Veltri1998 - Abstract
The focus of this review is to survey pretreatment biopsy and patient-derived information applicable to predicting pathological stage and prognosis of men with a diagnosis of prostate cancer. Various sources of clinical and pathological information that may contribute to building decision support tools (DSTs) for application by the urologist to manage prostate cancer patients are presented. These DSTs use serum biomarkers and objective, well-established, pathology information extracted by experienced pathologists from needle-core tissue samples that describe tumor size, grade, and location. Other valuable data can be derived from the biopsy tissue, such as computer-assisted image cytometry-derived DNA ploidy and nuclear morphometry informatics, as well as select tissue biomarker results that may provide supplemental prognostic information. Also discussed are the technical and clinical limitations of these DSTs with respect to the prediction accuracy. A commercially available pretreatment prediction algorithm (UroScore, Oklahoma City, OK) was applied to predict the disease organ confinement status of the prostate cancer test case. Finally, the authors present existing and future applications of computer-derived computational solutions for incorporating all patient history, clinical laboratory, and pathology information into algorithms that can generate patient-specific predictive probability estimates of stage, recurrence, and progression.
Veltri, R.W.; O'Dowd, G.J.; Orozco, R.; Miller, M.C. The role of biopsy pathology, quantitative nuclear morphometry, and biomarkers in the preoperative prediction of prostate cancer staging and prognosis. Semin Urol Oncol., 1998 Aug; 16(3):106-117.