23 results on '"Dalla Riva, Giulio V"'
Search Results
2. Analysing ecological networks of species interactions.
- Author
-
Delmas, Eva, Besson, Mathilde, Brice, Marie-Hélène, Burkle, Laura A, Dalla Riva, Giulio V, Fortin, Marie-Josée, Gravel, Dominique, Guimarães, Paulo R, Hembry, David H, Newman, Erica A, Olesen, Jens M, Pires, Mathias M, Yeakel, Justin D, and Poisot, Timothée
- Subjects
biogeography ,community ecology ,ecological networks ,graph theory ,interactions ,Evolutionary Biology ,Biological Sciences - Abstract
Network approaches to ecological questions have been increasingly used, particularly in recent decades. The abstraction of ecological systems - such as communities - through networks of interactions between their components indeed provides a way to summarize this information with single objects. The methodological framework derived from graph theory also provides numerous approaches and measures to analyze these objects and can offer new perspectives on established ecological theories as well as tools to address new challenges. However, prior to using these methods to test ecological hypotheses, it is necessary that we understand, adapt, and use them in ways that both allow us to deliver their full potential and account for their limitations. Here, we attempt to increase the accessibility of network approaches by providing a review of the tools that have been developed so far, with - what we believe to be - their appropriate uses and potential limitations. This is not an exhaustive review of all methods and metrics, but rather, an overview of tools that are robust, informative, and ecologically sound. After providing a brief presentation of species interaction networks and how to build them in order to summarize ecological information of different types, we then classify methods and metrics by the types of ecological questions that they can be used to answer from global to local scales, including methods for hypothesis testing and future perspectives. Specifically, we show how the organization of species interactions in a community yields different network structures (e.g., more or less dense, modular or nested), how different measures can be used to describe and quantify these emerging structures, and how to compare communities based on these differences in structures. Within networks, we illustrate metrics that can be used to describe and compare the functional and dynamic roles of species based on their position in the network and the organization of their interactions as well as associated new methods to test the significance of these results. Lastly, we describe potential fruitful avenues for new methodological developments to address novel ecological questions.
- Published
- 2018
3. Graph embedding and transfer learning can help predict potential species interaction networks despite data limitations.
- Author
-
Strydom, Tanya, Bouskila, Salomé, Banville, Francis, Barros, Ceres, Caron, Dominique, Farrell, Maxwell J., Fortin, Marie‐Josée, Mercier, Benjamin, Pollock, Laura J., Runghen, Rogini, Dalla Riva, Giulio V., and Poisot, Timothée
- Subjects
SPECIES pools ,SPECIES - Abstract
Metawebs (networks of potential interactions within a species pool) are a powerful abstraction to understand how large‐scale species interaction networks are structured.Because metawebs are typically expressed at large spatial and taxonomic scales, assembling them is a tedious and costly process; predictive methods can help circumvent the limitations in data deficiencies, by providing a first approximation of metawebs.One way to improve our ability to predict metawebs is to maximize available information by using graph embeddings, as opposed to an exhaustive list of species interactions. Graph embedding is an emerging field in machine learning that holds great potential for ecological problems.Here, we outline how the challenges associated with inferring metawebs line‐up with the advantages of graph embeddings; followed by a discussion as to how the choice of the species pool has consequences on the reconstructed network, specifically as to the role of human‐made (or arbitrarily assigned) boundaries and how these may influence ecological hypotheses. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
4. Exploiting node metadata to predict interactions in bipartite networks using graph embedding and neural networks
- Author
-
Runghen, Rogini, primary, Stouffer, Daniel B., additional, and Dalla Riva, Giulio V., additional
- Published
- 2022
- Full Text
- View/download PDF
5. Food web reconstruction through phylogenetic transfer of low‐rank network representation
- Author
-
Strydom, Tanya, primary, Bouskila, Salomé, additional, Banville, Francis, additional, Barros, Ceres, additional, Caron, Dominique, additional, Farrell, Maxwell J., additional, Fortin, Marie‐Josée, additional, Hemming, Victoria, additional, Mercier, Benjamin, additional, Pollock, Laura J., additional, Runghen, Rogini, additional, Dalla Riva, Giulio V., additional, and Poisot, Timothée, additional
- Published
- 2022
- Full Text
- View/download PDF
6. Supplementary Information from Exploiting node metadata to predict interactions in bipartite networks using graph embedding and neural networks
- Author
-
Runghen, Rogini, Stouffer, Daniel B., and Dalla Riva, Giulio V.
