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Simple Summary: The study introduces a ZBLN-based AFT model for predicting 3-year and 5-year survival in CSLCD patients with metastases, showing superior performance over other models. Proper selection of survival analysis models, like ZBLN, is crucial for accurate predictions in clinical settings. Comparison of survival outcomes indicates higher rates for lung cancer patients with bone metastases alone compared to those with bone and brain metastases. Associations between gender, race, treatment modalities, and histological types are noted. Background: This study addresses the significant challenge of low survival rates in patients with cause-specific lung cancer accompanied by bone or brain metastases. Recognizing the critical need for an effective predictive model, the research aims to establish survival prediction models using both parametric and non-parametric approaches. Methods: Clinical data from lung cancer patients with at least one bone or brain metastasis between 2000 and 2020 from the SEER database were utilized. Four models were constructed: Cox proportional hazard, Weibull accelerated failure time (AFT), log-normal AFT, and Zografos–Balakrishnan log-normal (ZBLN). Independent prognostic factors for cause-specific survival were identified, and model fit was evaluated using Akaike's and Bayesian information criteria. Internal validation assessed predictive accuracy and discriminability through the Harriel Concordance Index (C-index) and calibration plots. Results: A total of 20,412 patients were included, with 14,290 (70%) as the training cohort and 6122 (30%) validation. Independent prognostic factors selected for the study were age, race, sex, primary tumor site, disease grade, total malignant tumor in situ, metastases, treatment modality, and histology. Among the accelerated failure time (AFT) models considered, the ZBLN distribution exhibited the most robust model fit for the 3- and 5-year survival, as evidenced by the lowest values of Akaike's information criterion of 6322 and 79,396, and the Bayesian information criterion of 63,495 and 79,396, respectively. This outperformed other AFT and Cox models (AIC = [156,891, 211,125]; BIC = [158,848, 211,287]). Regarding predictive accuracy, the ZBLN AFT model achieved the highest concordance C-index (0.682, 0.667), a better performance than the Cox model (0.669, 0.643). The calibration curves of the ZBLN AFT model demonstrated a high degree of concordance between actual and predicted values. All variables considered in this study demonstrated significance at the 0.05 level for the ZBLN AFT model. However, differences emerged in the significant variations in survival times between subgroups. The study revealed that patients with only bone metastases have a higher chance of survival compared to only brain and those with bone and brain metastases. Conclusions: The study highlights the underutilized but accurate nature of the accelerated failure time model in predicting lung cancer survival and identifying prognostic factors. These findings have implications for individualized clinical decisions, indicating the potential for screening and professional care of lung cancer patients with at least one bone or brain metastasis in the future. [ABSTRACT FROM AUTHOR]

Developing and evaluating statistical prediction models is challenging, and many pitfalls can arise. This article identifies what the authors believe are some common methodologic concerns that may be encountered. We describe each problem and make suggestions regarding how to address them. The hope is that this article will result in higher-quality publications of statistical prediction models. [ABSTRACT FROM AUTHOR]

Background: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user.Methods: Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate cancer, defined as Gleason grade group ≥ 2 on standard TRUS prostate biopsy. One large European PBCG cohort was withheld for external validation, where calibration-in-the-large (CIL), calibration curves, and area-underneath-the-receiver-operating characteristic curve (AUC) were evaluated. Ten-fold leave-one-cohort-internal validation further validated the optimal missing data approach.Results: Among 12,703 biopsies from 10 training cohorts, 3,597 (28%) had clinically significant prostate cancer, compared to 1,757 of 5,540 (32%) in the external validation cohort. In external validation, the available cases method that pooled individual patient data containing all risk factors input by an end-user had best CIL, under-predicting risks as percentages by 2.9% on average, and obtained an AUC of 75.7%. Imputation had the worst CIL (-13.3%). The available cases method was further validated as optimal in internal cross-validation and thus used for development of an online risk tool. For end-users of the risk tool, two risk factors were mandatory: serum prostate-specific antigen (PSA) and age, and ten were optional: digital rectal exam, prostate volume, prior negative biopsy, 5-alpha-reductase-inhibitor use, prior PSA screen, African ancestry, Hispanic ethnicity, first-degree prostate-, breast-, and second-degree prostate-cancer family history.Conclusion: Developers of clinical risk prediction tools should optimize use of available data and sources even in the presence of high amounts of missing data and offer options for users with missing risk factors. [ABSTRACT FROM AUTHOR]

Considerable heterogeneity persists in the conduct and reporting of statistical analyses in the medical literature. Authors submitting manuscripts to CHEST are encouraged to adhere to the following guidelines where possible. [ABSTRACT FROM AUTHOR]

Cohort studies are types of observational studies in which a cohort, or a group of individuals sharing some characteristic, are followed up over time, and outcomes are measured at one or more time points. Cohort studies can be classified as prospective or retrospective studies, and they have several advantages and disadvantages. This article reviews the essential characteristics of cohort studies and includes recommendations on the design, statistical analysis, and reporting of cohort studies in respiratory and critical care medicine. Tools are provided for researchers and reviewers. [ABSTRACT FROM AUTHOR]

We have entered the era of "big data" and with that the explosion of interest in prediction modeling. With this explosion comes the challenge of evaluating statistical prediction models, both from the standpoint of an author as well as a reviewer. This article provides guidance for the evaluation and critique of a statistical prediction model. Hopefully, this will improve the quality of statistical prediction modeling studies and facilitate their review. [ABSTRACT FROM AUTHOR]

Considerable heterogeneity persists in the conduct and reporting of statistical analyses in the medical literature. Authors submitting manuscripts to CHEST are encouraged to adhere to the following guidelines where possible. [ABSTRACT FROM AUTHOR]

Cohort studies are types of observational studies in which a cohort, or a group of individuals sharing some characteristic, are followed up over time, and outcomes are measured at one or more time points. Cohort studies can be classified as prospective or retrospective studies, and they have several advantages and disadvantages. This article reviews the essential characteristics of cohort studies and includes recommendations on the design, statistical analysis, and reporting of cohort studies in respiratory and critical care medicine. Tools are provided for researchers and reviewers. [ABSTRACT FROM AUTHOR]

We have entered the era of "big data" and with that the explosion of interest in prediction modeling. With this explosion comes the challenge of evaluating statistical prediction models, both from the standpoint of an author as well as a reviewer. This article provides guidance for the evaluation and critique of a statistical prediction model. Hopefully, this will improve the quality of statistical prediction modeling studies and facilitate their review. [ABSTRACT FROM AUTHOR]

