Jonathan Chipman

Expanded Prostate Cancer Index Composite for Clinical Practice: Development and Validation of a Practical Health Related Quality of Life Instrument for Use in the Routine Clinical Care of Patients With Prostate Cancer

PURPOSE Measuring the health related quality of life of patients with prostate cancer in routine clinical practice is hindered by the lack of instruments enabling efficient, real-time, point of care scoring of multiple health related quality of life domains. Thus, we developed an instrument for this purpose. MATERIALS AND METHODS The Expanded Prostate Cancer Index Composite for Clinical Practice is a 1-page, 16-item questionnaire that we constructed to measure urinary incontinence, urinary irritation, and the bowel, sexual and hormonal health related quality of life domains. We eliminated conceptually overlapping items from the 3-page Expanded Prostate Cancer Index Composite-26 and revised the questionnaire format to mirror the AUA symptom index, thereby enabling practitioners to calculate health related quality of life scores at the point of care. We administered the Expanded Prostate Cancer Index Composite for Clinical Practice to a new cohort of patients with prostate cancer in community based and academic oncology, radiation, and urology practices to evaluate instrument validity as well as ease of use in clinical practice. RESULTS A total of 175 treated and 132 untreated subjects with prostate cancer completed the Expanded Prostate Cancer Index Composite for Clinical Practice. The domain scores of the Expanded Prostate Cancer Index Composite for Clinical Practice correlated highly with the respective domain scores from longer versions of the Expanded Prostate Cancer Index Composite (r≥0.93 for all domains). The Expanded Prostate Cancer Index Composite for Clinical Practice showed high internal consistency (Cronbachs α 0.64-0.84) and sensitivity to prostate cancer treatment related effects (p<0.05 in each of 5 health related quality of life domains). Patients completed the Expanded Prostate Cancer Index Composite for Clinical Practice efficiently (96% in less than 10 minutes and with 11% missing items). It was deemed very convenient by clinicians in 87% of routine clinical encounters and clinicians accurately scored completed questionnaires 94% of the time. CONCLUSIONS The Expanded Prostate Cancer Index Composite for Clinical Practice is a valid instrument that enables patient reported, health related quality of life to be measured efficiently and accurately at the point of care, and thereby facilitates improved emphasis and management of patient reported outcomes.

Comparative effectiveness study of patient-reported outcomes after proton therapy or intensity-modulated radiotherapy for prostate cancer.

Data continue to emerge on the relative merits of different treatment modalities for prostate cancer. The objective of this study was to compare patient‐reported quality‐of‐life (QOL) outcomes after proton therapy (PT) and intensity‐modulated radiation therapy (IMRT) for prostate cancer.

Measuring and Predicting Prostate Cancer Related Quality of Life Changes Using EPIC for Clinical Practice

PURPOSE We expanded the clinical usefulness of EPIC-CP (Expanded Prostate Cancer Index Composite for Clinical Practice) by evaluating its responsiveness to health related quality of life changes, defining the minimally important differences for an individual patient change in each domain and applying it to a sexual outcome prediction model. MATERIALS AND METHODS In 1,201 subjects from a previously described multicenter longitudinal cohort we modeled the EPIC-CP domain scores of each treatment group before treatment, and at short-term and long-term followup. We considered a posttreatment domain score change from pretreatment of 0.5 SD or greater clinically significant and p ≤ 0.01 statistically significant. We determined the domain minimally important differences using the pooled 0.5 SD of the 2, 6, 12 and 24-month posttreatment changes from pretreatment values. We then recalibrated an EPIC-CP based nomogram model predicting 2-year post-prostatectomy functional erection from that developed using EPIC-26. RESULTS For each health related quality of life domain EPIC-CP was sensitive to similar posttreatment health related quality of life changes with time, as was observed using EPIC-26. The EPIC-CP minimally important differences in changes in the urinary incontinence, urinary irritation/obstruction, bowel, sexual and vitality/hormonal domains were 1.0, 1.3, 1.2, 1.6 and 1.0, respectively. The EPIC-CP based sexual prediction model performed well (AUC 0.76). It showed robust agreement with its EPIC-26 based counterpart with 10% or less predicted probability differences between models in 95% of individuals and a mean ± SD difference of 0.0 ± 0.05 across all individuals. CONCLUSIONS EPIC-CP is responsive to health related quality of life changes during convalescence and it can be used to predict 2-year post-prostatectomy sexual outcomes. It can facilitate shared medical decision making and patient centered care.