- Abstract
Networks are increasingly used in various fields to represent systems with the aim of understanding the underlying rules governing observed interactions, and hence predict how the system is likely to behave in the future. Recent developments in network science highlight that accounting for node metadata improves both our understanding of how nodes interact with one another, and the accuracy of link prediction. However, to predict interactions in a network within existing statistical and machine learning frameworks, we need to learn objects that rapidly grow in dimension with the number of nodes. Thus, the task becomes computationally and conceptually challenging for networks. Here, we present a new predictive procedure combining a statistical, low-rank graph embedding method with machine learning techniques which reduces substantially the complexity of the learning task and allows us to efficiently predict interactions from node metadata in bipartite networks. To illustrate its application on real-world data, we apply it to a large dataset of tourist visits across a country. We found that our procedure accurately reconstructs existing interactions and predicts new interactions in the network. Overall, both from a network science and data science perspective, our work offers a flexible and generalizable procedure for link prediction.
- Published
- 2022
- Full Text
- View/download PDF
7. Epidemiological trends and trajectories of MAFLD-associated hepatocellular carcinoma 2002–2033: the ITA.LI.CA database
- Author
-
Vitale, Alessandro, primary, Svegliati-Baroni, Gianluca, additional, Ortolani, Alessio, additional, Cucco, Monica, additional, Dalla Riva, Giulio V, additional, Giannini, Edoardo G, additional, Piscaglia, Fabio, additional, Rapaccini, Gianludovico, additional, Di Marco, Mariella, additional, Caturelli, Eugenio, additional, Zoli, Marco, additional, Sacco, Rodolfo, additional, Cabibbo, Giuseppe, additional, Marra, Fabio, additional, Mega, Andrea, additional, Morisco, Filomena, additional, Gasbarrini, Antonio, additional, Foschi, Francesco Giuseppe, additional, Missale, Gabriele, additional, Masotto, Alberto, additional, Nardone, Gerardo, additional, Raimondo, Giovanni, additional, Azzaroli, Francesco, additional, Vidili, Gianpaolo, additional, Oliveri, Filippo, additional, Pelizzaro, Filippo, additional, Ramirez Morales, Rafael, additional, Cillo, Umberto, additional, Trevisani, Franco, additional, Miele, Luca, additional, Marchesini, Giulio, additional, and Farinati, Fabio, additional
- Published
- 2021
- Full Text
- View/download PDF
8. Exploring the evolutionary signature of food websʼ backbones using functional traits
- Author
-
Dalla Riva, Giulio V. and Stouffer, Daniel B.
