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Population-based screening showed that men over age 50 with PSA of 3 ng per milliliter or higher and negative MRI results could safely forgo biopsy. Detection of clinically significant cancer among men with positive MRI results who underwent MRI-directed and standard biopsies was similar to that for the standard biopsy group, but the MRI group had fewer findings of clinically insignificant cancers.

In this study, clonal hematopoiesis with somatic mutations was found in 10% of otherwise healthy people older than 65. The risk of hematologic cancer was substantially increased among these persons; in two cases, the subsequent cancer was related to the clone that predated the cancer. The development of disease often involves dynamic processes that begin years or decades before the clinical onset. In many cases, however, the process of pathogenesis goes undetected until after the patient has symptoms and presents with clinically apparent disease. Cancer arises owing to the combined effects of multiple somatic mutations, which are likely to be acquired at different times. 1 Early mutations may be present many years before disease develops. In some models of cancer development, early mutations lead to clonal expansions by stem cells or other progenitor cells. 2 Such clonal expansions greatly increase the likelihood that later, cooperating mutations would . . .

Because more and more men are being diagnosed with prostate cancer worldwide, knowledge about and prevention of this disease is important. Epidemiological studies have provided some insight about the cause of prostate cancer in terms of diet and genetic factors. However, compared with other common cancers such as breast and lung cancer, the causes remain poorly understood. Several important issues could help in our understanding of this disease—the variation in incidence of prostate cancer between ethnic populations and the factors leading to familial clustering of the diseases.

The prostate-specific antigen (PSA) test is used to screen for prostate cancer but has a high false-positive rate that translates into unnecessary prostate biopsies and overdiagnosis of low-risk prostate cancers. We aimed to develop and validate a model to identify high-risk prostate cancer (with a Gleason score of at least 7) with better test characteristics than that provided by PSA screening alone. The Stockholm 3 (STHLM3) study is a prospective, population-based, paired, screen-positive, diagnostic study of men without prostate cancer aged 50–69 years randomly invited by date of birth from the Swedish Population Register kept by the Swedish Tax Agency. Men with prostate cancer at enrolment were excluded from the study. The predefined STHLM3 model (a combination of plasma protein biomarkers [PSA, free PSA, intact PSA, hK2, MSMB, MIC1], genetic polymorphisms [232 SNPs], and clinical variables [age, family, history, previous prostate biopsy, prostate exam]), and PSA concentration were both tested in all participants enrolled. The primary aim was to increase the specificity compared with PSA without decreasing the sensitivity to diagnose high-risk prostate cancer. The primary outcomes were number of detected high-risk cancers (sensitivity) and the number of performed prostate biopsies (specificity). The STHLM3 training cohort was used to train the STHLM3 model, which was prospectively tested in the STHLM3 validation cohort. Logistic regression was used to test for associations between biomarkers and clinical variables and prostate cancer with a Gleason score of at least 7. This study is registered with ISCRTN.com, number ISRCTN84445406. The STHLM3 model performed significantly better than PSA alone for detection of cancers with a Gleason score of at least 7 (p<0·0001), the area under the curve was 0·56 (95% CI 0·55–0·60) with PSA alone and 0·74 (95% CI 0·72–0·75) with the STHLM3 model. All variables used in the STHLM3 model were significantly associated with prostate cancers with a Gleason score of at least 7 (p<0·05) in a multiple logistic regression model. At the same level of sensitivity as the PSA test using a cutoff of ≥3 ng/mL to diagnose high risk prostate cancer, use of the STHLM3 model could reduce the number of biopsies by 32% (95% CI 24–39) and could avoid 44% (35–54) of benign biopsies. The STHLM3 model could reduce unnecessary biopsies without compromising the ability to diagnose prostate cancer with a Gleason score of at least 7, and could be a step towards personalised risk-based prostate cancer diagnostic programmes. Stockholm County Council (Stockholms Läns Landsting).

An increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatment and undertreatment of prostate cancer. To alleviate these problems, we aimed to develop an artificial intelligence (AI) system with clinically acceptable accuracy for prostate cancer detection, localisation, and Gleason grading. We digitised 6682 slides from needle core biopsies from 976 randomly selected participants aged 50–69 in the Swedish prospective and population-based STHLM3 diagnostic study done between May 28, 2012, and Dec 30, 2014 (ISRCTN84445406), and another 271 from 93 men from outside the study. The resulting images were used to train deep neural networks for assessment of prostate biopsies. The networks were evaluated by predicting the presence, extent, and Gleason grade of malignant tissue for an independent test dataset comprising 1631 biopsies from 246 men from STHLM3 and an external validation dataset of 330 biopsies from 73 men. We also evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology. We assessed discriminatory performance by receiver operating characteristics and tumour extent predictions by correlating predicted cancer length against measurements by the reporting pathologist. We quantified the concordance between grades assigned by the AI system and the expert urological pathologists using Cohen's kappa. The AI achieved an area under the receiver operating characteristics curve of 0·997 (95% CI 0·994–0·999) for distinguishing between benign (n=910) and malignant (n=721) biopsy cores on the independent test dataset and 0·986 (0·972–0·996) on the external validation dataset (benign n=108, malignant n=222). The correlation between cancer length predicted by the AI and assigned by the reporting pathologist was 0·96 (95% CI 0·95–0·97) for the independent test dataset and 0·87 (0·84–0·90) for the external validation dataset. For assigning Gleason grades, the AI achieved a mean pairwise kappa of 0·62, which was within the range of the corresponding values for the expert pathologists (0·60–0·73). An AI system can be trained to detect and grade cancer in prostate needle biopsy samples at a ranking comparable to that of international experts in prostate pathology. Clinical application could reduce pathology workload by reducing the assessment of benign biopsies and by automating the task of measuring cancer length in positive biopsy cores. An AI system with expert-level grading performance might contribute a second opinion, aid in standardising grading, and provide pathology expertise in parts of the world where it does not exist. Swedish Research Council, Swedish Cancer Society, Swedish eScience Research Center, EIT Health.

Screening for prostate cancer using prostate-specific antigen (PSA) reduces prostate cancer mortality but can lead to adverse outcomes. We aimed to compare a traditional screening approach with a diagnostic strategy of blood-based risk prediction combined with MRI-targeted biopsies. We did a prospective, population-based, randomised, open-label, non-inferiority trial (STHLM3-MRI) in Stockholm county, Sweden. Men aged 50–74 years were randomly selected by Statistics Sweden and invited by mail to participate in screening; those with an elevated risk of prostate cancer, defined as either a PSA of 3 ng/mL or higher or a Stockholm3 score of 0·11 or higher were eligible for randomisation. Men with a previous prostate cancer diagnosis, who had undergone a prostate biopsy within 60 days before the invitation to participate, with a contraindication for MRI, or with severe illness were excluded. Eligible participants were randomly assigned (2:3) using computer-generated blocks of five, stratified by clinically significant prostate cancer risk, to receive either systematic prostate biopsies (standard group) or biparametric MRI followed by MRI-targeted and systematic biopsy in MRI-positive participants (experimental group). The primary outcome was the detection of clinically significant prostate cancer at prostate biopsy, defined as a Gleason score of 3 + 4 or higher. We used a margin of 0·78 to assess non-inferiority for the primary outcome. Key secondary outcome measures included the proportion of men with clinically insignificant prostate cancer (defined as a Gleason score of 3 + 3), and the number of any prostate MRI and biopsy procedures done. We did two comparisons: Stockholm3 (using scores of 0·11 and 0·15 as cutoffs) versus PSA in the experimental group (paired analyses) and PSA plus standard biopsy versus Stockholm3 plus MRI-targeted and systematic biopsy (unpaired, randomised analyses). All analyses were intention to treat. This study is registered with ClinicalTrials.gov, NCT03377881. Between Feb 5, 2018, and March 4, 2020, 49 118 men were invited to participate, of whom 12 750 were enrolled and provided blood specimens, and 2293 with elevated risk were randomly assigned to the experimental group (n=1372) or the standard group (n=921). The area under the receiver-operating characteristic curve for detection of clinically significant prostate cancer was 0·76 (95% CI 0·72–0·80) for Stockholm3 and 0·60 (0·54–0·65) for PSA. In the experimental group, a Stockholm3 of 0·11 or higher was non-inferior to a PSA of 3 ng/mL or higher for detection of clinically significant prostate cancer (227 vs 192; relative proportion [RP] 1·18 [95% CI 1·09–1·28], p<0·0001 for non-inferiority), and also detected a similar number of low-grade prostate cancers (50 vs 41; 1·22 [0·96–1·55], p=0·053 for superiority) and was associated with more MRIs and biopsies. Compared with PSA of 3 ng/mL or higher, a Stockholm3 of 0·15 or higher provided identical sensitivity to detect clinically significant cancer, and led to fewer MRI procedures (545 vs 846; 0·64 [0·55–0·82]) and fewer biopsy procedures (311 vs 338; 0·92 (0·86–1·03). Compared with screening using PSA and systematic biopsies, a Stockholm3 of 0·11 or higher combined with MRI-targeted and systematic biopsies was associated with higher detection of clinically significant cancers (227 [3·0%] men tested vs 106 [2·1%] men tested; RP 1·44 [95% CI 1·15–1·81]), lower detection of low-grade cancers (50 [0·7%] vs 73 [1·4%]; 0·46 [0·32–0·66]), and led to fewer biopsy procedures. Patients randomly assigned to the experimental group had a lower incidence of prescription of antibiotics for infection (25 [1·8%] of 1372 vs 41 [4·4%] of 921; p=0·0002) and a lower incidence of admission to hospital (16 [1·2%] vs 31 [3·4%]; p=0·0003) than those in the standard group. The Stockholm3 test can inform risk stratification before MRI and targeted biopsies in prostate cancer screening. Combining the Stockholm3 test with an MRI-targeted biopsy approach for prostate cancer screening decreases overdetection while maintaining the ability to detect clinically significant cancer. The Swedish Cancer Society, the Swedish Research Council, and Stockholm City Council.

