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Antipsychotics in Adults With Schizophrenia: Comparative Effectiveness of First-Generation Versus Second-Generation Medications: A Systematic Review and Meta-analysis FREE

Lisa Hartling, PhD; Ahmed M. Abou-Setta, MD, PhD; Serdar Dursun, MD, PhD; Shima S. Mousavi, MD; Dion Pasichnyk, BSc; and Amanda S. Newton, RN, PhD
[+] Article and Author Information

From University of Alberta, Edmonton, Alberta, Canada, and University of Manitoba/Winnipeg Regional Health Authority, Winnipeg, Manitoba, Canada.

Acknowledgment: The authors thank Mrs. Carol Spooner and Ms. Janine Schouten for help in article selection and data extraction; Dr. Susan Armijo-Olivo for help in data extraction; Ms. Amy Beaith and Ms. Andrea Milne for help in literature searching; Ms. Annabritt Chisholm and Ms. Teodora Radisic for help in article retrieval; Mr. Ben Vandermeer for help in data analysis; Ms. Jennifer Seida for help in critical review and copyediting; Ms. Christine Ha, Ms. Elizabeth Sumamo Schellenberg, and Mr. Kai Wong for help in screening the gray literature; and the members of the technical expert panel (listed in full technical report).

Grant Support: By the Agency for Healthcare Research and Quality (AHRQ) (contract 290-2007-10021), U.S. Department of Health and Human Services.

Potential Conflicts of Interest: Dr. Hartling: Contract (money to institution): AHRQ. Dr. Abou-Setta: Grant (money to institution): AHRQ. Dr. Dursun: Grants/grants pending (money to institution): CIHR-Canada, Norlien Foundation; Patents (planned, pending, or issued): sodium nitroprusside for the treatment of schizophrenia, in partnership with the University of Alberta, TEC Edmonton Office. Dr. Newton: Grant (money to institution): AHRQ; Other (money paid to author): University of Alberta Evidence-based Practice Center. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-0362.

Requests for Single Reprints: Lisa Hartling, PhD, University of Alberta, ECHA 4-472, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada; e-mail, hartling@ualberta.ca.

Current Author Addresses: Dr. Hartling and Mr. Pasichnyk: University of Alberta, ECHA 4-472, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada.

Dr. Abou-Setta: George & Fay Yee Centre for Healthcare I, University of Manitoba/Winnipeg Regional Health Authority, GH-714, 820 Sherbrook Street, Winnipeg, Manitoba R3A 1R9, Canada.

Dr. Dursun: University of Alberta, Department of Psychiatry, Neurochemical Research Unit, CSB, 12-127, 11350 83 Avenue, Edmonton, Alberta T6G 2G3, Canada.

Dr. Mousavi: University of Alberta, Room #9416, Aberhart Center, 11402 University Avenue, Edmonton, Alberta T6G 2J3, Canada.

Dr. Newton: University of Alberta, 3-526 Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada.

Author Contributions: Conception and design: L. Hartling, A.M. Abou-Setta, S. Dursun.

Analysis and interpretation of the data: L. Hartling, A.M. Abou-Setta, S. Dursun, A.S. Newton.

Drafting of the article: L. Hartling, A.M. Abou-Setta, S. Dursun, A.S. Newton.

Critical revision of the article for important intellectual content: L. Hartling, A.M. Abou-Setta, S. Dursun, A.S. Newton.

Final approval of the article: L. Hartling, A.M. Abou-Setta, S. Dursun, A.S. Newton.

Provision of study materials or patients: S. Dursun.

Statistical expertise: A.M. Abou-Setta.

Obtaining of funding: L. Hartling.

Administrative, technical, or logistic support: A.M. Abou-Setta, S. Dursun, D. Pasichnyk.

Collection and assembly of data: L. Hartling, A.M. Abou-Setta, S. Dursun, S.S. Mousavi, D. Pasichnyk.


Ann Intern Med. 2012;157(7):498-511. doi:10.7326/0003-4819-157-7-201210020-00525
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Background: Debate continues about the comparative benefits and harms of first-generation antipsychotics (FGAs) and second-generation antipsychotics (SGAs) in treating schizophrenia.

Purpose: To compare the effects of FGAs with those of SGAs in the treatment of adults aged 18 to 64 years with schizophrenia and related psychosis on illness symptoms, diabetes mellitus, mortality, tardive dyskinesia, and a major metabolic syndrome.

Data Sources: English-language studies from 10 electronic databases to March 2012, reference lists of relevant articles, and gray literature.

Study Selection: Randomized trials for efficacy and cohort studies at least 2 years in duration for adverse events.

