Ifw-kiel.de

Psychiatry
Naturalistic Impact of Second-Generation Antipsychotics on
Weight Gain
Diana I Brixner, Qayyim Said, Patricia K Corey-Lisle, A Vickie Tuomari, Gilbert J L’Italien, William Stockdale, BACKGROUND: While second-generation antipsychotics (SGAs) have had benefits over earlier antipsychotic treatments, their use
has been associated with reports of weight gain. Body mass index (BMI) has been studied in clinical trials with limited comparison
between drugs.
OBJECTIVE: To investigate the impact of each SGA on the risk of weight increase in an adult population.
METHODS: Using a national electronic medical records database, a naturalistic impact of SGAs on BMI was evaluated. Patients
(aged ≥18 y) receiving a prescription for an antipsychotic drug between January 1995 and March 2004 were identified. An adverse
event was defined as at least a 7% increase in BMI from baseline within one year of antipsychotic prescription and a post-increase
BMI of at least 25 kg/m2.
RESULTS: A total of 9394 patients were identified, with 1514 cases of increased BMI after initial prescription. Risperidone (OR 1.39;
95% CI 1.16 to 1.66), quetiapine (OR 1.36; 95% CI 1.13 to 1.64), and olanzapine (OR 1.76; 95% CI 1.50 to 2.07) were significantly
more likely to cause BMI increase compared with first-generation antipsychotics (FGAs). Aripiprazole (OR 0.72; 95% CI 0.36 to
1.46), ziprasidone (OR 0.68; 95% CI 0.39 to 1.18), and clozapine (OR 1.01; 95% CI 0.56 to 1.81) were less likely to induce weight
gain compared with FGAs.
CONCLUSIONS: This study provides a foundation for understanding how SGAs impact weight gain in a naturalistic, as opposed to a
clinical trial, setting and provides evidence that there are differential risks of weight gain between SGAs. Because of negative long-
term health effects of weight gain, physicians need to take all factors into consideration when recommending pharmaceutical
therapy for patients with severe mental illness.
KEY WORDS: BMI, second-generation antipsychotic agents, weight gain.
Ann Pharmacother 2006;40:xxxx.
Published Online, 28 Mar 2006, www.theannals.com, DOI 10.1345/aph.1G564 Antipsychotic agents are commonly used in the treat- symptoms associated with psychosis, with a significantly ment of severe psychiatric disorders (eg, bipolar dis- lower risk of neurologic disorders.7 Despite the advantages
order, schizophrenia). First-generation antipsychotics (FGAs) of SGAs, their use has been associated with metabolic ad- have recognized efficacy in the suppression of positive verse effects such as weight gain, dyslipidemia, and hyper- symptoms (eg, delusions, hallucinations) of psychotic dis- glycemia.10,11 The relationship between antipsychotic med-
orders. However, many patients with chronic disorders ications and metabolic adverse effects has strong clinical have had less than optimal response or experienced relaps- relevance due to the high preexisting risk for metabolic es while receiving FGA treatment.1 Moreover, FGAs have
and cardiovascular disease among patients with schiz- been associated with neurologic disorders, such as acute ophrenia.12-16 Concern about metabolic disorders is also be-
extrapyramidal side effects and tardive dyskinesia.2-9
coming significant in other populations of antipsychotic The advent of second-generation antipsychotics (SGAs) users, such as those with bipolar disease. offered efficacy in the treatment of positive and negative More recent publications continue to fuel the controver- sy regarding efficacy versus tolerability between FGAs Author information provided at the end of the text.
and SGAs. The CATIE (Clinical Antipsychotic Trials of Copyright 2006 by Harvey Whitney Books Company. All rights reserved.
DI Brixner et al.
Intervention Effectiveness) investigators compared per- of body mass index (BMI) both within 90 days prior and 365 days after phenazine with 4 of the newer agents (ie, olanzapine, que- the initial prescription were included in the study. Patients were only in-cluded if they did not have a prescription order for an antipsychotic 6 tiapine, risperidone, ziprasidone).17 Rates of discontinua-
months prior to the index date, in an attempt to define new users. How- tion were similar between the older agent and 3 of the ever, because of the nature of EMR capture of prescription orders only, newer drugs. Efficacy and time to discontinuation were patients could have had an ongoing prescription that was ordered prior to greater in the olanzapine group; however, greater increases 6 months. It was assumed that this observation would be distributed in weight gain, glucose levels, and lipids were noted, which may be a concern in some patients. The most recentSGA, aripiprazole, was not included in the CATIE trial.
