Katia Pinello

Prof. Katia Pinello

ICBAS, Instituto de Ciências Biomédicas Abel Salazar, Porto, Portugal
orcid

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
31 March 2022 in Veterinary Sciences
Verified
Journal Article
Open access
PDF file
Katia PinelloKatia Pinello
Katia Pinello
Isabel PiresIsabel Pires
Isabel Pires
ACAna Filipa Castro
Ana Filipa Castro
PCPaulo Tiago Carvalho
Paulo Tiago Carvalho
ASAndreia Santos
Andreia Santos
JNJoão Niza-Ribeiro
João Niza-Ribeiro
The animal cancer burden is essential for the translational value of companion animals in comparative oncology. The present work aims to describe, analyze, and compare frequencies and associations of tumors in dogs and cats based on the Animal Cancer Registry created by Vet-OncoNet. With 9079 registries, regarding 2019 and 2020, 81% (n = 7355) belonged to dogs. In comparison, cats have a general one-year right advance in the mean age of cancer diagnosis compared to dogs. The multivariate topography group analysis shows a distinct pattern between the two species: dogs have higher odds of cancer in the genito-urinary system, spleen, soft tissue tumors and skin, while cats show higher odds for tumors in the eyes, digestive organs, nasal cavity, lymph nodes, bones and mammary glands. Regarding morphologies, dogs are overrepresented in mast cell tumors (MCT), melanomas, and hemangiosarcomas. While cats are overrepresented in fibrosarcomas, lymphomas (T and B-cell), in malignant mammary tumors, and squamous cell carcinoma (SCC). Females have greater odds only in the mammary gland, with males having greater odds in six of twelve topographies. This study is the first outcome of continuous animal cancer registration studies in Portugal.

28 September 2022 in Veterinary Sciences
Verified
Journal Article
Open access
PDF file
Katia PinelloKatia Pinello
Katia Pinello
IAIrina Amorim
Irina Amorim
Isabel PiresIsabel Pires
Isabel Pires
ACAna Canadas-Sousa
Ana Canadas-Sousa
JCJosé Catarino
José Catarino
JNJoão Niza-Ribeiro
João Niza-Ribeiro
Analysis of canine and feline tumor malignancy data can help clinicians identify high-risk patients and make more accurate decisions. Based on a sample of 16,272 cancer records, including 3266 cats and 13,006 dogs, collected from January 2019 to December 2021 in the Vet-OncoNet Network database, this study aimed to compare the tumor malignancy profile between cats and dogs, considering animal-related factors (sex, age, and breed), topography, and geographic location using a mixed-effects logistic regression model. Cats had a higher proportion of malignant tumors (78.7%) than dogs (46.2%), and the malignancy profile was very different regarding tumors’ topographies. The mean age of malignant tumors occurred eight months later than benign ones (9.1, SD = 3.4; 9.8, SD = 3.2), in general. Species (OR = 3.96, 95%CI 3.57: 4.39) and topography (MOR = 4.10) were the two most important determinants of malignancy risk. Female dogs had a higher risk than male dogs (OR = 1.19, 95%CI 1.08: 1.31), which does not appear to be the case in cats (OR = 0.98, 95%CI 0.77: 1.23). Breed contributed significantly to differences in malignancy risk in dogs (MOR = 1.56), particularly in pit bulls and boxers. District of residence was not so relevant in predicting malignancy risk (MOR = 1.14). In both species, the risk of malignancy increased by approximately 20% every three years. It could be hypothesized that species differences in genetic structure may contribute to tumor malignancy.

16 March 2022 in Cancers
Verified
Journal Article
Open access
PDF file
Katia PinelloKatia Pinello
Katia Pinello
VBValeria Baldassarre
Valeria Baldassarre
Katja SteigerKatja Steiger
Katja Steiger
Orlando PacielloOrlando Paciello
Orlando Paciello
Isabel PiresIsabel Pires
Isabel Pires
MDMaria Dagli
Maria Dagli
Cancer registries are fundamental tools for collecting epidemiological cancer data and developing cancer prevention and control strategies. While cancer registration is common in the human medical field, many attempts to develop animal cancer registries have been launched over time, but most have been discontinued. A pivotal aspect of cancer registration is the availability of cancer coding systems, as provided by the International Classification of Diseases for Oncology (ICD-O). Within the Global Initiative for Veterinary Cancer Surveillance (GIVCS), established to foster and coordinate animal cancer registration worldwide, a group of veterinary pathologists and epidemiologists developed a comparative coding system for canine neoplasms. Vet-ICD-O-canine-1 is compatible with the human ICD-O-3.2 and is consistent with the currently recognized classification schemes for canine tumors. It comprises 335 topography codes and 534 morphology codes. The same code as in ICD-O-3.2 was used for the majority of canine tumors showing a high level of similarity to their human counterparts (n = 408). De novo codes (n = 152) were created for specific canine tumor entities (n = 126) and topographic sites (n = 26). The Vet-ICD-O-canine-1 coding system represents a user-friendly, easily accessible, and comprehensive resource for developing a canine cancer registration system that will enable studies within the One Health space.

1 March 2019 in The Veterinary Journal
Verified
Journal Article
Closed access
Katia PinelloKatia Pinello
Katia Pinello
JNJoão Niza-Ribeiro
João Niza-Ribeiro
LFL. Fonseca
L. Fonseca
AMA.J. de Matos
A.J. de Matos

1 January 2009 in Experimental and Toxicologic Pathology
Verified
Journal Article
Closed access
MNMarcia Kazumi Nagamine
Marcia Kazumi Nagamine
TSTereza Cristina da Silva
Tereza Cristina da Silva
PMPatrícia Matsuzaki
Patrícia Matsuzaki
Katia PinelloKatia Pinello
Katia Pinello
BCBruno Cogliati
Bruno Cogliati
MDMaria Dagli
Maria Dagli

12 February 2020 in Veterinary and Comparative Oncology
Verified
Journal Article
Closed access
PDF file
Katia PinelloKatia Pinello
Katia Pinello
FQFelisbina Luisa Pereira Guedes Queiroga
Felisbina Luisa Pereira Guedes Queiroga
AMAugusto Matos
Augusto Matos
ASAndreia Santos
Andreia Santos
JRJoão Niza Ribeiro
João Niza Ribeiro
MDMaria Dagli
Maria Dagli