PurposeTo evaluate clinical variables, including magnetic resonance imaging (MRI) predictive of adverse pathology (AP) at radical prostatectomy (RP) in men initially enrolled in active surveillance (AS).MethodsA population-based cohort study of men diagnosed with low-risk prostate cancer (PCa), in Stockholm County, Sweden, during 2008–2017 enrolled in AS their intended primary treatment followed by RP. AP was defined as ISUP grade group  ≥ 3 and/or pT-stage ≥ T3. Association between clinical variables at diagnosis and time to AP was evaluated using Cox regression and multivariate logistic regression to evaluate the association between AP and clinical variables at last biopsy before RP.ResultsIn a cohort of 6021 patients with low-risk PCa, 3116 were selected for AS and 216 underwent RP. Follow-up was 10 years, with a median time on AS of 23 months. 37.7% of patients had AP at RP. Clinical T-stage [Hazard ratio (HR): 1.81, 95% confidence interval (CI) 1.04–3.18] and PSA (HR: 1.31, 95% CI 1.17–1.46) at diagnosis and age [Odds Ratio (OR): 1.09, 95% CI 1.02–1.18), PSA (OR: 1.22, 95% CI 1.07–1.41), and PI-RADS (OR 1.66, 95% CI 1.11–2.55)] at last re-biopsy were significantly associated with AP.ConclusionPI-RADS score is significantly associated with AP at RP and support current guidelines recommending MRI before enrollment in AS. Furthermore, age, cT-stage, and PSA are significantly associated with AP.

Key Points Prostate cancer is the most common form of non-skin cancer in men in developed countries. The cause(s) of prostate cancer have not yet been clarified. Although heritable factors are implicated, immigration studies indicate that environmental exposures are also important. Chronic infection and inflammation cause cancer in several organs including the stomach, liver and large intestine. Data from histopathological, molecular histopathological, epidemiological and genetic epidemiological studies show that chronic inflammation might also be important in prostate carcinogenesis. The source of intraprostatic inflammation is often unknown, but might be caused by infection (for example, with sexually transmitted agents), cell injury (owing to exposure to chemical and physical trauma from urine reflux and prostatic calculi formation), hormonal variations and/or exposures, or dietary factors such as charred meats. The resultant epithelial cellular injury might cause a loss of tolerance to normal prostatic antigens, resulting in a self-perpetuating autoimmune reaction. Exposures to infectious agents and dietary carcinogens are postulated to directly injure the prostate epithelium, resulting in the histological lesions known as proliferative inflammatory atrophy (PIA), or proliferative atrophy. These lesions are postulated to be a manifestation of the 'field effect' caused by environmental exposures. Despite a strong genetic component to prostate cancer risk, no highly penetrant hereditary prostate cancer genes have been uncovered to date. Although complex, genetic variation in inflammatory genes is associated with prostate cancer risk. Several challenges remain regarding the inflammation hypothesis in prostate cancer, including the determination of the cause(s) of chronic inflammation in the prostate, an understanding of the cellular and molecular biology of the immune response in the prostate, whether inflammatory cells are truly causative in the process, and the determination of the target cell types within the proposed precursor lesions of prostate cancer. The refinement and application of new epidemiological approaches, including high-throughput genetic epidemiology, improved rodent models of prostate inflammation and cancer, and advances in the application of molecular techniques to histopathological studies should provide insights into the cause of prostate inflammation and its relevance to prostate carcinogenesis. Recent evidence indicates that both endogenous and environmental factors induce prostate inflammatory lesions that are proposed to increase the risk of cancer development. This Review explores different approaches aimed at clarifying whether inflammation drives prostate cancer and could be used to develop new prevention strategies. About 20% of all human cancers are caused by chronic infection or chronic inflammatory states. Recently, a new hypothesis has been proposed for prostate carcinogenesis. It proposes that exposure to environmental factors such as infectious agents and dietary carcinogens, and hormonal imbalances lead to injury of the prostate and to the development of chronic inflammation and regenerative 'risk factor' lesions, referred to as proliferative inflammatory atrophy (PIA). By developing new experimental animal models coupled with classical epidemiological studies, genetic epidemiological studies and molecular pathological approaches, we should be able to determine whether prostate cancer is driven by inflammation, and if so, to develop new strategies to prevent the disease.

