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Fornaro M, Caiazza C, Solini N, De Prisco M, Billeci M, Vannini M, Shorr R, Caiolo S, Lussignoli M, Siskind D, Pigato G, Barone A, Sambataro F, de Bartolomeis A, Correll CU, Solmi M. Pharmacological interventions for antipsychotic-related sialorrhea: a systematic review and network meta-analysis of randomized trials. Mol Psychiatry 2023; 28:3648-3660. [PMID: 37821573 DOI: 10.1038/s41380-023-02266-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 08/30/2023] [Accepted: 09/11/2023] [Indexed: 10/13/2023]
Abstract
Antipsychotic-induced sialorrhea carries a significant burden, but evidence-based treatment guidance is incomplete, warranting network meta-analysis (NMA) of pharmacological interventions for antipsychotic-related sialorrhea. PubMed Central/PsycInfo/Cochrane Central database/Clinicaltrials.gov/WHO-ICTRP and the Chinese Electronic Journal Database (Qikan.cqvip.com) were searched for published/unpublished RCTs of antipsychotic-induced sialorrhea (any definition) in adults, up to 06/12/2023. We assessed global/local inconsistencies, publication bias, risk of bias (RoB2), and confidence in the evidence, conducting subgroup/sensitivity analyses. Co-primary efficacy outcomes were changes in saliva production (standardized mean difference/SMD) and study-defined response (risk ratios/RRs). The acceptability outcome was all-cause discontinuation (RR). Primary nodes were molecules; the mechanism of action (MoA) was secondary. Thirty-four RCTs entered a systematic review, 33 NMA (n = 1958). All interventions were for clozapine-induced sialorrhea in subjects with mental disorders. Regarding individual agents and response, metoclopramide (RR = 3.11, 95% C.I. = 1.39-6.98), cyproheptadine, (RR = 2.76, 95% C.I. = 2.00-3.82), sulpiride (RR = 2.49, 95% C.I. = 1.65-3.77), propantheline (RR = 2.39, 95% C.I. = 1.97-2.90), diphenhydramine (RR = 2.32, 95% C.I. = 1.88-2.86), benzhexol (RR = 2.32, 95% C.I. = 1.59-3.38), doxepin (RR = 2.30, 95% C.I. = 1.85-2.88), amisulpride (RR = 2.23, 95% C.I. = 1.30-3.81), chlorpheniramine (RR = 2.20, 95% C.I. = 1.67-2.89), amitriptyline (RR = 2.09, 95% C.I. = 1.34-3.26), atropine, (RR = 2.03, 95% C.I. = 1.22-3.38), and astemizole, (RR = 1.70, 95% C.I. = 1.28-2.26) outperformed placebo, but not glycopyrrolate or ipratropium. Across secondary nodes (k = 28, n = 1821), antimuscarinics (RR = 2.26, 95% C.I. = 1.91-2.68), benzamides (RR = 2.23, 95% C.I. = 1.75-3.10), TCAs (RR = 2.23, 95% C.I. = 1.83-2.72), and antihistamines (RR = 2.18, 95% C.I. = 1.83-2.59) outperformed placebo. In head-to-head comparisons, astemizole and ipratropium were outperformed by several interventions. All secondary nodes, except benzamides, outperformed the placebo on the continuous efficacy outcome. For nocturnal sialorrhea, neither benzamides nor atropine outperformed the placebo. Active interventions did not differ significantly from placebo regarding constipation or sleepiness/drowsiness. Low-confidence findings prompt caution in the interpretation of the results. Considering primary nodes' co-primary efficacy outcomes and head-to-head comparisons, efficacy for sialorrhea is most consistent for the following agents, decreasing from metoclopramide through cyproheptadine, sulpiride, propantheline, diphenhydramine, benzhexol, doxepin, amisulpride, chlorpheniramine, to amitriptyline, and atropine (the latter not for nocturnal sialorrhea). Shared decision-making with the patient should guide treatment decisions regarding clozapine-related sialorrhea.
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Affiliation(s)
- Michele Fornaro
- Section of Psychiatry - Department of Neuroscience, Reproductive Sciences, and Dentistry, University School of Medicine Federico II, Naples, Italy.
