Yang Lv, Xu Han, Chunyan Zhang, Yuan Fang, Ning Pu, Yuan Ji, Dansong Wang, Xu Xuefeng and Wenhui Lou
Chromogranin A (CgA) and neuron-specific enolase (NSE) are important markers for neuroendocrine tumors; however, the clinical value of combining these markers has not been well studied. In this study, we investigated the utility of each marker individually and in combination for patients with nonfunctional pancreatic neuroendocrine tumors (NF-pNETs).
Patients and Methods
In this study, NF-pNET patients and controls were recruited from December 2011 to March 2016; 784 serum samples from peripheral vein were collected. The clinical characteristics and biomarker values of all the individuals were recorded and analyzed. Tumor burdens were calculated by CT/MRI scan. Receiver-operating characteristic curves were constructed to assess the diagnostic predictive values; sensitivity and specificity were calculated to determine the cut-off value. Therapeutic responses reflected on the changes of the biomarkers’ concentration were assessed by the RECIST criterion. Clinical relations between the prognosis and the biomarker values were also analyzed. Statistical significance was defined as P value less than 0.05.
Among the 167 NF-pNETs patients, 82 were males (49.1%) and the mean age was 50.0 (17.4). The mean CgA values of G1, G2 and G3 NF-pNENs were 75, 121 and 134 μg/L (P < 0.05), respectively. In NF-pNETs, CgA correlated with the WHO tumor grade (WHO G1 vs G2, P < 0.05); the linear regression relationships were found between the tumor burdens (both in pancreas and liver) and CgA concentration (P < 0.001); changes in CgA and NSE concentrations also reflect treatment response (P < 0.001).
CgA and NSE are important diagnostic and follow-up markers in patients with NF-pNETs. The combined monitoring of CgA and NSE possesses more accuracy than individual values of CgA and NSE at predicting prognosis and disease progression.
Xu Han, Xuefeng Xu, Hongyun Ma, Yuan Ji, Dansong Wang, Tiantao Kuang, Wenchuan Wu, Bin Song, Gang Li, Gang Jin and Wenhui Lou
Emerging evidence suggests G3 pancreatic neuroendocrine neoplasms (pNENs) present heterogeneous morphology and biology. The 2017 WHO classification has introduced a new category of well-differentiated pancreatic neuroendocrine tumors (WD-pNETs) G3, compared with poorly differentiated pancreatic neuroendocrine carcinomas (PD-pNECs) G3. We aim to analysis the demographics and outcomes of patients with resectable 2017 WHO G3 pNENs to facilitate the distinction between two entities.
The multi-institutional retrospective cohort involving 57 surgically treated patients affected by 2017 WHO G3 pNENs were morphologically identified and clinically analyzed. Patients having WD-pNETs G3 and those having PD-pNECs G3 were compared.
Thirty patients had WD-pNETs and 27 patients had PD-pNECs. The distributions of Ki-67 and mitotic count in patients with PD-pNECs or WD-pNETs showed remarkable disparities. ROC indicated cut-off value of Ki-67 was 45. PD-pNECs were more common in patients with elevated Ki-67 and mitotic count, advanced AJCC TNM stage, vascular invasion, regional lymph-node metastases, elevated NSE and decreased CgA levels compared with WD-pNETs (P < 0.05). The association between 2017 WHO G3 grade and TTR was statistically significant (P < 0.05). Univariate analysis indicated OS rates were associated with morphologic differentiation (WD-pNETs vs PD-pNECs), Ki-67, TNM staging, synchronous distant metastases, initial treatments, vascular invasion, regional lymph nodes metastases, mitotic count and age (P < 0.05). Multivariate analyses illustrated Ki-67, differentiation, TNM staging and vascular invasion were independent predictors (P < 0.05).
PD-pNECs G3 presented malignant biological behavior and dismal outcome compared with WD-pNETs G3. These findings challenge 2010 WHO classification and suggest the categorization can be improved by refined tumor grading.
Yang Lv, Ning Pu, Wei-lin Mao, Wen-qi Chen, Huan-yu Wang, Xu Han, Yuan Ji, Lei Zhang, Da-yong Jin, Wen-Hui Lou and Xue-feng Xu
We aim to investigate the clinical characteristics of the rectal NECs and the prognosis-related factors and construct a nomogram for prognosis prediction.
The data of 41 patients and 1028 patients with rectal NEC were retrieved respectively from our institution and SEER database. OS or PFS was defined as the major study outcome. Variables were compared by chi-square test and t-test when appropriate. Kaplan–Meier analysis with log-rank test was used for survival analysis and the Cox regression analysis was applied. The nomogram integrating risk factors for predicting OS was constructed by R to achieve superior discriminatory ability. Predictive utility of the nomogram was determined by concordance index (C-index) and calibration curve.
In the univariate and multivariate analyses, tumor differentiation, N stage, M stage and resection of primary site were identified as independent prognostic indicators. The linear regression relationship was found between the value of Ki-67 index and the duration of OS (P < 0.05). Furthermore, the independent prognostic factors were added to formulate prognostic nomogram. The constructed nomogram showed good performance according to the C-index.
Contrary to WHO classification guideline, we found that the rectal NEC diseases are heterogeneous and should be divided as different categories according to the pathological differentiation. Besides, the nomogram formulated in this study showed excellent discriminative capability to predict OS for those patients. More advanced predictive model for this disease is required to assist risk stratification via the formulated nomogram.