Title |
The role of P16ink4a and P53 immunostaining in predicting recurrence of HG-CIN after conization treatment
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Published in |
Revista do Colégio Brasileiro de Cirurgiões, February 2016
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DOI | 10.1590/0100-69912016001008 |
Pubmed ID | |
Authors |
Fernanda Villar Fonseca, Flávio Daniel S. Tomasich, Juliana Elizabeth Jung, Carlos Afonso Maestri, Newton Sérgio de Carvalho |
Abstract |
Io evaluate the expression of p16INK4a and p53 biomarkers in conization specimens from patients with high grade cervical intraepithelial neoplasia (HG-CIN), correlating them with the ability to predict the recurrence. we conducted a retrospective study of patients with HG-CIN in cervical biopsy treated with conization between January 1999 and January 2006 who had a minimum follow-up of 18 months. The expression of the p16 and p53 was assessed by tissue microarrays and correlated with disease recurrence. For analysis, we used the test of proportions (chi-square), considering value p<0.05, 95% CI and calculations of sensitivity, specificity and accuracy of these immunomarkers in predicting recurrence. the series comprised 83 patients aged between 16 and 86 years (35±11.7), divided into two groups: 30 with HG-CIN recurrence (study group) and 53 without recurrence (control group). Mean age, parity, smoking and conization technique were similar in both groups. The p53 expression was present in 43% of the study group and 57% of the control group, and the p16 was present in 43% of the study group and in 57% of the control group (p>0.05). p53 had a positive predictive value (PPV) of 42% and negative predictive value (NPV) of 73%, sensitivity 70%, specificity of 47% and accuracy of 59%. The p16, PPV 42%, NPV 72%, sensitivity 66%, specificity of 49% and accuracy of 56%. immunohistochemistry expression of p53 and p16 showed low sensitivity and low specificity as predictors of HG-CIN recurrence after conization treatment. |
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Geographical breakdown
Country | Count | As % |
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Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Doctoral Student | 2 | 14% |
Student > Bachelor | 1 | 7% |
Student > Ph. D. Student | 1 | 7% |
Student > Master | 1 | 7% |
Researcher | 1 | 7% |
Other | 1 | 7% |
Unknown | 7 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 4 | 29% |
Immunology and Microbiology | 1 | 7% |
Biochemistry, Genetics and Molecular Biology | 1 | 7% |
Unknown | 8 | 57% |