Biomarkers in chronic obstructive pulmonary diseases. Clinical and functional correlations.

Asthma and chronic obstructive pulmonary disease (COPD) are two distinct lung diseases with distinctive clinical and inflammatory features. A proportion of asthmatic patients experience a fixed airflow obstruction that persists despite optimal pharmacologic treatment for reasons that are still largely unknown. We found that patients with asthma and COPD sharing a similar fixed airflow obstruction have an increased lung function decline and frequency of exacerbations. Nevertheless, the decline in lung function is associated with specific features of the underlying inflammation. Airway inflammation increases during asthma exacerbation and disease severity. Less is known about the correlations between symptoms and airway inflammation in COPD patients. We found that there is no correlation between symptoms and lung function in COPD patients. Nevertheless symptoms changes are associated with specific inflammatory changes: cough is associated with an increase of sputum neutrophils in COPD, dyspnoea is associated with an increase of eosinophils. The mechanisms of this correlation remain unknown. Neutrophils inflammation is associated with bacterial colonization in stable COPD. Is not known whether inhaled corticosteroids might facilitate bacterial colonization in COPD patients. We found that the use of inhaled corticosteroids in COPD patients is associated with an increase of airway bacterial load and with an increase of airway pathogen detection. Bacterial and viral infections are the main causes of COPD and asthma exacerbations. Impaired innate immune responses to rhinovirus infections have been described in adult patients with atopic asthma. Whether this impaired immune condition is present early in life and whether is modulated by a concomitant atopic condition is currently unknown. We found that deficient innate immune responses to rhinovirus infection are already present early in life in atopic patients without asthma and in asthmatic subjects. These findings generalize the scenario of increased susceptibility to viral infections to other Th2 oriented conditions.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

Clinical outcome and biological characteristics of Chronic Myeloid Leukemia patients treated with nilotinib front-line

The present work reports the outcome of the GIMEMA CML WP study CML0811, an independent trial investigating nilotinib as front-line treatment in chronic phase chronic myeloid leukemia (CML). Moreover, the results of the proteomic analysis of the CD34+ cells collected at CML diagnosis, compared to the counterpart from healthy donors, are reported. Our study confirmed that nilotinib is highly effective in the prevention of the progression to accelerated/blast phase, a condition that today is still associated with high mortality rates. Despite the relatively short follow-up, cardiovascular issues, particularly atherosclerotic adverse events (AE), have emerged, and the frequency of these AEs may counterbalance the anti-leukemic efficacy. The deep molecular response rates in our study compare favorably to those obtained with imatinib, in historic cohorts, and confirm the findings of the Company-sponsored ENESTnd study. Considering the increasing rates of deep MR over time we observed, a significant proportion of patients will be candidate to treatment discontinuation in the next years, with higher probability of remaining disease-free in the long term. The presence of the additional and complex changes we found at the proteomic level in CML CD34+ cells should be taken into account for the investigation on novel targeted therapies, aimed at the eradication of the disease.