Estimating Bleeding Risk in Patients with Cancer-Associated Thrombosis: Evaluation of Existing Risk Scores and Development of a New Risk Score

Abstract Background Bleeding risk is highly relevant for treatment decisions in cancer-associated thrombosis (CAT). Several risk scores exist, but have never been validated in patients with CAT and are not recommended for practice. Objectives To compare methods of estimating clinically relevant (major and clinically relevant nonmajor) bleeding risk in patients with CAT: (1) existing risk scores for bleeding in venous thromboembolism, (2) pragmatic classification based on cancer type, and (3) new prediction model. Methods In a posthoc analysis of the Hokusai VTE Cancer study, a randomized trial comparing edoxaban with dalteparin for treatment of CAT, seven bleeding risk scores were externally validated (ACCP-VTE, HAS-BLED, Hokusai, Kuijer, Martinez, RIETE, and VTE-BLEED). The predictive performance of these scores was compared with a pragmatic classification based on cancer type (gastrointestinal; genitourinary; other) and a newly derived competing risk-adjusted prediction model based on clinical predictors for clinically relevant bleeding within 6 months after CAT diagnosis with nonbleeding-related mortality as the competing event (“CAT-BLEED”). Results Data of 1,046 patients (149 events) were analyzed. Predictive performance of existing risk scores was poor to moderate (C-statistics: 0.50–0.57; poor calibration). Internal validation of the pragmatic classification and “CAT-BLEED” showed moderate performance (respective C-statistics: 0.61; 95% confidence interval [CI]: 0.56–0.66, and 0.63; 95% CI 0.58–0.68; good calibration). Conclusion Existing risk scores for bleeding perform poorly after CAT. Pragmatic classification based on cancer type provides marginally better estimates of clinically relevant bleeding risk. Further improvement may be achieved with “CAT-BLEED,” but this requires external validation in practice-based settings and with other DOACs and its clinical usefulness is yet to be demonstrated.

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Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data

BMJ ◽

10.1136/bmj.l4293 ◽

2019 ◽

pp. l4293 ◽

Cited By ~ 3

Author(s):

Mohammed T Hudda ◽

Mary S Fewtrell ◽

Dalia Haroun ◽

Sooky Lum ◽

Jane E Williams ◽

...

Keyword(s):

Confidence Interval ◽

Prediction Model ◽

Fat Mass ◽

Meta Analysis ◽

External Validation ◽

Predictive Performance ◽

Individual Participant Data ◽

Internal Validation ◽

Individual Participant ◽

Complex Forms

Abstract Objectives To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need for more complex forms of assessment. Design Individual participant data meta-analysis. Setting Four population based cross sectional studies and a fifth study for external validation, United Kingdom. Participants A pooled derivation dataset (four studies) of 2375 children and an external validation dataset of 176 children with complete data on anthropometric measurements and deuterium dilution assessments of fat mass. Main outcome measure Multivariable linear regression analysis, using backwards selection for inclusion of predictor variables and allowing non-linear relations, was used to develop a prediction model for fat-free mass (and subsequently fat mass by subtracting resulting estimates from weight) based on the four studies. Internal validation and then internal-external cross validation were used to examine overfitting and generalisability of the model’s predictive performance within the four development studies; external validation followed using the fifth dataset. Results Model derivation was based on a multi-ethnic population of 2375 children (47.8% boys, n=1136) aged 4-15 years. The final model containing predictor variables of height, weight, age, sex, and ethnicity had extremely high predictive ability (optimism adjusted R 2 : 94.8%, 95% confidence interval 94.4% to 95.2%) with excellent calibration of observed and predicted values. The internal validation showed minimal overfitting and good model generalisability, with excellent calibration and predictive performance. External validation in 176 children aged 11-12 years showed promising generalisability of the model (R 2 : 90.0%, 95% confidence interval 87.2% to 92.8%) with good calibration of observed and predicted fat mass (slope: 1.02, 95% confidence interval 0.97 to 1.07). The mean difference between observed and predicted fat mass was −1.29 kg (95% confidence interval −1.62 to −0.96 kg). Conclusion The developed model accurately predicted levels of fat mass in children aged 4-15 years. The prediction model is based on simple anthropometric measures without the need for more complex forms of assessment and could improve the accuracy of assessments for body fatness in children (compared with those provided by body mass index) for effective surveillance, prevention, and management of clinical and public health obesity.

