ArticlePharmacoEconomics - open2023
Budget Impact Analysis of Risperidone Use and Adverse Event Monitoring in Autism Spectrum Disorder in Brazil: Assessment of Theoretical Versus Real Data.
Article in PharmacoEconomics - open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Review of Autism Spectrum Disorder (ASD): Epidemiology, Aetiology, Pathology, and Pharmacological Treatment.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Recalculation of the budgetary impact of risperidone use for Autism Spectrum Disorder: a case study using measured demand data, Brazil, 2017-2019.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
BACKGROUND AND
aimsRisperidone is used in autism spectrum disorder (ASD) to manage aggressive behavior. Budget impact analysis (BIA) assists managers in promoting more sustainable health systems; however, it is unclear whether BIAs underestimate or overestimate the estimates derived from real-world data. This study aimed to compare the estimated BIA values of risperidone use and the monitoring of adverse events in ASD using theoretical and real data.
methodsAnalyses were conducted based on the clinical protocol and the Brazilian therapeutic guidelines for ASD. The perspective adopted was that of the Unified Health System (SUS), considering a time horizon of 5 years. Three possible scenarios were considered based on the maximum daily dose of risperidone. Expenses related to the acquisition of risperidone and the monitoring of adverse events were taken into account using health databases in Brazil. For the calculation based on theoretical data, the prevalence of ASD was estimated using information from the scientific literature and the Brazilian demographic census. The model calculated from real data was obtained by analyzing the linear trend of the number of users assisted in the SUS from 2017 to 2021.
resultsThe population estimated by the theoretical model compared with the model calculated from the real data was higher. Likewise, the 5-year budgetary impact of the theoretical model versus the model calculated from the real data was higher, with statistical significance in all scenarios (p < 0.001). In the real data model, the most economically advantageous scenarios were Scenario 1 for children (International dollars [I$] 7,630,040.73) and Scenario 3 for adults (I$60,329,288.17). Estimated expenditures for monitoring adverse events ranged from 17 to 74% in children and from 50% to 63% in adults.
conclusionsThe data revealed significant differences in population and cost estimation between theoretical data and real-world data. The expenses associated with monitoring adverse events represented a substantial expenditure estimate for the SUS.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.