Analysis of web visit histories, part I: Distance-based visualization of sequence rules

This paper constitutes Part I of the contribution to the analysis of web visit histories through a new methodological framework. Firstly, web usage and web structure mining are considered as an unique mining process to detect the latent structure of the web navigation across the web sections of a single portal. We extend association rules theory to web data defining new concepts of web (patterns) association and preference matrices, as well as of (indirect and direct) sequence rules. We identify the most significant rules, according to a multiple testing procedure. In the literature, web usage patterns can be visualized in no-distance-based graphs describing the navigation behavior across web pages with sequential arrows. In the following, we introduce a geometrical visualization of sequence rules at any click of the web navigation. In particular, we provide two distance-based visualization methods for the static analysis of all data tout court and the dynamic analysis to discover the most significant web paths click by click. A real world case study is considered throughout the methodological description

Biofilm production in Staphylococcus epidermidis strains isolated from the skin of hospitalized patients: Genetic and phenotypic characteristics

A major virulence factor of Staphylococcus epidermidis is its ability to form biofilms, permitting it to adhere to a surface and, in turn, to form a mucoid layer on polymer surfaces. Multiple factors have been found to influence bacterial attachment. Currently, this bacterium is commonly associated with hospital infections as a consequence of its ability to colonize, albeit accidentally, medical devices. This study investigated the genetic and phenotypic formation of biofilm in 105 S. epidermidis strains isolated from the skin of hospitalized patients. Fifty-eight of these strains were positive for the mecA gene (MRSE) and 47 were found to be negative (MSSE). Genetic characterizations were performed for the detection of the mecA, icaADBC, atlE, aap, bhp, IS256 and agr groups by PCR. Biofilm production was examined by culturing the strains in TBS medium and TBS with 0.5 and 1% respectively of glucose, and a semiquantitative assay on tissue culture plates was used. Although a molecular analysis estimate of detailed biofilm formation is costly in terms of time and complexity, a semiquantitative assay can be proposed as a rapid and cheap diagnostic method for initial screening to discover virulent strains. We confirmed a close correlation between genetic and phenotypic characteristics, highlighting the fact that, when S. epidermidis isolates were cultured in TSB with 1% of glucose, an increase in biofilm production was observed, as confirmed by positivity for the ica locus by molecular analysis

Influenza vaccination coverage among medical residents: An Italian multicenter survey

Although influenza vaccination is recognized to be safe and effective, recent studies have confirmed that immunization coverage among health care workers remain generally low, especially among medical residents (MRs). Aim of the present multicenter study was to investigate attitudes and determinants associated with acceptance of influenza vaccination among Italian MRs. A survey was performed in 2012 on MRs attending post-graduate schools of 18 Italian Universities. Each participant was interviewed via an anonymous, self-administered, web-based questionnaire including questions on attitudes regarding influenza vaccination. A total of 2506 MRs were recruited in the survey and 299 (11.9%) of these stated they had accepted influenza vaccination in 2011-2012 season. Vaccinated MRs were older (P = 0.006), working in clinical settings (P = 0.048), and vaccinated in the 2 previous seasons (P < 0.001 in both seasons). Moreover, MRs who had recommended influenza vaccination to their patients were significantly more compliant with influenza vaccination uptake in 2011-2012 season (P < 0.001). "To avoid spreading influenza among patients" was recognized as the main reason for accepting vaccination by less than 15% of vaccinated MRs. Italian MRs seem to have a very low compliance with influenza vaccination and they seem to accept influenza vaccination as a habit that is unrelated to professional and ethical responsibility. Otherwise, residents who refuse vaccination in the previous seasons usually maintain their behaviors. Promoting correct attitudes and good practice in order to improve the influenza immunization rates of MRs could represent a decisive goal for increasing immunization coverage among health care workers of the future. © 2014 Landes Bioscience

ITALIAN CANCER FIGURES - REPORT 2015: The burden of rare cancers in Italy = I TUMORI IN ITALIA - RAPPORTO 2015: I tumori rari in Italia

