This study aims at developing a single numerical measure that represents a depressed patient's individual burden of illness. An exploratory study examined depressed outpatients (n = 317) followed by a hypothesis confirmatory study using the NIMH STAR*D trial (n = 2,967). Eigenvalues/eigenvectors were obtained from the Principal Component Analyses of patient-reported measures of symptom severity, functioning, and quality of life. The study shows that a single principal component labeled as the Individual Burden of Illness Index for Depression (IBI-D) accounts for the vast majority of the variance contained in these three measures providing a numerical z score for clinicians and investigators to determine an individual's burden of illness, relative to other depressed patients.

Data from a state-wide survey of California middle and high school students (N=20,203) were used to assess whether county income inequality and poverty rates were associated with adolescent smoking. Greater county income inequality, but not poverty rates, was associated with higher established smoking risk (p= 0.0019). The association was stronger in males than females, whites than other ethnic groups, and urban than rural settings. Neither county income inequality nor poverty rates were associated with experimental smoking. The findings suggest that it may be important to consider and address economic inequality in the prevention and control of adolescent tobacco use.

Purpose To examine the relationship between the expression of 7 promising apoptotic/cell proliferation proteins (Ki-67, p53, MDM2, bcl-2, bax, p16, and Cox-2) and risk of distant metastasis (DM). Experimental Design RTOG 92-02 compared external beam radiotherapy (EBRT) to ~70 Gy+short term androgen deprivation therapy (STADT) with EBRT+long term ADT (LTADT). Immunohistochemical analysis was available for ≥4 biomarkers in 616 of 1521 assessable cases. Biomarkers were evaluated individually and jointly via multivariable modeling of DM using competing risks hazards regression, adjusting for age, PSA, Gleason score, T-stage, and treatment. Results Modeling identified four biomarkers (Ki-67, MDM2, p16 and Cox-2) that were jointly associated with DM. The c-index was 0.77 for the full model and 0.70 for the model without the biomarkers; a relative improvement of about 10% (likelihood ratio p < 0.001). Subdivision of the patients into quartiles based on predicted DM risk identified a high risk group with 10-year DM risk of 52.5% after EBRT+STADT and 31% with EBRT+LTADT; associated 10-year prostate cancer specific mortality (PCSM) risks were 45.9% and 14.5% with STADT and LTADT. Conclusion Four biomarkers were found to contribute significantly to a model that predicted DM and identified a subgroup of patients at a particularly high risk of both DM and PCSM when EBRT+STADT was used. LTADT resulted in significant reductions in DM and improvements in PCSM, and there was a suggestion of greater importance in this very high risk subgroup.

Motivation: Off-target activity commonly exists in RNA interference (RNAi) screens and often generates false positives. Existing analytic methods for addressing the off-target effects are demonstrably inadequate in RNAi confirmatory screens. Results: Here, we present an analytic method assessing the collective activity of multiple short interfering RNAs (siRNAs) targeting a gene. Using this method, we can not only reduce the impact of off-target activities, but also evaluate the specific effect of an siRNA, thus providing information about potential off-target effects. Using in-house RNAi screens, we demonstrate that our method obtains more reasonable and sensible results than current methods such as the redundant siRNA activity (RSA) method, the RNAi gene enrichment ranking (RIGER) method, the frequency approach and the t-test.