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Background We aimed to explore the relationship between body mass index (BMI) and body weight perception (BWP) with suicidal behaviors among mainland Chinese adolescents. Methods A nationally representative sample (N = 10 110) of Chinese adolescents was assessed in this study. Suicidal behaviors (ideation, plan and attempt) were evaluated by four self-reported questions. Generalized linear mixed model was used to estimate the adjusted odds ratios (ORs) for the association between BWP/BMI with suicidal behaviors. Results The prevalence of suicidal ideation, suicidal plan and suicidal attempt was 12, 5 and 2.1%, respectively. After adjusting potential covariates, perceiving oneself as obese was significantly associated with increased risks of suicidal ideation (OR: 2.4, 95% confidence intervals, CI: 1.6–4.0, P = 0.001), suicidal plan (OR: 3.1, 95% CI: 1.5–6.3, P = 0.002) and suicidal attempt (OR: 3.7, 95% CI: 1.5–9.1, P = 0.001) compared with perceiving as normal weight among male adolescents; the effect attenuated to null among female adolescents. Perceiving oneself as underweight and overweight both exhibited significant adverse effect on suicidal behaviors (only suicidal ideation and suicidal plan) compared with perceiving oneself as normal weight among male adolescents, but not among female adolescents. The actual measured BMI was not significantly associated with suicidal behaviors among neither gender. Conclusions Self-perception of their body image rather than actual measured weight may have a gender-specific adverse effect on suicidal behaviors among Chinese adolescents.

Introduction: Advanced lung cancer inflammation index (ALI) within esophageal squamous cell carcinoma (ESCC) importance is unclear. We aimed to investigate whether ALI is linked to poor short-term outcomes and long-term prognosis within cases of ESCC after minimally invasive esophagectomy (MIE). Methods: Kaplan-Meier survival assessment was applied for comparing cancer-specific survival (CSS) across different cohorts. Clinicopathological features across the two cohorts were eliminated by propensity score matching (PSM). We established a new model for predicting CSS by combining ALI and tumor-node-metastasis (TNM) staging according to Cox multivariate results. Time-dependent area under the curve (t-AUC) and decision curve analyses (DCA) evaluated predictive /clinical relevance capacities for this model. Results: Severe postoperative complication manifestations within low ALI cohort were significantly elevated compared to within high ALI cohort (25.3% vs 16.7, P=0.01), nil variations were identified across both cohorts after PSM (25.3% vs 18.3%, P = 0.06). Both, within overall cohort and the matched cohort, low ALI only significantly reduced the 5-year CSS in locally advanced ESCC patients (all P < 0.05) relative to high ALI. Further analysis demonstrated that patients within high ALI cohort were at increased risk for adverse postoperative CSS in most clinicopathological subgroups. Cox multivariate analysis demonstrated that TNM staging and ALI were variables that independently influenced adverse CSS in both cohorts (P < 0.05). Therefore, a new prediction model was established by combining these two factors. The t-AUC and DCA demonstrated that this model had a more accurate prediction effect and better clinical use value than the TNM stage alone. Conclusion: ALI proved to be an effective biological indicator of CSS after MIE in locally advanced ESCC patients. The combined application of the ALI and TNM model can thus improve the clinical prediction ability.

Background Preoperative imaging examination is the primary method for diagnosing metastatic gastrointestinal stromal tumor (GIST), but it is associated with a high rate of missed diagnosis. Therefore, it is important to establish an accurate model for predicting occult peritoneal metastasis (PM) of GIST. Patients and methods GIST patients seen between April 2002 and December 2018 were selected from an institutional database. Using multivariate logistic regression analyses, we created a nomogram to predict occult PM of GIST and validated it with an independent cohort from the same center. The concordance index (C-index), decision curve analysis (DCA) and a clinical impact curve (CIC) were used to evaluate its predictive ability. Results A total of 522 eligible GIST patients were enrolled in this study and divided into training (n=350) and validation cohorts (n=172). Factors associated with occult PM were included in the model: tumor size (odds ratio [OR] 1.194 95% confidence interval [CI], 1.034-1.378; p=0.016), primary location (OR 7.365 95% CI, 2.192-24.746; p=0.001), tumor capsule (OR 4.282 95% CI, 1.209-15.166; p=0.024), Alb (OR 0.813 95% CI, 0.693-0.954; p=0.011) and FIB (OR 2.322 95% CI, 1.410-3.823; p=0.001). The C-index was 0.951 (95% CI, 0.917-0.985) in the training cohort and 0.946 (95% CI, 0.900-0.992) in the validation cohort. In the training cohort, the prediction model had a sensitivity of 82.8%, a specificity of 93.8%, a positive predictive value of 54.7%, and a negative predictive value of 98.4%; the validation cohort values were 94.7%, 85.0%, 43.9% and 99.2%, respectively. DCA and CIC results showed that the nomogram had clinical value in predicting occult PM in GIST patients. Conclusion Imaging and inflammatory indexes are significantly associated with microscopic metastases of GIST. A nomogram including these factors would have an excellent ability to predict occult PM.