Given the number of confounders in predicting erectile function recovery after radical prostatectomy (RP), a nomogram predicting the chance to be functional after RP would be useful to patients' and clinicians' discussions. To develop preoperative and postoperative nomograms to aid in the prediction of erectile function recovery after RP. International Index of Erectile Function (IIEF) erectile function domain score-based erectile function. A prospective quality-of-life database was used to develop a series of nomograms using multivariable ordinal logistic regression models. Standard preoperative and postoperative factors were included. The nomograms predicted the probability of recovering functional erections (erectile function domain scores ≥24) and severe erectile dysfunction (≤10) 2 years after RP. 3 nomograms have been developed, including a preoperative, an early postoperative, and a 12-month postoperative version. The concordance indexes for all 3 exceeded 0.78, and the calibration was good. These nomograms may aid clinicians in discussing erectile function recovery with patients undergoing RP. Strengths of this study included a large population, validated instrument, nerve-sparing grading, and nomograms that are well calibrated with excellent discrimination ability. Limitations include current absence of external validation and an overall low comorbidity index. It is hoped that these nomograms will allow for a more accurate discussion between patients and clinicians regarding erectile function recovery after RP. Mulhall JP, Kattan MW, Bennett NE, et al. Development of Nomograms to Predict the Recovery of Erectile Function Following Radical Prostatectomy J Sex Med 2019;16:1796–1802. [ABSTRACT FROM AUTHOR]

We show that the widely used concordance index for time to event outcome is not proper when interest is in predicting a $t$-year risk of an event, for example 10-year mortality. In the situation with a fixed prediction horizon, the concordance index can be higher for a misspecified model than for a correctly specified model. Impropriety happens because the concordance index assesses the order of the event times and not the order of the event status at the prediction horizon. The time-dependent area under the receiver operating characteristic curve does not have this problem and is proper in this context. [ABSTRACT FROM AUTHOR]

In a Perspective article, Sigrid Carlsson and Michael Kattan discuss Gnanapragasam and colleagues' accompanying research study on refining risk stratification in early prostate cancer. [ABSTRACT FROM AUTHOR]

Objective: To develop and validate a prognostic nomogram for predicting the probability of 12-month progression-free survival (PFS) for patients receiving first-line pazopanib for advanced renal cell carcinoma (RCC). Methods: Statistical modeling was performed with data from 557 pazopanib-treated patients in the phase 3 COMPARZ trial. A multivariable Cox model was fit using known prognostic indicators. Variables included neutrophil count, serum levels of albumin and alkaline phosphatase, time from diagnosis to treatment, and bone metastases. Data from the pazopanib arm of a placebo-controlled phase 3 trial were used for validation. Results: The model included ten prognostic variables and was plotted as a nomogram for predicting the probability of 12-month PFS. Calibration plots suggested reasonable correspondence between predicted probabilities and actual proportions of PFS. The concordance index for 12-month PFS was 0.625. Significant associations (p < 0.05) were observed between PFS and bone metastases, time from diagnosis to treatment, albumin, and alkaline phosphatase. Albumin and alkaline phosphatase appeared to be influential predictors. Conclusion: The nomogram predicts, with reasonable accuracy, PFS in patients with advanced RCC receiving pazopanib, based on their baseline clinical characteristics. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Given a predictive marker and a time-to-event response variable, the proportion of concordant pairs in a data set is called concordance index. A specifically useful marker is the risk predicted by a survival regression model. This article extends the existing methodology for applications where the length of the follow-up period depends on the predictor variables. A class of inverse probability of censoring weighted estimators is discussed in which the estimates rely on a working model for the conditional censoring distribution. The estimators are consistent for a truncated concordance index if the working model is correctly specified and if the probability of being uncensored at the truncation time is positive. In this framework, all kinds of prediction models can be assessed, and time trends in the discrimination ability of a model can be captured by varying the truncation time point. For illustration, we re-analyze a study on risk prediction for prostate cancer patients. The effects of misspecification of the censoring model are studied in simulated data. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Objective: To compare the ability of clinicians vs a nomogram at predicting future bone scan positivity in patients with prostate cancer. Materials and Methods: This investigation was conducted during an advisory board meeting in June 2011. Details of 25 androgen deprivation therapy-naive prostate cancer patients were given to 24 prostate cancer experts, including urologists and oncologists. The clinicians were asked to predict the probability that the patients would have a positive bone scan if left untreated for 1 year. These predictions and those of the Slovin nomogram were compared with the actual occurrence of metastatic disease, and the discrimination ability was quantified using the concordance index (C index). Results: A higher C index value was obtained with the Slovin nomogram (0.812) than with the clinicians (0.628). The nomogram outperformed all of the clinicians; individual clinician C index values varied between 0.47 and 0.75. The urologists provided superior predictions compared with the oncologists. Conclusion: Future bone scan positivity can be predicted more accurately using a nomogram than by expert clinicians. Nomograms should, therefore, become an integral part of the clinical decision-making process in the prostate cancer setting for patients with a rising prostate-specific antigen level after radical prostatectomy. [ABSTRACT FROM AUTHOR]

Purpose: Development of user-friendly tools for the prediction of single-patient probability of late rectal toxicity after conformal radiotherapy for prostate cancer. Methods and Materials: This multicenter protocol was characterized by the prospective evaluation of rectal toxicity through self-assessed questionnaires (minimum follow-up, 36 months) by 718 adult men in the AIROPROS 0102 trial. Doses were between 70 and 80 Gy. Nomograms were created based on multivariable logistic regression analysis. Three endpoints were considered: G2 to G3 late rectal bleeding (52/718 events), G3 late rectal bleeding (24/718 events), and G2 to G3 late fecal incontinence (LINC, 19/718 events). Results: Inputs for the nomogram for G2 to G3 late rectal bleeding estimation were as follows: presence of abdominal surgery before RT, percentage volume of rectum receiving >75 Gy (V75Gy), and nomogram-based estimation of the probability of G2 to G3 acute gastrointestinal toxicity (continuous variable, which was estimated using a previously published nomogram). G3 late rectal bleeding estimation was based on abdominal surgery before RT, V75Gy, and NOMACU. Prediction of G2 to G3 late fecal incontinence was based on abdominal surgery before RT, presence of hemorrhoids, use of antihypertensive medications (protective factor), and percentage volume of rectum receiving >40 Gy. Conclusions: We developed and internally validated the first set of nomograms available in the literature for the prediction of radio-induced toxicity in prostate cancer patients. Calculations included dosimetric as well as clinical variables to help radiation oncologists predict late rectal morbidity, thus introducing the possibility of RT plan corrections to better tailor treatment to the patient’s characteristics, to avoid unnecessary worsening of quality of life, and to provide support to the patient in selecting the best therapeutic approach. [ABSTRACT FROM AUTHOR]

