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Background: An electronic health record-based tool could improve accuracy and eliminate bias in provider estimation of the risk of death from other causes among men with nonmetastatic cancer., Objective: To recalibrate and validate the Veterans Aging Cohort Study Charlson Comorbidity Index (VACS-CCI) to predict non-prostate cancer mortality (non-PCM) and to compare it with a tool predicting prostate cancer mortality (PCM)., Design, Setting, and Participants: An observational cohort of men with biopsy-confirmed nonmetastatic prostate cancer, enrolled from 2001 to 2018 in the national US Veterans Health Administration (VA), was divided by the year of diagnosis into the development (2001-2006 and 2008-2018) and validation (2007) sets., Outcome Measurements and Statistical Analysis: Mortality (all cause, non-PCM, and PCM) was evaluated. Accuracy was assessed using calibration curves and C statistic in the development, validation, and combined sets; overall; and by age (<65 and 65+ yr), race (White and Black), Hispanic ethnicity, and treatment groups., Results and Limitations: Among 107 370 individuals, we observed 24 977 deaths (86% non-PCM). The median age was 65 yr, 4947 were Black, and 5010 were Hispanic. Compared with CCI and age alone (C statistic 0.67, 95% confidence interval [CI] 0.67-0.68), VACS-CCI demonstrated improved validated discrimination (C statistic 0.75, 95% CI 0.74-0.75 for non-PCM). The prostate cancer mortality tool also discriminated well in validation (C statistic 0.81, 95% CI 0.78-0.83). Both were well calibrated overall and within subgroups. Owing to missing data, 18 009/125 379 (14%) were excluded, and VACS-CCI should be validated outside the VA prior to outside application., Conclusions: VACS-CCI is ready for implementation within the VA. Electronic health record-assisted calculation is feasible, improves accuracy over age and CCI alone, and could mitigate inaccuracy and bias in provider estimation., Patient Summary: Veterans Aging Cohort Study Charlson Comorbidity Index is ready for application within the Veterans Health Administration. Electronic health record-assisted calculation is feasible, improves accuracy over age and Charlson Comorbidity Index alone, and might help mitigate inaccuracy and bias in provider estimation of the risk of non-prostate cancer mortality., (Published by Elsevier B.V.)

Background: Screening is not recommended for prostate cancer in the UK. Asymptomatic men aged ≥50 years can request a prostate-specific antigen (PSA) test following counselling on potential harms and benefits. There are areas of clinical uncertainty among GPs, resulting in the content and quality of counselling varying., Aim: To produce a consensus that can influence guidelines for UK primary care on the optimal use of the PSA test in asymptomatic men for early prostate cancer detection., Design and Setting: Prostate Cancer UK facilitated a RAND/UCLA consensus., Method: Statements covering five topics were developed with a subgroup of experts. A panel of 15 experts in prostate cancer scored (round one) statements on a scale of one (strongly disagree) to nine (strongly agree). Panellists met to discuss statements before rescoring (round two). A lived experience panel of seven men scored a subset of statements with outcomes fed into the main panel., Results: Of the initial 94 statements reviewed by the expert panel, a final 48/85 (56%) achieved consensus. In the absence of screening, there was consensus on proactive approaches to initiate discussions about the PSA test with men who were at higher-than-average risk., Conclusion: Improvements in the prostate cancer diagnostic pathway may have reduced some of the harms associated with PSA testing; however, several areas of uncertainty remain in relation to screening, including optimal PSA thresholds for referral and intervals for retesting. There is consensus on proactive approaches to testing in higher-than-average risk groups. This should prompt a review of current guidelines., (© The Authors.)

Hyperpolarised magnetic resonance imaging (HP- 13 C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1- 13 C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1- 13 C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1- 13 C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer., (© 2024. The Author(s).)

Prostate cancer screening using prostate-specific antigen (PSA) has been shown to reduce mortality but with substantial overdiagnosis, leading to unnecessary biopsies. The identification of a highly specific biomarker using liquid biopsies, represents an unmet need in the diagnostic pathway for prostate cancer. In this study, we employed a method that enriches for methylated cell-free DNA fragments coupled with a machine learning algorithm which enabled the detection of metastatic and localized cancers with AUCs of 0.96 and 0.74, respectively. The model also detected 51.8% (14/27) of localized and 88.7% (79/89) of patients with metastatic cancer in an external dataset. Furthermore, we show that the differentially methylated regions reflect epigenetic and transcriptomic changes at the tissue level. Notably, these regions are significantly enriched for biologically relevant pathways associated with the regulation of cellular proliferation and TGF-beta signaling. This demonstrates the potential of circulating tumor DNA methylation for prostate cancer detection and prognostication., Competing Interests: The authors do not claim any competing interest in this work., (© 2024 The Authors.)

Competing Interests: The authors declare no conflicts of interest.

While radical prostatectomy remains the mainstay of prostate cancer (PCa) treatment, 20 to 40% of patients develop postsurgical biochemical recurrence (BCR). A particularly challenging clinical cohort includes patients with intermediate-risk disease whose risk stratification would benefit from advanced approaches that complement standard-of-care diagnostic tools. Here, we show that imaging tumor lactate using hyperpolarized 13 C MRI and spatial metabolomics identifies BCR-positive patients in two prospective intermediate-risk surgical cohorts. Supported by spatially resolved tissue analysis of established glycolytic biomarkers, this study provides the rationale for multicenter trials of tumor metabolic imaging as an auxiliary tool to support PCa treatment decision-making., Competing Interests: Competing interests statement:G.H., J.R., S.T.B., and R.J.A.G. are AstraZeneca employees.