EXCLUSION CRITERIA
Furthermore, the study was conducted only in patients The following exclusion criteria were applied. Patients who had a with diagnosed schizophrenia, not in all patients exposed prescription for prochlorperazine but no diagnosis for any psychotic dis- order were excluded because this drug is primarily used for the treatment Therefore, further study across all available therapies in of nausea and vomiting.18 This indication could have a significant impact
a naturalistic setting is warranted to further demonstrate on the primary endpoint of BMI as well. Patients with no start date for a important differences in all patients being treated with drug or where medication information was blocked due to potentialHIPAA violations were also excluded. To focus on the impact of specific these drugs. The availability of the General Electric (GE) SGAs on BMI, patients who had prescriptions for both an FGA and Centricity electronic medical records (EMR) database, SGA within a given 365 day period and those who had prescriptions for which captures longitudinal clinical information directly more than one SGA within a given 365 day period were excluded from from clinical encounters, including demographics, diag- noses, medications, test results, and other data elements,affords an opportunity to analyze these metabolic out- ADVERSE EVENTS
comes in a naturalistic setting. The purpose of this project To determine the impact of antipsychotic agents on BMI, the occur- was to investigate the impact of SGA agents on the risk of rence of an adverse event was defined as a specified change in BMI from a baseline value within one year of prescription. The baseline valuewas identified as the most recent BMI within 90 days prior to the initial prescription. An average was determined in the cases where more thanone value was recorded within 90 days. Specifically, a BMI increase of DATA SOURCE
at least 7% from baseline within one year of initial prescription and a
BMI of at least 25 kg/m2, including the 7% increase, were categorized as
The GE Centricity EMR database contains ambulatory electronic an adverse event. The value of 7% was agreed upon by the investigators health record data for over 3.2 million patients. In general, the database contains longitudinal clinical patient data including, but not limited to,demographic information, vital signs, laboratory test orders and results, CRITERIA FOR STATISTICAL EVALUATION
medication list entries and prescriptions, and payment types. The datahave been collected from over 70 consortium member institutions. These Parameter estimates from logistic regression indicated the effect on consortium members are located in over 40 states and represent a variety BMI of an SGA agent, with reference to FGAs. In the case of logistic re- of practice types ranging from solo practitioners to community clinics, gression, an odds ratio greater than 1 indicated an increased probability academic medical centers, and large integrated delivery networks. Ap- of outcome and less than 1 indicated a decreased probability of outcome, proximately two-thirds of the participating clinicians practice primarycare, with the rest practicing various specialties. Data include patient vi-tal signs, clinical outcomes, payment plans, prescription and over-the-counter drugs, and laboratory test results. Because information is enteredinto the database daily, current data are available for research. All data Table 1. Drugs Included in the Analysis
were de-identified in accordance with current Health Insurance Portabili- First-Generation
Second-Generation
ty and Accountability Act (HIPAA) standards, and the study was ap- Antipsychotics
Antipsychotics
proved by the University of Utah institutional review board. prochlorperazine (Compazine)a
The database tracks initial prescription orders and new orders due to a prescription change. Initial prescription refers to the first recorded pre- scription in the GE Centricity EMR database. Switching between drugs can be easily determined in this database. Discontinuation can either be assumed by a lack of a new prescription one year after the initial pre- scription or detected by noting a removal of the drug from the medica- trifluoperazine (Stelazine)mesoridazine (Serentil, APO- INCLUSION CRITERIA
All adult (≥18 y) patients who had a one year prescription order for aOnly patients with a diagnosis for psychotic disorder were included.
an antipsychotic agent (FGA or SGA; Table 1) and at least one recording Impact of Second-Generation Antipsychotics on Weight Gain
as a result of that particular SGA agent, with reference to FGAs. To ex- fy patients taking drugs associated with weight gain or tak- amine the impact of antipsychotic therapy on BMI, both unadjusted and ing weight loss drugs. Patients may have been either man- adjusted odds ratios were derived using logistic regression. Results were aged by additional drug therapy for treatment or had these adjusted for age, gender, baseline BMI, diagnosis, and concomitant med- outcomes aggravated by concomitant medications. Results ications likely to have an impact on the weight. Age in years was includ-ed as a continuous variable.
