The latest exploration of staging and prognostic classification for pancreatic neuroendocrine tumors: a large population-based study

Gao, Shanshan; Pu, Ning; Liu, Lingxiao; Li, Changyu; Xu, Xuefeng; Xiao-lin, Wang; Lou, Wenhui

doi:10.7150/jca.24178

Cited by 14 publications

(9 citation statements)

References 35 publications

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“…In addition, patients with AJCC stage II exhibited no statistically significant differences in CSS compared with patients in stage I, which suggested that the prognostic discrimination of stage I and stage II in the 7th edition of the AJCC staging system may need to be improved. These results were consistent with a previous study (13).…”

Section: Discussionsupporting

confidence: 94%

Prognostic and metastasis‑related factors in colorectal neuroendocrine tumors: A cross‑sectional study based on the Surveillance, Epidemiology and End Results

et al. 2019

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The incidence of colorectal neuroendocrine tumors (NETs) is gradually increasing with the increasing availability of colonoscopy and computed tomography. However, prognostic and metastatic factors for colorectal NETs are unknown. The aim of the present study was to identify clinicopathological prognostic and metastasis-related risk factors for colorectal NETs. Based on the Surveillance, Epidemiology and End Results (SEER) program, the data of 3,093 patients with colorectal NETs were included in the present study. χ2 test, crosstabulation, Kaplan-Meier method, Cox proportional hazard regression model, nomogram and logistic regression analysis were used to evaluate the risk factors. Systemic analysis of data from 3,093 patients revealed that age (P<0.001), marital status (P<0.001), number of malignant tumors (P<0.001), histopathological grade (P<0.001) and clinical stage (P<0.001) were independent prognostic factors of cancer-specific survival (CSS). Among them, married patients exhibited longer CSS compared with unmarried patients (P<0.05). A nomogram based on these five factors with an area under the curve of 0.921 [95% confidence interval (CI), 0.908–0.934; P<0.001] was constructed. Age (P=0.010), primary tumor site (P<0.001), surgery (P<0.001), tumor size (P<0.001) and histopathological grade (P<0.001) were risk factors for distant metastasis of colorectal NETs. In conclusion, age, marital status, number of malignant tumors, histopathological grade and clinical stage may be independent prognostic factors for CSS of colorectal NETs, and the nomogram may have higher predictive efficiency compared with clinical stage. Age, primary tumor site, surgery, tumor size and histopathological grade may be risk factors for the distant metastasis of colorectal NETs.

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Section: Discussionsupporting

confidence: 94%

Prognostic and metastasis‑related factors in colorectal neuroendocrine tumors: A cross‑sectional study based on the Surveillance, Epidemiology and End Results

et al. 2019

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“…The sensitivity of NSE is 33% and its specificity is 73%[ 81 , 82 ]. This poor sensitivity and specificity could be an explanation for the use of PNETs grade and stage as prognostic biomarkers for this neoplasia[ 83 ]. Additionally, CgA is an unspecific biomarker given that it can be released by non-neuroendocrine tumors including gastric disorder, inflammatory bowel disease, end-stage renal disease (ESRD), and obstruction of blood vessels (cardiovascular disease)[ 84 , 85 ].…”

Section: Pnet Lack Specific and Sensitive Biomarkersmentioning

confidence: 99%

Pancreatic neuroendocrine tumors: Therapeutic challenges and research limitations

