ArticleScientific data2021
A text-mining based analysis of 100,000 tumours affecting dogs and cats in the United Kingdom.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Spontaneous tumors in dogs and cats in Algeria: a dual-source descriptive study of practitioner-reported patterns and histopathology-submitted cases.BMC veterinary research · 2026Article
- Article
- Development and implementation of a data parsing protocol for companion animal cancer data.Veterinary pathology · 2026Article
- Epidemiology of Four Major Canine Tumours in the UK: Insights From a National Pathology Registry With Comparative Oncology Perspectives.Veterinary and comparative oncology · 2026Article
- Distribution of neoplasia in Danish cats: data from the Danish Veterinary Cancer Registry.Journal of feline medicine and surgery · 2026Article
- The epidemiological landscape of canine tumors in central Italy: animal cancer registry insights, distribution patterns, and incidence estimates.Frontiers in veterinary science · 2026Article
- Retrospective Analysis of Prevalence of Tumors in Dogs and Cats in Lithuania.Veterinary sciences · 2025Article
- Text mining for disease surveillance in veterinary clinical data: part one, the language of veterinary clinical records and searching for words.Frontiers in veterinary science · 2024Article
- Epidemiology of canine mammary tumours on the Canary Archipelago in Spain.BMC veterinary research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 2 countries.
Funding
Abstract
Cancer is a major reason for veterinary consultation, especially in companion animals. Cancer surveillance plays a key role in prevention but opportunities for such surveillance in companion animals are limited by the lack of suitable veterinary population health infrastructures. In this paper we describe a pathology-based animal tumour registry (PTR) developed within the Small Animal Veterinary Surveillance Network (SAVSNET) built from electronic pathology records (EPR) submitted to this network. From an original collection of 180232 free text (non-structured) EPRs reported between April 2018 and June 2019, we used specific text-mining methodologies to identify 109895 neoplasias. These data were normalized to describe both the tumour (type and location) and the animal (breed, neutering status and veterinary practice postcode). The resulting PTR, the largest of its kind for companion animals to date, is an important research resource being able to facilitate a wide array of research in areas including surveillance, clinical decision making and comparative cancer biology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.