Simplifying clinical use of the genetic risk prediction model BRCAPRO

Health care providers need simple tools to identify patients at genetic risk of breast and ovarian cancers. Genetic risk prediction models such as BRCAPRO could fill this gap if incorporated into Electronic Medical Records or other Health Information Technology solutions. However, BRCAPRO requires potentially extensive information on the counselee and her family history. Thus, it may be useful to provide simplified version(s) of BRCAPRO for use in settings that do not require exhaustive genetic counseling. We explore four simplified versions of BRCAPRO, each using less complete information than the original model. BRCAPROLYTE uses information on affected relatives only up to second degree. It is in clinical use but has not been evaluated. BRCAPROLYTE-Plus extends BRCAPROLYTE by imputing the ages of unaffected relatives. BRCAPROLYTE-Simple reduces the data collection burden associated with BRCAPROLYTE and BRCAPROLYTE-Plus by not collecting the family structure. BRCAPRO-1Degree only uses first-degree affected relatives. We use data on 2,713 individuals from seven sites of the Cancer Genetics Network and MD Anderson Cancer Center to compare these simplified tools with the Family History Assessment Tool (FHAT) and BRCAPRO, with the latter serving as the benchmark. BRCAPROLYTE retains high discrimination; however, because it ignores information on unaffected relatives, it overestimates carrier probabilities. BRCAPROLYTE-Plus and BRCAPROLYTE-Simple provide better calibration than BRCAPROLYTE, so they have higher specificity for similar values of sensitivity. BRCAPROLYTE-Plus performs slightly better than BRCAPROLYTE-Simple. The Areas Under the ROC curve are 0.783 (BRCAPRO), 0.763 (BRCAPROLYTE), 0.772 (BRCAPROLYTE-Plus), 0.773 (BRCAPROLYTE-Simple), 0.728 (BRCAPRO-1Degree), and 0.745 (FHAT). The simpler versions, especially BRCAPROLYTE-Plus and BRCAPROLYTE-Simple, lead to only modest loss in overall discrimination compared to BRCAPRO in this dataset. Thus, we conclude that simplified implementations of BRCAPRO can be used for genetic risk prediction in settings where collection of complete pedigree information is impractical.

Uncertainty and perception of danger among patients undergoing treatment for prostate cancer

Study Type – Therapy (attitude prevalence)

Recent BRCAPRO upgrades significantly improve calibration

The recent release of version 2.0-8 of the BayesMendel package contains an updated BRCAPRO risk prediction model, which includes revised modeling of contralateral breast cancer (CBC) penetrance, provisions for pedigrees of mixed ethnicity and an adjustment for mastectomies among family members. We estimated penetrance functions for CBC by a combination of parametric survival modeling of literature data and deconvolution of SEER9 data. We then validated the resulting updated model of CBC in BRCAPRO by comparing it with the previous release (BayesMendel 2.0-7), using pedigrees from the Cancer Genetics Network (CGN) Model Validation Study. Version 2.0-8 of BRCAPRO discriminates BRCA1/BRCA2 carriers from noncarriers with similar accuracy compared with the previous version (increase in AUC, 0.0043), is slightly more precise in terms of the root-mean-square error (decrease in RMSE, 0.0108), and it significantly improves calibration (ratio of observed to expected events of 0.9765 in version 2.0-8, compared with 0.8910 in version 2.0-7). We recommend that the new version be used in clinical counseling, particularly in settings where families with CBC are common. Cancer Epidemiol Biomarkers Prev; 23(8); 1689–95. ©2014 AACR.

Providing access to risk prediction tools via the HL7 XML-formatted risk web service

Cancer risk prediction tools provide valuable information to clinicians but remain computationally challenging. Many clinics find that CaGene or HughesRiskApps fit their needs for easy- and ready-to-use software to obtain cancer risks; however, these resources may not fit all clinics’ needs. The HughesRiskApps Group and BayesMendel Lab therefore developed a web service, called “Risk Service”, which may be integrated into any client software to quickly obtain standardized and up-to-date risk predictions for BayesMendel tools (BRCAPRO, MMRpro, PancPRO, and MelaPRO), the Tyrer-Cuzick IBIS Breast Cancer Risk Evaluation Tool, and the Colorectal Cancer Risk Assessment Tool. Software clients that can convert their local structured data into the HL7 XML-formatted family and clinical patient history (Pedigree model) may integrate with the Risk Service. The Risk Service uses Apache Tomcat and Apache Axis2 technologies to provide an all Java web service. The software client sends HL7 XML information containing anonymized family and clinical history to a Dana-Farber Cancer Institute (DFCI) server, where it is parsed, interpreted, and processed by multiple risk tools. The Risk Service then formats the results into an HL7 style message and returns the risk predictions to the originating software client. Upon consent, users may allow DFCI to maintain the data for future research. The Risk Service implementation is exemplified through HughesRiskApps. The Risk Service broadens the availability of valuable, up-to-date cancer risk tools and allows clinics and researchers to integrate risk prediction tools into their own software interface designed for their needs. Each software package can collect risk data using its own interface, and display the results using its own interface, while using a central, up-to-date risk calculator. This allows users to choose from multiple interfaces while always getting the latest risk calculations. Consenting users contribute their data for future research, thus building a rich multicenter resource.

