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This study was conducted to describe the changes in repeat multiparametric MRI (mpMRI) occurring in prostate cancer (PCa) patients during active surveillance (AS), and to study possible associations between mpMRI-related parameters in predicting prostate biopsy (Bx) Gleason score (GS) upgrading >3+3 and protocol-based treatment change (TC). The study cohort consisted of 76 AS patients with GS 3+3 PCa and at least two consecutive mpMRIs of the prostate performed between 2006-2015. Patients were followed according to the Prostate Cancer Research International Active Surveillance (PRIAS) protocol and an additional mpMRI. The primary end points were GS upgrading (GU) (>3+3) in protocol-based Bxs and protocol-based TC. Out of 76 patients, 53 (69%) had progression (PIRADS upgrade, size increase or new lesion[s]), while 18 (24%) had radiologically stable disease, and 5 (7%) had regression (PIRADS or size decrease, disappearance of lesion[s]) in repeat mpMRIs during AS. PIRADS scores of 4-5 in the initial mpMRI were associated with GU (p = 0.008) and protocol-based TC (p = 0.009). Tumour progression on repeat mpMRIs was associated with TC (p = 0.045) but not with GU (p = 1.00). PIRADS scores of 4-5 predict GU (sensitivity 0.80 [95% confidence interval (CI); 0.51-0.95, specificity 0.62 [95% CI; 0.52-0.77]) with PPV and NPV values of 0.34 (95% CI; 0.21-0.55) and 0.93 (95% CI; 0.80-0.98), respectively. mpMRI is a useful tool not only to select but also to monitor PCa patients on AS.

Background Healthcare costs are rising, and a substantial proportion of medical care is of little value. De-implementation of low-value practices is important for improving overall health outcomes and reducing costs. We aimed to identify and synthesize randomized controlled trials (RCTs) on de-implementation interventions and to provide guidance to improve future research. Methods MEDLINE and Scopus up to May 24, 2021, for individual and cluster RCTs comparing de-implementation interventions to usual care, another intervention, or placebo. We applied independent duplicate assessment of eligibility, study characteristics, outcomes, intervention categories, implementation theories, and risk of bias. Results Of the 227 eligible trials, 145 (64%) were cluster randomized trials (median 24 clusters; median follow-up time 305 days), and 82 (36%) were individually randomized trials (median follow-up time 274 days). Of the trials, 118 (52%) were published after 2010, 149 (66%) were conducted in a primary care setting, 163 (72%) aimed to reduce the use of drug treatment, 194 (85%) measured the total volume of care, and 64 (28%) low-value care use as outcomes. Of the trials, 48 (21%) described a theoretical basis for the intervention, and 40 (18%) had the study tailored by context-specific factors. Of the de-implementation interventions, 193 (85%) were targeted at physicians, 115 (51%) tested educational sessions, and 152 (67%) multicomponent interventions. Missing data led to high risk of bias in 137 (60%) trials, followed by baseline imbalances in 99 (44%), and deficiencies in allocation concealment in 56 (25%). Conclusions De-implementation trials were mainly conducted in primary care and typically aimed to reduce low-value drug treatments. Limitations of current de-implementation research may have led to unreliable effect estimates and decreased clinical applicability of studied de-implementation strategies. We identified potential research gaps, including de-implementation in secondary and tertiary care settings, and interventions targeted at other than physicians. Future trials could be improved by favoring simpler intervention designs, better control of potential confounders, larger number of clusters in cluster trials, considering context-specific factors when planning the intervention (tailoring), and using a theoretical basis in intervention design. Registration OSF Open Science Framework hk4b2

