Peter H. Gann

Prostate Specific Antigen Best Practice Statement: 2009 Update

PURPOSE We provide current information on the use of PSA testing for the evaluation of men at risk for prostate cancer, and the risks and benefits of early detection. MATERIALS AND METHODS The report is a summary of the American Urological Association PSA Best Practice Policy 2009. The summary statement is based on a review of the current professional literature, clinical experience and the expert opinions of a multispecialty panel. It is intended to serve as a resource for physicians, other health care professionals, and patients. It does not establish a fixed set of guidelines, define the legal standard of care or pre-empt physician judgment in individual cases. RESULTS There are two notable differences in the current policy. First, the age for obtaining a baseline PSA has been lowered to 40 years. Secondly, the current policy no longer recommends a single, threshold value of PSA, which should prompt prostate biopsy. Rather, the decision to proceed to prostate biopsy should be based primarily on PSA and DRE results, but should take into account multiple factors including free and total PSA, patient age, PSA velocity, PSA density, family history, ethnicity, prior biopsy history and comorbidities. CONCLUSIONS Although recently published trials show different results regarding the impact of prostate cancer screening on mortality, both suggest that prostate cancer screening leads to overdetection and overtreatment of some patients. Therefore, men should be informed of the risks and benefits of prostate cancer screening before biopsy and the option of active surveillance in lieu of immediate treatment for certain men diagnosed with prostate cancer.

Role of diet in prostate cancer development and progression

Increasing evidence supports the important role of nutrition in cancer prevention, including prevention of prostate cancer. In this review, we summarize data for some of the most consistently observed dietary associations for prostate cancer incidence, briefly consider possible postdiagnostic effects of nutrition on prostate cancer progression/survival, discuss new but limited data on diet-gene interactions, and comment on current areas of controversy for future research focus. Potential protective dietary elements include tomatoes/lycopene, other carotenoids, cruciferous vegetables, vitamin E, selenium, fish/marine omega-3 fatty acids, soy, isoflavones and polyphenols; whereas milk, dairy, calcium, zinc at high doses, saturated fat, grilled meats, and heterocyclic amines may increase risk. It is important to note that randomized clinical trial data exist only for vitamin E, calcium, beta-carotene, and selenium (all of which suggest inverse or no association). Several genes, such as MnSOD, XRCC1, and GST, may modify the association of specific nutrients and foods with prostate cancer risk; and further research is warranted to confirm these initial observed relationships. Until further clinical trial data are available on specific supplements and prostate cancer prevention, it would be prudent to emphasize a diet consisting of a wide variety of plant-based foods and fish; this is similar to what is recommended (and what is more well established) for the primary prevention of heart disease.

Insulin-like Growth Factors, Their Binding Proteins, and Prostate Cancer Risk: Analysis of Individual Patient Data from 12 Prospective Studies