Simpson's paradox in the integrated discrimination improvement

The integrated discrimination improvement (IDI) is commonly used to compare two risk prediction models; it summarizes the extent a new model increases risk in events and decreases risk in non-events. The IDI averages risks across events and non-events and is therefore susceptible to Simpsons paradox. In some settings, adding a predictive covariate to a well calibrated model results in an overall negative (positive) IDI. However, if stratified by that same covariate, the strata-specific IDIs are positive (negative). Meanwhile, the calibration (observed to expected ratio and Hosmer-Lemeshow Goodness of Fit Test), area under the receiver operating characteristic curve, and Brier score improve overall and by stratum. We ran extensive simulations to investigate the impact of an imbalanced covariate upon metrics (IDI, area under the receiver operating characteristic curve, Brier score, and R2), provide an analytic explanation for the paradox in the IDI, and use an investigative metric, a Weighted IDI, to better understand the paradox. In simulations, all instances of the paradox occurred under stratum-specific mis-calibration, yet there were mis-calibrated settings in which the paradox did not occur. The paradox is illustrated on Cancer Genomics Network data by calculating predictions based on two versions of BRCAPRO, a Mendelian risk prediction model for breast and ovarian cancer. In both simulations and the Cancer Genomics Network data, overall model calibration did not guarantee stratum-level calibration. We conclude that the IDI should only assess model performance among a clinically relevant subset when stratum-level calibration is strictly met and recommend calculating additional metrics to confirm the direction and conclusions of the IDI. Copyright

A two-stage approach to genetic risk assessment in primary care

Genetic risk prediction models such as BRCAPRO are used routinely in genetic counseling for identification of potential BRCA1 and BRCA2 mutation carriers. They require extensive information on the counselee and her family history, and thus are not practical for primary care. To address this gap, we develop and test a two-stage approach to genetic risk assessment by balancing the tradeoff between the amount of information used and accuracy achieved. The first stage is intended for primary care wherein limited information is collected and analyzed using a simplified version of BRCAPRO. If the assessed risk is sufficiently high, more extensive information is collected and the full BRCAPRO is used (stage two: intended for genetic counseling). We consider three first-stage tools: BRCAPROLYTE, BRCAPROLYTE-Plus, and BRCAPROLYTE-Simple. We evaluate the two-stage approach on independent clinical data on probands with family history of breast and ovarian cancers, and BRCA genetic test results. These include population-based data on 1344 probands from Newton-Wellesley Hospital and mostly high-risk family data on 2713 probands from Cancer Genetics Network and MD Anderson Cancer Center. We use discrimination and calibration measures, appropriately modified to evaluate the overall performance of a two-stage approach. We find that the proposed two-stage approach has very limited loss of discrimination and comparable calibration as BRCAPRO. It identifies a similar number of carriers without requiring a full family history evaluation on all probands. We conclude that the two-stage approach allows for practical large-scale genetic risk assessment in primary care.

Elevated Serum Cytokines and Trichomonas vaginalis Serology at Diagnosis Are Not Associated With Higher Gleason Grade or Lethal Prostate Cancer

Background Inflammation and infections have been associated with prostate cancer progression. We assessed whether elevated serum cytokines or T. vaginalis seropositivity at the time of diagnosis was associated with higher grade or lethal prostate cancer. Patients and Methods Men with localized or metastatic prostate cancer were included in this study. Cytokine serum levels including interleukin (IL)‐1&agr;, IL‐1&bgr;, IL‐2, IL‐6, IL‐8, monocyte chemotactic protein 1 (CCL‐2), tumor necrosis factor &agr;, and growth‐regulated oncogene &agr; (CXCL‐1) using a multiplex enzyme‐linked immunosorbent assay and T. vaginalis serology were measured in blood samples at diagnosis. Results A total of 324 patients were identified at time of localized disease and 118 at time of metastatic disease. Of the 189 patients with localized disease and clinical follow‐up data (median, 73 months), 28 developed lethal disease. There was no association between circulating cytokine levels above median concentrations nor T. vaginalis seropositivity and risk of intermediate‐ to high‐risk or lethal prostate cancer. Conclusion Higher levels of serum cytokine levels and T. vaginalis seropositivity at diagnosis are not associated with high‐grade or lethal prostate cancer and do not aid risk stratification of localized prostate cancer. Micro‐Abstract New prognostic biomarkers in prostate cancer are needed to identify patients with low‐risk localized prostate cancer who would benefit from earlier curative and aggressive treatments. We found no association between circulating cytokine levels that regulate both innate and adaptive immunity or proinflammatory chemokines nor Trichomonas vaginalis seropositivity and risk of intermediate‐ to high‐risk or lethal prostate cancer.