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Comparison of bleeding risk scores in patients with atrial fibrillation and cancer

EP Europace ◽

10.1093/europace/euab116.295 ◽

2021 ◽

Vol 23 (Supplement_3) ◽

Author(s):

D Pastori ◽

A Marang ◽

A Bisson ◽

J Herbert ◽

GYH Lip ◽

...

Keyword(s):

Atrial Fibrillation ◽

Bleeding Risk ◽

Hazard Ratio ◽

Risk Scores ◽

Cancer Type ◽

Gi Bleeding ◽

Bleeding Events ◽

Patients With Cancer ◽

Funding Sources ◽

Bleeding Score

Abstract Funding Acknowledgements Type of funding sources: None. Background. Cancer may increase bleeding risk in atrial fibrillation (AF), but the association between cancer type and specific bleeding events has been scarcely investigated. Furthermore, the performance of bleeding risk scores in this high-risk subgroup of patients is unclear. Purpose. To describe the incidence rate (IR) of major (MB), gastrointestinal (GI) bleeding and intracranial haemorrhage (ICH) according to cancer types. We also investigated the performance of HAS-BLED, ATRIA and ORBIT scores. Methods Observational retrospective cohort study including 399,344 patients with AF and cancer. Results. Mean age was 77.9 ± 10.2 years and 63.2% were men. During 2.0 years follow-up, the IR of MB was as high as 8.41%/y, GI bleeding was 3.61%/y and ICH 1.33%/y. MBs were more frequent in liver (12.68%/y), leukaemia (12.39%/y), pancreas (11.71%/y), bladder (11.67%/y) and myeloma (11.64%/y). GI bleedings were highest in liver (7.54%/y), pancreas (7.42%/y) and gastric (5.51%/y). ICH was highest in leukaemia (1.89%/y), myeloma (1.52%/y), lymphoma/liver (1.45%/y) and pancreas (1.41%/y) cancer. The Table shows the hazard ratio and AUC values for each bleeding score. All the three scores significantly associated with bleeding outcomes, with the HAS-BLED score performing better than others for ICH prediction, and the ORBIT score predicting MB and GI bleedings (p < 0.0001 for all AUC comparisons). Conclusions. Cancer increases the risk of bleeding in patients with cancer, with specific differences according to each cancer type. HAS-BLED score showed the best predictive value for ICH and the ORBIT score for MB and GI bleeding. MB GI bleeding ICH Hazard Ratio (95%CI) HASBLED score≥3 6.575 (6.390-6.765) 5.735 (5.502-5.978) 5.803 (5.416-6.218) ATRIA score≥5 5.372 (5.241-5.506) 3.617 (3.499-3.739) 1.469 (1.403-1.538) ORBIT score≥4 13.326 (12.977-13.686) 7.453 (7.202-7.712) 2.578 (2.463-2.699) AUC (95%CI) HASBLED score≥3 0.716 (0.714-0.718) 0.702 (0.699-0.704) 0.698 (0.694-0.702) ATRIA score≥5 0.700 (0.698-0.702) 0.662 (0.659-0.665) 0.563 (0.557-0.568) ORBIT score≥4 0.805 (0.804-0.807) 0.756 (0.753-0.758) 0.641 (0.635-0.646) AUC Difference (95% CI) HASBLED≥3 vs ATRIA≥5 0.016 (0.014-0.018) 0.040 (0.037-0.042) 0.136 (0.133-0.138) HASBLED≥3 vs ORBIT≥4 -0.089 (-0.091–0.087) -0.054 (-0.056–0.052) 0.057 (0.055-0.059) ATRIA≥5 vsORBIT≥4 -0.106 (-0.108–0.104) -0.094 (-0.095–0.092) -0.078 (-0.080–0.076)

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Comparison of the HAS-BLED, ORBIT and ATRIA bleeding risk scores in 399,344 patients with atrial fibrillation and cancer

European Heart Journal ◽

10.1093/eurheartj/ehab724.0438 ◽

2021 ◽

Vol 42 (Supplement_1) ◽

Author(s):

D Pastori ◽

A Marang ◽

A Bisson ◽

J Herbert ◽

G.Y.H Lip ◽

...