Objectives: To construct a nomogram that can be used to estimate the risk of prostate cancer (PCa) and high-grade PCa using readily available clinical information for men undergoing initial extended prostate biopsy (PBx). Many nomograms have been developed to predict the outcome of initial PBx. However, most require information not available at the decision to biopsy. Methods: From March 2000 to April 2010, 1551 men with a prostate-specific antigen (PSA) of ≤10 ng/mL who underwent initial extended PBx were included in the present study. The nomogram predictor variables were patient age, race, prostate-specific antigen (PSA) level, percent free PSA, family history of PCa, and the digital rectal examination findings. The area under the receiver operating characteristic curve was calculated as a measure of discrimination. The calibration was assessed graphically. Results: Of the 1551 men, 606 (39.1%) had PCa on biopsy. The mean value for age, PSA, and percent free PSA was 63.4 years, 5.1 ng/mL, and 21.4%, respectively. Also, 25.1% and 7.8% of patients with positive PBx findings had digital rectal examination abnormalities and a positive family history, respectively. The univariate and multivariate analyses suggested that all 6 risk factors were predictors of PCa in the study cohort (P < .05). The area under the curve for all factors in a model predicting PCa was 0.73 (95% confidence interval 0.71-0.76). The area under the curve for predicting high-grade PCa was 0.71 (95% confidence interval 0.69-0.74). Conclusions: The present predictive model allows an assessment of the risk of PCa and high-grade PCa for men undergoing initial extended PBx using readily available, noninvasively obtained clinical data. [ABSTRACT FROM AUTHOR]

Objectives: To develop a nomogram that allows the prediction of disease recurrence using preoperative clinical factors for patients with clinically localized prostate cancer who are candidates for laparoscopic radical prostatectomy. Few published studies have combined the clinical prognostic factors into risk profiles that can be used to predict the likelihood of recurrence or metastatic progression after laparoscopic radical prostatectomy for prostate cancer. Methods: Using Cox proportional hazards regression analysis, we modeled the clinical data and disease follow-up data for 2272 men with clinically localized prostate cancer who had undergone laparoscopic radical prostatectomy. The clinical data included the pretreatment serum prostate-specific antigen level, biopsy Gleason grade, clinical stage, number of positive cores, and number of negative cores. Treatment failure was recorded when clinical evidence of disease recurrence was present, the serum prostate-specific antigen level had increased (2 measurements of ≥0.1 ng/mL and increasing), or the initiation of adjuvant therapy. Validation was also performed on an external data set of 1151 men. Results: Treatment failure was noted in 229 of the 2272 men. The group without failure had a median follow-up of 16.7 months (range 0-120.6). The concordance index, when the nomogram was applied to the validation data set, was 0.77. The calibration in this data set was adequate. The predictions from this nomogram were more accurate than those using an open prostatectomy nomogram. Conclusions: We have externally validated a nomogram that predicts the 5-year probability of treatment failure among men with clinically localized prostate cancer treated with laparoscopic radical prostatectomy. [ABSTRACT FROM AUTHOR]

BACKGROUND: Patients with primary high-grade retroperitoneal soft tissue sarcomas have a 5-year disease-specificsurvival (DSS) of <40%. The impact of neoadjuvant therapy on histopathologic response and DSS are unknown.METHODS: From 1987 to 2007, 55 patients with primary high-grade retroperitoneal sarcoma received neoadjuvanttherapy. All patients underwent surgical resection, and response was assessed histopathologically. Patients with ≥95% pathologic necrosis were classified as responders. Clinicopathologic variables were analyzed for associationwith DSS. Observed DSS was then compared with the Memorial Sloan-Kettering Cancer Center Sarcoma Nomogrampredicted DSS. RESULTS: The median tumor size was 15 cm, and the median follow-up time for survivors was 68 months. The 5-year DSS for all 55 patients was 47% and did not significantly differ from the 37% predicted by the sarcoma nomogram for such patients (P = .44). Fourteen (25%) of the patients had ≥95% pathologic necrosis and weredefined as responders; 41 (75%) were nonresponders. The 5-year DSS for responders was 83%. This was significantlybetter than the 5-year DSS of 34% for nonresponders (P = .002) and the 39% predicted by the sarcoma nomogramfor responders (P = .018). The 34% 5-year DSS for nonresponders did not significantly differ from the 35% predictedby the sarcoma nomogram (P = .51). CONCLUSIONS: Neoadjuvant therapy was not associated with an overall improvement in DSS in patients with primary high-grade retroperitoneal sarcoma compared with the sarcoma nomogram prediction. Histopathologic response to neoadjuvant therapy was associated with a significantly improved DSScompared with nonresponders and with the sarcoma nomogram prediction for such patients. [ABSTRACT FROM AUTHOR]

