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Dogs spontaneously develop mammary gland tumors (MGT) and exhibit striking similarities in clinical and epidemiological characteristics to human breast cancer (HBC). Descriptive and comparative analysis of HBC and canine MGT with a focus on evaluating similarities and geographical distribution were the aims of this study. HBC cases were obtained from North Regional Oncological Registry (RORENO) (2010-2015) and canine MGT cases from Vet-OncoNet (2019-2022). Analyses were performed based on published and well accepted classification systems (ICD-O-3.2 for humans and Vet-ICD-O-canine-1). Age-standardized incidence risks (ASIR) of Porto district municipalities were calculated using 2021 Portuguese census (INE) and data from the Portuguese animal registration system (SIAC). Among 7,674 HBC cases and 1,140 MGT cases, a similar age and sex distribution pattern was observed. Approximately 69.2% of HBC cases were between 40 and 69 years old, while 66.9% of MGT cases were diagnosed between 7 and 12 years old (mean age of 9.6 years, SD = 2.6). In women, Invasive breast carcinoma (8500/3) was the most common histological type (n = 5,679, 74%) while in dogs it was the Complex Carcinoma (8983.1/3) (n = 205, 39%). Cocker and Yorkshire Terriers exhibited the highest relative risks (3.2 and 1.6, p < 0.05, respectively) when compared to cross breed dogs. The municipalities' ASIR of the two species exhibited a high correlation (R = 0.85, p < 0.01) and the spatial cluster analysis revealed similar geographic hotspots. Also, higher ASIR values both in women and dogs weremore frequently found in urbanized areas compared to rural areas. This research sheds light on the shared features and geographical correlation between HBC and canine MGT, highlighting the potential of cross-species environmental oncology studies. [ABSTRACT FROM AUTHOR]

Simple Summary: The development of a widely accepted and comparable animal cancer registration system lacks standardized animal cancer coding. The GIVCS group have developed a comparative coding system for canine neoplasms—Vet-ICD-O-canine-1—compatible with the human ICD-O-3.2 and consistent with the currently recognized classification schemes for canine tumors. This system comprises 335 topography codes and 534 morphology codes allowing the collection of consistent epidemiologic canine cancer data and offering a robust framework for comparative oncology studies. 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. [ABSTRACT FROM AUTHOR]

Vet-OncoNet is a replicable tripartite animal cancer database with the scientific and academic purposes of collecting data and producing evidence-based knowledge for cancer science in general. Inspired by the One Health vision, Vet-OncoNet uses business intelligence tools to optimize the process of capturing, treating, and reporting animal cancer data to a national level in three interfaces: ACR (animal cancer registry, pathology-based), COR (clinical oncology registry, vet practice-based) and RFR (risk factor registry, owner-based). The first results show that skin and mammary gland are by far the most affected systems. Mast cell tumors and complex adenoma of the mammary gland are the most frequent histologic type in dogs, while in cats they are squamous cell carcinomas, tubular adenocarcinoma of the mammary gland and lymphomas. Regarding COR, it provides valuable information on the landscape of veterinary oncology practices, therapeutics options, outcomes and owners' drivers' adherence towards therapies, which range from 30% up to 80% upon vet practices. Furthermore, being aware of the role of animals within the family and as possible sentinels of environmental risks to cancer in humans, the network built an interface (Pet-OncoNet) dedicated to owners and a database (RFR) that receives information regarding pets and owners' daily habits. [ABSTRACT FROM AUTHOR]