{"title":"The association between pain and WHO grade of pancreatic neuroendocrine neoplasms: A multicenter study.","authors":"Cheng Wang, Tingting Lin, Xin Chen, Wenjing Cui, Chuangen Guo, Zhongqiu Wang, Xiao Chen","doi":"10.3233/CBM-220080","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Abdominal or back pain is a common symptom in pancreatic diseases. However, the role of pain in pancreatic neuroendocrine neoplasm (PNENs) has not been clarified.</p><p><strong>Objective: </strong>In this study, we aimed to show the association between the pain and the grade of PNENs.</p><p><strong>Methods: </strong>A total of 186 patients with pathologically confirmed PNENs were included in this study. Clinical features and histological or radiological findings (size, location, and vascular invasion and local organs invasion and distal metastasis) were collected. Logistic regression analyses were used to show the association between pain and grade of PNENs. Nomogram was developed based on associated factors to predict the higher grade of PNENs. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of size and nomogram model.</p><p><strong>Results: </strong>The prevalence of pain in the cohort was 30.6% (n= 57). The vascular invasion and G3 PNENs were more common in the pain group (P= 0.02, P< 0.01). The tumor size was larger and incident of higher grade of PNENs was higher in the pain group than the non-pain group (p< 0.01). Age, pain and size were independent risk factors for G2/G3 or G3 PNENs. The odds ratio was 3.03 (95% CI: 1.67-7.91) and 3.32 (95% CI: 1.42-7.79) for pain, respectively. The nomogram model was developed to predict the G2/G3 or G3 PNENs. The area under the curve (AUC) of the nomogram model was 0.84 (95% CI, 0.77-0.91) in predicting the G2/G3 PNENs, and was 0.84 (95% CI, 0.78-0.91) in predicting the G3 PNENs.</p><p><strong>Conclusion: </strong>Abdominal or back pain is associated with the grade of PNENs. The nomograms based on clinical features may be a powerful numerical tool for predicting the grade of PNENs.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"36 4","pages":"279-286"},"PeriodicalIF":2.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Biomarkers","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3233/CBM-220080","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Abdominal or back pain is a common symptom in pancreatic diseases. However, the role of pain in pancreatic neuroendocrine neoplasm (PNENs) has not been clarified.
Objective: In this study, we aimed to show the association between the pain and the grade of PNENs.
Methods: A total of 186 patients with pathologically confirmed PNENs were included in this study. Clinical features and histological or radiological findings (size, location, and vascular invasion and local organs invasion and distal metastasis) were collected. Logistic regression analyses were used to show the association between pain and grade of PNENs. Nomogram was developed based on associated factors to predict the higher grade of PNENs. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of size and nomogram model.
Results: The prevalence of pain in the cohort was 30.6% (n= 57). The vascular invasion and G3 PNENs were more common in the pain group (P= 0.02, P< 0.01). The tumor size was larger and incident of higher grade of PNENs was higher in the pain group than the non-pain group (p< 0.01). Age, pain and size were independent risk factors for G2/G3 or G3 PNENs. The odds ratio was 3.03 (95% CI: 1.67-7.91) and 3.32 (95% CI: 1.42-7.79) for pain, respectively. The nomogram model was developed to predict the G2/G3 or G3 PNENs. The area under the curve (AUC) of the nomogram model was 0.84 (95% CI, 0.77-0.91) in predicting the G2/G3 PNENs, and was 0.84 (95% CI, 0.78-0.91) in predicting the G3 PNENs.
Conclusion: Abdominal or back pain is associated with the grade of PNENs. The nomograms based on clinical features may be a powerful numerical tool for predicting the grade of PNENs.
Flavia B. Garcez MD, Marlon J. R. Aliberti MD, PhD, Paula C. E. Poco MD, Marcel Hiratsuka MD, Silvia de F. Takahashi MD, Venceslau A. Coelho MD, Danute B. Salotto MD, Marlos L. V. Moreira MD, Wilson Jacob-Filho MD, PhD, Thiago J. Avelino-Silva MD, PhD
期刊介绍:
Concentrating on molecular biomarkers in cancer research, Cancer Biomarkers publishes original research findings (and reviews solicited by the editor) on the subject of the identification of markers associated with the disease processes whether or not they are an integral part of the pathological lesion.
The disease markers may include, but are not limited to, genomic, epigenomic, proteomics, cellular and morphologic, and genetic factors predisposing to the disease or indicating the occurrence of the disease. Manuscripts on these factors or biomarkers, either in altered forms, abnormal concentrations or with abnormal tissue distribution leading to disease causation will be accepted.