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.

Individual prognosis at diagnosis in nonmetastatic prostate cancer: Development and external validation of the PREDICT Prostate multivariable model.

BACKGROUND: Prognostic stratification is the cornerstone of management in nonmetastatic prostate cancer (PCa). However, existing prognostic models are inadequate-often using treatment outcomes rather than survival, stratifying by broad heterogeneous groups and using heavily treated cohorts. To address this unmet need, we developed an individualised prognostic model that contextualises PCa-specific mortality (PCSM) against other cause mortality, and estimates the impact of treatment on survival. METHODS AND FINDINGS: Using records from the United Kingdom National Cancer Registration and Analysis Service (NCRAS), data were collated for 10,089 men diagnosed with nonmetastatic PCa between 2000 and 2010 in Eastern England. Median follow-up was 9.8 years with 3,829 deaths (1,202 PCa specific). Totals of 19.8%, 14.1%, 34.6%, and 31.5% of men underwent conservative management, prostatectomy, radiotherapy (RT), and androgen deprivation monotherapy, respectively. A total of 2,546 men diagnosed in Singapore over a similar time period represented an external validation cohort. Data were randomly split 70:30 into model development and validation cohorts. Fifteen-year PCSM and non-PCa mortality (NPCM) were explored using separate multivariable Cox models within a competing risks framework. Fractional polynomials (FPs) were utilised to fit continuous variables and baseline hazards. Model accuracy was assessed by discrimination and calibration using the Harrell C-index and chi-squared goodness of fit, respectively, within both validation cohorts. A multivariable model estimating individualised 10- and 15-year survival outcomes was constructed combining age, prostate-specific antigen (PSA), histological grade, biopsy core involvement, stage, and primary treatment, which were each independent prognostic factors for PCSM, and age and comorbidity, which were prognostic for NPCM. The model demonstrated good discrimination, with a C-index of 0.84 (95% CI: 0.82-0.86) and 0.84 (95% CI: 0.80-0.87) for 15-year PCSM in the UK and Singapore validation cohorts, respectively, comparing favourably to international risk-stratification criteria. Discrimination was maintained for overall mortality, with C-index 0.77 (95% CI: 0.75-0.78) and 0.76 (95% CI: 0.73-0.78). The model was well calibrated with no significant difference between predicted and observed PCa-specific (p = 0.19) or overall deaths (p = 0.43) in the UK cohort. Key study limitations were a relatively small external validation cohort, an inability to account for delayed changes to treatment beyond 12 months, and an absence of tumour-stage subclassifications. CONCLUSIONS: 'PREDICT Prostate' is an individualised multivariable PCa prognostic model built from baseline diagnostic information and the first to our knowledge that models potential treatment benefits on overall survival. Prognostic power is high despite using only routinely collected clinicopathological information.

Understanding of prognosis in non-metastatic prostate cancer: a randomised comparative study of clinician estimates measured against the PREDICT prostate prognostic model.

PREDICT Prostate is an individualised prognostic model that provides long-term survival estimates for men diagnosed with non-metastatic prostate cancer ( www.prostate.predict.nhs.uk ). In this study clinician estimates of survival were compared against model predictions and its potential value as a clinical tool was assessed. Prostate cancer (PCa) specialists were invited to participate in the study. 190 clinicians (63% urologists, 17% oncologists, 20% other) were randomised into two groups and shown 12 clinical vignettes through an online portal. Each group viewed opposing vignettes with clinical information alone, or alongside PREDICT Prostate estimates. 15-year clinician survival estimates were compared against model predictions and reported treatment recommendations with and without seeing PREDICT estimates were compared. 155 respondents (81.6%) reported counselling new PCa patients at least weekly. Clinician estimates of PCa-specific mortality exceeded PREDICT estimates in 10/12 vignettes. Their estimates for treatment survival benefit at 15 years were over-optimistic in every vignette, with mean clinician estimates more than 5-fold higher than PREDICT Prostate estimates. Concomitantly seeing PREDICT Prostate estimates led to significantly lower reported likelihoods of recommending radical treatment in 7/12 (58%) vignettes, particularly in older patients. These data suggest clinicians overestimate cancer-related mortality and radical treatment benefit. Using an individualised prognostic tool may help reduce overtreatment.

