Fifteen-Year Outcomes after Monitoring, Surgery, or Radiotherapy for Prostate Cancer.

BACKGROUND: Between 1999 and 2009 in the United Kingdom, 82,429 men between 50 and 69 years of age received a prostate-specific antigen (PSA) test. Localized prostate cancer was diagnosed in 2664 men. Of these men, 1643 were enrolled in a trial to evaluate the effectiveness of treatments, with 545 randomly assigned to receive active monitoring, 553 to undergo prostatectomy, and 545 to undergo radiotherapy. METHODS: At a median follow-up of 15 years (range, 11 to 21), we compared the results in this population with respect to death from prostate cancer (the primary outcome) and death from any cause, metastases, disease progression, and initiation of long-term androgen-deprivation therapy (secondary outcomes). RESULTS: Follow-up was complete for 1610 patients (98%). A risk-stratification analysis showed that more than one third of the men had intermediate or high-risk disease at diagnosis. Death from prostate cancer occurred in 45 men (2.7%): 17 (3.1%) in the active-monitoring group, 12 (2.2%) in the prostatectomy group, and 16 (2.9%) in the radiotherapy group (P = 0.53 for the overall comparison). Death from any cause occurred in 356 men (21.7%), with similar numbers in all three groups. Metastases developed in 51 men (9.4%) in the active-monitoring group, in 26 (4.7%) in the prostatectomy group, and in 27 (5.0%) in the radiotherapy group. Long-term androgen-deprivation therapy was initiated in 69 men (12.7%), 40 (7.2%), and 42 (7.7%), respectively; clinical progression occurred in 141 men (25.9%), 58 (10.5%), and 60 (11.0%), respectively. In the active-monitoring group, 133 men (24.4%) were alive without any prostate cancer treatment at the end of follow-up. No differential effects on cancer-specific mortality were noted in relation to the baseline PSA level, tumor stage or grade, or risk-stratification score. No treatment complications were reported after the 10-year analysis. CONCLUSIONS: After 15 years of follow-up, prostate cancer-specific mortality was low regardless of the treatment assigned. Thus, the choice of therapy involves weighing trade-offs between benefits and harms associated with treatments for localized prostate cancer. (Funded by the National Institute for Health and Care Research; ProtecT Current Controlled Trials number, ISRCTN20141297; ClinicalTrials.gov number, NCT02044172.).

Imaging tumor lactate is feasible for identifying intermediate-risk prostate cancer patients with postsurgical biochemical recurrence.

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 13C 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.

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.

Shifting the paradigm in the management of early prostate cancer.

Outcomes from active surveillance have clearly shown that it is the optimal method of managing many early prostate cancers. Yet, clinician training and healthcare systems are still primarily focused on the "need to treat". This comment explores the challenges and resource issues in future implementation of high-quality surveillance programmes.

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance.

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.

Urinary symptoms and prostate cancer-the misconception that may be preventing earlier presentation and better survival outcomes.

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.

Assessing the impact of MRI based diagnostics on pre-treatment disease classification and prognostic model performance in men diagnosed with new prostate cancer from an unscreened population.

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.

Functional and quality of life outcomes of localised prostate cancer treatments (Prostate Testing for Cancer and Treatment [ProtecT] study).

OBJECTIVE: To investigate the functional and quality of life (QoL) outcomes of treatments for localised prostate cancer and inform treatment decision-making. PATIENTS AND METHODS: Men aged 50-69 years diagnosed with localised prostate cancer by prostate-specific antigen testing and biopsies at nine UK centres in the Prostate Testing for Cancer and Treatment (ProtecT) trial were randomised to, or chose one of, three treatments. Of 2565 participants, 1135 men received active monitoring (AM), 750 a radical prostatectomy (RP), 603 external-beam radiotherapy (EBRT) with concurrent androgen-deprivation therapy (ADT) and 77 low-dose-rate brachytherapy (BT, not a randomised treatment). Patient-reported outcome measures (PROMs) completed annually for 6 years were analysed by initial treatment and censored for subsequent treatments. Mixed effects models were adjusted for baseline characteristics using propensity scores. RESULTS: Treatment-received analyses revealed different impacts of treatments over 6 years. Men remaining on AM experienced gradual declines in sexual and urinary function with age (e.g., increases in erectile dysfunction from 35% of men at baseline to 53% at 6 years and nocturia similarly from 20% to 38%). Radical treatment impacts were immediate and continued over 6 years. After RP, 95% of men reported erectile dysfunction persisting for 85% at 6 years, and after EBRT this was reported by 69% and 74%, respectively (P < 0.001 compared with AM). After RP, 36% of men reported urinary leakage requiring at least 1 pad/day, persisting for 20% at 6 years, compared with no change in men receiving EBRT or AM (P < 0.001). Worse bowel function and bother (e.g., bloody stools 6% at 6 years and faecal incontinence 10%) was experienced by men after EBRT than after RP or AM (P < 0.001) with lesser effects after BT. No treatment affected mental or physical QoL. CONCLUSION: Treatment decision-making for localised prostate cancer can be informed by these 6-year functional and QoL outcomes.

