{"title":"口腔鳞状细胞癌转移风险的临床-组织病理学预测模型的建立。","authors":"S V Sowmya, Roopa S Rao, Kavitha Prasad","doi":"10.4103/jcar.JCar_16_19","DOIUrl":null,"url":null,"abstract":"<p><strong>Context: </strong>Oral cancer metastasis is the leading cause of death globally. The decision-making on the mode of surgical treatment in clinically negative lymph nodes is challenging.</p><p><strong>Aim: </strong>The aim of this study was to develop a predictive model using clinical and histopathologic parameters that may help in the assessment of the metastatic risk of oral squamous cell carcinoma (OSCC).</p><p><strong>Settings and design: </strong>Clinical data of histopathologically confirmed primary OSCC from 2014 to 2017 were retrieved from the archives. Histopathological parameters for metastasis that were considered for evaluation in the study were tumor buds, cytoplasmic pseudofragments, tumor grade, depth of invasion, invasive tumor front (ITF) pattern, and lymphovascular invasion (LVI).</p><p><strong>Methods: </strong>Hematoxylin and eosin and pan-cytokeratin immunostained sections of metastatic and nonmetastatic OSCC were assessed for histopathological features and correlated with clinical parameters.</p><p><strong>Statistical analysis used: </strong>SPSS software (Statistical Package for Social Sciences for Windows, Version 22.0 (2013) (IBM Corp., Armonk, NY, USA)) was used for the statistical analysis. Pearson's Chi-square test was done to assess the grades of histopathological and clinical parameters between the study groups. Univariate analysis was performed to develop a clinicopathologic predictive model.</p><p><strong>Results: </strong>The clinicopathologic model signifies that OSCC with clinical Stage IV, high grades of tumor buds and cytoplasmic pseudofragments, Type V ITF pattern, positive LVI, deeply invasive tumors, and poorly differentiated grades of OSCC have a high risk of developing nodal metastasis. These parameters may be used as early predictors for metastasis of OSCC both in incisional and excisional biopsy specimens.</p><p><strong>Conclusions: </strong>The proposed predictive model is simple, cost-effective, and user-friendly for the early assessment of nodal metastatic risk in clinically negative lymph nodes.</p>","PeriodicalId":52464,"journal":{"name":"Journal of Carcinogenesis","volume":"19 ","pages":"2"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363157/pdf/","citationCount":"10","resultStr":"{\"title\":\"Development of clinico-histopathological predictive model for the assessment of metastatic risk of oral squamous cell carcinoma.\",\"authors\":\"S V Sowmya, Roopa S Rao, Kavitha Prasad\",\"doi\":\"10.4103/jcar.JCar_16_19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Context: </strong>Oral cancer metastasis is the leading cause of death globally. The decision-making on the mode of surgical treatment in clinically negative lymph nodes is challenging.</p><p><strong>Aim: </strong>The aim of this study was to develop a predictive model using clinical and histopathologic parameters that may help in the assessment of the metastatic risk of oral squamous cell carcinoma (OSCC).</p><p><strong>Settings and design: </strong>Clinical data of histopathologically confirmed primary OSCC from 2014 to 2017 were retrieved from the archives. Histopathological parameters for metastasis that were considered for evaluation in the study were tumor buds, cytoplasmic pseudofragments, tumor grade, depth of invasion, invasive tumor front (ITF) pattern, and lymphovascular invasion (LVI).</p><p><strong>Methods: </strong>Hematoxylin and eosin and pan-cytokeratin immunostained sections of metastatic and nonmetastatic OSCC were assessed for histopathological features and correlated with clinical parameters.</p><p><strong>Statistical analysis used: </strong>SPSS software (Statistical Package for Social Sciences for Windows, Version 22.0 (2013) (IBM Corp., Armonk, NY, USA)) was used for the statistical analysis. Pearson's Chi-square test was done to assess the grades of histopathological and clinical parameters between the study groups. Univariate analysis was performed to develop a clinicopathologic predictive model.