Biomedical subjects

Rodolfo Cotichini

Publications and source records attributed to Rodolfo Cotichini.

5 recordsLinked to original sources

PubMed2004

Prevalence of hepatitis C virus infection in lymphoproliferative diseases other than B-cell non-Hodgkin's lymphoma, and in myeloproliferative diseases: an Italian Multi-Center case-control study.

BACKGROUND AND OBJECTIVES: Infection with hepatitis C virus (HCV) is associated with type II mixed cryoglobulinemia (MC), a lymphoproliferative disorder which, in some patients, evolves into overt B-cell non-Hodgkin's lymphoma (B-NHL). Recently, also the association between HCV infection and B-NHL, which had long been controversial, was confirmed in a large case-control study. Little knowledge is, however, available on possible associations between HCV infection and other lymphoid or myeloid malignancies. The present study was set up in order to investigate this aspect. DESIGN AND METHODS: The study was conducted in hematology departments of ten hospitals in different Italian cities. The cases consisted of consecutive patients with a new diagnosis of T-NHL, Hodgkin's disease (HD), chronic lymphocytic leukemia (CLL), acute lymphoblastic leukemia (ALL), multiple myeloma (MM), acute myeloid leukemia (AML), and chronic myeloid leukemia (CML). The controls were patients in other departments of the same hospitals. HCV infection was investigated by testing for HCV antibodies and HCV-RNA in serum samples. RESULTS: The prevalence of HCV infection was not higher in patients with HD (3.2%, 5 out of 157 cases) or MM (4.7%, 5 out of 107) than in controls. On the other hand, it was consistently higher in T-NHL (13.8%, 4 out of 30), CLL (9.0%, 9 out of 100), ALL (7.6%, 5 out of 54), AML (7.9%, 11 out of 140), and CML (12.2%, 6 out of 49) patients. These patient groups were not, however, large enough to render statistically significant results. INTERPRETATION AND CONCLUSIONS: Our data suggest that HCV infection may be associated not only with B-NHL but also with some other lymphoid and myeloid malignancies.

Acute Disease↗

PubMed2003

Impact of large regenerative, low grade and high grade dysplastic nodules in hepatocellular carcinoma development.

BACKGROUND/AIMS: The natural outcome of ultrasound-detected macronodules in cirrhosis is still poorly understood. In this study we assessed the incidence and predictors of malignant transformation in a prospective study of 90 consecutive ultrasound-detected macronodules in cirrhosis. METHODS: Macronodules classification was based on recently proposed histological criteria. Extranodular large (LCC) and small cell changes were also evaluated. The follow-up included ultrasound and serum alfa-fetoprotein determination every 3 months. Independent predictors of hepatocellular carcinoma were evaluated by Cox proportional hazards regression analysis. RESULTS: During a mean follow-up of 33 months, 28 (31%) nodules transformed into hepatocellular carcinoma. The incidence of hepatocellular carcinoma per 100 person-years of follow-up was 11.3%, with a malignant transformation rate of 3.5, 15.5, 31 and 48.5% at 1, 2, 3, and 5 years respectively. High-grade dysplastic nodules (HGDN) (hazard risk=2.4; CI 95%=1.1-5.0) and LCC (hazard risk=3.1; CI 95%=1.2-7.8) were independent predictors of malignant transformation. Eight additional hepatocellular carcinomas developed outside the original lesions raising the overall malignant transformation rate to 40% while 15 macronodules (17%) became undetectable at ultrasound (US). CONCLUSIONS: Macronodules characterize a cirrhotic subpopulation with high risk of hepatocellular carcinoma. HGDN and LCC are strong predictors of malignant transformation; subjects with simultaneous presence of both these two conditions are at highest risk of cancer development. The management of cirrhotics with macronodules should be based on morphologic features detected on liver microsamples.

Adult↗

PubMed2002

The Italian Twin Project: from the personal identification number to a national twin registry.

The unique opportunity given by the "fiscal code", an alphanumeric identification with demographic information on any single person residing in Italy, introduced in 1976 by the Ministry of Finance, allowed a database of all potential Italian twins to be created. This database contains up to now name, surname, date and place of birth and home address of about 1,300,000 "possible twins". Even though we estimated an excess of 40% of pseudo-twins, this still is the world's largest twin population ever collected. The database of possible twins is currently used in population-based studies on multiple sclerosis, Alzheimer's disease, celiac disease, and type 1 diabetes. A system is currently being developed for linking the database with data from mortality and cancer registries. In 2001, the Italian Government, through the Ministry of Health, financed a broad national research program on twin studies, including the establishment of a national twin registry. Among all the possible twins, a sample of 500,000 individuals are going to be contacted and we expect to enrol around 120,000 real twin pairs in a formal Twin Registry. According to available financial resources, a sub sample of the enrolled population will be asked to donate DNA. A biological bank from twins will be then implemented, guaranteeing information on future etiological questions regarding genetic and modifiable factors for physical impairment and disability, cancers, cardiovascular diseases and other age related chronic illnesses.

Aging↗

PubMedDate not supplied

[Twins in biomedical research and the creation of the "National Twin Registry"].

Twins are a valuable resource for the study of complex traits. The twin method is substantially based on the comparison between correlations and concordance in monozygotic (MZ) and dizygotic (DZ) twins and allows several applications in biomedical and molecular genetic research. It allows either the qualitative and quantitative evaluation of the influences that genetic and environmental factors exert on phenotypes or the estimation of trait variability. Moreover, classical genetic linkage analysis is more powerful if performed in DZ twins. However, the twin method has some pitfalls, such as the necessity that collected samples be representative of both twin and general population. For this reason, over the last few years, a number of Countries have established population-based twin registers, which guarantee the maximum level of representation and, consequently, are of extreme value for epidemiological studies. Italy is also implementing a national twin register. The following is the description of the procedure that led to the establishment of the Italian Twin Registry.

Databases, Factual↗

PubMedDate not supplied

[Regression methods and causal inference: structural equations models].

The estimate of correlations among observed outcomes is crucial in biomedical research, especially when the aim of the study is to infer, from the magnitude of these correlations, the causal influence of certain, sometimes latent, factors. In such situations, a typical regression approach, known as "structural equation models" (SEM), which was introduced in the 1970s, becomes significant. These models allow hypotheses to be formulated quite clearly, thanks to some explicit and rigorous graphical representations, on which the "path analysis" is based. SEM, which were initially used in economics, have in the past decade been applied in a wide variety of fields, especially in genetic epidemiology. It's in this field that SEM are extraordinarily effective, representing a simple yet powerful means of estimating the contribution of genes and the environment to the phenotypic expression of a given disease. To this end, data on twins are particularly useful, and in this case the correlation between the outcomes describes the extent of similarity of the twin phenotypes. From this standpoint, SEM undoubtedly constitute one of the most promising statistical tools for family studies and quantitative genetic research. The method can be easily extended to traditional epidemiology, and some interesting applications have already been developed in occupational and social epidemiology. In this paper, we describe in detail the SEM approach and discuss the use of these models in genetic epidemiology, using twin studies as an example. We also discuss the application of SEM in fields other than genetic research.

Causality↗