After surgery of localized renal cell carcinoma, over 20% of the patients will develop distant metastases. Our aim was to develop an easy-to-use prognostic model for predicting metastasis-free survival after radical or partial nephrectomy of localized clear cell RCC. Model training was performed on 196 patients. Right-censored metastasis-free survival was analysed using LASSO-regularized Cox regression, which identified three key prediction features. The model was validated in an external cohort of 714 patients. 55 (28%) and 134 (19%) patients developed distant metastases during the median postoperative follow-up of 6.3 years (interquartile range 3.4–8.6) and 5.4 years (4.0–7.6) in the training and validation cohort, respectively. Patients were stratified into clinically meaningful risk categories using only three features: tumor size, tumor grade and microvascular invasion, and a representative nomogram and a visual prediction surface were constructed using these features in Cox proportional hazards model. Concordance indices in the training and validation cohorts were 0.755 ± 0.029 and 0.836 ± 0.015 for our novel model, which were comparable to the C-indices of the original Leibovich prediction model (0.734 ± 0.035 and 0.848 ± 0.017, respectively). Thus, the presented model retains high accuracy while requiring only three features that are routinely collected and widely available.

Background The aim of this study is to investigate the potential impact of prostate magnetic resonance imaging (MRI) -related interreader variability on a population-based randomized prostate cancer screening trial (ProScreen). Methods From January 2014 to January 2018, 100 men aged 50–63 years with clinical suspicion of prostate cancer (PCa) in Helsinki University Hospital underwent MRI. Nine radiologists individually reviewed the pseudonymized MRI scans of all 100 men in two ProScreen trial centers. All 100 men were biopsied according to a histological composite variable comprising radical prostatectomy histology ( N  = 38) or biopsy result within 1 year from the imaging ( N  = 62). Fleiss’ kappa (κ) was used to estimate the combined agreement between all individual radiologists. Sample data were subsequently extrapolated to 1000-men subgroups of the ProScreen cohort. Results Altogether 89% men of the 100-men sample were diagnosed with PCa within a median of 2.4 years of follow-up. Clinically significant PCa (csPCa) was identified in 76% men. For all PCa, mean sensitivity was 79% (SD ±10%, range 62–96%), and mean specificity 60% (SD ±22%, range 27–82%). For csPCa (Gleason Grade 2–5) MRI was equally sensitive (mean 82%, SD ±9%, range 67–97%) but less specific (mean 47%, SD ±20%, range 21–75%). Interreader agreement for any lesion was fair (κ 0.40) and for PI-RADS 4–5 lesions it was moderate (κ 0.60). Upon extrapolating these data, the average sensitivity and specificity to a screening positive subgroup of 1000 men from ProScreen with a 30% prevalence of csPCa, 639 would be biopsied. Of these, 244 men would be true positive, and 395 false positive. Moreover, 361 men would not be referred to biopsy and among these, 56 csPCas would be missed. The variation among the radiologists was broad as the least sensitive radiologist would have twice as many men biopsied and almost three times more men would undergo unnecessary biopsies. Although the most sensitive radiologist would miss only 2.6% of csPCa (false negatives), the least sensitive radiologist would miss every third. Conclusions Interreader agreement was fair to moderate. The role of MRI in the ongoing ProScreen trial is crucial and has a substantial impact on the screening process.

Purpose Prostate cancer (PCa) histology, particularly the Gleason score, is an independent prognostic predictor in PCa. Little is known about the inter-reader variability in grading of targeted prostate biopsy based on magnetic resonance imaging (MRI). The aim of this study was to assess inter-reader variability in Gleason grading of MRI-targeted biopsy among uropathologists and its potential impact on a population-based randomized PCa screening trial (ProScreen). Methods From June 2014 to May 2018, 100 men with clinically suspected PCa were retrospectively selected. All men underwent prostate MRI and 86 underwent targeted prostate of the prostate. Six pathologists individually reviewed the pathology slides of the prostate biopsies. The five-tier ISUP (The International Society of Urological Pathology) grade grouping (GG) system was used. Fleiss’ weighted kappa ( κ ) and Model-based kappa for associations were computed to estimate the combined agreement between individual pathologists. Results GG reporting of targeted prostate was highly consistent among the trial pathologists. Inter-reader agreement for cancer (GG1–5) vs. benign was excellent (Model-based kappa 0.90, Fleiss’ kappa κ  = 0.90) and for clinically significant prostate cancer (csPCa) (GG2–5 vs. GG0 vs. GG1), it was good (Model-based kappa 0.70, Fleiss’ kappa κ 0.67). Conclusions Inter-reader agreement in grading of MRI-targeted biopsy was good to excellent, while it was fair to moderate for MRI in the same cohort, as previously shown. Importantly, there was wide consensus by pathologists in assigning the contemporary GG on MRI-targeted biopsy suggesting high reproducibility of pathology reporting in the ProScreen trial.