</p><p><strong>Results: </strong>The clinicopathologic model signifies that OSCC with clinical Stage IV, high grades of tumor buds and cytoplasmic pseudofragments, Type V ITF pattern, positive LVI, deeply invasive tumors, and poorly differentiated grades of OSCC have a high risk of developing nodal metastasis. These parameters may be used as early predictors for metastasis of OSCC both in incisional and excisional biopsy specimens.</p><p><strong>Conclusions: </strong>The proposed predictive model is simple, cost-effective, and user-friendly for the early assessment of nodal metastatic risk in clinically negative lymph nodes.</p>\",\"PeriodicalId\":52464,\"journal\":{\"name\":\"Journal of Carcinogenesis\",\"volume\":\"19 \",\"pages\":\"2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363157/pdf/\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Carcinogenesis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4103/jcar.JCar_16_19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Carcinogenesis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/jcar.JCar_16_19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 10
摘要
背景:口腔癌转移是全球死亡的主要原因。临床阴性淋巴结的手术治疗模式的决策具有挑战性。目的:本研究的目的是建立一个使用临床和组织病理学参数的预测模型，这可能有助于评估口腔鳞状细胞癌(OSCC)的转移风险。设置和设计:从档案中检索2014 - 2017年经组织病理学证实的原发性OSCC的临床资料。研究中评估转移的组织病理学参数包括肿瘤芽、细胞质假片段、肿瘤分级、浸润深度、浸润性肿瘤前缘(ITF)模式和淋巴血管浸润(LVI)。方法:对转移性和非转移性OSCC进行苏木精、伊红和泛细胞角蛋白免疫染色切片，评估其组织病理学特征并与临床参数相关。统计分析使用SPSS软件(Statistical Package for Social Sciences for Windows, Version 22.0 (2013) (IBM Corp.， Armonk, NY, USA))进行统计分析。采用皮尔逊卡方检验评估各组间组织病理学和临床参数的分级。采用单因素分析建立临床病理预测模型。结果:临床病理模型提示临床分期为ⅳ期、高级别肿瘤芽和细胞质假片段、V型ITF模式、LVI阳性、肿瘤深度浸润、低分化级别的OSCC发生淋巴结转移的风险较高。这些参数可作为OSCC在切口和切除活检标本中转移的早期预测指标。结论:提出的预测模型简单、经济、用户友好，可用于早期评估临床阴性淋巴结的淋巴结转移风险。
Development of clinico-histopathological predictive model for the assessment of metastatic risk of oral squamous cell carcinoma.
Context: Oral cancer metastasis is the leading cause of death globally. The decision-making on the mode of surgical treatment in clinically negative lymph nodes is challenging.
Aim: The aim of this study was to develop a predictive model using clinical and histopathologic parameters that may help in the assessment of the metastatic risk of oral squamous cell carcinoma (OSCC).
Settings and design: Clinical data of histopathologically confirmed primary OSCC from 2014 to 2017 were retrieved from the archives. Histopathological parameters for metastasis that were considered for evaluation in the study were tumor buds, cytoplasmic pseudofragments, tumor grade, depth of invasion, invasive tumor front (ITF) pattern, and lymphovascular invasion (LVI).
Methods: Hematoxylin and eosin and pan-cytokeratin immunostained sections of metastatic and nonmetastatic OSCC were assessed for histopathological features and correlated with clinical parameters.
Statistical analysis used: SPSS software (Statistical Package for Social Sciences for Windows, Version 22.0 (2013) (IBM Corp., Armonk, NY, USA)) was used for the statistical analysis. Pearson's Chi-square test was done to assess the grades of histopathological and clinical parameters between the study groups. Univariate analysis was performed to develop a clinicopathologic predictive model.
Results: The clinicopathologic model signifies that OSCC with clinical Stage IV, high grades of tumor buds and cytoplasmic pseudofragments, Type V ITF pattern, positive LVI, deeply invasive tumors, and poorly differentiated grades of OSCC have a high risk of developing nodal metastasis. These parameters may be used as early predictors for metastasis of OSCC both in incisional and excisional biopsy specimens.
Conclusions: The proposed predictive model is simple, cost-effective, and user-friendly for the early assessment of nodal metastatic risk in clinically negative lymph nodes.
期刊介绍：
Journal of Carcinogenesis considers manuscripts in many areas of carcinogenesis and Chemoprevention. Primary areas of interest to the journal include: physical and chemical carcinogenesis and mutagenesis; processes influencing or modulating carcinogenesis, such as DNA repair; genetics, nutrition, and metabolism of carcinogens; the mechanism of action of carcinogens and modulating agents; epidemiological studies; and, the formation, detection, identification, and quantification of environmental carcinogens. Manuscripts that contribute to the understanding of cancer prevention are especially encouraged for submission
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