Mpilla

Philip

El‐Rayes

et al. 2020

WJG

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Pancreatic neuroendocrine tumors (PNETs) are known to be the second most common epithelial malignancy of the pancreas. PNETs can be listed among the slowest growing as well as the fastest growing human cancers. The prevalence of PNETs is deceptively low; however, its incidence has significantly increased over the past decades. According to the American Cancer Society’s estimate, about 4032 (> 7% of all pancreatic malignancies) individuals will be diagnosed with PNETs in 2020. PNETs often cause severe morbidity due to excessive secretion of hormones (such as serotonin) and/or overall tumor mass. Patients can live for many years (except for those patients with poorly differentiated G3 neuroendocrine tumors); thus, the prevalence of the tumors that is the number of patients actually dealing with the disease at any given time is fairly high because the survival is much longer than pancreatic ductal adenocarcinoma. Due to significant heterogeneity, the management of PNETs is very complex and remains an unmet clinical challenge. In terms of research studies, modest improvements have been made over the past decades in the identification of potential oncogenic drivers in order to enhance the quality of life and increase survival for this growing population of patients. Unfortunately, the majority of systematic therapies approved for the management of advanced stage PNETs lack objective response or at most result in modest benefits in survival. In this review, we aim to discuss the broad challenges associated with the management and the study of PNETs.

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“…As a result, the third and fourth stages (65% vs 55%. p = 0.36) cannot be effectively distinguished [ 12 ]. In addition, these staging systems only focus on the survival rate of patients with NETs at specific sites.…”

Section: Discussionmentioning

confidence: 99%

Predicting the Survival Probability of Neuroendocrine Tumor Populations: Developing and Evaluating a New Predictive Nomogram

Jian-xian

Lin

Meng

et al. 2021

BioMed Research International

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Purpose. The purpose of this study was to develop and initially validate a nomogram model in order to predict the 3-year and 5-year survival rates of neuroendocrine tumor patients. Methods. Accordingly, 348 neuroendocrine tumor patients were enrolled as study objects, of which 244 (70%) patients were included in the training set to establish the nomogram model, while 104 (30%) patients were included in the validation set to verify the robustness of the model. First, the variables related to the survival rate were determined by univariable analysis. In addition, variables that were sufficiently significant were selected for constructing the nomogram model. Furthermore, the concordance index (C-index), receiver operating characteristic (ROC), and calibration curve analysis were used to evaluate the performance of the proposed nomogram model. The survival analysis was then used to evaluate the return to survival probability as well as the indicators of constructing the nomogram model. Results. According to the multivariable analysis, lymphatic metastasis, international normalized ratio (INR), prothrombin time (PT), tumor differentiation, and the number of tumor metastases were found to be independent predictors of survival rate. Moreover, the C-index results demonstrated that the model was robust in both the training set (0.891) and validation set (0.804). In addition, the ROC results further verified the robustness of the model either in the training set ( AUC = 0.823 ) or training set ( AUC = 0.768 ). Furthermore, the calibration curve results showed that the model can be used to predict the 3-year and 5-year survival probability of neuroendocrine tumor patients. Meaningfully, five variables were found: lymphatic metastasis ( p = 0.0095 ), international standardized ratio ( p = 0.024 ), prothrombin time ( p = 0.0036 ), tumor differentiation ( p = 0.0026 ), and the number of tumor metastases ( p = 0.00096 ), which were all significantly related to the 3-year and 5-year survival probability of neuroendocrine tumor patients. Conclusion. In summary, a nomogram model was constructed in this study based on five variables (lymphatic metastasis, international normalized ratio (INR), prothrombin time (PT), tumor differentiation, and number of tumor metastases), which was shown to predict the survival probability of patients with neuroendocrine tumors. Additionally, the proposed nomogram exhibited good ability in predicting survival probability, which may be easily adopted for clinical use.

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The latest exploration of staging and prognostic classification for pancreatic neuroendocrine tumors: a large population-based study

Cited by 14 publications

References 35 publications

Prognostic and metastasis‑related factors in colorectal neuroendocrine tumors: A cross‑sectional study based on the Surveillance, Epidemiology and End Results

Prognostic and metastasis‑related factors in colorectal neuroendocrine tumors: A cross‑sectional study based on the Surveillance, Epidemiology and End Results

Pancreatic neuroendocrine tumors: Therapeutic challenges and research limitations

Predicting the Survival Probability of Neuroendocrine Tumor Populations: Developing and Evaluating a New Predictive Nomogram

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