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. 2013 Jun;196(3):492-8.
doi: 10.1016/j.tvjl.2012.11.018. Epub 2013 Feb 4.

Validation of the prognostic value of histopathological grading or c-kit mutation in canine cutaneous mast cell tumours: a retrospective cohort study

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Validation of the prognostic value of histopathological grading or c-kit mutation in canine cutaneous mast cell tumours: a retrospective cohort study

Yoshinori Takeuchi et al. Vet J. 2013 Jun.

Abstract

The objective of this retrospective cohort study was to validate the prognostic value of histological grading of canine cutaneous mast cell tumours (MCTs) according to the Patnaik (grades I-III) and Kiupel (low, high) grading systems, and to confirm the prognostic significance of internal tandem duplications (ITDs) within exon 11 of the c-kit gene (ITD-Exon11). The baseline characteristics and outcome data from 47 dogs diagnosed with cutaneous MCTs were collected and reviewed. Tumours were graded according to both grading systems and the nucleotide sequence of c-kit was evaluated. Results were analyzed to evaluate predictive factors for overall survival (OS) and progression-free survival (PFS). Log-rank tests indicated that dogs with Patnaik grade III MCTs had significantly reduced OS and PFS compared to those with either grade I or II tumours. However, no significant difference in OS or PFS was observed between grade I and II tumours. The dogs with Kiupel high-grade MCTs had significantly shorter OS and PFS than dogs with low-grade MCTs. The presence of ITD-Exon11 was significantly associated with shorter PFS. The result of Cox regression analysis showed that the Kiupel grading system for OS and PFS, and lymph node metastasis for OS, independently predicted prognosis. Kappa statistics confirmed a significantly higher inter-observer consistency for the Kiupel compared to the Patnaik grading system. These findings demonstrate that the Kiupel grading system is a useful prognostic tool for canine cutaneous MCTs in predicting OS and PFS, while the occurrence of ITD-Exon11 appeared to be a useful predictor for PFS.

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