Using prognosis to guide inclusion criteria, define standardised endpoints and stratify follow-up in active surveillance for prostate cancer.

OBJECTIVES: To test whether using disease prognosis can inform a rational approach to active surveillance (AS) for early prostate cancer. PATIENTS AND METHODS: We previously developed the Cambridge Prognostics Groups (CPG) classification, a five-tiered model that uses prostate-specific antigen (PSA), Grade Group and Stage to predict cancer survival outcomes. We applied the CPG model to a UK and a Swedish prostate cancer cohort to test differences in prostate cancer mortality (PCM) in men managed conservatively or by upfront treatment in CPG2 and 3 (which subdivides the intermediate-risk classification) vs CPG1 (low-risk). We then applied the CPG model to a contemporary UK AS cohort, which was optimally characterised at baseline for disease burden, to identify predictors of true prognostic progression. Results were re-tested in an external AS cohort from Spain. RESULTS: In a UK cohort (n = 3659) the 10-year PCM was 2.3% in CPG1, 1.5%/3.5% in treated/untreated CPG2, and 1.9%/8.6% in treated/untreated CPG3. In the Swedish cohort (n = 27 942) the10-year PCM was 1.0% in CPG1, 2.2%/2.7% in treated/untreated CPG2, and 6.1%/12.5% in treated/untreated CPG3. We then tested using progression to CPG3 as a hard endpoint in a modern AS cohort (n = 133). During follow-up (median 3.5 years) only 6% (eight of 133) progressed to CPG3. Predictors of progression were a PSA density ≥0.15 ng/mL/mL and CPG2 at diagnosis. Progression occurred in 1%, 8% and 21% of men with neither factor, only one, or both, respectively. In an independent Spanish AS cohort (n = 143) the corresponding rates were 3%, 10% and 14%, respectively. CONCLUSION: Using disease prognosis allows a rational approach to inclusion criteria, discontinuation triggers and risk-stratified management in AS.

Progression and treatment rates using an active surveillance protocol incorporating image-guided baseline biopsies and multiparametric magnetic resonance imaging monitoring for men with favourable-risk prostate cancer.

OBJECTIVE: To assess early outcomes since the introduction of an active surveillance (AS) protocol incorporating multiparametric magnetic resonance imaging (mpMRI)-guided baseline biopsies and image-based surveillance. PATIENTS AND METHODS: A new AS protocol mandating image-guided baseline biopsies, annual mpMRI and 3-monthly prostate-specific antigen (PSA) testing, but which retained protocol re-biopsies, was tested. Pathological progression, treatment conversion and triggers for non-protocol biopsy were recorded prospectively. RESULTS: Data from 157 men enrolled in the AS protocol (median age 64 years, PSA 6.8 ng/mL, follow-up 39 months) were interrogated. A total of 12 men (7.6%) left the AS programme by choice. Of the 145 men who remained, 104 had re-biopsies either triggered by a rise in PSA level, change in mpMRI findings or by protocol. Overall, 23 men (15.9%) experienced disease progression; pathological changes were observed in 20 men and changes in imaging results were observed in three men. Of these 23 men, 17 switched to treatment, giving a conversion rate of 11.7% (<4% per year). Of the 20 men with pathological progression, this was detected in four of them after a PSA increase triggered a re-biopsy, while in 10 men progression was detected after an mpMRI change. Progression was detected in six men, however, solely after a protocol re-biopsy without prior PSA or mpMRI changes. Using PSA and mpMRI changes alone to detect progression was found to have a sensitivity and specificity of 70.0% and 81.7%, respectively. CONCLUSION: Our AS protocol, with thorough baseline assessment and imaging-based surveillance, showed low rates of progression and treatment conversion. Changes in mpMRI findings were the principle trigger for detecting progression by imaging alone or pathologically; however, per protocol re-biopsy still detected a significant number of pathological progressions without mpMRI or PSA changes.

