Samina Ali1,2, Gareth Hopkin3, Naveen Poonai4, Lawrence Richer5, Maryna Yaskina6, Anna Heath7,8,9, Terry Paul Klassen10,11, Chris McCabe3. 1. Department of Pediatrics, University of Alberta, AB, Edmonton, Canada. sali@ualberta.ca. 2. Women and Children's Health Research Institute, University of Alberta, Edmonton, Alberta, Canada. sali@ualberta.ca. 3. Institute of Health Economics, Edmonton, Alberta, Canada. 4. Departments of Pediatrics and Internal Medicine, Schulich School of Medicine & Dentistry, Childrens' Health Research Institute, London, Ontario, Canada. 5. Department of Pediatrics, University of Alberta, AB, Edmonton, Canada. 6. Women and Children's Health Research Institute, University of Alberta, Edmonton, Alberta, Canada. 7. The Hospital for Sick Children, Toronto, Ontario, Canada. 8. University of Toronto, Toronto, Ontario, Canada. 9. University College London, London, UK. 10. Max Rady College of Medicine, Pediatrics and Child Health, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada. 11. Children's Hospital Research Institute of Manitoba, Winnipeg, Manitoba, Canada.
Abstract
BACKGROUND: Patients and their families often have preferences for medical care that relate to wider considerations beyond the clinical effectiveness of the proposed interventions. Traditionally, these preferences have not been adequately considered in research. Research questions where patients and families have strong preferences may not be appropriate for traditional randomized controlled trials (RCTs) due to threats to internal and external validity, as there may be high levels of drop-out and non-adherence or recruitment of a sample that is not representative of the treatment population. Several preference-informed designs have been developed to address problems with traditional RCTs, but these designs have their own limitations and may not be suitable for many research questions where strong preferences and opinions are present. METHODS: In this paper, we propose a novel and innovative preference-informed complementary trial (PICT) design which addresses key weaknesses with both traditional RCTs and available preference-informed designs. In the PICT design, complementary trials would be operated within a single study, and patients and/or families would be given the opportunity to choose between a trial with all treatment options available and a trial with treatment options that exclude the option which is subject to strong preferences. This approach would allow those with strong preferences to take part in research and would improve external validity through recruiting more representative populations and internal validity. Here we discuss the strengths and limitations of the PICT design and considerations for analysis and present a motivating example for the design based on the use of opioids for pain management for children with musculoskeletal injuries. CONCLUSIONS: PICTs provide a novel and innovative design for clinical trials with more than two arms, which can address problems with existing preference-informed trial designs and enhance the ability of researchers to reflect shared decision-making in research as well as improving the validity of trials of topics with strong preferences.
BACKGROUND:Patients and their families often have preferences for medical care that relate to wider considerations beyond the clinical effectiveness of the proposed interventions. Traditionally, these preferences have not been adequately considered in research. Research questions where patients and families have strong preferences may not be appropriate for traditional randomized controlled trials (RCTs) due to threats to internal and external validity, as there may be high levels of drop-out and non-adherence or recruitment of a sample that is not representative of the treatment population. Several preference-informed designs have been developed to address problems with traditional RCTs, but these designs have their own limitations and may not be suitable for many research questions where strong preferences and opinions are present. METHODS: In this paper, we propose a novel and innovative preference-informed complementary trial (PICT) design which addresses key weaknesses with both traditional RCTs and available preference-informed designs. In the PICT design, complementary trials would be operated within a single study, and patients and/or families would be given the opportunity to choose between a trial with all treatment options available and a trial with treatment options that exclude the option which is subject to strong preferences. This approach would allow those with strong preferences to take part in research and would improve external validity through recruiting more representative populations and internal validity. Here we discuss the strengths and limitations of the PICT design and considerations for analysis and present a motivating example for the design based on the use of opioids for pain management for children with musculoskeletal injuries. CONCLUSIONS: PICTs provide a novel and innovative design for clinical trials with more than two arms, which can address problems with existing preference-informed trial designs and enhance the ability of researchers to reflect shared decision-making in research as well as improving the validity of trials of topics with strong preferences.
Authors: Samina Ali; Manasi Rajagopal; Terry Klassen; Lawrence Richer; Christopher McCabe; Andy Willan; Maryna Yaskina; Anna Heath; Amy L Drendel; Martin Offringa; Serge Gouin; Antonia Stang; Scott Sawyer; Maala Bhatt; Serena Hickes; Naveen Poonai Journal: BMJ Open Date: 2020-06-21 Impact factor: 2.692
Authors: Samina Ali; Gareth Hopkin; Naveen Poonai; Lawrence Richer; Maryna Yaskina; Anna Heath; Terry Paul Klassen; Chris McCabe Journal: Trials Date: 2021-05-20 Impact factor: 2.279