RESUMO
Background: To determine if mitotic activity played a role in classifying breast cancer in terms of its biological behaviour. We investigated the prospect of identifying a more meaningful cell proliferation marker for categorising treatment-naive breast cancer. Methods: The 150 cases diagnosed as invasive breast carcinoma in the histopathology section were systematically studied for the clinical, gross, and microscopic features. Results: the 50% patients were grade 2 (75), 41% were grade 3 (71) and 9% (14) were grade 1 in present study. The distribution of intrinsic subtypes was luminal A 25% (38), luminal B 59% (88), HER2 enriched 10% (15), basal 6% (9). Out of 150 cases, 29% (43) cases were T1, T2 were 65% (97), T3 were 2% (4), T4 were 4% (6). Mean Ki 67 was 15.6±8.8 in grade 1, 23.3±15.4 and 38.2± in grade 3. There was significant difference between I and III, and II and III (p<0.05). Mean mitotic count in grade 1 was 5.4±2.7, in grade 2 it was 9.7±13.5, in grade 3 it was 16.1±6.9. There was significant difference between grade 1 and 2, grade 2 and 3, grade 1 and 3 (p<0.05). There was significant difference between T stages (p<0.05). Conclusions: Ki 67 showed a more significant statistical correlation with prognostic factors as compared to mitotic count; we feel Ki 67 is more superior to mitotic count as a prognostic factor.
RESUMO
Background: To determine if mitotic activity played a role in classifying breast cancer in terms of its biological behaviour. We investigated the prospect of identifying a more meaningful cell proliferation marker for categorising treatment-naive breast cancer. Methods: The 150 cases diagnosed as invasive breast carcinoma in the histopathology section were systematically studied for the clinical, gross, and microscopic features. Results: the 50% patients were grade 2 (75), 41% were grade 3 (71) and 9% (14) were grade 1 in present study. The distribution of intrinsic subtypes was luminal A 25% (38), luminal B 59% (88), HER2 enriched 10% (15), basal 6% (9). Out of 150 cases, 29% (43) cases were T1, T2 were 65% (97), T3 were 2% (4), T4 were 4% (6). Mean Ki 67 was 15.6±8.8 in grade 1, 23.3±15.4 and 38.2± in grade 3. There was significant difference between I and III, and II and III (p<0.05). Mean mitotic count in grade 1 was 5.4±2.7, in grade 2 it was 9.7±13.5, in grade 3 it was 16.1±6.9. There was significant difference between grade 1 and 2, grade 2 and 3, grade 1 and 3 (p<0.05). There was significant difference between T stages (p<0.05). Conclusions: Ki 67 showed a more significant statistical correlation with prognostic factors as compared to mitotic count; we feel Ki 67 is more superior to mitotic count as a prognostic factor.
RESUMO
Context: A total of 350 million individuals are affected by chronic hepatitis B virus infection world-wide. Historically, liver biopsy has been instrumental in adequately assessing patients with chronic liver disease. A number of non-invasive models have been studied world-wide. Aim: The aim of this study is to assess the utility of non-invasive mathematical models of liver fi brosis in chronic hepatitis B (CHB). Indian patients in a resource limited setting using routinely performed non-invasive laboratory investigations. Settings and Design: A cross-sectional study carried out at a tertiary care center. Subjects and Methods: A total of 52 consecutive chronic liver disease patients who underwent percutaneous liver biopsy and 25 healthy controls were enrolled in the study. Routine laboratory investigations included serum aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Gama glutamyl transpeptidase (GGT), total bilirubin, total cholesterol, prothrombin time and platelet count. Three non-invasive models for namely aspartate aminotransferase to platelet ratio index (APRI), Fibrosis 4 (FIB-4) and Forn’s index were calculated. Outcomes were compared for the assessment of best predictor of fi brosis by calculating the sensitivity, specifi city, positive predictive value (PPV) and negative predictive value (NPV) of each index. Statistical Analysis Used: Medcalc online software and by Microsoft Excel Worksheet. Chi-square test was used for signifi cance. P value < 0.05 was taken as signifi cant. Results: While the serum levels of AST, ALT and GGT were signifi cantly higher in patients group as compare with the healthy controls (P < 0.01), the platelet counts were signifi cantly lower in patient group as compared to the control group (P < 0.01). Mean value of all 3 indices were signifi cantly higher in patients group as compare with the controls (P < 0.01). Conclusions: Out of the three indices, APRI index with a NPV of 95% appeared to be a better model for excluding signifi cant liver fi brosis while FIB-4 with a PPV of 61% showed fair correlation with signifi cant fi brosis. Thus, these two non-invasive models for predicting of liver fi brosis, namely APRI and FIB-4, can be utilized in combination as screening tools in monitoring of CHB patients, especially in resource limiting settings.