Incorporating multiparametric MRI staging and the new histological Grade Group system improves risk-stratified detection of bone metastasis in prostate cancer.

BACKGROUND: There remains uncertainty on the need for bone staging in men with intermediate-risk prostate cancer. Current guidelines do not use mpMRI-staging information and rely on historic pathology grading. METHODS: We investigated the ability of mpMRI and the new Grade Group system to better predict bone metastasis status in a retrospective cohort study of 438 men with prostate cancer undergoing baseline mpMRI and isotope bone scintigraphy (BS). RESULTS: Including mpMRI-staging information significantly increased the specificity of bone metastasis detection from 3.0% to 24.2% (P<0.01) and sensitivity from 89.2% to 97.3%. The new Grade Group score demonstrated progressive increase in bone metastasis rates (P<0.001). A novel risk-stratification model combining Grade Groups, PSA and mpMRI staging shows promise in predicting bone metastasis and could potentially reduce BS usage by 22.4%-34.7%. CONCLUSIONS: Incorporating the new Grade Group system and mpMRI staging more accurately identified bone metastatic risk and suggests men with Grade Group ⩽2 and/or without radiological T3 disease could safely avoid routine bone staging.

Evolution and oncological outcomes of a contemporary radical prostatectomy practice in a UK regional tertiary referral centre.

OBJECTIVE: To investigate the clinical and pathological trends, over a 10-year period, in robot-assisted laparoscopic prostatectomy (RALP) in a UK regional tertiary referral centre. PATIENTS AND METHODS: In all, 1 500 consecutive patients underwent RALP between October 2005 and January 2015. Prospective data were collected on clinicopathological details at presentation as well as surgical outcomes and compared over time. RESULTS: The median (range) age of patients throughout the period was 62 (35-78) years. The proportion of preoperative high-grade cases (Gleason score 8-10) rose from 4.6% in 2005-2008 to 18.2% in 2013-2015 (P < 0.001). In the same periods the proportion of clinical stage T3 cases operated on rose from 2.4% to 11.4% (P < 0.001). The median prostate-specific antigen (PSA) level at diagnosis did not alter significantly. Overall, 11.6% of men in 2005-2008 were classified preoperatively as high-risk by National Institute for Health and Care Excellence criteria, compared with 33.6% in 2013-2015 (P < 0.001). The corresponding proportions for low-risk cases were 48.6% and 17.3%, respectively. Final surgical pathology showed an increase in tumour stage, Gleason grade, and nodal status over time. The proportion of pT3 cases rose from 43.2% in 2005-2008 to 55.5% in 2013-2015 (P < 0.001), Gleason score 9-10 tumours increased from 1.8% to 9.1% (P < 0.001) and positive nodal status increased from 1.6% to 12.9% (P < 0.001) between the same periods. Despite this, positive surgical margin rates showed a downward trend in all pT groups across the different eras (P = 0.72). CONCLUSION: This study suggests that the patient profile for RALP in our unit is changing, with increasing proportions of higher stage and more advanced disease being referred and operated on. However, surgical margin outcomes have remained good.

Adaption and National Validation of a Tool for Predicting Mortality from Other Causes Among Men with Nonmetastatic Prostate Cancer.

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.

Sentinel lymph node biopsy for risk-reducing mastectomy.

