The effects of delays in radiotherapy treatment on tumour control.
There is often a considerable delay from initial tumour diagnosis to the start of radiotherapy treatment, which may be due to factors such as waiting lists and referral delays. This paper uses widely published models and clinical parameters to calculate the effect of delays in treatment on local tumour control for four different types of tumour-squamous cell carcinoma (head and neck), breast, cervix and prostate. The Poisson model for tumour control probability (TCP), an exponential function for tumour growth and the linear quadratic model of cell kill are used to calculate the change in TCP for delays between diagnosis and treatment of up to 100 days. Typical values of the clinical parameters have been taken from the literature; these include alpha and beta, sigma(alpha), tumour size at diagnosis, pre-treatment doubling time, delay in onset of accelerated repopulation and doubling time during treatment. It is acknowledged that there are limitations in the reliability of these data for predicting absolute values of tumour control, but models are still useful for predicting how changes in treatment parameters are likely to affect the outcome. It is shown that for fast-growing tumours a delay of 1-2 months can have a significant adverse effect on the outcome, whereas for slow-growing tumours such as Ca prostate a delay of a few months does not significantly reduce the probability of tumour control. These calculations show the importance of ensuring that delays from diagnosis through to treatment are minimized, especially for patients with rapidly proliferating tumours.
Wyatt
R M
RM
Department of Radiotherapy Physics, Queen Elizabeth Hospital, Edgbaston, Birmingham B15 2TH, UK.
Beddoe
A H
AH
Dale
R G
RG
D001071:Appointments and Schedules; D001943:Breast Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000532:radiotherapy; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis / Q000401:mortality / Q000532:radiotherapy; D004307:Dose-Response Relationship, Radiation; D005260:Female; D006258:Head and Neck Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000532:radiotherapy; D006801:Humans; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D009369:Neoplasms / Q000175:diagnosis / Q000401:mortality* / Q000532:radiotherapy*; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000532:radiotherapy; D011874:Radiometry / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D018570:Risk Assessment / Q000379:methods*; D016019:Survival Analysis; D013997:Time Factors; D016896:Treatment Outcome; D006113:United Kingdom / Q000453:epidemiology; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000532:radiotherapy; D014850:Waiting Lists