drugs. We aimed to investigate how combining AZCERT drug categories impacts QT duration and how relative drug exposure affects the extent of pharmacodynamic drug-drug interactions.

METHODS

In a cohort of 2558 psychiatric inpatients and outpatients, we modeled whether AZCERT class and number of coprescribed QT-prolonging drugs correlates with observed rate-corrected QT duration (QTc) while also considering age, sex, inpatient status, and other QTc-prolonging risk factors. We concurrently considered administered drug doses and pharmacokinetic interactions modulating drug clearance to calculate individual weights of relative exposure with AZCERT drugs. Because QTc duration is concentration-dependent, we estimated individual drug exposure with these drugs and included this information as weights in weighted regression analyses.

RESULTS

Drugs attributing a 'known' risk for clinical consequences were associated with the largest QTc prolongations. However, the presence of at least two versus one QTc-prolonging drug yielded nonsignificant prolongations [exposure-weighted parameter estimates with 95% confidence intervals for 'known' risk drugs + 0.93 ms (-8.88;10.75)]. Estimates for the 'conditional' risk class increased upon refinement with relative drug exposure and co-administration of a 'known' risk drug as a further risk factor.

CONCLUSIONS

These observations indicate that indiscriminate combinations of QTc-prolonging drugs do not necessarily result in additive QTc prolongation and suggest that QT prolongation caused by drug combinations strongly depends on the nature of the combination partners and individual drug exposure. Concurrently, it stresses the value of the AZCERT classification also for the risk prediction of combination therapies with QT-prolonging drugs.

Association of preventable adverse drug events with inpatients' length of stay-A propensity-matched cohort study

PURPOSE

Using clinical administrative data (CAD) of inpatients, we aimed to identify ICD-10 codes coding for potentially preventable inhospital adverse drug events (ADE) that affect the length of hospital stay (LOS) and thus patient well-being and cost.

METHODS

We retrospectively assessed CAD of all inpatient stays in 2012 of a German university hospital. Predefined ICD-10 codes indicating ADE (ADE codes) were further specified based on expert ratings of the ADE mechanism and ADE preventability in clinical routine to particularly identify preventable inhospital ADE. In a propensity-matched cohort design, we compared patients with one or more ADE codes to control patients with regard to differences in LOS for three situations: all cases with an ADE code, cases with an inhospital ADE code, and cases with a preventable inhospital ADE code.

RESULTS

Out of 54 032 cases analysed, in 8.3% (N=4 462) at least one ADE code was present. Nine of 128 evaluated ADE codes were rated as preventable in clinical routine, relating to 220 inpatients (4.9% of all identified inpatients with at least one ADE code and 0.4% of the entire cohort, respectively). Out of 48 072 evaluable inpatients for propensity score matching, 7 938 controls without ADE code and 4 006 cases with ADE code were selected. In all three settings, cases showed prolonged LOS vs controls (delta 1.13 d; 0.88 d and 1.88 d, respectively), significantly exceeding the maximum LOS as defined for each Diagnosis-Related Group.

CONCLUSION

Inpatients with ADE codes referring to inhospital, potentially preventable ADE exceeded the maximum hospital stay fully reimbursed by insurance companies, indicating unnecessary long and costly inpatient stays.

Is Polypharmacy Associated with Frailty in Older People? Results From the ESTHER Cohort Study

OBJECTIVES

To investigate the relationship between polypharmacy and frailty.

DESIGN

Longitudinal, observational cohort study.

SETTING

Saarland, Germany.

PARTICIPANTS

3,058 community-dwelling adults aged between 57 and 84 years.

MEASUREMENTS

Frailty was assessed according to the frailty phenotype, described by Fried et al. Polypharmacy and hyperpolypharmacy were defined as the concomitant use of five or more and 10 or more drugs, respectively. We assessed associations between polypharmacy and prevalent and incident frailty within 3 years of follow-up by logistic regression models controlled for multiple potential confounders including comorbidity. Additionally, cubic splines were used to assess dose-response associations.