Non-textbook outcome (non-TO) represents a new prognostic evaluation index for surgical oncology. The present study aimed to develop new nomograms based on non-TO to predict the mortality and recurrence rate in patients with esophageal squamous cell cancer (ESCC) after minimally invasive esophagectomy (MIE).The study involved a retrospective analysis of 613 ESCC patients, from the prospectively maintained database from January 2011 to December 2018. All the included ESCC patients underwent MIE, and they were randomly (1:1) assigned to the training cohort (307 patients) and the validation cohort (306 patients). Kaplan-Meier survival analysis was used to analyze the differences recorded between overall survival (OS) and disease-free survival (DFS). In the case of the training cohort, the nomograms based on non-TO were developed using Cox regression, and the performance of these nomograms was calibrated and evaluated in the validation cohort.Significant differences were recorded for 5-year OS and DFS between non-TO and TO groups (p 0.05). Multivariate cox analysis revealed that non-TO, intraoperative bleeding, T stage, and N stage acted as independent risk factors that affected OS and DFS (p 0.05). The results for multivariate regression were used to build non-TO-based nomograms to predict OS and DFS of patients with ESCC, the t-AUC curve analysis showed that the nomograms predicting OS and DFS were more accurate as compared to TNM staging, during the follow-up period in the training cohort and validation cohort. Further, the nomogram score was used to divide ESCC patients into low-, middle-, and high-risk groups and significant differences were recorded for OS and DFS between these three groups (p 0.001).Non-TO was identified as an independent prognostic factor for ESCC patients. The nomograms based on non-TO could availably predict OS and DFS in ESCC patients after MIE.

BACKGROUND: The textbook outcome (TO) emerges as a novel prognostic factor in surgical oncology. The present study aimed to evaluate the effect of TO on the risk of death and recurrence in patients with esophageal squamous cell carcinoma (ESCC) after minimally invasive esophagectomy (MIE). METHODS: The study involved retrospective analysis of 528 patients with ESCC who were subjected to MIE from January 2011 to December 2017. TO included 8 parameters: complete resection; microscopically tumor-negative resection margins (R0); ≥15 lymph nodes removed and examined; no serious postoperative complications; no postoperative intervention; no re-admission to the intensive care unit (ICU); hospital stay ≤21 days; and no readmission ≤30 days. The Cox and logistic regression model were used to analyze the prognostic factors of survival and risk factors for TO. RESULTS: Among the 528 patients with ESCC who were subjected to MIE, 53.2% reached TO. In the case of patients with locally advanced ESCC, 5-year overall survival (OS) was 51.1% (41.2–61.2%) for the TO group but 33.7% (23.7–43.7%) for the non-TO group (HR =0.644, 95% CI: 0.449–0.924, P=0.015). Similarly, 5-year disease-free survival (DFS) was 47.6% (38.0–57.2%) for the TO group but 29.1% (20.1–38.1%) for the non-TO group (HR =0.671, 95% CI: 0.479–0.940, P=0.018). In addition, 5-year recurrence-free survival (RFS) was 62.9% (53.7–72.1%) for the TO group but 39.8% (29.4–50.2%) for the non-TO group (HR =0.606, 95% CI: 0.407–0.902, P=0.012). Multivariate logistic regression analysis further showed that age, American Society of Anesthesiology (ASA) score, intraoperative blood loss, and smoking status acted as independent risk factors for TO. The results of the multivariate analysis assisted in the establishment of a nomogram for the prediction of TO occurrence. This nomogram exhibited satisfactory consistency and prediction ability [area under the receiving operator characteristic (AUROC) =0.717]. CONCLUSIONS: The present study showed that achieving of TO after MIE improves survival rate and reduce the recurrence rate in patients with locally advanced ESCC. The study further determined the independent factors associated with TO achievement and established a prediction model.

