An evidence-based estimate of appropriate radiotherapy utilization rate for breast cancer.
OBJECTIVE
Current estimates of the proportion of cancer patients who will require radiotherapy (RT) are based almost entirely on expert opinion. We sought to use an evidence-based approach to estimate the proportion of incident cases of breast cancer that will require RT at any point in the evolution of the illness.


METHODS
We undertook a systematic review of the literature to identify indications for RT for breast cancer and to ascertain the level of evidence that supported each indication. An epidemiologic approach was then used to estimate the incidence of each indication for RT in a typical North American population of breast cancer patients. The effect of sampling error on the estimated appropriate rate of RT was calculated mathematically, and the effect of systematic error was estimated by sensitivity analysis.


RESULTS
It was estimated that 66.4% +/- 4.8% of breast cancer patients develop one or more indications for RT at some point in the course of the illness. The plausible range for this rate was 56.3%-72.4% on sensitivity analysis. Of all breast cancer patients, 57.3% +/- 4.7% require RT in their initial treatment and 9.1% +/- 1.0% do so later for recurrence or progression. The proportion of patients who ever require RT is stage dependent: 39.8% +/- 1.1% in ductal carcinoma in situ; 68.6% +/- 4.1% in Stage I invasive carcinoma; 81.5% +/- 2.3% in Stage II; 95.3% +/- 0.3% in Stage III; and 63.7% +/- 0.3% in Stage IV.


CONCLUSIONS
This method provides a rational starting point for the long-term planning of RT services and for the audit of access to RT at the population level. By completing such evaluations in the major cancer sites, it will be possible to estimate the appropriate RT treatment rate for the cancer population as a whole.
Foroudi
Farshad
F
Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute and Kingston Regional Cancer Centre, Kingston, Ontario, Canada.
Tyldesley
Scott
S
Walker
Hugh
H
Mackillop
William J
WJ
D000465:Algorithms; D001943:Breast Neoplasms / Q000453:epidemiology* / Q000532:radiotherapy*; D002277:Carcinoma / Q000532:radiotherapy*; D005260:Female; D006801:Humans; D011878:Radiotherapy / Q000379:methods* / Q000706:statistics & numerical data*; D012307:Risk Factors; D012680:Sensitivity and Specificity