Study Type – Prognosis (case series) Level of Evidence 4 OBJECTIVE To re-calibrate the previously published Duke Prostate Center (DPC) nomogram for the prediction of biochemical recurrence (BCR) after radical prostatectomy (RP) to not only predict overall BCR but also the clinically more relevant endpoint of an aggressive recurrence (i.e. a BCR with a postoperative PSA doubling time (PSADT) of <9 months). PATIENTS AND METHODS Using the established point-scale system based upon the previously published DPC nomogram, we re-calibrated this point system to predict not just BCR, but also aggressive BCR within 2599 men treated with RP from the DPC database. PSADT was computed on all patients meeting the recurrence definition who had a minimum of two PSA values, separated by at least 3 months, and ≤2 years after recurrence. External validation was performed using data from 1695 men treated with RP within the Shared Equal Access Regional Cancer Hospital (SEARCH) database by calculating the concordance index c and by plotting calibration curves. RESULTS The median follow-up for patients with no BCR was 56 and 47 months for DPC and SEARCH, respectively. In the DPC modelling cohort and the SEARCH validation cohort, 645 (25%) and 557 (33%) men had BCR, while 83 (3.2%) and 71 (4.2%) patients had an aggressive recurrence. In external validation, predictive accuracy for an aggressive BCR was high (c = 0.83) and the nomogram showed good calibration. CONCLUSIONS We re-calibrated an existing nomogram to not only predict overall BCR after RP but also aggressive recurrence after RP. Our new tool can provide valuable information for patient counselling and patient selection for adjuvant therapy trials. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to predict seminal vesicle invasion (SVI) by developing a new nomogram based on clinical features including the status of cancer at the base of the prostate on systematic biopsy. Methods: We studied the 466 patients with T1–3N0M0 prostate cancer who were treated with radical prostatectomy at three institutions. Preoperative clinical variables were correlated with the presence or absence of SVI with an area under the curve (AUC) of receiver–operator characteristics analysis. A nomogram was developed to predict SVI based on logistic regression analysis. Results: A total of 81 patients (17%) had SVI. Cancer was present in a biopsy core from the base of the prostate in 209 patients, of whom 32.5% had SVI, compared with only 5% of the 257 patients without cancer at the base of the prostate ( P < 0.005). On multivariate analysis, serum prostate-specific antigen, biopsy Gleason score, clinical T stage, and presence or absence of cancer in a biopsy core at the base of the prostate were significant predictors of SVI ( P < 0.005 for all). The AUC of a standard model including clinical stage, Gleason score, and prostate-specific antigen was 0.83, which was significantly enhanced by including the presence of cancer at the base of the prostate (none, unilateral or bilateral lobes) (AUC 0.87, P= 0.023). Based on the logistic analysis, we developed the nomogram to predict SVI. The calibration plots appeared to be excellent. Conclusion: The information of presence or absence of cancer at the base from prostate biopsy and the resulting nomogram allow an accurate prediction of SVI in patients undergoing radical prostatectomy for prostate cancer. [ABSTRACT FROM AUTHOR]

OBJECTIVE -- Sulfonylureas have historically been analyzed as a medication class, which may be inappropriate given the differences in properties inherent to the individual sulfonylureas (hypoglycemic risk, sulfonylurea receptor selectivity, and effects on myocardial ischemic preconditioning). The purpose of this study was to assess the relationship of individual sulfonylureas and the risk of overall mortality in a large cohort of patients with type 2 diabetes. RESEARCH DESIGN AND METHODS -- A retrospective cohort study was conducted using an academic health center enterprise-wide electronic health record (EHR) system to identify 11,141 patients with type 2 diabetes (4,279 initiators of monotherapy with glyburide, 4,325 initiators of monotherapy with glipizide, and 2,537 initiators of monotherapy with glimepiride), ≥ 18 years of age with and without a history of coronary artery disease (CAD) and not on insulin or a noninsulin injectable at baseline. The patients were followed for mortality by documentation in the EHR and Social Security Death Index. Multivariable Cox models were used to compare cohorts. RESULTS -- No statistically significant difference in the risk of overall mortality was observed among these agents in the entire cohort, but we did find evidence of a trend toward an increased overall mortality risk with glyburide versus glimepiride (hazard ratio 1.36 [95 % CI 0.96-1.91]) and glipizide versus glimepiride (1.39 [0.99-1.96]) in those with documented CAD. CONCLUSIONS-- Our results did not identify an increased mortality risk among the individual sulfonylureas but did suggest that glimepiride may be the preferred sulfonylurea in those with underlying CAD. [ABSTRACT FROM AUTHOR]

Study Type – Diagnostic (exploratory cohort) Level of Evidence 2b OBJECTIVE To develop a nomogram to predict the probability that the pathological Gleason sum (GS) will be higher than that indicated by the biopsy, suggesting a higher risk for the patient presumed to be at low risk, as a substantial proportion of patients with low and intermediate grade on biopsy are upgraded on interpretation of the radical prostatectomy (RP) specimens, but a similar clarification of accurate Gleason scoring is not available in patients with no surgical histology. PATIENTS AND METHODS The study included 1017 patients who had RP after biopsy showing GS 6 and 7 (3 + 4) from 2000 to 2007. Nomogram predictor variables included age, race, digital rectal examination, prostate-specific antigen (PSA) level, number of cores taken, number of positive cores, maximum percentage cancer in any core, number of previous biopsies, prostate volume, clinical stage, high-grade prostatic intraepithelial neoplasia, atypical small acinar proliferation, inflammation and perineural invasion. We calculated the nomogram-predicted probability in each patient. The area under the receiver operating characteristic curve was calculated as a measure of discrimination, and the calibration was assessed graphically. RESULTS The mean age of the patients was 60 years, the mean PSA level 6.62 ng/mL; 336 patients were upgraded (33%), 623 remained the same (61.3%) and 58 were downgraded (5.7%). A nomogram for predicting the possibility of upgrading was constructed that had a concordance index of 0.68. The nomogram was well calibrated. CONCLUSIONS Our nomogram for predicting upgrading provides important additional information for deciding on treatment to both the urologist and the patient with low- and intermediate-grade prostate cancer. It might prove useful when the possibility of a more aggressive Gleason variant can change the management, and is especially meaningful when management options other than surgery are selected based on the inability to recognize the true pathological actual GS. [ABSTRACT FROM AUTHOR]

Introduction: Nomograms are statistical tools designed to predict outcomes. This study evaluates the effects of peri-operative chemotherapy on the accuracy of a prognostic nomogram for disease-specific survival (DSS) after resection of colorectal liver metastases (CRLM) established at Memorial-Sloan Kettering Cancer Center (MSKCC).hpb_106 592..599 Methods: An external cohort of 203 patients who underwent resection of CRLM between 1996 and 2006 was used to assess the nomogram. Results: After median follow-up of 30.4 months (range 0.33-150), Kaplan--Meier (KM) estimates for 3-, 5- and 8-year post-resection DSS were 56%, 41%, and 32%, respectively; similar to nomogram- predicted probabilities for DSS. The concordance index for the nomogram was higher (0.602) than for the Fong colorectal risk score (CRS; 0.533). KM DSS was longer for patients (n = 50) treated with at least 6 months of peri-operative irinotecan or oxaliplatin compared with all other patients (median 66 vs. 40 months, P = 0.06). KM DSS was greater than nomogram predicted DSS for treated patients and less than nomogram predicted DSS for all other patients. Conclusions: The CRLM nomogram was validated by an external cohort and more accurately predicted post-resection survival than the commonly used CRS. Differences in observed and nomogram-predicted survival may reflect the effect of treatment factors, such as peri-operative chemotherapy. [ABSTRACT FROM AUTHOR]

The article reports on the development of prostate cancer prediction tools toward the formation of metagram that can be used to tailor management to patients. According to the authors, the tools are categorized through a combination of treatment modality and the outcome being predicted. It reveals that the prediction tools provide the most accurate estimates of outcomes in prostate cancer. However, its current role in patient counseling is complicated by the large number of existing tools.

