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Background. The iterative sure independence screening (ISIS) is a popular method in selecting important variables while maintaining most of the informative variables relevant to the outcome in high throughput data. However, it not only is computationally intensive but also may cause high false discovery rate (FDR). We propose to use the FDR as a screening method to reduce the high dimension to a lower dimension as well as controlling the FDR with three popular variable selection methods: LASSO, SCAD, and MCP. Method. The three methods with the proposed screenings were applied to prostate cancer data with presence of metastasis as the outcome. Results. Simulations showed that the three variable selection methods with the proposed screenings controlled the predefined FDR and produced high area under the receiver operating characteristic curve (AUROC) scores. In applying these methods to the prostate cancer example, LASSO and MCP selected 12 and 8 genes and produced AUROC scores of 0.746 and 0.764, respectively. Conclusions. We demonstrated that the variable selection methods with the sequential use of FDR and ISIS not only controlled the predefined FDR in the final models but also had relatively high AUROC scores. [ABSTRACT FROM AUTHOR]

Objective The Brief Pain Inventory ( BPI) was designed to yield separate scores for pain intensity and interference. It has been proposed that the pain interference factor can be further broken down into unique factors of affective (e.g., mood) and activity (e.g., work) interference. The purpose of this analysis was to confirm this affective/activity interference dichotomy. Patients and Methods A retrospective confirmatory factor analysis was completed for a sample of 184 individuals diagnosed with castrate-resistant prostate cancer (age 40-86, mean = 65.46, 77% White non- Hispanic) who had been administered the BPI as part of Cancer and Leukemia Group B trial 9480. A one-factor model was compared against two-factor and three-factor models that were developed based on the design of the instrument. Results Root mean squared error of approximation (0.075), comparative fit index (0.971), and change in chi-square, given the corresponding change in degrees of freedom (13.33, P < 0.05) values for the three-factor model (i.e., pain intensity, activity interference, and affective interference), were statistically superior in comparison with the one- and two-factor models. This three-factor structure was found to be invariant across age, mean prostate-specific antigen, and hemoglobin levels. Conclusions These results confirm that the BPI can be used to quantify the degree to which pain separately interferes with affective and activity aspects of a patient's everyday life. These findings will provide clinical trialists, pharmaceutical sponsors, and regulators with confidence in the flexibility of the BPI as they consider the use of this instrument to assist with understanding the patient experience as it relates to treatment. [ABSTRACT FROM AUTHOR]

New systemic therapies have prolonged the lives of men with metastatic castration-resistant prostate cancer (mCRPC). Use of these therapies in the adjuvant setting when the disease may be micrometastatic and potentially more sensitive to therapies may decrease mortality from prostate cancer. However, the conduct of adjuvant prostate cancer clinical trials is hampered by taking longer than a decade to reach the meaningful endpoint of overall survival (OS) and the fact that many men never die from prostate cancer, even if they relapse. A validated intermediate clinical endpoint (ICE) in prostate cancer that is a robust surrogate for OS has yet to be defined. This paper details the plans, process, and progress of the international Intermediate Clinical Endpoints in Cancer of the Prostate (ICECaP) working group to pool individual patient data from all available clinical trials of radiation or prostatectomy for localized disease and conduct the requisite analyses to determine whether an ICE can be identified. This paper further details the challenges and the a priori statistical analytical plans and strategies to define an ICE for adjuvant prostate cancer clinical trials. In addition, a brief review of the health economic analyses to model the benefits to patients, society and manufacturers is detailed. If successful, the results from this work will provide a robust surrogate for OS that will expedite the design and conduct of future adjuvant therapy trials using new agents that have proven activity in mCRPC. Moreover, it will also define the health economic benefits to patients and societies. [ABSTRACT FROM AUTHOR]