Introduction: Modern image-guided biopsy pathways at diagnostic centres have greatly refined the investigations of men referred with suspected prostate cancer. However, the referral criteria from primary care are still based on historical prostate-specific antigen (PSA) cut-offs and age-referenced thresholds. Here, we tested whether better contemporary pathways and biopsy methods had improved the predictive utility value of PSA referral thresholds., Methods: PSA referral thresholds, age-referenced ranges and PSA density (PSAd) were assessed for positive predictive value (PPV) in detection of clinically significant prostate cancer (csPCa - histological ⩾ Grade Group 2). Data were analysed from men referred to three diagnostics centres who used multi-parametric magnetic resonance imaging (mpMRI)-guided prostate biopsies for disease characterisation. Findings were validated in a separate multicentre cohort. Results: Data from 2767 men were included in this study. The median age, PSA and PSAd were 66.4 years, 7.3 ng/mL and 0.1 ng/mL 2 , respectively. Biopsy detected csPCa was found in 38.7%. The overall area under the curve (AUC) for PSA was 0.68 which is similar to historical performance. A PSA threshold of ⩾ 3 ng/mL had a PPV of 40.3%, but this was age dependent (PPV: 24.8%, 32.7% and 56.8% in men 50-59 years, 60-69 years and ⩾ 70 years, respectively). Different PSA cut-offs and age-reference ranges failed to demonstrate better performance. PSAd demonstrated improved AUC (0.78 vs 0.68, p < 0.0001) and improved PPV compared to PSA. A PSAd of ⩾ 0.10 had a PPV of 48.2% and similar negative predictive value (NPV) to PSA ⩾ 3 ng/mL and out-performed PSA age-reference ranges. This improved performance was recapitulated in a separate multi-centre cohort ( n = 541)., Conclusion: The introduction of MRI-based image-guided biopsy pathways does not appear to have altered PSA diagnostic test characteristics to positively detect csPCa. We find no added value to PSA age-referenced ranges, while PSAd offers better PPV and the potential for a single clinically useful threshold (⩾0.10) for all age groups., Level of Evidence: IV., Competing Interests: Conflicting interests The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Serial MRI is an essential assessment tool in prostate cancer (PCa) patients enrolled on active surveillance (AS). However, it has only moderate sensitivity for predicting histopathological tumour progression at follow-up, which is in part due to the subjective nature of its clinical reporting and variation among centres and readers. In this study, we used a long short-term memory (LSTM) recurrent neural network (RNN) to develop a time series radiomics (TSR) predictive model that analysed longitudinal changes in tumour-derived radiomic features across 297 scans from 76 AS patients, 28 with histopathological PCa progression and 48 with stable disease. Using leave-one-out cross-validation (LOOCV), we found that an LSTM-based model combining TSR and serial PSA density (AUC 0.86 [95% CI: 0.78-0.94]) significantly outperformed a model combining conventional delta-radiomics and delta-PSA density (0.75 [0.64-0.87]; p = 0.048) and achieved comparable performance to expert-performed serial MRI analysis using the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) scoring system (0.84 [0.76-0.93]; p = 0.710). The proposed TSR framework, therefore, offers a feasible quantitative tool for standardising serial MRI assessment in PCa AS. It also presents a novel methodological approach to serial image analysis that can be used to support clinical decision-making in multiple scenarios, from continuous disease monitoring to treatment response evaluation. KEY POINTS: •LSTM RNN can be used to predict the outcome of PCa AS using time series changes in tumour-derived radiomic features and PSA density. •Using all available TSR features and serial PSA density yields a significantly better predictive performance compared to using just two time points within the delta-radiomics framework. •The concept of TSR can be applied to other clinical scenarios involving serial imaging, setting out a new field in AI-driven radiology research., (© 2023. The Author(s).)

Background: Active surveillance (AS) is a major management option for men with early prostate cancer. Current guidelines however advocate identical AS follow-up for all without considering different disease trajectories. We previously proposed a pragmatic three-tier STRATified CANcer Surveillance (STRATCANS) follow-up strategy based on different progression risks from clinic-pathological and imaging features., Objective: To report early outcomes from the implementation of the STRATCANS protocol in our centre., Design Setting and Participants: Men on AS were enrolled into a prospective stratified follow-up programme., Intervention: Three tiers of increasing follow-up intensity based on National Institute for Health and Care Excellence (NICE): Cambridge Prognostic Group (CPG) 1 or 2, prostate-specific antigen density, and magnetic resonance imaging (MRI) Likert score at entry., Outcome Measurements and Statistical Analysis: Rates of progression to CPG ≥3, any pathological progression, AS attrition, and patient choice for treatment were assessed. Differences in progression were compared with chi-square statistics., Results and Limitations: Data from 156 men (median age 67.3 yr) were analysed. Of these, 38.4% had CPG2 disease and 27.5% had grade group 2 disease at diagnosis. The median time on AS was 4 yr (interquartile range 3.2-4.9) and 1.5 yr on STRATCANS. Overall, 135/156 (86.5%) men remained on AS or converted to watchful waiting and 6/156 (3.8%) stopped AS by choice by the end of the evaluation period. Of the 156 patients, 66 (42.3%) were allocated to STRATCANS 1 (least intense follow-up), 61 (39.1%) to STRATCANS 2, and 29 (18.6%) to STRATCANS 3 (highest intensity). By increasing STRATCANS tier, progression rates to CPG ≥3 and any progression events were 0% and 4.6%, 3.4% and 8.6%, and 7.4% and 22.2%, respectively ( p = 0.019). Modelling resource usage suggested potential reductions in appointments by 22% and MRI by 42% compared with current NICE guideline recommendations (first 12 months of AS). The study is limited by short follow-up, a relatively small cohort, and being single centre., Conclusions: A simple risk-tiered AS strategy is possible with early outcomes supporting stratified follow-up intensity. STRATCANS implementation could de-escalate follow-up in men at a low risk of progression while husbanding resources for those who need closer follow-up., Patient Summary: We report a practical way to personalise follow-up for men on active surveillance for early prostate cancer. Our method may allow reductions in the follow-up burden for men at a low risk of disease change while maintaining vigilance for those at a higher risk., (© 2023 The Author(s).)

