Outcome and patterns of failure after postoperative intensity modulated radiotherapy for locally advanced or high-risk oral cavity squamous cell carcinoma

Background To determine the outcome and patterns of failure in oral cavity cancer (OCC) patients after postoperative intensity modulated radiotherapy (IMRT) with concomitant systemic therapy. Methods All patients with locally advanced (AJCC stage III/IV) or high-risk OCC (AJCC stage II) who underwent postoperative IMRT at our institution between December 2006 and July 2010 were retrospectively analyzed. The primary endpoint was locoregional recurrence-free survival (LRRFS). Secondary endpoints included distant metastasis-free survival (DMFS), overall survival (OS), acute and late toxicities. Results Overall 53 patients were analyzed. Twenty-three patients (43%) underwent concomitant chemotherapy with cisplatin, two patients with carboplatin (4%) and four patients were treated with the monoclonal antibody cetuximab (8%). At a median follow-up of 2.3 (range, 1.1–4.6) years the 3-year LRRFS, DMFS and OS estimates were 79%, 90%, and 73% respectively. Twelve patients experienced a locoregional recurrence. Eight patients, 5 of which had both a flap reconstruction and extracapsular extension (ECE), showed an unusual multifocal pattern of recurrence. Ten locoregional recurrences occurred marginally or outside of the high-risk target volumes. Acute toxicity grades of 2 (27%) and 3 (66%) and late toxicity grades of 2 (34%) and 3 (11%) were observed. Conclusion LRRFS after postoperative IMRT is satisfying and toxicity is acceptable. The majority of locoregional recurrences occurred marginally or outside of the high-risk target volumes. Improvement of high-risk target volume definition especially in patients with flap reconstruction and ECE might transfer into better locoregional control.

Predictors of severe late radiotherapy-related toxicity after hyperfractionated radiotherapy with or without concomitant cisplatin in locally advanced head and neck cancer. Secondary retrospective analysis of a randomized phase III trial (SAKK 10/94)

This secondary analysis was performed to identify predictive factors for severe late radiotherapy (RT)-related toxicity after treatment with hyperfractionated RT +/- concomitant cisplatin in locally advanced head and neck cancer.

Locally generated particulate pollution and respiratory symptoms in young children

BACKGROUND: Particulate matter <10 mum (PM(10)) from fossil fuel combustion is associated with an increased prevalence of respiratory symptoms in children and adolescents. However, the effect of PM(10) on respiratory symptoms in young children is unclear. METHODS: The association between primary PM(10) (particles directly emitted from local sources) and the prevalence and incidence of respiratory symptoms was studied in a random sample cohort of 4400 Leicestershire children aged 1-5 years surveyed in 1998 and again in 2001. Annual exposure to primary PM(10) was calculated for the home address using the Airviro dispersion model and adjusted odds ratios (ORS) and 95% confidence intervals were calculated for each microg/m(3) increase. RESULTS: Exposure to primary PM(10) was associated with the prevalence of cough without a cold in both 1998 and 2001, with adjusted ORs of 1.21 (1.07 to 1.38) and 1.56 (1.32 to 1.84) respectively. For night time cough the ORs were 1.06 (0.94 to 1.19) and 1.25 (1.06 to 1.47), and for current wheeze 0.99 (0.88 to 1.12) and 1.28 (1.04 to 1.58), respectively. There was also an association between primary PM(10) and new onset symptoms. The ORs for incident symptoms were 1.62 (1.31 to 2.00) for cough without a cold and 1.42 (1.02 to 1.97) for wheeze. CONCLUSION: In young children there was a consistent association between locally generated primary PM(10) and the prevalence and incidence of cough without a cold and the incidence of wheeze which was independent of potential confounders.

Locally Efficient Estimation with Current Status Data and High Dimensional Covariates