OBJECTIVES: This collaborative study, based on data collected by the network of Italian Cancer Registries (AIRTUM), describes the burden of rare cancers in Italy. Estimated number of new rare cancer cases yearly diagnosed (incidence), proportion of patients alive after diagnosis (survival), and estimated number of people still alive after a new cancer diagnosis (prevalence) are provided for about 200 different cancer entities. MATERIALS AND METHODS: Data herein presented were provided by AIRTUM population- based cancer registries (CRs), covering nowadays 52% of the Italian population. This monograph uses the AIRTUM database (January 2015), which includes all malignant cancer cases diagnosed between 1976 and 2010. All cases are coded according to the International Classification of Diseases for Oncology (ICD-O-3). Data underwent standard quality checks (described in the AIRTUM data management protocol) and were checked against rare-cancer specific quality indicators proposed and published by RARECARE and HAEMACARE (www.rarecarenet.eu; www.haemacare.eu). The definition and list of rare cancers proposed by the RARECAREnet "Information Network on Rare Cancers" project were adopted: rare cancers are entities (defined as a combination of topographical and morphological codes of the ICD-O-3) having an incidence rate of less than 6 per 100,000 per year in the European population. This monograph presents 198 rare cancers grouped in 14 major groups. Crude incidence rates were estimated as the number of all new cancers occurring in 2000-2010 divided by the overall population at risk, for males and females (also for gender-specific tumours).The proportion of rare cancers out of the total cancers (rare and common) by site was also calculated. Incidence rates by sex and age are reported. The expected number of new cases in 2015 in Italy was estimated assuming the incidence in Italy to be the same as in the AIRTUM area. One- and 5-year relative survival estimates of cases aged 0-99 years diagnosed between 2000 and 2008 in the AIRTUM database, and followed up to 31 December 2009, were calculated using complete cohort survival analysis. To estimate the observed prevalence in Italy, incidence and follow-up data from 11 CRs for the period 1992-2006 were used, with a prevalence index date of 1 January 2007. Observed prevalence in the general population was disentangled by time prior to the reference date (≤2 years, 2-5 years, ≤15 years). To calculate the complete prevalence proportion at 1 January 2007 in Italy, the 15-year observed prevalence was corrected by the completeness index, in order to account for those cancer survivors diagnosed before the cancer registry activity started. The completeness index by cancer and age was obtained by means of statistical regression models, using incidence and survival data available in the European RARECAREnet data. RESULTS: In total, 339,403 tumours were included in the incidence analysis. The annual incidence rate (IR) of all 198 rare cancers in the period 2000-2010 was 147 per 100,000 per year, corresponding to about 89,000 new diagnoses in Italy each year, accounting for 25% of all cancer. Five cancers, rare at European level, were not rare in Italy because their IR was higher than 6 per 100,000; these tumours were: diffuse large B-cell lymphoma and squamous cell carcinoma of larynx (whose IRs in Italy were 7 per 100,000), multiple myeloma (IR: 8 per 100,000), hepatocellular carcinoma (IR: 9 per 100,000) and carcinoma of thyroid gland (IR: 14 per 100,000). Among the remaining 193 rare cancers, more than two thirds (No. 139) had an annual IR &lt;0.5 per 100,000, accounting for about 7,100 new cancers cases; for 25 cancer types, the IR ranged between 0.5 and 1 per 100,000, accounting for about 10,000 new diagnoses; while for 29 cancer types the IR was between 1 and 6 per 100,000, accounting for about 41,000 new cancer cases. Among all rare cancers diagnosed in Italy, 7% were rare haematological diseases (IR: 41 per 100,000), 18% were solid rare cancers. Among the latter, the rare epithelial tumours of the digestive system were the most common (23%, IR: 26 per 100,000), followed by epithelial tumours of head and neck (17%, IR: 19) and rare cancers of the female genital system (17%, IR: 17), endocrine tumours (13% including thyroid carcinomas and less than 1% with an IR of 0.4 excluding thyroid carcinomas), sarcomas (8%, IR: 9 per 100,000), central nervous system tumours and rare epithelial tumours of the thoracic cavity (5%with an IR equal to 6 and 5 per 100,000, respectively). The remaining (rare male genital tumours, IR: 4 per 100,000; tumours