The symbolic two-step method applied to cancer care delivery research: Safeguarding against designing an underpowered cluster randomized trial with a continuous outcome by accounting for the imprecision in the within- and between-center variation.

Background: Knowing the predictive factors of the variation in a center-level continuous outcome of interest is valuable in the design and analysis of parallel-arm cluster randomized trials. The symbolic two-step method for sample size planning that we present incorporates this knowledge while simultaneously accounting for patient-level characteristics. Our approach is illustrated through application to cluster randomized trials in cancer care delivery research.

Favorable Outcomes With Early Component Separation, Primary Closure of Necrotizing Soft Tissue Infections of the Genitalia (Fournier's Gangrene) Debridement Wound Defects.

Objective: To evaluate the efficacy of early necrotizing soft-tissue infections of the genitalia (NSTIG) component separation, primary wound closure (CSC). We hypothesized that early CSC would be safe, decrease the need for split-thickness skin grafting (STSG) and decrease wound convalescence time.

Materials/methods: Management of consecutive NSTIG patients from a single institution were evaluated.

Symbolic two-step method compared with single-step methods to model the center-mean outcome in cluster randomized trials.

Background: A recently developed two-step method provides an alternative to single-step methods in the analysis of cluster randomized trials (CRTs). This method, called the symbolic two-step method because it was developed within the symbolic data analysis framework, adjusts for patient-level factors when estimating and testing effects of center-level factors on both the average center-level outcome and its variation. Estimation/testing of center-level effects on center-outcome variation is the innovation of the method; identifying such effects may lead to practice changes to reduce such variation.