Item response theory in early phase clinical trials: Utilization of a reference model to analyze the Montgomery-Åsberg Depression Rating Scale.

In clinical trials, Montgomery-Åsberg Depression Rating Scale (MADRS) questionnaire data are added up to total scores before analysis, assuming equal contribution of each separate question. Item Response Theory (IRT)-based analysis avoids this by using individual question responses to determine the latent variable (ψ), which represents a measure of depression severity. However, utilization of IRT in early phase trials remains difficult, because large datasets are needed to develop IRT models. Therefore, we aimed to evaluate the application and assumptions of a reference IRT model for analysis of an early phase trial. A cross-over, placebo-controlled study investigating the effect of intravenous racemic ketamine on MADRS scores in patients with treatment-resistant major depressive disorder was used as a case study. One hundred forty-seven MADRS responses were measured in 17 patients at five timepoints (predose to 2 weeks after dosing). Two reference IRT models based on different patient populations were selected from literature and used to determine ψ, while testing multiple approaches regarding assumed data distribution. Use of ψ versus total score to determine treatment effect was compared through linear mixed model analysis. Results showed that determined ψ values did not differ significantly between assumed distributions, but were significantly different when changing reference IRT model. Estimated treatment effect size was not significantly affected by chosen approach nor reference population. Finally, increased precision to determine treatment effect was achieved by using IRT versus total scores. This demonstrates the usefulness of reference IRT model application for analysis of questionnaire data in early phase clinical trials.

Semimechanistic modeling of copeptin and aldosterone kinetics and dynamics in response to rehydration treatment for diabetic ketoacidosis in children.

Diabetic ketoacidosis (DKA), a frequent complication of type 1 diabetes (T1D), is characterized by hyperosmolar hypovolemia. The response of water-regulating hormones arginine vasopressin (AVP; antidiuretic hormone) and aldosterone to DKA treatment in children is not well understood, although they may have potential as future diagnostic, prognostic, and/or treatment monitoring markers in diabetic patients. We aimed to characterize the dynamics of the response in copeptin (marker for AVP) and aldosterone secretion to rehydration treatment in pediatric patients with DKA. Data originated from a prospective, observational, multicenter study including 28 pediatric T1D patients treated for DKA (median age, 11.5 years; weight, 35 kg). Serial measurements of hormone levels were obtained during 72 h following rehydration start. Semimechanistic pharmacometric modeling was used to analyze the kinetic/dynamic relationship of copeptin and aldosterone secretion in response to the correction of hyperosmolality and hypovolemia, respectively. Modeling revealed different sensitivities for osmolality-dependent copeptin secretion during the first 72 h of rehydration, possibly explained by an osmotic shift introduced by hypovolemia. Response in aldosterone secretion to the correction of hypovolemia seemed to be delayed, which was well described by an extra upstream turnover compartment, possibly representing chronic upregulation of aldosterone synthase (cytochrome P450 11B2). In conclusion, semimechanistic modeling provided novel physiological insights in hormonal water regulation in pediatric patients during DKA treatment, providing rationale to further evaluate the potential of monitoring copeptin, but not aldosterone due to its delayed response, for future optimization of rehydration treatment to reduce the risk of acute complications such as cerebral edema.

Transcranial magnetic stimulation as biomarker of excitability in drug development: A randomized, double-blind, placebo-controlled, cross-over study.

AIMS: The purpose of this study was to investigate pharmacodynamic effects of drugs targeting cortical excitability using transcranial magnetic stimulation (TMS) combined with electromyography (EMG) and electroencephalography (EEG) in healthy subjects, to further develop TMS outcomes as biomarkers for proof-of-mechanism in early-phase clinical drug development. Antiepileptic drugs presumably modulate cortical excitability. Therefore, we studied effects of levetiracetam, valproic acid and lorazepam on cortical excitability in a double-blind, placebo-controlled, 4-way cross-over study. METHODS: In 16 healthy male subjects, single- and paired-pulse TMS-EMG-EEG measurements were performed predose and 1.5, 7 and 24 hours postdose. Treatment effects on motor-evoked potential, short and long intracortical inhibition and TMS-evoked potential amplitudes, were analysed using a mixed model ANCOVA and cluster-based permutation analysis. RESULTS: We show that motor-evoked potential amplitudes decreased after administration of levetiracetam (estimated difference [ED] -378.4 µV; 95%CI: -644.3, -112.5 µV; P < .01), valproic acid (ED -268.8 µV; 95%CI: -532.9, -4.6 µV; P = .047) and lorazepam (ED -330.7 µV; 95%CI: -595.6, -65.8 µV; P = .02) when compared with placebo. Long intracortical inhibition was enhanced by levetiracetam (ED -60.3%; 95%CI: -87.1%, -33.5%; P < .001) and lorazepam (ED -68.2%; 95%CI: -94.7%, -41.7%; P < .001) at a 50-ms interstimulus interval. Levetiracetam increased TMS-evoked potential component N45 (P = .004) in a central cluster and decreased N100 (P < .001) in a contralateral cluster. CONCLUSION: This study shows that levetiracetam, valproic acid and lorazepam decrease cortical excitability, which can be detected using TMS-EMG-EEG in healthy subjects. These findings provide support for the use of TMS excitability measures as biomarkers to demonstrate pharmacodynamic effects of drugs that influence cortical excitability.