showed that, of the patients analyzed for the impact of an- For the adjustment of diagnosis, patients were stratified by disease, tipsychotic therapy on BMI, 45.4% were taking medica- which was identified as bipolar, depression, schizophrenia or schizoaf- tions that have an associated risk of weight gain, while less fective disorder, or no related mental health diagnosis. Patients with a than 1% of patients were taking either weight loss drugs or mental health diagnosis, but not falling into any of these categories, were also included in the analysis. In addition, patients with more than onedisease category were included. Specifically, for the purposes of analy- The outcome variable was specified as the adverse sis, patients were divided into 6 groups according to the following ICD - event in the form of an increase in BMI after the initial 9 codes: (1) bipolar: 296, 296.0, 296.1, 296.4, 296.5, 296.6, 296.8; (2) prescription. Sixteen percent of the patients experienced depression: 311, 300.4, 296.2, 296.3; (3) schizophrenia/schizoaffective: the specified increase in BMI and were categorized as hav- 295; (4) other: 300; (5) multiple (ie, patients in >1 group of the previous ing an adverse event. Unadjusted and adjusted odds ratios 4); and (6) none of the previous 4 disease groups (reference group).
Concomitant medications were evaluated by assessment of additional are depicted in Table 3. The results show that risperidone, drugs the patients were taking within the study time frame, other than the quetiapine, and olanzapine were significantly more likely antipsychotics under study. Association of these additional
drugs with weight gain was determined via a literature
search.19 Further, pharmacists at the University of Utah
were consulted to include information on drugs that have
become available since published literature. To formally in-
Table 2. Descriptive Statistics of the Overall Samplea
corporate the impact of concomitant drugs on BMI, medi- Pts. with BMI
cations were divided into 4 groups: (1) those that increase Variable
Pts., n (%)
the risk of weight gain, (2) those used for the treatment of Antipsychotic agent
weight gain (weight loss drugs), (3) both of the above, and (4) neither of the above (reference group). A list of these medications is available on request from the authors. A total of 50 238 patients met the initial in- first-generationb
clusion criteria of having a prescription for any Psychiatric diagnosis
of the antipsychotic medications. Of these, 22 375 met one or more of the exclusion crite- ria, leaving 27 863 patients who could be fur- ther analyzed. A total of 9394 patients were identified for final analysis after applying the no psychiatric diagnosisb
criterion of having at least one BMI recording Drugs influencing weight
both before and after the initial prescription.
Of these, 1514 cases of increased BMI after initial antipsychotic prescription were found.
neitherb
Descriptive statistics are presented in Table 2. stratified by psychotic-related diagnosis. Re- sults showed that roughly 40% of the patients did not have a psychotic-related ICD -9 code, which in a primary care setting could indicate a psychiatric referral. Further, about one-quar- Baseline BMI (kg/m2)
ter of the patients had a diagnosis for depres- sion, and approximately 10% had a diagnosis for bipolar disorder. Approximately 6% of pa- tients had a diagnosis for schizophrenia/schizo- AE = adverse event; BMI = body mass index.
aData are from the General Electric Centricity electronic medical records database
An examination of the patients’ concomi- covering the period from January 1995 to March 2004.
bReference categories.
tant medications was also conducted to identi- DI Brixner et al.
to cause BMI increase compared with FGAs. Aripiprazole, gistic regression analysis. These factors included concomi- ziprasidone, and clozapine were less likely to induce weight tant medications, diagnoses, age, gender, and baseline gain compared with FGAs.20,21
Few studies27 have explored the impact of all the SGAs,
Discussion
in particular the newer antipsychotics such as aripiprazoleand ziprasidone, on weight gain in a naturalistic setting.