Risk-reducing mastectomy (RRM) confers 90-95% decreased risk of breast cancer, and may reduce mortality, especially in high-risk groups such as BRCA carriers. Risk of occult disease in RRM specimen is ~5%. This demands axillary staging: sentinel lymph node (SLN) biopsy is no longer possible, axillary clearance confers significant risks and may prove negative. Contemporaneous SLN biopsy allows axillary staging with minimal further dissection. Women undergoing RRM and SLN biopsy between June 2005 and July 2010 were reviewed retrospectively from our prospectively maintained database of 1,522 SLN procedures in 1,498 patients. SLN(s) localized using routine tracer methods. SLNs and mastectomy specimens underwent routine histologic examination. Eighty-three RRMs with SLN biopsy were performed in 71 patients (12 bilateral). Indications for RRM: contralateral invasive (55), in situ (5) disease, BRCA 1/2 mutation (12), and strong family history (10). Mean number of SLNs: 1.35. Occult disease was detected in four cases (4.8%), with one case of occult invasive lobular carcinoma (1.2%). Remaining occult disease was lobular in situ neoplasia (LISN). SLNs were negative in all cases. Our findings are comparable to those in the literature: 4.8% rate of occult disease overall, 1.2% invasive. The significant risk with SLN biopsy is lymphoedema, quoted around 7%. We have had no reports of symptomatic lymphoedema in patients undergoing RRM and SLN biopsy. We propose that SLN at the time of mastectomy requires only limited further dissection, and confers minimal risk compared with secondary axillary surgery.

Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database.

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.

Orchidopexy for Testicular Torsion: A Systematic Review of Surgical Technique.

CONTEXT: Acute testicular torsion is a common urological emergency. Accepted practice is surgical exploration, detorsion, and orchidopexy for a salvageable testis. OBJECTIVE: To critically evaluate the methods of orchidopexy and their outcomes with a view to determining the optimal surgical technique. EVIDENCE ACQUISITION: This review protocol was published via PROSPERO [CRD42016043165] and conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). EMBASE, MEDLINE, and CENTRAL databases were searched using the following terms: "orchidopexy", "fixation", "exploration", "torsion", "scrotum", and variants. Article screening was performed by two reviewers independently. The primary outcome was retorsion rate of the ipsilateral testis following orchidopexy. Secondary outcomes included testicular atrophy and fertility. EVIDENCE SYNTHESIS: To our knowledge, this is the first systematic review on this topic. The search yielded 2257 abstracts. Five studies (n = 138 patients) were included. All five techniques differed in incision and/or type of suture and/or point(s) of fixation. Postoperative complications were reported in one study, and included scrotal abscess in 9.1% and stitch abscess in 4.5%. The contralateral testis was fixed in 57.6% of cases. Three studies reported follow-up duration (range 6-31 wk). No study reported any episodes of ipsilateral retorsion. In the studies reporting ipsilateral atrophy rate, this ranged from 9.1% to 47.5%. Fertility outcomes and patient-reported outcome measures were not reported in any studies. CONCLUSIONS: There is limited evidence in favour of any one surgical technique for acute testicular torsion. During the consent process for scrotal exploration, uncertainties in long-term harms should be discussed. This review highlights the need for an interim consensus on surgical approach until robust studies examining the effects of an operative approach on clinical and fertility outcomes are available. PATIENT SUMMARY: Twisting of blood supply to the testis, termed testicular torsion, is a urological emergency. Testicular torsion is treated using an operation to untwist the cord that contains the blood vessels. If the testis is still salvageable, surgery can be performed to prevent further torsion. The method that is used to prevent further torsion varies. We reviewed the literature to assess the outcomes of using various surgical techniques to fix the twisting of the testis. Our review shows that there is limited evidence in favour of any one technique.

Clinical Impact of the Predict Prostate Risk Communication Tool in Men Newly Diagnosed with Nonmetastatic Prostate Cancer: A Multicentre Randomised Controlled Trial.

