Evidence map›Paper›PMID 41681401›Full record

ArticleAnimals : an open access journal from MDPI2026

Preoperative Clinical Predictors of Histologic Malignancy and Carcinoma Grade in 286 Canine Mammary Nodules from 92 Bitches: A Retrospective Study.

Manuel Fuertes-Recuero, Paula García San José, Guillermo Valdivia, María Suarez-Redondo, Silvia Penelo, Mario Arenillas, Laura Camacho-Alonso, Laura Peña, Dolores Pérez-Alenza, Gustavo Ortiz-Díez

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Manuel Fuertes-RecueroComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0003-0736-8791
Paula García San JoséComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0001-8531-9069
Guillermo ValdiviaComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0002-6969-1597
María Suarez-RedondoComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0001-8689-2713
Silvia PeneloComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0001-9199-7341
Mario ArenillasComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0002-3315-7931
Laura Camacho-AlonsoComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.
Laura PeñaComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0001-7135-6280
Dolores Pérez-AlenzaComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0002-0426-0083
Gustavo Ortiz-DíezComplutense Veterinary Teaching Hospital, Complutense University of Madrid, Avda. Puerta de Hierro s/n, 28040 Madrid, Spain.ORCID 0000-0002-8242-2658

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Canine mammary tumours often present as multiple synchronous nodules, necessitating decisions regarding staging intensity and surgical planning prior to histology. We developed two preoperative nodule-level prediction models using only the medical history and physical examination of client-owned bitches with mammary disease, which were staged using the WHO-modified TNM system with a M0 classification (no distant metastasis) at the time of presentation. This retrospective study analysed 286 surgically excised mammary nodules from 92 dogs managed under a standardised mammary oncology protocol; those with inflammatory mammary carcinoma or distant metastasis were excluded. The outcomes were (i) malignant versus benign/non-neoplastic histology (for all nodules) and (ii) intermediate/high histologic grade (II-III versus I) among carcinomas. Separate multivariable Firth penalised logistic regression models accounted for within-dog clustering with dog-level bootstrap internal validation. Multiple imputation was used in a sensitivity analysis for missingness in the detection-to-surgery interval. Malignancy was confirmed in 87/286 (30.4%) of the nodules (86 carcinomas), including 35/87 (40.2%) that measured less than 1 cm. Among complete cases (153 nodules), malignancy was associated with age at neutering, maximum tumour diameter, owner-reported rapid growth and a detection-to-surgery interval of more than 3.5 months (an exploratory ROC-derived threshold) with good discrimination (area under the curve (AUC) 0.805; optimism-corrected 0.799) and acceptable calibration. Among carcinomas (83 specimen), previous mammary tumours, bloody nipple discharge and fewer synchronous nodules were associated with intermediate/high malignancy grade (AUC 0.859). Sensitivity analyses yielded directionally consistent estimates. Routinely available clinical information may provide interpretable preoperative risk stratification to support staging and surgical planning, pending external validation.

Indexed as

canine mammary tumoursclustered datafirth logistic regressionhistological gradehistological malignancyprediction modelpreoperative clinical predictors

Identifiers

PMID41681401
PMCPMC12896456

What Socratic holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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 Socratic graph.