A novel online calculator to predict early recurrence and long-term survival of patients with resectable pancreatic ductal adenocarcinoma after pancreaticoduodenectomy: A multicenter study

The impact of anxiety on the risk of kidney stone disease: Insights into eGFR-mediated effects

BACKGROUND

Previous studies have linked kidney stone disease (KSD) with depression, but there are no reports on the relationship between anxiety and KSD, and the mechanism underlying the potential relationship remains unclear.

METHODS

Associations of anxiety and incident KSD were assessed in the National Health and Nutrition Examination Survey (NHENES) using multivariate logistic regression. Two-sample bidirectional Mendelian randomization studies and a two-step two-sample MR was used to estimate the mediating factors that influence KSD risk.

RESULTS

Examinations of NHANES data revealed that a rise in the frequency and intensity of anxiety were independently associated with incident KSD. In MR analysis, anxiety (uk-a-51 and uk-b-6519) were from the UK Biobank, with sample sizes of 328,717 and 450,765 respectively. KSD data were from the FinnGen, including 8597 cases and 333,128 controls. In the IVW analysis, genetically predicted anxieties (ukb-a-51 and ukb-b-6519) were found to be causally associated with a higher risk of KSD, with odds ratios of 6.18 (95 % CI 2.54-15.04) and 3.44 (95 % CI 1.67-7.08), respectively. There were no reverse causal effects. Further mediation analysis indicated that anxiety increases the risk of KSD by raising eGFR, through which 11.8 % of the effect of anxiety on KSD risk was mediated.

LIMITATIONS

The research was confined to individuals of European heritage, and there could be specific genetic variances among diverse ethnicities.

CONCLUSION

The current study suggests anxiety as an independent causal risk factor for KSD and unveils a new pathogenic mechanism, showing that anxiety raises eGFR, thereby increasing the risk of KSD.

Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma

OBJECTIVES

We evaluated the value of dual-energy computed tomography (DECT) parameters derived from pancreatic ductal adenocarcinoma (PDAC) to discriminate between high- and low-grade tumors and predict overall survival (OS) in patients.

METHODS

Data were retrospectively collected from 169 consecutive patients with pathologically confirmed PDAC who underwent third-generation dual-source DECT enhanced dual-phase scanning before surgery between January 2017 and March 2023. Patients with prior treatments, other malignancies, small tumors, or poor-quality scans were excluded. Two radiologists evaluated three clinical and seven radiological features and measured sixteen DECT-derived parameters. Univariate and multivariate analyses were applied to select independent predictors. A prediction model and a corresponding nomogram were developed, and the area under the curve (AUC), calibration, and clinical applicability were assessed. The correlations between factors and OS were evaluated using Kaplan-Meier survival and Cox regression analyses.

RESULTS

One hundred sixty-nine patients were randomly divided into training (n = 118) and validation (n = 51) cohorts, among which 43 (36.4%) and 19 (37.3%) had high-grade PDAC confirmed by pathology, respectively. The vascular invasion, normalized iodine concentration in the venous phase, and effective atomic number in the venous phase were independent predictors for histological grading. A nomogram was constructed to predict the risk of high-grade tumors in PDAC, with AUCs of 0.887 and 0.844 in the training and validation cohorts, respectively. The nomogram exhibited good calibration and was more beneficial than a single parameter in both cohorts. Pathological- and nomoscore-predicted high-grade PDACs were associated with poor OS (all p < 0.05).

CONCLUSIONS

The nomogram, which combines DECT parameters and radiological features, can predict the histological grade and OS in patients with PDAC before surgery.

KEY POINTS

Question Preoperative determination of histological grade in PDAC is crucial for guiding treatment, yet current methods are invasive and limited. Findings A DECT-based nomogram combining vascular invasion, normalized iodine concentration, and effective atomic number accurately predicts histological grade and OS in PDAC patients. Clinical relevance The DECT-based nomogram is a reliable, non-invasive tool for predicting histological grade and OS in PDAC. It provides essential information to guide personalized treatment strategies, potentially improving patient management and outcomes.