For men with newly diagnosed prostate cancer, we aimed to develop and validate a model to predict the risk of progression on active surveillance (AS), which could inform more personalised AS strategies. In total, 883 men from 3 European centres were used for model development and internal validation, and 151 men from a fourth European centre were used for external validation. Men with Cambridge Prognostic Group (CPG) 1-2 disease at diagnosis were eligible. The endpoint was progression to the composite endpoint of CPG3 disease or worse (≥CPG3). Model performance at 4 years was evaluated through discrimination (C-index), calibration plots, and decision curve analysis. The final multivariable model incorporated prostate-specific antigen (PSA), Grade Group, magnetic resonance imaging (MRI) score (Prostate Imaging Reporting & Data System (PI-RADS) or Likert), and prostate volume. Calibration and discrimination were good in both internal validation (C-index 0.742, 95% CI 0.694-0.793) and external validation (C-index 0.845, 95% CI 0.712-0.958). In decision curve analysis, the model offered net benefit compared to a 'follow-all' strategy at risk thresholds of ≥0.08 and ≥0.04 in development and external validation, respectively. In conclusion, our model demonstrated good accuracy and clinical utility in predicting the progression on AS at 4 years post-diagnosis. Men with lower risk predictions could subsequently be offered less-intense surveillance. Further external validation in larger cohorts is now required.

Clinical management of prostate cancer is challenging because of its highly variable natural history and so there is a need for improved predictors of outcome in non-metastatic men at the time of diagnosis. In this study we calculated the model score from the leading clinical multivariable model, PREDICT prostate, and the poor prognosis DESNT molecular subtype, in a combined expression and clinical dataset that were taken from malignant tissue at prostatectomy (n = 359). Both PREDICT score (p < 0.0001, IQR HR = 1.59) and DESNT score (p < 0.0001, IQR HR = 2.08) were significant predictors for time to biochemical recurrence. A joint model combining the continuous PREDICT and DESNT score (p < 0.0001, IQR HR = 1.53 and 1.79, respectively) produced a significantly improved predictor than either model alone (p < 0.001). An increased probability of mortality after diagnosis, as estimated by PREDICT, was characterised by upregulation of cell-cycle related pathways and the downregulation of metabolism and cholesterol biosynthesis. The DESNT molecular subtype has distinct biological characteristics to those associated with the PREDICT model. We conclude that the inclusion of biological information alongside current clinical prognostic tools has the potential to improve the ability to choose the optimal treatment pathway for a patient.

Purpose: To investigate the accuracy of surface-based ultrasound-derived PSA-density (US-PSAD) versus gold-standard MRI-PSAD as a risk-stratification tool., Methods: Single-centre prospective study of patients undergoing MRI for suspected prostate cancer (PCa). Four combinations of US-volumes were calculated using transperineal (TP) and transabdominal (TA) views, with triplanar measurements to calculate volume and US-PSAD. Intra-class correlation coefficient (ICC) was used to compare US and MRI volumes. Categorical comparison of MRI-PSAD and US-PSAD was performed at PSAD cut-offs <0.15, 0.15-0.20, and >0.20 ng/mL2 to assess agreement with MRI-PSAD risk-stratification decisions., Results: 64 men were investigated, mean age 69 years and PSA 7.0 ng/mL. 36/64 had biopsy-confirmed prostate cancer (18 Gleason 3+3, 18 Gleason ≥3+4). Mean MRI-derived gland volume was 60 mL, compared to 56 mL for TA-US, and 65 mL TP-US. ICC demonstrated good agreement for all US volumes with MRI, with highest agreement for transabdominal US, followed by combined TA/TP volumes. Risk-stratification decisions to biopsy showed concordant agreement between triplanar MRI-PSAD and ultrasound-PSAD in 86-91% and 92-95% at PSAD thresholds of >0.15 ng/mL2 and >0.12 ng/mL2, respectively. Decision to biopsy at threshold >0.12 ng/mL2, demonstrated sensitivity ranges of 81-100%, specificity 85-100%, PPV 86-100% and NPV 83-100%. Transabdominal US provided optimal sensitivity of 100% for this clinical decision, with specificity 85%, and transperineal US provided optimal specificity of 100%, with sensitivity 87%., Conclusion: Transperineal-US and combined TA-TP US-derived PSA density values compare well with standard MRI-derived values and could be used to provide accurate PSAD at presentation and inform the need for further investigations., Competing Interests: The authors have declared that no competing interests exist.

