Editorials

Prognostic factors in prostate cancer

BMJ 2001; 322 doi: https://doi.org/10.1136/bmj.322.7283.378 (Published 17 February 2001) Cite this as: BMJ 2001;322:378

Pathologists glean a wealth of clinical detail from the smallest piece of tissue

  1. Rodolfo Montironi, professor of pathology (r.montironi@popcsi.unian.it)
  1. Institute of Pathological Anatomy, University of Ancona School of Medicine, Regional Hospital, 60020 Torrette di Ancona, Italy

    Prostate cancer is a leading cause of morbidity and mortality in men, accounting for about 30% of all new cases of cancer and 14% of deaths from cancer. Despite considerable advances in our ability to detect and treat prostate cancer, there have been no significant corresponding decreases in morbidity and mortality.1 The two main issues for clinicians and pathologists involved in prostate cancer are early detection of the cancer and identifying the prognostic factors that predict outcome in individual patients.2

    Early detection of prostate cancer, preferably in the preinvasive phase (in lesions such as high grade prostatic intraepithelial neoplasia), is important if a treatment can be found that will arrest development of the cancer. Although a relatively new concept, chemoprevention is a promising strategy for preventing or arresting the development of prostate cancer and is most effective in the early stages of cancer formation, when reversibility may be feasible.3

    Much research effort has also gone into the prognostic factors that can predict outcome in individual patients with prostate cancer, and these were the subject of two recent international consensus conferences. 4 5 The goal is to tailor the therapeutic approach to the clinical, morphological, and molecular features of each patient. Many of the clinically important predictive factors in prostate cancer are still derived from a pathologist's examination of tissue specimens using light microscopy, but the challenge of assembling the information is such that the use of artificial neural networks is expected to improve accuracy in diagnosis, …

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