BACKGROUND: Predict Prostate is a freely available online personalised risk communication tool for men with nonmetastatic prostate cancer. Its accuracy has been assessed in multiple validation studies, but its clinical impact among patients has not hitherto been assessed. OBJECTIVE: To assess the impact of the tool on patient decision-making and disease perception. DESIGN, SETTING, AND PARTICIPANTS: A multicentre randomised controlled trial was performed across eight UK centres among newly diagnosed men considering either active surveillance or radical treatment. A total of 145 patients were included between 2018 and 2020, with median age 67 yr (interquartile range [IQR] 61-72) and prostate-specific antigen 6.8 ng/ml (IQR 5.1-8.8). INTERVENTION: Participants were randomised to either standard of care (SOC) information or SOC and a structured presentation of the Predict Prostate tool. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Validated questionnaires were completed by assessing the impact of the tool on decisional conflict, uncertainty, anxiety, and perception of survival. RESULTS AND LIMITATIONS: Mean Decisional Conflict Scale scores were 26% lower in the Predict Prostate group (mean = 16.1) than in the SOC group (mean = 21.7; p = 0.027). Scores on the "support", "uncertainty", and "value clarity" subscales all favoured Predict Prostate (all p < 0.05). There was no significant difference in anxiety scores or final treatment selection between the two groups. Patient perception of 15-yr prostate cancer-specific mortality (PCSM) and overall survival benefit from radical treatment were considerably lower and more accurate among men in the Predict Prostate group (p < 0.001). In total, 57% of men reported that the Predict Prostate estimates for PCSM were lower than expected, and 36% reported being less likely to select radical treatment. Over 90% of patients in the intervention group found it useful and 94% would recommend it to others. CONCLUSIONS: Predict Prostate reduces decisional conflict and uncertainty, and shifts patient perception around prognosis to be more realistic. This randomised trial demonstrates that Predict Prostate can directly inform the complex decision-making process in prostate cancer and is felt to be useful by patients. Future larger trials are warranted to test its impact upon final treatment decisions. PATIENT SUMMARY: In this national study, we assessed the impact of an individualised risk communication tool, called Predict Prostate, on patient decision-making after a diagnosis of localised prostate cancer. Men were randomly assigned to two groups, which received either standard counselling and information, or this in addition to a structured presentation of the Predict Prostate tool. Men who saw the tool were less conflicted and uncertain in their decision-making, and recommended the tool highly. Those who saw the tool had more realistic perception about their long-term survival and the potential impact of treatment upon this. TAKE HOME MESSAGE: The use of an individualised risk communication tool, such as Predict Prostate, reduces patient decisional conflict and uncertainty when deciding about treatment for nonmetastatic prostate cancer. The tool leads to more realistic perceptions about survival outcomes and prognosis.

Radical Cystectomy in England from 2013 to 2019 on 12,644 patients: An analysis of national trends and comparison of surgical approaches using Hospital Episode Statistics data.

Introduction: We evaluate the data of 12,644 Radical Cystectomies in England (Open, Robotic and Laparoscopic) with trends in the adaption of techniques and post-operative complications. Methods: This analysis utilised national Hospital Episode Statistics (HES) from NHS England. Results: There was a statistically significant increase (P < .001) in the number of Robotic assisted radical cystectomies from 10.8% in 2013-2014 and 39.5% in 2018-2019.The average LOS reduced from 12.3 to 10.8 days for RARC from 2013 to 2019 similarly the LOS reduced from 16.2 to 14.3 for ORC. The rate of sepsis (0-90 days) did rise from 5% to 14.5% between 2013-2014 and 2017-2018 for the entire cohort (P < .001). Acute renal failure (ARF) increased over the years from 9.5% to 17% (P < .001). The rate for fever, UTI, critical care activity and ARF were higher for ORC than RARC (P < .001).The comparison of all episodes within 90 days for conduit versus non-conduit diversions showed significantly higher rates of sepsis, infections, UTI and fever in non-conduit group .Overall complications were significantly higher in non-conduit group throughout the duration except was year 2016-17(P < .001).The robotic approach has increased in last 5 years with nearly 40% of the cystectomies now being robotically in 2018-19 from the initial percentage of 10.8% in 2013-14. Conclusion: This evaluation of the HES data from NHS England for 12,644 RC confirms an increase in the adoption of Robotic Cystectomy. Our data confirms the need to develop strategies with enhanced recovery protocols and post-operative close monitoring following Radical Cystectomy in order to reduce post-operative complications.

