Authors:
Işıl Aytemiz Danyer Ministry of Agriculture and Forestry, Ankara, Türkiye
Department of Pathology, Veterinary Faculty, University of Istanbul-Cerrahpasa, 34500 Büyükçekmece, Istanbul, Türkiye

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Aydın Gürel Department of Pathology, Veterinary Faculty, University of Istanbul-Cerrahpasa, 34500 Büyükçekmece, Istanbul, Türkiye

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Abstract

Canine cutaneous mast cell tumours (CCMCTs) are common in dogs and exhibit many unpredictable behaviors. This study aimed to encourage pathology laboratories in developing countries to routinely assess prognosis by applying commonly used histopathological grading systems and immunohistochemistry (IHC) markers. We performed histological grading according to both the Patnaik and Kiupel systems, determined the mitotic count (MC) and carried out IHC for the detection of Ki67, Bax, Bcl-2 and KIT in 54 CCMCT cases. MC was associated with both grading systems in terms of survival following diagnosis and prognostic factors differed among cases categorized by the cut-off value of 5. KIT patterns were associated with grading systems and MC. The cohort with pattern II had a lower survival rate than those with patterns I and III. Ki67 was associated with survival when evaluated over the cut-off value of 0.018. Bax expression was associated with both grading systems. Median survival time was longer in patients with lower Bax expression level. Immunohistochemical detection of KIT, Ki67 and Bax improves histopathology in predicting the prognosis. If IHC is unavailable, reports regarding MC and values from both grading systems are the most effective, convenient and cost-effective way to provide the most reliable prognostic data and guidance for the clinicians.

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Editor-in-Chief: Ferenc BASKA

Editorial assistant: Szilvia PÁLINKÁS

 

Editorial Board

  • Mária BENKŐ (Acta Veterinaria Hungarica, Budapest, Hungary)
  • Gábor BODÓ (University of Veterinary Medicine, Budapest, Hungary)
  • Béla DÉNES (University of Veterinary Medicine, Budapest Hungary)
  • Edit ESZTERBAUER (Veterinary Medical Research Institute, Budapest, Hungary)
  • Hedvig FÉBEL (National Agricultural Innovation Centre, Herceghalom, Hungary)
  • László FODOR (University of Veterinary Medicine, Budapest, Hungary)
  • János GÁL (University of Veterinary Medicine, Budapest, Hungary)
  • Balázs HARRACH (Veterinary Medical Research Institute, Budapest, Hungary)
  • Peter MASSÁNYI (Slovak University of Agriculture in Nitra, Nitra, Slovak Republic)
  • Béla NAGY (Veterinary Medical Research Institute, Budapest, Hungary)
  • Tibor NÉMETH (University of Veterinary Medicine, Budapest, Hungary)
  • Zsuzsanna NEOGRÁDY (University of Veterinary Medicine, Budapest, Hungary)
  • Dušan PALIĆ (Ludwig Maximilian University, Munich, Germany)
  • Alessandra PELAGALLI (University of Naples Federico II, Naples, Italy)
  • Kurt PFISTER (Ludwig-Maximilians-University of Munich, Munich, Germany)
  • László SOLTI (University of Veterinary Medicine, Budapest, Hungary)
  • József SZABÓ (University of Veterinary Medicine, Budapest, Hungary)
  • Péter VAJDOVICH (University of Veterinary Medicine, Budapest, Hungary)
  • János VARGA (University of Veterinary Medicine, Budapest, Hungary)
  • Štefan VILČEK (University of Veterinary Medicine in Kosice, Kosice, Slovak Republic)
  • Károly VÖRÖS (University of Veterinary Medicine, Budapest, Hungary)
  • Herbert WEISSENBÖCK (University of Veterinary Medicine, Vienna, Austria)
  • Attila ZSARNOVSZKY (Szent István University, Gödöllő, Hungary)

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2022  
Web of Science  
Total Cites
WoS
972
Journal Impact Factor 0.900
Rank by Impact Factor

Veterinary Sciences 95/143

Impact Factor
without
Journal Self Cites
0.900
5 Year
Impact Factor
1.1
Journal Citation Indicator 0.47
Rank by Journal Citation Indicator

Veterinary Sciences 103/170

Scimago  
Scimago
H-index
38
Scimago
Journal Rank
0.277
Scimago Quartile Score

Veterinary (miscellaneous) Q2

Scopus  
Scopus
Cite Score
1.9
Scopus
CIte Score Rank
General Veterinary 76/186 (59th PCTL)
Scopus
SNIP
0.475

2021  
Web of Science  
Total Cites
WoS
1040
Journal Impact Factor 0,959
Rank by Impact Factor Veterinary Sciences 103/144
Impact Factor
without
Journal Self Cites
0,876
5 Year
Impact Factor
1,222
Journal Citation Indicator 0,48
Rank by Journal Citation Indicator Veterinary Sciences 106/168
Scimago  
Scimago
H-index
36
Scimago
Journal Rank
0,313
Scimago Quartile Score Veterinary (miscellaneous) (Q2)
Scopus  
Scopus
Cite Score
1,7
Scopus
CIte Score Rank
General Veterinary 79/183 (Q2)
Scopus
SNIP
0,610

2020  
Total Cites 987
WoS
Journal
Impact Factor
0,955
Rank by Veterinary Sciences 101/146 (Q3)
Impact Factor  
Impact Factor 0,920
without
Journal Self Cites
5 Year 1,164
Impact Factor
Journal  0,57
Citation Indicator  
Rank by Journal  Veterinary Sciences 93/166 (Q3)
Citation Indicator   
Citable 49
Items
Total 49
Articles
Total 0
Reviews
Scimago 33
H-index
Scimago 0,395
Journal Rank
Scimago Veterinary (miscellaneous) Q2
Quartile Score  
Scopus 355/217=1,6
Scite Score  
Scopus General Veterinary 73/183 (Q2)
Scite Score Rank  
Scopus 0,565
SNIP  
Days from  145
submission  
to acceptance  
Days from  150
acceptance  
to publication  
Acceptance 19%
Rate

 

2019  
Total Cites
WoS
798
Impact Factor 0,991
Impact Factor
without
Journal Self Cites
0,897
5 Year
Impact Factor
1,092
Immediacy
Index
0,119
Citable
Items
59
Total
Articles
59
Total
Reviews
0
Cited
Half-Life
9,1
Citing
Half-Life
9,2
Eigenfactor
Score
0,00080
Article Influence
Score
0,253
% Articles
in
Citable Items
100,00
Normalized
Eigenfactor
0,09791
Average
IF
Percentile
42,606
Scimago
H-index
32
Scimago
Journal Rank
0,372
Scopus
Scite Score
335/213=1,6
Scopus
Scite Score Rank
General Veterinary 62/178 (Q2)
Scopus
SNIP
0,634
Acceptance
Rate
18%

 

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Acta Veterinaria Hungarica
Language English
Size A4
Year of
Foundation
1951
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia
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Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
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Address
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Publisher
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ISSN 0236-6290 (Print)
ISSN 1588-2705 (Online)

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