Construction of a NETosis-related gene signature for predicting the prognostic status of sepsis patients

Background

Sepsis is a common traumatic complication of response disorder of the body to infection. Some studies have found that NETosis may be associated with the progression of sepsis.

Methods

Data of the sepsis samples were acquired from Gene Expression Omnibus (GEO) database. Gene set enrichment score was calculated using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) networks analysis, and stepwise multivariable regression analysis were performed to identify NETosis-associated genes for sepsis prognosis. To assess the infiltration of immune cells, the ESTIMATE and CIBERPSORT algorithms were used. Functional enrichment analysis was conducted in the clusterProfiler package.

Results

Different programmed death pathways were abnormally activated in sepsis patients as compared to normal samples. We screened five important NETosis associated genes, namely, CEACAM8, PGLYRP1, MAPK14, S100A12, and LCN2. These genes were significantly positively correlated with entotic cell death and ferroptosis and negatively correlated with autophagy. A clinical prognostic model based on riskscore was established using the five genes. The ROC curves of the model at 7 days, 14 days and 21 days all had high AUC values, indicating a strong stability of the model. Patients with high riskscore had lower survival rate than those with low riskscore. After the development of a nomogram, calibration curve and decision curve evaluation also showed a strong prediction performance and reliability of the model. As for clinicopathological features, older patients and female patients had a relatively high riskscore. The riskscore was significantly positively correlated with cell cycle-related pathways and significantly negatively correlated with inflammatory pathways.

Conclusion

We screened five NETosis-associated genes that affected sepsis prognosis, and then established a riskscore model that can accurately evaluate the prognosis and survival for sepsis patients. Our research may be helpful for the diagnosis and clinical treatment of sepsis.

Efficiency evaluation of dual-energy CT to predict the postoperative early recurrence of pancreatic ductal adenocarcinoma

OBJECTIVES

To evaluate the efficacy of quantitative parameters from dual-energy CT (DECT) and basic CT features in predicting the postoperative early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC).

METHODS

In this study, patients with PDAC who underwent radical resection and DECT from 2018 to 2022 were enrolled and categorised into ER and non-ER groups. The clinical data, basic CT features and DECT parameters of all patients were analyzed. Independent predictors of ER were identified with Logistic regression analyses. Three models (model A: basic CT features; model B: DECT parameters; model C: basic CT features + DECT parameters) were established. Receiver operating characteristic curve analysis was utilized to evaluate predictive performance.

RESULTS

A total of 150 patients were enrolled (ER group: n = 63; non-ER group: n = 87). Rim enhancement (odds ratio [OR], 3.32), peripancreatic strands appearance (OR, 2.68), electron density in the pancreatic parenchymal phase (P-Rho; OR, 0.90), arterial enhancement fraction (AEF; OR, 0.05) and pancreatic parenchyma fat fraction in the delayed phase (OR, 1.25) were identified as independent predictors of ER. Model C showed the highest area under the curve of 0.898. In addition, the corresponding ER risk factors were identified separately for resectable and borderline resectable PDAC subgroups.

CONCLUSIONS

DECT quantitative parameters allow for the noninvasive prediction of postoperative ER in patients with PDAC, and the combination of DECT parameters and basic CT features shows a high prediction efficiency. Our model can help to identify patients with high-risk factors to guide preoperative decision making.

A novel nomogram based on the number of positive lymph nodes can predict the overall survival of patients with pancreatic head cancer after radical surgery

BACKGROUND

This study aimed to construct a novel nomogram based on the number of positive lymph nodes to predict the overall survival of patients with pancreatic head cancer after radical surgery.