of eye, IR: 0.7 per 100,000; neuroendocrine tumours, IR: 4 per 100,000; embryonal tumours, IR: 0.4 per 100,000; rare skin tumours and malignant melanoma of mucosae, IR: 0.8 per 100,000) each constituted &lt;4% of all solid rare cancers. Patients with rare cancers were on average younger than those with common cancers. Essentially, all childhood cancers were rare, while after age 40 years, the common cancers (breast, prostate, colon, rectum, and lung) became increasingly more frequent. For 254,821 rare cancers diagnosed in 2000-2008, 5-year RS was on average 55%, lower than the corresponding figures for patients with common cancers (68%). RS was lower for rare cancers than for common cancers at 1 year and continued to diverge up to 3 years, while the gap remained constant from 3 to 5 years after diagnosis. For rare and common cancers, survival decreased with increasing age. Five-year RS was similar and high for both rare and common cancers up to 54 years; it decreased with age, especially after 54 years, with the elderly (75+ years) having a 37% and 20% lower survival than those aged 55-64 years for rare and common cancers, respectively. We estimated that about 900,000 people were alive in Italy with a previous diagnosis of a rare cancer in 2010 (prevalence). The highest prevalence was observed for rare haematological diseases (278 per 100,000) and rare tumours of the female genital system (265 per 100,000). Very low prevalence (&lt;10 prt 100,000) was observed for rare epithelial skin cancers, for rare epithelial tumours of the digestive system and rare epithelial tumours of the thoracic cavity. COMMENTS: One in four cancers cases diagnosed in Italy is a rare cancer, in agreement with estimates of 24% calculated in Europe overall. In Italy, the group of all rare cancers combined, include 5 cancer types with an IR&gt;6 per 100,000 in Italy, in particular thyroid cancer (IR: 14 per 100,000).The exclusion of thyroid carcinoma from rare cancers reduces the proportion of them in Italy in 2010 to 22%. Differences in incidence across population can be due to the different distribution of risk factors (whether environmental, lifestyle, occupational, or genetic), heterogeneous diagnostic intensity activity, as well as different diagnostic capacity; moreover heterogeneity in accuracy of registration may determine some minor differences in the account of rare cancers. Rare cancers had worse prognosis than common cancers at 1, 3, and 5 years from diagnosis. Differences between rare and common cancers were small 1 year after diagnosis, but survival for rare cancers declined more markedly thereafter, consistent with the idea that treatments for rare cancers are less effective than those for common cancers. However, differences in stage at diagnosis could not be excluded, as 1- and 3-year RS for rare cancers was lower than the corresponding figures for common cancers. Moreover, rare cancers include many cancer entities with a bad prognosis (5-year RS &lt;50%): cancer of head and neck, oesophagus, small intestine, ovary, brain, biliary tract, liver, pleura, multiple myeloma, acute myeloid and lymphatic leukaemia; in contrast, most common cancer cases are breast, prostate, and colorectal cancers, which have a good prognosis. The high prevalence observed for rare haematological diseases and rare tumours of the female genital system is due to their high incidence (the majority of haematological diseases are rare and gynaecological cancers added up to fairly high incidence rates) and relatively good prognosis. The low prevalence of rare epithelial tumours of the digestive system was due to the low survival rates of the majority of tumours included in this group (oesophagus, stomach, small intestine, pancreas, and liver), regardless of the high incidence rate of rare epithelial cancers of these sites. This AIRTUM study confirms that rare cancers are a major public health problem in Italy and provides quantitative estimations, for the first time in Italy, to a problem long known to exist. This monograph provides detailed epidemiologic indicators for almost 200 rare cancers, the majority of which (72%) are very rare (IR&lt;0.5 per 100,000). These data are of major interest for different stakeholders. Health care planners can find useful information herein to properly plan and think of how to reorganise health care services. Researchers now have numbers to design clinical trials considering alternative study designs and statistical approaches. Population-based cancer registries with good quality data are the best source of information to describe the rare cancer burden in a population

