Leslie A. Mangold

Risk of Prostate Cancer–Specific Mortality Following Biochemical Recurrence After Radical Prostatectomy

ContextThe natural history of biochemical recurrence after radical prostatectomy can be long but variable. Better risk assessment models are needed to identify men who are at high risk for prostate cancer death early and who may benefit from aggressive salvage treatment and to identify men who are at low risk for prostate cancer death and can be safely observed.ObjectivesTo define risk factors for prostate cancer death following radical prostatectomy and to develop tables to risk stratify for prostate cancer–specific survival.Design, Setting, and PatientsRetrospective cohort study of 379 men who had undergone radical prostatectomy at an urban tertiary care hospital between 1982 and 2000 and who had a biochemical recurrence and after biochemical failure had at least 2 prostate-specific antigen (PSA) values at least 3 months apart in order to calculate PSA doubling time (PSADT). The mean (SD) follow-up after surgery was 10.3 (4.7) years and median follow-up was 10 years (range, 1-20 years).Main Outcome MeasureProstate cancer–specific mortality.ResultsMedian survival had not been reached after 16 years of follow-up after biochemical recurrence. Prostate-specific doubling time (<3.0 vs 3.0-8.9 vs 9.0-14.9 vs ≥15.0 months), pathological Gleason score (≤7 vs 8-10), and time from surgery to biochemical recurrence (≤3 vs >3 years) were all significant risk factors for time to prostate-specific mortality. Using these 3 variables, tables were constructed to estimate the risk of prostate cancer–specific survival at year 15 after biochemical recurrence.ConclusionClinical parameters (PSADT, pathological Gleason score, and time from surgery to biochemical recurrence) can help risk stratify patients for prostate cancer–specific mortality following biochemical recurrence after radical prostatectomy. These preliminary findings may serve as useful guides to patients and their physicians to identify patients at high risk for prostate cancer–specific mortality following biochemical recurrence after radical prostatectomy to enroll them in early aggressive treatment trials. In addition, these preliminary findings highlight that survival in low-risk patients can be quite prolonged.

Characteristics of insignificant clinical T1c prostate tumors: A contemporary analysis

The authors examined the cases of men who had undergone radical prostatectomy for low‐volume clinical T1c prostate carcinoma that was judged to be ‘insignificant’ on the basis of previously established preoperative clinicopathologic parameters. Pathologic findings subsequently were analyzed for correlations with extent of disease in an attempt to validate the contemporary usefulness of existing parameters for predicting the ‘significance’ of prostate tumors.

Preoperative Serum DNA GSTP1 CpG Island Hypermethylation and the Risk of Early Prostate-Specific Antigen Recurrence Following Radical Prostatectomy

Purpose: Hypermethylation of the CpG island at the promoter region of the π-class glutathione S-transferase gene (GSTP1) is the most common somatic genome abnormality in human prostate cancer. We evaluated circulating cell-free DNA GSTP1 CpG island hypermethylation as a prognostic biomarker in the serum of men with prostate cancer. Experimental Design: Prostate cancer DNA GSTP1 CpG island hypermethylation was detected using a restriction endonuclease quantitative PCR technique. We analyzed preoperative serum from 85 men with clinically localized prostate cancer treated with radical prostatectomy and from 35 men with a negative prostate biopsy. We then assayed preoperative serum from a data set of 55 pairs of men with clinically localized prostate cancer treated with radical prostatectomy, matched for Gleason score, comprising 55 men suffering prostate-specific antigen (PSA) recurrence (median, 2 years) and 55 men who were free of disease at last follow-up (median, 3 years). The association of serum GSTP1 CpG island hypermethylation and PSA recurrence was determined. Results: Circulating cell-free DNA with GSTP1 CpG island hypermethylation was not detected in the serum of men with a negative prostate biopsy but was detected in 12% of men with clinically localized disease and 28% of men with metastatic cancer (P = 0.003). In the matched data set, eight men (15%) who developed PSA recurrence were positive for DNA with GSTP1 CpG hypermethylation, whereas no patient who was free of disease was positive for GSTP1 CpG island hypermethylation (McNemar test, χ2 = 6.1, P = 0.01). In a multivariable analysis that accounted for recognized prognostic factors, the presence of serum DNA with GTSP1 CpG island hypermethylation was the most significant predictor of PSA recurrence (hazard ratio, 4.4; 95% confidence interval, 2.2, 8.8; P < 0.001). Conclusion: Our study suggests that GSTP1 CpG island hypermethylation may be an important DNA-based prognostic serum biomarker for prostate cancer.

