Marcos Lujan

Screening and Prostate-Cancer Mortality in a Randomized European Study

BACKGROUND The European Randomized Study of Screening for Prostate Cancer was initiated in the early 1990s to evaluate the effect of screening with prostate-specific-antigen (PSA) testing on death rates from prostate cancer. METHODS We identified 182,000 men between the ages of 50 and 74 years through registries in seven European countries for inclusion in our study. The men were randomly assigned to a group that was offered PSA screening at an average of once every 4 years or to a control group that did not receive such screening. The predefined core age group for this study included 162,243 men between the ages of 55 and 69 years. The primary outcome was the rate of death from prostate cancer. Mortality follow-up was identical for the two study groups and ended on December 31, 2006. RESULTS In the screening group, 82% of men accepted at least one offer of screening. During a median follow-up of 9 years, the cumulative incidence of prostate cancer was 8.2% in the screening group and 4.8% in the control group. The rate ratio for death from prostate cancer in the screening group, as compared with the control group, was 0.80 (95% confidence interval [CI], 0.65 to 0.98; adjusted P=0.04). The absolute risk difference was 0.71 death per 1000 men. This means that 1410 men would need to be screened and 48 additional cases of prostate cancer would need to be treated to prevent one death from prostate cancer. The analysis of men who were actually screened during the first round (excluding subjects with noncompliance) provided a rate ratio for death from prostate cancer of 0.73 (95% CI, 0.56 to 0.90). CONCLUSIONS PSA-based screening reduced the rate of death from prostate cancer by 20% but was associated with a high risk of overdiagnosis. (Current Controlled Trials number, ISRCTN49127736.)

Prostate-cancer mortality at 11 years of follow-up

BACKGROUND Several trials evaluating the effect of prostate-specific antigen (PSA) testing on prostate-cancer mortality have shown conflicting results. We updated prostate-cancer mortality in the European Randomized Study of Screening for Prostate Cancer with 2 additional years of follow-up. METHODS The study involved 182,160 men between the ages of 50 and 74 years at entry, with a predefined core age group of 162,388 men 55 to 69 years of age. The trial was conducted in eight European countries. Men who were randomly assigned to the screening group were offered PSA-based screening, whereas those in the control group were not offered such screening. The primary outcome was mortality from prostate cancer. RESULTS After a median follow-up of 11 years in the core age group, the relative reduction in the risk of death from prostate cancer in the screening group was 21% (rate ratio, 0.79; 95% confidence interval [CI], 0.68 to 0.91; P=0.001), and 29% after adjustment for noncompliance. The absolute reduction in mortality in the screening group was 0.10 deaths per 1000 person-years or 1.07 deaths per 1000 men who underwent randomization. The rate ratio for death from prostate cancer during follow-up years 10 and 11 was 0.62 (95% CI, 0.45 to 0.85; P=0.003). To prevent one death from prostate cancer at 11 years of follow-up, 1055 men would need to be invited for screening and 37 cancers would need to be detected. There was no significant between-group difference in all-cause mortality. CONCLUSIONS Analyses after 2 additional years of follow-up consolidated our previous finding that PSA-based screening significantly reduced mortality from prostate cancer but did not affect all-cause mortality. (Current Controlled Trials number, ISRCTN49127736.).

Prostate Cancer Mortality Reduction by Prostate-Specific Antigen-Based Screening Adjusted for Nonattendance and Contamination in the European Randomised Study of Screening for Prostate Cancer (ERSPC)

BACKGROUND Prostate-specific antigen (PSA) based screening for prostate cancer (PCa) has been shown to reduce prostate specific mortality by 20% in an intention to screen (ITS) analysis in a randomised trial (European Randomised Study of Screening for Prostate Cancer [ERSPC]). This effect may be diluted by nonattendance in men randomised to the screening arm and contamination in men randomised to the control arm. OBJECTIVE To assess the magnitude of the PCa-specific mortality reduction after adjustment for nonattendance and contamination. DESIGN, SETTING, AND PARTICIPANTS We analysed the occurrence of PCa deaths during an average follow-up of 9 yr in 162,243 men 55-69 yr of age randomised in seven participating centres of the ERSPC. Centres were also grouped according to the type of randomisation (ie, before or after informed written consent). INTERVENTION Nonattendance was defined as nonattending the initial screening round in ERSPC. The estimate of contamination was based on PSA use in controls in ERSPC Rotterdam. MEASUREMENTS Relative risks (RRs) with 95% confidence intervals (CIs) were compared between an ITS analysis and analyses adjusting for nonattendance and contamination using a statistical method developed for this purpose. RESULTS AND LIMITATIONS In the ITS analysis, the RR of PCa death in men allocated to the intervention arm relative to the control arm was 0.80 (95% CI, 0.68-0.96). Adjustment for nonattendance resulted in a RR of 0.73 (95% CI, 0.58-0.93), and additional adjustment for contamination using two different estimates led to estimated reductions of 0.69 (95% CI, 0.51-0.92) to 0.71 (95% CI, 0.55-0.93), respectively. Contamination data were obtained through extrapolation of single-centre data. No heterogeneity was found between the groups of centres. CONCLUSIONS PSA screening reduces the risk of dying of PCa by up to 31% in men actually screened. This benefit should be weighed against a degree of overdiagnosis and overtreatment inherent in PCa screening.

The effect of study arm on prostate cancer treatment in the large screening trial ERSPC

Prostate cancer (PC) mortality is the most valid end‐point in screening trials, but could be influenced by the choice of initial treatment if treatment has an effect on mortality. In this study, PC treatment was compared between the screening and control arms in a screening trial. Data were collected from the European Randomized Study of Screening for Prostate Cancer (ERSPC). The characteristics and initial treatment of PC cases detected in the screening and the control arm were compared. Polytomous logistic regression analysis was used to assess the influence of study arm on treatment, adjusting for potential confounders and with statistical imputation of missing values. A total of 8,389 PC cases were detected, 5,422 in the screening arm and 3,145 in the control arm. Polytomous regression showed that trial arm was associated with treatment choice after correction for missing values, especially in men with high‐risk PC. A control subject with high‐risk PC was more likely than a screen subject to receive radiotherapy (OR: 1.43, 95% CI: 1.01–2.05, p = 0.047), expectant management (OR: 2.92, 95% CI: 1.33–6.42, p = 0.007) or hormonal treatment (OR: 1.77, 95% CI: 1.07–2.94, p = 0.026) instead of radical prostatectomy. However, trial arm had only a minor role in treatment choice compared to other variables. In conclusion, a small effect of trial arm on treatment choice was seen, particularly in men with high‐risk PC. Therefore, differences in treatment between arms are unlikely to play a major role in the interpretation of the results of the ERSPC.

Metastatic prostate cancer incidence and prostate-specific antigen testing: New insights from the European Randomized Study of Screening for Prostate Cancer

BACKGROUND The European Randomized Study of Screening for Prostate Cancer (ERSPC) has shown a 21% reduction in prostate cancer (PCa) mortality and a 1.6-fold increase in PCa incidence with prostate-specific antigen (PSA)-based screening (at 13 yr of follow-up). We evaluated PCa incidence by risk category at diagnosis across the study arms to assess the potential impact on PCa mortality. DESIGN, SETTING, AND PARTICIPANTS Information on arm, centre, T and M stage, Gleason score, serum PSA at diagnosis, age at randomisation, follow-up time, and vital status were extracted from the ERSPC database. Four risk categories at diagnosis were defined: 1, low; 2, intermediate; 3, high; 4, metastatic disease. PSA (≤100 or >100 ng/ml) was used as the indicator of metastasis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Incidence rate ratios (IRRs) for screening versus control arm by risk category at diagnosis and follow-up time were calculated using Poisson regression analysis for seven centres. Follow-up was truncated at 13 yr. Missing data were imputed using chained equations. The analyses were carried out on an intention-to-treat basis. RESULTS AND LIMITATIONS In the screening arm, 7408 PCa cases were diagnosed and 6107 in the control arm. The proportion of missing stage, Gleason score, or PSA value was comparable in the two arms (8% vs 10%), but differed among centres. The IRRs were elevated in the screening arm for the low-risk (IRR: 2.14; 95% CI, 2.03-2.25) and intermediate-risk (IRR: 1.24; 95% CI, 1.16-1.34) categories at diagnosis, equal to unity for the high-risk category at diagnosis (IRR: 1.00; 95% CI, 0.89-1.13), and reduced for metastatic disease at diagnosis (IRR: 0.60; 95% CI, 0.52-0.70). The IRR of metastatic disease had temporal pattern similar to mortality, shifted forwards an average of almost 3 yr, although the mortality reduction was smaller. CONCLUSIONS The results confirm a reduction in metastatic disease at diagnosis in the screening arm, preceding mortality reduction by almost 3 yr. PATIENT SUMMARY The findings of this study indicate that the decrease in metastatic disease at diagnosis is the major determinant of the prostate cancer mortality reduction in the European Randomized study of Screening for Prostate Cancer.

Reliability of the Routine Cytological Diagnosis in Bladder Cancer

Objectives: To establish the reliability of three cytopathologists for cytological diagnosis of primary bladder tumors. Methods: Preoperative voided urine specimens of 71 patients with bladder cancer and 55 noncancer controls were retrospectively and blindly reviewed by 3 independent cytologists, and their results compared. The estimation of the interobserver agreement was calculated using the weighted κ coefficient. A multivariate analysis was carried out to identify the factors associated with the disagreement between the three observers. The sensitivity and specificity for each of the participants was calculated in order to clearly identify the origin of the disagreement, in terms of the performance of the diagnostic test in the hands of each observer. A comparison of the overall diagnostic performance was made by plotting sensitivity versus 1-specificity. Results: The weighted κ coefficient among the 3 observers was 0.46. The multivariate analysis did not identify any variable that could have caused such disagreement. Vast differences in sensitivity and specificity were detected between observer 1 (sens. 0.90, spec. 0.45) and observers 2 (sens. 0.67, spec. 0.72) and 3 (sens. 0.71, spec. 0.80), but the overall diagnostic performance (sensitivity vs. 1-specificity) was superimposable in the 3 cases (p = NS). Conclusions: Simple, reproducible and agreed-on-diagnostic criteria should be established to yield reliable results in a group of cytologists. The consideration of individual diagnostic performances can give a false idea of homogeneity between observers. In this field, concordance analysis makes quality control reliable and should be a routine procedure of any pathology department.

Reconciling the Effects of Screening on Prostate Cancer Mortality in the ERSPC and PLCO Trials

More than 2 decades after prostate-specific antigen (PSA) screening for prostate cancer entered clinical practice, in 2012 the U.S. Preventive Services Task Force (USPSTF) determined that there was very low probability of preventing a death from prostate cancer in the long term and recommended against routine use of the test (1). Since then, rates of PSA screening and prostate cancer incidence have decreased significantly in the United States (2, 3). The USPSTF recommendation relied heavily on results from the ERSPC (European Randomized Study of Screening for Prostate Cancer) (ISRCTN registry number: ISRCTN49127736) and the PLCO (Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial) (ClinicalTrials.gov: NCT00002540). However, the trials had apparently conflicting results, with the ERSPC reporting a 21% reduction in prostate cancer mortality (46) and the PLCO finding no difference in mortality between the trial groups (79). Interpretation of the trial results is complicated by differences in their implementation (including design and adherence) and practice settings. The PLCO used a shorter screening interval (annual vs. every 2 to 4 years in the ERSPC), had a higher PSA threshold for biopsy referral (4.0 g/L vs. 3.0 g/L in most ERSPC centers and rounds), and stopped regular screening after 6 rounds. Prostate cancer incidence was higher in the United States than in Europe before the trials started, reflecting different populations and clinical diagnosis patterns. The U.S. practice setting also contributed to more frequent screening in the PLCO control group and less frequent biopsy than in the ERSPC. Consequently, the PLCO compared the effects of an organized screening program versus opportunistic screening rather than screening versus no screening (810). Nonetheless, the PLCO results have been viewed as more relevant to the U.S. setting (11). The objectives of this study were to formally test whether the effects of screening on prostate cancer mortality differed between the ERSPC and PLCO after differences in implementation and practice settings were accounted for and to estimate the effects of screening in both trials relative to no screening. Methods Overview Our study used individual records from both trials in a collaboration between trial investigators and the prostate cancer working group of the Cancer Intervention and Surveillance Modeling Network. In the intervention groups, these records included age and year of randomization, enrollment center, dates and results of PSA tests and rectal examinations, whether biopsy was performed, date of cancer diagnosis, and date and cause of death. In the control groups, the records included age and year of randomization, enrollment center, date of cancer diagnosis, and date and cause of death. For consistency with prior publications, ERSPC data included men aged 55 to 69 years at randomization (12), and PLCO data included men aged 55 to 74 years at randomization (13). We first conducted a traditional statistical analysis that combined data from both trials and compared hazards of prostate cancer death in the intervention groups versus the control groups, with adjustment for participant age and trial setting. However, this analysis is questionable because of remaining differences in implementation between the trials. To overcome this limitation, we also performed extended analyses that accounted for variable screening and diagnostic work-up (hereafter screening intensity) in each trial group, which we operationalized using mean lead times (MLTs). The MLTs reflect the magnitude of increased prostate cancer incidence relative to a baseline level expected in the absence of screening, thus capturing differences in both design and adherence (see the next section). We estimated the MLTs both empirically and using analytic or microsimulation models; using multiple approaches allowed us to assess the robustness of results to this uncertain quantity. Estimating MLTs The MLT is usually defined as the average time by which diagnosis is advanced by screening relative to the date of diagnosis without screening. Under complete follow-up, where all preclinical cases are eventually diagnosed in the no-screening setting, the MLT corresponds to the difference in areas under 2 survival curves (one in the absence of screening minus one in the presence of screening) for time from randomization to diagnosis. Under limited follow-up, we can define a restricted version of the MLT as an analogous difference in areas under survival curves up to a specified time point (14). Restricting the analysis to the duration of the trial recognizes that events after the trial period cannot affect mortality during the trial. To make estimates between trials comparable, follow-up was restricted to 11 years. Of note, our estimates of the MLTs differ from other estimates in the literature that can be interpreted as the average time by which screening advances diagnosis among cases that would have been clinically diagnosed (15). Our MLTs are designed as proxies for the intensity of screening and diagnosis, with higher values reflecting higher attendance rates at screening examinations, more frequent screening examinations, less conservative criteria for biopsy referral, and/or more frequent biopsy. Thus, accounting for variable MLTs across trial groups captures in a single measure important differences in the trial screening protocols, participant adherence to those protocols in the intervention groups, and control group screening. We estimated the MLTs empirically, with no model assumptions about cancer progression and diagnosis, and also using 3 models of cancer natural history and diagnosis. The empirical approach estimated the MLTs by calculating the difference between survival curves for observed time from randomization to diagnosis in each trial group relative to an assumed baseline level. The assumed baseline probability of diagnosis in the absence of screening was derived using incidence rates from the SEER (Surveillance, Epidemiology, and End Results) program in 1986just before PSA screening began in the United Stateswith adjustment to reflect distributions of age at randomization in each trial. In addition, 1 analytic model (University of Michigan [UMICH]) and 2 simulation models (Fred Hutchinson Cancer Research Center [FHCRC] and Erasmus University Medical Center MIcrosimulation SCreening ANalysis [MISCAN]) estimated times from randomization to diagnosis in the absence and presence of screening based on cancer progression and diagnosis rates, which were estimated using individual-patient data on attendance, screening, and incidence. The fitted models then estimated MLTs as in the empirical approach, but using projected instead of observed incidence rates. Each MLT was then scaled by the corresponding fraction of patients diagnosed within the 11-year follow-up and was projected so that it could be interpreted as an average interval among cancer cases detected in the relevant trial group. Further details are provided in the Supplement. Supplement. Additional Information Statistical Analysis We used Cox regression to model survival from randomization to prostate cancer death, censoring persons who died of other causes or were alive at the last follow-up. We performed both a traditional statistical analysis and extended analyses that incorporated the measure of screening intensity captured by the estimated MLTs. Both types of analysis included participant age at randomization and a trial setting indicator (PLCO vs. ERSPC), which allowed for a different baseline risk for prostate cancer death in the absence of screening between trial settings. Traditional Statistical Analysis We first conducted a traditional analysis to test whether the effect of screening differed between trials. Specifically, we tested the effect of being randomly assigned to the intervention group (relative to the control group) on the risk for prostate cancer death. The exponential of the coefficient for the trial group indicator is the hazard ratio for prostate cancer death in the intervention group relative to the control group; in other words, it reflects the effect of screening on prostate cancer mortality in an intention-to-screen analysis. We fitted this model with and without allowing separate effects of screening in each trial (that is, with and without interaction between the trial group and the trial setting indicator), then used a likelihood ratio test to evaluate evidence of differential effects of screening between trials. Extended Statistical Analysis Next, we replaced the trial group indicator with the corresponding MLT, which was estimated empirically or using a model-based approach. The exponential of the coefficient for the MLT represents the hazard ratio for prostate cancer death per additional year of MLT; in other words, it reflects screening efficacy standardized by screening intensity. As in the traditional analysis, we fitted this model with and without allowing separate effects of screening on prostate cancer mortality in each trial (that is, with and without interaction between the MLT and the trial setting indicator), then used a likelihood ratio test to evaluate evidence of differential effects of screening between trials. Our extended analyses are consistent with the analyses in the trial publications (4, 7), with 2 important differences. First, rather than relying on an intention-to-treat effect of screening determined by the assigned group in a single trial, we explicitly included a covariate (MLT) to capture the intensity of screening in each group. This represents a transition from thinking about screening as all or nothing (corresponding to an intervention and control group) to a continuous metric of screening intensity, with resulting coefficient estimates interpreted relative to a no-screening setting (where the MLT equals zero). Second, we used combined data from both trials in a sing

PSA-Use in a Spanish Industrial Area

OBJECTIVES To document the extent of prostate-specific antigen (PSA)-testing in the general population at Getafe (Spain) outside our prostate cancer (PC) screening program, and to check its performance in terms of PC detection. METHODS A total of 5371 PSA-test records (1997-1999) were reviewed and testing rates estimated per 1000 person-years. The extent of patient referral (men referred to our facilities) was calculated adjusting for PSA levels. To approach the performance of testing in the general population, our PC screening program acted as a standard for comparison. The probability of missing one PC in the general population was estimated in terms of number of men necessary to screen (NNS). Calculations were made adjusting for PSA levels. RESULTS PSA-testing rate in the general population was 21.6/1000 person-years. In the age-group 55-69 years, this rate was 86.8/1000 (152.6 in men >70 years). Referral rates were 67.9 and 39.5% for men with PSA 4-10 and >10 ng/ml, respectively. Overall PC detection rate was 1.76%. Detection rates for PSA 4-10 and >10 ng/ml were 4.66 and 12.94%, respectively. When compared with the performance of the screening program, for every 17 men with a PSA in the range 4-10 ng/ml one cancer was missed (95% confidence interval (CI), 9-580). Similarly, one cancer was lost for every four men with a PSA >10 ng/ml (95% CI, 2-8). CONCLUSIONS The extent of opportunistic testing in our setting is very high, particularly in the older age groups. Opportunistic screening renders PC detection rates lower than expected for every PSA level and cannot be encouraged.

Prostate specific antigen variation in patients without clinically evident prostate cancer.

PURPOSE We address long-term within individual variation of serum prostate specific antigen (PSA) in men without clinical or biopsy evidence of prostate cancer. MATERIALS AND METHODS We studied 943 men from a prostate cancer screening program with 2 PSA (PSA1 and PSA2) measurements available. A third PSA (PSA3) was obtained from 571 men. Only participants with no clinical evidence of cancer were included in the study. Within individual PSA variability was calculated based on indexes of percent coefficient of variation, ratio difference and PSA velocity. The relationship among these indexes, interval between measurements and number of PSA samples was assessed. RESULTS Mean interval was 670.4 days between PSA1 and PSA2, and 801.8 days between PSA2 and PSA3 (p<0.001). Mean coefficient of variation was 18% after 2 and 15.7% after 3 PSA measurements. Mean ratio differences were -0.047 ng./ml. for 2 and 0.033 ng./ml. for 3 samples. Mean PSA velocity was -0.128 ng./ml. per year for 2 and -0.055 ng./ml. per year for 3 samples, with 95% confidence intervals of 0.634 and 0.315, respectively. Variability was higher if only 2 PSA measurements were done (p<0.001). No clear relationship was found between individual variability and interval between measurements. CONCLUSIONS PSA velocity is within normal limits in almost all men (more than 95%) without clinically relevant prostate cancer. PSA individual variability is not fully dependent on the time between measurements when intervals are long, and can be substantially decreased with a third PSA sample.

ROLE OF AUTONOMIC INNERVATION IN RAT PROSTATIC STRUCTURE MAINTENANCE: A MORPHOMETRIC ANALYSIS

PURPOSE To analyze the effects of major pelvic ganglion (MPG) excision on the structure of rat prostate. MATERIALS AND METHODS We studied 80 Sprague-Dawley rats (300-350 gm. weight). Forty-two were anesthetized and the right MPG excised. After 28-30 days, the same-side prostatic ventral lobe (VL) was obtained for macroscopic, light (LM), and transmission electron microscopy (TEM) evaluation. A computerized morphometric analysis was performed on epithelial and muscle cells. Results were compared with 38 right VL of non-operated, same-aged rats. RESULTS A 36.6% reduction (0.14 gm.) of VL fresh weight was found in the denervated group (p <0.001). Mean tissue proportions observed in the LM study were 27.9% (epithelial), 48.3% (stromal), and 51.8% (glandular) in the non-operated group, versus 14.8% (p <0.001), 55.7%, and 44.4% (not significant) respectively, after MPG excision. No difference was found regarding the vascular pattern. In the denervated rats, TEM analysis found a significant reduction in total and supranuclear cell height (change in cell polarity), as well as in cytoplasm, Golgi and endoplasmic reticulum areas. Secretory granule count, total area (p <0.001), and density of apical microvilli were also reduced. On the other hand, only an increase in the area of cytoplasm ribosomal aggregates was detected in the smooth muscle cell analysis. CONCLUSIONS Our study demonstrated a rat prostatic VL atrophy in the denervated side, due to a shrinkage in the epithelial component of the gland. Ultrastructural findings also suggest an overall decrease of epithelial cell secretory activity. Finally, the increase of ribosomal aggregates found in stromal smooth muscle could reflect an activation of these cells after denervation.