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Using data extracted from a radiotherapy record & verify system to infer outcomes of patients treated for radical brain cancer

Published online by Cambridge University Press:  24 May 2019

Martin Sykes Open the ORCID record for Martin Sykes [Opens in a new window]
Martin Sykes*
Affiliation:
Radiotherapy, Hull University Teaching Hospitals NHS Trust, Castle Road, Cottingham, East Riding of Yorkshire, England
*
Address for correspondence: Martin Sykes, Radiotherapy, Queens Centre, Castle Hill Hospital, Cottingham, HU16 5JQ, UK. Tel: 01482 461216. E-mail: [email protected]
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Abstract

Aim:

The aims of this study were to explore the outcome measures that can be recorded in a radiotherapy IT system and the extract mortality results for a group of patients receiving radical radiotherapy treatment for primary brain cancer.

Method:

Treatment mortality outcomes were extracted from a radiotherapy database and were compared to treatment technique used between 1 January 2011 and 31 December 2017. The patients selected received 1 course of radiotherapy of 60 Gray in 30 treatments (n = 270). These patients received either Conformal Radiotherapy (CRT) (n = 127) or Volumetric Modulated Arc Therapy (VMAT) (n = 143). Kaplan–Meier plots were generated for these two groups to assess the survival. The median survival was 20·1 months (95%CI = 16·8−23·4) and 14·0 months (95%CI = 11·1−16·5) for CRT and VMAT, respectively.

Discussion:

Surprisingly, the results of this data extraction demonstrated that CRT gave better survival for this group of patients, than VMAT. The reason for the difference in survival is unclear and more data are needed to explain the result.

Conclusion:

This demonstrates that not only that a radiotherapy database can be used to extract outcome measures but that it must be done to explore where a change in treatment delivery has been of benefit to the patients or not.

Keywords

Glioblastomainformaticsoutcomesradiotherapysurvival
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 19 , Issue 1 , March 2020 , pp. 4 - 9
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Copyright
© Cambridge University Press 2019 

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References

Cancer Research UK. Brain, other CNS and intracranial tumours incidence statistics Cancer Research UK. 2018. http://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/brain-other-cns-and-intracranial-tumours/incidence#heading-Four". Accessed on 19th May 2018.Google Scholar
Brodbelt, A, Greenberg, D, Winters, T, Williams, M, Vernon, S, Collins, V P. Glioblastoma in England: 2007–2011. Eur J Cancer 2015; 51: 533–542.CrossRefGoogle ScholarPubMed
Brada, M, Haylock, B. Is current technology improving outcomes with radiation therapy for gliomas? ASCO Edu Book 2014; 34: 89–94.Google Scholar
Wagner, D, Christiansen, H, Wolff, H, Vorwerk, H. Radiotherapy of malignant gliomas: comparison of volumetric single arc technique (RapidArc), dynamic intensity-modulated technique and 3D conformal technique. Radiot Oncol 2009; 93 (3): 593–596.Google Scholar
Gzell, C, Back, M, Wheeler, H, Bailey, D, Foote, M. Radiotherapy in Glioblastoma: the past, the present and the future. Clin Oncol 2017; 29 (1): 15–25.Google ScholarPubMed
Amelio, D, Lorentini, S, Schwarz, M, Amichetti, M. Intensity-modulated radiation therapy in newly diagnosed Glioblastoma: a systematic review on clinical and technical issues. Radiot Oncol 2010; 97 (3): 361–369.CrossRefGoogle ScholarPubMed
World Health Organisation. Classification of Diseases (ICD). https://www.who.int/classifications/icd/icdonlineversions/en/. Accessed on 15th April 2019.Google Scholar
Rich, J T, Neely, J G, Paniello, R C, Voelker, C C, Nussenbaum, B, Wang, E W. A practical guide to understanding Kaplan-Meier curves. Otolaryngol Head Neck Surg 2010; 143 (3): 331–336.Google ScholarPubMed
Stupp, R, Mason, W P, van den Bent, M J, et al. Radiotherapy plus concomitant and adjuvant temozolomide for Glioblastoma. New England J Med 2005; 352 (10): 987–996.Google ScholarPubMed
Oken, M, Creech, R, Tormey, D C, et al. Toxicity and response criteria of the eastern cooperative oncology group. Am J Clin Oncol 1982; 5: 649–655.CrossRefGoogle ScholarPubMed
Marks, L B, Yorke, E D, Jackson, A, et al. Use of normal tissue complication probability models in the clinic. Int J Radiat Oncol Biol Phys 2010; 76: S10–S19 (3 SUPPL.).CrossRefGoogle ScholarPubMed
The Royal College of Radiologists. Radiotherapy Dose- Fractionation. London: Royal College of Radiologists, 2016: 25–32.Google Scholar
Niyazi, M, Brada, M, Chalmers, A J, et al. ESTRO-ACROP guideline “target delineation of Glioblastomas”. Radiot Oncol 2016; 118 (1): 35–42.CrossRefGoogle Scholar