A heuristic algorithm for the consensus ranking problem

Preference rankings virtually appear in all field of science (behavioural sciences, machine learning, decision making and so on). The well-known social choice problem consists in trying to find a reasonable procedure to use the aggregate preferences expressed by subjects (usually called judges) to reach a collective decision. This problem turns out to be equivalent to the problem of estimating the consensus (central) ranking from data that is NP-hard. A branch and bound algorithm has been previously proposed to calculate the consensus ranking given n rankings expressed on m objects. We propose a new algorithm to find the consensus ranking that is perfectly equivalent to the previous algorithm in terms of solutions reached but permits a remarkable saving in computational time

On Concurvity in nonlinear and nonparametric regression models

When data are affected by multicollinearity in the linear regression framework, then concurvity will be present in fitting a Generalized additive model (GAM). The term concurvity describes nonlinear dependencies among the predictor variables. As collinearity results in inflated variance of the estimated regression coefficients in the linear regression model, the result of the presence of concurvity leads to instability of the estimated coefficients in GAM. Even if the backfitting algorithm will always converge to a solution, in the case of concurvity the final solution of the backfitting procedure in fitting a GAM is influenced by the starting functions. While exact concurvity is highly unlikely, approximate concurvity, the analogue of multicollinearity, is of practical concern as it can lead to upwardly biased estimates of the parameters and to underestimation of their standard errors, increasing the risk of committing type I error. We compare the existing approaches to detect concurvity, pointing out their advantages and drawbacks, using several simulated and real data sets. As a result, a general criterion to detect concurvity in nonlinear and non parametric regression models will be provided to ensure the robustness of the parameters estimation

An extension of the Adjusted Rand Index for fuzzy partitions

Invited talk: To compare clustering partitions, Rand index (RI) and Adjusted Rand index (ARI) are commonly used for measuring the agreement between partitions. Both these external validation indexes aim to analyze how close is a cluster to a reference (or to prior knowledge about the data) by counting corrected classified pairs of elements. When the aim is to evaluate the solution of a fuzzy clustering algorithm, the computation of these measures require converting the soft partitions into hard ones. It is known that different fuzzy partitions describing very different structures in the data can lead to the same crisp partition and consequently to the same values of these measures. We compare the existing approaches to evaluate the external validation criteria in fuzzy clustering and we propose an extension of the ARI for fuzzy partitions based on the normalized degree of concordance, which we call Adjusted Concordance Index. Through use of real and simulated data, we analyze and evaluate the performance of our proposal

Analysis of Web Visit Histories, Part II: Predicting Navigation by Nested STUMP Regression Trees

This paper constitutes part II of the contribution to the analysis of web visit histories through a new methodological framework for web usage-structure mining considering association rules theory. The aim is to explore through a tree structure the sequence of direct rules (i.e. paths) that characterize a web navigator who keeps standing longer on a web page with respect to the path characterizing navigators who leave the web earlier. A novel tree-based structure is introduced to take into account that the learning sample changes click by click leaving out navigators who drop off from the web after any click. The response variable at each time point is the remaining number of clicks before leaving the web. The split is induced by the predictors that describe the preferred web sections. The methodology introduced results in a Nested Stump Regression Tree that is an hierarchy of stump trees, where a stump is a tree with only one split or, equivalently, with only two terminal nodes. Suitable properties are outlined. As in first part of the contribution to the analysis of the web visit histories, a methodological description is provided by considering a web portal with a fixed set of web sections, i.e. a data set coming from the UCI Machine Learning Repository