Comparative performance of MRI-derived PRECISE scores and delta-radiomics models for the prediction of prostate cancer progression in patients on active surveillance.

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.

Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition.

Mutations of the tricarboxylic acid cycle enzyme fumarate hydratase cause hereditary leiomyomatosis and renal cell cancer. Fumarate hydratase-deficient renal cancers are highly aggressive and metastasize even when small, leading to a very poor clinical outcome. Fumarate, a small molecule metabolite that accumulates in fumarate hydratase-deficient cells, plays a key role in cell transformation, making it a bona fide oncometabolite. Fumarate has been shown to inhibit α-ketoglutarate-dependent dioxygenases that are involved in DNA and histone demethylation. However, the link between fumarate accumulation, epigenetic changes, and tumorigenesis is unclear. Here we show that loss of fumarate hydratase and the subsequent accumulation of fumarate in mouse and human cells elicits an epithelial-to-mesenchymal-transition (EMT), a phenotypic switch associated with cancer initiation, invasion, and metastasis. We demonstrate that fumarate inhibits Tet-mediated demethylation of a regulatory region of the antimetastatic miRNA cluster mir-200ba429, leading to the expression of EMT-related transcription factors and enhanced migratory properties. These epigenetic and phenotypic changes are recapitulated by the incubation of fumarate hydratase-proficient cells with cell-permeable fumarate. Loss of fumarate hydratase is associated with suppression of miR-200 and the EMT signature in renal cancer and is associated with poor clinical outcome. These results imply that loss of fumarate hydratase and fumarate accumulation contribute to the aggressive features of fumarate hydratase-deficient tumours.

Discovery of PTN as a serum-based biomarker of pro-metastatic prostate cancer.

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.

Risk-Based Selection for Active Surveillance: Results of the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance (GAP3) Initiative.

PURPOSE: We sought to identify and validate known predictors of disease reclassification at 1 or 4 years to support risk-based selection of patients suitable for active surveillance. MATERIALS AND METHODS: An individual participant data meta-analysis using data from 25 established cohorts within the Movember Foundations GAP3 Consortium. In total 5,530 men were included. Disease reclassification was defined as any increase in Gleason grade group at biopsy at 1 and 4 years. Associations were estimated using random effect logistic regression models. The discriminative ability of combinations of predictors was assessed in an internal-external validation procedure using the AUC curve. RESULTS: Among the 5,570 men evaluated at 1 year, we found 815 reclassifications to higher Gleason grade group at biopsy (pooled reclassification rate 13%, range 0% to 31%). Important predictors were age, prostate specific antigen, prostate volume, T-stage and number of biopsy cores with prostate cancer. Among the 1,515 men evaluated at 4 years, we found 205 reclassifications (pooled reclassification rates 14%, range 3% to 40%), with similar predictors. The average areas under the receiver operating characteristic curve at internal-external validation were 0.68 and 0.61 for 1-year and 4-year reclassification, respectively. CONCLUSIONS: Disease reclassification occurs typically in 13% to 14% of biopsies at 1 and 4 years after the start of active surveillance with substantial between-study heterogeneity. Current guidelines might be extended by considering prostate volume to improve individualized selection for active surveillance. Additional predictors are needed to improve patient selection for active surveillance.

MRI-derived PRECISE scores for predicting pathologically-confirmed radiological progression in prostate cancer patients on active surveillance.

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.

Robust and flexible inference for the covariate-specific receiver operating characteristic curve.

Diagnostic tests are of critical importance in health care and medical research. Motivated by the impact that atypical and outlying test outcomes might have on the assessment of the discriminatory ability of a diagnostic test, we develop a robust and flexible model for conducting inference about the covariate-specific receiver operating characteristic (ROC) curve that safeguards against outlying test results while also accommodating for possible nonlinear effects of the covariates. Specifically, we postulate a location-scale regression model for the test outcomes in both the diseased and nondiseased populations, combining additive regression B-splines and M-estimation for the regression function, while the distribution of the error term is estimated via a weighted empirical distribution function of the standardized residuals. The results of the simulation study show that our approach successfully recovers the true covariate-specific area under the ROC curve on a variety of conceivable test outcomes contamination scenarios. Our method is applied to a dataset derived from a prostate cancer study where we seek to assess the ability of the Prostate Health Index to discriminate between men with and without Gleason 7 or above prostate cancer, and if and how such discriminatory capacity changes with age.