Keyword(s):

Atrial Fibrillation ◽

High Risk ◽

Bleeding Risk ◽

Risk Scores ◽

Cancer Type ◽

Gi Bleeding ◽

Bleeding Events ◽

Patients With Cancer ◽

Funding Sources ◽

Hazard Ratios

Abstract Background The presence of cancer worsens the prognosis of patients with atrial fibrillation (AF). However, the association between cancer type and specific bleeding events has been scarcely investigated. Furthermore, the performance of bleeding risk scores, such HAS-BLED, ORBIT and ATRIA, in this high-risk subgroup of AF patients is unclear. Purpose To investigate the incidence rate (IR) of major, gastrointestinal (GI) bleeding and intracranial haemorrhage (ICH) according to cancer types. We also investigated the performance of HAS-BLED, ATRIA and ORBIT scores. HASBLED ≥3, ATRIA ≥5 and ORBIT ≥4 were defined as high-risk. Methods Observational retrospective cohort study including 399,344 patients with AF and cancer. Results Mean age was 77.9±10.2 years and 63.2% were men. During a mean follow-up of 2.0 years, the IR of major bleeding was as high as 8.41%/year, GI bleeding was 3.61%/year and ICH 1.33%/year. Major bleedings were more frequent in liver (12.68%/year), leukaemia (12.39%/year), pancreas (11.71%/year), bladder (11.67%/year) and myeloma (11.64%/year). GI bleeding were highest in liver (7.54%/year), pancreas (7.42%/year) and gastric (5.51%/year). The highest IR of ICH was found in leukaemia (1.89%/year), myeloma (1.52%/year), lymphoma and liver (1.45%/year) and pancreas cancer (1.41%/year). Figure 1 shows the hazard ratios and AUC values for the three scores against each endpoint. All the three scores were significantly associated with major, GI and ICH. The HAS-BLED score performed better than others for ICH prediction, while the ORBIT score showed the best predictivity for major and GI bleedings (p<0.0001 for all AUC comparisons) Conclusions Cancer increases the risk of bleeding in patients with cancer, with specific differences according to each cancer type. HAS-BLED score identified patients at highest risk for ICH and the ORBIT score for major and GI bleeding. FUNDunding Acknowledgement Type of funding sources: None. Figure 1

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Comparison of Bleeding Risk Scores in Elderly Patients Receiving Extended Anticoagulation with Vitamin K Antagonists for Venous Thromboembolism

Thrombosis and Haemostasis ◽

10.1055/s-0041-1726345 ◽

2021 ◽

Author(s):

Andrea N. Frei ◽

Odile Stalder ◽

Andreas Limacher ◽

Marie Méan ◽

Christine Baumgartner ◽

...

Keyword(s):

Venous Thromboembolism ◽

Elderly Patients ◽

Vitamin K ◽

Vitamin K Antagonists ◽

Predictive Performance ◽

Roc Curves ◽

Bleeding Risk ◽

Risk Scores ◽

Likelihood Ratios ◽

Risk Categories

Abstract Background In elderly patients with venous thromboembolism (VTE), the decision to extend anticoagulation beyond 3 months must be weighed against the bleeding risk. We compared the predictive performance of 10 clinical bleeding scores (VTE-BLEED, Seiler, Kuijer, Kearon, RIETE, ACCP, OBRI, HEMORR2HAGES, HAS-BLED, ATRIA) in elderly patients receiving extended anticoagulation for VTE. Methods In a multicenter Swiss cohort study, we analyzed 743 patients aged ≥65 years who received extended treatment with vitamin K antagonists after VTE. The outcomes were the time to a first major and clinically relevant bleeding. For each score, we classified patients into two bleeding risk categories (low/moderate vs. high). We calculated likelihood ratios and the area under the receiver operating characteristic (ROC) curve for each score. Results Over a median anticoagulation duration of 10.1 months, 45 patients (6.1%) had a first major and 127 (17.1%) a clinically relevant bleeding. The positive likelihood ratios for predicting major bleeding ranged from 0.69 (OBRI) to 2.56 (Seiler) and from 1.07 (ACCP) to 2.36 (Seiler) for clinically relevant bleeding. The areas under the ROC curves were poor to fair and varied between 0.47 (OBRI) and 0.70 (Seiler) for major and between 0.52 (OBRI) and 0.67 (HEMORR2HAGES) for clinically relevant bleeding. Conclusion The predictive performance of most clinical bleeding risk scores does not appear to be sufficiently high to identify elderly patients with VTE who are at high risk of bleeding and who may therefore not be suitable candidates for extended anticoagulation.