- Published
- 2016
- Full Text
- View/download PDF
9. The dimensionality of plant–plant competition
- Author
-
Stouffer, Daniel B., primary, Godoy, Oscar, additional, Dalla Riva, Giulio V., additional, and Mayfield, Margaret M., additional
- Published
- 2021
- Full Text
- View/download PDF
10. Exploiting node metadata to predict interactions in large networks using graph embedding and neural networks
- Author
-
Runghen, Rogini, primary, Stouffer, Daniel B, additional, and Dalla Riva, Giulio V, additional
- Published
- 2021
- Full Text
- View/download PDF
11. SVD Entropy Reveals the High Complexity of Ecological Networks
- Author
-
Strydom, Tanya, primary, Dalla Riva, Giulio V., additional, and Poisot, Timothée, additional
- Published
- 2021
- Full Text
- View/download PDF
12. Epidemiological trends and trajectories of MAFLD-associated hepatocellular carcinoma 2002-2033: the ITA.LI.CA database
- Author
-
Vitale, Alessandro, Svegliati-Baroni, Gianluca, Ortolani, Alessio, Cucco, Monica, Dalla Riva, Giulio V, Giannini, Edoardo G, Piscaglia, Fabio, Rapaccini, Gianludovico, Di Marco, Mariella, Caturelli, Eugenio, Zoli, Marco, Sacco, Rodolfo, Cabibbo, Giuseppe, Marra, Fabio, Mega, Andrea, Morisco, Filomena, Gasbarrini, Antonio, Foschi, Francesco Giuseppe, Missale, Gabriele, Masotto, Alberto, Nardone, Gerardo, Raimondo, Giovanni, Azzaroli, Francesco, Vidili, Gianpaolo, Oliveri, Filippo, Pelizzaro, Filippo, Ramirez Morales, Rafael, Cillo, Umberto, Trevisani, Franco, Miele, Luca, Marchesini, Giulio, Farinati, Fabio, Gasbarrini, Antonio (ORCID:0000-0002-7278-4823), Miele, Luca (ORCID:0000-0003-3464-0068), Vitale, Alessandro, Svegliati-Baroni, Gianluca, Ortolani, Alessio, Cucco, Monica, Dalla Riva, Giulio V, Giannini, Edoardo G, Piscaglia, Fabio, Rapaccini, Gianludovico, Di Marco, Mariella, Caturelli, Eugenio, Zoli, Marco, Sacco, Rodolfo, Cabibbo, Giuseppe, Marra, Fabio, Mega, Andrea, Morisco, Filomena, Gasbarrini, Antonio, Foschi, Francesco Giuseppe, Missale, Gabriele, Masotto, Alberto, Nardone, Gerardo, Raimondo, Giovanni, Azzaroli, Francesco, Vidili, Gianpaolo, Oliveri, Filippo, Pelizzaro, Filippo, Ramirez Morales, Rafael, Cillo, Umberto, Trevisani, Franco, Miele, Luca, Marchesini, Giulio, Farinati, Fabio, Gasbarrini, Antonio (ORCID:0000-0002-7278-4823), and Miele, Luca (ORCID:0000-0003-3464-0068)
- Abstract
Background Metabolic dysfunction-associated fatty liver disease (MAFLD) represents a new inclusive definition of the whole spectrum of liver diseases associated to metabolic disorders. The main objective of this study was to compare patients with MAFLD and non-MAFLD with hepatocellular carcinoma (HCC) included in a nationally representative cohort. Methods We analysed 6882 consecutive patients with HCC enrolled from 2002 to 2019 by 23 Italian Liver Cancer centres to compare epidemiological and future trends in three subgroups: pure, single aetiology MAFLD (S-MAFLD); mixed aetiology MAFLD (metabolic and others, M-MAFLD); and non-MAFLD HCC. Results MAFLD was diagnosed in the majority of patients with HCC (68.4%). The proportion of both total MAFLD and S-MAFLD HCC significantly increased over time (from 50.4% and 3.6% in 2002-2003, to 77.3% and 28.9% in 2018-2019, respectively, p<0.001). In Italy S-MAFLD HCC is expected to overcome M-MAFLD HCC in about 6 years. Patients with S-MAFLD HCC were older, more frequently men and less frequently cirrhotic with clinically relevant portal hypertension and a surveillance-related diagnosis. They had more frequently large tumours and extrahepatic metastases. After weighting, and compared with patients with non-MAFLD, S-MAFLD and M-MAFLD HCC showed a significantly lower overall (p=0.026, p=0.004) and HCC-related (p<0.001, for both) risk of death. Patients with S-MAFLD HCC showed a significantly higher risk of non-HCC-related death (p=0.006). Conclusions The prevalence of MAFLD HCC in Italy is rapidly increasing to cover the majority of patients with HCC. Despite a less favourable cancer stage at diagnosis, patients with MAFLD HCC have a lower risk of HCC-related death, suggesting reduced cancer aggressiveness.
