Literature DB >> 28463151

Patient-Reported Outcomes After Radiation Therapy in Men With Prostate Cancer: A Systematic Review of Prognostic Tool Accuracy and Validity.

Michael E O'Callaghan1, Elspeth Raymond2, Jared M Campbell3, Andrew D Vincent4, Kerri Beckmann5, David Roder6, Sue Evans7, John McNeil7, Jeremy Millar8, John Zalcberg7, Martin Borg9, Kim Moretti10.   

Abstract

PURPOSE: To identify, through a systematic review, all validated tools used for the prediction of patient-reported outcome measures (PROMs) in patients being treated with radiation therapy for prostate cancer, and provide a comparative summary of accuracy and generalizability. METHODS AND MATERIALS: PubMed and EMBASE were searched from July 2007. Title/abstract screening, full text review, and critical appraisal were undertaken by 2 reviewers, whereas data extraction was performed by a single reviewer. Eligible articles had to provide a summary measure of accuracy and undertake internal or external validation. Tools were recommended for clinical implementation if they had been externally validated and found to have accuracy ≥70%.
RESULTS: The search strategy identified 3839 potential studies, of which 236 progressed to full text review and 22 were included. From these studies, 50 tools predicted gastrointestinal/rectal symptoms, 29 tools predicted genitourinary symptoms, 4 tools predicted erectile dysfunction, and no tools predicted quality of life. For patients treated with external beam radiation therapy, 3 tools could be recommended for the prediction of rectal toxicity, gastrointestinal toxicity, and erectile dysfunction. For patients treated with brachytherapy, 2 tools could be recommended for the prediction of urinary retention and erectile dysfunction.
CONCLUSIONS: A large number of tools for the prediction of PROMs in prostate cancer patients treated with radiation therapy have been developed. Only a small minority are accurate and have been shown to be generalizable through external validation. This review provides an accessible catalogue of tools that are ready for clinical implementation as well as which should be prioritized for validation.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28463151     DOI: 10.1016/j.ijrobp.2017.02.024

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  4 in total

Review 1.  Machine Learning and Radiogenomics: Lessons Learned and Future Directions.

Authors:  John Kang; Tiziana Rancati; Sangkyu Lee; Jung Hun Oh; Sarah L Kerns; Jacob G Scott; Russell Schwartz; Seyoung Kim; Barry S Rosenstein
Journal:  Front Oncol       Date:  2018-06-21       Impact factor: 6.244

2.  Electronic Patient-Reported Outcome Measures in Radiation Oncology: Initial Experience After Workflow Implementation.

Authors:  Franziska Hauth; Verena Bizu; Rehan App; Heinrich Lautenbacher; Alina Tenev; Michael Bitzer; Nisar Peter Malek; Daniel Zips; Cihan Gani
Journal:  JMIR Mhealth Uhealth       Date:  2019-07-24       Impact factor: 4.773

3.  A case-control study using motion-inclusive spatial dose-volume metrics to account for genito-urinary toxicity following high-precision radiotherapy for prostate cancer.

Authors:  Oscar Casares-Magaz; Ludvig P Muren; Niclas Pettersson; Maria Thor; Austin Hopper; Rick Knopp; Joseph O Deasy; Michael Væth; John Einck; Vitali Moiseenko
Journal:  Phys Imaging Radiat Oncol       Date:  2018-10-05

4.  Assessing concordance between patient-reported and investigator-reported CTCAE after proton beam therapy for prostate cancer.

Authors:  Roman O Kowalchuk; David Hillman; Thomas B Daniels; Carlos E Vargas; Jean-Claude M Rwigema; William W Wong; Bradley J Stish; Amylou C Dueck; Richard Choo
Journal:  Clin Transl Radiat Oncol       Date:  2021-09-15
  4 in total

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