It has been suggested that weight gain is a significant These results demonstrate that aripiprazole, ziprasidone, risk factor for metabolic syndrome.22 A major concern
and clozapine are less likely to induce weight gain com- with metabolic syndrome is its causal link with future inci- pared with FGAs. On the other hand, quetiapine, olanza- dence of diabetes and cardiovascular disease. Research has pine, and risperidone significantly increase the risk of shown that metabolic syndrome constitutes elevated risk weight gain. For the most part, these results corroborate for cardiovascular disease and diabetes.23-26 Because of the
findings from randomized clinical trials, with the excep- high prevalence and associated morbidity and mortality, it tion of the lack of evidence for clozapine causing weight is imperative to identify effective pharmacologic manage- gain, which has been shown in previous studies to increase ment strategies to address the problem of weight gain and, weight.4 Clozapine is often reserved for second-line thera-
by implication, related metabolic syndrome and chronic py; therefore, it is likely that weight gain could have been attributed to the initial therapy and thus was not recognized In light of the concerns regarding the metabolic adverse in our study. Alternatively, because prior prescription use effects of SGAs, this study investigated weight gain in is difficult to confirm, a greater proportion of patients may comparison with FGAs in a naturalistic setting. To achieve have been taking clozapine for longer periods of time due this purpose, a rigorous methodology was adopted in to its extended time on the market compared with newly which patients receiving polypharmacy within any given introduced agents. Finally, this confounding finding is an year were excluded. Also, to isolate the real impact of an- example of research conducted on large retrospective tipsychotic therapy, several factors known to influence the databases in which perhaps all conditions cannot be as outcomes under investigation were adjusted for, using lo- well controlled as in a clinical trial. Despite these limita- Table 3. Odds Ratios of Patients Taking SGAs vs FGAsa
Unadjusted OR
Adjusted OR
Variable
Psychiatric diagnosisc
Drugs influencing weightd
Baseline BMIe
BMI = body mass index; FGA = first-generation antipsychotic; SGA = second-generation antipsychotic.
aBased on the General Electric Centricity electronic medical records database covering the period from January 1995 to March 2004.
bThe reference category is patients taking FGAs.
cThe reference category is patients with no psychiatric diagnosis.
dThe reference category is patients taking no medications influencing weight.
eIncluded as continuous variables.
fThe reference category is male patients.
Impact of Second-Generation Antipsychotics on Weight Gain
tions, it is impressive to note the correlation of findings in Limitations
other drug categories to that supported by clinical trials. Asclinical trials follow very restrictive protocols, the support There are several limitations in using an EMR database of those findings in a naturalistic setting can be of particu- for outcomes research. For example, prescriptions are tracked by prescription orders and medication lists and not Two additional issues concerning the naturalistic use of by actual prescriptions filled at the pharmacy. In addition, SGAs were studied, including concomitant drug therapy patients enter the database via a primary care physician and the associated diagnosis of patients taking these network and, therefore, health care received outside of the agents. First, patients were stratified by the use of con- primary care setting may not be captured in the database.
comitant medications that influence weight. Excess weight To maintain sample sizes for adequate statistical power, is one of the major determinants of the metabolic syn- drug categories were not broken down by dose; BMI vari- drome, which is causally linked with future incidence of ance may be dose related in some products. As some dos- chronic conditions including diabetes and cardiovascular ing issues may relate to age (eg, low-dose SGAs used to disease. Interestingly, many patients were taking additional induce sleep in the elderly), this was partially accounted medications that influence the possible weight gain ad- for through control of age as a variable. Patients were verse effect of antipsychotic medications, both drugs that viewed in a specific time frame, and prior history was not further aggravate it and pharmacologic agents used for its necessarily considered. However, the ability to track pa- treatment. More patients were receiving therapy that in- tient care and outcomes in a naturalistic setting can provide creased the risk of weight gain. Heightened awareness of valuable information to healthcare providers. the impact of concomitant medications on weight gain Further, we did not include time to adverse event (BMI increase) in our analysis because we only knew when BMI The results of this study provide evidence to primary was measured on a visit to a physician, but not when care physicians that, along with the consideration of weight was actually gained. We would also like to urge weight gain as an adverse effect in patients taking SGAs, caution about interpreting the results for aripiprazole, concomitant therapies, which also may cause weight gain, ziprasidone, and clozapine. The insignificance of these re- should be considered when optimizing treatment strate- sults may have been due to relatively smaller sample sizes.
gies. Because of the high prevalence of weight gain and However, we believe that these data still add value, given the associated morbidity and mortality, it is imperative to the paucity of data on the first 2 drugs. identify optimal intervention strategies including diet, ex-ercise, and pharmacotherapy. Proper management of obe- Conclusions
sity may then inhibit an increased incidence of chronic SGAs provide a significant improvement in treatment conditions including diabetes and cardiovascular disease.
