Quantitative biopsy pathology for the prediction of pathologically organ‐confined prostate carcinoma

Abstract

BACKGROUNDQuantitative biopsy pathology with prostate specific antigen significantly improves the prediction of pathologic stage in patients with clinically localized prostate carcinoma (PCa). The authors recently reported a computational model for predicting patient specific likelihood of organ confinement of PCa using biopsy pathology and clinical data. The current study validates the initial models and presents an new, improved tool for clinical decision making.METHODSThe authors assessed 10 biopsy pathologic parameters and 2 clinical parameters using data from two institutions. Of 1287 patients, 798 men had pathologically organ confined (OC) PCa, 282 men had nonorgan‐confined disease with capsular penetration (NOC‐CP) only, and 207 men showed seminal vesicle or lymph node invasion (NOC‐AD) after undergoing pelvic lymphadenectomy and radical prostatectomy. Patient input data were evaluated by ordinal logistic (OLOGIT) and neural network (NN) models; and the likelihood of developing OC, NOC‐CP, or NOC‐AD disease was calculated for the combined and separate data sets and was compared with the results from original presentation. In addition, a new two‐output model was constructed (OC/NOC‐CP vs. NOC‐AD).RESULTSThe three‐output OLOGIT and NN models predicted OC disease with 95.0% and 98.6% accuracy, respectively, for the combined data set and with 93.0% and 98.6% accuracy, respectively, on subset analysis. The combined accuracy for predicting OC, NOC‐CP, and NOC‐AD disease in the entire validation set was 66.7% for OLOGIT model and 66.0% for the NN model. The two‐output OLOGIT and NN models correctly predicted 94.9% and 100.0% of all OC/NOC‐CP disease, respectively.CONCLUSIONSBoth computation models predicted OC PCa with an accuracy of 93.0–98.6% when they were validated with two different data sets. The OLOGIT and NN‐based, two‐output model permitted an appropriate treatment decision for 85.2–90.2% of patients. These data support the use of quantitative pathology and clinical data‐based decision modeling to manage patients with clinically localized PCa. Cancer 2003;97:969–78. © 2003 American Cancer Society.DOI 10.1002/cncr.11153

Prediction of patient‐specific risk and percentile cohort risk of pathological stage outcome using continuous prostate‐specific antigen measurement, clinical stage and biopsy Gleason score

“…The ability to predict accurately the pathological stage of PCa before surgery allows for improved patient counselling, a more appropriate selection of treatment plan and risk stratification for novel clinical trials for those with more advanced disease. Our group and others have published algorithms and nomograms predicting the pathological stage of patients with localized PCa [4–13]. The Partin Tables were updated in 2007 to reflect stage migration and they continue to provide a clinically useful adjunct to predict the pathological stage of patients with PCa [7].…”

The Percent of Biopsy Cores Positive for Cancer Is a Predictor of Advanced Pathological Stage and Poor Clinical Outcomes in Patients Treated With Radical Prostatectomy

“…Several studies used the amount and distribution of Gleason grade 4 or 5 cancer in prostate biopsies to predict the risk of lymph node spread. 13,14 Furthermore, evaluating percent positive prostate biopsy cores has been shown to help predict the risk of PSA relapse 15 and time to PSA failure after radical prostatectomy. 16 To confirm these findings and further assess the hypothesis that a proportion of men with biologically aggressive clinically localized prostate cancer have higher percent PosBx we investigated the association of percent PosBx with prostate cancer features and outcomes in a large cohort of consecutive patients with clinically localized prostate cancer who underwent radical prostatectomy.…”

Tumour growth fraction measured by immunohistochemical staining of Ki67 is an independent prognostic factor in preoperative prostate biopsies with small‐volume or low‐grade prostate cancer

“…A most recent preoperative nomogram also considers the number of positive biopsy cores 6. Several authors investigated the association of quantitative pathology biopsy features with biochemical recurrence7, 8 and intraprostatic perineural invasion and total percentage of biopsy tissue with tumour (TPT) were suggested as independent predictors of either adverse pathological findings or PSA recurrence after definitive treatment 9, 10. Despite these promising data and tools, there is a need for additional pretherapeutic prognosticators to better stratify potentially life threatening from clinically less significant prostate cancers in individual patients 11, 12…”