Introduction: Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population., Patient and Methods: Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm., Results: Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years' respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years' time frame)., Conclusion: MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available., (© 2022. The Author(s).)

Active Surveillance (AS) for prostate cancer is a management option that continually monitors early disease and considers intervention if progression occurs. A robust method to incorporate "live" updates of progression risk during follow-up has hitherto been lacking. To address this, we developed a deep learning-based individualised longitudinal survival model using Dynamic-DeepHit-Lite (DDHL) that learns data-driven distribution of time-to-event outcomes. Further refining outputs, we used a reinforcement learning approach (Actor-Critic) for temporal predictive clustering (AC-TPC) to discover groups with similar time-to-event outcomes to support clinical utility. We applied these methods to data from 585 men on AS with longitudinal and comprehensive follow-up (median 4.4 years). Time-dependent C-indices and Brier scores were calculated and compared to Cox regression and landmarking methods. Both Cox and DDHL models including only baseline variables showed comparable C-indices but the DDHL model performance improved with additional follow-up data. With 3 years of data collection and 3 years follow-up the DDHL model had a C-index of 0.79 (±0.11) compared to 0.70 (±0.15) for landmarking Cox and 0.67 (±0.09) for baseline Cox only. Model calibration was good across all models tested. The AC-TPC method further discovered 4 distinct outcome-related temporal clusters with distinct progression trajectories. Those in the lowest risk cluster had negligible progression risk while those in the highest cluster had a 50% risk of progression by 5 years. In summary, we report a novel machine learning approach to inform personalised follow-up during active surveillance which improves predictive power with increasing data input over time., (© 2022. The Author(s).)

Background: Prostate cancer is an epidemic of the modern age, and despite efforts to improve awareness, it remains the case that mortality has hardly altered over the decades, driven largely by late presentation. There is a strong public perception that male urinary symptoms is one of the key indicators of prostate cancer, and this continues to be part of messaging from national guidelines and media health campaigns. This narrative, however, is not based on evidence and may be seriously hampering efforts to encourage early presentation., Discussion: Anatomically, prostate cancer most often arises in the peripheral zone, while urinary symptoms result from compression of the urethra by prostatic enlargement more centrally. Biopsy studies show that mean prostate volume is actually lower in men found to have (early) prostate cancer compared to those with benign biopsies. This inverse relationship between prostate size and the probability of cancer is so strong that PSA density (PSA corrected for prostate volume) is known to be significantly more accurate in predicting a positive biopsy than PSA alone. Thus, this disconnect between scientific evidence and the current perception is very striking. There is also evidence that using symptoms for investigating possible cancer may lead to higher proportions of men presenting with locally advanced or metastatic disease compared to PSA testing or screening programmes. Concerns about overwhelming health care services if men are encouraged to get tested without symptoms may also be overstated, with recent newer approaches to reduce over-investigation and treatment. In this article, we explore the link between urinary symptoms and prostate cancer and propose that public and professional messaging needs to change., Conclusion: If rates of earlier diagnosis are to improve, we call for strong clear messaging that prostate cancer is a silent disease especially in the curable stages and men should come forward for testing regardless of whether or not they have symptoms. This should be done in parallel with other ongoing efforts to raise awareness including targeting men at highest risk due to racial ancestry or family history. While the current resurgence in interest and debate about prostate cancer screening is timely, change of this message by guideline bodies, charities and the media can be a first simple step to improving earlier presentation and hence cures rates., (© 2022. The Author(s).)

European and American guidelines recommend abdominal computed tomography (CT) and bone scans for staging of high-risk prostate cancer (PC). To improve clinical risk stratification of nonmetastatic PC a new, five-tier risk classification system has been developed, the Cambridge Prognostic Groups (CPG), in which "high-risk" PC is divided into favourable CPG 4 and unfavourable CPG 5. We used the National Prostate Cancer Register of Sweden (NPCR) to define the rates of positive CT and bone scan findings among men with CPG 4 or 5 cancer. Among men with CPG 4 and prostate-specific antigen (PSA) <50 ng/ml, only 3.6% (95% confidence interval 2.9-4.5%) of the CT scans showed regional lymph-node metastasis (N1M0), while 6.2% (95% confidence interval 5.4-7.0%) of the bone scans were positive. Rates for both were higher in the subgroups with PSA 50-99 ng/ml (10% and 15%) and with CPG 5 disease. The low positivity rate questions routine use of CT for men with CPG 4 cancer and PSA <50 ng/ml, particularly considering the poor sensitivity and specificity for detection of lymph node metastasis. The positivity rate was higher for bone scans, and as current clinical practice relies on trials using bone scans for staging (eg, to define low- versus high-volume metastatic disease), continued routine use of bone scans seems justified., Patient Summary: Our analysis of data from the National Prostate Cancer Register of Sweden showed that for men with favourable high-risk prostate cancer (Cambridge Prognostic Group 4), the rate of positive computed tomography (CT) scans was low. This result suggests that CT scans may not be necessary for detecting cancer spread in men with Cambridge Prognostic Group 4 prostate cancer ., (© 2022 The Author(s).)

