Literature DB >> 26718152

Evidence-based optimal number of radiotherapy fractions for cancer: A useful tool to estimate radiotherapy demand.

Karen Wong1, Geoff P Delaney2, Michael B Barton3.   

Abstract

BACKGROUND AND
PURPOSE: The recently updated optimal radiotherapy utilisation model estimated that 48.3% of all cancer patients should receive external beam radiotherapy at least once during their disease course. Adapting this model, we constructed an evidence-based model to estimate the optimal number of fractions for notifiable cancers in Australia to determine equipment and workload implications.
MATERIALS AND METHODS: The optimal number of fractions was calculated based on the frequency of specific clinical conditions where radiotherapy is indicated and the evidence-based recommended number of fractions for each condition. Sensitivity analysis was performed to assess the impact of variables on the model.
RESULTS: Of the 27 cancer sites, the optimal number of fractions for the first course of radiotherapy ranged from 0 to 23.3 per cancer patient, and 1.5 to 29.1 per treatment course. Brain, prostate and head and neck cancers had the highest average number of fractions per course. Overall, the optimal number of fractions was 9.4 per cancer patient (range 8.7-10.0) and 19.4 per course (range 18.0-20.7).
CONCLUSIONS: These results provide valuable data for radiotherapy services planning and comparison with actual practice. The model can be easily adapted by inserting population-specific epidemiological data thus making it applicable to other jurisdictions.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Cancer; Fractions; Optimal; Radiotherapy

Mesh:

Year:  2015        PMID: 26718152     DOI: 10.1016/j.radonc.2015.12.001

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  7 in total

Review 1.  Health services research in German radiation oncology: new opportunities to advance cancer care.

Authors:  Daniel Medenwald; Christian T Dietzel; Dirk Vordermark
Journal:  Strahlenther Onkol       Date:  2018-09-04       Impact factor: 3.621

Review 2.  What is the optimal radiotherapy utilization rate for lung cancer?-a systematic review.

Authors:  Wei Liu; Alissa Liu; Jessica Chan; R Gabriel Boldt; Pablo Munoz-Schuffenegger; Alexander V Louie
Journal:  Transl Lung Cancer Res       Date:  2019-09

3.  Variation in the use of radiotherapy fractionation for breast cancer: Survival outcome and cost implications.

Authors:  Vikneswary Batumalai; Geoff P Delaney; Joseph Descallar; Gabriel Gabriel; Karen Wong; Jesmin Shafiq; Michael Barton
Journal:  Radiother Oncol       Date:  2020-07-25       Impact factor: 6.280

4.  Clinical adoption patterns of 0.35 Tesla MR-guided radiation therapy in Europe and Asia.

Authors:  Berend J Slotman; Mary Ann Clark; Enis Özyar; Myungsoo Kim; Jun Itami; Agnès Tallet; Jürgen Debus; Raphael Pfeffer; PierCarlo Gentile; Yukihiro Hama; Nicolaus Andratschke; Olivier Riou; Philip Camilleri; Claus Belka; Magali Quivrin; BoKyong Kim; Anders Pedersen; Mette van Overeem Felter; Young Il Kim; Jin Ho Kim; Martin Fuss; Vincenzo Valentini
Journal:  Radiat Oncol       Date:  2022-08-22       Impact factor: 4.309

5.  A 13-gene expression-based radioresistance score highlights the heterogeneity in the response to radiation therapy across HPV-negative HNSCC molecular subtypes.

Authors:  Jean-Philippe Foy; Louis Bazire; Sandra Ortiz-Cuaran; Sophie Deneuve; Janice Kielbassa; Emilie Thomas; Alain Viari; Alain Puisieux; Patrick Goudot; Chloé Bertolus; Nicolas Foray; Youlia Kirova; Pierre Verrelle; Pierre Saintigny
Journal:  BMC Med       Date:  2017-09-01       Impact factor: 8.775

6.  Trends in radiotherapy inpatient admissions in Germany: a population-based study over a 10-year period.

Authors:  Daniel Medenwald; Rainer Fietkau; Gunther Klautke; Susan Langer; Florian Würschmidt; Dirk Vordermark
Journal:  Strahlenther Onkol       Date:  2021-09-03       Impact factor: 3.621

7.  Number of radiotherapy treatment machines in the population and cancer mortality: an ecological study.

Authors:  Daniel Medenwald; Dirk Vordermark; Christian T Dietzel
Journal:  Clin Epidemiol       Date:  2018-09-21       Impact factor: 4.790

  7 in total

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