Development and Validation of Models to Predict Pathological Outcomes of Radical Prostatectomy in Regional and National Cohorts.

PURPOSE: Prediction models are recommended by national guidelines to support clinical decision making in prostate cancer. Existing models to predict pathological outcomes of radical prostatectomy (RP)-the Memorial Sloan Kettering (MSK) models, Partin tables, and the Briganti nomogram-have been developed using data from tertiary care centers and may not generalize well to other settings. MATERIALS AND METHODS: Data from a regional cohort (Michigan Urological Surgery Improvement Collaborative [MUSIC]) were used to develop models to predict extraprostatic extension (EPE), seminal vesicle invasion (SVI), lymph node invasion (LNI), and nonorgan-confined disease (NOCD) in patients undergoing RP. The MUSIC models were compared against the MSK models, Partin tables, and Briganti nomogram (for LNI) using data from a national cohort (Surveillance, Epidemiology, and End Results [SEER] registry). RESULTS: We identified 7,491 eligible patients in the SEER registry. The MUSIC model had good discrimination (SEER AUC EPE: 0.77; SVI: 0.80; LNI: 0.83; NOCD: 0.77) and was well calibrated. While the MSK models had similar discrimination to the MUSIC models (SEER AUC EPE: 0.76; SVI: 0.80; LNI: 0.84; NOCD: 0.76), they overestimated the risk of EPE, LNI, and NOCD. The Partin tables had inferior discrimination (SEER AUC EPE: 0.67; SVI: 0.76; LNI: 0.69; NOCD: 0.72) as compared to other models. The Briganti LNI nomogram had an AUC of 0.81 in SEER but overestimated the risk. CONCLUSIONS: New models developed using the MUSIC registry outperformed existing models and should be considered as potential replacements for the prediction of pathological outcomes in prostate cancer.

Increasing Utilization of Emergency Department Neuroimaging From 2007 Through 2017.

BACKGROUND. The volume of emergency department (ED) visits and the number of neuroimaging examinations have increased since the start of the century. Little is known about this growth in the commercially insured and Medicare Advantage populations. OBJECTIVE. The purpose of our study was to evaluate changing ED utilization of neuroimaging from 2007 through 2017 in both commercially insured and Medicare Advantage enrollees. METHODS. Using patient-level claims from Optum's deidentified Clinformatics Data Mart database, which annually includes approximately 12-14 million commercial and Medicare Advantage health plan enrollees, annual ED utilization rates of head CT, head MRI, head CTA, neck CTA, head MRA, neck MRA, and carotid duplex ultrasound (US) were assessed from 2007 through 2017. To account for an aging sample population, utilization rates were adjusted using annual relative proportions of age groups and stratified by patient demographics, payer type, and provider state. RESULTS. Between 2007 and 2017, age-adjusted ED neuroimaging utilization rates per 1000 ED visits increased 72% overall (compound annual growth rate [CAGR], 5%). This overall increase corresponded to an increase of 69% for head CT (CAGR, 5%), 67% for head MRI (CAGR, 5%), 1100% for head CTA (CAGR, 25%), 1300% for neck CTA (CAGR, 27%), 36% for head MRA (CAGR, 3%), and 52% for neck MRA (CAGR, 4%) and to a decrease of 8% for carotid duplex US (CAGR, -1%). The utilization of head CT and CTA of the head and neck per 1000 ED visits increased in enrollees 65 years old or older by 48% (CAGR, 4%) and 1011% (CAGR, 24%). CONCLUSION. Neuroimaging utilization in the ED grew considerably between 2007 and 2017, with growth of head and neck CTA far outpacing the growth of other modalities. Unenhanced head CT remains by far the dominant ED neuroimaging examination. CLINICAL IMPACT. The rapid growth of head and neck CTA observed in the fee-for-service Medicare population is also observed in the commercially insured and Medicare Advantage populations. The appropriateness of this growth should be monitored as the indications for CTA expand.

Gene expression profiling-based risk prediction and profiles of immune infiltration in diffuse large B-cell lymphoma.

The clinical risk stratification of diffuse large B-cell lymphoma (DLBCL) relies on the International Prognostic Index (IPI) for the identification of high-risk disease. Recent studies suggest that the immune microenvironment plays a role in treatment response prediction and survival in DLBCL. This study developed a risk prediction model and evaluated the model's biological implications in association with the estimated profiles of immune infiltration. Gene-expression profiling of 718 patients with DLBCL was done, for which RNA sequencing data and clinical covariates were obtained from Reddy et al. (2017). Using unsupervised and supervised machine learning methods to identify survival-associated gene signatures, a multivariable model of survival was constructed. Tumor-infiltrating immune cell compositions were enumerated using CIBERSORT deconvolution analysis. A four gene-signature-based score was developed that separated patients into high- and low-risk groups. The combination of the gene-expression-based score with the IPI improved the discrimination on the validation and complete sets. The gene signatures were successfully validated with the deconvolution output. Correlating the deconvolution findings with the gene signatures and risk score, CD8+ T-cells and naïve CD4+ T-cells were associated with favorable prognosis. By analyzing the gene-expression data with a systematic approach, a risk prediction model that outperforms the existing risk assessment methods was developed and validated.

