Applying advanced psychometrics to antipsychotic treatment trials: A protocol comparing effect estimates.

Open research Europe Pub Date : 2026-06-17 eCollection Date: 2026-01-01 DOI:10.12688/openreseurope.23623.1
Timo Schurr, Fiona Boland, David Byrne, Frank Doyle
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引用次数: 0

Abstract

Background: Antipsychotic trials in schizophrenia quantify treatment efficacy using clinician-rated scales such as the Positive and Negative Syndrome Scale (PANSS) and Brief Psychiatric Rating Scale (BPRS). If these scales include redundant or weakly informative items, measurement noise can blur drug-comparator differences that may dilute real effect sizes. Modern psychometric methods can refine and re-weight symptom scores that may improve precision and potentially increase detectable treatment effects, although it is unclear which approaches might be best.

Aims: To 1) determine best psychometric models for the PANSS and BPRS, and 2) test whether psychometrically-informed scoring of PANSS/BPRS alters estimated antipsychotic effect sizes compared with conventional total-score analyses, and 3) to explore whether any changes differ across symptom domains and by sex.

Method: We will conduct secondary analyses of anonymised individual participant data from randomized Phase II-IV schizophrenia trials accessed via secure data-sharing platforms (YODA Project and Vivli). Item-level PANSS/BPRS data will be harmonised at baseline and outcome. Psychometric models will be derived using confirmatory factor analysis, item response theory, and network analysis. Stability and invariance analyses will be conducted, examining covariates such as age and sex. Antipsychotic efficacy will be estimated using mixed-effects participant-level models, expressed as Cohen's d standardised mean differences (SMDs) for both conventional and psychometrically-informed outcomes. The primary outcome will be the difference in SMDs between conventional and psychometrically-informed effect sizes, summarised across trials.

Conclusions: This study will determine whether best practice psychometric refinement of existing measures meaningfully changes antipsychotic effect size estimates, informing outcome measurement choices and interpretation of trial results.

将先进的心理测量学应用于抗精神病治疗试验:比较效果估计的方案。
背景:精神分裂症的抗精神病药物试验使用临床评定量表,如阳性和阴性症状量表(PANSS)和简短精神病学评定量表(BPRS)来量化治疗效果。如果这些量表包含冗余或弱信息项目,测量噪声会模糊药物比较器的差异,从而可能稀释实际效应大小。现代心理测量方法可以改进和重新衡量症状评分,这可能提高准确性,并可能增加可检测的治疗效果,尽管尚不清楚哪种方法可能是最好的。目的:1)确定PANSS和BPRS的最佳心理测量模型;2)测试与传统总分分析相比,PANSS/BPRS的心理测量信息评分是否会改变估计的抗精神病药物效应大小;3)探索症状域和性别之间是否存在差异。方法:我们将对通过安全数据共享平台(YODA项目和Vivli)访问的随机II-IV期精神分裂症试验的匿名个体参与者数据进行二次分析。项目一级的PANSS/BPRS数据将在基线和结果方面进行协调。心理测量模型将使用验证性因子分析、项目反应理论和网络分析来推导。将进行稳定性和不变性分析,检查协变量,如年龄和性别。抗精神病疗效将使用混合效应参与者水平模型进行估计,该模型表示为常规结果和心理计量学结果的科恩标准平均差异(smd)。主要结果将是传统和心理测量学效应量之间的smd差异,并在试验中进行总结。结论:本研究将确定现有措施的最佳实践心理测量改进是否有意义地改变抗精神病药物效应大小估计,为结果测量选择和试验结果的解释提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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