Rationalising the use of investigation for urinary tract infections: Analysis of 700 patients and proposal for a diagnostic algorithm.

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.

The ProtecT randomised trial cost-effectiveness analysis comparing active monitoring, surgery, or radiotherapy for prostate cancer.

BACKGROUND: There is limited evidence relating to the cost-effectiveness of treatments for localised prostate cancer. METHODS: The cost-effectiveness of active monitoring, surgery, and radiotherapy was evaluated within the Prostate Testing for Cancer and Treatment (ProtecT) randomised controlled trial from a UK NHS perspective at 10 years' median follow-up. Prostate cancer resource-use collected from hospital records and trial participants was valued using UK reference-costs. QALYs (quality-adjusted-life-years) were calculated from patient-reported EQ-5D-3L measurements. Adjusted mean costs, QALYs, and incremental cost-effectiveness ratios were calculated; cost-effectiveness acceptability curves and sensitivity analyses addressed uncertainty; subgroup analyses considered age and disease-risk. RESULTS: Adjusted mean QALYs were similar between groups: 6.89 (active monitoring), 7.09 (radiotherapy), and 6.91 (surgery). Active monitoring had lower adjusted mean costs (£5913) than radiotherapy (£7361) and surgery (£7519). Radiotherapy was the most likely (58% probability) cost-effective option at the UK NICE willingness-to-pay threshold (£20,000 per QALY). Subgroup analyses confirmed radiotherapy was cost-effective for older men and intermediate/high-risk disease groups; active monitoring was more likely to be the cost-effective option for younger men and low-risk groups. CONCLUSIONS: Longer follow-up and modelling are required to determine the most cost-effective treatment for localised prostate cancer over a man's lifetime. TRIAL REGISTRATION: Current Controlled Trials number, ISRCTN20141297: http://isrctn.org (14/10/2002); ClinicalTrials.gov number, NCT02044172: http://www.clinicaltrials.gov (23/01/2014).

Comparative performance and external validation of the multivariable PREDICT Prostate tool for non-metastatic prostate cancer: a study in 69,206 men from Prostate Cancer data Base Sweden (PCBaSe).

BACKGROUND: PREDICT Prostate is an endorsed prognostic model that provides individualised long-term prostate cancer-specific and overall survival estimates. The model, derived from UK data, estimates potential treatment benefit on overall survival. In this study, we externally validated the model in a large independent dataset and compared performance to existing models and within treatment groups. METHODS: Men with non-metastatic prostate cancer and prostate-specific antigen (PSA) < 100 ng/ml diagnosed between 2000 and 2010 in the nationwide population-based Prostate Cancer data Base Sweden (PCBaSe) were included. Data on age, PSA, clinical stage, grade group, biopsy involvement, primary treatment and comorbidity were retrieved. Sixty-nine thousand two hundred six men were included with 13.9 years of median follow-up. Fifteen-year survival estimates were calculated using PREDICT Prostate for prostate cancer-specific mortality (PCSM) and all-cause mortality (ACM). Discrimination was assessed using Harrell's concordance (c)-index in R. Calibration was evaluated using cumulative available follow-up in Stata (TX, USA). RESULTS: Overall discrimination of PREDICT Prostate was good with c-indices of 0.85 (95% CI 0.85-0.86) for PCSM and 0.79 (95% CI 0.79-0.80) for ACM. Overall calibration of the model was excellent with 25,925 deaths predicted and 25,849 deaths observed. Within the conservative management and radical treatment groups, c-indices for 15-year PCSM were 0.81 and 0.78, respectively. Calibration also remained good within treatment groups. The discrimination of PREDICT Prostate significantly outperformed the EAU, NCCN and CAPRA scores for both PCSM and ACM within this cohort overall. A key limitation is the use of retrospective cohort data. CONCLUSIONS: This large external validation demonstrates that PREDICT Prostate is a robust and generalisable model to aid clinical decision-making.

Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study.