Remaining challenges in predicting patient outcomes for diffuse large B-cell lymphoma.

Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma and is an aggressive malignancy with heterogeneous outcomes. Diverse methods for DLBCL outcomes assessment ranging from clinical to genomic have been developed with variable predictive and prognostic success.Areas covered: The authors provide an overview of the various methods currently used to estimate prognosis in DLBCL patients. Models incorporating cell of origin, genomic features, sociodemographic factors, treatment effectiveness measures, and machine learning are described.Expert opinion: The clinical and genetic heterogeneity of DLBCL presents distinct challenges in predicting response to therapy and overall prognosis. Successful integration of predictive and prognostic tools in clinical trials and in a standard clinical workflow for DLBCL will likely require a combination of methods incorporating clinical, sociodemographic, and molecular factors with the aid of machine learning and high-dimensional data analysis.

Evaluation of Prostate Cancer Risk Calculators for Shared Decision Making Across Diverse Urology Practices in Michigan.

OBJECTIVE: To compare the predictive performance of a logistic regression model developed with contemporary data from a diverse group of urology practices to that of the Prostate Cancer Prevention Trial (PCPT) Risk Calculator version 2.0. MATERIALS AND METHODS: With data from all first-time prostate biopsies performed between January 2012 and March 2015 across the Michigan Urological Surgery Improvement Collaborative (MUSIC), we developed a multinomial logistic regression model to predict the likelihood of finding high-grade cancer (Gleason score ≥7), low-grade cancer (Gleason score ≤6), or no cancer on prostate biopsy. The performance of the MUSIC model was evaluated in out-of-sample data using 10-fold cross-validation. Discrimination and calibration statistics were used to compare the performance of the MUSIC model to that of the PCPT risk calculator in the MUSIC cohort. RESULTS: Of the 11,809 biopsies included, 4289 (36.3%) revealed high-grade cancer; 2027 (17.2%) revealed low-grade cancer; and the remaining 5493 (46.5%) were negative. In the MUSIC model, prostate-specific antigen level, rectal examination findings, age, race, and family history of prostate cancer were significant predictors of finding high-grade cancer on biopsy. The 2 models, based on similar predictors, had comparable discrimination (multiclass area under the curve = 0.63 for the MUSIC model and 0.62 for the PCPT calculator). Calibration analyses demonstrated that the MUSIC model more accurately predicted observed outcomes, whereas the PCPT risk calculator substantively overestimated the likelihood of finding no cancer while underestimating the risk of high-grade cancer in this population. CONCLUSION: The PCPT risk calculator may not be a good predictor of individual biopsy outcomes for patients seen in contemporary urology practices.

Factors Influencing Selection of Active Surveillance for Localized Prostate Cancer.

OBJECTIVE: To determine how well demographic and clinical factors predict the initiation of Active Surveillance (AS). METHODS: AS has been suggested as a way to reduce overtreatment of men who have prostate cancer; however, factors associated with the decision to choose AS are poorly quantified. Using the Michigan Urological Surgery Improvement Collaborative registry, we identified 2977 men with prostate cancer who made treatment decisions from January 1, 2012, through December 31, 2013. We used chi-square and Wilcoxon tests to examine the association between factors and initiation of AS. Logistic regression models were fit for D'Amico risk categories. Measures of model discrimination and calibration were estimated, including area under the curve (AUC) and Brier score (BS). RESULTS: Patient age, Gleason score, clinical T-stage, urology practice, and tumor volume (greatest percent of a core involved with cancer and proportion of positive cores) were associated with the decision to choose AS in the intermediate-risk cohort (AUC = 0.875, BS = 0.07) and the complete cohort (AUC = 0.89, BS = 0.10). Patient age, urology practice, and tumor volume were significant in the low-risk cohort (AUC = 0.71, BS = 0.22). The addition of urology practice increased AUC in the low-risk cohort from 0.71 to 0.76 and reduced BS from 0.22 to 0.21. CONCLUSION: The urology practice at which a patient is seen is an important predictor for whether patients will initiate AS. Predictions were least accurate for low-risk patients, suggesting that factors such as patient preference play a role in treatment decisions.

Assessment of long-term outcomes associated with urinary prostate cancer antigen 3 and TMPRSS2:ERG gene fusion at repeat biopsy.