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing. Metastatic castration-resistant prostate cancer is a highly aggressive disease, with a variable response to treatment. Here, the authors validate ctDNA fraction as a poor prognostic factor and develop a model to predict whether patients harbor sufficient ctDNA for informative blood-based genotyping.

Importance Stratifying patients with biochemical recurrence (BCR) after primary treatment for prostate cancer based on the risk of prostate cancer–specific mortality (PCSM) is essential for determining the need for further testing and treatments. Objective To evaluate the association of BCR after radical prostatectomy or radiotherapy and its current risk stratification with PCSM. Design, Setting, and Participants This population-based cohort study included a total of 16 311 male patients with 10 364 (64%) undergoing radical prostatectomy and 5947 (36%) undergoing radiotherapy with curative intent (cT1-3, cM0) and PSA follow-up in Stockholm, Sweden, between 2003 and 2019. Follow-up for all patients was until death, emigration, or end of the study (ie, December 31, 2018). Data were analyzed between September 2022 and March 2023. Main Outcomes and Measures Primary outcomes of the study were the cumulative incidence of BCR and PCSM. Patients with BCR were stratified in low- and high-risk according to European Association of Urology (EAU) criteria. Exposures Radical prostatectomy or radiotherapy. Results A total of 16 311 patients were included. Median (IQR) age was 64 (59-68) years in the radical prostatectomy cohort (10 364 patients) and 69 (64-73) years in the radiotherapy cohort (5947 patients). Median (IQR) follow-up for survivors was 88 (55-138) months and 89 (53-134) months, respectively. Following radical prostatectomy, the 15-year cumulative incidences of BCR were 16% (95% CI, 15%-18%) for the 4024 patients in the low D’Amico risk group, 30% (95% CI, 27%-32%) for the 5239 patients in the intermediate D’Amico risk group, and 46% (95% CI, 42%-51%) for 1101 patients in the high D’Amico risk group. Following radiotherapy, the 15-year cumulative incidences of BCR were 18% (95% CI, 15%-21%) for the 1230 patients in the low-risk group, 24% (95% CI, 21%-26%) for the 2355 patients in the intermediate-risk group, and 36% (95% CI, 33%-39%) for the 2362 patients in the high-risk group. The 10-year cumulative incidences of PCSM after radical prostatectomy were 4% (95% CI, 2%-6%) for the 1101 patients who developed low-risk EAU-BCR and 9% (95% CI, 5%-13%) for 649 patients who developed high-risk EAU-BCR. After radiotherapy, the 10-year PCSM cumulative incidences were 24% (95% CI, 19%-29%) for the 591 patients in the low-risk EAU-BCR category and 46% (95% CI, 40%-51%) for the 600 patients in the high-risk EAU-BCR category. Conclusions and Relevance These findings suggest the validity of EAU-BCR stratification system. However, while the risk of dying from prostate cancer in low-risk EAU-BCR after radical prostatectomy was very low, patients who developed low-risk EAU-BCR after radiotherapy had a nonnegligible risk of prostate cancer mortality. Improving risk stratification of patients with BCR is pivotal to guide salvage treatment decisions, reduce overtreatment, and limit the number of staging tests in the event of PSA elevations after primary treatment.