Objective: Currently the National Institute for Health and Care Excellence (NICE) recommends an abnormal digital rectal examination (DRE) as a standalone referral criterion for suspected prostate cancer. Unlike referrals for a raised prostate-specific antigen (PSA) which are triaged directly to magnetic resonance imaging (MRI), an abnormal DRE requires re-examination in a secondary clinic first. Here, we investigated the ongoing value of the abnormal DRE as a referral criterion., Methods: This study is a retrospective review of patients referred to secondary care for suspected prostate cancer based on an abnormal DRE over a 15-month period at a single UK hospital ( n = 158). Age, PSA, primary and repeat DRE findings and eventual diagnosis were collated., Results: A concurrent raised PSA was present in 65/158 (41%). Concordance between primary and secondary care DRE was only 72/158 (46%). The overall and significant cancer detection rate was 26/158 (16%) and 22/158 (14%), respectively. Among men with a concurrent raised PSA, 19/65 (29%) had significant cancer found, whereas with an abnormal primary care DRE and normal PSA ( n = 93), only 3/93 (3%) had a significant cancer. Mandating a PSA before referral for an abnormal DRE would have redirected 65/158 (41%) of men to MRI first, negating the need for a repeat DRE ( p < 0.0001). This finding was recapitulated in a second prospective validation cohort ( n = 30) with 9/30 (30%) redirected to MRI first., Conclusions: This is one of the first studies to investigate the value of the DRE in contemporary practice. We propose that PSA is used to triage men with an abnormal DRE to MRI without needing a repeat DRE. If the PSA is normal, the diagnostic yield is low but may still warrant a repeat DRE to assess the need for further investigations. Additional multicentre studies are required to further validate our findings., Level of Evidence: 4., Competing Interests: Conflicting interests The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Objective: To analyse serial changes in MRI-derived tumour measurements and apparent diffusion coefficient (ADC) values in prostate cancer (PCa) patients on active surveillance (AS) with and without histopathological disease progression., Methods: This study included AS patients with biopsy-proven PCa with a minimum of two consecutive MR examinations and at least one repeat targeted biopsy. Tumour volumes, largest axial two-dimensional (2D) surface areas, and maximum diameters were measured on T 2 weighted images ( T 2 WI). ADC values were derived from the whole lesions, 2D areas, and small-volume regions of interest (ROIs) where tumours were most conspicuous. Areas under the ROC curve (AUCs) were calculated for combinations of T 2 WI and ADC parameters with optimal specificity and sensitivity., Results: 60 patients (30 progressors and 30 non-progressors) were included. In progressors, T 2 WI-derived tumour volume, 2D surface area, and maximum tumour diameter had a median increase of +99.5%,+55.3%, and +21.7% compared to +29.2%,+8.1%, and +6.9% in non-progressors ( p < 0.005 for all). Follow-up whole-volume and small-volume ROIs ADC values were significantly reduced in progressors (-11.7% and -9.5%) compared to non-progressors (-6.1% and -1.6%) ( p < 0.05 for both). The combined AUC of a relative increase in maximum tumour diameter by 20% and reduction in small-volume ADC by 10% was 0.67., Conclusion: AS patients show significant differences in tumour measurements and ADC values between those with and without histopathological disease progression., Advances in Knowledge: This paper proposes specific clinical cut-offs for T 2 WI-derived maximum tumour diameter (+20%) and small-volume ADC (-10%) to predict histopathological PCa progression on AS and supplement subjective serial MRI assessment.

Hyperpolarised magnetic resonance imaging (HP  13 C-MRI) is an emerging clinical technique to detect [1- 13 C]lactate production in prostate cancer (PCa) following intravenous injection of hyperpolarised [1- 13 C]pyruvate. Here we differentiate clinically significant PCa from indolent disease in a low/intermediate-risk population by correlating [1- 13 C]lactate labelling on MRI with the percentage of Gleason pattern 4 (%GP4) disease. Using immunohistochemistry and spatial transcriptomics, we show that HP  13 C-MRI predominantly measures metabolism in the epithelial compartment of the tumour, rather than the stroma. MRI-derived tumour [1- 13 C]lactate labelling correlated with epithelial mRNA expression of the enzyme lactate dehydrogenase (LDHA and LDHB combined), and the ratio of lactate transporter expression between the epithelial and stromal compartments (epithelium-to-stroma MCT4). We observe similar changes in MCT4, LDHA, and LDHB between tumours with primary Gleason patterns 3 and 4 in an independent TCGA cohort. Therefore, HP  13 C-MRI can metabolically phenotype clinically significant disease based on underlying metabolic differences in the epithelial and stromal tumour compartments., (© 2022. The Author(s).)

Objectives: To compare the performance of the PRECISE scoring system against several MRI-derived delta-radiomics models for predicting histopathological prostate cancer (PCa) progression in patients on active surveillance (AS)., Methods: The study included AS patients with biopsy-proven PCa with a minimum follow-up of 2 years and at least one repeat targeted biopsy. Histopathological progression was defined as grade group progression from diagnostic biopsy. The control group included patients with both radiologically and histopathologically stable disease. PRECISE scores were applied prospectively by four uro-radiologists with 5-16 years' experience. T2WI- and ADC-derived delta-radiomics features were computed using baseline and latest available MRI scans, with the predictive modelling performed using the parenclitic networks (PN), least absolute shrinkage and selection operator (LASSO) logistic regression, and random forests (RF) algorithms. Standard measures of discrimination and areas under the ROC curve (AUCs) were calculated, with AUCs compared using DeLong's test., Results: The study included 64 patients (27 progressors and 37 non-progressors) with a median follow-up of 46 months. PRECISE scores had the highest specificity (94.7%) and positive predictive value (90.9%), whilst RF had the highest sensitivity (92.6%) and negative predictive value (92.6%) for predicting disease progression. The AUC for PRECISE (84.4%) was non-significantly higher than AUCs of 81.5%, 78.0%, and 80.9% for PN, LASSO regression, and RF, respectively (p = 0.64, 0.43, and 0.57, respectively). No significant differences were observed between AUCs of the three delta-radiomics models (p-value range 0.34-0.77)., Conclusions: PRECISE and delta-radiomics models achieved comparably good performance for predicting PCa progression in AS patients., Key Points: • The observed high specificity and PPV of PRECISE are complemented by the high sensitivity and NPV of delta-radiomics, suggesting a possible synergy between the two image assessment approaches. • The comparable performance of delta-radiomics to PRECISE scores applied by expert readers highlights the prospective use of the former as an objective and standardisable quantitative tool for MRI-guided AS follow-up. • The marginally superior performance of parenclitic networks compared to conventional machine learning algorithms warrants its further use in radiomics research., (© 2021. The Author(s).)

