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Optimising plasma clozapine levels to improve treatment response: an individual patient data meta-analysis and receiver operating characteristic curve analysis

Published online by Cambridge University Press:  30 March 2023

Korinne Northwood
Affiliation:
Metro South Addiction and Mental Health Service, Metro South Health, Australia and Faculty of Medicine, University of Queensland, Australia
E. Pearson
Affiliation:
College of Medicine and Public Health, Flinders University, Australia
U. Arnautovska
Affiliation:
Metro South Addiction and Mental Health Service, Metro South Health, Australia and Faculty of Medicine, University of Queensland, Australia
S. Kisely
Affiliation:
Metro South Addiction and Mental Health Service, Metro South Health, Australia and Faculty of Medicine, University of Queensland, Australia
M. Pawar
Affiliation:
Metro South Addiction and Mental Health Service, Metro South Health, Australia
M. Sharma
Affiliation:
Department of Mental Health, Monash Health, Australia
K. Vitangcol
Affiliation:
Faculty of Medicine, University of Queensland, Australia
E. Wagner
Affiliation:
Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany
N. Warren
Affiliation:
Metro South Addiction and Mental Health Service, Metro South Health, Australia and Faculty of Medicine, University of Queensland, Australia
Dan Siskind*
Affiliation:
Metro South Addiction and Mental Health Service, Metro South Health, Australia and Faculty of Medicine, University of Queensland, Australia
*
Correspondence: Dan Siskind. Email: d.siskind@uq.edu.au
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Abstract

Background

Although clozapine is the most efficacious medication for treatment-refractory schizophrenia, not all patients will have an adequate response. Optimising clozapine dose using therapeutic drug monitoring could therefore maximise response.

Aims

Using individual patient data, we undertook a receiver operating characteristic (ROC) curve analysis to determine an optimal therapeutic range for clozapine levels to guide clinical practice.

Method

We conducted a systematic review of PubMed, PsycINFO and Embase for studies that provided individual participant level data on clozapine levels and response. These data were analysed using ROC curves to determine the prediction performance of plasma clozapine levels for treatment response.

Results

We included data on 294 individual participants from nine studies. ROC analysis yielded an area under the curve of 0.612. The clozapine level at the point of optimal diagnostic benefit was 372 ng/mL; at this level, the response sensitivity was 57.3%, and specificity 65.7%. The interquartile range for treatment response was 223–558 ng/mL. There was no improvement in ROC performance with mixed models including patient gender, age or length of trial. Clozapine dose and clozapine concentration to dose ratio did not provide significantly meaningful prediction of response to clozapine.

Conclusions

Clozapine dose should be optimised based on clozapine therapeutic levels. We found that a range between 250 and 550 ng/mL could be recommended, while noting that a level of >350 ng/mL is the most optimal for response. Although some patients may not respond without clozapine levels >550 ng/mL, the benefits should be weighed against the increased risk of adverse drug reactions.

Information

Type
Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists
Figure 0

Fig. 1 Receiver operating characteristic (ROC) analysis of clozapine treatment response. Non-parametric ROC analysis demonstrates that therapeutic level (solid line) is a better classifier of clozapine treatment response then chance (dotted line), with an area under the curve of 0.612 (95% CI 0.540.68). The Youden Index, indicating point of optimal response prediction was found at the clozapine level of 372 ng/mL, with a response specificity of 57.3% and sensitivity of 65.7%. FPR, false positive rate; TPR, true positive rate.

Figure 1

Fig. 2 Metric Youden Index by clozapine level cut-point. Youden Index integrates specificity and sensitivity to determine the point of highest ‘informedness’ for prediction of response by clozapine level, with Loess smoothing applied as the solid line over unsmoothed values. Youden Index peaks at clozapine levels between 350 and 500 ng/mL, tapering to zero from levels of >800 ng/mL.

Figure 2

Fig. 3 Two-sample Kolmogorov–Smirnov plot for cumulative distribution of positive and negative response values. Two-sample Kolmogorov–Smirnov test demonstrates that the non-responder patient population (light-blue line) and the responder patient population (dark-blue line) represent two distinct but similarly distributed populations (P = 0.21). The responder population demonstrates higher cumulative probability of response, diverging from the non-responder population at a clozapine level of ~250 ng/mL. The dashed blue line indicates the point of the Kolmogorov–Smirnov statistic, which is the widest divergence of the two populations, at 376.3 ng/mL, with grey shaded area representing the 95% confidence interval for prediction of response.

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