Models predicting survival to guide treatment decision-making in newly diagnosed primary non-metastatic prostate cancer: a systematic review.

OBJECTIVES: Men diagnosed with non-metastatic prostate cancer require standardised and robust long-term prognostic information to help them decide on management. Most currently-used tools use short-term and surrogate outcomes. We explored the evidence base in the literature on available pre-treatment, prognostic models built around long-term survival and assess the accuracy, generalisability and clinical availability of these models. DESIGN: Systematic literature review, pre-specified and registered on PROSPERO (CRD42018086394). DATA SOURCES: MEDLINE, Embase and The Cochrane Library were searched from January 2000 through February 2018, using previously-tested search terms. ELIGIBILITY CRITERIA: Inclusion required a multivariable model prognostic model for non-metastatic prostate cancer, using long-term survival data (defined as ≥5 years), which was not treatment-specific and usable at the point of diagnosis. DATA EXTRACTION AND SYNTHESIS: Title, abstract and full-text screening were sequentially performed by three reviewers. Data extraction was performed for items in the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Individual studies were assessed using the new Prediction model Risk Of Bias ASsessment Tool. RESULTS: Database searches yielded 6581 studies after deduplication. Twelve studies were included in the final review. Nine were model development studies using data from over 231 888 men. However, only six of the nine studies included any conservatively managed cases and only three of the nine included treatment as a predictor variable. Every included study had at least one parameter for which there was high risk of bias, with failure to report accuracy, and inadequate reporting of missing data common failings. Three external validation studies were included, reporting two available models: The University of California San Francisco (UCSF) Cancer of the Prostate Risk Assessment score and the Cambridge Prognostic Groups. Neither included treatment effect, and both had potential flaws in design, but represent the most robust and usable prognostic models currently available. CONCLUSION: Few long-term prognostic models exist to inform decision-making at diagnosis of non-metastatic prostate cancer. Improved models are required to inform management and avoid undertreatment and overtreatment of non-metastatic prostate cancer.

Magnetic Resonance Imaging-targeted Biopsy Versus Systematic Biopsy in the Detection of Prostate Cancer: A Systematic Review and Meta-analysis.

CONTEXT: Magnetic resonance imaging (MRI)-targeted prostate biopsy (MRI-TB) may be an alternative to systematic biopsy for diagnosing prostate cancer. OBJECTIVE: The primary aims of this systematic review and meta-analysis were to compare the detection rates of clinically significant and clinically insignificant cancer by MRI-TB with those by systematic biopsy in men undergoing prostate biopsy to identify prostate cancer. EVIDENCE ACQUISITION: A literature search was conducted using the PubMed, Embase, Web of Science, Cochrane library, and Clinicaltrials.gov databases. We included prospective and retrospective paired studies where the index test was MRI-TB and the comparator test was systematic biopsy. We also included randomised controlled trials (RCTs) if one arm included MRI-TB and another arm included systematic biopsy. The risk of bias was assessed using a modified Quality Assessment of Diagnostic Accuracy Studies-2 checklist. In addition, the Cochrane risk of bias 2.0 tool was used for RCTs. EVIDENCE SYNTHESIS: We included 68 studies with a paired design and eight RCTs, comprising a total of 14709 men who either received both MRI-TB and systematic biopsy, or were randomised to receive one of the tests. MRI-TB detected more men with clinically significant cancer than systematic biopsy (detection ratio [DR] 1.16 [95% confidence interval {CI} 1.09-1.24], p<0.0001) and fewer men with clinically insignificant cancer than systematic biopsy (DR 0.66 [95% CI 0.57-0.76], p<0.0001). The proportion of cores positive for cancer was greater for MRI-TB than for systematic biopsy (relative risk 3.17 [95% CI 2.82-3.56], p<0.0001). CONCLUSIONS: MRI-TB is an attractive alternative diagnostic strategy to systematic biopsy. PATIENT SUMMARY: We evaluated the published literature, comparing two methods of diagnosing prostate cancer. We found that biopsies targeted to suspicious areas on magnetic resonance imaging were better at detecting prostate cancer that needs to be treated and avoiding the diagnosis of disease that does not need treatment than the traditional systematic biopsy.