for psychotic disorders. For associated impact on weight, This study demonstrates the need for increased awareness risperidone, quetiapine, and olanzapine demonstrated a by healthcare providers of all concomitant medications risk of increased BMI, whereas aripiprazole, ziprasidone, taken by patients receiving SGAs to minimize exposure to and clozapine had a lower risk. Database studies in a natu- ralistic setting can be very useful in validating outcomes Finally, the patients were stratified by diagnosis to deter- from controlled clinical trials. Patients taking SGAs were mine the primary reason for the prescription of SGAs. Due often receiving concomitant drugs that treat or aggravate to the perceived stigma of certain diseases or potential re- this adverse outcome. These variances can be important imbursement issues, actual diagnosis coding in a primary when selecting appropriate therapy for patients with psy- care setting may vary.28-32 The indicated diseases, schizo-
chotic disorders. Further research should investigate addi- phrenia and schizoaffective disorder, were the least record- tional components of metabolic syndrome, including hy- ed ICD -9 code; instead, depression was noted most often.
perlipidemia and hyperglycemia, to assist in the manage- Moreover, a large number of patients did not have any mental health–related diagnosis. This could be due to aninitial diagnosis by a primary care physician followed by a Diana I Brixner PhD, Associate Professor and Chair, Depart-
referral to a psychiatrist or perhaps to a perceived stigma ment of Pharmacotherapy; Executive Director, Pharmacothera- of a schizophrenia diagnosis. Patients taking SGAs are of- py Outcomes Research Center, University of Utah, Salt Lake City,UT ten undiagnosed or may be misdiagnosed in primary care, Qayyim Said PhD, Research Assistant Professor, Pharmacother-
which may have an impact on the continuity of care in op- apy Outcomes Research Center, University of Utah timizing patients’ outcomes. Whatever the reason, physi- Patricia K Corey-Lisle PhD, Director, Bristol-Myers Squibb Co.,
Wallingford, CT
cians tend to prescribe SGAs outside of the approved indi- A Vickie Tuomari MS, Senior Manager, Bristol-Myers Squibb Co.,
DI Brixner et al.
Gilbert J L’Italien PhD, Group Director, Bristol-Myers Squibb Co.,
22. Deen D. Metabolic syndrome: time for action. Am Fam Physician 2004; William Stockdale MBA, Research Assistant Professor, Pharma-
23. Lakka HM, Laaksonen DE, Lakka TA, et al. The metabolic syndrome cotherapy Outcomes Research Center, University of Utah and total and cardiovascular disease mortality in middle-aged men.
Gary M Oderda PharmD MPH, Professor, Department of Phar-
macotherapy; Director, Pharmacotherapy Outcomes Research Cen- 24. Onat A, Ceyhan K, Basar O, Erer B, Toprak S, Sansoy V. Metabolic syn- drome: major impact on coronary risk in a population with low choles- Reprints: Dr. Brixner, Pharmacotherapy Outcomes Research Cen-
terol levels—a prospective and cross-sectional evaluation. Atherosclero- ter, University of Utah, 421 Wakara Way, Rm. 208, Salt Lake City, UT 84108-3546, fax 801/587-7923, [email protected] 25. Laaksonen DE, Lakka HM, Niskanen LK, Kaplan GA, Salonen JT, Lak- This study was funded by a research grant from the Bristol-Myers ka TA. Metabolic syndrome and development of diabetes mellitus: appli- cation and validation of recently suggested definitions of the metabolicsyndrome in a prospective cohort study. Am J Epidemiol 2002;156: This research was presented in part at the American Diabetes As- sociation Annual Meeting, San Diego, CA, June 10–15, 2005.
