Predict nutrition-related adverse outcomes in head and neck cancer patients undergoing radiotherapy: A systematic review.

BACKGROUND: Acute nutrition-related adverse outcomes are common in head and neck cancer patients undergoing radiotherapy. Predictive models can assist in identifying high-risk patients to enable targeted intervention. We aimed to systematically evaluate predictive models for predicting severe acute nutritional symptoms, insufficient intake, tube feeding, sarcopenia, and weight loss. METHODS: We searched PubMed, Web of Science, EBSCO, Embase, WanFang, CNKI, and SinoMed. We selected studies developing predictive models for the aforementioned outcomes. Data were extracted using a predefined checklist. Risk of bias and applicability assessment were assessed using the Prediction model Risk of Bias Assessment Tool. A narrative synthesis was conducted to summarize the model characteristics, risk of bias, and performance. RESULTS: A total of 2941 studies were retrieved and 19 were included. Study outcome measure were different symptoms (n = 11), weight loss (n = 5), tube feeding (n = 3), and symptom or tube feeding (n = 1). Predictive factors mainly encompassed sociodemographic data, disease-related data, and treatment-related data. Seventeen studies reported area under the curve or C-index values ranging from 0.610 to 0.96, indicating moderate to good predictive performance. However, candidate predictors were incomplete, outcome measures were diverse, and the risk of bias was high. Most of them used traditional model development methods, and only two used machine learning. CONCLUSIONS: Most current models showed moderate to good predictive performance. However, predictors are incomplete, outcome are inconsistent, and the risk of bias is high. Clinicians could carefully select the models with better model performance from the available models according to their actual conditions. Future research should include comprehensive and modifiable indicators and prioritize well-designed and reported studies for model development.

Construction and validation of a risk-prediction model for chemotherapy-related cognitive impairment in patients with breast cancer.

PURPOSE: To identify risk factors of chemotherapy-related cognitive impairment (CRCI) and construct and validate a visual prediction model of such for patients with breast cancer. METHODS: A multicenter, descriptive, and cross-sectional design was adopted. Data were collected from ten public tertiary hospitals in China. Cognitive function was assessed by using Functional Assessment of Cancer Therapy-cognitive function. Socio-demographic, clinical, psychological, and physical indicators were also assessed. The logistic prediction model was constructed by fivefold cross-validation. Then, a nomogram was utilized to visualize the prediction model, which was also evaluated via discrimination, calibration, and decision curve analysis. RESULTS: A total of 71 breast cancer patients had CRCI with a prevalence of 9.58%. This visual prediction model was constructed based on education background, exercise frequency, chemotherapy times, and fatigue and demonstrated good discrimination, with an area under the receiver operating characteristic curve of 0.882. The calibration curve indicated good agreement between experimental and projected values, and the decision curve proved good clinical applicability. CONCLUSION: Education background, exercise frequency, chemotherapy times, and fatigue were associated with high incidence of CRCI. The prediction model exhibits superior performance and has promise as a useful instrument for assessing the likelihood of CRCI in breast cancer patients. IMPLICATIONS FOR CANCER SURVIVORS: Our findings could provide breast cancer survivors with risk screening based on CRCI predictors to implement prevention and early intervention, and help patients integrate into society and achieve comprehensive recovery.

Lymphocyte migration regulation related proteins in urine exosomes may serve as a potential biomarker for lung cancer diagnosis.

BACKGROUND: The migration of lymphocytes shares many similarities in mode and mechanism with the metastasis of lung cancer tumor cells. But changes in the expression of lymphocyte migration regulation related proteins in urine exosomes remain unclear. This study is to investigate the expression changes of lymphocyte migration regulation related proteins in urine exosomes of lung cancer patients, and further verify their correlation with the development and progression of lung cancer. METHODS: Urine exosomes were collected from lung cancer patients and healthy people aged 15-79 years. Mass spectrometry was used to screen and explore the expression changes of lymphocyte migration regulation related proteins in healthy people of different ages. Enzyme-linked immunosorbent assay and western blotting were used to detect the expression changes of lymphocyte migration regulation related proteins in lung cancer patients. RESULTS: Analyzing the data of urine exosome proteomics, a total of 12 lymphocyte related proteins were identified, 5 of which were lymphocyte migration regulation related proteins. Among these proteins, WASL and STK10 proteins showed a gradual decrease in expression with age, and WNK1 protein showed a gradual increase. Lung cancer patients had reduced expression of WASL and increased expression of STK10 and WNK1 proteins in urine exosomes compared to normal people. Urine exosome WASL, STK10, and WNK1 were diagnosed with lung cancer, with a combined AUC of 0.760. CONCLUSIONS: Lymphocyte migration regulation related proteins were differentially expressed in the urine exosome of lung cancer patients, and WASL, STK10 and WNK1 may serve as potential biomarkers for lung cancer diagnosis.