Background De-implementation of low-value care can increase health care sustainability. We evaluated the reporting of direct costs of de-implementation and subsequent change (increase or decrease) in health care costs in randomized trials of de-implementation research. Methods We searched MEDLINE and Scopus databases without any language restrictions up to May 2021. We conducted study screening and data extraction independently and in duplicate. We extracted information related to study characteristics, types and characteristics of interventions, de-implementation costs, and impacts on health care costs. We assessed risk of bias using a modified Cochrane risk-of-bias tool. Results We screened 10,733 articles, with 227 studies meeting the inclusion criteria, of which 50 included information on direct cost of de-implementation or impact of de-implementation on health care costs. Studies were mostly conducted in North America (36%) or Europe (32%) and in the primary care context (70%). The most common practice of interest was reduction in the use of antibiotics or other medications (74%). Most studies used education strategies (meetings, materials) (64%). Studies used either a single strategy (52%) or were multifaceted (48%). Of the 227 eligible studies, 18 (8%) reported on direct costs of the used de-implementation strategy; of which, 13 reported total costs, and 12 reported per unit costs (7 reported both). The costs of de-implementation strategies varied considerably. Of the 227 eligible studies, 43 (19%) reported on impact of de-implementation on health care costs. Health care costs decreased in 27 studies (63%), increased in 2 (5%), and were unchanged in 14 (33%). Conclusion De-implementation randomized controlled trials typically did not report direct costs of the de-implementation strategies (92%) or the impacts of de-implementation on health care costs (81%). Lack of cost information may limit the value of de-implementation trials to decision-makers. Trial registration OSF (Open Science Framework): https://osf.io/ueq32 .

Precise cause of death (CoD) ascertainment is crucial in any cancer screening trial to avoid bias from misclassification due to excessive recording of diagnosed cancer as a CoD in death certificates instead of non-cancer disease that actually caused death. We estimated whether there was bias in CoD determination between screening (SA) and control arms (CA) in a population-based prostate cancer (PCa) screening trial. Our trial is the largest component of the European Randomized Study of Screening for Prostate Cancer with more than 80,000 men. Randomly selected deaths in men with PCa (N=442/2568 cases, 17.2%) were reviewed by an independent CoD committee. Median follow-up was 16.8 years in both arms. Overdiagnosis of PCa was present in the SA as the risk ratio for PCa incidence was 1.19 (95% confidence interval (CI) 1.14–1.24). The hazard ratio (HR) for PCa mortality was 0.94 (95%CI 0.82–1.08) in favor of the SA. Agreement with official CoD registry was 94.6% (κ=0.88) in the SA and 95.4% (κ=0.91) in the CA. Altogether 14 PCa deaths were estimated as false-positive in both arms and exclusion of these resulted in HR 0.92 (95% CI 0.80–1.06). A small differential misclassification bias in ascertainment of CoD was present, most likely due to attribution bias (overdiagnosis in the SA). Maximum precision in CoD ascertainment can only be achieved with independent review of all deaths in the diseased population. However, this is cumbersome and expensive and may provide little benefit compared to random sampling.