Background: Biopsy of the prostate for suspected cancer is usually performed transrectally under local anaesthesia in the outpatient clinic setting. As this involves piercing the bowel wall, the procedure is associated with a risk of infection. Recently, devices that facilitate transperineal biopsy approaches have been developed that avoid piercing the bowel and so should reduce the risk of infection., Objective: The aim of this study was to estimate the cost effectiveness of transperineal versus transrectal ultrasound-guided local anaesthesia procedures for prostate biopsy from the perspective of the UK NHS and to estimate the value of further research in the area., Methods: a) Decision tree and Markov model synthesising all relevant evidence estimating the life-time costs and QALYs accrued from each biopsy mode. b) Value of information analysis to predict the return from further research and thus guide future research efforts., Results: Transperineal biopsy yields an ICER below £20,000 per QALY gained at a per-procedure device acquisition cost below £81, or £41 for cost-neutrality. These results are driven by differences in consumables cost, reduced cost of treating infections, and QALY gains associated with reduced infections. There is value in future research on the diagnostic accuracy of transperineal versus transrectal biopsies and the incidence of iatrogenic infection and sepsis; consideration should be given to enriching the patient population with men with intermediate-risk disease., Conclusions: Transperineal biopsy devices may be cost effective compared with transrectal biopsy at per-procedure acquisition costs below £81 and cost-neutral if under £41. Future research is required to confirm or refute these findings, particularly randomised comparisons of the diagnostic accuracy and infection risks between the methods., (© 2021. The Author(s).)

Tumor cells may share some patterns of gene expression with their cell of origin, providing clues into the differentiation state and origin of cancer. Here, we study the differentiation state and cellular origin of 1300 childhood and adult kidney tumors. Using single cell mRNA reference maps of normal tissues, we quantify reference "cellular signals" in each tumor. Quantifying global differentiation, we find that childhood tumors exhibit fetal cellular signals, replacing the presumption of "fetalness" with a quantitative measure of immaturity. By contrast, in adult cancers our assessment refutes the suggestion of dedifferentiation towards a fetal state in most cases. We find an intimate connection between developmental mesenchymal populations and childhood renal tumors. We demonstrate the diagnostic potential of our approach with a case study of a cryptic renal tumor. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer.

Nearly half of patients with prostate cancer (PCa) harbour low- or intermediate-risk disease considered suitable for active surveillance (AS). However, up to 44% of patients discontinue AS within the first five years, highlighting the unmet clinical need for robust baseline risk-stratification tools that enable timely and accurate prediction of tumour progression. In this proof-of-concept study, we sought to investigate the added value of MRI-derived radiomic features to standard-of-care clinical parameters for improving baseline prediction of PCa progression in AS patients. Tumour T 2 -weighted imaging (T2WI) and apparent diffusion coefficient radiomic features were extracted, with rigorous calibration and pre-processing methods applied to select the most robust features for predictive modelling. Following leave-one-out cross-validation, the addition of T2WI-derived radiomic features to clinical variables alone improved the area under the ROC curve for predicting progression from 0.61 (95% confidence interval [CI] 0.481-0.743) to 0.75 (95% CI 0.64-0.86). These exploratory findings demonstrate the potential benefit of MRI-derived radiomics to add incremental benefit to clinical data only models in the baseline prediction of PCa progression on AS, paving the way for future multicentre studies validating the proposed model and evaluating its impact on clinical outcomes.

Aims: To evaluate the diagnostic yield of investigations performed on patients with a history of urinary tract infections (UTI)., Methods: A retrospective review was conducted on patients who underwent cystoscopy and imaging for a history of UTI between 2014 and 2019 in a single UK teaching hospital. Data were collected on demographics, cystoscopy and radiological findings requiring further management. The cohort was stratified by age, gender and a confirmed history of recurrent UTI (rUTI). The subsequent algorithm was re-tested in a second cohort to validate its use., Results: Seven hundred patients were included in the primary analysis-427 female and 273 males. Three hundred and thirty-one met the criteria of rUTI. The median age was 64 years (18-97). Imaging abnormalities were equally frequent in men 6.3% (15/241) and women 8% (30/380) and the majority noted in patients aged ≥55 years, 30/45 (66.7%). Amongst those who did not meet the definition of rUTI, abnormal imaging was identified in 5%-7% regardless of age group and gender. Cystoscopy abnormalities (n = 24) were twice more likely in males, 5.5%(15/273) than females, 2%(9/427). About 88%(21/24) were identified in patients ≥55 years. There were no positive findings in women <55 years. Applying baseline imaging but confining cystoscopy to those aged ≥55 years and men with a confirmed history of rUTI would have saved 44% of procedures, missed no abnormalities with an overall diagnosis detection rate of 9.8% (69/700). This algorithm was validated in a separate cohort of 63 patients; applying it would have saved 46% (29/63) of cystoscopies with a positive diagnostic rate of 9.5% and no missed findings., Conclusion: To our knowledge this is one of the largest studies reporting the outcomes of investigations for UTI and rUTI. Our result suggests that imaging is a useful baseline assessment, but cystoscopy should be limited to specific subgroups. We propose and validate a simple decision algorithm to manage investigations for referrals for UTI in secondary care., (© 2020 John Wiley & Sons Ltd.)

