[Construction of a nomogram model for predicting 2-year survival rate of small cell lung cancer based on more comprehensive variables].

Objective: To construct a novel prognostic nomogram model based on more comprehensive variables for patients with small-cell lung cancer (SCLC). Methods: The data of 722 patients with SCLC confirmed by pathology in Affiliated Cancer Hospital of Shanxi Medical University from January 2015 to December 2018 were retrospectively analyzed [including 592 males and 130 females, aged from 23 to 82(61±9) years]. A random seed count of 133 was used to divide those patients into training set (n=422) and validation set (n=300). Kaplan-Meier was used for survival curves analysis and univariate Log-rank test was used for evaluating the influence of clinical variables on the prognosis of sclc, variables with P<0.05 in univariate analysis were included in a multivariate Cox regression model. The nomogram was constructed based on the variables which P<0.05 in multivariate analysis. Receiver operating characteristic (ROC) curve, calibration by Integrated Brier score (IBS) and clinical net benefit by decision curve analysis (DCA) were used to evaluate model discriminative power, prediction error value, and clinical net benefit, and compared with the American Joint Committee on Cancer 8th TNM. Results: Male, abnormal monocyte (MON) counts, abnormal neuron specific enolase (NSE), abnormal cytokeratin 19 fragment (Cyfra211), M1a stage, M1b stage, M1c stage, radiotherapy (RT), chemotherapy ≥4 cycles and prophylactic cranial irradiation (PCI) were prognostic factors for SCLC[HR(95%CI)=1.39(1.00-1.92), 1.29(1.02-1.63), 1.41(1.11-1.80), 2.02(1.48-2.76), 1.09(0.77-1.55), 1.44(0.94-2.22), 2.01(1.49-2.71), 0.75(0.57-0.98), 0.40(0.31-0.51)and 0.42(0.26-0.68), respectively, all P<0.05]. The area under ROC curve (AUC) of the nomogram in training set and validation set were 0.814(95%CI: 0.765-0.862)and 0.787 (95%CI: 0.725-0.849), which were higher than TNM [0.616(95%CI: 0.558-0.674) and 0.648(95%CI: 0.581-0.715)].The calibration curve showed a good correlation between the nomogram prediction and actual observation for the 2-year overall survival (OS). IBS indicted a lower prediction error rate (training set: 0.132 vs 0.169; validation set: 0.138 vs 0.169). DCA showed a wider threshold range than TNM (training set: 0.01-0.96 vs 0.01-0.85, validation set: 0.01-0.94 vs 0.01-0.86) and a greater improvement of the clinical net benefit (in training set the nomogram had a greater clinical benefit than TNM in the range of 0.19-0.96, and remained in validation set in the range of 0.19-0.94). Conclusion: The established nomogram model for predicting 2-year OS in patients with SCLC based on 8 variables, including gender, MON, NSE, Cyfra211, M stage, RT, CT cycles and PCI can be used for an more accurately prognosis prediction and reference for therapeutic regimen selection.

Peripheral hyperalgesia in experimental neuropathy: exacerbation by neuropeptide Y.

Injury of peripheral nerves often results in hyperalgesia (an increased sensitivity to painful stimuli). This hyperalgesia is mediated in part by sympathetic neurotransmitters. We examined the effect of neuropeptide Y (NPY), specific Y1 and Y2 agonists, and an NPY antagonist on peripheral hyperalgesia in rats whose sciatic nerves had been partially transected. NPY and the Y2 agonist, N-acetyl [Leu28,Leu31] NPY 24-36 exacerbated both mechanical and thermal hyperalgesia, while the Y1 agonist, [Leu31, Pro34]NPY relieved thermal hyperalgesia. Mechanical and thermal hyperalgesia were both relieved by alpha-trinositol (PP56), a non-competitive antagonist of the actions of neuropeptide Y. Hyperalgesia was also relieved by surgical sympathectomy, which eliminated the effects of NPY and its agonists. These results suggest that neuropeptide Y contributes to peripheral hyperalgesia by actions at Y2 receptors, which may be located on postganglionic sympathetic terminals.