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P–419 On prognosis after unexplained recurrent pregnancy losses (RPL); a systematic review and external validation of clinical prediction models

Human Reproduction ◽

10.1093/humrep/deab130.418 ◽

2021 ◽

Vol 36 (Supplement_1) ◽

Author(s):

A Youssef

Keyword(s):

Systematic Review ◽

Supportive Care ◽

Prediction Model ◽

Pregnancy Outcome ◽

Prediction Models ◽

External Validation ◽

Model Development ◽

Predictive Performance ◽

Pregnancy Rates ◽

Cochrane Library

Abstract Study question Which models that predict pregnancy outcome in couples with unexplained RPL exist and what is the performance of the most used model? Summary answer We identified seven prediction models; none followed the recommended prediction model development steps. Moreover, the most used model showed poor predictive performance. What is known already RPL remains unexplained in 50–75% of couples For these couples, there is no effective treatment option and clinical management rests on supportive care. Essential part of supportive care consists of counselling on the prognosis of subsequent pregnancies. Indeed, multiple prediction models exist, however the quality and validity of these models varies. In addition, the prediction model developed by Brigham et al is the most widely used model, but has never been externally validated. Study design, size, duration We performed a systematic review to identify prediction models for pregnancy outcome after unexplained RPL. In addition we performed an external validation of the Brigham model in a retrospective cohort, consisting of 668 couples with unexplained RPL that visited our RPL clinic between 2004 and 2019. Participants/materials, setting, methods A systematic search was performed in December 2020 in Pubmed, Embase, Web of Science and Cochrane library to identify relevant studies. Eligible studies were selected and assessed according to the TRIPOD) guidelines, covering topics on model performance and validation statement. The performance of predicting live birth in the Brigham model was evaluated through calibration and discrimination, in which the observed pregnancy rates were compared to the predicted pregnancy rates. Main results and the role of chance Seven models were compared and assessed according to the TRIPOD statement. This resulted in two studies of low, three of moderate and two of above average reporting quality. These studies did not follow the recommended steps for model development and did not calculate a sample size. Furthermore, the predictive performance of neither of these models was internally- or externally validated. We performed an external validation of Brigham model. Calibration showed overestimation of the model and too extreme predictions, with a negative calibration intercept of –0.52 (CI 95% –0.68 – –0.36), with a calibration slope of 0.39 (CI 95% 0.07 – 0.71). The discriminative ability of the model was very low with a concordance statistic of 0.55 (CI 95% 0.50 – 0.59). Limitations, reasons for caution None of the studies are specifically named prediction models, therefore models may have been missed in the selection process. The external validation cohort used a retrospective design, in which only the first pregnancy after intake was registered. Follow-up time was not limited, which is important in counselling unexplained RPL couples. Wider implications of the findings: Currently, there are no suitable models that predict on pregnancy outcome after RPL. Moreover, we are in need of a model with several variables such that prognosis is individualized, and factors from both the female as the male to enable a couple specific prognosis. Trial registration number Not applicable

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GARFIELD-AF model for prediction of stroke and major bleeding in atrial fibrillation: a Danish nationwide validation study

BMJ Open ◽

10.1136/bmjopen-2019-033283 ◽

2019 ◽

Vol 9 (11) ◽

pp. e033283 ◽

Cited By ~ 3

Author(s):

Frederik Dalgaard ◽

Karen Pieper ◽

Freek Verheugt ◽

A John Camm ◽

Keith AA Fox ◽

...

Keyword(s):