Context Insulin-like growth factors (IGFs) and IGF binding proteins may be associated with some cancers. Contribution This reanalysis of individual patient data from 12 studies of the association between IGFs and IGF binding proteins and prostate cancer suggests that higher levels of serum IGF-I are associated with higher risk for prostate cancer. Caution The 12 studies varied in the types of patients they studied and in how they measured IGFs. Implication High IGF-I levels seem to be a risk factor for prostate cancer. The Editors Prostate cancer is one of the most common types of cancer in men, yet few risk factors for the disease, other than age, race, and a family history, have been established (1, 2). Insulin-like growth factors (IGFs) and their associated binding proteins (IGFBPs) have been the subject of many epidemiologic investigations of prostate cancer because they are known to help regulate cell proliferation, differentiation, and apoptosis (3). Although results from some, but not all, studies suggest an association between IGFs and IGFBPs and prostate cancer risk, there has been much uncertainty about its consistency and magnitude. A previous meta-analysis that included only 3 prospective studies suggested that high levels could be associated with more than a 2-fold increase in risk (4), although recent studies have suggested the risk is lower. Furthermore, given that these peptides are correlated with each other, uncertainty remains about any observed relationships. The individual studies are rarely large enough to allow proper mutual adjustment for these correlated factors, and they are insufficiently powered to investigate the consistency of their findings in key subgroups (for example, stage and grade of disease). Such analyses are important because studies have suggested that IGF-I might be more associated with advanced than with localized disease (5, 6). The Endogenous Hormones and Prostate Cancer Collaborative Group was established to conduct collaborative reanalyses of individual data from prospective studies on the relationships between circulating levels of sex hormones and IGFs and subsequent prostate cancer risk. Results for the sex hormones have been reported elsewhere and show no statistically significant relation between androgen or estrogen levels in men and the subsequent risk for prostate cancer (7). We report results for concentrations of IGFs and IGFBPs. Methods Participants The Endogenous Hormones and Prostate Cancer Collaborative Group is described in detail elsewhere (7). In brief, the group invited principal investigators of all studies, found by searching PubMed, Web of Science, and CancerLit, that provided data on circulating concentrations of sex steroids, IGFs or IGFBPs, and prostate cancer risk by using prospectively collected blood samples to join the collaboration. Thirteen studies collected data on circulating IGF concentrations and the subsequent risk for prostate cancer (5, 6, 820), of which 1 contributed only data on sex hormones (20). Eleven of the studies used a matched casecontrol design nested within a prospective cohort study (5, 6, 812, 16, 19) or a randomized trial (1315, 17). One study used a casecohort design (18) and was converted into a matched casecontrol design by randomly matching up to 3 control participants to each case patient by age at recruitment, time between blood collection and diagnosis, time of blood draw, and race. (Table 1 provides a full description of the studies and matching criteria used.) Most of the prospective studies were population-based, with the exception of 1 based on health plan members (9), 1 that recruited male health professionals (16), and 1 that was a combination of an intervention study and a monitoring study for cardiovascular disease (6, 10). Two of the randomized trials did not have prostate cancer as a primary end point (5, 8, 15); the other 2 were based within a screening trial (13) or were about treatment of prostate-specific antigen (PSA)detected prostate cancer (14). Table 1. Study Characteristics Individual participant data were available for age; height; weight; smoking status; alcohol consumption; marital status; socioeconomic status (assessed by educational achievement); race; concentrations of IGFs, IGFBPs, and endogenous sex steroids; and PSA level. Information sought about prostate cancer included date of diagnosis, stage and grade of disease, and method of case patient ascertainment. Some studies (5, 6, 8, 10, 16) published more than 1 article or performed assays at different times on the association between IGFs and prostate cancer risk, sometimes with different matched casecontrol sets, laboratory measurements, and durations of follow-up. For each study, we created a single data set in which each participant appeared only once. In our analysis, we treated any participant who appeared in a study as both a control participant and a case patient as a case patient only. We removed matched set identifiers, and