Data Extraction: Two independent reviewers extracted data from 114 studies involving 22 comparisons and graded the strength of evidence for primary outcomes as insufficient, low, moderate, or high using the Grading of Recommendations Assessment, Development and Evaluation approach.

Data Synthesis: Few differences of clinical importance were found for core illness symptoms; lack of precision in effect estimates precluded firm conclusions for many comparisons. Moderate-strength evidence showed a clinically important benefit of haloperidol over olanzapine for improving positive symptoms, but the benefit was scale-dependent: It was seen when the Scale for the Assessment of Positive Symptoms was used but not when the Positive and Negative Syndrome Scale (PANSS) was used. Moderate-strength evidence showed a clinically important benefit of olanzapine over haloperidol in improving negative symptoms when the PANSS and the Scale for the Assessment of Negative Symptoms were used. Low-strength evidence showed no difference in mortality for chlorpromazine verus clozapine or haloperidol versus aripiprazole, increased incidence of the metabolic syndrome for olanzapine versus haloperidol (risk differences, 2% and 22%), and higher incidence of tardive dyskinesia for chlorpromazine versus clozapine (risk differences, 5% and 9%). Evidence was insufficient to draw conclusions for diabetes mellitus.

Limitations: All studies had high or unclear risk of bias. Length of study follow-up was often too brief to adequately measure adverse events. Medication comparisons, dosage, and outcome measurement were heterogenous for head-to-head comparisons. Selective patient populations limit generalizability.

Conclusion: Clear benefits of FGAs versus SGAs for treating schizophrenia remain inconclusive because of variation in assessing outcomes and lack of clinically important differences for most comparisons. The strength of evidence on safety for major medical events is low or insufficient.

Primary Funding Source: Agency for Healthcare Research and Quality.


The introduction of second-generation antipsychotics (SGAs) for treatment of schizophrenia was an important effort to improve symptom management, reduce extrapyramidal symptoms caused by first-generation antipsychotics (FGAs), and offer patients improved quality of life and functioning. Today, 20 commercial FGAs and SGAs that have been approved by the U.S. Food and Drug Administration (FDA) are available in the United States (Appendix Table 1). Of these, SGAs are more frequently prescribed by physicians. In 2003, three quarters of the 2 million adult patients in the United States who were prescribed an antipsychotic medication were prescribed an SGA, which accounted for 93% of the estimated $2.82 billion spent on these medications in the United States (1).

Table Jump PlaceholderAppendix Table 1.  

Antipsychotics Included in the Systematic Review

Recent large-scale trials and meta-analyses have called into question whether SGAs and FGAs provide clinically important differences for patient outcomes (13), and the question of which medication is more efficacious has yet to be definitively answered. Part of the uncertainty about medication efficacy relates to the lack of studies focused on long-term management. Such issues as how patient management should be influenced by medication heterogeneity within the 2 classes also add ambiguity for physician decision making (1, 46), as do differences between recently published reviews in defining eligible medication comparisons, patients, and clinically important outcomes and evaluating the strength of evidence (1, 719).

This comparative effectiveness review summarizes the benefits and harms associated with commercially available, FDA-approved FGAs and SGAs. Broad inclusion criteria were used for comparisons among FGAs and SGAs, patients, and study outcomes to address the diversity of previously published reviews.

We followed an open process for this review with input from various stakeholders, including the public (20), and a protocol that followed standards for systematic reviews (2123). A full technical report with detailed search strategies, methods, and evidence tables is available from the Agency for Healthcare Research and Quality (21).

Literature Search

We conducted comprehensive searches in MEDLINE (Appendix Table 2), EMBASE, PsycINFO, International Pharmaceutical Abstracts, CINAHL, ProQuest Dissertations and Theses—Full Text, the Cochrane Central Register of Controlled Trials, and Scopus for studies published from 1950 to March 2012. For adverse events, we also searched the U.S. National Library of Medicine's TOXLINE and the MedEffect Canada Adverse Reaction Database.

Table Jump PlaceholderAppendix Table 2.  

Ovid MEDLINE Search Strategy

We hand-searched proceedings from the annual meetings of the American Psychiatric Association (2008–2010) and the International College of Neuropsychopharmacology (2008–2010). We searched clinical trial registries and contacted experts in the field and authors of relevant studies. We retrieved new drug applications for each of the included interventions from the FDA Web site. We reviewed the reference lists of reviews, guidelines, and new drug applications and searched for articles citing relevant studies using Scopus Citation Tracker.