In biostatistical applications, interest often focuses on the estimation of the distribution of time T between two consecutive events. If the initial event time is observed and the subsequent event time is only known to be larger or smaller than an observed monitoring time, then the data is described by the well known singly-censored current status model, also known as interval censored data, case I. We extend this current status model by allowing the presence of a time-dependent process, which is partly observed and allowing C to depend on T through the observed part of this time-dependent process. Because of the high dimension of the covariate process, no globally efficient estimators exist with a good practical performance at moderate sample sizes. We follow the approach of Robins and Rotnitzky (1992) by modeling the censoring variable, given the time-variable and the covariate-process, i.e., the missingness process, under the restriction that it satisfied coarsening at random. We propose a generalization of the simple current status estimator of the distribution of T and of smooth functionals of the distribution of T, which is based on an estimate of the missingness. In this estimator the covariates enter only through the estimate of the missingness process. Due to the coarsening at random assumption, the estimator has the interesting property that if we estimate the missingness process more nonparametrically, then we improve its efficiency. We show that by local estimation of an optimal model or optimal function of the covariates for the missingness process, the generalized current status estimator for smooth functionals become locally efficient; meaning it is efficient if the right model or covariate is consistently estimated and it is consistent and asymptotically normal in general. Estimation of the optimal model requires estimation of the conditional distribution of T, given the covariates. Any (prior) knowledge of this conditional distribution can be used at this stage without any risk of losing root-n consistency. We also propose locally efficient one step estimators. Finally, we show some simulation results.

Locally Efficient Estimation with Bivariate Right Censored Data

Estimation for bivariate right censored data is a problem that has had much study over the past 15 years. In this paper we propose a new class of estimators for the bivariate survival function based on locally efficient estimation. We introduce the locally efficient estimator for bivariate right censored data, present an asymptotic theorem, present the results of simulation studies and perform a brief data analysis illustrating the use of the locally efficient estimator.

Locally Efficient Estimation in Censored Data Models: Theory and Examples

In many applications the observed data can be viewed as a censored high dimensional full data random variable X. By the curve of dimensionality it is typically not possible to construct estimators that are asymptotically efficient at every probability distribution in a semiparametric censored data model of such a high dimensional censored data structure. We provide a general method for construction of one-step estimators that are efficient at a chosen submodel of the full-data model, are still well behaved off this submodel and can be chosen to always improve on a given initial estimator. These one-step estimators rely on good estimators of the censoring mechanism and thus will require a parametric or semiparametric model for the censoring mechanism. We present a general theorem that provides a template for proving the desired asymptotic results. We illustrate the general one-step estimation methods by constructing locally efficient one-step estimators of marginal distributions and regression parameters with right-censored data, current status data and bivariate right-censored data, in all models allowing the presence of time-dependent covariates. The conditions of the asymptotics theorem are rigorously verified in one of the examples and the key condition of the general theorem is verified for all examples.

Accuracy of Preoperative Endoscopic Ultrasound (EUS) to Distinguish Between Early and Locally Advanced Esophageal Cancer in Daily Clinical Practice

Introduction: Preoperative chemoradiotherapy is generally recommended for locally advanced esophageal cancer (clinical stage T3 or T4 or nodal positive disease) but not for early cancer (clinical stage T0 to T2, N0). EUS has been described as the most accurate method to distinguish between early and locally advanced stage in several studies. Recently however, the high accuracy of EUS (90% or higher) was questioned by some investigators. This raises the issue whether the results of studies focused on EUS accuracy may be directly translated into daily clinical practice. Aim & Methods: The aim of this retrospective analysis was to assess the accuracy of preoperative EUS to distinguish between early and locally advanced esophageal cancer in daily clinical practice outside a study setting. EUS was performed by several investigators, including trainees in one university hospital. For this purpose, EUS reports and patient files (medical and surgical) including histological reports of 300 consecutive pts with esophageal tumors were reviewed. In pts with adenocarcinoma or squamous cell cancer and surgical resection without previous radio-/chemotherapy, EUS tumor staging was compared with histological diagnosis. Results: Out of the 300 consecutive pts with esophageal tumor and EUS 102 pts had esophageal surgery after EUS-staging without any radio-/chemotherapy. In 93 pts oesophageal cancer was confirmed, whereas 9 had other tumors. The mean age was 65 years (range 27-89), sex ratio female:male was 1:3.2. To distinguish between early and late tumor stage, the accuracy was 85%. The sensitivity and specificity for early cancer was 59%, and 93%, respectively. The diagnostic accuracy for local tumor spread was 90%, 90%, 68%, 69%, 89% for pT0, pT1, pT2, pT3 and pT4 lesions, respectively. The overall accuracy for T-stage was 74%. For pN-positive staging the accuracy of EUS was 73%. Conclusion: In daily clinical practice, the accuracy of EUS in assessing esophageal tumor staging is lower than in specific studies focusing on EUS accuracy. Mainly early esophageal cancer stages were overstaged. Thus, the implementation of recommendations for diagnostic work-up of esophageal cancer patients resulting from highly specific studies should consider the appropriate clinical setting.