Identifying SCC Lesions Capable of Spontaneous Regression by Using Immunohistochemistry: A Systematic Review and Meta-Analysis.

IF 2.5 4区 医学 Q2 DERMATOLOGY
Maryam Hedayati, Behzad Garousi, Zahrasadat Rezaei, Yasaman Nazerian, Younes Yassaghi, Arian Tavasol, Dorsa Bahrami Zanjanbar, Sanaz Sharifpour, Amir Golestani, Mansoor Bolideei, Farajolah Maleki
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Abstract

Introduction: Keratoacanthoma (KA) and squamous cell carcinoma (SCC) are two cutaneous conditions with morphological resemblance, which can complicate the diagnosis in some cases. Using immunohistochemistry staining of biomarkers could be beneficial in resolving this obstacle.

Objectives: We investigated a variety of biomarkers assessed in different studies in order to find the most important and helpful biomarkers for differentiation between SCC and lesions capable of spontaneous regression.

Methods: MEDLINE via PubMed and Google Scholar database were used to identify relevant literature up to 15 June 2022. The aim of our analyses was to determine the capability of biomarkers to distinguish between SCC and lesions capable of spontaneous regression using calculated individual and pooled odds ratios (OR) and 95% confidence intervals (CI) and I2 tests.

Results: Six potential biomarkers were CD10 with pooled OR= 0.006 (95% CI: 0.001-0.057) and I2=0%; COX-2 with pooled OR=0.089 (95% CI: 0.029-0.269) and I2=17.1%; elastic fibers with pooled OR= 6.69 (95% CI: 2.928-15.281) and I2=0%; IMP-3 with pooled OR=0.145 (95% CI: 0.021-1.001) and I2=44.5%; P53 with pooled OR=0.371 (95% CI: 0.188-0.733) and I2=55.9%; AT1R with OR=0.026 (95% CI: 0.006-0.107).

Conclusions: We suggest the utilization of the following IHC biomarkers for discrimination between lesions with spontaneous regression such as KA and SCC: CD10, COX-2, and elastic fibers.

通过免疫组化鉴定可自发消退的 SCC 病变:系统回顾与元分析》。
导言:角化棘皮瘤(KA)和鳞状细胞癌(SCC)是两种形态相似的皮肤病,在某些情况下会使诊断复杂化。使用免疫组化染色生物标志物可能有助于解决这一障碍:我们对不同研究中评估的各种生物标志物进行了调查,以找到最重要、最有助于区分 SCC 和能够自发消退的病变的生物标志物:通过 PubMed 和 Google Scholar 数据库的 MEDLINE 查找截至 2022 年 6 月 15 日的相关文献。我们的分析目的是通过计算个体和汇总的几率比(OR)、95%置信区间(CI)和I2检验,确定生物标志物区分SCC和能够自发消退的病变的能力:六个潜在的生物标志物分别为:CD10,集合 OR= 0.006 (95% CI: 0.001-0.057) ,I2=0%;COX-2,集合 OR= 0.089 (95% CI: 0.029-0.269) ,I2=17.1%;弹性纤维,集合 OR= 6.69 (95% CI: 2.928-15.281),I2=0%;IMP-3,汇总OR=0.145(95% CI:0.021-1.001),I2=44.5%;P53,汇总OR=0.371(95% CI:0.188-0.733),I2=55.9%;AT1R,OR=0.026(95% CI:0.006-0.107):我们建议利用以下 IHC 生物标记物来区分自发消退的病变(如 KA 和 SCC):CD10、COX-2 和弹性纤维。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
0.00%
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217
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