Comparison of prognosis after partial and total surgical resection for parathyroid carcinoma: an inverse probability of treatment weighting analysis of the SEER database.

Background: Complete resection of the tumor and the ipsilateral thyroid lobe at the primary surgery is the "gold standard" for the treatment of parathyroid carcinoma (PC). However, differences in the overall survival (OS) of patients with PC who underwent partial and total surgical resection remain to be determined. Methods: Data on patients with PC who underwent partial and total surgical resection were extracted from the Surveillance, Epidemiology and End Results (SEER) database (2000-2018). The X-tile software (https://medicine.yale.edu/lab/rimm/research/software/) was used to define the optimal cut-off values for continuous variables. The inverse probability of treatment weighting (IPTW) method was used to reduce the selection bias. IPTW-adjusted Kaplan-Meier curves and Cox proportional hazards models were used to compare the OS of patients with PC in the partial and total surgical resection groups. Results: A total of 334 patients with PC were included in this study (183 and 151 in the partial and total surgical resection groups, respectively). The optimal cut-off values for age at diagnosis were 53 and 73 years, respectively, while that for tumor size was 34 mm. In both the Kaplan-Meier analysis and univariable Cox proportional hazards regression analysis before IPTW, the difference in OS between the partial and total surgical resection groups was not statistically significant (p>0.05). These findings were confirmed in the IPTW-adjusted Kaplan-Meier analysis and multivariate Cox proportional hazards regression analysis (p>0.05). Subgroup analysis revealed that total surgical resection was beneficial for OS only in the subgroup with unknown tumor size. Conclusion: There was no significant difference in the prognosis of patients who underwent partial and total surgical resection. This finding may provide a useful reference for the treatment of PC.

Thyroid cancer burden and risk factors in China from 1990-2019: a systematic analysis using the global burden of disease study.

Background: Thyroid cancer (TC) is the most common endocrine system malignancy with a rapidly increasing incidence in China. Epidemiological data on TC at the national level are lacking. This study aimed to quantify the TC disease burden in China between 1990 and 2019 and evaluate the current status and trends of the disease burden attributed to a high body mass index (HBMI). Methods: The 2019 Global Burden of Disease Study dataset was used to explore the TC disease burden. Age-standardized rates of incidence (ASIR), prevalence (ASPR), deaths (ASDR), and disability-adjusted life years (DALYs) were considered and the estimated annual percentage change (EAPC) was calculated as a measure of the average change in age-standardized rates. The trend in TC-related mortality and DALYs attributed to an HBMI, accounting for different age groups and sexes, was examined. Results: Between 1990 and 2019, the ASDR and DALYs for TC decreased by 0.02/100000 and 1.17/100000, respectively. The ASPR and ASIR increased by 9.88/100000 and 1.04/100000, respectively. The EAPC for ASDR, age-standardized rates of DALYs, ASPR, and ASIR were 0.06 (95% CI: -0.09, 0.21), -0.20 (95% CI: -0.31, -0.10), 3.52 (95% CI: 3.35, 3.68), and 2.73 (95% CI: 2.58, 2.88), respectively. TC-related deaths, DALYs, and their prevalence and incidence in China increased by 118%, 350%, 81%, and 290%, respectively. The disease burden of TC was higher among male than female patients in different age groups, with varying distributions. The disease burden attributed to HBMI gradually increased over the past 30 years according to age-standardized DALYs, particularly in male patients. Conclusion: The TC burden has increased in China over the past 30 years, and population aging poses a challenge to TC prevention and control. HBMI has become an important factor in the TC disease burden and further research should focus on reducing the disease burden among Chinese male patients with TC.