MATERIALS AND METHODS

2271 and 973 patients in the SEER Database were included in the development set and validation set, respectively. The primary clinical endpoint was OS (overall survival). Univariate and multivariate Cox regression analyses were used to screen independent risk factors of OS, and then independent risk factors were used to construct a novel nomogram. The C-index, calibration curves, and decision analysis curves were used to evaluate the predictive power of the nomogram in the development and validation sets.

RESULTS

After multivariate Cox regression analysis, the independent risk factors for OS included age, tumor extent, chemotherapy, tumor size, LN (lymph nodes) examined, and LN positive. A nomogram was constructed by using independent risk factors for OS. The C-index of the nomogram for OS was 0.652 [(95% confidence interval (CI): 0.639-0.666)] and 0.661 (95%CI: 0.641-0.680) in the development and validation sets, respectively. The calibration curves and decision analysis curves proved that the nomogram had good predictive ability.

CONCLUSIONS

The nomogram based on the number of positive LN can effectively predict the overall survival of patients with pancreatic head cancer after surgery.

Prognostic role of nutrition parameters on short- and long-term outcome in patients with primary resectable pancreatic ductal adenocarcinoma

PURPOSE

Nutrition status of patients with pancreatic ductal adenocarcinoma (PDAC) has gained an increasing importance - especially in the preoperative setting. The aim of the present study was to evaluate different preoperative nutritional parameters including body composition parameters regarding their impact on short- and long-term outcome in patients with resectable PDAC.

METHODS

This retrospective single center study included 162 patients, who underwent primary resection of PDAC from January 2003 to December 2018 at the University Hospital of Erlangen. The influence of different preoperative nutrition parameters as well as different CT-based body composition parameters on short- (major morbidity, postoperative pancreatic fistula (POPF) and longer hospital stay) as well as on long-term outcome (overall and disease-free survival) were tested using multiple regression analysis.

RESULTS

Major morbidity and POPF occurred in 30% respectively 18%. Median length of hospital stay was 18 days. Median overall and disease free survival were 20.3 respectively 12.0 months. Multivariate analysis revealed among the different nutritional parameters following independent predictors: PMTH (psoas muscle thickness/height) for major morbidity (HR 2.1, p = 0.038), PMA (psoas muscle area) for a prolonged hospital stay >18 days (HR 7.3, p = 0.010) and NRS (nutritional risk score) for overall survival (HR 1.7, p = 0.043).

CONCLUSION

In our cohort, nutritional parameters played a minor role in predicting short- and long-term outcome in patients with primary resectable PDAC, as there were only significant associations between selected psoas muscle parameters and short-term outcome parameters and the nutritional risk score (NRS) with the overall survival.

Development of a radiomics-based model to predict occult liver metastases of pancreatic ductal adenocarcinoma: a multicenter study

BACKGROUND

Undetectable occult liver metastases block the long-term survival of pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop a radiomics-based model to predict occult liver metastases and assess its prognostic capacity for survival.

MATERIALS AND METHODS

Patients who underwent surgical resection and were pathologically proven with PDAC were recruited retrospectively from five tertiary hospitals between January 2015 and December 2020. Radiomics features were extracted from tumors, and the radiomics-based model was developed in the training cohort using LASSO-logistic regression. The model's performance was assessed in the internal and external validation cohorts using the area under the receiver operating curve (AUC). Subsequently, the association of the model's risk stratification with progression-free survival (PFS) and overall survival (OS) was then statistically examined using Cox regression analysis and the log-rank test.

RESULTS

A total of 438 patients [mean (SD) age, 62.0 (10.0) years; 255 (58.2%) male] were divided into the training cohort ( n =235), internal validation cohort ( n =100), and external validation cohort ( n =103). The radiomics-based model yielded an AUC of 0.73 (95% CI: 0.66-0.80), 0.72 (95% CI: 0.62-0.80), and 0.71 (95% CI: 0.61-0.80) in the training, internal validation, and external validation cohorts, respectively, which were higher than the preoperative clinical model. The model's risk stratification was an independent predictor of PFS (all P <0.05) and OS (all P <0.05). Furthermore, patients in the high-risk group stratified by the model consistently had a significantly shorter PFS and OS at each TNM stage (all P <0.05).