- Published
- 2021
13. Epidemiological trends and trajectories of MAFLD-associated hepatocellular carcinoma 2002–2033: the ITA.LI.CA database
- Author
-
Vitale, Alessandro, Svegliati-Baroni, Gianluca, Ortolani, Alessio, Cucco, Monica, Dalla Riva, Giulio V, Giannini, Edoardo G, Piscaglia, Fabio, Rapaccini, Gianludovico, Di Marco, Mariella, Caturelli, Eugenio, Zoli, Marco, Sacco, Rodolfo, Cabibbo, Giuseppe, Marra, Fabio, Mega, Andrea, Morisco, Filomena, Gasbarrini, Antonio, Foschi, Francesco Giuseppe, Missale, Gabriele, Masotto, Alberto, Nardone, Gerardo, Raimondo, Giovanni, Azzaroli, Francesco, Vidili, Gianpaolo, Oliveri, Filippo, Pelizzaro, Filippo, Ramirez Morales, Rafael, Cillo, Umberto, Trevisani, Franco, Miele, Luca, Marchesini, Giulio, and Farinati, Fabio
- Abstract
BackgroundMetabolic dysfunction-associated fatty liver disease (MAFLD) represents a new inclusive definition of the whole spectrum of liver diseases associated to metabolic disorders. The main objective of this study was to compare patients with MAFLD and non-MAFLD with hepatocellular carcinoma (HCC) included in a nationally representative cohort.MethodsWe analysed 6882 consecutive patients with HCC enrolled from 2002 to 2019 by 23 Italian Liver Cancer centres to compare epidemiological and future trends in three subgroups: pure, single aetiology MAFLD (S-MAFLD); mixed aetiology MAFLD (metabolic and others, M-MAFLD); and non-MAFLD HCC.ResultsMAFLD was diagnosed in the majority of patients with HCC (68.4%). The proportion of both total MAFLD and S-MAFLD HCC significantly increased over time (from 50.4% and 3.6% in 2002–2003, to 77.3% and 28.9% in 2018–2019, respectively, p<0.001). In Italy S-MAFLD HCC is expected to overcome M-MAFLD HCC in about 6 years. Patients with S-MAFLD HCC were older, more frequently men and less frequently cirrhotic with clinically relevant portal hypertension and a surveillance-related diagnosis. They had more frequently large tumours and extrahepatic metastases. After weighting, and compared with patients with non-MAFLD, S-MAFLD and M-MAFLD HCC showed a significantly lower overall (p=0.026, p=0.004) and HCC-related (p<0.001, for both) risk of death. Patients with S-MAFLD HCC showed a significantly higher risk of non-HCC-related death (p=0.006).ConclusionsThe prevalence of MAFLD HCC in Italy is rapidly increasing to cover the majority of patients with HCC. Despite a less favourable cancer stage at diagnosis, patients with MAFLD HCC have a lower risk of HCC-related death, suggesting reduced cancer aggressiveness.
- Published
- 2023
- Full Text
- View/download PDF
14. Related plants tend to share pollinators and herbivores, but strength of phylogenetic signal varies among plant families
- Author
-
Cirtwill, Alyssa R., Dalla Riva, Giulio V., Baker, Nick J., Ohlsson, Mikael, Norstrom, Isabelle, Wohlfarth, Inger-Marie, Thia, Joshua A., Stouffer, Daniel B., Cirtwill, Alyssa R., Dalla Riva, Giulio V., Baker, Nick J., Ohlsson, Mikael, Norstrom, Isabelle, Wohlfarth, Inger-Marie, Thia, Joshua A., and Stouffer, Daniel B.
