Literature DB >> 22819439

Analyzing phase III studies in hospice/palliative care. a solution that sits between intention-to-treat and per protocol analyses: the palliative-modified ITT analysis.

David C Currow1, John L Plummer, Jean S Kutner, Greg P Samsa, Amy P Abernethy.   

Abstract

Intention-to-treat (ITT) analyses are the standard way to evaluate randomized controlled trials (RCTs) to minimize Type I errors related to differential rates of noncompletion from one study arm. People in palliative care often die sooner than predicted as a direct result of disease progression, some of whom will be participating in RCTs and who will, therefore, withdraw or die after randomization for reasons unrelated to the intervention. This proportion of withdrawals is statistically negligible in other clinical disciplines, but commonplace in hospice/palliative care, creating a systematic bias away from the true effect. ITT analyses in hospice/palliative care that deem all withdrawals to be treatment failures or that impute data from deteriorating participants systematically underestimate the benefits of interventions, reducing the power of these studies. Equally unacceptable would be a per protocol analysis that excludes all withdrawals after randomization as this will underestimate toxicity. A modified analytic approach is needed on a continuum between ITT and per protocol analyses. To address data after randomization where there is a high rate of withdrawals because of death or deterioration, criteria need to include being: 1) prespecified in the original protocol; 2) clinically absolutely the result of disease progression; 3) identified by the blinded Independent Data Monitoring Committee as being unrelated to the intervention(s); and 4) accounted for in the study's CONSORT diagram. Such data should not be included in the analysis of the primary outcome. This article aims to define a better way of balancing Type I and Type II errors in hospice/palliative care RCT analyses using the palliative-modified ITT analysis. Arguably, the palliative-modified ITT analysis should be the primary evaluation of hospice/palliative care Phase III studies but, as a minimum, should routinely be the key sensitivity analysis.
Copyright © 2012 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22819439     DOI: 10.1016/j.jpainsymman.2011.10.028

Source DB:  PubMed          Journal:  J Pain Symptom Manage        ISSN: 0885-3924            Impact factor:   3.612


  13 in total

Review 1.  Association Between Palliative Care and Patient and Caregiver Outcomes: A Systematic Review and Meta-analysis.

Authors:  Dio Kavalieratos; Jennifer Corbelli; Di Zhang; J Nicholas Dionne-Odom; Natalie C Ernecoff; Janel Hanmer; Zachariah P Hoydich; Dara Z Ikejiani; Michele Klein-Fedyshin; Camilla Zimmermann; Sally C Morton; Robert M Arnold; Lucas Heller; Yael Schenker
Journal:  JAMA       Date:  2016-11-22       Impact factor: 56.272

2.  A semiparametric joint model for terminal trend of quality of life and survival in palliative care research.

Authors:  Zhigang Li; H R Frost; Tor D Tosteson; Lihui Zhao; Lei Liu; Kathleen Lyons; Huaihou Chen; Bernard Cole; David Currow; Marie Bakitas
Journal:  Stat Med       Date:  2017-08-17       Impact factor: 2.373

Review 3.  Treating an established episode of delirium in palliative care: expert opinion and review of the current evidence base with recommendations for future development.

Authors:  Shirley H Bush; Salmaan Kanji; José L Pereira; Daniel H J Davis; David C Currow; David Meagher; Kiran Rabheru; David Wright; Eduardo Bruera; Michael Hartwick; Pierre R Gagnon; Bruno Gagnon; William Breitbart; Laura Regnier; Peter G Lawlor
Journal:  J Pain Symptom Manage       Date:  2014-01-28       Impact factor: 3.612

4.  Understanding Treatment Effect Terminology in Pain and Symptom Management Research.

Authors:  Melissa M Garrido; Bryan Dowd; Paul L Hebert; Matthew L Maciejewski
Journal:  J Pain Symptom Manage       Date:  2016-05-21       Impact factor: 3.612

Review 5.  Considerations in reporting palliative care clinical trials: standardizing information reported and authorship practices.

Authors:  Thomas W LeBlanc; Amy P Abernethy; David C Currow; Jean S Kutner
Journal:  Curr Opin Support Palliat Care       Date:  2012-12       Impact factor: 2.302

6.  Caregiver-guided pain coping skills training for patients with advanced cancer: Results from a randomized clinical trial.

Authors:  Laura S Porter; Jennifer L Steel; Diane L Fairclough; Thomas W LeBlanc; Janet Bull; Laura C Hanson; Stacy Fischer; Francis J Keefe
Journal:  Palliat Med       Date:  2021-03-29       Impact factor: 4.762

7.  Effects of a Self-Monitoring Quality of Life Intervention in Outpatients with Breast Cancer: A Preliminary Report of A Randomized Controlled Trial.

Authors:  Ayako Matsuda; Kenichi Inoue; Manami Momiyama; Kobayashi Kunihiko; Kaoru Kubota; Soerindra S R S Ramai; Maarten J Fischer; Judith R Kroep; Adrian A Kaptein; Kazue Yamaoka
Journal:  Asian Pac J Cancer Prev       Date:  2022-01-01

8.  The impact of the carer support needs assessment tool (CSNAT) in community palliative care using a stepped wedge cluster trial.

Authors:  Samar M Aoun; Gunn Grande; Denise Howting; Kathleen Deas; Chris Toye; Lakkhina Troeung; Kelli Stajduhar; Gail Ewing
Journal:  PLoS One       Date:  2015-04-07       Impact factor: 3.240

Review 9.  Missing data in randomized controlled trials testing palliative interventions pose a significant risk of bias and loss of power: a systematic review and meta-analyses.

Authors:  Jamilla A Hussain; Ian R White; Dean Langan; Miriam J Johnson; David C Currow; David J Torgerson; Martin Bland
Journal:  J Clin Epidemiol       Date:  2015-12-21       Impact factor: 6.437

10.  Data analysis methods for assessing palliative care interventions in one-group pre-post studies.

Authors:  Takeshi Ioroi; Tatsuyuki Kakuma; Akihiro Sakashita; Yuki Miki; Kanako Ohtagaki; Yuka Fujiwara; Yuko Utsubo; Yoshihiro Nishimura; Midori Hirai
Journal:  SAGE Open Med       Date:  2015-11-15
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