CONCLUSION

The proposed radiomics-based model provided a promising tool to predict occult liver metastases and had a great significance in prognosis.

Comprehensive analysis of necroptotic patterns and associated immune landscapes in individualized treatment of skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) constitutes a malignant cutaneous neoplasm characterized by an exceedingly unfavorable prognosis. Over the past years, necroptosis, a manifestation of inflammatory programmed cell demise, has gained substantial traction in its application. However, a conclusive correlation between the expression of necroptosis-related genes (NRGs) and SKCM patient's prognosis remains elusive. In this endeavor, we have undertaken an integrative analysis of genomic data, aiming to provide an exhaustive evaluation of the intricate interplay between melanoma necroptosis and immune-infiltration nuances within the tumor microenvironment. Through meticulous scrutiny, we have endeavored to discern the prognostic potency harbored by individual necroptosis-associated genes. Our efforts culminated in the establishment of a risk stratification framework, allowing for the appraisal of necroptosis irregularities within each afflicted cutaneous melanoma patient. Notably, those SKCM patients classified within the low-risk cohort exhibited a markedly elevated survival quotient, in stark contrast to their high-risk counterparts (p < 0.001). Remarkably, the low-risk cohort not only displayed a more favorable survival rate but also exhibited an enhanced responsiveness to immunotherapeutic interventions, relative to their high-risk counterparts. The outcomes of this investigation proffer insights into a conceivable mechanistic underpinning linking necroptosis-related attributes to the intricacies of the tumor microenvironment. This prompts a conjecture regarding the plausible association between necroptosis characteristics and the broader tumor microenvironmental milieu. However, it is imperative to emphasize that the pursuit of discerning whether the expression profiles of NRG genes can indeed be regarded as viable therapeutic targets necessitates further comprehensive exploration and scrutiny. In conclusion, our study sheds light on the intricate interrelationship between necroptosis-related factors and the tumor microenvironment, potentially opening avenues for therapeutic interventions. However, the prospect of translating these findings into clinical applications mandates rigorous investigation.

Development and validation of web calculators to predict early recurrence and long-term survival in patients with duodenal papilla carcinoma after pancreaticoduodenectomy

BACKGROUND

Duodenal papilla carcinoma (DPC) is prone to relapse even after radical pancreaticoduodenectomy (PD) (including robotic, laparoscopic and open approach). This study aimed to develop web calculators to predict early recurrence (ER) (within two years after surgery) and long-term survival in patients with DPC after PD.

METHODS

Patients with DPC after radical PD were included. Univariate and multivariate logistic regression analyses were used to identify independent risk factors. Two web calculators were developed based on independent risk factors in the training cohort and then tested in the validation cohort.

RESULTS

Of the 251 patients who met the inclusion criteria, 180 and 71 patients were enrolled in the training and validation cohorts, respectively. Multivariate logistic regression analysis revealed that tumor size [Odds Ratio (OR) 1.386; 95% confidence interval (CI) 1070-1.797; P = 0.014]; number of lymph node metastasis (OR 2.535; 95% CI 1.114-5.769; P = 0.027), perineural invasion (OR 3.078; 95% CI 1.147-8.257; P = 0.026), and tumor differentiation (OR 3.552; 95% CI 1.132-11.152; P = 0.030) were independent risk factors for ER. Nomogram based on the above four factors achieved good C-statistics of 0.759 and 0.729 in predicting ER in the training and the validation cohorts, respectively. Time-dependent ROC analysis (timeROC) and decision curve analysis (DCA) revealed that the nomogram provided superior diagnostic capacity and net benefit compared with single variable.

CONCLUSIONS

This study developed and validated two web calculators that can predict ER and long-term survival in patients with DPC with high degree of stability and accuracy.