ObjectiveTo evaluate the effectiveness of various de-implementation interventions in primary care, targeting care (treatments or tests) that provides no or limited value for patients (low value care).DesignSystematic review and meta-analysis.Data sourcesMedline and Scopus databases, from inception to 10 July 2024.Eligibility criteria for selecting studiesRandomised trials comparing de-implementation interventions with placebo or sham intervention, no intervention, or other de-implementation intervention strategies in primary care. Eligible trials provided information on the use of low value care, total volume of care, appropriate care, and health outcomes.Data extraction and synthesisTitles, abstracts, and full texts were screened, data were extracted, and risk of bias was assessed independently and in duplicate. Random effects meta-analyses were conducted, and the certainty of evidence was assessed with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.Results13 008 abstracts were screened and 140 were eligible for inclusion in the study. Median follow-up was 287 days (interquartile range 180-365). In 75 (54%) trials the aim was to reduce the use of antibiotics, in 42 (30%) to reduce other drug treatments, in 17 (12%) to reduce imaging, and in 15 (11%) to reduce laboratory testing. The certainty of the evidence was moderate that provider education combined with audit and feedback reduced the use of targeted low value care (odds ratio 0.73, 95% confidence interval (95% CI) 0.63 to 0.84). Provider education (0.86, 95% CI 0.72 to 1.03), audit and feedback (0.82, 0.67 to 1.00), and patient education (0.70, 0.30 to 1.66), and a combination of these strategies (point estimates for odds ratios ranging from 0.57 to 0.64) may reduce the use of targeted low value care (low certainty of evidence for all).ConclusionsThe results suggested with moderate certainty of evidence that provider education combined with audit and feedback reduced the use of targeted low value care. Individual strategies may slightly reduce the use of targeted low value care, but achieving a meaningful impact on low value care may require the use of multiple strategies. The results may be useful for patients, clinicians, policy makers, and guideline developers when deciding on future de-implementation strategies and research priorities.Systematic review registrationPROSPERO CRD42023411768.

Background To determine the added value of preoperative prostate multiparametric MRI (mpMRI) supplementary to clinical variables and their role in predicting post prostatectomy adverse findings and biochemically recurrent cancer (BCR). Methods All consecutive patients treated at HUS Helsinki University Hospital with robot assisted radical prostatectomy (RALP) between 2014 and 2015 were included in the analysis. The mpMRI data, clinical variables, histopathological characteristics, and follow-up information were collected. Study end-points were adverse RALP findings: extraprostatic extension, seminal vesicle invasion, lymph node involvement, and BCR. The Memorial Sloan Kettering Cancer Center (MSKCC) nomogram, Cancer of the Prostate Risk Assessment (CAPRA) score and the Partin score were combined with any adverse findings at mpMRI. Predictive accuracy for adverse RALP findings by the regression models was estimated before and after the addition of MRI results. Logistic regression, area under curve (AUC), decision curve analyses, Kaplan-Meier survival curves and Cox proportional hazard models were used. Results Preoperative mpMRI data from 387 patients were available for analysis. Clinical variables alone, MSKCC nomogram or Partin tables were outperformed by models with mpMRI for the prediction of any adverse finding at RP. AUC for clinical parameters versus clinical parameters and mpMRI variables were 0.77 versus 0.82 for any adverse finding. For MSKCC nomogram versus MSKCC nomogram and mpMRI variables the AUCs were 0.71 and 0.78 for any adverse finding. For Partin tables versus Partin tables and mpMRI variables the AUCs were 0.62 and 0.73 for any adverse finding. In survival analysis, mpMRI-projected adverse RP findings stratify CAPRA and MSKCC high-risk patients into groups with distinct probability for BCR. Conclusions Preoperative mpMRI improves the predictive value of commonly used clinical variables for pathological stage at RP and time to BCR. mpMRI is available for risk stratification prebiopsy, and should be considered as additional source of information to the standard predictive nomograms.