Atrial Fibrillation ◽

Ischaemic Stroke ◽

Major Bleeding ◽

Risk Model ◽

Oral Anticoagulants ◽

External Validation ◽

Bleeding Risk ◽

Risk Scores ◽

Secondary Outcome

ObjectivesTo externally validate the accuracy of the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) model against existing risk scores for stroke and major bleeding risk in patients with non-valvular AF in a population-based cohort.DesignRetrospective cohort study.SettingDanish nationwide registries.Participants90 693 patients with newly diagnosed non-valvular AF were included between 2010 and 2016, with follow-up censored at 1 year.Primary and secondary outcome measuresExternal validation was performed using discrimination and calibration plots. C-statistics were compared with CHA2DS2VASc score for ischaemic stroke/systemic embolism (SE) and HAS-BLED score for major bleeding/haemorrhagic stroke outcomes.ResultsOf the 90 693 included, 51 180 patients received oral anticoagulants (OAC). Overall median age (Q1, Q3) were 75 (66–83) years and 48 486 (53.5%) were male. At 1-year follow-up, a total of 2094 (2.3%) strokes/SE, 2642 (2.9%) major bleedings and 10 915 (12.0%) deaths occurred. The GARFIELD-AF model was well calibrated with the predicted risk for stroke/SE and major bleeding. The discriminatory value of GARFIELD-AF risk model was superior to CHA2DS2VASc for predicting stroke in the overall cohort (C-index: 0.71, 95% CI: 0.70 to 0.72 vs C-index: 0.67, 95% CI: 0.66 to 0.68, p<0.001) as well as in low-risk patients (C-index: 0.64, 95% CI: 0.59 to 0.69 vs C-index: 0.57, 95% CI: 0.53 to 0.61, p=0.007). The GARFIELD-AF model was comparable to HAS-BLED in predicting the risk of major bleeding in patients on OAC therapy (C-index: 0.64, 95% CI: 0.63 to 0.66 vs C-index: 0.64, 95% CI: 0.63 to 0.65, p=0.60).ConclusionIn a nationwide Danish cohort with non-valvular AF, the GARFIELD-AF model adequately predicted the risk of ischaemic stroke/SE and major bleeding. Our external validation confirms that the GARFIELD-AF model was superior to CHA2DS2VASc in predicting stroke/SE and comparable with HAS-BLED for predicting major bleeding.

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A Risk Score for Predicting the Incidence of Hemorrhage in Critically Ill Neonates: Development and Validation Study

Thrombosis and Haemostasis ◽

10.1055/s-0040-1715832 ◽

2020 ◽

Cited By ~ 1

Author(s):

Rozeta Sokou ◽

Daniele Piovani ◽

Aikaterini Konstantinidi ◽

Andreas G. Tsantes ◽

Stavroula Parastatidou ◽

...

Keyword(s):

Prediction Model ◽

Critically Ill ◽

Risk Score ◽

External Validation ◽

Prognostic Index ◽

Bleeding Risk ◽

Outcome Variable ◽

Calibration Plot ◽

Characteristic Analysis ◽

Critically Ill Neonates

AbstractThe aim of the study was to develop and validate a prediction model for hemorrhage in critically ill neonates which combines rotational thromboelastometry (ROTEM) parameters and clinical variables. This cohort study included 332 consecutive full-term and preterm critically ill neonates. We performed ROTEM and used the neonatal bleeding assessment tool (NeoBAT) to record bleeding events. We fitted double selection least absolute shrinkage and selection operator logit regression to build our prediction model. Bleeding within 24 hours of the ROTEM testing was the outcome variable, while patient characteristics, biochemical, hematological, and thromboelastometry parameters were the candidate predictors of bleeding. We used both cross-validation and bootstrap as internal validation techniques. Then, we built a prognostic index of bleeding by converting the coefficients from the final multivariable model of relevant prognostic variables into a risk score. A receiver operating characteristic analysis was used to calculate the area under curve (AUC) of our prediction index. EXTEM A10 and LI60, platelet counts, and creatinine levels were identified as the most robust predictors of bleeding and included them into a Neonatal Bleeding Risk (NeoBRis) index. The NeoBRis index demonstrated excellent model performance with an AUC of 0.908 (95% confidence interval [CI]: 0.870–0.946). Calibration plot displayed optimal calibration and discrimination of the index, while bootstrap resampling ensured internal validity by showing an AUC of 0.907 (95% CI: 0.868–0.947). We developed and internally validated an easy-to-apply prediction model of hemorrhage in critically ill neonates. After external validation, this model will enable clinicians to quantify the 24-hour bleeding risk.

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Direct comparison of predictive performance of PRECISE-DAPT versus PARIS versus CREDO-Kyoto: a subanalysis of the ReCre8 trial

Netherlands Heart Journal ◽

10.1007/s12471-020-01486-y ◽

2020 ◽

Author(s):

R. Rozemeijer ◽

W. P. van Bezouwen ◽

N. D. van Hemert ◽

J. A. Damen ◽

S. Koudstaal ◽

...

