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Antipsychotics, glycemic disorders, and life-threatening diabetic events: a Bayesian data-mining analysis of the FDA adverse event reporting system (1968-2004).
Ann Clin Psychiatry. 2008 Jan-Mar; 20(1):21-31.AC

Abstract

BACKGROUND

This analysis compared diabetes-related adverse events associated with use of different antipsychotic agents. A disproportionality analysis of the US Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) was performed.

METHODS

Data from the FDA postmarketing AERS database (1968 through first quarter 2004) were evaluated. Drugs studied included aripiprazole, clozapine, haloperidol, olanzapine, quetiapine, risperidone, and ziprasidone. Fourteen Medical Dictionary for Regulatory Activities (MedDRA) Primary Terms (MPTs) were chosen to identify diabetes-related adverse events; 3 groupings into higher-level descriptive categories were also studied. Three methods of measuring drug-event associations were used: proportional reporting ratio, the empirical Bayes data-mining algorithm known as the Multi-Item Gamma Poisson Shrinker, and logistic regression (LR) analysis. Quantitative measures of association strength, with corresponding confidence intervals, between drugs and specified adverse events were computed and graphed. Some of the LR analyses were repeated separately for reports from patients under and over 45 years of age. Differences in association strength were declared statistically significant if the corresponding 90% confidence intervals did not overlap.

RESULTS

Association with various glycemic events differed for different drugs. On average, the rankings of association strength agreed with the following ordering: low association, ziprasidone, aripiprazole, haloperidol, and risperidone; medium association, quetiapine; and strong association, clozapine and olanzapine. The median rank correlation between the above ordering and the 17 sets of LR coefficients (1 set for each glycemic event) was 93%. Many of the disproportionality measures were significantly different across drugs, and ratios of disproportionality factors of 5 or more were frequently observed.

CONCLUSIONS

There are consistent and substantial differences between atypical antipsychotic drugs in the disproportionality reporting ratios relating to glycemic effects, especially life-threatening events, in the AERS database. The relative associational rankings of drugs are similar in reports from younger and older patients. These results agree with several other reports in the literature, do not support a "class effect" hypothesis, and provide a strong rationale for further studies to clarify the issue.

Authors+Show Affiliations

Lincoln Technologies Inc., Waltham, Massachusetts, USA.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

18297583

Citation

DuMouchel, William, et al. "Antipsychotics, Glycemic Disorders, and Life-threatening Diabetic Events: a Bayesian Data-mining Analysis of the FDA Adverse Event Reporting System (1968-2004)." Annals of Clinical Psychiatry : Official Journal of the American Academy of Clinical Psychiatrists, vol. 20, no. 1, 2008, pp. 21-31.
DuMouchel W, Fram D, Yang X, et al. Antipsychotics, glycemic disorders, and life-threatening diabetic events: a Bayesian data-mining analysis of the FDA adverse event reporting system (1968-2004). Ann Clin Psychiatry. 2008;20(1):21-31.
DuMouchel, W., Fram, D., Yang, X., Mahmoud, R. A., Grogg, A. L., Engelhart, L., & Ramaswamy, K. (2008). Antipsychotics, glycemic disorders, and life-threatening diabetic events: a Bayesian data-mining analysis of the FDA adverse event reporting system (1968-2004). Annals of Clinical Psychiatry : Official Journal of the American Academy of Clinical Psychiatrists, 20(1), 21-31. https://doi.org/10.1080/10401230701844612
DuMouchel W, et al. Antipsychotics, Glycemic Disorders, and Life-threatening Diabetic Events: a Bayesian Data-mining Analysis of the FDA Adverse Event Reporting System (1968-2004). Ann Clin Psychiatry. 2008 Jan-Mar;20(1):21-31. PubMed PMID: 18297583.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Antipsychotics, glycemic disorders, and life-threatening diabetic events: a Bayesian data-mining analysis of the FDA adverse event reporting system (1968-2004). AU - DuMouchel,William, AU - Fram,David, AU - Yang,Xionghu, AU - Mahmoud,Ramy A, AU - Grogg,Amy L, AU - Engelhart,Luella, AU - Ramaswamy,Krishnan, PY - 2008/2/26/pubmed PY - 2008/4/9/medline PY - 2008/2/26/entrez SP - 21 EP - 31 JF - Annals of clinical psychiatry : official journal of the American Academy of Clinical Psychiatrists JO - Ann Clin Psychiatry VL - 20 IS - 1 N2 - BACKGROUND: This analysis compared diabetes-related adverse events associated with use of different antipsychotic agents. A disproportionality analysis of the US Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) was performed. METHODS: Data from the FDA postmarketing AERS database (1968 through first quarter 2004) were evaluated. Drugs studied included aripiprazole, clozapine, haloperidol, olanzapine, quetiapine, risperidone, and ziprasidone. Fourteen Medical Dictionary for Regulatory Activities (MedDRA) Primary Terms (MPTs) were chosen to identify diabetes-related adverse events; 3 groupings into higher-level descriptive categories were also studied. Three methods of measuring drug-event associations were used: proportional reporting ratio, the empirical Bayes data-mining algorithm known as the Multi-Item Gamma Poisson Shrinker, and logistic regression (LR) analysis. Quantitative measures of association strength, with corresponding confidence intervals, between drugs and specified adverse events were computed and graphed. Some of the LR analyses were repeated separately for reports from patients under and over 45 years of age. Differences in association strength were declared statistically significant if the corresponding 90% confidence intervals did not overlap. RESULTS: Association with various glycemic events differed for different drugs. On average, the rankings of association strength agreed with the following ordering: low association, ziprasidone, aripiprazole, haloperidol, and risperidone; medium association, quetiapine; and strong association, clozapine and olanzapine. The median rank correlation between the above ordering and the 17 sets of LR coefficients (1 set for each glycemic event) was 93%. Many of the disproportionality measures were significantly different across drugs, and ratios of disproportionality factors of 5 or more were frequently observed. CONCLUSIONS: There are consistent and substantial differences between atypical antipsychotic drugs in the disproportionality reporting ratios relating to glycemic effects, especially life-threatening events, in the AERS database. The relative associational rankings of drugs are similar in reports from younger and older patients. These results agree with several other reports in the literature, do not support a "class effect" hypothesis, and provide a strong rationale for further studies to clarify the issue. SN - 1547-3325 UR - https://www.unboundmedicine.com/medline/citation/18297583/Antipsychotics_glycemic_disorders_and_life_threatening_diabetic_events:_a_Bayesian_data_mining_analysis_of_the_FDA_adverse_event_reporting_system__1968_2004__ L2 - https://medlineplus.gov/hyperglycemia.html DB - PRIME DP - Unbound Medicine ER -