Risk of venous thromboembolism in patients undergoing gastric cancer surgery: a systematic review and meta-analysis.

BACKGROUND: Venous thromboembolism (VTE) is a common postoperative complication in patients undergoing surgery for gastric cancer (GC). Although VTE incidence may vary among cancers, guidelines rarely stratify preventive methods for postoperative VTE by cancer type. The risk of VTE in patients undergoing surgery for GC remains unclear. METHODS: A systematic review and meta-analysis was undertaken to determine the risk of VTE after GC surgery and discuss the clinical value of pharmacological thromboprophylaxis in these cases. Medline, Embase, Web of Science, and Cochrane Library databases were searched for articles published from their inception to September 2022. RESULTS: Overall, 13 studies (111,936 patients) were included. The overall 1-month incidence of VTE, deep vein thrombosis (DVT), and pulmonary embolism (PE) after GC surgery was 1.8% (95% CI, 0.8-3.1%; I²=98.5%), 1.2% (95% CI, 0.5-2.1%; I²=96.1%), and 0.4% (95% CI, 0.1-1.1%; I²=96.3%), respectively. The prevalence of postoperative VTE was comparable between Asian and Western populations (1.8% vs. 1.8%; P > 0.05). Compared with mechanical prophylaxis alone, mechanical plus pharmacological prophylaxis was associated with a significantly lower 1-month rate of postoperative VTE and DVT (0.6% vs. 2.9% and 0.6% vs. 2.8%, respectively; all P < 0.05), but not PE (P > 0.05). The 1-month postoperative incidence of VTE was not significantly different between laparoscopic and open surgery (1.8% vs. 4.3%, P > 0.05). CONCLUSION: Patients undergoing GC surgery do not have a high risk of VTE. The incidence of VTE after GC surgery is not significantly different between Eastern and Western patients. Mechanical plus pharmacological prophylaxis is more effective than mechanical prophylaxis alone in postoperative VTE prevention. The VTE risk is comparable between open and laparoscopic surgery for GC.

Joint Performance of a Continuous Glass Fiber/Polypropylene Composite.

Thermoplastic composite structures possess superior properties compared with thermosetting composites, including recyclability and high damage tolerance. However, the poor adhesion properties of thermoplastic composites make their joining process challenging. In this research, three bonding techniques, namely adhesive, mechanical joining, and hybrid bonding, are investigated using lap shear specimens to evaluate their mechanical properties and failure modes. The stress distributions at the joints of the three bonding techniques are analyzed by numerical simulation. The findings demonstrate that hybrid bonding enhances the strength of composite joints, albeit at the expense of some stiffness due to the presence of an open hole. This method is particularly suitable for applications that necessitate robust connections requiring high strength.

Prediction of lung papillary adenocarcinoma-specific survival using ensemble machine learning models.

Accurate prognostic prediction is crucial for treatment decision-making in lung papillary adenocarcinoma (LPADC). The aim of this study was to predict cancer-specific survival in LPADC using ensemble machine learning and classical Cox regression models. Moreover, models were evaluated to provide recommendations based on quantitative data for personalized treatment of LPADC. Data of patients diagnosed with LPADC (2004-2018) were extracted from the Surveillance, Epidemiology, and End Results database. The set of samples was randomly divided into the training and validation sets at a ratio of 7:3. Three ensemble models were selected, namely gradient boosting survival (GBS), random survival forest (RSF), and extra survival trees (EST). In addition, Cox proportional hazards (CoxPH) regression was used to construct the prognostic models. The Harrell's concordance index (C-index), integrated Brier score (IBS), and area under the time-dependent receiver operating characteristic curve (time-dependent AUC) were used to evaluate the performance of the predictive models. A user-friendly web access panel was provided to easily evaluate the model for the prediction of survival and treatment recommendations. A total of 3615 patients were randomly divided into the training and validation cohorts (n = 2530 and 1085, respectively). The extra survival trees, RSF, GBS, and CoxPH models showed good discriminative ability and calibration in both the training and validation cohorts (mean of time-dependent AUC: > 0.84 and > 0.82; C-index: > 0.79 and > 0.77; IBS: < 0.16 and < 0.17, respectively). The RSF and GBS models were more consistent than the CoxPH model in predicting long-term survival. We implemented the developed models as web applications for deployment into clinical practice (accessible through https://shinyshine-820-lpaprediction-model-z3ubbu.streamlit.app/ ). All four prognostic models showed good discriminative ability and calibration. The RSF and GBS models exhibited the highest effectiveness among all models in predicting the long-term cancer-specific survival of patients with LPADC. This approach may facilitate the development of personalized treatment plans and prediction of prognosis for LPADC.

