Literature DB >> 25128043

PRO data collection in clinical trials using mixed modes: report of the ISPOR PRO mixed modes good research practices task force.

Sonya Eremenco1, Stephen Joel Coons2, Jean Paty3, Karin Coyne4, Antonia V Bennett5, Damian McEntegart6.   

Abstract

The objective of this report was to address the use and mixing of data collection modes within and between trials in which patient-reported outcome (PRO) end points are intended to be used to support medical product labeling. The report first addresses the factors that should be considered when selecting a mode or modes of PRO data collection in a clinical trial, which is often when mixing is first considered. Next, a summary of how to "faithfully" migrate instruments is presented followed by a section on qualitative and quantitative study designs used to evaluate measurement equivalence of the new and original modes of data collection. Finally, the report discusses a number of issues that must be taken into account when mixing modes is deemed necessary or unavoidable within or between trials, including considerations of the risk of mixing at different levels within a clinical trial program and mixing between different types of platforms. In the absence of documented evidence of measurement equivalence, it is strongly recommended that a quantitative equivalence study be conducted before mixing modes in a trial to ensure that sufficient equivalence can be demonstrated to have confidence in pooling PRO data collected by the different modes. However, we also strongly discourage the mixing of paper and electronic field-based instruments and suggest that mixing of electronic modes be considered for clinical trials and only after equivalence has been established. If proceeding with mixing modes, it is important to implement data collection carefully in the trial itself in a planned manner at the country level or higher and minimize ad hoc mixing by sites or individual subjects. Finally, when mixing occurs, it must be addressed in the statistical analysis plan for the trial and the ability to pool the data must be evaluated to then evaluate treatment effects with mixed modes data. A successful mixed modes trial requires a "faithful migration," measurement equivalence established between modes, and carefully planned implementation to minimize the risk of increased measurement error impacting the power of the trial to detect a treatment effect.
Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ePRO; electronic PRO; equivalence; mixed modes

Mesh:

Year:  2014        PMID: 25128043     DOI: 10.1016/j.jval.2014.06.005

Source DB:  PubMed          Journal:  Value Health        ISSN: 1098-3015            Impact factor:   5.725


  22 in total

1.  Constructing arguments for the interpretation and use of patient-reported outcome measures in research: an application of modern validity theory.

Authors:  Kevin P Weinfurt
Journal:  Qual Life Res       Date:  2021-02-25       Impact factor: 4.147

2.  Interactive Voice Response and Text-based Self-report Versions of the Electronic Columbia-Suicide Severity Rating Scale Are Equivalent.

Authors:  Chad Gwaltney; James C Mundt; John H Greist; Jean Paty; Brian Tiplady
Journal:  Innov Clin Neurosci       Date:  2017-04-01

3.  Clinical Outcome Assessments: Conceptual Foundation-Report of the ISPOR Clinical Outcomes Assessment - Emerging Good Practices for Outcomes Research Task Force.

Authors:  Marc K Walton; John H Powers; Jeremy Hobart; Donald Patrick; Patrick Marquis; Spiros Vamvakas; Maria Isaac; Elizabeth Molsen; Stefan Cano; Laurie B Burke
Journal:  Value Health       Date:  2015-08-24       Impact factor: 5.725

4.  Systematic collection of patient reported outcome research data: A checklist for clinical research professionals.

Authors:  Leslie Wehrlen; Mike Krumlauf; Elizabeth Ness; Damiana Maloof; Margaret Bevans
Journal:  Contemp Clin Trials       Date:  2016-03-19       Impact factor: 2.226

5.  Negligible Effects of the Survey Modes for Patient-Reported Outcomes: A Report From the Childhood Cancer Survivor Study.

Authors:  Jin-Ah Sim; Geehong Hyun; Todd M Gibson; Yutaka Yasui; Wendy Leisenring; Melissa M Hudson; Leslie L Robison; Gregory T Armstrong; Kevin R Krull; I-Chan Huang
Journal:  JCO Clin Cancer Inform       Date:  2020-01

6.  Methods for Implementing and Reporting Patient-reported Outcome (PRO) Measures of Symptomatic Adverse Events in Cancer Clinical Trials.

Authors:  Ethan Basch; Lauren J Rogak; Amylou C Dueck
Journal:  Clin Ther       Date:  2016-04-02       Impact factor: 3.393

Review 7.  SPIRIT-PRO Extension explanation and elaboration: guidelines for inclusion of patient-reported outcomes in protocols of clinical trials.

Authors:  Melanie Calvert; Madeleine King; Rebecca Mercieca-Bebber; Olalekan Aiyegbusi; Derek Kyte; Anita Slade; An-Wen Chan; E Basch; Jill Bell; Antonia Bennett; Vishal Bhatnagar; Jane Blazeby; Andrew Bottomley; Julia Brown; Michael Brundage; Lisa Campbell; Joseph C Cappelleri; Heather Draper; Amylou C Dueck; Carolyn Ells; Lori Frank; Robert M Golub; Ingolf Griebsch; Kirstie Haywood; Amanda Hunn; Bellinda King-Kallimanis; Laura Martin; Sandra Mitchell; Thomas Morel; Linda Nelson; Josephine Norquist; Daniel O'Connor; Michael Palmer; Donald Patrick; Gary Price; Antoine Regnault; Ameeta Retzer; Dennis Revicki; Jane Scott; Richard Stephens; Grace Turner; Antonia Valakas; Galina Velikova; Maria von Hildebrand; Anita Walker; Lari Wenzel
Journal:  BMJ Open       Date:  2021-06-30       Impact factor: 2.692

8.  Underreporting of Symptomatic Adverse Events in Phase I Clinical Trials.

Authors:  Zachary W Veitch; Daniel Shepshelovich; Christina Gallagher; Lisa Wang; Albiruni R Abdul Razak; Anna Spreafico; Philippe L Bedard; Lillian L Siu; Lori Minasian; Aaron R Hansen
Journal:  J Natl Cancer Inst       Date:  2021-08-02       Impact factor: 13.506

9.  Capturing Patient-Reported Outcome (PRO) Data Electronically: The Past, Present, and Promise of ePRO Measurement in Clinical Trials.

Authors:  Stephen Joel Coons; Sonya Eremenco; J Jason Lundy; Paul O'Donohoe; Hannah O'Gorman; William Malizia
Journal:  Patient       Date:  2015-08       Impact factor: 3.883

10.  Comparing the measurement equivalence of EQ-5D-5L across different modes of administration.

Authors:  Brendan Mulhern; Hannah O'Gorman; Neil Rotherham; John Brazier
Journal:  Health Qual Life Outcomes       Date:  2015-11-26       Impact factor: 3.186

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