BACKGROUND: In men with clinically localized prostate cancer who have undergone at least 1 previous negative biopsy and have elevated serum prostate-specific antigen (PSA) levels, long-term health outcomes associated with the assessment of urinary prostate cancer antigen 3 (PCA3) and the transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) gene fusion (T2:ERG) have not been investigated previously in relation to the decision to recommend a repeat biopsy. METHODS: The authors performed a decision analysis using a decision tree for men with elevated PSA levels. The probability of cancer was estimated using the Prostate Cancer Prevention Trial Risk Calculator (version 2.0). The use of PSA alone was compared with the use of PCA3 and T2:ERG scores, with each evaluated independently, in combination with PSA to trigger a repeat biopsy. When PCA3 and T2:ERG score evaluations were used, predefined thresholds were established to determine whether the patient should undergo a repeat biopsy. Biopsy outcomes were defined as either positive (with a Gleason score of <7, 7, or >7) or negative. Probabilities and estimates of 10-year overall survival and 15-year cancer-specific survival were derived from previous studies and a literature review. Outcomes were defined as age-dependent and Gleason score-dependent 10-year overall and 15-year cancer-specific survival rates and the percentage of biopsies avoided. RESULTS: Incorporating the PCA3 score (biopsy threshold, 25; generated based on the urine PCA3 level normalized to the amount of PSA messenger RNA) or the T2:ERG score (biopsy threshold, 10; based on the urine T2:ERG level normalized to the amount of PSA messenger RNA) into the decision to recommend repeat biopsy would have avoided 55.4% or 64.7% of repeat biopsies for the base-case patient, respectively, and changes in the 10-year survival rate were only 0.93% or 1.41%, respectively. Multi-way sensitivity analyses suggested that these results were robust with respect to the model parameters. CONCLUSIONS: The use of PCA3 or T2:ERG testing for repeat biopsy decisions can substantially reduce the number of biopsies without significantly affecting 10-year survival.

Clinical predictors and recommendations for staging computed tomography scan among men with prostate cancer.

OBJECTIVE: To identify clinical variables associated with a positive computed tomography (CT) scan and estimate the performance of imaging recommendations in patients from a diverse sample of urology practices. MATERIALS AND METHODS: This study comprised 2380 men with newly diagnosed prostate cancer seen at 28 practices in the Michigan Urological Surgery Improvement Collaborative from March 2012 through September 2013. Data included age, prostate-specific antigen (PSA) level, Gleason score (GS), clinical T stage, total number of positive biopsy cores, whether or not the patient received a staging abdominal and/or pelvic CT scan, and CT scan result. We fit a multivariate logistic regression model to identify clinical variables associated with metastases detected by CT scan. We estimated the sensitivity and specificity of existing imaging recommendations. RESULTS: Among 643 men (27.4%) who underwent a staging CT scan, 62 men (9.6%) had a positive study. In the multivariate analysis, PSA, GS, and clinical T stage were independently associated with the occurrence of a positive CT scan (all P values <.05). The American Urological Association's Best Practice Statements' recommendations for imaging when PSA level >20 ng/mL or GS ≥ 8 or locally advanced cancer had a sensitivity of 87.3% and specificity of 82.6%. Compared with current practice, implementing this recommendation in the Michigan Urological Surgery Improvement Collaborative population was estimated to result in approximately 0.5% of positive study results being missed, and 26.1% of fewer study results overall. CONCLUSION: Successful implementation of CT imaging criterion of PSA level >20, GS ≥ 8, or clinical stage ≥ T3 would ensure that CT scans are performed for almost all men who would have positive study results while reducing the number of negative study results.

Toward better use of bone scans among men with early-stage prostate cancer.

OBJECTIVE: To evaluate the performance of published guidelines compared with that of current practice for radiographic staging of men with newly diagnosed prostate cancer. MATERIALS AND METHODS: Using data from the Michigan Urological Surgery Improvement Collaborative clinical registry, we identified 1509 men diagnosed with prostate cancer from March 2012 through June 2013. Clinical data included age, prostate-specific antigen (PSA) level, Gleason score (GS), clinical trial stage, number of biopsy cores, and bone scan (BS) results. We then fit a multivariate logistic regression model to examine the association between clinical variables and the occurrence of bone metastases. Because some patients did not undergo BS, we used established methods to correct for verification bias and estimate the diagnostic accuracy of published guidelines. RESULTS: Among 416 men who received a BS, 48 (11.5%) had evidence of bone metastases. Patients with bone metastases were older, with higher PSA levels and GS (all P <.05). In multivariate analyses, PSA (P <.001) and GS (P = .004) were the only independent predictors of positive BS. Guidelines from the American Urological Association and the National Comprehensive Cancer Network demonstrated similar performance in detecting bone metastases in our population, with fewer negative study results than those of the European Association of Urology guideline. Applying the American Urological Association recommendations (ie, image when PSA level >20 ng/mL or GS ≥ 8) to current clinical practice, we estimate that <1% of positive study results would be missed, whereas the number of negative study results would be reduced by 38%. CONCLUSION: Based on current practice patterns, more uniform application of existing guidelines would ensure that BS is performed for almost all men with bone metastases, while avoiding many negative imaging studies.