we generated a series of strata (equivalent to matched sets) in which participants in each study were grouped according to age at recruitment (2-year age bands) and date of recruitment (by year), because these matching criteria were common to most studies (Table 1). The number of strata used in the collaborative analysis was slightly less than that of matched sets used in the original analyses. To ensure that this process did not introduce any bias, we checked that the results for each study, using the original matched sets, were the same as those using the strata described above. Tumors were classified as advanced if the tumor was described as extending beyond the prostate capsule (T3/T4), and/or there was lymph node involvement (N1/N2/N3), and/or there were distant metastases (M1); tumors were classified as localized if they were T0/T1/T2 and N0/NX and M0. We classified tumors as high-grade if they had a Gleason score of 7 or more or were moderately poorly or poorly differentiated; otherwise, they were classified as low-grade. Statistical Analysis We calculated partial correlation coefficients between log-transformed IGF and IGFBP concentrations among control participants, adjusted for age at blood collection (<50, 50 to 59, 60 to 69, or 70 years) and study. For each IGF and IGFBP, we categorized men into quintiles of IGF and IGFBP serum concentrations, with cut-points defined by the study-specific quintiles of the distribution within control participants. For studies with more than 1 publication or in which the serum assays were done at different times, resulting in different absolute levels of IGFs (5, 6, 8, 10, 16), we calculated cut-points separately for each substudy. We used a conditional logistic regression stratified by study, age at recruitment (2-year age bands), and date of recruitment (single year) as our main method of analysis. To provide a summary measure of risk, we calculated a linear trend by scoring the quintiles of the serum IGF or IGFBP concentrations as 0, 0.25, 0.5, 0.75, and 1. Under the assumption of linearity, a unit change in this trend variable is equivalent to the odds ratio (OR) comparing the highest with the lowest quintile. All results are unadjusted for participant characteristics, except for those controlled by the stratification variables. We examined the possible influence of 5 participant characteristics by adjusting the relevant conditional logistic regression models for body mass index (BMI) (<22.5, 22.5 to 24.9, 25.0 to 27.4, 27.5 to 29.9, or >30 kg/m2), marital status (married or cohabiting, or not married or cohabiting), educational status (did not attend college or university, or attended college or university), smoking (never, previous, or current), and alcohol consumption (<10 or 10 g/d). We excluded participants from the analysis if they had a missing value for the characteristic under examination. We assessed heterogeneity in linear trends among studies by using a chi-square statistic to test whether the study-specific ORs were statistically different from the overall OR (21). Heterogeneity among studies was also quantified by calculating the H and I 2 statistics (22). To test whether the linear trend OR estimates for each IGF and IGFBP varied according to case patient characteristics, we estimated a series of subsets for each characteristic: stage at diagnosis (localized or advanced), grade at diagnosis (low or high), year of diagnosis (before 1990, 1990 to 1994, or 1995 onward; these year cutoffs were chosen to attempt to reflect differences in the use of the PSA test for cancer detection), age at diagnosis (<60, 60 to 69, or 70 years), and time between blood collection and diagnosis (<3, 3 to 6, or 7 years). We excluded case patients from the analyses of stage and grade at diagnosis if the relevant information was not available. For each of these case patient characteristics, we calculated a heterogeneity chi-square statistic to assess whether the estimated ORs statistically differed from each other (21). To assess whether the OR estimate of the linear trend for each IGF or IGFBP varied according to PSA level at recruitment (<2 g/L or 2 g/L), we entered an interaction term into the conditional logistic regression model for each IGF or IGFBP, and we tested the statistical significance of the interaction term with a likelihood ratio test. Statistical significance was set at the 5% level. All statistical tests were 2-sided. All statistical analyses were done with Stata, version 9.0 (StataCorp, College Station, Texas). Results Table 1 shows the characteristics of the studies. The 12 prospective studies included approximately 3700 case patients with prostate cancer and 5200 control participants. Insulin-like growth factor I and IGFBP-III measurements were available for all and 3600 case patients, respectively. However, IGF-II and IGFBP-II measurements were available for only 379 and 419 case patients, respectively (Table 2). Mean age at blood collection