Death in Patients With Recurrent Prostate Cancer After Radical Prostatectomy: Prostate-Specific Antigen Doubling Time Subgroups and Their Associated Contributions to All-Cause Mortality

PURPOSE Among patients with biochemical recurrence after radical prostatectomy, we found previously that postoperative prostate-specific antigen doubling time (PSADT) was associated with risk of prostate cancer death. However, given the small number of patients in the highest risk PSADT subgroup, it is unclear which PSADT subgroups contribute the greatest to prostate cancer-specific death and how this influences all-cause mortality. PATIENTS AND METHODS This study was a retrospective analysis of 379 patients treated with radical prostatectomy between 1982 and 2000 who had a biochemical recurrence and PSADT data available. Mean and median follow-up after surgery was 11.4 (standard deviation, 5.4) and 11.0 years, respectively (range, 1.6 to 23.0 years). RESULTS Shorter PSADT was significantly associated with prostate cancer-specific and all-cause mortality (P < .001). Although patients with a PSADT less than 3 months were at the greatest risk of death, because of the limited number of patients in this group, they accounted for only 13% of prostate cancer deaths at 15 years after biochemical recurrence, whereas patients with an intermediate PSADT (3.0 to 8.9 months) accounted for 58% of all prostate cancer deaths. Among patients with a PSADT less than 15 months, prostate cancer accounted for 90% of all deaths. Only patients in the slowest PSADT subgroup (> or = 15 months) had a greater risk of competing-causes mortality compared with that from prostate cancer. CONCLUSION Among a select cohort of young, healthy patients with PSA recurrence after radical prostatectomy and a PSADT less than 15 months, prostate cancer accounted for an estimated 90% of all deaths by 15 years after recurrence. The majority of prostate cancer deaths occurred among patients with an intermediate PSADT (3.0 to 8.9 months).

Radical prostatectomy for clinical stage T3a disease.

Men with clinical stage T3a disease are at high risk and are often encouraged to undergo radiation therapy with concomitant hormonal therapy. The long‐term outcomes among men treated with radical prostatectomy for clinical stage T3a disease were examined.

Proenzyme psa for the early detection of prostate cancer in the 2.5-4.0 ng/ml total psa range: preliminary analysis.

OBJECTIVES To determine the clinical utility of using proenzyme prostate-specific antigen (pPSA) for early detection of prostate cancer in the 2.5 to 4.0 ng/mL total PSA range. pPSA, the precursor form of PSA that contains a 7 amino acid leader peptide, and truncated forms such as [-2]pPSA and [-4]pPSA can be measured in serum by research immunoassay. METHODS Archival serum from 119 men (noncancer, 88; cancer, 31), obtained before biopsy and in the total PSA range of 2.5 to 4.0 ng/mL, were assayed for total PSA, free PSA (fPSA), and pPSA. pPSA was defined as the sum of the [-2], [-4], and [-7] forms, and the percent pPSA (%pPSA) was defined as pPSA/fPSA. RESULTS pPSA averaged 4.6% +/- 0.4% (SEM) of total PSA and 39.3% +/- 3.5% of fPSA. PSA and %fPSA values were similar between the noncancer and cancer groups, and %pPSA tended to be higher in the cancer group (50.1% +/- 4.4%) compared with the noncancer group (35.5% +/- 6.7%; P = 0.07). Using receiver operating characteristic analysis to assess clinical utility, the area under the curve for %pPSA was 0.688 compared with 0.567 for %fPSA. At a fixed sensitivity of 75%, the specificity was significantly greater for %pPSA at 59% compared with %fPSA at 33% (P <0.0001). CONCLUSIONS In the 2.5 to 4.0 ng/mL total PSA range, 75% of cancers can potentially be detected with 59% of unnecessary biopsies being spared using %pPSA; use of %fPSA would result in sparing only 33% of unnecessary biopsies. A large prospective clinical trial is needed to confirm these preliminary findings.

Clinical and Pathologic Outcome After Radical Prostatectomy for Prostate Cancer Patients With a Preoperative Gleason Sum of 8 to 10

Men with a biopsy Gleason sum of 8 to 10 are considered high‐risk. The current study sought to identify whether there was a subset of men with high biopsy Gleason sums who would have a good pathologic and biochemical outcome with surgical monotherapy. To increase the generalizability of the findings, data were used from patients treated at 2 very different practice settings: a tertiary care referral center (Johns Hopkins Hospital) and multiple equal‐access medical centers (Shared Equal Access Regional Cancer Hospital [SEARCH] Database).