Study Selection

Two reviewers independently screened titles and abstracts. We retrieved the full text of potentially relevant studies. Two reviewers independently reviewed each article using a standardized form with a priori eligibility criteria (Appendix Table 3). We resolved discrepancies through discussion or third-party adjudication. We included studies if they were randomized, controlled trials (RCTs); were nonrandomized, controlled trials (non-RCTs); were cohort studies with a minimum follow-up of 2 years; included adults aged 18 to 64 years with schizophrenia or related psychoses; compared a commercially available FDA-approved FGA with an FDA-approved SGA; and provided data on illness symptoms (Appendix Table 4) or the following adverse events: diabetes mellitus, death, tardive dyskinesia, or a major metabolic syndrome.

Table Jump PlaceholderAppendix Table 3.  

Inclusion and Exclusion Criteria

Table Jump PlaceholderAppendix Table 4.  

Examples of Core Symptoms

Quality Assessment and Rating the Body of Evidence

Two reviewers independently assessed the methodological quality of included studies and resolved disagreements through discussion. We assessed RCTs and non-RCTs using the Cochrane Risk of Bias Tool (22) and cohort studies using the Newcastle–Ottawa Scale (24).

Two reviewers independently evaluated strength of evidence using the Grading of Recommendations Assessment, Development and Evaluation approach of the Evidence-based Practice Center Program and resolved discrepancies through discussion (25). We examined 4 domains: risk of bias, consistency, directness, and precision. Within the grading system, randomized trials always begin with a “high” strength of evidence that can be downgraded on the basis of shortcomings in the body of evidence (for example, overall risk of bias, inconsistency between study results, indirectness of the measured outcomes, and imprecision of the pooled estimate). In contrast, observational studies (for example, cohort studies) begin with a “low” strength of evidence that can be further downgraded (similar to randomized trials) but can also, in rare cases, be upgraded. We assigned an overall grade of “high,” “moderate,” “low,” or “insufficient” strength of evidence. We graded core illness symptoms in the categories of positive symptoms, negative symptoms, general psychopathology, and global ratings or total scores (typically a compilation of positive and negative symptoms or general psychopathology, which included these symptoms plus mood states). We provided a grade for each scale that was reported in the relevant studies. We also graded the adverse events listed in the previous section.

Data Extraction

Two reviewers independently extracted data using standardized forms and resolved discrepancies by referring to the original report. We extracted information on study characteristics, populations, interventions, outcomes, and results. Primary outcomes were improved core symptoms of illness (positive and negative symptoms and general psychopathology) and 4 adverse events specified a priori. Secondary outcomes included functional outcomes; health care system use; response, remission, and relapse rates and medication adherence; health-related quality of life; other patient-oriented outcomes (for example, patient satisfaction); and general and specific measures of other adverse events (for example, extrapyramidal symptoms and weight gain).

When studies incorporated multiple relevant treatment groups or multiple follow-up periods, we extracted data from all groups for the longest follow-up period. In cases of multiple reports of the same study, we referenced the primary, or most relevant, study and extracted additional data from companion reports.

Data Analysis

We conducted meta-analyses in RevMan, version 5.01 (The Cochrane Collaboration, Nordic Cochrane Centre, Copenhagen, Denmark), using a random-effects model (26) when studies were sufficiently similar in terms of design, population, interventions, and outcomes. We combined risk ratios for dichotomous outcomes using the DerSimonian and Laird random-effects model and combined continuous outcomes using mean differences with 95% CIs. We quantified statistical heterogeneity using the I2 statistic. For trials with multiple study groups, we pooled the data for all relevant groups in the same trial before including the study in any meta-analysis so that the same groups were never represented more than once in any given meta-analysis. Where measures of variance were not reported in the studies, we imputed the variance from the largest reported SD in the given meta-analysis.

We conducted subgroup and sensitivity analyses for illness or disorder subtypes, sex, age group (18 to 35 years, 36 to 54 years, and 55 to 64 years), race, comorbid conditions, drug dosage, follow-up period, previous exposure to antipsychotics, treatment of a first episode versus prior episodes, and treatment resistance. Details of these analyses are presented in the appendices to the full technical report. We report subgroup and sensitivity analyses if there was substantial heterogeneity (I2 ≥ 50%). For comparisons with at least 10 studies, we assessed publication bias using funnel plots and statistical tests (2729). For our primary outcome of core symptoms, we considered a difference of 20% to be clinically important (7, 30). We calculated absolute differences (that is, risk differences) for adverse events to enhance interpretation of results.

Role of the Funding Source

The Agency for Healthcare Research and Quality suggested the initial questions and approved copyright assertion for the manuscript but did not participate in the literature search, data analysis, or interpretation of the results.

