PREDICTION OF PATHOLOGICAL STAGE IN PATIENTS WITH CLINICAL STAGE T1C PROSTATE CANCER: THE NEW CHALLENGE ROBERT W. VELTRI,*,† M. CRAIG MILLER,† LESLIE A. MANGOLD, GERARD J. O’DOWD,† JONATHAN I. EPSTEIN AND ALAN W. PARTIN‡ From The Brady Urological Institute of The Johns Hopkins Medical Institutions, Baltimore, Maryland, Immunicon Corp., Huntingdon Valley, Pennsylvania, and UroCor, Inc., Oklahoma City, Oklahoma ABSTRACT Purpose: We developed an algorithm for predicting the likelihood of organ confined disease in patients with clinical stage T1c prostate cancer using biopsy pathology, computer assisted image analysis and serum prostate specific antigen (PSA). Materials and Methods: Of the 557 consecutive men enrolled in this study between October 1998 and January 2000 scheduled for radical prostatectomy at a single institution 386 (69%) presented with clinical stage T1c disease. Study exclusion criteria included neoadjuvant hor- monal treatment with luteinizing hormone-releasing hormone, antiandrogen or 5-reductase inhibitors. Preoperative serum, biopsy histology slides, clinical demographic information, pros- tatectomy pathology and prostate weight data were obtained. Biomarkers assessed included total PSA, complexed PSA, free PSA, the free-to-total PSA ratio, quantitative nuclear grade deter- mined by image analysis, complexed PSA density, and biopsy Gleason grade and score. To determine patient specific quantitative nuclear grade values, images from approximately 125 cancer nuclei were captured per patient from the area of the biopsy section with the highest Gleason score. The variance in 60 nuclear size, shape and chromatin texture descriptors was calculated for each gallery of nuclei. Logistic regression was done to determine the most accurate combination of variables for predicting organ confined prostate cancer. Results: Complete results and data were available on 255 of the 386 men (66%) with an average age plus or minus standard deviation of 58.8  6 years who had stage T1c disease, including 49 (19%) with pathologically nonorgan confined disease. Logistic regression analysis revealed that quantitative nuclear grade, biopsy Gleason score, total PSA, the calculated free-to-total PSA ratio, complexed PSA and complexed PSA density were univariately significant for predicting organ confined disease (p 0.05). On backward stepwise logistic regression only quantitative nuclear grade, complexed PSA density and Gleason score remained in a model yielding an area under the receiver operating characteristics curve of 82.4%. Conclusions: The quantitative nuclear grade biomarker was the strongest independent pre- dictor of pathological stage in men with clinical stage T1c prostate cancer when combined with biopsy Gleason score and complexed PSA density data. KEY WORDS: prostate; prostatic neoplasms; prostate-specific antigen; tumor markers; biological; neoplasm staging Prostate cancer is the most common malignancy in men in the United States. In 2000 it caused an estimated 180,400 new cases and 31,900 deaths. 1 Approximately 30% of men who are treated for localized disease have recurrence and a subset of these men may have progressive disease. 1–4 Clini- cal staging of prostate cancer continues to depend on serum prostate-specific antigen (PSA) molecular forms and digital rectal examination. About 90% to 95% of patients diagnosed early with organ confined tumors are curable with radical prostatectomy, 2, 4 while about 85% to 95% are curable with radiation therapy. 5 Today approximately 25% to 40% of patients diagnosed with clinical stage T1c disease have advanced pathology findings (grade and/or stage) at radical prostatectomy. 6–8 The mech- anisms of disease development, growth and progression likely involve multiple genetic and/or epigenetic factors that contribute to the biological heterogeneity of prostate cancer, and the variability in the rate of progression and disease- specific mortality. 9 –12 Such large-scale genomic alterations in prostate tumor cells are reflected by gross changes in the amount and organization of DNA (chromatin) in individual tumor cells that can often be detected by microscopy and quantified by image analysis. 12–17 Some nuclear structural alterations can be quantified using nuclear morphometric descriptors. These mathematical calculations measure sev- eral nuclear size, shape, DNA content and chromatin distri- bution features (such as Markovian and nonMarkovian de- rived texture features), and are used to develop patient specific quantitative nuclear grade value for disease outcome predictions. 13–17 We evaluated the quantitative nuclear grade image analysis biomarker combined with other clini- cal, pathological and PSA parameters in biopsy cases of clin- ical stage T1c disease to predict pathological stage in a con- temporary sample. MATERIALS AND METHODS Patient sample. Of the 557 patients enrolled in a 2 1 /2 year prospective prostate cancer study 255 with clinical stage T1c Accepted for publication February 1, 2002. Supported by UroCor, Inc., Department of Defense Grant DAMD17-98-1-8468 and the David Koch Research Foundation. * Requests for reprints: The Brady Urological Institute, The Johns Hopkins Hospital, 600 North Wolfe St., Baltimore, Maryland 21287- 2101. † Financial interest and/or other relationship with UroCor. ‡ Financial interest and/or other relationship with Bayer and UroCor. 0022-5347/02/1681-0100/0 THE JOURNAL OF UROLOGY ® Vol. 168, 100 –104, July 2002 Copyright © 2002 by AMERICAN UROLOGICAL ASSOCIATION,INC. ® Printed in U.S.A. 100