Background Preoperative imaging examination is the primary method for diagnosing metastatic gastrointestinal stromal tumor (GIST), but it is associated with a high rate of missed diagnosis. Therefore, it is important to establish an accurate model for predicting occult peritoneal metastasis (PM) of GIST. Patients and Methods GIST patients seen between April 2002 and December 2018 were selected from an institutional database. Using multivariate logistic regression analyses, we created a nomogram to predict occult PM of GIST and validated it with an independent cohort from the same center. The concordance index (C-index), decision curve analysis (DCA) and a clinical impact curve (CIC) were used to evaluate its predictive ability. Results A total of 522 eligible GIST patients were enrolled in this study and divided into training (n=350) and validation cohorts (n=172). Factors associated with occult PM were included in the model: tumor size (odds ratio [OR] 1.194 95% confidence interval [CI], 1.034–1.378; p=0.016), primary location (OR 7.365 95% CI, 2.192–24.746; p=0.001), tumor capsule (OR 4.282 95% CI, 1.209–15.166; p=0.024), Alb (OR 0.813 95% CI, 0.693–0.954; p=0.011) and FIB (OR 2.322 95% CI, 1.410–3.823; p=0.001). The C-index was 0.951 (95% CI, 0.917–0.985) in the training cohort and 0.946 (95% CI, 0.900–0.992) in the validation cohort. In the training cohort, the prediction model had a sensitivity of 82.8%, a specificity of 93.8%, a positive predictive value of 54.7%, and a negative predictive value of 98.4%; the validation cohort values were 94.7%, 85.0%, 43.9% and 99.2%, respectively. DCA and CIC results showed that the nomogram had clinical value in predicting occult PM in GIST patients. Conclusion Imaging and inflammatory indexes are significantly associated with microscopic metastases of GIST. A nomogram including these factors would have an excellent ability to predict occult PM.

SUMMARYVolatility functionals are widely used in financial econometrics. In the literature, they are estimated with realized volatility functionals using high-frequency data. In this paper we introduce a nonparametric local bootstrap method that resamples the high-frequency returns with replacement in local windows shrinking to zero. While the block bootstrap in time series (Hall et al., 1995) aims to reduce correlation, the local bootstrap is intended to eliminate the heterogeneity of volatility. We prove that the local bootstrap distribution of the studentized realized volatility functional is first-order accurate. We present Edgeworth expansions of the studentized realized variance with and without local bootstrapping in the absence of the leverage effect and jumps. The expansions show that the local bootstrap distribution of the studentized realized variance is second-order accurate. Extensive simulation studies verify the theory.

Compared to other ethnic groups Asians are more likely to be sensitive to alcohol, due to polymorphisms of alcohol-metabolizing enzymes. Although previous studies have found positive association between regular alcohol use and high-sensitivity C-reactive protein (HsCRP), whether this association is modified by alcohol sensitivity has not been clarified. We therefore sought to examined this potential effect modification in a cross-sectional community sample with high prevalence of alcohol sensitivity, using data from 2903 men aged ≥50years recruited during phase 1 of the Guangzhou Biobank Cohort Study. Information on alcohol consumption and sensitivity (facial flushing, palpitation or dizziness after drinking) was obtained by questionnaire and HsCRP was measured by an immunoturbidometric assay. Elevated HsCRP was defined as HsCRP level equal to or higher than 2.81 mg/L(median). Excessive alcohol use was defined as use of ≥210 g ethanol per week. After adjustment for age, educational level, occupation, smoking status, physical activity and history of cardiovascular disease, alcohol use was associated with HsCRP in a dose-response pattern. The risks of elevated HsCRP were higher in those who drank daily (odds ratio (OR) = 1.38 (1.10, 1.72)) or drank excessively (1.57 (1.22, 2.02)), and were even higher in alcohol users with alcohol sensitivity (1.82 (1.24, 2.65) for daily users and 2.34 (1.48, 3.71) for excessive users). Results of this study have showed an important role of alcohol sensitivity in modifying the association between alcohol use and HsCRP level. Reduction of alcohol use should be an important public heath target, particularly among populations with high prevalence of alcohol sensitivity.