26. Janssen I, Katzmarzyk PT, Srinivasan SR, et al. Combined influence of body mass index and waist circumference on coronary artery disease risk References
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27. Barbui C, Lintas C, Percudani M. Head-to-head comparison of the costs 1. Moller HJ. Antipsychotic agents. Gradually improving treatment from of atypical antipsychotics: a systemic review. CNS Drugs 2005;19:935- the traditional oral neuroleptics to the first atypical depot. Eur Psychiatry 28. Torgersen T, Rosseland LA, Malt UF. Coding guidelines for ICD -9 sec- 2. Remington G, Chong SA. Conventional versus novel antipsychotics: tion on mental disorders and reliability of chart clinical diagnoses. Acta changing concepts and clinical implications. J Psychiatry Neurosci 29. Angermeyer MC, Matschinger H. Public attitudes to people with depres- 3. Shen WW. A history of antipsychotic drug development. Compr Psychi- sion: have there been any changes over the last decade? J Affect Disord 4. Casey DE. Side effect profiles of new antipsychotic agents. J Clin Psy- 30. Pyne JM, Kuc EJ, Schroeder PJ, Fortney JC, Edlund M, Sullivan G. Re- chiatry 1996;57(suppl 11):40-5; discussion 46-52. lationship between perceived stigma and depression severity. J Nerv 5. Kane JM. Pharmacologic treatment of schizophrenia. Biol Psychiatry 31. Ertugrul A, Ulug B. Perception of stigma among patients with schizo- 6. Krausz M. Efficacy review of antipsychotics. Curr Med Res Opin phrenia. Soc Psychiatry Psychiatr Epidemiol 2004;39:73-7.
32. Rost K, Smith R, Matthews DB, Guise B. The deliberate misdiagnosis of 7. Lieberman JA. Atypical antipsychotic drugs as a first-line treatment of major depression in primary care. Arch Fam Med 1994;3:333-7.
schizophrenia: a rationale and hypothesis. J Clin Psychiatry 1996;57(suppl 11):68-71. 8. Worrel JA, Marken PA, Beckman SE, Ruehter VL. Atypical antipsychot- ic agents: a critical review. Am J Health Syst Pharm 2000;57:238-55. 9. Lieberman JA, Tollefson G, Tohen M, et al. Comparative efficacy and safety of atypical and conventional antipsychotic drugs in first-episode INTRODUCCION: Si bien los antipsicóticos de segunda generación (ASGs)
psychosis: a randomized, double-blind trial of olanzapine versus halo- han supuesto beneficios respecto a los antipsicóticos clásicos, su peridol. Am J Psychiatry 2003;160:1396- 404.
utilización se ha asociado a un incremento de peso. El índice de masa 10. American Diabetes Association. Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care 2004;27: corporal (IMC) ha sido estudiado en ensayos clínicos con escasos datos 11. Allison DB, Mentore JL, Heo M, et al. Antipsychotic-induced weight OBJETIVO: Investigar el impacto de cada uno de los ASGs sobre el riesgo
gain: a comprehensive research synthesis. Am J Psychiatry 1999;156: de incremento de peso en la población adulta. MÉTODO: Se evaluó de forma naturalística el impacto de los ASGs sobre
12. Koro CE, Fedder DO, L’Italien GJ, et al. An assessment of the indepen- el IMC utilizando una base de datos médica electrónica nacional. Se dent effects of olanzapine and risperidone exposure on the risk of hyper-lipidemia in schizophrenic patients. Arch Gen Psychiatry 2002;59:1021-6.
identificaron los pacientes (>18 años) que recibían una prescripción deun antipsicótico durante el periodo enero 1995 y marzo 2004. Se 13. Koro CE, Fedder DO, L’Italien GJ, et al. Assessment of independent ef- fect of olanzapine and risperidone on risk of diabetes among patients identificó como un efecto adverso un incremento de al menos un 7% en with schizophrenia: population based nested case–control study. BMJ el IMC durante el primer año de tratamiento con el antipsicótico y un incremento del IMC de al menos 25 kg/m2.
14. Casey DE. Metabolic issues and cardiovascular disease in patients with RESULTADOS: Un total de 9394 pacientes fueron identificados, de los que
psychiatric disorders. Am J Med 2005;118(suppl 2):15S-22S.
1514 casos incrementaron el IMC después de la prescripción inicial.
15. Newcomer JW. Metabolic risk during antipsychotic treatment. Clin Ther Risperidona (OR 1.39; 95% CI 1.16 a 1.66), quetiapina (OR 1.36; CI 1.13 a 1.64), y olanzapina (OR 1.76; CI 1.50 a 2.07) causaron un 16. Newcomer JW. Abnormalities of glucose metabolism associated with incremento significativo del IMC, en comparación con los antipsicóticos atypical antipsychotic drugs. J Clin Psychiatry 2004;65(suppl 18):36- 46.
de primera generación. Aripiprazol (OR 0.72; CI 0.36 a 1.46), 17. Lieberman JA, Stroup TS, McEvoy JP, et al. Effectiveness of antipsy- ziprasidona (OR 0.68; CI 0.39 a 1.18), y clozapina (OR 1.01; CI 0.56 chotic drugs in patients with chronic schizophrenia. N Engl J Med a1.81) presentaban menor riesgo de inducir un aumento de peso, en 2005;353:1209-23. Epub 19 Sept 2005.
comparación con los antipsicóticos de primera generación.
