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Joint Estimation of Treatment and Placebo Effects in Clinical Trials with Longitudinal Blinding Assessments.
Liu, Wei; Zhang, Zhiwei; Schroeder, R Jason; Ho, Martin; Zhang, Bo; Long, Cynthia; Zhang, Hui; Irony, Telba Z.
Afiliación
  • Liu W; Department of Mathematics, Harbin Institute of Technology, Harbin, P. R. China; Division of Biostatistics, Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Zhang Z; Division of Biostatistics, Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Schroeder RJ; Division of Biostatistics, Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Ho M; Division of Biostatistics, Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Zhang B; Division of Biostatistics, Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Long C; Division of Reproductive, Gastro-Renal, and Urological Devices, Office of Device Evaluation, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Zhang H; Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.
  • Irony TZ; Office of Biostatistics and Epidemiology, Center for Biologic Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.
J Am Stat Assoc ; 111(514): 538-548, 2016.
Article en En | MEDLINE | ID: mdl-27110045
In some therapeutic areas, treatment evaluation is frequently complicated by a possible placebo effect (i.e., the psychobiological effect of a patient's knowledge or belief of being treated). When a substantial placebo effect is likely to exist, it is important to distinguish the treatment and placebo effects in quantifying the clinical benefit of a new treatment. These causal effects can be formally defined in a joint causal model that includes treatment (e.g., new versus placebo) and treatmentality (i.e., a patient's belief or mentality about which treatment she or he has received) as separate exposures. Information about the treatmentality exposure can be obtained from blinding assessments, which are increasingly common in clinical trials where blinding success is in question. Assuming that treatmentality has a lagged effect and is measured at multiple time points, this article is concerned with joint evaluation of treatment and placebo effects in clinical trials with longitudinal follow-up, possibly with monotone missing data. We describe and discuss several methods adapted from the longitudinal causal inference literature, apply them to a weight loss study, and compare them in simulation experiments that mimic the weight loss study.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: J Am Stat Assoc Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: J Am Stat Assoc Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos