Is further screening of men with baseline PSA < 1 ng ml−1worthwhile? The discussion continues-Results of the Swiss ERSPC (Aarau)

Lifetime Benefits and Harms of Prostate-Specific Antigen-Based Risk-Stratified Screening for Prostate Cancer

Background

Studies conducted in Swedish populations have shown that men with lowest prostate-specific antigen (PSA) levels at ages 44–50 years and 60 years have very low risk of future distant metastasis or death from prostate cancer. This study investigates benefits and harms of screening strategies stratified by PSA levels.

Methods

PSA levels and diagnosis patterns from two microsimulation models of prostate cancer progression, detection, and mortality were compared against results of the Malmö Preventive Project, which stored serum and tracked subsequent prostate cancer diagnoses for 25 years. The models predicted the harms (tests and overdiagnoses) and benefits (lives saved and life-years gained) of PSA-stratified screening strategies compared with biennial screening from age 45 years to age 69 years.

Results

Compared with biennial screening for ages 45–69 years, lengthening screening intervals for men with PSA less than 1.0 ng/mL at age 45 years led to 46.8–47.0% fewer tests (range between models), 0.9–2.1% fewer overdiagnoses, and 3.1–3.8% fewer lives saved. Stopping screening when PSA was less than 1.0 ng/mL at age 60 years and older led to 12.8–16.0% fewer tests, 5.0–24.0% fewer overdiagnoses, and 5.0–13.1% fewer lives saved. Differences in model results can be partially explained by differences in assumptions about the link between PSA growth and the risk of disease progression.

Conclusion

Relative to a biennial screening strategy, PSA-stratified screening strategies investigated in this study substantially reduced the testing burden and modestly reduced overdiagnosis while preserving most lives saved. Further research is needed to clarify the link between PSA growth and disease progression.

Screening for prostate cancer: History, evidence, controversies and future perspectives toward individualized screening

Differences in the incidence and mortality rate of prostate cancer between the USA and Japan have been decreasing over time, and were only twofold in 2017. Therefore, countermeasures against prostate cancer could be very important not only in Western countries, but also in developed Asian countries. Screening for prostate cancer in the general population using transrectal ultrasonography, digital rectal examination and/or prostate acid phosphatase began in Japan in the early 1980s, and screening with prostate-specific antigen and digital rectal examination has been widespread in the USA since the late 1980s. Large- and mid-scale randomized controlled trials on screening for prostate cancer began around 1990 in the USA, Canada and Europe. However, most of these studies failed as randomized controlled trials because of high contamination in the control arm, low compliance in the screening arm or insufficient screening setting about screening frequency and/or biopsy indication. The best available level 1 evidence is data from the European Randomized Study of Screening for Prostate Cancer and the Göteborg screening study. However, several non-urological organizations and lay media around the world have mischaracterized the efficacy of prostate-specific antigen screening. To avoid long-term confusion about screening for prostate cancer, leading professional urological organizations, including the Japanese Urological Association, are moving toward the establishment of an optimal screening system that minimizes the drawbacks of overdetection, overtreatment and loss of quality of life due to treatment, and maximizes reductions in the risk of death as a result of prostate cancer and the development of metastatic prostate cancer.

Machine learning methods can more efficiently predict prostate cancer compared with prostate-specific antigen density and prostate-specific antigen velocity

Background

Prostate-specific antigen (PSA)–based screening for prostate cancer has been widely performed, but its accuracy is unsatisfactory. To improve accuracy, building an effective statistical model using machine learning methods (MLMs) is a promising approach.

Methods

Data on continuous changes in the PSA level over the past 2 years were accumulated from 512 patients who underwent prostate biopsy after PSA screening. The age of the patients, PSA level, prostate volumes, and white blood cell count in urinalysis were used as input data for the MLMs. As MLMs, we evaluated the efficacy of three different techniques: artificial neural networks (ANNs), random forest, and support vector machine. Model performance was evaluated using area under the receiver operating characteristic curve (AUC) and compared with the PSA level and the conventional PSA–based parameters: PSA density and PSA velocity.

Results

When using two annual PSA testing, all receiver operating characteristic curves of the three MLMs were above the curve for the PSA level, PSA density, and PSA velocity. The AUCs of ANNs, random forest, and support vector machine were 0.69, 0.64, and 0.63, respectively. Those values were higher than the AUCs of the PSA level, PSA density, and PSA velocity, 0.53, 0.41, and 0.55, respectively. The accuracies of the MLMs (71.6% to 72.1%) were also superior to those of the PSA level (39.1%), PSA density (49.7%), and PSA velocity (54.9%). Among the MLMs, ANNs showed the most favorable AUC. The MLMs showed higher sensitivity and specificity than conventional PSA–based parameters. The model performance did not improve when using three annual PSA testing.

Conclusion

The present retrospective study results indicate that machine learning techniques can predict prostate cancer with significantly better AUCs than those of PSA density and PSA velocity.

Evidenced-based clinical practice guideline for prostate cancer (summary: Japanese Urological Association, 2016 edition)

These guidelines cover a wide range of topics from prostate cancer epidemiology to palliative care. Questions arising in daily clinical practice have been extracted and formulated as clinical questions. In the 4 years since the previous edition, there have been major changes - for example, robot-assisted prostatectomy has rapidly come into widespread use, and new hormones and anticancer drugs have been developed for castration-resistant prostate cancer. In response to these developments, the number of fields included in this guideline was increased from 11 in the 2012 edition to 16, and the number of clinical questions was increased from 63 to 70. The number of papers identified in searches of the existing literature increased from 4662 in the first edition, published in 2006, to 10 490 in the 2012 edition. The number of references has reached 29 448 just during this review period, indicating the exponential increase in research on the topic of prostate cancer. Clinical answers have been prepared based on the latest evidence. Recommendation grades for the clinical answers were determined by radiologists, pathologists, and other specialists in addition to urologists in order to reflect the recent advances and diversity of prostate cancer treatment. Here, we present a short English version of the original guideline, and overview its key clinical issues.

Optimal screening interval for men with low baseline prostate-specific antigen levels (≤1.0 ng/mL) in a prostate cancer screening program

PURPOSE

To optimize the rescreening schedule for men with low baseline prostate-specific antigen (PSA) levels, we evaluated men with baseline PSA levels of ≤1.0 ng/mL in PSA-based population screening.

METHODS

We enrolled 8086 men aged 55-69 years with baseline PSA levels of ≤1.0 ng/mL, who were screened annually. The relationships of baseline PSA and age with the cumulative risks and clinicopathological features of screening-detected cancer were investigated.

RESULTS

Among the 8086 participants, 28 (0.35 %) and 18 (0.22 %) were diagnosed with prostate cancer and cancer with a Gleason score (GS) of ≥7 during the observation period, respectively. The cumulative probabilities of prostate cancer at 12 years were 0.42, 1.0, 3.4, and 4.3 % in men with baseline PSA levels of 0.0-0.4, 0.5-0.6, 0.7-0.8, and 0.9-1.0 ng/mL, respectively. Those with GS of ≥7 had cumulative probabilities of 0.42, 0.73, 2.8, and 1.9 %, respectively. The cumulative probabilities of prostate cancer were significantly lower when baseline PSA levels were 0.0-0.6 ng/mL compared with 0.7-1.0 ng/mL. Prostate cancer with a GS of ≥7 was not detected during the first 10 years of screening when baseline PSA levels were 0.0-0.6 ng/mL and was not detected during the first 2 years when baseline PSA levels were 0.7-1.0 ng/mL.

CONCLUSIONS

Our study demonstrated that men with baseline PSA levels of 0.0-0.6 ng/mL might benefit from longer screening intervals than those recommended in the guidelines of the Japanese Urological Association. Further investigation is needed to confirm the optimal screening interval for men with low baseline PSA levels.

Baseline PSA in a Spanish male population aged 40-49 years anticipates detection of prostate cancer

INTRODUCTION

We researched the usefulness of optimizing prostate cancer (PC) screening in our community using baseline PSA readings in men between 40-49 years of age.

MATERIAL AND METHOD

A retrospective study was performed that analyzed baseline PSA in the fifth decade of life and its ability to predict the development of PC in a population of Madrid (Spain). An ROC curve was created and a cutoff was proposed. We compared the evolution of PSA from baseline in patients with consecutive readings using the Friedman test. We established baseline PSA ranges with different risks of developing cancer and assessed the diagnostic utility of the annual PSA velocity (PSAV) in this population.

RESULTS

Some 4,304 men aged 40-49 years underwent opportunistic screening over the course of 17 years, with at least one serum PSA reading (6,001 readings) and a mean follow-up of 57.1±36.8 months. Of these, 768 underwent biopsy of some organ, and 104 underwent prostate biopsy. Fourteen patients (.33%) were diagnosed with prostate cancer. The median baseline PSA was .74 (.01-58.5) ng/mL for patients without PC and 4.21 (.76-47.4) ng/mL for those with PC. The median time from the reading to diagnosis was 26.8 (1.5-143.8) months. The optimal cutoff for detecting PC was 1.9ng/mL (sensitivity, 92.86%; specificity, 92.54%; PPV, 3.9%; NPV, 99.97%), and the area under the curve was 92.8%. In terms of the repeated reading, the evolution of the PSA showed no statistically significant differences between the patients without cancer (p=.56) and those with cancer (P=.64). However, a PSAV value >.3ng/mL/year revealed high specificity for detecting cancer in this population.

CONCLUSIONS

A baseline PSA level ≥1.9ng/mL in Spanish men aged 40-49 years predicted the development of PC. This value could therefore be of use for opportunistic screening at an early age. An appropriate follow-up adapted to the risk of this population needs to be defined, but an annual PSAV ≥.3ng/mL/year appears of use for reaching an early diagnosis.

A positive family history as a risk factor for prostate cancer in a population-based study with organised prostate-specific antigen screening: results of the Swiss European Randomised Study of Screening for Prostate Cancer (ERSPC, Aarau)

OBJECTIVE

To assess the value of a positive family history (FH) as a risk factor for prostate cancer incidence and grade among men undergoing organised prostate-specific antigen (PSA) screening in a population-based study.

SUBJECTS AND METHODS

The study cohort comprised all attendees of the Swiss arm of the European Randomised Study of Screening for Prostate Cancer (ERSPC) with systematic PSA level tests every 4 years. Men reporting first-degree relative(s) diagnosed with prostate cancer were considered to have a positive FH. Biopsy was exclusively PSA triggered at a PSA level threshold of 3 ng/mL. The primary endpoint was prostate cancer diagnosis. Kaplan-Meier and Cox regression analyses were used.

RESULTS

Of 4 932 attendees with a median (interquartile range, IQR) age of 60.9 (57.6-65.1) years, 334 (6.8%) reported a positive FH. The median (IQR) follow-up duration was 11.6 (10.3-13.3) years. Cumulative prostate cancer incidence was 60/334 (18%, positive FH) and 550/4 598 (12%, negative FH) [odds ratio 1.6, 95% confidence interval (CI) 1.2-2.2, P = 0.001). In both groups, most prostate cancer diagnosed was low grade. There were no significant differences in PSA level at diagnosis, biopsy Gleason score or Gleason score on pathological specimen among men who underwent radical prostatectomy between both groups. On multivariable analysis, age (hazard ratio [HR] 1.04, 95% CI 1.02-1.06), baseline PSA level (HR 1.13, 95% CI 1.12-1.14), and FH (HR 1.6, 95% CI 1.24-2.14) were independent predictors for overall prostate cancer incidence (all P < 0.001). Only baseline PSA level (HR 1.14, 95% CI 1.12-1.16, P < 0.001) was an independent predictor of Gleason score ≥7 prostate cancer on prostate biopsy. The proportion of interval prostate cancer diagnosed in-between the screening rounds was not significantly different.

CONCLUSION

Irrespective of the FH status, the current PSA-based screening setting detects the majority of aggressive prostate cancers and missed only a minority of interval cancers with a 4-year screening algorithm. Our results suggest that men with a positive FH are at increased risk of low-grade but not aggressive prostate cancer.