Evaluation of influenza vaccination efficacy in reducing influenza-related complications and excess mortality in Northern Italy (2014-2017).

OBJECTIVE: The main objective of this study was to estimate the efficacy of influenza vaccination in reducing influenza-attributable hospitalization and emergency room (ER) admission for severe complications and influenza-attributable excess mortality in individuals ≥65 years of age. METHODS: We analyzed the ≥65 years-old community (n = 952,822) afferent to the Brescia (Northern Italy) Health Protection Agency, considered an Italian population reference, to evaluate the efficacy of influenza vaccination (seasons 2014-17) in reducing deaths, ER-admissions, and hospitalizations for influenza-related complications in the elderly. RESULTS: A protective effect of influenza vaccination emerged in reducing hospitalization and ER admission for diseases of the respiratory system and for death from all causes in people ≥65 years. The major effect of influenza vaccination was the reduction in risk of death from all causes, increasing with age and comorbidity. CONCLUSION: Influenza vaccination has reduced the number of ER admissions and hospitalizations caused by influenza-related complications and has prevented death among high-risk groups in elderly ≥65 years, resulting in social and public health cost savings. Stronger or new vaccination strategies are needed to improve vaccination rates among the elderly.

Elderly people: propensity to be vaccinated for seasonal influenza in Italy.

Seasonal influenza continues to be a major cause of illness and death. Vaccination is the most cost-effective prophylaxis to prevent the disease and it is particularly important for people who are at high risk of serious complications derived from influenza, especially for people ≥65 years. In Italy, the influenza vaccination program has been unsuccessful with low rates of uptake in people ≥65 years. We analyzed all the community ≥65 years of the Health Promoting Agency (HPA) of Brescia (northern Italy) to evaluate the propensity attitudes toward influenza vaccination among people ≥65 years in four consecutive seasonal influenza campaigns (from 2014/2015 to 2017/2018). Information about subjects were retrieved from administrative databases. Data from 952,822 records were analyzed. The prevalence of vaccinated subjects in the four campaigns was 38.6%, 33.7%, 37.7%, and 40.1%, respectively. Among vaccinated people, the frequencies of individuals aged 65-69.9 years were lower than the frequencies of those in the other age classes, with highest frequencies of vaccinated people in the 75-79.9 years age-class. Overall, males showed a slightly higher propensity to be vaccinated and the propensity toward vaccination increased with age in both genders. Suffering from a chronic disease increased the propensity to vaccination; hypertension had the highest impact on the propensity whereas suffering from vasculopathy has the opposite effect. The value of this study is the possibility to know the factors that might indicate a propensity to get an influenza vaccination and to consider a different approach to people ≥65 years with the characteristics indicating a lower propensity to vaccination.

Long-term survival between total colectomy versus proctocolectomy in patients with FAP: a registry-based, observational cohort study.

BACKGROUND: The best surgical choice for patients with familial adenomatous polyposis (FAP) is still debated. No prospective trials have been carried out to evaluate the pros and cons of the recommended procedures: total colectomy (ileorectal anastomosis [IRA]) vs restorative proctocolectomy (ileal pouch-anal anastomosis [IPAA]). The aim of this study was to provide a basis for tailored precision surgery in patients with FAP. METHODS: We conducted a retrospective review of patients with FAP who underwent surgery and were registered in a dedicated database in Milan, Italy. Twenty-year survival related to surgical approach and prognostic factors were investigated using a Cox regression model. RESULTS: A total of 925 patients underwent surgery between 1947 and 2015: 340 (36.8%) IPAA and 585 (63.2%) IRA. Colorectal cancer (CRC) at surgery was diagnosed in 28.6% of patients and a pathogenic APC variant was identified in 88%. During a median follow-up of 129 months, 150 patients died. The survival probability was significantly higher in the IRA than the IPAA group: 0.82 vs 0.75 (hazard ratio [HR] 0.6, 95% confidence interval [CI] 0.42-0.84). Multivariable regression modeling adjusted for propensity scores showed a similar difference, although no longer significant. Multivariable analysis indicated as independent risk factors CRC (HR 4.68, 95% CI 3.04-7.20) and age at surgery (HR 1.03, 95% CI 1.02-1.06). Among patients without cancer, the main risk factor for shorter survival was older age (HR 1.06, 95% CI 1.04-1.09). CONCLUSION: The study confirms excellent long-term results of surgical approaches with IRA and IPAA, suggesting that the best surgical choice may be an individually and clinically tailored approach, preferably at a young age.

