• Login
    View Item 
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of ChristieCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsThis CollectionTitleAuthorsIssue DateSubmit DateSubjects

    My Account

    LoginRegister

    Local Links

    The Christie WebsiteChristie Library and Knowledge Service

    Statistics

    Display statistics

    Normal Tissue Complication Probability Modelling for Toxicity Prediction and Patient Selection in Proton Beam Therapy to the Central Nervous System: A Literature Review

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Authors
    Gaito, S.
    Burnet, N.
    Aznar, M.
    Crellin, A.
    Indelicato, D. J.
    Ingram, S.
    Pan, S.
    Price, G.
    Hwang, E.
    France, A.
    Smith, E.
    Whitfield, G.
    Show allShow less
    Affiliation
    Proton Clinical Outcomes Unit, The Christie NHS Foundation Trust, Manchester, UK; Division of Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK. Electronic address: Simona.gaito@nhs.net. Clinical Oncology, Proton Beam Therapy Centre, The Christie NHS Foundation Trust, Manchester, UK. Division of Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; Department of Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, UK. Division of Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; NHS England National Clinical Lead Proton Beam Therapy, UK. University of Florida Department of Radiation Oncology, Jacksonville, Florida, USA. Division of Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK. Department of Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, UK. Clinical Oncology, Proton Beam Therapy Centre, The Christie NHS Foundation Trust, Manchester, UK; Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia. Proton Clinical Outcomes Unit, The Christie NHS Foundation Trust, Manchester, UK. Proton Clinical Outcomes Unit, The Christie NHS Foundation Trust, Manchester, UK; Division of Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; Clinical Oncology, Proton Beam Therapy Centre, The Christie NHS Foundation Trust, Manchester, UK. Division of Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK; Clinical Oncology, Proton Beam Therapy Centre, The Christie NHS Foundation Trust, Manchester, UK.
    Issue Date
    2022
    
    Metadata
    Show full item record
    Abstract
    Normal tissue complication probability (NTCP) models can guide clinical decision making in radiotherapy. In recent years, they have been used for patient selection for proton beam therapy (PBT) for some anatomical tumour sites. This review synthesizes the published evidence regarding the use of NTCP models to predict the toxicity of PBT, for different end points in patients with brain tumours. A search of Medline and Embase using the Patients, Intervention, Comparison, Outcome (PICO) criteria was undertaken. In total, 37 articles were deemed relevant and were reviewed in detail. Nineteen articles on NTCP modelling of toxicity end points were included. Of these, 11 were comparative NTCP studies of PBT versus conventional photon radiotherapy (XRT), which evaluated differences in plan dosimetry and then assumed that XRT-derived literature estimates of NTCP would be applicable to both. Seven papers derived NTCP models based on PBT outcome data, two of which provided model parameters. Among analysed end points, the reduced risk of secondary tumours with PBT as compared with XRT is estimated – through modelling studies – to be considerable and was highlighted by most authors. For other analysed end points, the clinical benefit of PBT mainly depends on tumour location in relation to organs at risk as well as prescription doses. NTCP models can be useful tools for treatment plan comparison. However, most published toxicity data were derived from XRT cohorts; this review has highlighted the need for further studies relating dose-volume parameters to observed toxicity in PBT-treated patients. Specifically, there is a need for PBT-specific NTCP models that can be implemented in the clinical practice. NTCP models built on robust clinical data for the most common radiotherapy toxicities in the brain would potentially redefine the current indications for PBT.
    Citation
    Gaito S, Burnet N, Aznar M, Crellin A, Indelicato DJ, Ingram S, et al. Normal Tissue Complication Probability Modelling for Toxicity Prediction and Patient Selection in Proton Beam Therapy to the Central Nervous System: A Literature Review. Clinical Oncology. Elsevier BV; 2022.
    Journal
    Clin Oncol (R Coll Radiol)
    URI
    http://hdl.handle.net/10541/625074
    DOI
    10.1016/j.clon.2021.12.015
    PubMed ID
    35042622
    Additional Links
    https://dx.doi.org/10.1016/j.clon.2021.12.015
    Type
    Other
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.clon.2021.12.015
    Scopus Count
    Collections
    All Christie Publications

    entitlement

    Related articles

    • Identification of patient benefit from proton beam therapy in brain tumour patients based on dosimetric and NTCP analyses.
    • Authors: Dutz A, Lühr A, Troost EGC, Agolli L, Bütof R, Valentini C, Baumann M, Vermeren X, Geismar D, Timmermann B, Krause M, Löck S
    • Issue date: 2021 Jul
    • Assessing the uncertainty in a normal tissue complication probability difference (∆NTCP): radiation-induced liver disease (RILD) in liver tumour patients treated with proton vs X-ray therapy.
    • Authors: Kobashi K, Prayongrat A, Kimoto T, Toramatsu C, Dekura Y, Katoh N, Shimizu S, Ito YM, Shirato H
    • Issue date: 2018 Mar 1
    • A Model-Based Approach to Predict Short-Term Toxicity Benefits With Proton Therapy for Oropharyngeal Cancer.
    • Authors: Rwigema JM, Langendijk JA, Paul van der Laan H, Lukens JN, Swisher-McClure SD, Lin A
    • Issue date: 2019 Jul 1
    • Toward a model-based patient selection strategy for proton therapy: External validation of photon-derived normal tissue complication probability models in a head and neck proton therapy cohort.
    • Authors: Blanchard P, Wong AJ, Gunn GB, Garden AS, Mohamed ASR, Rosenthal DI, Crutison J, Wu R, Zhang X, Zhu XR, Mohan R, Amin MV, Fuller CD, Frank SJ
    • Issue date: 2016 Dec
    • A study on predicting cases that would benefit from proton beam therapy in primary liver tumors of less than or equal to 5 cm based on the estimated incidence of hepatic toxicity.
    • Authors: Uchinami Y, Katoh N, Suzuki R, Kanehira T, Tamura M, Takao S, Matsuura T, Miyamoto N, Fujita Y, Koizumi F, Taguchi H, Yasuda K, Nishioka K, Yokota I, Kobashi K, Aoyama H
    • Issue date: 2022 Jul
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.