Nomogram established using risk factors of early gastric cancer for predicting the lymph node metastasis.

BACKGROUND: For the prognosis of patients with early gastric cancer (EGC), lymph node metastasis (LNM) plays a crucial role. A thorough and precise evaluation of the patient for LNM is now required. AIM: To determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients. METHODS: Clinical information and pathology data of 2217 EGC patients downloaded from the Surveillance, Epidemiology, and End Results database were collected and analyzed. Based on a 7:3 ratio, 1550 people were categorized into training sets and 667 people were assigned to testing sets, randomly. Based on the factors influencing LNM determined by the training sets, the nomogram was drawn and verified. RESULTS: Based on multivariate analysis, age at diagnosis, histology type, grade, T-stage, and size were risk factors of LNM for EGC. Besides, nomogram was drawn to predict the risk of LNM for EGC patients. Among the categorical variables, the effect of grade (well, moderate, and poor) was the most significant prognosis factor. For training sets and testing sets, respectively, area under the receiver-operating characteristic curve of nomograms were 0.751 [95% confidence interval (CI): 0.721-0.782] and 0.786 (95%CI: 0.742-0.830). In addition, the calibration curves showed that the prediction model of LNM had good consistency. CONCLUSION: Age at diagnosis, histology type, grade, T-stage, and tumor size were independent variables for LNM in EGC. Based on the above risk factors, prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.

The Value of Cervical Node Features in Predicting Long-Term Survival of Nasopharyngeal Carcinoma in the Intensity-Modulated Radiotherapy Era.

OBJECTIVE: To investigate the prognostic value of cervical node features in patients with nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiotherapy (IMRT) and build a prognostic nomogram to predict the long-term survival. METHODS: In this study, 1752 patients after IMRT from 2008 to 2011 were recruited. The clinical and laboratory characteristics and the nodal features including the nodal number, maximum dimension diameter, extranodal extension (ENE), and cervical node necrosis (CNN) were retrospective analyzed. Univariate Cox and multivariate proportional hazard regression models were used to test the prognostic value of nodal features. Prognostic nomograms were established to predict survival. RESULTS: The 10-year distant metastases-free survival (DMFS) and disease-specific survival (DSS) rates were 86.5% and 80.8%, respectively. Multivariate analysis showed that age, sex, lactate dehydrogenase (LDH), CNN, ENE, T stage, and N stage were independent factors for DSS. Two nomograms-nomogram A (without nodal features) and nomogram B (with nodal features)-were built. The calibration curve for the probability of DSS showed good agreement between prediction by nomogram and the actual observation. The C-index of nomogram B was higher than that for nomogram A in predicting DSS (0.708 vs 0.676, P<0.01). CONCLUSION: The nodal features including ENE and CNN were negative prognostic factors for NPC, and the prognostic nomogram incorporating the nodal features was more accurate in predicting survival than the nomogram without nodal features.

Prognostic model and optimal treatment for patients with stage IVc nasopharyngeal carcinoma at diagnosis.

The treatment for patients with stage IVc nasopharyngeal carcinoma (NPC) at diagnosis was still controversial. In this study, we tried to build a prognostic score model and optimize the treatment for the patients. The prognostic model was based on the primary cohort involving 289 patients from 2002 to 2011 and the validation involving another 156 patients from 2012 to 2015.The prognostic model was built based on the hazard ratios of significant prognostic factors for overall survival (OS). By multivariate analysis, factors associated with poor OS were Karnofsky performance score ≤70, liver metastases, multiple-organ metastases, ≥2 metastatic lesions, lactate dehydrogenase >245 IU/I and poor response to chemotherapy (all P < 0.01). Based on these prognostic factors, patients were divided into the low-risk (0-2 points), intermediate-risk (3-6 points) and high-risk (≥7 points) groups. Five-year OS rates for the low-, intermediate- and high-risk groups were 49.3%, 9.7% and 0.0%, respectively (P < 0.01). Furthermore, loco-regional radiotherapy was associated with significantly better OS in low- and intermediate-risk patients, but not in high-risk patients. These results demonstrated that the prognostic score model based on six negative factors can effectively predict OS in patients with stage IVc NPC at diagnosis. Loco-regional radiotherapy may be beneficial for low- and intermediate-risk patients, but not for high-risk patients.

Iron species-mediated dopamine oxidation, proteasome inhibition, and dopaminergic cell demise: implications for iron-related dopaminergic neuron degeneration.

Iron species have been suggested to be highly involved in the pathogenesis of Parkinson disease. However, the detailed mechanism of iron-induced dopaminergic degeneration is still unclear. In this study, we demonstrate that free iron ions (trivalent or bivalent) and iron ions in stable complex with cyanide ions (K(4)Fe(CN)(6) and K(3)Fe(CN)(6)) can induce dopamine (DA) oxidation with different profiles and subsequently lead to proteasome inhibition and even dopaminergic MN9D cell demise via different mechanisms. The free iron ions could mediate extensive DA oxidation in an iron-DA complex-dependent manner. However, iron ions in stable complex with cyanide ions could not induce, or could induce only brief, DA oxidation. Deferoxamine, a specific iron ion chelator, could disrupt iron-DA complex formation and thus abrogate free iron ion-catalyzed DA oxidation and subsequent cell toxicity. Glutathione could neither disrupt iron-DA complex formation nor influence free iron ion-catalyzed DA oxidation but could protect against iron-mediated toxicity via detoxification of toxic by-products of iron-mediated DA oxidation. The resulting DA oxidation could inhibit chymotrypsin-like, trypsin-like, and caspase-like proteasome activities. However, we demonstrated that oxidative damage was not the major toxic mechanism of MN9D cell degeneration, but it was the DA quinones derived from iron-induced DA oxidation that contributed significantly to proteasome inhibition and even dopaminergic cell demise.