Modelling heterogeneity in Latent Space Models for Multidimensional Networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This paper introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models

Residual Site Radiotherapy After Immunochemotherapy in Primary Mediastinal B-Cell Lymphoma: A Monoinstitutional Retrospective Study

Aim: To evaluate the efficacy of residual site radiation therapy (RSRT) on local control (LC), progressionfree (PFS) and overall (OS) survival in patients with primary mediastinal lymphoma (PMBCL), following rituximab and chemotherapy treatment (ICHT). Patients and Methods: The study included 34 patients with PMBCL treated between 2006 and 2014 with ICHT with/without autologous stem cell transplantation and RSRT. Between the end of ICHT/stem cell transplantation and RSRT, patients were evaluated with F-18-fluorodeoxyglucose positron-emission tomography. The gross tumor volume included morphological mediastinal residual disease after ICHT/SCT. The percentage of LC, PFS and OS were assessed. Results: All patients received RSRT with a median dose of 30 Gy. Median follow-up was 82 months. One patient out of 34 (3%) showed progressive disease 9 months from diagnosis. The 10-year PFS and OS were 97% and 97% respectively. Conclusion: RSRT in patients with PMBCL treated with ICHT did not impact unfavorably on LC and patient survival

Minimal Extrathyroidal Extension in Predicting 1-Year Outcomes: A Longitudinal Multicenter Study of Low-to-Intermediate-Risk Papillary Thyroid Carcinoma (ITCO#4)

Background: The role of minimal extrathyroidal extension (mETE) as a risk factor for persistent papillary thyroid carcinoma (PTC) is still debated. The aim of this study was to assess the clinical impact of mETE as a predictor of worse initial treatment response in PTC patients and to verify the impact of radioiodine therapy after surgery in patients with mETE. Methods: We reviewed all records in the Italian Thyroid Cancer Observatory (ITCO) database and selected 2237 consecutive patients with PTC who satisfied the inclusion criteria (PTC with no lymph node metastases and at least 1 year of follow-up). For each case, we considered initial surgery, histological variant of PTC, tumor diameter, recurrence risk class according to the American Thyroid Association (ATA) risk stratification system, use of radioiodine therapy, and initial therapy response, as suggested by ATA guidelines. Results: At 1-year follow-up, 1831 patients (81.8%) had an excellent response, 296 (13.2%) had an indeterminate response, 55 (2.5%) had a biochemical incomplete response, and 55 (2.5%) had a structural incomplete response. Statistical analysis suggested that mETE (odds ratio [OR] 1.16, p=0.65), tumor size >2 cm (OR 1.45, p=0.34), aggressive PTC histology (OR 0.55, p=0.15), and age at diagnosis (OR 0.90, p=0.32) were not significant risk factors for a worse initial therapy response. When evaluating the combination of mETE, tumor size, and aggressive PTC histology, the presence of mETE with a >2 cm tumor was significantly associated with a worse outcome (OR 5.27, 95% CI, p=0.014). The role of radioiodine ablation in patients with mETE was also evaluated. When considering radioiodine treatment, propensity score-based matching was performed, and no significant differences were found between treated and non-treated patients (p=0.24). Conclusions: This study failed to show the prognostic value of mETE in predicting initial therapy response in a large cohort of PTC patients without lymph node metastases. The study suggests that the combination of tumor diameter and mETE can be used as a reliable prognostic factor for persistence and could be easily applied in clinical practice to manage PTC patients with low-to-intermediate risk of recurrent/persistent disease

Two-part regression models for longitudinal zero-inflated count data

Two-part models are quite well established in the economic literature, since they resemble accurately a principal-agent type model, where homogeneous, observable, counted outcomes are subject to a (prior, exogenous) selection choice. The first decision can be represented by a binary choice model, modeled using a probit or a logit link; the second can be analyzed through a truncated discrete distribution such as a truncated Poisson, negative binomial, and so on. Only recently, a particular attention has been devoted to the extension of two-part models to handle longitudinal data. The authors discuss a semi-parametric estimation method for dynamic two-part models and propose a comparison with other, well-established alternatives. Heterogeneity sources that influence the first level decision process, that is, the decision to use a certain service, are assumed to influence also the (truncated) distribution of the positive outcomes. Estimation is carried out through an EM algorithm without parametric assumptions on the random effects distribution. Furthermore, the authors investigate the extension of the finite mixture representation to allow for unobservable transition between components in each of these parts. The proposed models are discussed using empirical as well as simulated data

Official Environmental Statistical Information in Italy

In this paper, we provide descriptions of the official statistical information sources regarding the environment with a focus on soil and water. The discussion focuses on two major contributors of official statistical information in the field, ISTAT and ISPRA, describing their internal structures and links to corresponding EU institutions. We further review their latest production of statistical information on soil and water and provide several suggestions for the potential development of the field

Finite mixtures of regression models for longitudinal data

Individual-specific, time-constant, random effects are often introduced in model specification to account for dependence and/or omitted covariates in regression models for longitudinal data. This approach has been frequently criticized as it would not be robust to the presence of correlation between the observed and the unobserved covariates. Often, this is felt as a reason to chooose the fixed effect estimator instead. Starting from the so-called correlated effect approach, we argue that the conditional random effect distribution may be estimated non-parametrically by using a discrete distribution, leading to a general solution to the problem. The effectivenes of the proposed approach is shown via a large scale simulation study