A total of 9703 unique study reports were identified; we included 114 primary publications (2, 31143) (110 RCTs, 2 non-RCTs, and 2 retrospective cohort studies) and 149 companion publications (Figure). The studies were published between 1974 and 2012 and involved 22 drug comparisons. Most studies were multicenter (54%), involved inpatients (48%), and were conducted in North America (42%). The number of participants ranged from 10 to 118 522 (median, 78; interquartile range, 38 to 296). The average participant age ranged from 21 to 50 years (median, 37 years; interquartile range, 32 to 40 years). The length of follow-up (that is, study duration) ranged from less than 1 day to 4 years (median, 8 weeks; interquartile range, 6 to 26 weeks) for RCTs and non-RCTs; the cohort studies were 3 and 22 years in duration. The route of medication administration was primarily oral; intramuscular administration occurred in 10 studies (9%). Sixty-eight percent of studies were supported by the pharmaceutical industry.

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Figure.

Summary of evidence search and selection.

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None of the RCTs and non-RCTs had low risk of bias, 67% had unclear risk of bias, and 33% had high risk of bias. Trials were commonly assessed as having unclear risk of bias because of incomplete reporting of sequence generation, allocation concealment, and blinding methods. The most common reasons for trials to be assessed as having high risk of bias were lack of blinding and inadequate handling or reporting of outcome data. Methodological quality of the cohort studies was good; both collected data retrospectively.

Core Illness Symptoms

The findings for core illness symptoms are presented in Table 1. Comparisons and outcomes for which strength of evidence was insufficient (for example, evidence from single trials) to draw a conclusion are not displayed; these results for the Positive and Negative Syndrome Scale (PANSS) are displayed in Appendix Table 5. The following sections describe the results for which there was at least low strength of evidence.

Table Jump PlaceholderTable 1.  

Summary of Results and Strength of Evidence for Core Illness Symptoms

Table Jump PlaceholderAppendix Table 5.  

Summary of Insufficient Strength of Evidence for Core Illness Symptoms When the PANSS Was Used

Two differences were found in positive symptom alleviation in comparisons of haloperidol with 5 SGAs, as measured by the PANSS and the Scale for the Assessment of Positive Symptoms. Low-strength evidence showed a benefit for risperidone compared with haloperidol on the PANSS; the difference was not considered clinically important, and there was indication of publication bias. Moderate-strength evidence showed a clinically important benefit of haloperidol over olanzapine on the Scale for the Assessment of Positive Symptoms (Appendix Figure 1). The low strength of evidence for all remaining comparisons was driven by lack of precision in effect estimates.

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Appendix Figure 1.

Positive symptoms (SAPS): haloperidol versus olanzapine.

IV = inverse variance; SAPS = Scale for the Assessment of Positive Symptoms.

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Evidence of benefit for treating negative symptoms with SGAs was stronger. Haloperidol was compared with 6 SGAs by using the PANSS and the Scale for the Assessment of Negative Symptoms. Moderate-strength evidence showed that olanzapine had a clinically important benefit compared with haloperidol for both scales (Appendix Figure 2), with no indication of publication bias. Risperidone also showed moderate-strength evidence of benefit compared with haloperidol on the PANSS, although results were not considered clinically important. There was also no indication of publication bias. Aripiprazole showed moderate-strength evidence of benefit compared with haloperidol, although the difference was not considered clinically important. Strength of evidence for haloperidol versus clozapine, quetiapine, and ziprasidone was low due to lack of precision in effect estimates.

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Appendix Figure 2.

Negative symptoms (PANSS and SANS): haloperidol versus olanzapine.

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale; SANS = Scale for the Assessment of Negative Symptoms.

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There were few differences between FGAs and SGAs in global rating and total symptom score improvement. Moderate-strength evidence showed that olanzapine had a clinically important benefit compared with haloperidol on the PANSS (Appendix Figure 3), with no indication of publication bias. Olanzapine also showed a difference compared with haloperidol on the Clinical Global Impression—Severity scale, but it was not considered clinically important. Moderate-strength evidence showed a clinically important benefit of risperidone compared with haloperidol on the PANSS (Appendix Figure 4), although there was substantial heterogeneity (I2 = 76%). When 1 outlier (significantly favoring haloperidol) was removed, heterogeneity decreased and results remained in favor of risperidone (Appendix Figure 5); there was no indication of publication bias. The outlying study (n = 100) used a relatively small fixed dose of risperidone (2 mg/d), whereas most of the other studies used a range from 1 mg/d to 5 to 20 mg/d. Subgroup analyses by dosage showed less heterogeneity and more benefits for higher doses of risperidone (data in technical report). Moderate-strength evidence showed a benefit for haloperidol compared with quetiapine on the Clinical Global Impression—Severity scale, but the difference was not clinically important. Moderate-strength evidence showed a clinically important benefit for clozapine compared with chlorpromazine based on the total score from the Brief Psychiatric Rating Scale (Appendix Figure 6).

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Appendix Figure 3.

