BACKGROUND: Routine metabolic screening and consideration of patient metabolic status in the choice of a second-generation antipsychotic (SGA) medication are recommended. This study evaluated the association between abnormal blood glucose and lipid values and SGA prescribing patterns. MATERIALS AND METHODS: A retrospective cohort study using administrative data from 2 managed care plans in the United States evaluated 7904 adults initiating SGA therapy between 2001 and 2004. Baseline serum glucose, total cholesterol, and triglyceride values were available for 989 patients (12.5%), and follow-up assessments were done in 699 patients (8.8%). Abnormal values were defined as the following: total cholesterol, 200 mg/dL or higher; triglycerides, 200 mg/dL or higher; and glucose, 126 mg/dL or higher. The likelihood of abnormal laboratory values being associated with selection of a lower metabolic risk SGA drug (aripiprazole or ziprasidone) and with switching decisions was assessed using multivariate logistic regression models. RESULTS: Thirteen percent of the patients had glucose and lipid tests within 6 months of starting SGA therapy. The likelihood of starting a patient on an SGA drug with lower metabolic risk (ziprasidone: odds ratio, 3.26; 95% confidence interval, 1.25-8.47; aripiprazole: odds ratio, 2.13; 95% confidence interval, 0.77-5.88) was higher if the patient had elevated glucose values but was not associated with elevated cholesterol or triglyceride values or if the patient had preexisting diabetes or dyslipidemia. Abnormal glucose and lipid values were not associated with switching SGA medications in the first 6 months of therapy. Among patients who did switch SGA medications, elevated glucose and lipid values were not associated with a greater likelihood of switching to aripiprazole or ziprasidone. CONCLUSIONS: Low rates of recommended monitoring were observed. Abnormal metabolic parameters among those who were tested were not consistently associated with the selection of an SGA drug with lower metabolic risk.
BACKGROUND: Routine metabolic screening and consideration of patient metabolic status in the choice of a second-generation antipsychotic (SGA) medication are recommended. This study evaluated the association between abnormal blood glucose and lipid values and SGA prescribing patterns. MATERIALS AND METHODS: A retrospective cohort study using administrative data from 2 managed care plans in the United States evaluated 7904 adults initiating SGA therapy between 2001 and 2004. Baseline serum glucose, total cholesterol, and triglyceride values were available for 989 patients (12.5%), and follow-up assessments were done in 699 patients (8.8%). Abnormal values were defined as the following: total cholesterol, 200 mg/dL or higher; triglycerides, 200 mg/dL or higher; and glucose, 126 mg/dL or higher. The likelihood of abnormal laboratory values being associated with selection of a lower metabolic risk SGA drug (aripiprazole or ziprasidone) and with switching decisions was assessed using multivariate logistic regression models. RESULTS: Thirteen percent of the patients had glucose and lipid tests within 6 months of starting SGA therapy. The likelihood of starting a patient on an SGA drug with lower metabolic risk (ziprasidone: odds ratio, 3.26; 95% confidence interval, 1.25-8.47; aripiprazole: odds ratio, 2.13; 95% confidence interval, 0.77-5.88) was higher if the patient had elevated glucose values but was not associated with elevated cholesterol or triglyceride values or if the patient had preexisting diabetes or dyslipidemia. Abnormal glucose and lipid values were not associated with switching SGA medications in the first 6 months of therapy. Among patients who did switch SGA medications, elevated glucose and lipid values were not associated with a greater likelihood of switching to aripiprazole or ziprasidone. CONCLUSIONS: Low rates of recommended monitoring were observed. Abnormal metabolic parameters among those who were tested were not consistently associated with the selection of an SGA drug with lower metabolic risk.
Authors: Christina Mangurian; Chelsea Modlin; Lindsey Williams; Susan Essock; Nicholas S Riano; Martha Shumway; John W Newcomer; James W Dilley; Dean Schillinger Journal: Community Ment Health J Date: 2017-11-28
Authors: Maithri Prabhakar; William G Haynes; William H Coryell; Elizabeth A Chrischilles; Del D Miller; Stephan Arndt; Vicki L Ellingrod; Lois Warren; Jess G Fiedorowicz Journal: Pharmacotherapy Date: 2011-08 Impact factor: 4.705
Authors: Robert O Cotes; Alex de Nesnera; Michael Kelly; Karen Orsini; Haiyi Xie; Greg McHugo; Stephen Bartels; Mary F Brunette Journal: Community Ment Health J Date: 2015-02-03
Authors: Marc DE Hert; Christoph U Correll; Julio Bobes; Marcelo Cetkovich-Bakmas; Dan Cohen; Itsuo Asai; Johan Detraux; Shiv Gautam; Hans-Jurgen Möller; David M Ndetei; John W Newcomer; Richard Uwakwe; Stefan Leucht Journal: World Psychiatry Date: 2011-02 Impact factor: 49.548