Affiliations: [a] Shanghai Institute of Medical Imaging, Shanghai, China | [b] Department of Radiology, Zhongshan Hospital, Shanghai Medical College Fudan University, Shanghai, China | [c] Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China | [d] Department of Radiology, Shanghai Sixth People’s Hospital, Shanghai Jiaotong University, Shanghai, China | [e] Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
Correspondence:
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Corresponding authors: Zhongqiu Wang and Xiao Chen, Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China. E-mails: [email protected] or [email protected] and
Note: [1] Cheng Wang, Tingting Lin and Xin Chen contributed equally to this work.
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.
Keywords: Pancreatic neuroendocrine neoplasm, grade, pain, nomogram, clinical features