The article presents a clinical study regarding the risk assessment on surgical operations done on patients with prostate cancer. It provides therapeutic claims on the danger of encountered before, during, and after the medical procedure. Based on the study, the use of preoperative nomogram provides the statistical analysis of biochemical recurrence of prostate cancer.

Abstract: Context: The sensitivity and specificity profile of measuring levels of prostate-specific antigen (PSA) to select men for prostate biopsy is not optimal. This has prompted the construction of nomograms and artificial neural networks (ANNs) to increase the performance of PSA measurements. Objective: A systematic review of nomograms and ANNs designed to predict the risk of a positive prostate biopsy for cancer was conducted in order to determine their value versus measuring PSA levels alone. Evidence acquisition: Medical Literature Analysis and Retrieval System Online (U.S. National Library of Medicine''s life science database; MEDLINE) was searched using the terms “nomogram” “artificial neural network” and “prostate cancer” for dates up to and including July 2007 and was supplemented by manual searches of reference lists. Included studies used an assessment tool to examine the risk of a positive prostate biopsy in a man without a known cancer diagnosis. Intramodel comparisons with evaluation of PSA levels alone, and intermodel comparisons of area under the curve (AUC) from receiver operating characteristic (ROC) curves were conducted. Individual case examples were also used for comparisons. Evidence synthesis: Twenty-three studies examining 36 models were included. With the exception of two studies, all the models had AUC values of 0.70 or greater, with eight reporting an AUC of ≥0.80 and four (all ANNs) reporting an AUC ≥0.85, with variable validation status. Fourteen studies compared the AUC with PSA levels alone: all showed a benefit from using AUCs which varied from 0.02 to 0.26. Of the 16 external validation comparisons, in 13 the AUC was lower in the external population than in the model population. Conclusions: Nomograms and ANNs produce improvements in AUC over measurement of PSA levels alone, but many lack external validation. Where this is available, the benefits are often diminished, although most remain significantly better than with evaluation of PSA levels alone. In men without additional risk factors, PSA cutoff values alone provide a relatively precise risk estimate, but if additional risk factors are known, PSA values alone are less accurate. [Copyright &y& Elsevier]

Abstract: Estimation and hypothesis testing have been popular in applied statistical analysis. More recently, emphasis has been placed on prediction. Traditional questions of estimation and hypothesis testing are being reframed as problems of prediction, and as such, the methods and approaches have shifted. The reporting of P values is de-emphasized from the prediction philosophy perspective, and incremental predictive accuracy has become the metric of choice. Ties to individual patient decision making and outcomes research are presented. [Copyright &y& Elsevier]

Abstract: Objectives: Men with clinically detected localized prostate cancer treated without curative intent are at risk of complications from local tumor growth. We investigated rates of local progression and need for local therapy among such men. Methods: Men diagnosed with prostate cancer during 1990–1996 were identified from cancer registries throughout the United Kingdom. Inclusion criteria were age ≤76 yr at diagnosis, PSA level ≤100ng/ml, and, within 6 mo after diagnosis, no radiation therapy, radical prostatectomy, evidence of metastatic disease, or death. Local progression was defined as increase in clinical stage from T1/2 to T3/T4 disease, T3 to T4 disease, and/or need for transurethral resection of the prostate (TURP) to relieve symptoms >6 mo after cancer diagnosis. Results: The study included 2333 men with median follow-up of 85 mo (range: 6–174). Diagnosis was by TURP in 1255 men (54%), needle biopsy in 1039 (45%), and unspecified in 39 (2%). Only 29% were treated with hormonal therapy within 6 mo of diagnosis. Local progression occurred in 335 men, including 212 undergoing TURP. Factors most predictive of local progression on multivariable analysis were PSA at diagnosis and Gleason score of the diagnostic tissue (detrimental), and early hormonal therapy (protective). We present a nomogram that predicts the likelihood of local progression within 120 mo after diagnosis. Conclusions: Men with clinically detected localized prostate cancer managed without curative intent have an approximately 15% risk for local progression within 10 yr of diagnosis. Among those with progression, the need for treatment is common, even among men diagnosed by TURP. When counseling men who are candidates for management without curative intent, the likelihood of symptoms from local progression must be considered. [Copyright &y& Elsevier]

Objectives: To test the accuracy of the 2001 Partin Tables in African American men who underwent radical prostatectomy at multiple centers throughout the United States. Methods: We compiled a large multiethnic cohort of men (n = 3748) treated with radical prostatectomy at multiple sites, including all of the sites of the Department of Veterans Affairs–based Shared Equal Access Regional Cancer Hospital (SEARCH) database (n = 1524), Wayne State University (n = 1305), the University of Texas Health Science Center (n = 522), and the Henry Ford Hospital (n = 397). We evaluated the accuracy of the 2001 Partin Tables using area under the receiver operator characteristic curve (AUC) separately among African American and white men. Results: African American men (n = 1188, 32%), despite being more likely to have clinical Stage T1c disease (56% versus 47%, chi-square P <0.001), had higher preoperative PSA values (9.1 versus 7.7 ng/mL, rank-sum P <0.001) and were more likely to have higher-grade disease on diagnostic biopsy (chi-square P = 0.005). Despite these differences in baseline clinical characteristics, the 2001 Partin Tables performed equally well in both racial groups. Specifically, there were no differences in the AUC for African American and white men for predicting organ-confined disease (AUC 0.73 versus 0.72; P = 0.56), extraprostatic extension (AUC 0.62 versus 0.62; P = 0.99), or seminal vesicle invasion (AUC 0.77 versus 0.79; P = 0.53). Conclusions: These data lend further support to the idea that although baseline differences between the races existed that may underlie an overall more aggressive disease among African American men, for the individual patient, race is not valuable for prognostication. [Copyright &y& Elsevier]