General practitioner perception of prostate-specific antigen testing has improved, but more awareness of prostate cancer risk in younger patients is still awaited.

BACKGROUND: In 2006, a county-wide survey of general practitioners (GPs) in the United Kingdom (UK) identified a reluctance to refer younger men with abnormal prostate specific antigen (PSA) levels. Younger men have the most to gain from early-detection of prostate cancer (PCa), which remains a national government priority in the UK and around the world. We sought to assess changes in perception of abnormal PSA-values amongst UK GPs over the past 10 years. MATERIALS AND METHODS: A total of 500 self-administered paper questionnaires were distributed to individually named GPs. One hundred and forty two responded (28.4%), representing a patient population of ∼600,000. A series of visual analogue questions assessed referral thresholds and understanding of risk factors related to the development of PCa. RESULTS: GPs with a median of 23-years experience responded. Although mean PSA threshold for referral to urology did fall between 2006 and 2016 in both the 45-year (5.42 ng/mL vs. 4.61 ng/mL P = 0.0003) and 55-year (5.81 ng/mL vs. 5.30 ng/mL P = 0.0164) age groups, the median referral values were unchanged. Significantly, referral thresholds quoted for younger men (<65 years) were considerably higher than recommended UK maximum PSA-levels. Using case-based scenarios, practitioners appeared more likely to refer older men with abnormal PSA values, with GPs reporting an average 56.2% likelihood of referring an asymptomatic 55-year-old with elevated age-adjusted PSA of 4.6 ng/mL. A total of 95.1% recognised a family history of PCa to be a potential risk factor but other at-risk categories were not so clearly understood. CONCLUSION: Awareness of abnormal PSA values in UK primary care is improving, but continues to lag behind the evidence. Strategies to disseminate knowledge of maximum PSA-values to GPs should focus especially on those for younger patients.

Colonoscopic polyp detection rate is stable throughout the workday including evening colonoscopy sessions.

OBJECTIVE: Polyp detection rate (PDR) is an accepted measure of colonoscopy quality. Several factors may influence PDR including time of procedure and order of colonoscopy within a session. Our unit provides evening colonoscopy lists (6-9 pm). We examined whether colonoscopy performance declines in the evening. DESIGN: Data for all National Health Service (NHS) outpatient colonoscopies performed at Norfolk and Norwich University Hospital in 2011 were examined. Timing, demographics, indication and colonoscopy findings were recorded. Statistical analysis was performed using multivariate regression. RESULTS: Data from 2576 colonoscopies were included: 1163 (45.1%) in the morning, 1123 (43.6%) in the afternoon and 290 (11.3%) in the evening.  Overall PDR was 40.80%. Males, increasing age and successful caecal intubation were all significantly associated with higher polyp detection. The indications 'faecal occult blood screening' (p<0.001) and 'polyp surveillance' (p<0.001) were strongly positively associated and 'anaemia' (p=0.01) was negatively associated with PDR. Following adjustment for  covariates, there was no significant difference in PDR between sessions. With the morning as the reference value, the odds ratio for polyp detection in the afternoon and evening were 0.93 (95% CI = 0.72-1.18) and 1.15 (95%CI = 0.82-1.61) respectively. PDR was not affected by rank of colonoscopy within a list, sedation dose or trainee-involvement. CONCLUSIONS: Time of day did not affect polyp detection rate in clinical practice. Evening colonoscopy had equivalent efficacy and is an effective tool in meeting increasing demands for endoscopy. Standardisation was shown to have a considerable effect as demographics, indication and endoscopist varied substantially between sessions. Evening sessions were popular with a younger population.