BACKGROUND: The clinical pathway to detect and diagnose prostate cancer has been revolutionised by the use of multiparametric MRI (mpMRI pre-biopsy). mpMRI however remains a resource-intensive test and is highly operator dependent with variable effectiveness with regard to its negative predictive value. Here we tested the use of the phi assay in standard clinical practice to pre-select men at the highest risk of harbouring significant cancer and hence refine the use of mpMRI and biopsies. METHODS: A prospective five-centre study recruited men being investigated through an mpMRI-based prostate cancer diagnostic pathway. Test statistics for PSA, PSA density (PSAd) and phi were assessed for detecting significant cancers using 2 definitions: ≥ Grade Group (GG2) and ≥ Cambridge Prognostic Groups (CPG) 3. Cost modelling and decision curve analysis (DCA) was simultaneously performed. RESULTS: A total of 545 men were recruited and studied with a median age, PSA and phi of 66 years, 8.0 ng/ml and 44 respectively. Overall, ≥ GG2 and ≥ CPG3 cancer detection rates were 64% (349/545), 47% (256/545) and 32% (174/545) respectively. There was no difference across centres for patient demographics or cancer detection rates. The overall area under the curve (AUC) for predicting ≥ GG2 cancers was 0.70 for PSA and 0.82 for phi. AUCs for ≥ CPG3 cancers were 0.81 and 0.87 for PSA and phi respectively. AUC values for phi did not differ between centres suggesting reliability of the test in different diagnostic settings. Pre-referral phi cut-offs between 20 and 30 had NPVs of 0.85-0.90 for ≥ GG2 cancers and 0.94-1.0 for ≥ CPG3 cancers. A strategy of mpMRI in all and biopsy only positive lesions reduced unnecessary biopsies by 35% but missed 9% of ≥ GG2 and 5% of ≥ CPG3 cancers. Using PH ≥ 30 to rule out referrals missed 8% and 5% of ≥ GG2 and ≥ CPG3 cancers (and reduced unnecessary biopsies by 40%). This was achieved however with 25% fewer mpMRI. Pathways incorporating PSAd missed fewer cancers but necessitated more unnecessary biopsies. The phi strategy had the lowest mean costs with DCA demonstrating net clinical benefit over a range of thresholds. CONCLUSION: phi as a triaging test may be an effective way to reduce mpMRI and biopsies without compromising detection of significant prostate cancers.

Removing rician bias in diffusional kurtosis of the prostate using real-data reconstruction.

PURPOSE: To compare prostate diffusional kurtosis imaging (DKI) metrics generated using phase-corrected real data with those generated using magnitude data with and without noise compensation (NC). METHODS: Diffusion-weighted images were acquired at 3T in 16 prostate cancer patients, measuring 6 b-values (0-1500 s/mm2 ), each acquired with 6 signal averages along 3 diffusion directions, with noise-only images acquired to allow NC. In addition to conventional magnitude averaging, phase-corrected real data were averaged in an attempt to reduce rician noise-bias, with a range of phase-correction low-pass filter (LPF) sizes (8-128 pixels) tested. Each method was also tested using simulations. Pixelwise maps of apparent diffusion (D) and apparent kurtosis (K) were calculated for magnitude data with and without NC and phase-corrected real data. Average values were compared in tumor, normal transition zone (NTZ), and normal peripheral zone (NPZ). RESULTS: Simulations indicated LPF size can strongly affect K metrics, where 64-pixel LPFs produced accurate metrics. Relative to metrics estimated from magnitude data without NC, median NC K were lower (P < 0.0001) by 6/11/8% in tumor/NPZ/NTZ, 64-LPF real-data K were lower (P < 0.0001) by 4/10/7%, respectively. CONCLUSION: Compared with magnitude data with NC, phase-corrected real data can produce similar K, although the choice of phase-correction LPF should be chosen carefully.

Impact of hospital nephrectomy volume on intermediate- to long-term survival in renal cell carcinoma.

OBJECTIVE: To evaluate the relationship between hospital volume and intermediate- and long-term patient survival for patients undergoing nephrectomy for renal cell carcinoma (RCC). PATIENTS AND METHODS: Adult patients with RCC treated with nephrectomy between 2000 and 2010 were identified from the English Hospital Episode Statistics database and National Cancer Data Repository. Patients with nodal or metastatic disease were excluded. Hospitals were categorised into low- (LV; <20 cases/year), medium- (20-39 cases/year) and high-volume (HV; ≥40 cases/year), based on annual cases of RCC nephrectomy. Multivariable Cox regression analyses were used to calculate hazard ratios (HRs) for all-cause mortality by hospital volume, adjusting for patient, tumour and surgical characteristics. We assessed conditional survival over three follow-up periods: short (30 days to 1 year), intermediate (1-3 years) and long (3-5 years). We additionally explored whether associations between volume and outcomes varied by tumour stage. RESULTS: A total of 12 912 patients were included. Patients in HV hospitals had a 34% reduction in mortality risks up to 1 year compared to those in LV hospitals (HR 0.66, 95% confidence interval 0.53-0.83; P < 0.01). Assuming causality, treatment in HV hospitals was associated with one fewer death in every 71 patients treated. Benefit of nephrectomy centralisation did not change with higher T stage (P = 0.17). No significant association between hospital volume and survival was observed beyond the first year. CONCLUSIONS: Nephrectomy for RCC in HV hospitals was associated with improved survival for up to 1 year after treatment. Our results contribute new insights regarding the value of nephrectomy centralisation.