Cuproptosis-Related 4-Gene Risk Model for Predicting Immunotherapy Drug Response and Prognosis of Kidney Renal Clear Cell Carcinoma.

Background Kidney renal clear cell carcinoma (KIRC) is one of the most common renal malignancies with a high mortality rate. Cuproptosis, a novel form of cell death, is strongly linked to mitochondrial metabolism and is mediated by protein lipoylation, leading to a proteotoxic stress response and cell death. To date, few studies have ellucidated the holistic role of cuproptosis-related genes (CRGs) in the pathogenesis of KIRC.Methods We comprehensively and completely analyzed the RNA sequencing data and corresponding clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We screened for differentially expressed CRGs and constructed a prognostic risk model using univariate and multivariate Cox proportional regression analyses. Kaplan-Meier analysis was performed and receiver operating characteristic (ROC) curves were plotted to predict the prognosis of KIRC patients. Functional enrichment analysis was utilized to explore the internal mechanisms. Immune-related functions were analyzed using single-sample gene set enrichment analysis (ssGSEA), tumour immune dysfunction and exclusion (TIDE) scores, and drug sensitivity analysis.Results We established a concise prognostic risk model consisting of four CRGs (DBT, DLAT, LIAS and PDHB) to predict the overall survival (OS) in KIRC patients. The results of the survival analysis indicated a significantly lower OS in the high-risk group as compared to the patients in the low-risk group. The area under the time-dependent ROC curve (AUC) at 1, 3, and 5 year was 0.691, 0.618, and 0.614 in KIRC. Functional enrichment analysis demonstrated that CRGs were significantly enriched in tricarboxylic acid (TCA) cycle-related processes and metabolism-related pathways. Sorafenib, doxorubicin, embelin, and vinorelbine were more sensitive in the high-risk group.Conclusions We constructed a concise CRGs risk model to evaluate the prognosis of KIRC patients and this may be a new direction for the diagnosis and treatment of KIRC.

CD44-Targeted Photoactivatable Polymeric Nanosystem with On-Demand Drug Release as a "Photoactivatable Bomb" for Combined Photodynamic Therapy-Chemotherapy of Cancer.

Nowadays, the combined use of chemotherapy and photodynamic therapy (PDT) remains the most popular strategy for cancer treatment with high theraprutic efficacy. However, targeted therapy with the on-demand release of drugs is what most clinical treatments lack, leading to heavy side effects. Herein, a new CD44-targeted and red-light-activatable nanosystem, Ru-HA@DOX nanoparticles (NPs), was developed by conjugating hydrophilic biodegradable hyaluronic acid (HA) and hydrophobic photoresponsive ruthenium (Ru) complexes, which could encapsulate the chemotherapeutic drug doxrubicin (DOX). Ru-HA@DOX NPs can selectively accumulate at the tumor through the enhanced permeability and retention (EPR) effect and CD44-mediated endocytosis, thus avoiding off-target toxicity during circulation. After 660 nm of irradiation at the tumor site, Ru-HA@DOX NPs, as a "photoactivatable bomb", was split via the photocleavable Ru-N coordination bond to fast release DOX and produce singlet oxygen (1O2) for PDT. In general, Ru-HA@DOX NPs retained its integrity before irradiation and possessed minimal cytotoxicity, while under red-light irradiation, Ru-HA@DOX NPs showed significant cytotoxicity due to the release of DOX and production of 1O2 at the tumor. Chemotherapy-PDT of Ru-HA@DOX NPs resulted in a significant inhibition of tumor growth in A549-tumor-bearing mice and reduced the cardiotoxicity of DOX. Therefore, this study offers a novel CD44-targeted drug-delivery system with on-demand drug release for synergistic chemotherapy-PDT.

