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Association between the glyco-metabolic adverse effects of antipsychotic drugs and their chemical and pharmacological profile: a network meta-analysis and regression

Published online by Cambridge University Press:  24 February 2021

Carla Carnovale
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy
Ersilia Lucenteforte
Affiliation:
Unit of Medical Statistics, Department of Clinical and Experimental Medicine, University of Pisa, Via Savi 10, 56126 Pisa, Italy
Vera Battini
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy
Faizan Mazhar
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy
Marco Fornili
Affiliation:
Unit of Medical Statistics, Department of Clinical and Experimental Medicine, University of Pisa, Via Savi 10, 56126 Pisa, Italy
Elena Invernizzi
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy
Giulia Mosini
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy
Michele Gringeri
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy
Annalisa Capuano
Affiliation:
Department of Experimental Medicine, Campania Regional Centre for Pharmacovigilance and Pharmacoepidemiology, Section of Pharmacology “L. Donatelli”, University of Campania “Luigi Vanvitelli”, Naples, Italy
Cristina Scavone
Affiliation:
Department of Experimental Medicine, Campania Regional Centre for Pharmacovigilance and Pharmacoepidemiology, Section of Pharmacology “L. Donatelli”, University of Campania “Luigi Vanvitelli”, Naples, Italy
Maria Nobile
Affiliation:
Scientific institute IRCCS E. Medea, Bosisio Parini, LC, 23892, Italy
Chiara Vantaggiato
Affiliation:
Scientific institute IRCCS E. Medea, Bosisio Parini, LC, 23892, Italy
Simone Pisano
Affiliation:
Department of Translational Medical Sciences, Federico II University, Naples, Italy Department of Neuroscience, AORN Santobono-Pausilipon, Naples, Italy
Carmela Bravaccio
Affiliation:
Department of Translational Medical Sciences, Federico II University, Naples, Italy
Sonia Radice
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy
Emilio Clementi*
Affiliation:
Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, “Luigi Sacco” University Hospital, Università di Milano, Milan, Italy Scientific institute IRCCS E. Medea, Bosisio Parini, LC, 23892, Italy
Marco Pozzi
Affiliation:
Scientific institute IRCCS E. Medea, Bosisio Parini, LC, 23892, Italy
*
Author for correspondence: Emilio Clementi, E-mail: emilio.clementi@unimi.it

Abstract

Background

Glyco-metabolic deteriorations are the most limiting adverse reactions to antipsychotics in the long term. They have been incompletely investigated and the properties of antipsychotics that determine their magnitude are not clarified.

To rank antipsychotics by the magnitude of glyco-metabolic alterations and to associate it to their pharmacological and chemical properties, we conducted a network meta-analysis.

Methods

We searched PubMed, Embase, and Psycinfo on 10 September 2020. We selected studies containing the endpoint-baseline difference or the distinct values of at least one outcome among glucose, HbA1c, insulin, HOMA-IR, triglycerides, total/HDL/LDL cholesterols. Of 2094 articles, 46 were included in network meta-analysis. Study quality was assessed by the RoB 2 and ROBINS-I tools. Mean differences (MD) were obtained by random-effects network meta-analysis; relations between MD and antipsychotic properties were analyzed by linear regressions. Antipsychotic properties investigated were acidic and basic pKa, polar surface area, polarizability, and occupancies of D2, H1, M1, M3, α1A, α2A, 5-HT1A, 5-HT2A, 5-HT2C receptors.

Results

We meta-analyzed 46 studies (11 464 patients); on average, studies lasted 15.47 weeks, patients had between 17.68 and 61.06 years of mean age and 61.64% were males. Olanzapine and clozapine associated with greater deteriorations, aripiprazole and ziprasidone with smaller deteriorations. Higher polarizability and 5-HT1A receptor occupancy were associated with smaller deteriorations, H1, M1, and M3 receptor occupancies with larger deteriorations.

Conclusions

Drug rankings may guide antipsychotic switching toward metabolically safer drugs. Mechanistic insights may suggest improvements for combination therapies and drug development. More data are required regarding newer antipsychotics.

Type
Original Article
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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Footnotes

*

These authors contributed equally to this work.

Co-Last Authors.

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