Les carcinomes adénosquameux de la sphère ORL : à propos de 20 cas et revue de la littérature

Le but de cette étude rétrospective et descriptive était de déterminer les aspects cliniques et anatomopathologiques ainsi que les modes de presentation et de récidive des carcinomes adénosquameux de la sphere ORL, traités de manière curative, et recensés entre le 1er janvier 1989 et le 31 décembre 2010 au sein des Institutions du Rare Cancer Network. Nous avons retenu 20 cas de patients traités par chirurgie (S), et/ou radiothérapie (RT), avec ou sans chimiothérapie (CT) concomitante. L'âge médian était de 59.5 ans au moment du diagnostic (étendue, 48-73). La classification selon le TNM montrait des stades avancés pour la majorité des patients, avec un, deux, cinq et 11 patients présentant respectivement une Uimeur de stade I, II, III, et IVa. Les sites anatomiques incriminés étaient la cavité orale (n=4), l'oropharynx (n=5), Phypopharynx (n=2), le larynx (n2), les glandes salivaires (n=2), le vestibule nasal (n=2), les sinus maxillaires (n=2) et enfin le nasopharynx (n=l). Seize patients ont bénéficié d'une chirurgie, et 17 d'un traitement combiné (S+RT chez 13, RT+CT chez deux, et les trois modalités chez les deux derniers patients). Apres un suivi médian de 16 mois (étendue, 9-62), 3, 1, 1, 1,2 and 4 patients ont développé une récidive à distance, régionale, locale, locorégionale, locorégionale + à distance, et régionale + à distance. Toutes les récidives locales sont survenues dans le champ d'irradiation. Au dernier suivi, neuf patients étaient vivants sans maladie. La survie globale, la survie sans maladie, et le contrôle locorégional médians et à 3 ans étaient respectivement de 39 mois et 52% (95%[CI]:28-75%), 12 mois et 32% (95%[CI]: 11-54%) et enfin 33 mois et 47% (95%[CI]:20-74%). L'analyse multivariée a montré que la survie sans maladie était inversement corrélée à la présence d'effractions capsulaires (p=0.01) et aux stades avancés (IV versus I-III, p=0.002). D'une manière générale, nous avons confirmé que le pronostic global des carcinomes adénosquameux de la sphère ORL est sombre, ceci étant majoritairement dû à la survenue précoce de métastases ganglionnaires et à distance, lesquelles surviennent chez plus de la moitié des patients. En revanche, nous avons pu montrer que le contrôle local obtenu par un traitement combiné de radio-chimiothérapie permet aux patients diagnostiqués à un stade précoce de bénéficier d'une survie sans maladie tout à fait favorable

Optimality of estimators for misspecified semi-Markov models

Suppose we observe a geometrically ergodic semi-Markov process and have a parametric model for the transition distribution of the embedded Markov chain, for the conditional distribution of the inter-arrival times, or for both. The first two models for the process are semiparametric, and the parameters can be estimated by conditional maximum likelihood estimators. The third model for the process is parametric, and the parameter can be estimated by an unconditional maximum likelihood estimator. We determine heuristically the asymptotic distributions of these estimators and show that they are asymptotically efficient. If the parametric models are not correct, the (conditional) maximum likelihood estimators estimate the parameter that maximizes the Kullback--Leibler information. We show that they remain asymptotically efficient in a nonparametric sense.Comment: To appear in a Special Volume of Stochastics: An International Journal of Probability and Stochastic Processes (http://www.informaworld.com/openurl?genre=journal%26issn=1744-2508) edited by N.H. Bingham and I.V. Evstigneev which will be reprinted as Volume 57 of the IMS Lecture Notes Monograph Series (http://imstat.org/publications/lecnotes.htm

Inference about the slope in linear regression: an empirical likelihood approach

We present a new, efficient maximum empirical likelihood estimator for the slope in linear regression with independent errors and covariates. The estimator does not require estimation of the influence function, in contrast to other approaches, and is easy to obtain numerically. Our approach can also be used in the model with responses missing at random, for which we recommend a complete case analysis. This suffices thanks to results by Müller and Schick (Bernoulli 23:2693–2719, 2017), which demonstrate that efficiency is preserved. We provide confidence intervals and tests for the slope, based on the limiting Chi-square distribution of the empirical likelihood, and a uniform expansion for the empirical likelihood ratio. The article concludes with a small simulation study

Efficient prediction for linear and nonlinear autoregressive models

Conditional expectations given past observations in stationary time series are usually estimated directly by kernel estimators, or by plugging in kernel estimators for transition densities. We show that, for linear and nonlinear autoregressive models driven by independent innovations, appropriate smoothed and weighted von Mises statistics of residuals estimate conditional expectations at better parametric rates and are asymptotically efficient. The proof is based on a uniform stochastic expansion for smoothed and weighted von Mises processes of residuals. We consider, in particular, estimation of conditional distribution functions and of conditional quantile functions.Comment: Published at http://dx.doi.org/10.1214/009053606000000812 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

The transfer principle: A tool for complete case analysis

This paper gives a general method for deriving limiting distributions of complete case statistics for missing data models from corresponding results for the model where all data are observed. This provides a convenient tool for obtaining the asymptotic behavior of complete case versions of established full data methods without lengthy proofs. The methodology is illustrated by analyzing three inference procedures for partially linear regression models with responses missing at random. We first show that complete case versions of asymptotically efficient estimators of the slope parameter for the full model are efficient, thereby solving the problem of constructing efficient estimators of the slope parameter for this model. Second, we derive an asymptotically distribution free test for fitting a normal distribution to the errors. Finally, we obtain an asymptotically distribution free test for linearity, that is, for testing that the nonparametric component of these models is a constant. This test is new both when data are fully observed and when data are missing at random.Comment: Published in at http://dx.doi.org/10.1214/12-AOS1061 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour

This paper presents the segmentation of bilateral parotid glands in the Head and Neck (H&N) CT images using an active contour based atlas registration. We compare segmentation results from three atlas selection strategies: (i) selection of "single-most-similar" atlas for each image to be segmented, (ii) fusion of segmentation results from multiple atlases using STAPLE, and (iii) fusion of segmentation results using majority voting. Among these three approaches, fusion using majority voting provided the best results. Finally, we present a detailed evaluation on a dataset of eight images (provided as a part of H&N auto segmentation challenge conducted in conjunction with MICCAI-2010 conference) using majority voting strategy