GENETICALLY ENGINEERED NEURAL NETWORKS FOR PREDICTING PROSTATE CANCER PROGRESSION AFTER RADICAL PROSTATECTOMY

OBJECTIVES To use pathologic, morphometric, DNA ploidy, and clinical data to develop and test a genetically engineered neural network (GENN) for the prediction of biochemical (prostate-specific antigen [PSA]) progression after radical prostatectomy in a select group of men with clinically localized prostate cancer. METHODS Two hundred fourteen men who underwent anatomic radical retropubic prostatectomy for clinically localized prostate cancer were selected on the basis of adequate follow-up, pathologic criteria indicating an intermediate risk of progression, and availability of archival tissue. The median age was 58.9 years (range 40 to 87). Men with Gleason score 5 to 7 and clinical Stage T1b-T2c tumors were included. Follow-up was a median of 9.5 years. Three GENNs were developed using pathologic findings (Gleason score, extraprostatic extension, surgical margin status), age, quantitative nuclear grade (QNG), and DNA ploidy. These networks were developed using three randomly selected training (n = 136) and testing (n = 35) sets. Different variable subsets were compared for the ability to maximize prediction of progression. Both standard logistic regression and Cox regression analyses were used concurrently to calculate progression risk. RESULTS Biochemical (PSA) progression occurred in 84 men (40%), with a median time to progression of 48 months (range 1 to 168). GENN models were trained using inputs consisting of (a) pathologic features and patient age; (b) QNG and DNA ploidy; and (c) all variables combined. These GENN models achieved an average accuracy of 74.4%, 63.1 %, and 73.5%, respectively, for the prediction of progression in the training sets. In the testing sets, the three GENN models had an accuracy of 74.3%, 80.0%, and 78.1%, respectively. CONCLUSIONS The GENN models developed show promise in predicting progression in select groups of men after radical prostatectomy. Neural networks using QNG and DNA ploidy as input variables performed as well as networks using Gleason score and staging information. All GENN models were superior to logistic regression modeling and to Cox regression analysis in prediction of PSA progression. The development of models using improved input variables and imaging systems in larger, well-characterized patient groups with long-term follow-up is ongoing.

Probability of biochemical recurrence by analysis of pathologic stage, gleason score, and margin status for localized prostate cancer

OBJECTIVES The Partin tables provide pretreatment information regarding the probability of various pathologic stages (eg, organ confined, extraprostatic extension, and seminal vesicle or lymph node involvement). Although the pathologic stage serves as an excellent surrogate for outcome after radical prostatectomy (RRP), many patients and physicians want to know how the predictions made from the Partin tables can be translated into long-term biochemical recurrence-free survival. In this work, we go beyond the pathologic outcomes predicted by the Partin nomograms to provide long-term biochemical recurrence-free estimates on the basis of the pathologic data obtained at RRP to help counsel patients after surgery for prostate cancer. METHODS The study group comprised 1955 men treated by one surgeon with RRP and pelvic lymph node dissection for clinically localized disease (1989 to 2001). The patients were followed up for at least 1 year postoperatively, and the disease-free survival rates were determined using Kaplan-Meier analysis. RESULTS The pathologic stages were as follows: organ confined in 57%, extraprostatic extension in 35%, seminal vesicle involvement in 4%, and lymph node involvement in 4%. The prostatectomy Gleason score distribution was as follows: 2 to 4 in 1%, 5 to 6 in 63%, 7 in 30%, and 8 to 10 in 6%. Overall, a positive surgical margin was present in 9.8%. On the basis of the prostatectomy Gleason score, pathologic stage, and surgical margin status, the probability of long-term biochemical recurrence-free survival was divided into four groups: excellent, good, moderate, and low. CONCLUSIONS These simple to use and explain risk groups can be used to predict long-term biochemical recurrence-free survival from pathologic stage data obtained at surgery or predicted from the Partin tables, along with surgical margin status and Gleason score information obtained at RRP.

Evaluation of GSTP1 and APC methylation as indicators for repeat biopsy in a high-risk cohort of men with negative initial prostate biopsies

Study Type – Diagnostic (exploratory cohort)