Objective: The aim of this study was to investigate the influence of psychosocial variables on patients with multiple sclerosis (MS) and the relationship between these variables and the onset of MS. Background: The current evidence indicates that many types of psychosocial factors are involved in the development and relapse of MS, and it has been suggested that they could serve as predictors as well. So far, little has been reported on the effect of psychosocial factors on MS and the relationship between psychosocial factors and the onset of MS. Methods: Forty-one patients, 15 males and 26 females, average age 37.44 ± 12.24 years (mean ± SD), were evaluated by the Life Event Scale, Eysenck Personality Questionnaire, Social Support Revaluate Scale and Symptom Check List 90 and compared with 41 equivalent healthy control subjects, 15 males and 26 females, average age 36.38 ± 12.84 years (mean ± SD). Disease, demographic, psychosocial and lifestyle factors were measured at baseline. Patients with MS were first diagnosed by 3 neurologists according to the Poser (1983) MS diagnostic criteria. Results: Significant differences were found between the MS and the control group in their negative emotions and symptoms such as depression, anxiety, obsession, phobia, tense interpersonal relationship and somatization disorder. Significant differences were found between the two groups in the total number of negative life events, their family problems and the utilization of social support. The scores for various negative emotions in the MS group correlated positively with those for neuroticisms in personality type, and negatively with those for introverted and extroverted personality. Many kinds of negative emotions in the MS group correlated positively with the total number of life events, negative life events and family problems. Many kinds of negative emotions in the MS group correlated negatively with the utilization of social support. Conclusion: The psychosocial factors are closely associated with MS onset and may play important roles in the development of the disease.
Systemic inflammation is closely related to the occurrence and development of tumours. Based on preoperative neutrophil, monocyte, and lymphocyte counts, a new systemic inflammation response index (SIRI) was established, and the predictive ability of the SIRI for the survival of patients with adenocarcinoma of the oesophagogastric junction (AEG) was evaluated by propensity score matching (PSM) analysis. A total of 302 AEG patients undergoing radical surgery were studied. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Time-dependent receiver operating characteristic (ROC) curves were used to compare the predictive capabilities of the SIRI. PSM was implemented to balance the baseline characteristics. The results showed that the SIRI, PLR, NLR, and MLR were associated with overall survival (OS) in AEG patients based on the Kaplan-Meier survival analysis. Multivariate analysis demonstrated that the SIRI was an independent prognostic factor. The AUC for the SIRI was significantly greater than that for the NLR, PLR, and MLR in predicting the 3- and 5-year OS of AEG patients. In PSM analysis, the SIRI remained an independent prognostic indicator of OS in AEG patients. The SIRI is a novel, simple, and inexpensive prognostic predictor for AEG. The prognostic value of the SIRI is superior to that of the PLR, NLR, and MLR. The SIRI can be used to distinguish the prognosis of AEG patients with different TNM stages and can be an important supplement to TNM staging.
Background Metastatic regional lymph nodes (LN) is a strong predictor of worse long-term outcome. Therefore, different LN staging systems have been proposed in recent years. In this study, we proposed a modified lymph node ratio (mLNR) as a new lymph node staging system and then compared the prognostic performance of mLNR with American Joint Committee on Cancer N stage, lymph node ratio (LNR) and log odds of metastatic lymph nodes in breast cancer patients. Methods Breast cancer patients who underwent surgery between 2004 and 2012 were identified from the Surveillance, Epidemiology, and End Results database. Restricted cubic spline functions were calculated to characterize the association between variables and the risk of death. The Cox proportional hazards models were constructed to assess the predictive ability of different lymph node staging systems using the Akaike’s Information Criterion (AIC) and Harrell’s concordance index (C-index). Results A total of 264,096 breast cancer patients were enrolled and 187,785 (71.1%) patients had a limited number of LNs harvested. In the limited LN harvest cohort, the prognostic performance of LNR decreased and mLNR could greatly solve this problem. In addition, among the entire cohort, mLNR modeled as a continuous value had the best predictive ability (AIC: 922021.9 and C-index: 0.727) than other lymph node staging systems. Conclusions The predictive ability of LNR is restricted by a limited LN harvest. However, mLNR shows superiority to LNR and other lymph node staging systems especially in a limited LN harvest cohort, making mLNR the most powerful lymph node staging systems.
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