Detection of Non-palpable Prostate Cancer. A Mathematical and Laboratory Model
Autor: | J. Wan, W. D. Belville, Hans Stricker, L. J. Ruddock |
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Rok vydání: | 1993 |
Předmět: |
Male
medicine.medical_specialty Biopsy Urology Disease Models Biological Asymptomatic Prostate cancer Bayes' theorem Prostate Humans Medicine Probability medicine.diagnostic_test business.industry Prostatic Neoplasms Conditional probability Cancer medicine.disease Surgery medicine.anatomical_structure Radiology medicine.symptom business |
Zdroj: | British Journal of Urology. 71:43-46 |
ISSN: | 1464-410X 0007-1331 |
DOI: | 10.1111/j.1464-410x.1993.tb15878.x |
Popis: | Summary-Prostate cancer is currently the most commonly diagnosed cancer among males in the United States. As technology improves and the search for this enigmatic condition intensifies, we are detecting greater numbers of non-palpable tumours. These tumours are generally treated aggressively, given the uncertainty of their behaviour, but this approach may be over-zealous for small volume disease. The likelihood of detecting any cancer volume can be derived from Bayes' theorem of conditional probability. A laboratory model using coloured clay was created to contrast tumour volumes of 2.5,5 and 20% (n = 75). Six random systematic biopsies were then taken from each model in a blind fashion; 36% of the 2.5%, 44% of the 5% and all of the 20% models had at least 1 positive biopsy. Twenty-two of the 25 models representing 20% tumour had 3 or more biopsy cores positive. These data suggest that low volume disease with low biological potential will be found by random biopsy as the mathematical probability predicts. The high incidence of occult prostate cancer in the older population makes this a worrying observation. Also, and perhaps more important, there is a direct correlation between the volume of disease and the number of positive biopsies. This correlation is easily seen in both models and may allow for an estimation of tumour volume. This ability to estimate tumour volume may be a useful clinical tool that helps to guide therapy and assess prognosis. |
Databáze: | OpenAIRE |
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