Background: The prognosis of men with clinically localized prostate cancer is highly variable, and it is difficult to counsel a man who may be considering avoiding, or delaying, aggressive therapy. After collecting data on a large cohort of men who received no initial active prostate cancer therapy, the aim was to develop, and to internally validate, a nomogram for prediction of disease-specific survival.Methods: Working with 6 cancer registries within England and numerous hospitals in the region, a population-based cohort of men diagnosed with prostate cancer between 1990 and 1996 was constructed. All men had baseline serum prostate-specific antigen (PSA) measurements, centralized pathologic grading, and centralized review of clinical stage assignment. Based on the clinical and pathologic data from 1911 men, a statistical model was developed and validated that served as the basis for the nomogram. The discrimination and calibration of the nomogram were assessed with use of one-third of the men, who were omitted from modeling and used as a test sample.Results: The median age of the included men was 70.4 years. The 25th and 75th percentiles of PSA were 7.3 and 32.6 ng/mL respectively, and the median was 15.4 ng/mL. Forty-two percent of the men had high-grade disease. The nomogram predicted well, with a concordance index of 0.73, and had good calibration.Conclusions: An accurate tool was developed for predicting the probability that a man with clinically localized prostate cancer will survive his disease for 120 months if the cancer is not treated with curative intent immediately. The tool should be helpful for patient counseling and clinical trial design. [ABSTRACT FROM AUTHOR]

Objectives: To update our previously published nomogram predicting for biochemical outcome with 10-year data from a larger cohort of patients treated with three-dimensional conformal radiotherapy (RT) or intensity-modulated RT for localized prostate cancer. Methods: From 1988 to 2004, 2253 patients were treated with three-dimensional conformal RT or intensity-modulated RT for clinical Stage T1-T3 prostate cancer. Prescription doses ranged from 64.8 to 86.4 Gy. The median follow-up time was 7 years. The nomogram was developed using a proportional hazards regression model predicting for the probability of biochemical relapse after RT according to the nadir plus 2 ng/mL definition of prostate-specific antigen (PSA) relapse. Results: The 10-year PSA relapse-free survival rate was 62%. The nomogram incorporated the following variables to predict likelihood of PSA failure after RT: pretreatment PSA level, Gleason score, radiation dose, use of neoadjuvant androgen deprivation, and clinical stage. The concordance index of this long-term nomogram was 0.72. Conclusions: A nomogram predicting the 10-year probability of biochemical control after three-dimensional conformal RT or intensity-modulated RT for prostate cancer was reasonably accurate and discriminating. The nomogram also provided evidence that long-term biochemical control can be achieved after conformal RT for the treatment of localized prostate cancer. [Copyright &y& Elsevier]

There are several papers in this section on various aspects of prostate cancer: predictive models, robotic radical prostatectomy in large glands, PSA distribution, bicalutamide and PIN, and finally the clinical characteristics of bladder cancer in patients previously treated with irradiation for prostate cancer. There are also several manuscripts on renal, testis and penile cancer. A wide variety of topics, from authors of many nationalities, maintaining the unique internationalism of the BJU International. [ABSTRACT FROM AUTHOR]

In this section there are two reviews concerning prostate cancer, both from the same group of authors. In the first, they describe the combination of nomograms with PSA screening to assess risk and to predict outcomes in the management of prostate cancer. In the second, they indicate how outcomes and quality of life can be optimised in the hormonal treatment of prostate cancer. Botulinum toxin has become very popular in the management of a whole range of conditions both inside and outside the urinary tract. Now it has been extended to prostatic disorders, and the mini-review presented here has evaluated reports and the authors’ personal experience in the mechanisms of action and clinical efficacy of Botulinum toxin in the prostate. Finally, there is a mini-review of FISH in bladder cancer, particularly its development, applications, and its potential for the future. We review the role of prostate-specific antigen (PSA) and the importance of patient education in the management of prostate cancer, based on discussions held at a European symposium on managing prostate cancer. Although PSA is the most widely used serum marker for detecting prostate cancer and for monitoring treatment responses, its use as a diagnostic marker is controversial due to concerns of over-diagnosis and low specificity. PSA isoforms, as well as PSA doubling time, might improve the specificity for earlier prostate cancer detection and can be used as surrogate markers for treatment efficacy. Patients can differ considerably in the importance they place on health-related quality of life aspects and fear of cancer progression. Consequently, there needs to be active, educated discussion of risk and outcomes between physicians and patients. Risk assessment tools, e.g. validated nomograms, enable clinicians to improve their decision analysis and form the basis for subsequent discussion of treatment options between the physician and patient, thereby enabling informed consent and appropriate decision-making. [ABSTRACT FROM AUTHOR]

The article discusses the measures used to monitor hot flashes in men with prostate cancer undergoing androgen ablation treatment or orchiectomy. Hot flashes are the common side effect of prostate cancer treatment. Evaluation tools are needed to define the effects of hot flashes in the daily functioning of the patients receiving the therapy. Measures of this side effect in breast cancer survivors and menopausal women are also considered for comparison and understanding of the subject matter.

Abstract: Objectives: To develop a prediction model, or nomogram, that would predict the probability that a man with benign prostatic hyperplasia would experience acute urinary retention (AUR) or require surgical intervention (SI) within 2 years, with or without dutasteride therapy. Methods: We modeled 4294 men treated in the Phase III dutasteride benign prostatic hyperplasia trials. These men were characterized at baseline by a number of parameters, including the American Urological Association Symptom Index, Benign Prostatic Hyperplasia Impact Index questionnaire, prior use of selective alpha1-blockers, prostate volume, prostate-specific antigen level, and maximal flow rate. Cox proportional hazards regression analysis was used to relate these baseline variables to their future probability of AUR/SI within 2 years. The nomogram was internally validated with bootstrapping to assess its discrimination and calibration. Discrimination was quantified as the concordance index. Results: The nomogram appeared to be accurately calibrated and discriminating (concordance index 0.71, P <0.001). Conclusions: We constructed a nomogram for predicting the probability that a man would experience AUR or require SI within 2 years of benign prostatic hyperplasia diagnosis. At 24 months of follow-up, 7.4% of placebo patients and 3.7% of dutasteride patients had experienced AUR and/or SI, representing a 50% relative risk reduction and a 3.7% absolute risk reduction. For the greatest risk patient randomized to the Phase III dutasteride trial, the nomogram predicted a maximal risk of 27%, significantly greater than the median risk of the placebo-treated patients. [Copyright &y& Elsevier]