18. Golembiewski J, Chernin E, Chopra T. Prevention and treatment of post- operative nausea and vomiting. Am J Health Syst Pharm 2005;62:1247- CONCLUSIONES: Este estudio proporciona un fundamento para entender el
impacto de los ASGs sobre el incremento de peso a través de un estudio 19. Pijl H, Meinders AE. Bodyweight change as an adverse effect of drug naturalístico como contrapartida a un ensayo clínico y proporciona treatment. Mechanisms and management. Drug Saf 1996;14:329- 42.
evidencia sobre las diferencias en el riesgo de incrementar el peso entre 20. McQuade RD, Stock E, Marcus R, et al. A comparison of weight change los ASGs. Considerando los efectos negativos a largo plazo del during treatment with olanzapine or aripiprazole: results from a random- incremento de peso sobre la salud, es necesario que los médicos tengan ized, double-blind study. J Clin Psychiatry 2004;65(suppl 18):47-56.
en cuenta todos los factores cuando recomiendan un tratamiento 21. Ananth J, Venkatesh R, Burgoyne K, Gadasalli R, Binford R, Gunatilake farmacológico en los pacientes con enfermedad mental severa.
S. Atypical antipsychotic induced weight gain: pathophysiology andmanagement. Ann Clin Psychiatry 2004;16:75-85.
Impact of Second-Generation Antipsychotics on Weight Gain
antipsychotique. La probabilité que la rispéridone (rapport de cote ou HISTORIQUE: Bien que les antipsychotiques de deuxième génération
Odds Ratio [OR] 1.39; IC 95% 1.16 à 1.66), la quétiapine (OR 1.36; IC présentent des avantages sur les antipsychotiques plus anciens, leur 95% 1.13 à 1.64), et l’olanzapine (OR 1.76; IC 95% 1.50 à 2.07) sont utilisation est cependant associée à un gain de poids significatif. L’indice associés à une augmentation significative de l’IMC, est plus élevée que de masse corporelle (IMC) a été étudiée dans le cadre d’essais cliniques pour les antipsychotiques de première génération. La probabilité que mais peu de données comparatives issues d’une même étude sur les l’aripiprazole (OR 0.72; IC 95% 0.36 à 1.46), la ziprasidone (OR 0.68; divers médicaments et leur effet sur l’MC sont disponibles. IC 95% 0.39 à 1.18), et la clozapine (OR 1.01; IC 95% 0.56 à 1.81)produisent un gain de poids est moins élevée que celle des OBJECTIF: Évaluer l’impact de chaque nouvel antipsychotique sur le
antipsychotiques de deuxième génération. risque de gain de poids dans la population adulte. CONCLUSIONS: Cette étude montre l’impact des antipsychotiques de
MÉTHODOLOGIE: À l’aide des données issues d’une banque nationale
deuxième génération sur le gain de poids en situation réelle plutôt que informatisée de dossiers médicaux, l’histoire naturelle de l’impact de dans des conditions contrôlées d’un essai clinique et laisse entrevoir un l’utilisation des antipsychotiques de deuxième génération sur l’IMC a risque différent selon le médicament utilisé. En raison d’un effet négatif été évaluée. Toutes les personnes de 18 ans ou plus ayant reçu une du gain pondéral sur la santé à long terme, les médecins doivent prendre prescription pour un antipsychotique entre janvier 1995 et mars 2004 ont cet effet indésirable en considération lorsqu’il s’agit de sélectionner un été sélectionnées. Un effet indésirable en terme de gain de poids était traitement pharmacologique chez les personnes présentant une maladie défini par l’augmentation d’au moins 7% de l’IMC à partir de la valeur de base à l’intérieur d’une période d’un an depuis le début du traitement
et une augmentation au-delà de cette période d’au moins 25 kg/m2.
RÉSULTATS: Un total de 9394 patients ont été identifiés, dont 1514 ont
présenté une augmentation de l’IMC suite à la prescription initiale d’un

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