Salivary estradiol and progesterone levels in conception and nonconception cycles in women: evaluation of a new assay for salivary estradiol☆

OBJECTIVE To determine the usefulness of salivary E2 and progesterone for noninvasive assessment of ovarian function. DESIGN Prospective study of salivary hormone levels in women planning a pregnancy. SETTING Department of Obstetrics and Gynecology at Northwestern University Medical School in Chicago, Illinois. PATIENT(S) Fourteen women aged 23-39 years with regular menstrual cycles who were planning a pregnancy. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) Salivary estradiol and progesterone concentrations. RESULT(S) The sensitivity of the E2 assay is 2.0 pmol/L; the interassay coefficient of variation was 5.2% (mean value 17 pmol/L). Recovery of E2 added to saliva was 106%. The correlation with simultaneous serum samples was 0.71. Menstrual cycle patterns contained a preovulatory depression and a midcycle surge. By comparison with nonconception cycles, the luteal phases of conception cycles had significantly elevated salivary E2 within the first 5 days after ovulation. Salivary progesterone was significantly elevated but not until 10 days after ovulation. CONCLUSION(S) Salivary measurements of E2 and progesterone can be used as noninvasive methods for assessment of ovarian function. Salivary specimens can be collected at home and brought to the laboratory for analysis, obviating the need for frequent phlebotomy. The sensitivity and precision of the salivary E2 assay make it comparable with assays of serum E2 for assessing changes in hormone levels.

Hormone receptor status of breast tumors in black, Hispanic, and non‐Hispanic white women: An analysis of 13,239 cases

It has been postulated that different biologic characteristics of a tumor might account for at least a portion of the disparity in breast cancer survival for patients across racial and ethnic groups. The hormone receptor status of breast tumors is one characteristic with prognostic significance. Results of several studies indicate a higher proportion of estrogen receptor negative (ER‐) breast tumors among black or Hispanic women compared with non‐Hispanic whites. We investigated whether the association between race and ethnicity and the joint combination of ER and progesterone receptor (PR) status was independent of age and other tumor characteristics at diagnosis.

Fruits and vegetables and prostate cancer: no association among 1104 cases in a prospective study of 130544 men in the European Prospective Investigation into Cancer and Nutrition (EPIC).

We examined the association between self‐reported consumption of fruits and vegetables and prostate cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC). Data on food consumption and complete follow‐up for cancer incidence were available for 130,544 men in 7 countries recruited into EPIC between 1993 and 1999. After an average of 4.8 years of follow‐up, there were 1,104 incident cases of prostate cancer. The associations of consumption of total fruits, total vegetables, cruciferous vegetables and combined total fruits and vegetables with prostate cancer risk were examined using Cox regression, stratified for recruitment center and adjusted for height, weight and energy intake. There was a wide range in consumption of fruits and vegetables: mean intakes (g/day) in the bottom and top fifths of the distribution, as estimated from 24‐hr recalls in a subsample of participants, were 53.2 and 410.7 for fruits, 97.1 and 242.1 for vegetables and 169.0 and 633.7 for fruits and vegetables combined. No significant associations between fruit and vegetable consumption and prostate cancer risk were observed. Relative risks (95% confidence intervals) in the top fifth of the distribution of consumption, compared to the bottom fifth, were 1.06 (0.84–1.34) for total fruits, 1.00 (0.81–1.22) for total vegetables and 1.00 (0.79–1.26) for total fruits and vegetables combined; intake of cruciferous vegetables was not associated with risk. These results suggest that total consumption of fruits and vegetables is not associated with the risk for prostate cancer.

Evidence for field cancerization of the prostate

Field cancerization, which is not yet well‐characterized in the prostate, occurs when large areas of an organ or tissue surface are affected by a carcinogenic insult, resulting in the development of multi‐focal independent premalignant foci and molecular lesions that precede histological change.