Global rating and total symptom score improvement (PANSS): haloperidol versus olanzapine.

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale.

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Appendix Figure 4.

Global rating and total symptom score improvement (PANSS): haloperidol versus risperidone (with outlier).

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale.

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Appendix Figure 5.

Global rating and total symptom score improvement (PANSS): haloperidol versus risperidone (outlier removed).

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale.

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Appendix Figure 6.

Global rating and total symptom score improvement (BPRS): chlorpromazine versus clozapine.

BPRS = Brief Psychiatric Rating Scale; IV = inverse variance.

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Haloperidol was compared with 4 SGAs, most commonly olanzapine, and results were reported for 8 scales assessing an overall change in general psychopathology. Moderate-strength evidence showed a difference for 1 of 14 comparisons: Olanzapine showed a clinically important benefit on the Montgomery–Asberg Depression Rating Scale (Appendix Figure 7).

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Appendix Figure 7.

General psychopathology (MADRS): haloperidol versus olanzapine.

IV = inverse variance; MADRS = Montgomery–Asberg Depression Rating Scale.

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Response, Remission, and Relapse Rates and Medication Adherence

Findings for these outcomes are presented in Table 2 and were available for 17 head-to-head comparisons. A statistically significant difference in response rates was found favoring clozapine over chlorpromazine (3 studies) (75, 84, 91). Olanzapine was favored over haloperidol for remission (3 trials) (88, 144145) and response rates (14 trials) (40, 85, 88, 98, 101103, 107, 112, 126, 135, 140, 144145). Risperidone was favored over haloperidol for relapse rates (6 trials) (63, 67, 110, 115, 127, 130). Olanzapine was favored over perphenazine for time to all-cause medication discontinuation (37). Clozapine was favored over chlorpromazine for medication adherence (77). These last 2 findings are based on single studies and should be interpreted with caution.

Table Jump PlaceholderTable 2.  

Summary of Results for Other Outcomes

Patient-Oriented Outcomes and Health Care System Use

Patient-oriented outcomes broadly refer to functional outcomes (for example, sexual dysfunction, employment, and economic independence) and outcomes that are important to patients (for example, health-related quality of life). Results for functional outcomes were available for 9 head-to-head comparisons (Table 2), with no statistically significant differences in any comparisons. In terms of health-related quality of life, aripiprazole compared with perphenazine showed 20% improvement (1 trial) (90), and ziprasidone compared with haloperidol showed benefits on the Quality-of-Life Scale (1 trial) (118). Statistically significant differences were found favoring aripiprazole over haloperidol for caregiver satisfaction (1 trial) (66) and patient satisfaction (1 trial) (66). Results for health care system use were available for 10 head-to-head comparisons, with no statistically significant differences for any comparison (Table 2). Some of the results described in this section and Table 2 are based on single trials and should be interpreted with caution.

Medication-Associated Adverse Events and Safety

For the 4 key adverse events, the strength of evidence was insufficient to draw conclusions for most comparisons (Appendix Table 6). Two trials each provided data on mortality for chlorpromazine versus clozapine (105106) and haloperidol versus aripiprazole (Table 3) (34, 136). Absolute differences were small, ranging from 1% to 4% and 0% to 1%, respectively. The length of follow-up (that is, duration) of the trials for the latter comparison was only 24 hours, and the drug was administered via intramuscular injection in both studies. Low-strength evidence showed a higher incidence of the metabolic syndrome for olanzapine than for haloperidol; risk differences were 2% and 22%, respectively, in the 2 relevant studies (88, 102). Low-strength evidence showed a higher incidence of tardive dyskinesia for chlorpromazine than for clozapine; risk differences were 5% and 9% at 12 weeks and 9 years, respectively (77, 84). Across all studies involving adverse events, the strength of evidence was driven by lack of precision in the estimates of effect because of the small numbers of participants studied and events observed.

Table Jump PlaceholderAppendix Table 6.  

Summary of Results for 4 Key Adverse Events With Insufficient Strength of Evidence

Table Jump PlaceholderTable 3.  

Summary of Results and Strength of Evidence for Key Adverse Events

Data were also recorded for general measures of adverse events and specific adverse events by physiologic system; extrapyramidal symptoms were the most frequently reported event (detailed data and analyses available in technical report). For general measures of adverse events, statistically significant differences were found in the incidence of adverse events and withdrawals due to adverse events for several comparisons. The comparison usually included haloperidol, and the risk was consistently higher with the FGA.

Despite FGAs and SGAs being a mainstay in the treatment of schizophrenia in adults, questions remain about whether and how the various commercially available medications differ in efficacy and safety profiles (16). This review provides a comprehensive synthesis of the evidence on the comparative benefits and harms of FDA-approved FGAs and SGAs. We used a broad approach to inclusion criteria for comparisons, patients, and study outcomes to bring together the diversity of previously published reviews and provide a broader perspective on evidence in the field (1, 719).

