Nur Hani Zainal, Corina Benjet, Yesica Albor, Mauricio Nuñez-Delgado, Renato Zambrano-Cruz, Carlos C. Contreras-Ibáñez, Lorena Cudris-Torres, Francisco R. de la Peña, Noé González, José Benjamín Guerrero-López, Raúl A. Gutierrez-Garcia, Ana Lucía Jiménez-Peréz, Maria Elena Medina-Mora, Pamela Patiño, Pim Cuijpers, Sarah M. Gildea, Alan E. Kazdin, Chris J. Kennedy, Alex Luedtke, Nancy A. Sampson, Maria V. Petukhova, Jose R. Zubizarreta, Ronald C. Kessler
{"title":"在制定精确治疗规则的随机临床试验中，调整干预依从性影响的统计方法。","authors":"Nur Hani Zainal, Corina Benjet, Yesica Albor, Mauricio Nuñez-Delgado, Renato Zambrano-Cruz, Carlos C. Contreras-Ibáñez, Lorena Cudris-Torres, Francisco R. de la Peña, Noé González, José Benjamín Guerrero-López, Raúl A. Gutierrez-Garcia, Ana Lucía Jiménez-Peréz, Maria Elena Medina-Mora, Pamela Patiño, Pim Cuijpers, Sarah M. Gildea, Alan E. Kazdin, Chris J. Kennedy, Alex Luedtke, Nancy A. Sampson, Maria V. Petukhova, Jose R. Zubizarreta, Ronald C. Kessler","doi":"10.1002/mpr.70005","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Heterogeneity of treatment effects (HTEs) can occur because of either differential treatment compliance or differential treatment effectiveness. This distinction is important, as it has action implications, but it is unclear how to distinguish these two possibilities statistically in precision treatment analysis given that compliance is not observed until after randomization. We review available statistical methods and illustrate a recommended method in secondary analysis in a trial focused on HTE.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>The trial randomized <i>n</i> = 880 anxious and/or depressed university students to guided internet-delivered cognitive behavioral therapy (i-CBT) or treatment-as-usual (TAU) and evaluated joint remission. Previously reported analyses documented superiority of i-CBT but significant HTE. In the reanalysis reported here, we used baseline (i.e., pre-randomization) covariates to predict compliance among participants randomized to guided i-CBT, generated a cross-validated within-person expected compliance score based on this model in <i>both</i> intervention groups, and then used this expected composite score as a predictor in an expanded HTE analysis.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The significant intervention effect was limited to participants with high expected compliance. Residual HTE was nonsignificant.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Future psychotherapy HTE trials should routinely develop and include expected compliance composite scores to distinguish the effects of differential treatment compliance from the effects of differential treatment effectiveness.</p>\n </section>\n </div>","PeriodicalId":50310,"journal":{"name":"International Journal of Methods in Psychiatric Research","volume":"34 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11711205/pdf/","citationCount":"0","resultStr":"{\"title\":\"Statistical methods to adjust for the effects on intervention compliance in randomized clinical trials where precision treatment rules are being developed\",\"authors\":\"Nur Hani Zainal, Corina Benjet, Yesica Albor, Mauricio Nuñez-Delgado, Renato Zambrano-Cruz, Carlos C. Contreras-Ibáñez, Lorena Cudris-Torres, Francisco R. de la Peña, Noé González, José Benjamín Guerrero-López, Raúl A. Gutierrez-Garcia, Ana Lucía Jiménez-Peréz, Maria Elena Medina-Mora, Pamela Patiño, Pim Cuijpers, Sarah M. Gildea, Alan E. Kazdin, Chris J. Kennedy, Alex Luedtke, Nancy A. Sampson, Maria V. Petukhova, Jose R. Zubizarreta, Ronald C. Kessler\",\"doi\":\"10.1002/mpr.70005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Heterogeneity of treatment effects (HTEs) can occur because of either differential treatment compliance or differential treatment effectiveness. This distinction is important, as it has action implications, but it is unclear how to distinguish these two possibilities statistically in precision treatment analysis given that compliance is not observed until after randomization. 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Statistical methods to adjust for the effects on intervention compliance in randomized clinical trials where precision treatment rules are being developed
Background
Heterogeneity of treatment effects (HTEs) can occur because of either differential treatment compliance or differential treatment effectiveness. This distinction is important, as it has action implications, but it is unclear how to distinguish these two possibilities statistically in precision treatment analysis given that compliance is not observed until after randomization. We review available statistical methods and illustrate a recommended method in secondary analysis in a trial focused on HTE.
Methods
The trial randomized n = 880 anxious and/or depressed university students to guided internet-delivered cognitive behavioral therapy (i-CBT) or treatment-as-usual (TAU) and evaluated joint remission. Previously reported analyses documented superiority of i-CBT but significant HTE. In the reanalysis reported here, we used baseline (i.e., pre-randomization) covariates to predict compliance among participants randomized to guided i-CBT, generated a cross-validated within-person expected compliance score based on this model in both intervention groups, and then used this expected composite score as a predictor in an expanded HTE analysis.
Results
The significant intervention effect was limited to participants with high expected compliance. Residual HTE was nonsignificant.
Conclusions
Future psychotherapy HTE trials should routinely develop and include expected compliance composite scores to distinguish the effects of differential treatment compliance from the effects of differential treatment effectiveness.
期刊介绍：
The International Journal of Methods in Psychiatric Research (MPR) publishes high-standard original research of a technical, methodological, experimental and clinical nature, contributing to the theory, methodology, practice and evaluation of mental and behavioural disorders. The journal targets in particular detailed methodological and design papers from major national and international multicentre studies. There is a close working relationship with the US National Institute of Mental Health, the World Health Organisation (WHO) Diagnostic Instruments Committees, as well as several other European and international organisations.
MPR aims to publish rapidly articles of highest methodological quality in such areas as epidemiology, biostatistics, generics, psychopharmacology, psychology and the neurosciences. Articles informing about innovative and critical methodological, statistical and clinical issues, including nosology, can be submitted as regular papers and brief reports. Reviews are only occasionally accepted.
MPR seeks to monitor, discuss, influence and improve the standards of mental health and behavioral neuroscience research by providing a platform for rapid publication of outstanding contributions. As a quarterly journal MPR is a major source of information and ideas and is an important medium for students, clinicians and researchers in psychiatry, clinical psychology, epidemiology and the allied disciplines in the mental health field.
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