Widen NomoGram for multinomial logistic regression: an application to staging liver fibrosis in chronic hepatitis C patients.

The interpretation of regression models results can often benefit from the generation of nomograms, 'user friendly' graphical devices especially useful for assisting the decision-making processes. However, in the case of multinomial regression models, whenever categorical responses with more than two classes are involved, nomograms cannot be drawn in the conventional way. Such a difficulty in managing and interpreting the outcome could often result in a limitation of the use of multinomial regression in decision-making support. In the present paper, we illustrate the derivation of a non-conventional nomogram for multinomial regression models, intended to overcome this issue. Although it may appear less straightforward at first sight, the proposed methodology allows an easy interpretation of the results of multinomial regression models and makes them more accessible for clinicians and general practitioners too. Development of prediction model based on multinomial logistic regression and of the pertinent graphical tool is illustrated by means of an example involving the prediction of the extent of liver fibrosis in hepatitis C patients by routinely available markers.

Adherence to antibiotic treatment guidelines and outcomes in the hospitalized elderly with different types of pneumonia.

BACKGROUND: Few studies evaluated the clinical outcomes of Community Acquired Pneumonia (CAP), Hospital-Acquired Pneumonia (HAP) and Health Care-Associated Pneumonia (HCAP) in relation to the adherence of antibiotic treatment to the guidelines of the Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) in hospitalized elderly people (65 years or older). METHODS: Data were obtained from REPOSI, a prospective registry held in 87 Italian internal medicine and geriatric wards. Patients with a diagnosis of pneumonia (ICD-9 480-487) or prescribed with an antibiotic for pneumonia as indication were selected. The empirical antibiotic regimen was defined to be adherent to guidelines if concordant with the treatment regimens recommended by IDSA/ATS for CAP, HAP, and HCAP. Outcomes were assessed by logistic regression models. RESULTS: A diagnosis of pneumonia was made in 317 patients. Only 38.8% of them received an empirical antibiotic regimen that was adherent to guidelines. However, no significant association was found between adherence to guidelines and outcomes. Having HAP, older age, and higher CIRS severity index were the main factors associated with in-hospital mortality. CONCLUSIONS: The adherence to antibiotic treatment guidelines was poor, particularly for HAP and HCAP, suggesting the need for more adherence to the optimal management of antibiotics in the elderly with pneumonia.

Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies.

The interconnected network of pathways downstream of the TGFß, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis.We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions.Starting from an initial "physiologic condition", the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model.Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal.

The In-Out dispositional affective style questionnaire (IN-OUT DASQ): an exploratory factorial analysis.

The issue of individual differences has always been an important area of research in psychology and, more recently, neuroimaging. A major source of interindividual variability stems from differences in basic affective dispositions. In order to make a contribution to this field of research, we have developed a new type of assessment - the In-Out dispositional affective style questionnaire (IN-OUT DASQ) - to measure the proneness between two different ways of feeling situated: a predominantly body-bound one in the case of the inward tendency and an externally anchored one in the case of the outward tendency (Arciero and Bondolfi, 2009). The IN-OUT DASQ contains two scales of seven items each, Self-centric engagement (SCE) and Other-centric engagement (OCE), as a disposition index for inwardness and outwardness respectively. The exploratory factor analysis in sample 1 (n = 292) confirmed a two-factor solution. Confirmatory factor analysis in sample 2 (n = 300) showed the good fit of this two-factor model. Next, we examined construct validity also investigating the correlations between the IN-OUT DASQ, the Big Five Questionnaire and the Positive and Negative Affect Schedule in sample 3 (n = 153). The SCE and OCE scales had robust internal consistency and reliability, though the capacity to discriminate higher inward and outward participants was stronger in SCE. Although further validation research is required, the present study suggests the IN-OUT DASQ has the potential to be a measurement tool for detecting individual differences in social behavior and social affective neuroscience.

Assessing Agreement between miRNA Microarray Platforms.

Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland-Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland-Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland-Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.