Gene Expression Patterns in the Human Breast after Pregnancy

Epidemiologic studies have established that pregnancy has a bidirectional, time-dependent effect on breast cancer risk; a period of elevated risk is followed by a long-term period of protection. The purpose of the present study was to determine whether pregnancy and involution are associated with gene expression changes in the normal breast, and whether such changes are transient or persistent. We examined the expression of a customized gene set in normal breast tissue from nulliparous, recently pregnant (0-2 years since pregnancy), and distantly pregnant (5-10 years since pregnancy) age-matched premenopausal women. This gene set included breast cancer biomarkers and genes related to immune/inflammation, extracellular matrix remodeling, angiogenesis, and hormone signaling. Laser capture microdissection and RNA extraction were done from formalin-fixed paraffin-embedded reduction mammoplasty and benign biopsy specimens and analyzed using real-time PCR arrays containing 59 pathway-specific and 5 housekeeping genes. We report 14 of 64 (22%) of the selected gene set to be differentially regulated (at P < 0.05 level) in nulliparous versus parous breast tissues. Based on gene set analysis, inflammation-associated genes were significantly upregulated as a group in both parous groups compared with nulliparous women (P = 0.03). Moreover, parous subjects had significantly reduced expression of estrogen receptor α (ERα, ESR1), progesterone receptor (PGR), and ERBB2 (Her2/neu) and 2-fold higher estrogen receptor-β (ESR2) expression compared with nulliparous subjects. These initial data, among the first on gene expression in samples of normal human breast, provide intriguing clues about the mechanisms behind the time-dependent effects of pregnancy on breast cancer risk. Cancer Prev Res; 3(3); 301–11

What is the true number needed to screen and treat to save a life with prostate-specific antigen testing?

PURPOSE The European Randomized Study of Screening for Prostate Cancer (ERSPC) reported a 20% mortality reduction with prostate-specific antigen (PSA) screening. However, they estimated a number needed to screen (NNS) of 1,410 and a number needed to treat (NNT) of 48 to prevent one prostate cancer death at 9 years. Although NNS and NNT are useful statistics to assess the benefits and harms of an intervention, in a survival study setting such as the ERSPC, NNS and NNT are time specific, and reporting values at one time point may lead to misinterpretation of results. Our objective was to re-examine the effect of varying follow-up times on NNS and NNT using data extrapolated from the ERSPC report. MATERIALS AND METHODS On the basis of published ERSPC data, we modeled the cumulative hazard function using a piecewise exponential model, assuming a constant hazard of 0.0002 for the screening and control groups for years 1 to 7 of the trial and different constant rates of 0.00062 and 0.00102 for the screening and control groups, respectively, for years 8 to 12. Annualized cancer detection and drop-out rates were also approximated based on the observed number of individuals at risk in published ERSPC data. RESULTS According to our model, the NNS and NNT at 9 years were 1,254 and 43, respectively. Subsequently, NNS decreased from 837 at year 10 to 503 at year 12, and NNT decreased from 29 to 18. CONCLUSION Despite the seemingly simplistic nature of estimating NNT, there is widespread misunderstanding of its pitfalls. With additional follow-up in the ERSPC, if the mortality difference continues to grow, the NNT to save a life with PSA screening will decrease.

Serum androgens and prostate cancer among 643 cases and 643 controls in the European Prospective Investigation into Cancer and Nutrition.

We examined the hypothesis that serum concentrations of circulating androgens and sex hormone binding globulin (SHBG) are associated with risk for prostate cancer in a case‐control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of androstenedione, testosterone, androstanediol glucuronide and SHBG were measured in serum samples for 643 prostate cancer cases and 643 matched control participants, and concentrations of free testosterone were calculated. Conditional logistic regression models were used to calculate odds ratios for risk of prostate cancer in relation to the serum concentration of each hormone. After adjustment for potential confounders, there was no significant association with overall risk for prostate cancer for serum total or free testosterone concentrations (highest versus the lowest thirds: OR, 1.02; 95% CI, 0.73–1.41 and OR, 1.07, 95% CI, 0.74–1.55, respectively) or for other androgens or SHBG. Subgroup analyses showed significant heterogeneity for androstenedione by cancer stage, with a significant inverse association of androstenedione concentration and risk for advanced prostate cancer. There were also weak positive associations between free testosterone concentration and risk for total prostate cancer among younger men and risk for high‐grade disease. In summary, in this large nested case‐control study, concentrations of circulating androgens or SHBG were not strongly associated with risk for total prostate cancer. However, our findings are compatible with a positive association of free testosterone with risk in younger men and possible heterogeneity in the association with androstenedione concentration by stage of disease; these findings warrant further investigation.