The controversial topic of the effect of finasteride therapy on Gleason grade, raised by the Prostate Cancer Prevention Trial, is discussed by authors from New York. They assessed a series of patients who had been treated with finasteride, and who subsequently had a radical prostatectomy, to see if this pharmaceutical agent prevented accurate Gleason grade assignment and prediction of biochemical recurrence. They found that Gleason grade remains an important prognostic predictor in men diagnosed with prostate cancer while on finasteride therapy.Authors from Amsterdam assessed the accuracy of ultrasonography-guided fine-needle aspiration cytology as a method of detecting occult lymph node metastases in patients with penile cancer, and found that it can be used as an initial investigation in such patients, with helpful clinical outcomes.To evaluate men treated with finasteride for lower urinary tract symptoms, who subsequently were diagnosed with prostate cancer and had a radical prostatectomy (RP) at our institution, to determine if finasteride therapy prevented accurate Gleason grade assignment and prediction of biochemical recurrence.Between May 1996 and July 2003, 45 men were identified who had RP and had previously been treated with finasteride for≥ 6 months before the diagnosis of prostate cancer. Clinical and pathological information was gathered from a RP database. Serum prostate-specific antigen (PSA) level, duration of finasteride therapy, biopsy Gleason grade, clinical stage, RP Gleason grade and pathological stage were reviewed. Freedom from recurrence was predicted using validated nomograms before and after RP, and compared against actuarial 5-year freedom from recurrence using the Kaplan-Meier method.The mean duration of finasteride therapy before diagnosis was 23.6 months, the mean serum PSA (doubled to account for finasteride use) 11.02 ng/mL and mean biopsy Gleason score 6. When comparing the biopsy and RP specimen Gleason score, it was downgraded by 1 point in six men, upgraded by 1 point in eight, and upgraded by 2 points in one. The Gleason score was constant in 30 patients. The nomograms predicted freedom from recurrence in 83% and 85%, respectively; the 5-year actuarial freedom from recurrence was 86%.Finasteride does not appear to compromise the assignment of Gleason grade for use in prediction tools before or after RP in men undergoing prostate biopsy or RP. The actuarial 5-year freedom from recurrence was similar to that predicted by the validated nomograms. Gleason grade remains an important prognostic predictor in men treated with finasteride and undergoing RP for clinically localized prostate cancer. [ABSTRACT FROM AUTHOR]

A risk prediction model is a statistical technique that gives a predicted probability of a certain event for an individual patient. Prediction models outperform the traditional risk classification systems that work by assigning patients into risk groups based on the presence or absence of particular risk factors, such as stage of disease. As such, risk prediction models have a number of important possible uses in clinical trials. For Phase II studies, prediction models can help adjust comparisons with historical control groups for differences in case mix. For Phase III studies, prediction models can ensure that accrued patients are at sufficiently high risk. This improves statistical power and avoids unethical inclusion of low-risk patients. We also propose that prediction models could potentially be used for applying the results of Phase III trials to individual patients. Clinical decisions could be informed by individualized estimates of treatment benefit, rather than by average treatment effects. [Copyright &y& Elsevier]

The generally indolent nature of prostate cancer, as well as the impact that treatment can have on quality of life (QOL) and cancer control, makes the decision analysis difficult for patients facing the task of selecting a treatment for clinically localized disease. Instruments to aid patients and their physicians in this decision analysis are needed. Nomograms are instruments that predict outcomes using specific clinical parameters. Nomograms use algorithms that incorporate several variables to calculate the predicted probability that a patient will achieve a particular clinical end point. Nomograms tend to outperform both clinical experts and predictive models using methods of risk grouping. We briefly outline the uses and limitations of nomograms, principles of nomogram construction, and the available models for predicting the progression-free probability after local definitive therapy with radical prostatectomy, external-beam radiotherapy, or brachytherapy. There is a need for additional nomograms that predict outcomes after salvage therapy, as well other clinical end points, including QOL-adjusted survival. [Copyright &y& Elsevier]

: PurposeTo outline the process for developing a data management system for patients with prostate cancer.: Methods and materialsBetween 1997 and 2002, several generations of a working database using a Microsoft Access platform were developed for the tracking of patients with prostate cancer. The database evolved to include both the management of clinical practice and outcomes research. A chronological data system lists events by their date and value. Algorithms for data exporting can access these lists in defined ways to mine for specific parameters.: ResultsThe most recent working model of our database was implemented with over 2000 patients entered and over 250,000 rows of data. It is utilized by the entire staff and is central for processing prostate cancer data within the department. Outcome studies have been performed using the system, and data export algorithm development remains ongoing.: ConclusionsThis work demonstrates that functional database systems are possible for large clinics treating patients with prostate cancer. The ability to maintain up-to-the-minute data variables is vital not only for unbiased outcomes analysis, but for patient flow and care. Future systems will migrate to web platforms. [Copyright &y& Elsevier]

Background: Although there is no proven benefit associated with screening for lung cancer, screening programs are attracting many individuals who perceive themselves to be at high risk due to smoking. We sought to determine whether the risk of lung cancer varies predictably among smokers. Methods: We used data on 18172 subjects enrolled in the Carotene and Retinol Efficacy Trial (CARET)—a large, randomized trial of lung cancer prevention—to derive a lung cancer risk prediction model. Model inputs included the subject's age, sex, asbestos exposure history, and smoking history. We assessed the model's calibration by comparing predicted and observed rates of lung cancer across risk deciles and validated it by assessing the extent to which a model estimated on data from five CARET study sites could predict events in the sixth study site. We then applied the model to evaluate the risk of lung cancer among smokers enrolled in a study of lung cancer screening with computed tomography (CT). Results: The model was internally valid and well calibrated. Ten-year lung cancer risk varied greatly among participants in the CT study, from 15% for a 68-year-old man who has smoked two packs per day for 50 years and continues to smoke, to 0.8% for a 51-year-old woman who smoked one pack per day for 28 years before quitting 9 years earlier. Even among the subset of CT study participants who would be eligible for a clinical trial of cancer prevention, risk varied greatly. Conclusions: The risk of lung cancer varies widely among smokers. Accurate risk prediction may help individuals who are contemplating voluntary screening to balance the potential benefits and risks. Risk prediction may also be useful for researchers designing clinical trials of lung cancer prevention. [ABSTRACT FROM AUTHOR]