- Abstract
Related plants are often hypothesized to interact with similar sets of pollinators and herbivores, but this idea has only mixed empirical support. This may be because plant families vary in their tendency to share interaction partners. We quantify overlap of interaction partners for all pairs of plants in 59 pollination and 11 herbivory networks based on the numbers of shared and unshared interaction partners (thereby capturing both proportional and absolute overlap). We test for relationships between phylogenetic distance and partner overlap within each network; whether these relationships varied with the composition of the plant community; and whether well-represented plant families showed different relationships. Across all networks, more closely related plants tended to have greater overlap. The strength of this relationship within a network was unrelated to the composition of the networks plant component, but, when considered separately, different plant families showed different relationships between phylogenetic distance and overlap of interaction partners. The variety of relationships between phylogenetic distance and partner overlap in different plant families probably reflects a comparable variety of ecological and evolutionary processes. Considering factors affecting particular species-rich groups within a community could be the key to understanding the distribution of interactions at the network level., Funding Agencies|NSERC PGS-D graduate scholarship; Marsden Fund Fast-Start grantRoyal Society of New ZealandMarsden Fund (NZ) [UOC-1101]; Rutherford Discovery Fellowship
- Published
- 2020
- Full Text
- View/download PDF
15. Solid Organ Transplantation During COVID-19 Pandemic: An International Web-based Survey on Resources’ Allocation
- Author
-
Giovinazzo, Francesco, primary, Avolio, Alfonso W., additional, Galiandro, Federica, additional, Vitale, Alessandro, additional, Dalla Riva, Giulio V., additional, Biancofiore, Gianni, additional, Sharma, Shivani, additional, Muiesan, Paolo, additional, Agnes, Salvatore, additional, and Burra, Patrizia, additional
- Published
- 2021
- Full Text
- View/download PDF
16. Related plants tend to share pollinators and herbivores, but strength of phylogenetic signal varies among plant families
- Author
-
Cirtwill, Alyssa R., primary, Dalla Riva, Giulio V., additional, Baker, Nick J., additional, Ohlsson, Mikael, additional, Norström, Isabelle, additional, Wohlfarth, Inger‐Marie, additional, Thia, Joshua A., additional, and Stouffer, Daniel B., additional
- Published
- 2020
- Full Text
- View/download PDF
17. Unmasking structural patterns in incidence matrices: an application to ecological data
- Author
-
Bramon Mora, Bernat, primary, Dalla Riva, Giulio V., additional, and Stouffer, Daniel B., additional
- Published
- 2019
- Full Text
- View/download PDF
18. Building sustainable health data capability in Aotearoa New Zealand : opportunities and challenges highlighted through COVID-19
- Author
-
Dalla Riva, Giulio Valentino
- Published
- 2024
19. A review of species role concepts in food webs
- Author
-
Cirtwill, Alyssa, Dalla Riva, Giulio V., Gaiarsa, Marilia P., Bimler, Malyon D., Cagua, E. Fernando, Coux, Camille, Dehling, D. Matthias, Cirtwill, Alyssa, Dalla Riva, Giulio V., Gaiarsa, Marilia P., Bimler, Malyon D., Cagua, E. Fernando, Coux, Camille, and Dehling, D. Matthias
- Abstract
Many different concepts have been used to describe species' roles in food webs (i.e., the ways in which species participate in their communities as consumers and resources). As each concept focuses on a different aspect of food-web structure, it can be difficult to relate these concepts to each other and to other aspects of ecology. Here we use the Eltonian niche as an overarching framework, within which we summarize several commonly-used role concepts (degree, trophic level, motif roles, and centrality). We focus mainly on the topological versions of these concepts but, where dynamical versions of a role concept exist, we acknowledge these as well. Our aim is to highlight areas of overlap and ambiguity between different role concepts and to describe how these roles can be used to group species according to different strategies (i.e., equivalence and functional roles). The existence of “gray areas” between role concepts make it essential for authors to carefully consider both which role concept(s) are most appropriate for the analyses they wish to conduct and what aspect of species' niches (if any) they wish to address. The ecological meaning of differences between species' roles can change dramatically depending on which role concept(s) are used.
- Published
- 2018
- Full Text
- View/download PDF
20. Analyzing ecological networks of species interactions
- Author
-
Delmas, Eva, primary, Besson, Mathilde, additional, Brice, Marie-Hélène, additional, Burkle, Laura A., additional, Dalla Riva, Giulio V., additional, Fortin, Marie-Josée, additional, Gravel, Dominique, additional, Guimarães, Paulo R, additional, Hembry, David, additional, Newman, Erica, additional, Olesen, Jens M., additional, Pires, Mathias M., additional, Yeakel, Justin D., additional, and Poisot, Timothée, additional
- Published
- 2017
- Full Text
- View/download PDF
21. Analysing ecological networks of species interactions.
- Author
-
Delmas, Eva, Besson, Mathilde, Brice, Marie‐Hélène, Burkle, Laura A., Dalla Riva, Giulio V., Fortin, Marie‐Josée, Gravel, Dominique, Guimarães, Paulo R., Hembry, David H., Newman, Erica A., Olesen, Jens M., Pires, Mathias M., Yeakel, Justin D., and Poisot, Timothée
- Subjects
GRAPH theory ,INTERACTION (Philosophy) ,BIOGEOGRAPHY ,BIOTIC communities ,ECOSYSTEMS - Abstract
Network approaches to ecological questions have been increasingly used, particularly in recent decades. The abstraction of ecological systems – such as communities – through networks of interactions between their components indeed provides a way to summarize this information with single objects. The methodological framework derived from graph theory also provides numerous approaches and measures to analyze these objects and can offer new perspectives on established ecological theories as well as tools to address new challenges. However, prior to using these methods to test ecological hypotheses, it is necessary that we understand, adapt, and use them in ways that both allow us to deliver their full potential and account for their limitations. Here, we attempt to increase the accessibility of network approaches by providing a review of the tools that have been developed so far, with – what we believe to be – their appropriate uses and potential limitations. This is not an exhaustive review of all methods and metrics, but rather, an overview of tools that are robust, informative, and ecologically sound. After providing a brief presentation of species interaction networks and how to build them in order to summarize ecological information of different types, we then classify methods and metrics by the types of ecological questions that they can be used to answer from global to local scales, including methods for hypothesis testing and future perspectives. Specifically, we show how the organization of species interactions in a community yields different network structures (e.g., more or less dense, modular or nested), how different measures can be used to describe and quantify these emerging structures, and how to compare communities based on these differences in structures. Within networks, we illustrate metrics that can be used to describe and compare the functional and dynamic roles of species based on their position in the network and the organization of their interactions as well as associated new methods to test the significance of these results. Lastly, we describe potential fruitful avenues for new methodological developments to address novel ecological questions. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
22. Exploring the evolutionary signature of food webs' backbones using functional traits
- Author
-
Dalla Riva, Giulio V., primary and Stouffer, Daniel B., additional
- Published
- 2015
- Full Text
- View/download PDF
23. Epidemiological trends and trajectories of MAFLD-associated hepatocellular carcinoma 2002-2033: The ITA.LI.CA database
- Author
-
Alessandro, Vitale, Gianluca, Svegliati-Baroni, Alessio, Ortolani, Monica, Cucco, Giulio V, Dalla Riva, Edoardo G, Giannini, Fabio, Piscaglia, Gianludovico, Rapaccini, Mariella, Di Marco, Eugenio, Caturelli, Marco, Zoli, Rodolfo, Sacco, Giuseppe, Cabibbo, Fabio, Marra, Andrea, Mega, Filomena, Morisco, Antonio, Gasbarrini, Francesco Giuseppe, Foschi, Gabriele, Missale, Alberto, Masotto, Gerardo, Nardone, Giovanni, Raimondo, Francesco, Azzaroli, Gianpaolo, Vidili, Filippo, Oliveri, Filippo, Pelizzaro, Rafael, Ramirez Morales, Umberto, Cillo, Franco, Trevisani, Luca, Miele, Giulio, Marchesini, Fabio, Farinati, Alessandro, Di Bucchianico, Vitale, A., Svegliati-Baroni, G., Ortolani, A., Cucco, M., Dalla Riva, G. V., Giannini, E. G., Piscaglia, F., Rapaccini, G., Di Marco, M., Caturelli, E., Zoli, M., Sacco, R., Cabibbo, G., Marra, F., Mega, A., Morisco, F., Gasbarrini, A., Foschi, F. G., Missale, G., Masotto, A., Nardone, G., Raimondo, G., Azzaroli, F., Vidili, G., Oliveri, F., Pelizzaro, F., Ramirez Morales, R., Cillo, U., Trevisani, F., Miele, L., Marchesini, G., Farinati, F., Alessandro Vitale, Gianluca Svegliati-Baroni, Alessio Ortolani, Monica Cucco, Giulio V Dalla Riva, Edoardo G Giannini, Fabio Piscaglia, Gianludovico Rapaccini, Mariella Di Marco, Eugenio Caturelli, Marco Zoli, Rodolfo Sacco, Giuseppe Cabibbo, Fabio Marra, Andrea Mega, Filomena Morisco, Antonio Gasbarrini, Francesco Giuseppe Foschi, Gabriele Missale, Alberto Masotto, Gerardo Nardone, Giovanni Raimondo, Francesco Azzaroli, Gianpaolo Vidili, Filippo Oliveri, Filippo Pelizzaro, Rafael Ramirez Morales, Umberto Cillo, Franco Trevisani, Luca Miele, Giulio Marchesini, Fabio Farinati, Vitale, Alessandro, Svegliati-Baroni, Gianluca, Ortolani, Alessio, Cucco, Monica, Dalla Riva, Giulio V, Giannini, Edoardo G, Piscaglia, Fabio, Rapaccini, Gianludovico, Di Marco, Mariella, Caturelli, Eugenio, Zoli, Marco, Sacco, Rodolfo, Cabibbo, Giuseppe, Marra, Fabio, Mega, Andrea, Morisco, Filomena, Gasbarrini, Antonio, Foschi, Francesco Giuseppe, Missale, Gabriele, Masotto, Alberto, Nardone, Gerardo, Raimondo, Giovanni, Azzaroli, Francesco, Vidili, Gianpaolo, Oliveri, Filippo, Pelizzaro, Filippo, Ramirez Morales, Rafael, Cillo, Umberto, Trevisani, Franco, Miele, Luca, Marchesini, Giulio, and Farinati, Fabio
- Subjects
Male ,Settore MED/12 - Gastroenterologia ,Carcinoma, Hepatocellular ,Liver Neoplasms ,nonalcoholic steatohepatitis ,Gastroenterology ,hepatocellular carcinoma ,digestive system diseases ,Non-alcoholic Fatty Liver Disease ,Risk Factors ,Humans ,neoplasms - Abstract
BackgroundMetabolic dysfunction-associated fatty liver disease (MAFLD) represents a new inclusive definition of the whole spectrum of liver diseases associated to metabolic disorders. The main objective of this study was to compare patients with MAFLD and non-MAFLD with hepatocellular carcinoma (HCC) included in a nationally representative cohort.MethodsWe analysed 6882 consecutive patients with HCC enrolled from 2002 to 2019 by 23 Italian Liver Cancer centres to compare epidemiological and future trends in three subgroups: pure, single aetiology MAFLD (S-MAFLD); mixed aetiology MAFLD (metabolic and others, M-MAFLD); and non-MAFLD HCC.ResultsMAFLD was diagnosed in the majority of patients with HCC (68.4%). The proportion of both total MAFLD and S-MAFLD HCC significantly increased over time (from 50.4% and 3.6% in 2002–2003, to 77.3% and 28.9% in 2018–2019, respectively, pConclusionsThe prevalence of MAFLD HCC in Italy is rapidly increasing to cover the majority of patients with HCC. Despite a less favourable cancer stage at diagnosis, patients with MAFLD HCC have a lower risk of HCC-related death, suggesting reduced cancer aggressiveness.
- Published
- 2021
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.