We identified a large number of relevant studies (114 studies and 22 different comparisons), the majority of which were efficacy trials (146). The most frequent comparisons involved haloperidol and risperidone (40 studies) or olanzapine (35 studies); however, the number of studies available for each comparison and outcome was often limited.

Overall, we found few differences of clinical importance between the active drugs; however, this does not imply that they are equivalent. The strength of evidence from these studies was generally low or insufficient, with considerable variation in scales and subscales used to measure symptoms. This heterogeneity, coupled with the small number of studies within specific comparisons, suggests that there is insufficient power to explain some of the negative findings and precludes firm conclusions that are needed for front-line clinical decision making.

At this time, evidence supporting the use of SGAs for negative symptoms is stronger than that supporting their use for positive symptoms; olanzapine and risperidone were found to be more efficacious than haloperidol in reducing such symptoms as blunted affect and withdrawal. This effect, however, was not observed for improving overall (global) functioning and general psychopathology. Contrary to recent reviews (78), we found no evidence of benefit in improving symptoms with clozapine compared with haloperidol, although moderate-strength evidence showed benefits for clozapine compared with chlorpromazine. Differences in study inclusion criteria between our review and previously published reviews probably account for the different outcomes, with our review including more studies from which to base conclusions. In light of the totality of evidence in this review, the ample low-quality evidence showing no difference between haloperidol and various SGAs in improving symptoms provides an inadequate evidence base to advocate for one medication over another.

The data for adverse events were of low to insufficient strength, suggesting the need for a more focused evaluation of drug safety. Despite our efforts to identify long-term safety data from observational studies, only 2 retrospective cohort studies provided follow-up data at least 2 years in duration. Short-term efficacy trials, which are accepted by the regulatory authorities, may not identify time-dependent adverse events, such as tardive dyskinesia, diabetes mellitus, the metabolic syndrome, or death. Although few studies measured mortality, some evidence suggests that treatment with FGAs or SGAs is no different after immediate use (within 24 hours) or long-term use (>12 months). The strength of evidence for other mortality-related outcomes (such as suicide-related behaviors, which is a risk in this clinical population) (147149) was insufficient to draw conclusions.

We found low-strength evidence for an increased incidence of the metabolic syndrome with use of olanzapine. In general, most studies showed no difference between FGAs and SGAs in terms of increased risk for the metabolic syndrome or diabetes mellitus; however, the strength of evidence was usually insufficient. Although the methodological and reporting limitations of these studies make conclusions about these outcomes premature (150), several reviews have identified clozapine and olanzapine as contributing to greater weight gain (7, 151153), but this may not necessarily translate into increased risk for more severe outcomes. Further study of this trajectory is warranted with higher-quality longitudinal studies.

Our results are consistent with those of CATIE (Clinical Antipsychotic Trials of Intervention Effectiveness) (2), a widely cited trial in this field. CATIE was designed to evaluate whether FGAs were inferior to SGAs in efficacy and safety. Findings from CATIE suggested that the FGA perphenazine and various SGAs (olanzapine, quetiapine, risperidone, and ziprasidone) differed more in their adverse effect profiles than in their therapeutic effect profiles. The study, like this review, also showed that effectiveness across medications varied and that the difference was clinically important in some cases.

Our results are also similar to those of a recent systematic review of SGAs versus FGAs, although our review is broader in scope in terms of medications included, patient populations, and outcomes (1). There were several methodological differences between the previous review and this one: The previous review included non–FDA-approved antipsychotics, restricted the analysis to only double-blind trials, included only studies examining optimum SGA dosage and oral route of administration, pooled data across efficacy outcome measures, and pooled different FGAs. The different methodologies may have led to slightly different conclusions about individual SGAs.

One of the unique features of our review is the strength-of-evidence assessments, which provide information on the level of confidence one can place on the results of existing studies. In most cases, the strength of evidence was insufficient or low, highlighting the likelihood that future research may change the estimates of effect and the need for a stronger evidence base to inform clinical practice. Current treatment guidelines from the American Psychiatric Association for patients with schizophrenia provide specific recommendations on medication timing (for example, acute phase or first episode) but broad variables for medication options (154). This approach may reflect the current state of evidence for FGAs and SGAs, and as stronger evidence emerges, it may come to reflect more specific recommendations for prescribing physicians.