: ObjectivesTo explore the impact of cross-cultural differences on University of California, Los Angeles, Prostate Cancer Index (PCI) reliability and validity, which is unknown. The PCI represents the most widely used prostate cancer-specific health-related quality-of-life assessment tool.: MethodsThe PCI sexual and urinary scales, the RAND SF-36 survey, and the Prostate Outcomes Research Team (PORT) prostate cancer treatment complication profile were self-administered. The principal sample consisted of 2415 men (anglophone 256, francophone 2159) treated with radical prostatectomy in Quebec between 1988 and 1996. An additional 35 men (anglophone 17, francophone 18) formed the retest sample.: ResultsThe PCI demonstrated excellent internal consistency and test-retest reliability in tests based on the entire cohort and in tests addressing the two linguistically different groups. The instrument showed a lack of convergence with the SF-36 scales, confirming the distinctness of the generic and prostate cancer-specific constructs. The PCI sexual scales converged with the aggregate PORT sexual items (r = 0.8), and the PCI urinary scales were strongly related to the aggregate PORT urinary items (r = 0.7). Convergence between PCI urinary bother and function was strong (r = 0.8), but only moderate convergence was noted between PCI sexual bother and function (r = 0.4). The relation between bother and function in both urinary and sexual domains was weaker in anglophone participants relative to their francophone counterparts.: ConclusionsThe PCI is reliable and, at best, only modestly affected by cultural differences when administered to culturally distinct English-speaking men or when translated into French. [Copyright &y& Elsevier]

Utilizing data from the largest European organ transplantation organization, we developed KTOP, the first European online risk tool for predicting kidney transplantation outcomes. The tool provides comprehensive guidance for patient and clinician decision-making regarding transplantation both before and after a donor is identified. European kidney donation shortages mandate efficient organ allocation by optimizing the prediction of success for individual recipients. To develop the first European online risk tool for kidney transplant outcomes on the basis of recipient-only and recipient plus donor characteristics. We used individual recipient and donor risk factors and three outcomes (death, death with functioning graft [DWFG], and graft loss) for 32 958 transplants within the Eurotransplant kidney allocation system and the Eurotransplant senior program between January 2006 and May 2018 in eight European countries to develop and validate a risk tool. Cox proportional-hazards models were used to analyze the association of risk factors with overall patient mortality, and proportional subdistribution hazard regression models for their association with graft loss and DWFG. Prediction models were developed with recipient-only and recipient-donor risk factors. Sensitivity analyses based on time-specific area under the receiver operating characteristic curve (AUC) with leave-one-country-out validation were performed and calibration plots were generated. The 10-yr cumulative incidence rate was 37% for mortality, 12% for DWFG, and 41% for graft loss. In recipient-donor models the leading risk factors for mortality were recipient diabetes (hazard ratio [HR] 10.73), retransplantation (HR 3.08 per transplant), and recipient age (HR 1.08). Effects were similar for DWFG. For graft loss, diabetes (subdistributional HR [SHR] 1.32), increased donor age (SHR 1.02), and prolonged cold ischemia time (SHR 1.02) had increased SHRs. All p values were <0.001. Previously identified risk factors for outcomes following kidney transplants allow for outcome prediction with 10-yr AUC values of up to 0.81. Using European data, we estimated individual risks to predict the success of kidney transplants and support physicians in decision-making. An online tool is now available (https://riskcalc.org/ktop/) for predicting kidney transplant outcomes both before and after a donor has been identified. [ABSTRACT FROM AUTHOR]

Aims: To investigate the independent contributions of glycated haemoglobin (HbA1c) reduction and weight loss to clinical outcomes in patients with type 2 diabetes (T2D) treated with antidiabetic drugs, including glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs). Materials and Methods: This observational, retrospective cohort study used deidentified electronic health record‐derived data from patients evaluated at the Cleveland Clinic (1 January 2000–31 December 2020). Cohort A included 8876 patients with newly diagnosed T2D treated with any of six antidiabetic drug classes. Cohort B included 4161 patients with T2D initiating GLP‐1RA treatment. The effects of body mass index (BMI) and HbA1c reduction, variability, and durability on clinical outcomes were investigated. Results: In Cohort A, each 1% BMI reduction was associated with 3%, 1%, and 4% reduced risk of heart failure (p = 0.017), hypertension (p = 0.006), and insulin initiation (p = 0.001), respectively. Each 1% (~11 mmol/mol) HbA1c reduction was associated with 4% and 29% reduced risk of hypertension (p = 0.041) and insulin initiation (p = 0.001), respectively. In Cohort B, each 1% BMI reduction was associated with 4% and 3% reduced risk of cardiovascular disease (p = 0.008) and insulin initiation (p = 0.002), respectively. Each 1% (~11 mmol/mol) HbA1c reduction was associated with 4% and 16% reduced risk of chronic kidney disease (p = 0.014) and insulin initiation (p = 1 × 10−4), respectively. Lower BMI variability and greater BMI durability were associated with decreased risk of clinical outcomes in both cohorts. Conclusions: Antidiabetic medication‐associated, and specifically GLP‐1RA‐associated, weight loss and HbA1c reductions independently reduce real‐world clinical outcome risk. [ABSTRACT FROM AUTHOR]

Simple Summary: For patients with newly diagnosed prostate cancer, it is important to detect tumor growth beyond the prostate, as this can affect a patient's prognosis, influence management decisions, and alter treatment strategies. It is recognized that on prostate MRI, some instances of extraprostatic tumor growth can be missed. In this study, we merged patient data from multiple hospitals in different countries and developed a type of mathematical formula called "nomogram" that combines MRI findings with other available patient data. The results of our study allow physicians to more accurately diagnose extraprostatic tumor growth by combining clinical, biopsy, and MRI-derived information according to their relative statistical importance. Background: To develop an international, multi-site nomogram for side-specific prediction of extraprostatic extension (EPE) of prostate cancer based on clinical, biopsy, and magnetic resonance imaging- (MRI) derived data. Methods: Ten institutions from the USA and Europe contributed clinical and side-specific biopsy and MRI variables of consecutive patients who underwent prostatectomy. A logistic regression model was used to develop a nomogram for predicting side-specific EPE on prostatectomy specimens. The performance of the statistical model was evaluated by bootstrap resampling and cross validation and compared with the performance of benchmark models that do not incorporate MRI findings. Results: Data from 840 patients were analyzed; pathologic EPE was found in 320/840 (31.8%). The nomogram model included patient age, prostate-specific antigen density, side-specific biopsy data (i.e., Gleason grade group, percent positive cores, tumor extent), and side-specific MRI features (i.e., presence of a PI-RADSv2 4 or 5 lesion, level of suspicion for EPE, length of capsular contact). The area under the receiver operating characteristic curve of the new, MRI-inclusive model (0.828, 95% confidence limits: 0.805, 0.852) was significantly higher than that of any of the benchmark models (p < 0.001 for all). Conclusions: In an international, multi-site study, we developed an MRI-inclusive nomogram for the side-specific prediction of EPE of prostate cancer that demonstrated significantly greater accuracy than clinical benchmark models. [ABSTRACT FROM AUTHOR]