Second-generation antipsychotics are associated with moderate benefits in terms of improved schizophrenia symptoms, but also with higher rates of side-effects such as excessive weight gain (WG); a consensus on their efficacy has not been reached. To date, no study has evaluated the interplay of treatments and side-effects in a single framework, which is a critical step to clarify the role of side-effects in explaining the efficacy of these antipsychotics. We used recent methods for mediation and interaction to clarify the role of WG in explaining the effects of second-generation drugs on schizophrenia symptoms. We used data from 1460 participants in the CATIE trial, assigned to either perphenazine (first-generation comparison drug), olanzapine, quetiapine, risperidone, or ziprasidone. The primary outcome was an individual's score on the Positive and Negative Syndrome Scale (PANSS) for symptoms of schizophrenia after 9 months, separately evaluated as positive (PANSS+), negative (PANSS-), and total PANSS score. WG after 6 months was investigated as a potential mediator and effect modifier. Results showed that, by limiting WG, patients would benefit of a considerably better improvement in terms of PANSS symptoms. In the scenario of weight change being controlled between -2% and 1% for all participants, patients assigned to olanzapine would experience the highest significant improvements in both PANSS+ (-2.66 points; 95% CI: -4.98, -0.35), PANSS- (-1.59; 95% CI: -4.31, 1.14), and total PANSS (-6.11; 95% CI: -13.13, 0.92). In conclusion, occurrence of excessive WG hampers the potentially beneficial effects of second-generation antipsychotics, thus suggesting future directions for treatment and interventions.
Clinical trial data are the gold standard for evaluating pharmaceutical safety and efficacy. There is an ethical and scientific imperative for transparency and data sharing to confirm published results and generate new knowledge. The Open Translational Science in Schizophrenia (OPTICS) Project was an open-science initiative aggregating Janssen clinical trial and NIH/NIMH data from real-world studies and trials in schizophrenia. The project aims were to show the value of using shared data to examine: therapeutic safety and efficacy; disease etiologies and course; and methods development. The success of project investigators was due to collaboration from project applications through analyses, with support from the Harvard Catalyst. Project work was independent of Janssen; all intellectual property was dedicated to the public. Efforts such as this are necessary to gain deeper insights into the biology of disease, foster collaboration, and to achieve the goal of developing better treatments, reducing the overall public health burden of devastating brain diseases.
People with schizophrenia are at considerably higher risk of cardiometabolic morbidity than the general population. Second-generation antipsychotic drugs contribute to that risk partly through their weight gain effects, exacerbating an already high burden of disease. While standard ‘as-randomized’ analyses of clinical trials provide valuable information, they ignore adherence patterns across treatment arms, confounding estimates of realized treatment exposure on outcome. We assess the effect of specific second-generation antipsychotics on weight gain, defined as at least a 7% increase in weight from randomization, using a Bayesian hierarchical model network meta-analysis with individual patient level data. Our data consisted of 14 randomized clinical trials contributing 5923 subjects (mean age = 39 [SD = 12]) assessing various combinations of olanzapine (n = 533), paliperidone (n = 3482), risperidone (n = 540), and placebo (n = 1368). The median time from randomization to dropout or trial completion was 6 weeks (range: 0–60 weeks). The unadjusted probability of weight gain in the placebo group was 4.8% across trials. For each 10 g chlorpromazine equivalent dose increase in olanzapine, the odds of weight gain increased by 5 (95% credible interval: 1.4, 5.3); the effect of risperidone (odds ratio = 1.6 [0.25, 9.1]) was estimated with considerable uncertainty but no different from paliperidone (odds ratio = 1.3 [1.2, 1.5]).
To date, no study has evaluated the joint role of symptoms and adverse events as mediators of the effect of second-generation antipsychotics on patients’ social functioning. We used recently developed methods for mediation analysis with multiple mediators to clarify the interplay of adverse events and symptoms in explaining the effects of paliperidone (R code for implementing the mediation analysis for multiple mediators is provided). We used data from 490 participants in a 6-week randomized dose–response trial that assigned three fixed dosages of ER OROS paliperidone (3, 9, and 15 mg/day). The primary outcome was an individual’s score on the social performance scale assessed after 6 weeks. The sum of Positive and Negative Syndrome Scale (PANSS), weight gain, and extrapyramidal symptoms measured via the Simpson–Angus Scale after 5 weeks were investigated as potential mediators and effect modifiers of treatment effects. Results from mediation analyses showed that the improvements in social functioning are partly explained by reduction in PANSS symptoms. Suggestive evidence that adverse events could play a role as mediators was found. In particular, weight gain displayed a non-linear relationship with social functioning, whereby beneficial effects observed at small levels of weight gain were reduced in the presence of excessive weight gain. In conclusion, we found that the short-term effects of paliperidone on social functioning were dependent on the successful reduction in PANSS symptoms and possibly the occurrence of excessive weight gain, thus suggesting future directions for treatment and interventions.
Mediation analysis allows decomposing a total effect into a direct effect of the exposure on the outcome and an indirect effect operating through a number of possible hypothesized pathways. Recent studies have provided formal definitions of direct and indirect effects when multiple mediators are of interest, and have described parametric and semi-parametric methods for their estimation. Investigating direct and indirect effects with multiple mediators, however, can be challenging in the presence of multiple exposure-mediator and mediator-mediator interactions. In this paper we derive a decomposition of the total effect that unifies mediation and interaction when multiple mediators are present. We illustrate the properties of the proposed framework, in a secondary analysis of a pragmatic trial for the treatment of schizophrenia. The decomposition is employed to investigate the interplay of side-effects and psychiatric symptoms in explaining the effect of antipsychotic on quality of life in schizophrenia patients. Our result offers a valuable tool to identify the proportions of total effect due to mediation and interaction when more than one mediator is present, providing the finest decomposition of the total effect that unifies multiple mediators and interactions.