Keyword(s):

Risk Stratification ◽

Risk Score ◽

Invasive Procedure ◽

Predictive Performance ◽

Bleeding Risk ◽

Coronary Intervention ◽

Risk Scores ◽

Drug Eluting Stent ◽

Bleeding Events ◽

Post Discharge

Abstract Background Multiple scores have been proposed to guide risk stratification after percutaneous coronary intervention. This study assessed the performance of the PRECISE-DAPT, PARIS and CREDO-Kyoto risk scores to predict post-discharge ischaemic or bleeding events. Methods A total of 1491 patients treated with latest-generation drug-eluting stent implantation were evaluated. Risk scores for post-discharge ischaemic or bleeding events were calculated and directly compared. Prognostic performance of both risk scores was assessed with calibration, Harrell’s c‑statistics net reclassification index and decision curve analyses. Results Post-discharge ischaemic events occurred in 56 patients (3.8%) and post-discharge bleeding events in 34 patients (2.3%) within the first year after the invasive procedure. C‑statistics for the PARIS ischaemic risk score was marginal (0.59, 95% confidence interval (CI) 0.51–0.68), whereas the CREDO-Kyoto ischaemic risk score was moderate (0.68, 95% CI 0.60–0.75). With regard to post-discharge bleeding events, CREDO-Kyoto displayed moderate discrimination (c-statistic 0.67, 95% CI 0.56–0.77), whereas PRECISE-DAPT (0.59, 95% CI 0.48–0.69) and PARIS (0.55, 95% CI 0.44–0.65) had a marginal discriminative capacity. Net reclassification index and decision curve analysis favoured CREDO-Kyoto-derived bleeding risk assessment. Conclusion In this contemporary all-comer population, PARIS and PRECISE-DAPT risk scores were not resilient to independent testing for post-discharge bleeding events. CREDO-Kyoto-derived risk stratification was associated with a moderate predictive capability for post-discharge ischaemic or bleeding events. Future studies are warranted to improve risk stratification with more focus on robustness and rigorous testing.

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Development and external validation of a novel risk score to identify insignificant prostate cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.5073 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 5073-5073

Author(s):

Lorenzo Dutto ◽

Jorn H. Witt ◽

Katarina Urbanova ◽

Christian Wagner ◽

Andreas Schuette ◽

...

Keyword(s):

Prostate Cancer ◽

Radical Prostatectomy ◽

Risk Score ◽

External Validation ◽

Tumour Volume ◽

Risk Scores ◽

Clinical Predictors ◽

Predictive Tools ◽

Tertiary Referral Center ◽

Insignificant Prostate Cancer

5073 Background: Active surveillance is increasingly used for insignificant prostate cancer (PCa). In order to identify suitable patients, risk scores have been developed which use pre-operative factors. We evaluated the accuracy of 9 separate tools developed to identify patients harbouring insignificant PCa in 2613 patients who underwent radical prostatectomy for Gleason 3+3 PCa. We have developed and validated a novel risk score to correctly identify insignificant PCa for use in unscreened patient cohorts using non-dichotomised clinical predictors. Methods: 2799 patients who would have been candidates for AS (Gleason score 6 only) patients underwent robotic radical prostatectomy between 2006 and 2016 at a tertiary referral center. The volume and grade of tumour in the resected prostate was analysed. Inignificant PCa was defined as Gleason 3+3 only, index tumour volume <1.3 cm3 , total tumour volume <2.5 cm3 (updated ERSPC definition). 2613 patients were included in the final analysis. We computed the accuracy (specificity, sensitivity and area under the curve (AUC) of the receiver operator characteristic) of 9 predictive tools. Multivariate logistic regression with elastic net regularisation was used to develop a novel tool to predict insignificant prostate cancer using age at diagnosis, baseline PSA, TRUS volume, clinical T-stage, number of positive cores and percentage of positive cores as predictors. This tool was validated in an external cohort of 441 unscreened patients undergoing surgery for Gleason 6 PCa. Results: All of the predefined tools rated poorly as predictors of insignificant disease as none of them reached the required AUC threshold of 0.7. The new tool performed well in training and validation cohorts. Conclusions: Pre-existing predictive tools to identify indolent PCa have a poor predictive value when applied to an unscreened cohort of patients. Our novel tool shows good predictive power for insignificant PCa in this population in training and validation cohorts. The inherent selection bias due to analysis of a surgical cohort is acknowledged. [Table: see text]

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