Matthew R. Cooperberg

PSA screening: determinants of primary-care physician practice patterns

Background:The effect of practice guidelines and the European Randomised Screening for Prostate Cancer (ERSPC) and Prostate, Lung, Colorectal and Ovarian (PLCO) trials on PSA screening practices of primary-care physicians (PCPs) is unknown.Methods:We conducted a national cross-sectional on-line survey of a random sample of 3010 PCPs from July to August 2010. Participants were queried about their knowledge of prostate cancer, PSA screening guidelines, the ERSPC and PLCO trials, and about their PSA screening practices. Factors associated with PSA screening were identified using multivariable linear regression.Results:A total of 152 (5%) participants opened and 89 completed the on-line survey, yielding a response rate of 58% for those that viewed the invitation. Eighty percent of respondents correctly identified prostate cancer risk factors. In all, 51% and 64% reported that they discuss and order PSA screening for men aged 50–75 years, respectively. Fifty-four percent were most influenced by the US Preventative Services Task Force (USPSTF) guidelines. Also, 21% and 28% of respondents stated that their PSA screening practices were influenced by the ERSPC and PLCO trials, respectively. Medical specialty was the only variable associated with propensity to screen, with family medicine physicians more likely to use PSA screening than internists (β=0.21, P=0.02).Conclusions:Half of the physicians surveyed did not routinely discuss PSA screening with eligible patients. The impact of the ERSPC and PLCO trials on PSA screening practices was low among US PCPs. USPSTF recommendations for PSA screening continue to be the strongest influence on PCPs propensity to use PSA screening.

Comparative Analysis of Biopsy Upgrading in Four Prostate Cancer Active Surveillance Cohorts