Ultra-sensitive troponin I levels to exclude acute myocardial infarction from myocardial injury.

BACKGROUND: Third generation troponin assays should aid in the rule-out of acute myocardial infarction (AMI). The study aim was to assess the capability of admission measurement of ultra-sensitive troponin I (TnI-Ultra) to exclude AMI from other myocardial injury. METHODS: The first TnI-Ultra sample from 856 patients at presentation to the Emergency Department and subsequent admission to the Cardiac Care Unit were considered in this case series. Myoglobin was simultaneously detected in 684 patients. RESULTS: The sensitivity of the first single TnI-Ultra level was 82.5% in overall AMI, and similar in ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), admitted, respectively at 3 and 8 h from symptoms. The diagnostic capability of a first single TnI-Ultra level was poor for both STEMI and NSTEMI to discriminate and rule-out overall AMI from myocardial injury, with an area under the receiver-operating curve of 0.65 and a negative likelihood ratio of 0.55. Adopting an optimal test threshold or adding myoglobin detection did not improve TnI-Ultra performances. CONCLUSIONS: The capability of a first single TnI-Ultra level to exclude AMI from other myocardial injury in early and late presenters is poor. Addition of myoglobin assay offered no further improvement and was not considered useful.

Prognostic value of cystatin C in acute coronary syndromes: enhancer of atherosclerosis and promising therapeutic target.

BACKGROUND: Cystatin C (CC) has been proposed to play a role in atherosclerosis. We aimed to review the prognostic value of CC serum/plasma levels in patients with acute coronary syndromes (ACS). METHODS: Fifteen observational longitudinal studies were selected by Medline. RESULTS: Increased CC over threshold values ranging from 0.93 to 1.3 mg/L were prognostic for death (hazard ratio; HR: 2.04-3.6) and for the occurrence of any fatal and non-fatal cardiovascular events (HR: 1.7-9.6) for patients with either ACS only or coronary heart disease and prevalent ACS. Only one study showed an increased risk for future myocardial infarction (MI) in patients with marker levels higher than 1.0 mg/L. Three studies reported the risk associated with a change of one unit of CC for long-term death (HR ranging from 1.9 to 6.3) and for the composite end point of 1 year MI and death (HR 2.15). Some studies showed the additional prognostic value contributed from CC measurements to other markers and to conventional risk scores. CONCLUSION: Despite low to moderate evidence, there is a general agreement on the significant prognostic value of CC in ACS that might encourage further research focused on risk assessment for patients with MI.

From multimarker approach to multiplex assays in acute coronary syndromes: what are we searching for?

In the setting of acute coronary syndrome (ACS) the enhancement of analytical performances for several biomarkers improved the understanding of complex ACS pathogenesis highlighting the potential targets of treatment. The introduction of multiplex arrays, developed on ELISA methodology, measuring simultaneously multiple proteins in one assay, allowed the chance to obtain patient multimarker profiles. Aim of this commentary is to clarify the clinical reliability and usefulness of multiplex arrays, in ACS context, referring to available recent methodological and translational research literature. We reported that a certain number of clinical studies in ACS considered these methods but provided poor evidence, since their lack of standardization. The main drawback of multiplex arrays lies in the cross-reactions between the array antibodies with the reagents of co-detected analytes and with the sample matrix proteins. This cross-reactivity rises as the increasing number of markers assayed in the same plate. We have shown that these multiplex arrays were employed to screen markers potentially involved in the disease, among a wide spectrum of proteins, without a preliminary robust biological hypothesis. The need of up-to-date biostatistical approaches is stressed. Researchers should address their efforts to build up and standardize sub-microarrays measuring a lower number of markers than multiplex one, selected on a clear link with ACS evolution.

Improving outcome prediction of systemic sclerosis from isolated Raynaud's phenomenon: role of autoantibodies and nail-fold capillaroscopy.

