Cutaneous squamous cell carcinoma staging may influence management in users: A survey study.

PURPOSE: This study aims to determine whether there is consensus regarding staging and management of cutaneous squamous cell carcinoma (CSCC) across the various specialties that manage this disease. MATERIALS AND METHODS: A survey regarding CSCC high-risk features, staging, and management was created and emailed to cutaneous oncology experts including dermatology, head and neck surgery/surgical oncology, radiation oncology, and medical oncology. RESULTS: One hundred fifty-six (46%) of 357 invited physicians completed the survey. Depth of invasion (92%), perineural invasion (99%), histologic differentiation (85%), and patient immunosuppression (90%) achieved consensus (\u3e80%) as high-risk features of CSCC. Dermatologists were more likely to also choose clinical tumor diameter (79% vs. 54%) and histology (99% vs. 66%) as a high-risk feature. Dermatologists were also more likely to utilize the Brigham and Women\u27s Hospital (BWH) staging system alone or in conjunction with American Joint Committee on Cancer (AJCC) (71%), whereas other cancer specialists (OCS) tend to use only AJCC (71%). Respondents considered AJCC T3 and higher (90%) and BWH T2b and higher (100%) to be high risk and when they consider radiologic imaging, sentinel lymph node biopsy, post-operative radiation therapy, and increased follow-up. Notably, a large number of respondents do not use staging systems or tumor stage to determine treatment options beyond surgery in high-risk CSCC. CONCLUSION: This survey study highlights areas of consensus and differences regarding the definition of high-risk features of CSCC, staging approaches, and management patterns between dermatologists and OCS. High-risk CSCC is defined as, but not limited to, BWH T2b and higher and AJCC T3 and higher, and these thresholds can be used to identify cases for which treatment beyond surgery may be considered. Dermatologists are more likely to utilize BWH staging, likely because BWH validation studies showing advantages over AJCC were published in dermatology journals and discussed at dermatology meetings. Additional data are necessary to develop a comprehensive risk-based management approach for CSCC

A randomly perturbed DC/DC converter

by Chetan D. Pahlajan

Stochastic Averaging Correctors for a Noisy Hamiltonian System With Discontinuous Statistics

91 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.We construct here certain perturbed test functions for stochastic averaging of a noisy planar Hamiltonian system containing a homoclinic orbit. The noise is assumed to be small and have skewness at the homoclinic orbit. Following Sowers, we center our efforts on a singular perturbations problem in a boundary layer near the homoclinic orbit. At the heart of this analysis is the solution of a set of heat equations, coupled through their boundary data. We identify the glueing conditions, which are sufficient conditions ensuring solvability of the above problem. Probabilistically, the glueing conditions give the relative likelihoods, in the averaged picture, of diffusing into the various regions of phase space when one starts at the homoclinic orbit.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Fluctuation analysis for a class of nonlinear systems with fast periodic sampling and small state-dependent white noise

We consider a nonlinear differential equation under the combined influence of small state-dependent Brownian perturbations of size $\varepsilon$, and fast periodic sampling with period $\delta$; $0<\varepsilon, \delta \ll 1$. Thus, state samples (measurements) are taken every $\delta$ time units, and the instantaneous rate of change of the state depends on its current value as well as its most recent sample. We show that the resulting stochastic process indexed by $\varepsilon,\delta$, can be approximated, as $\varepsilon,\delta \searrow 0$, by an ordinary differential equation (ODE) with vector field obtained by replacing the most recent sample by the current value of the state. We next analyze the fluctuations of the stochastic process about the limiting ODE. Our main result asserts that, for the case when $\delta \searrow 0$ at the same rate as, or faster than, $\varepsilon \searrow 0$, the rescaled fluctuations can be approximated in a suitable strong (pathwise) sense by a limiting stochastic differential equation (SDE). This SDE varies depending on the exact rates at which $\varepsilon,\delta \searrow 0$. The key contribution here involves computing the effective drift term capturing the interplay between noise and sampling in the limiting SDE. The results essentially provide a first-order perturbation expansion, together with error estimates, for the stochastic process of interest. Connections with the performance analysis of feedback control systems with sampling are discussed and illustrated numerically through a simple example.Comment: 37 pages, 4 figure