Active surveillance (AS) is now the preferred approach for managing newly diagnosed, low-risk prostate cancer (1, 2). A recent guideline from the American Society of Clinical Oncology (2) supports the use of AS for low-risk prostate cancer and provides recommendations about the target population and surveillance protocol. However, the recommendations lack specific information about how AS should be implemented. Several studies in North America (36) and Europe (7) are investigating the outcomes of AS, but they involve different populations, follow-up durations, inclusion criteria, surveillance protocols, and definitions of progression that lead to treatment referral. Having data from several AS cohorts provides an opportunity to learn more about disease progression on AS. Recent analyses within specific cohorts (6, 8, 9) have pointed to prostate-specific antigen (PSA) level, number of prior stable biopsy results, PSA density, and history of any negative biopsy results as important predictors of progression. However, differences in AS implementation and adherence across cohorts preclude comparison of progression risks and prevent direct integration of results to inform best practices (10). This article brings together individual-level data from 4 of the largest North American AS studies to compare and integrate their information about prostate cancer progression on AS. We evaluated whether progression rates were consistent across cohorts after standardizing inclusion criteria and the definition of progression and after controlling for variable surveillance intervals and risks for competing treatments. In addition, we examined the expected consequences of more versus less frequent biopsies across AS studies. This cross-cohort analysis is critical to assessing representativeness of individual studies and to developing sound AS guidelines that balance timely intervention with the morbidity from intensive surveillance. Methods Data Sources Deidentified, individual-level data were obtained from the 4 AS cohorts after institutional review board approval. Records included patient age and year of diagnosis; clinical and pathologic information at diagnosis; and dates and results of all surveillance tests, including PSA values and biopsy results, dates of curative treatment, and vital status. Cohort inclusion criteria, surveillance strategies, and conditions for referral to treatment are summarized in Table 1. Table 1. Eligibility Criteria, Surveillance Protocol, and Definition of Progression in 4 Active Surveillance Studies Johns Hopkins University The Johns Hopkins University (JHU) (4) study began enrollment in 1995. Eligibility criteria are PSA density less than 0.15 g/L per mL, clinical stage T1c disease or lower, a Gleason score (GS) between 2 and 6, at most 2 positive biopsy cores, and at most 50% tumor in any single core. Men are monitored with a PSA test and digital rectal examination every 6 months and annual biopsies. Curative intervention is recommended for disease progression, defined as any adverse change on prostate biopsy. Canary Prostate Active Surveillance Study The Canary Prostate Active Surveillance Study (PASS) (3) began enrollment in 2008. Eligibility criteria are clinical stage T1 or T2 disease and either a 10-core biopsy less than 1 year before enrollment or at least 2 biopsies, 1 of which must be less than 1 year before enrollment (3). Men are monitored with PSA tests every 3 months, a digital rectal examination every 6 months, and biopsies at 6 to 12, 24, 48, and 72 months after enrollment. Curative intervention is recommended if either biopsy GS or volume increases (from 33% to >33% of cores containing cancer). University of Toronto The University of Toronto (UT) (5) study began enrollment in 1995. Between 1995 and 1999, eligibility criteria were a PSA level of 10 g/L or less and a GS between 2 and 6 for men younger than 70 years and a PSA level of 15 g/L or less and a GS of at most 3+4= 7 for men aged 70 years or older. In January 2000, eligibility criteria were expanded to include PSA levels of 20 g/L or less and GSs of at most 3+4= 7 in men with substantial comorbid conditions or a life expectancy less than 10 years. Men are monitored with PSA tests every 3 months for 2 years and every 6 months thereafter. A confirmatory biopsy is done within 12 months of the initial biopsy and then every 3 to 4 years until the patient reaches age 80 years. Curative intervention is recommended in cases of histologic upgrading on repeated biopsy or clinical progression between biopsies (or PSA kinetics before 2009). University of California, San Francisco The University of California, San Francisco (UCSF) (6), study began enrollment in 1990. Eligibility criteria have evolved over time and are currently a PSA level of 10 g/L or less, clinical stage T1 or T2 disease, a biopsy GS between 2 and 6, at most 33% positive biopsy cores, and at most 50% tumor in any single core. Selected patients who do not satisfy these criteria may be enrolled, and these make up more than 30% of the cohort (6). Men are monitored with a confirmatory biopsy within 12 months of the initial biopsy and every 12 to 24 months thereafter. Curative intervention is recommended for any biopsy reclassification. Statistical Analysis Exclusion Criteria and End Point Definitions Patients diagnosed before 1995, older than 80 years at enrollment, or with a GS of 7 or more at diagnosis were excluded from the analysis to obtain a more homogeneous population (Supplement Table 1). Further, we standardized the definition of disease progression to focus exclusively on biopsy upgradingthat is, the first point at which a biopsy GS of 7 or more is reached. We also defined competing treatments as initiation of active treatment in the absence of biopsy upgrading, such as in response to increased biopsy volume or increased PSA growth. Accounting for differences in risks for competing treatments is important because cohorts with a high frequency of competing treatments may seem to have a lower risk for biopsy upgrading than similar cohorts with a low frequency of competing treatments even if their underlying risk for biopsy upgrading is similar. Supplement. Supplemental Materials Estimating the Underlying Risks for Upgrading The empirical risk for upgrading is affected by both the surveillance protocol and the frequency of competing treatment. Our first objective was to compare underlying risks for upgrading across surveillance cohortsrisks that would be seen in the absence of competing treatments. A standard approach for obtaining underlying risks, the KaplanMeier curve, is valid only if the competing event is independent of the event of interest. In the AS setting, upgrading and treatment initiation may be dependent. For example, if patients with higher PSA levels or PSA velocities tend to initiate treatment more frequently, this could induce dependence between initiating treatment and upgrading risk. When a dependent competing risk is present, the KaplanMeier approach is biased (11, 12). However, a commonly used alternative, the cumulative incidence estimate, captures the risk for the event of interest in the presence of the competing event and can therefore be sensitive to the competing risk. For example, 2 cohorts could have the same underlying risk for upgrading, but 1 with a higher incidence of competing treatment would seem to have a lower incidence of upgrading. To overcome this problem, we first evaluated the dependence of the 2 events using a regression model that allowed both events to depend on patient age and PSA kinetics. Allowing risks for both upgrading and competing treatment to depend on these common patient variables enabled us to capture their potential dependence on each other. For example, if the risks for upgrading and treatment initiation both increased with PSA velocity, the 2 risks would be positively correlated. In practice, we estimated a joint model for the evolution of the patient variables and the risks for upgrading and treatment initiation (1315). After fitting the joint model, we extracted the risk for upgrading in the absence of competing treatments using standard statistical formulas for obtaining marginal from conditional data summaries. This avoided the limitations of the KaplanMeier and cumulative incidence approaches. The joint model had the following 3 components. First, the PSA model was a linear mixed-effects model for log PSA that captured heterogeneity in patient PSA kinetics, which comprised baseline PSA and PSA velocity, defined as the annual percentage change in the PSA level. Second, the model for time to upgrading was a Weibull regression that modeled the risk for upgrading given patient age and PSA kinetics. This model assumed that biopsy GS had no misclassification error. Thus, patients with all biopsy GSs between 2 and 6 were right censored for the event of upgrading (that is, their upgrading event could occur only after the end of their follow-up), and patients with an observed biopsy GS of 7 or higher must have upgraded after the prior biopsy but before this biopsy. Third, the model for time to competing treatment was another Weibull regression that modeled the risk for treatment initiation given patient age and PSA kinetics. We used Bayesian methods to estimate the 3 models simultaneously (Section 1 of the Supplement). We did not attempt to model pathologic GS because previous work encountered substantial difficulties in doing so using serial biopsies among men receiving AS (16). Predicting Consequences Under More Versus Less Intensive Surveillance Protocols Using the fitted joint model, we simulated times to upgrading in each cohort in the absence of competing treatments. We then superimposed surveillance protocols that involved regular biopsies every 1, 2, 3, and 4 years to determine the earliest point at which a biopsy would detect the upgrade. To acknowledge the clinical value of a confirmatory biopsy, w