There were limitations in the design and quality of the primary studies. Most studies were short-term RCTs, often with an a priori hypothesis that the SGA would be more efficacious (155). Most trials did not sufficiently report methods to prevent selection and performance bias. Few trials reported blinding study investigators and participants; single-blinded and open-label trials in this field have been found to favor SGAs over FGAs (1). Furthermore, the individual studies and, in many cases, the pooled results may not have sufficient power to detect equivalence or noninferiority between drugs.

Most studies in this review were industry-funded (69%), which can increase the chance of proindustry findings (156). Funding was not disclosed for 19% of studies, highlighting the need for transparency in reporting the nature and extent of financial support. The choice of medication comparisons, dosages, and outcomes in the studies included in this review may have been driven by the funder's interests and priorities. Publication and reporting of select comparisons and outcomes are other potential limitations of this body of evidence.

Few studies provided evidence for comparable patient populations. We found notable heterogeneity across studies for disorder subtypes, comorbid drug or alcohol use, treatment resistance, and number of previous episodes, which result in differential response to treatment. Furthermore, many studies were highly selective in patient enrollment, which may increase the likelihood of drug benefit and decrease the likelihood of adverse events. Detailed subgroup analyses are reported elsewhere (21). Characteristics of the research, including drug dosages (for example, lower doses of FGAs in more recent studies) and patient populations (for example, fewer patients already exposed to FGAs or proven treatment resistance to FGAs in recent studies), also changed over time. Finally, differences in medication comparisons and dosage and outcome measurement limited our synthesis, and outcomes that are important for understanding medication adherence and persistence (a common clinical encounter in this patient population), such as sedation and restlessness, were rarely reported.

More longitudinal research is needed on the long-term safety of FGAs versus SGAs. Despite our efforts to identify long-term safety data from observational studies, only 2 retrospective cohort studies were identified. Consensus is needed on the most important comparisons between FGAs and SGAs for future studies. Short- and long-term evaluations with patient subpopulations, including those with medical and neurologic comorbid conditions, are needed. There is a need for studies investigating the influence of dose, age, and other factors, such as comorbid conditions, on serious adverse events, which would help estimate possible risks in specific patient populations. Future studies should also examine functional outcomes that are important to patients, including health-related quality of life, relationships, academic and occupational performance, and legal interactions.

Existing studies on the comparative effectiveness of individual FGAs and SGAs preclude drawing firm conclusions because of sparse data and imprecise effect estimates. There were relatively few differences of clinical importance among 114 studies. The current evidence base is inadequate for clinicians and patients to make informed decisions about treatment. Outcomes potentially important to patients were rarely assessed. Data on long-term safety are lacking and urgently needed.

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This article was published at www.annals.org on 14 August 2012.

Figures

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Figure.

Summary of evidence search and selection.

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Appendix Figure 1.

Positive symptoms (SAPS): haloperidol versus olanzapine.

IV = inverse variance; SAPS = Scale for the Assessment of Positive Symptoms.

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Appendix Figure 2.

Negative symptoms (PANSS and SANS): haloperidol versus olanzapine.

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale; SANS = Scale for the Assessment of Negative Symptoms.

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Appendix Figure 3.

Global rating and total symptom score improvement (PANSS): haloperidol versus olanzapine.

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale.

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Appendix Figure 4.

Global rating and total symptom score improvement (PANSS): haloperidol versus risperidone (with outlier).

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale.

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Appendix Figure 5.

Global rating and total symptom score improvement (PANSS): haloperidol versus risperidone (outlier removed).

IV = inverse variance; PANSS = Positive and Negative Syndrome Scale.

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Appendix Figure 6.

Global rating and total symptom score improvement (BPRS): chlorpromazine versus clozapine.

BPRS = Brief Psychiatric Rating Scale; IV = inverse variance.

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Appendix Figure 7.

General psychopathology (MADRS): haloperidol versus olanzapine.

IV = inverse variance; MADRS = Montgomery–Asberg Depression Rating Scale.

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Tables

Table Jump PlaceholderAppendix Table 1.  

Antipsychotics Included in the Systematic Review

Table Jump PlaceholderAppendix Table 2.  

Ovid MEDLINE Search Strategy

Table Jump PlaceholderAppendix Table 3.  

Inclusion and Exclusion Criteria

Table Jump PlaceholderAppendix Table 4.  

Examples of Core Symptoms

Table Jump PlaceholderTable 1.  

Summary of Results and Strength of Evidence for Core Illness Symptoms

Table Jump PlaceholderAppendix Table 5.  

Summary of Insufficient Strength of Evidence for Core Illness Symptoms When the PANSS Was Used

Table Jump PlaceholderTable 2.  

Summary of Results for Other Outcomes

Table Jump PlaceholderAppendix Table 6.  

Summary of Results for 4 Key Adverse Events With Insufficient Strength of Evidence

Table Jump PlaceholderTable 3.  