RESULTS

Polypharmacy was reported in 39.1% (n = 1,194), and hyperpolypharmacy in 8.9% (n = 273) of participants. Prevalent frailty was present in 271 (8.9%) participants; 186 (9.3%) of 1,998 non-frail participants with follow-up data became frail within 3 years. After adjustment, polypharmacy and hyperpolypharmacy were associated with prevalent frailty with adjusted odds ratios (95% confidence interval) of 2.30 (1.60-3.31) and 4.97 (2.97-8.32), respectively. Polypharmacy (odds ratio (OR) 1.51 (1.05-2.16)) and hyperpolypharmacy (OR 1.90 (1.10-3.28)) were also independent predictors of incident frailty. Furthermore, there was a moderate exposure-response relationship between the number of medicines and prevalent as well as incident frailty.

CONCLUSION

Our study showed that polypharmacy is associated with frailty. Further research should address the potential benefit of reducing of inappropriate polypharmacy and better pharmacotherapeutic management for preventing medication-associated frailty.

How can we define and analyse drug exposure more precisely to improve the prediction of hospitalizations in longitudinal (claims) data?

BACKGROUND

Risk prediction models can be powerful tools to support clinical decision-making, to help targeting interventions, and, thus, to improve clinical and economic outcomes, provided that model performance is good and sensitivity and specificity are well balanced. Drug utilization as a potential risk factor for unplanned hospitalizations has recently emerged as a meaningful predictor variable in such models. Drug treatment is a rather unstable (i.e. time-dependent) phenomenon and most drug-induced events are concentration-dependent and therefore individual drug exposure will likely modulate the risk. This especially applies to longitudinal monitoring of appropriate drug treatment within claims data as another promising application for prediction models.

METHODS AND RESULTS

To guide future research towards this direction, we firstly reviewed current risk prediction models for unplanned hospitalizations that explicitly included information on drug utilization and were surprised to find that these models rarely attempted to consider dose and frequent modulators of drug clearance such as interactions with co-medication or co-morbidities. As another example, they often presumed class effects where in fact, differences between active moieties were well established. In addition, the study designs and statistical risk analysis disregarded the fact that medication and risk modulators and, thus, adverse events can vary over time. In a simulation study, we therefore evaluated the potential benefit of time-dependent Cox models over standard binary regression approaches with a fixed follow-up period.

CONCLUSIONS

Longitudinal drug information could be utilized much more efficiently both by precisely estimating individual drug exposure and by applying more refined statistical methodology to account for time-dependent drug utilization patterns.

Comparative evaluation of methods approximating drug prescription durations in claims data: modeling, simulation, and application to real data

PURPOSE

The purpose of this study was to compare the predictive accuracy of different methods suggested for approximation of drug prescription durations in claims data.

METHODS

We expanded a well-established modeling and simulation framework to compare approximated drug prescription durations with 'true' (i.e., simulated) durations. Real claims data of persons aged ≥65 years insured by the German nationwide 'Statutory Health Insurance Fund' AOK between 2010 and 2012 provided empiric input parameters that were completed with missing information on actual dosing patterns from an observational cohort. The distinct approximation methods were based on crude measures (one tablet a day), population-averaged measures (defined daily doses), or individually-derived measures (longitudinal coverage approximation of the applied dose, COV). As a proof-of-principle, we assessed the methods' performance to predict the well-characterized bleeding risks of anticoagulant, antiplatelet, and/or non-steroidal anti-inflammatory drugs.

RESULTS

When applied to modeling and simulation data sets, the closest, least biased, and thus most accurate approximation was observed using the COV approximation. In a real-data example, rather similar results to an external reference were obtained for all methods. However, some of the differences between methods were meaningful, and the most reasonable and consistent results were obtained with the COV approach.

CONCLUSION

Based on theoretically most accurate approximations and practically reasonable estimates, the individual COV approach was preferable over the population-averaged defined daily dose technique, although the latter might be justified in certain situations. Advantages of the COV approach are expected to be even bigger for drug therapies with particularly large dosing heterogeneity. Copyright © 2016 John Wiley & Sons, Ltd.