Objectives: To assess the predictive value and correlation to pathological progression of the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) scoring system in the follow-up of prostate cancer (PCa) patients on active surveillance (AS)., Methods: A total of 295 men enrolled on an AS programme between 2011 and 2018 were included. Baseline multiparametric magnetic resonance imaging (mpMRI) was performed at AS entry to guide biopsy. The follow-up mpMRI studies were prospectively reported by two sub-specialist uroradiologists with 10 years and 13 years of experience. PRECISE scores were dichotomized at the cut-off value of 4, and the sensitivity, specificity, positive predictive value and negative predictive value were calculated. Diagnostic performance was further quantified by using area under the receiver operating curve (AUC) which was based on the results of targeted MRI-US fusion biopsy. Univariate analysis using Cox regression was performed to assess which baseline clinical and mpMRI parameters were related to disease progression on AS., Results: Progression rate of the cohort was 13.9% (41/295) over a median follow-up of 52 months. With a cut-off value of category ≥ 4, the PRECISE scoring system showed sensitivity, specificity, PPV and NPV for predicting progression on AS of 0.76, 0.89, 0.52 and 0.96, respectively. The AUC was 0.82 (95% CI = 0.74-0.90). Prostate-specific antigen density (PSA-D), Likert lesion score and index lesion size were the only significant baseline predictors of progression (each p < 0.05)., Conclusion: The PRECISE scoring system showed good overall performance, and the high NPV may help limit the number of follow-up biopsies required in patients on AS., Key Points: • PRECISE scores 1-3 have high NPV which could reduce the need for re-biopsy during active surveillance. • PRECISE scores 4-5 have moderate PPV and should trigger either close monitoring or re-biopsy. • Three baseline predictors (PSA density, lesion size and Likert score) have a significant impact on the progression-free survival (PFS) time.

Background: Accurate prognostication is crucial in treatment decisions made for men diagnosed with non-metastatic prostate cancer. Current models rely on prespecified variables, which limits their performance. We aimed to investigate a novel machine learning approach to develop an improved prognostic model for predicting 10-year prostate cancer-specific mortality and compare its performance with existing validated models., Methods: We derived and tested a machine learning-based model using Survival Quilts, an algorithm that automatically selects and tunes ensembles of survival models using clinicopathological variables. Our study involved a US population-based cohort of 171 942 men diagnosed with non-metastatic prostate cancer between Jan 1, 2000, and Dec 31, 2016, from the prospectively maintained Surveillance, Epidemiology, and End Results (SEER) Program. The primary outcome was prediction of 10-year prostate cancer-specific mortality. Model discrimination was assessed using the concordance index (c-index), and calibration was assessed using Brier scores. The Survival Quilts model was compared with nine other prognostic models in clinical use, and decision curve analysis was done., Findings: 647 151 men with prostate cancer were enrolled into the SEER database, of whom 171 942 were included in this study. Discrimination improved with greater granularity, and multivariable models outperformed tier-based models. The Survival Quilts model showed good discrimination (c-index 0·829, 95% CI 0·820-0·838) for 10-year prostate cancer-specific mortality, which was similar to the top-ranked multivariable models: PREDICT Prostate (0·820, 0·811-0·829) and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram (0·787, 0·776-0·798). All three multivariable models showed good calibration with low Brier scores (Survival Quilts 0·036, 95% CI 0·035-0·037; PREDICT Prostate 0·036, 0·035-0·037; MSKCC 0·037, 0·035-0·039). Of the tier-based systems, the Cancer of the Prostate Risk Assessment model (c-index 0·782, 95% CI 0·771-0·793) and Cambridge Prognostic Groups model (0·779, 0·767-0·791) showed higher discrimination for predicting 10-year prostate cancer-specific mortality. c-indices for models from the National Comprehensive Cancer Care Network, Genitourinary Radiation Oncologists of Canada, American Urological Association, European Association of Urology, and National Institute for Health and Care Excellence ranged from 0·711 (0·701-0·721) to 0·761 (0·750-0·772). Discrimination for the Survival Quilts model was maintained when stratified by age and ethnicity. Decision curve analysis showed an incremental net benefit from the Survival Quilts model compared with the MSKCC and PREDICT Prostate models currently used in practice., Interpretation: A novel machine learning-based approach produced a prognostic model, Survival Quilts, with discrimination for 10-year prostate cancer-specific mortality similar to the top-ranked prognostic models, using only standard clinicopathological variables. Future integration of additional data will likely improve model performance and accuracy for personalised prognostics., Funding: None., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Distinguishing clinically significant from indolent prostate cancer (PC) is a major clinical challenge. We utilised targeted protein biomarker discovery approach to identify biomarkers specific for pro-metastatic PC. Serum samples from the cancer-free group; Cambridge Prognostic Group 1 (CPG1, low risk); CPG5 (high risk) and metastatic disease were analysed using Olink Proteomics panels. Tissue validation was performed by immunohistochemistry in a radical prostatectomy cohort (n = 234). We discovered that nine proteins (pleiotrophin (PTN), MK, PVRL4, EPHA2, TFPI-2, hK11, SYND1, ANGPT2, and hK14) were elevated in metastatic PC patients when compared to other groups. PTN levels were increased in serum from men with CPG5 compared to benign and CPG1. High tissue PTN level was an independent predictor of biochemical recurrence and metastatic progression in low- and intermediate-grade disease. These findings suggest that PTN may represent a novel biomarker for the presence of poor prognosis local disease with the potential to metastasise warranting further investigation.