Summary of Results and Strength of Evidence for Key Adverse Events

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Sponsorship of Research Articles Can Affect Findings
Posted on October 4, 2012
Thomas E. Finucane, MD
Johns Hopkins Bayview Medical Center
Conflict of Interest: None Declared

To the Editor:

In this (1) and in other contexts, the sponsorship of research articles has been shown to affect the findings. Can the authors say anything about the effects of Pharma sponsorship on the outcomes of the trials? This might be a particular problem with these vendors, as many have been paying billions of dollars in fines recently for a variety of behaviors related to promoting their products.

Thomas E. Finucane, MD

Johns Hopkins Bayview Medical Center

Reference

1. Lisa Hartling, PhD; Ahmed M. Abou-Setta, MD, PhD; Serdar Dursun, MD, PhD; Shima S. Mousavi, MD; Dion Pasichnyk, BSc; and Amanda S. Newton, RN, PhD Antipsychotics in Adults With Schizophrenia: Comparative Effectiveness of First-Generation Versus Second-Generation Medications: A Systematic Review and Meta-analysis . Ann Intern Med. 2 October 2012;157(7):498-511

Sponsorship of Research Articles Can Affect Findings: RESPONSE FROM AUTHORS
Posted on November 20, 2012
Lisa Hartling, PhD Amanda S. Newton, RN, PhD Serdar Dursun, MD, PhD
University of Alberta
Conflict of Interest: Dr. Hartling: Contract (money to institution): AHRQ. Dr. Abou-Setta: Grant (money to institution): AHRQ. Dr. Dursun: Grants/grants pending (money to institution): CIHR-Canada, Norlien Foundation; Patents (planned, pending, or issued): sodium nitroprusside for the treatment of schizophrenia, in partnership with the University of Alberta, TEC Edmonton Office. Dr. Newton: Grant (money to institution): AHRQ; Other (money paid to author): University of Alberta Evidence-based Practice Center.

There is a strong body of evidence to support Dr. Finucane’s observation that sponsorship of research articles has been shown to affect reported results (e.g., 1). In particular, there is evidence showing that industry-sponsored studies may show results supporting the industry’s product. An important task for systematic reviewers is to explore variables that may affect the validity of the reported results, including the source of funding. In our systematic review comparing first-generation with second-generation antipsychotics (2,3), we found that 70% of the included studies were industry-funded. We also noted that funding source was not disclosed for 19% of studies.

In our review we discussed that the choice of medication comparisons, dosages and outcomes may be driven by the funder’s interests and priorities (3). We conducted extensive subgroup and sensitivity analyses to examine variables that could result in differential treatment effects. These analyses included source of funding, risk of bias, patient characteristics (e.g., race, treatment resistance), treatment characteristics (e.g., dose), and study methods (e.g., duration of followup).

We found some differences when studies were grouped according to whether or not they were supported by industry funding. The patterns were not consistent and in some cases few studies were available for the “no industry” subgroup; therefore, it was difficult to discern whether no differences within this subgroup were due to the funding source or simply inadequate statistical power to detect differences. These analyses are detailed in an appendix to our full technical report (3).

The results of our review should be interpreted within the context that most studies contributing to this body of evidence were industry-funded. Our inability to draw firm clinical conclusions stemmed from inconsistencies across studies in terms of treatment comparisons, the outcomes assessed, how outcomes were measured, and patient populations. Within this field, stakeholders need to reach consensus on the most important comparisons that will be most informative and provide the most valid and accurate information to inform clinical decisions. Further, decisions involving patients, their families and their physicians need to be made regarding the most important outcomes and these should be the focus of future research. As we have mentioned, longer-term studies are needed as well as examination of important patient subpopulations, such as those with medical and neurological comorbidities. As with all research, full disclosure of the source of funding and role of the funder in the design, analysis and reporting of results is essential to interpreting the evidence.

References

1. Sismondo S. Pharmaceutical company funding and its consequences: a qualitative systematic review. Contemp Clin Trials 2008;29(2):109-13. PMID:17919992.

2. Hartling L, Abou-Setta AM, Dursun S, Mousavi SS, Psichnyk D, Newton AS. Antipsychotics in adults with schizophrenia: comparative effectiveness of first-generation versus second-generation medications: a systematic review and meta-analysis. Ann Intern Med 2012 Aug 14. doi: 10.7326/0003-4819-157-7-201210020-00525. [Epub ahead of print]

3. Abou-Setta AM, Mousavi SS, Spooner C, Schouten JR, Pasichnyk D, Armijo-Olivo S, Beaith A, Seida JC, Dursun S, Newton AS, Hartling L. First-Generation Versus Second-Generation Antipsychotics in Adults: Comparative Effectiveness [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2012 Aug.

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