| | - Claudio Caiazza
- Section of Psychiatry - Department of Neuroscience, Reproductive Sciences, and Dentistry, University School of Medicine Federico II, Naples, Italy
| | - Niccolò Solini
- Section of Psychiatry - Department of Neuroscience, Reproductive Sciences, and Dentistry, University School of Medicine Federico II, Naples, Italy
| | - Michele De Prisco
- Bipolar and Depressive Disorders Unit, IDIBAPS, CIBERSAM, Hospital Clinic, Barcelona, Catalonia, Spain
| | - Martina Billeci
- Section of Psychiatry - Department of Neuroscience, Reproductive Sciences, and Dentistry, University School of Medicine Federico II, Naples, Italy
| | - Martina Vannini
- Section of Psychiatry - Department of Neuroscience, Reproductive Sciences, and Dentistry, University School of Medicine Federico II, Naples, Italy
| | | | - Stefano Caiolo
- Department of Neuroscience, University of Padova, Padua, Italy
| | | | - Dan Siskind
- Metro South Addiction and Mental Health Service, Brisbane, QLD, Australia; School of Medicine, University of Queensland, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Giorgio Pigato
- Azienda Ospedale Università Padova, Padua University-Hospital, Padua, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience, Reproductive Sciences, and Dentistry, University School of Medicine Federico II, Naples, Italy
| | - Fabio Sambataro
- Department of Neuroscience, University of Padova, Padua, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience, Reproductive Sciences, and Dentistry, University School of Medicine Federico II, Naples, Italy
- Staff UNESCO Chair for Health Education and Sustainable Development at Federico II University of Naples, Naples, Italy
| | - Christoph U Correll
- Department of Psychiatry, Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Marco Solmi
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
- The Ottawa Hospital, Mental Health Department, Ottawa, ON, Canada
- Ottawa Hospital Research Institute (OHRI) Clinical Epidemiology Program University of Ottawa, Ottawa, ON, Canada
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
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Rosa LK, Costa FS, Hauagge CM, Mobile RZ, de Lima AAS, Amaral CDB, Machado RC, Nogueira ARA, Brancher JA, de Araujo MR. Oral health, organic and inorganic saliva composition of men with Schizophrenia: Case-control study. J Trace Elem Med Biol 2021; 66:126743. [PMID: 33740480 DOI: 10.1016/j.jtemb.2021.126743] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/03/2021] [Accepted: 03/09/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Schizophrenia (SCZ) presents complex challenges related to diagnosis and clinical monitoring. The study of conditions associated with SCZ can be facilitated by using potential markers and patterns that provide information to support the diagnosis and oral health. METHODS The salivary composition of patients diagnosed with SCZ (n = 50) was evaluated and compared to the control (n = 50). Saliva samples from male patients were collected and clinical parameters were evaluated. The concentration of total proteins and amylase were determined and salivary macro- and microelements were quantified by ICP OES and ICP-MS. Exploratory data analysis based on artificial intelligence tools was used in the investigation. RESULTS There was a significant increase in the salivary concentrations of Al, Fe, Li, Mg, Na, and V, higher prevalence of caries (p < 0.001), periodontal disease (p < 0.001), and reduced salivary flow rate (p = 0.019) in SCZ patients. Also, samples were grouped into six clusters. As, Co, Cr, Cu, Mn, Mo, Ni, Se, and Sr were correlated with each other, while Fe, K, Li, Ti, and V showed the highest concentrations in the samples distributed in the clusters with the highest association between SZC patients and controls. CONCLUSIONS The results obtained indicate changes in salivary flow, organic composition, and levels of macro- and microelements in SCZ patients. Salivary concentrations of Fe, Mg, and Na may be related to oral conditions, higher prevalence of caries, and periodontal disease. The exploratory analysis showed different patterns in the salivary composition of SCZ patients impacted by associations between oral health conditions and the use of medications. Future studies are encouraged to confirm the results investigated in this study.
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Affiliation(s)
- Letícia Kreutz Rosa
- Federal University of Paraná, Department of Stomatology, Curitiba, PR, 80210-170, Brazil
| | | | - Cecília Moraes Hauagge
- Federal University of Paraná, Department of Stomatology, Curitiba, PR, 80210-170, Brazil
| | - Rafael Zancan Mobile
- Federal University of Paraná, Department of Stomatology, Curitiba, PR, 80210-170, Brazil
| | | | - Clarice D B Amaral
- Federal University of Paraná, Department of Chemistry, Curitiba, PR, 81531-980, Brazil
| | - Raquel C Machado
- Federal University of São Carlos, Department of Chemistry, São Carlos, SP, 13565-905, Brazil
| | | | - João Armando Brancher
- Pontifícia Universidade Católica do Paraná, Escola de Ciências da Vida, Curitiba, PR, 80215-901, Brazil
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Li W, Deng G, Zhang J, Hu E, He Y, Lv J, Sun X, Wang K, Chen L. Identification of breast cancer risk modules via an integrated strategy. Aging (Albany NY) 2019; 11:12131-12146. [PMID: 31860871 PMCID: PMC6949069 DOI: 10.18632/aging.102546] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 11/19/2019] [Indexed: 12/17/2022]
Abstract
Breast cancer is one of the most common malignant cancers among females worldwide. This complex disease is not caused by a single gene, but resulted from multi-gene interactions, which could be represented by biological networks. Network modules are composed of genes with significant similarities in terms of expression, function and disease association. Therefore, the identification of disease risk modules could contribute to understanding the molecular mechanisms underlying breast cancer. In this paper, an integrated disease risk module identification strategy was proposed according to a multi-objective programming model for two similarity criteria as well as significance of permutation tests in Markov random field module score, function consistency score and Pearson correlation coefficient difference score. Three breast cancer risk modules were identified from a breast cancer-related interaction network. Genes in these risk modules were confirmed to play critical roles in breast cancer by literature review. These risk modules were enriched in breast cancer-related pathways or functions and could distinguish between breast tumor and normal samples with high accuracy for not only the microarray dataset used for breast cancer risk module identification, but also another two independent datasets. Our integrated strategy could be extended to other complex diseases to identify their risk modules and reveal their pathogenesis.
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Affiliation(s)
- Wan Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Gui Deng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Ji Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Erqiang Hu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yuehan He
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Junjie Lv
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xilin Sun
- Molecular Imaging Research Center (MIRC), Harbin Medical University, Harbin, China.,TOF-PET/CT/MR Center, the Fourth Hospital of Harbin Medical University, Harbin, China
| | - Kai Wang
- Molecular Imaging Research Center (MIRC), Harbin Medical University, Harbin, China.,TOF-PET/CT/MR Center, the Fourth Hospital of Harbin Medical University, Harbin, China
| | - Lina Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
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