OBJECTIVE: A simple weighted prognostic algorithm, based on capillaroscopy and autoantibodies, is developed to classify patients at different risk of transition from isolated RP to SSc within 5 years from the screening visit. METHODS: Two hundred and eighty-eight of 768 patients with isolated RP who underwent capillaroscopy were recruited. The prognostic contributions of capillaroscopic findings (giant loops, haemorrhages and the number of capillaries) and SSc-associated autoantibodies (ACAs, anti-topo I and ANAs) were assessed in a semi-parametric regression models suitable for competing risks. A prognostic index was built by a bagging technique. A structured tree approach was used to extract simple classificatory rules that can be directly interpreted. RESULTS: Thirty-four transitions from isolated RP to SSc and 42 to other CTDs were observed. All of the chosen variables had a substantial prognostic impact. A complex non-linear prognostic pattern was observed for capillaries, with the risk of developing SSc increasing as the number of loops decreased. The presence of ANAs had a strong impact on prognosis [hazard ratio (HR) = 9.70], which was increased by the presence of ACA (HR = 3.94; P < 0.001). A weighted prognostic classification for the development of SSc was constructed using capillary number, giant loops and ANAs. The prognostic discrimination was satisfactory (Harrell's C-index = 0.86). CONCLUSION: Our prognostic model is based on easy-to-obtain features (i.e. the number of capillaries, giant loops and ANAs) and could be used to facilitate clinical decision making in the screening phase, and may also have important implications for stratifying patients into risk groups for future clinical assessment.

Impact of calibration fitting models on the clinical value of chromogranin A.

BACKGROUND: The clinical relevance of chromogranin A (CgA) concentrations depends on the analytical performance of the assay. The goal of the present study was to define the clinical involvements in CgA calibration models by evaluating the confidence intervals (CIs) for values from patients who were undergoing monitoring for disease. METHODS: Thirty calibration curves for the CgA assay [immunoradiometric assay (IRMA), (CIS-BIO)] were built using linear regression (LR), and four-parameter logistic models were used to estimate CIs for patient concentrations. RESULTS: We reported the inadequacy of the LR curve estimation procedure. We showed: 1) no evidence that the straight calibration line could fit the average responses, 2) non-constant and non-uniform variance of the replicated calibration responses. All tests performed in the analysis of variance and CI calculation for the calibration curve should be invalidated. The four-parameter logistic function yielded results for 16 curves only; this result could be due to the low number and inappropriate concentration of calibrators. This suggests that some aspects of the assay design should be reviewed. However, using the variance function estimated in this model, we could assess the CI for calibration curves and patient samples. CONCLUSIONS: We showed that the four-parameter logistic calibration model with estimated variance function should better support clinical interpretation of marker concentration changes in patients serially tested.

Artificial neural network for the joint modelling of discrete cause-specific hazards.

OBJECTIVE: Artificial neural network (ANN) based regression methods have been introduced for modelling censored survival data to account for complex prognostic patterns. In the framework of ANN extensions of generalized linear models for survival data, PLANN is a partial logistic ANN, suitable for smoothed discrete hazard estimation as a function of time and covariates. An extension of PLANN for competing risks analysis (PLANNCR) is now proposed for discrete or grouped survival times, resorting to the multinomial likelihood. METHODS AND MATERIALS: PLANNCR is built by assigning input nodes to the explanatory variables with the time interval treated as an ordinal variable. The logistic function is used as activation for the hidden nodes of the network, whereas the softmax, which corresponds to the canonical link of generalized linear models for polytomous regression, is adopted for multiple output nodes, to provide a smoothed estimation of discrete conditional event probabilities for each event. The Kullback-Leibler distance is used as error function for the target vectors, amounting to half of the deviance of a multinomial logistic regression model. PLANNCR can jointly model non-linear, non-proportional and non-additive effects on cause-specific hazards (CSHs). The degree of smoothing is modulated by the number of hidden nodes and penalization of the error function (weight decay). Model optimisation is achieved by quasi-Newton algorithms, while non-linear cross-validation (NCV) and the Network Information Criterion (NIC) were adopted for model selection. PLANNCR was applied to data on 1793 women with primary invasive breast cancer, histologically N-, who underwent surgery at the Milan Cancer Institute between 1981 and 1986. RESULTS: Differential effects of covariates and time on the shape of the CSH for the three main failure causes, namely intra-breast tumor recurrences, distant metastases and contralateral breast cancer, have been enlightened. CONCLUSIONS: PLANNCR can be suitably adopted in an exploratory framework for a thorough evaluation of the disease dynamics in the presence of competing risks.