Magnetic resonance fingerprinting (MRF) is a rapidly developing fast quantitative mapping technique able to produce multiple property maps with reduced sensitivity to motion. MRF has shown promise in improving the diagnosis of clinically significant prostate cancer but requires further validation as part of a prostate multiparametric (mp) MRI protocol. mpMRI protocol mandates the inclusion of dynamic contrast enhanced (DCE) imaging, known for its significant T 1 shortening effect. MRF could be used to measure both pre- and post-contrast T 1 values, but its utility must be assessed. In this proof-of-concept study, we sought to evaluate the variation in MRF T 1 measurements post gadolinium-based contrast agent (GBCA) injection and the utility of such T 1 measurements to differentiate peripheral and transition zone tumours from normal prostatic tissue. We found that the T 1 variation in all tissues increased considerably post-GBCA following the expected significant T 1 shortening effect, compromising the ability of MRF T 1 to identify transition zone lesions. We, therefore, recommend performing MRF T 1 prior to DCE imaging to maintain its benefit for improving detection of both peripheral and transition zone lesions while reducing additional scanning time. Demonstrating the effect of GBCA on MRF T 1 relaxometry in patients also paves the way for future clinical studies investigating the added value of post-GBCA MRF in PCa, including its dynamic analysis as in DCE-MRF.

Background: More accurate risk assessments are needed to improve prostate cancer management., Objective: To identify blood-based protein biomarkers that provided prognostic information for risk stratification., Design Setting and Participants: Mass spectrometry was used to identify biomarker candidates from blood, and validation studies were performed in four independent cohorts retrospectively collected between 1988 and 2015., Outcome Measurements and Statistical Analysis: The primary outcome objectives were progression-free survival, prostate cancer-specific survival (PCSS), and overall survival. Statistical analyses to assess survival and model performance were performed., Results and Limitation: Serum leucine-rich α-2-glycoprotein 1 (LRG1) was found to be elevated in fatal prostate cancer. LRG1 provided prognostic information independent of metastasis and increased the accuracy in predicting PCSS, particularly in the first 3 yr. A high LRG1 level is associated with an average of two-fold higher risk of disease-progression and mortality in both high-risk and metastatic patients. However, our study design, with a retrospective analysis of samples spanning several decades back, limits the assessment of the clinical utility of LRG1 in today's clinical practice. Thus, independent prospective studies are needed to establish LRG1 as a clinically useful biomarker for patient management., Conclusions: High blood levels of LRG1 are unfavourable in newly diagnosed high-risk and metastatic prostate cancer, and LRG1 increased the accuracy of risk stratification of prostate cancer patients., Patient Summary: High blood levels of leucine-rich α-2-glycoprotein 1 are unfavourable in newly diagnosed high-risk and metastatic prostate cancer., (© 2020 The Author(s).)

Objectives: Active surveillance (AS) enables men with low risk, localised prostate cancer (PCa) to avoid radical treatment unless progression occurs; lack of reliable AS protocols to determine progression leaves uncertainties for men and clinicians. This study investigated men's strategies for coping with the uncertainties of active monitoring (AM, a surveillance strategy within the Prostate testing for cancer and Treatment, ProtecT trial) over the longer term and implications for optimising supportive care., Design: Longitudinal serial in-depth qualitative interviews every 2-3 years for a median 7 (range 6-14) years following diagnosis., Setting: Four centres within the UK Protect trial., Participants: Purposive sample of 20 men with localised PCa: median age at diagnosis 64 years (range 52-68); 15 (75%) had low-risk PCa; 12 randomly allocated to, 8 choosing AM. Eleven men continued with AM throughout the study period (median 7 years). Nine received radical treatment after a median 4 years (range 0.8-13.8 years)., Intervention: AM: 3-monthly serum prostate-specific antigen (PSA)-level assessment (year 1), 6-12 monthly thereafter; increase in PSA ≥50% during previous 12 months or patient/clinician concern triggered review., Main Outcomes: Thematic analysis of 73 interviews identified strategies to accommodate uncertainty and anxiety of living with untreated cancer; implications for patient care., Results: Men sought clarity, control or reassurance, with contextual factors mediating individual responses. Trust in the clinical team was critical for men in balancing anxiety and facilitating successful management change/continued monitoring. Only men from ProtecT were included; men outside ProtecT may have different experiences., Conclusion: Men looked to clinicians for clarity, control and reassurance. Where provided, men felt comfortable continuing AM or having radical treatments when indicated. Clinicians build patient trust by clearly describing uncertainties, allowing patients control wherever possible and being aware of how context influences individual responses. Insights indicate need for supportive services to build trust and patient engagement over the long term., Trial Registration Number: ISRCTN20141297; Pre-results., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)