Overall survival prediction models for gynecological endometrioid adenocarcinoma with squamous differentiation (GE-ASqD) using machine-learning algorithms.

The actual 5-year survival rates for Gynecological Endometrioid Adenocarcinoma with Squamous Differentiation (GE-ASqD) are rarely reported. The purpose of this study was to evaluate how histological subtypes affected long-term survivors of GE-ASqD (> 5 years). We conducted a retrospective analysis of patients diagnosed GE-ASqD from the Surveillance, Epidemiology, and End Results database (2004-2015). In order to conduct the studies, we employed the chi-square test, univariate cox regression, and multivariate cox proportional hazards model. A total of 1131 patients with GE-ASqD were included in the survival study from 2004 to 2015 after applying the inclusion and exclusion criteria and the sample randomly split into a training set and a test set at a ratio of 7:3. Five machine learning algorithms were trained based on nine clinical variables to predict the 5-year overall survival. The AUC of the training group for the LR, Decision Tree, forest, Gbdt, and gbm algorithms were 0.809, 0.336, 0.841, 0.823, and 0.856 respectively. The AUC of the testing group was 0.779, 0.738, 0.753, 0.767 and 0.734, respectively. The calibration curves confirmed good performance of the five machine learning algorithms. Finally, five algorithms were combined to create a machine learning model that forecasts the 5-year overall survival rate of patients with GE-ASqD.

Body composition and dietary intake in patients with head and neck cancer during radiotherapy: a longitudinal study.

OBJECTIVES: To investigate the body composition and dietary intake in the patients with head and neck cancer (HNC) during radiotherapy (RT), and explore the relationship between them. METHODS: This was a prospective, longitudinal observational study. Adult patients with HNC undergoing RT between March 2017 and August 2018 were recruited. Patients' body compositions were evaluated by bioelectrical impedance analysis, and dietary intake was recorded by 24-hour dietary recall at three time points, including baseline (T1), mid-treatment (T2) and post-treatment (T3). Patients were divided into low, middle and high energy intake groups based on the average daily energy intake (DEI). Changes in body weight (BW), fat mass (FM), fat-free mass (FFM) and skeletal muscle mass (SMM) among these three groups were compared. RESULTS: From T1 to T3, the median loss of patients' BW, FM, FFM and SMM was 4.60, 1.90, 2.60 and 1.50 kg, respectively. The loss of BW was more dramatic from T2 to T3 than that from T1 to T2. BW loss was mainly contributed by SMM loss from T1 to T2 and by FM loss from T2 to T3. Meanwhile, patients' dietary intake reduced during treatment. High DEI group had a significantly attenuated loss of patients' BW, FFM, SMM and FM compared with the low DEI group. CONCLUSION: Patients' BW, FM, FFM and SMM all significantly reduced, especially from T2 to T3, with decreased DEI during RT, which stresses the importance of nutrition intervention during the whole course of RT.

Tear trough ligament reset as a new method for tear trough deformity and dark circles correction.

Tear trough deformities and dark circles are important parts of periorbital aging. In this study, the tear trough ligament was reset to correct the tear trough deformity, and its effect on dark circles was analysed. The medical records of 60 patients who underwent eye bag plastic surgery between January 2021 and February 2022 were analysed (30 had traditional eye bag plastic surgery and 30 had the tear trough ligament reset). The tear trough deformity score and the dark circle score showed that the corrective effect on the tear trough deformity in the reset group was better than in the traditional surgery group at six-month follow up (mean (SD) tear trough rating scale (TTRS) score = 4.82 (0.95) vs 5.92 (1.00), p < 0.0001; L* value 55.27 (2.90) vs 47.51 (3.00), p < 0.0001). The satisfaction of patients in the reset group was significantly higher than it was in the traditional surgery group (25/30 vs 18/30, p = 0.045). Tear trough ligament reset is a safe and effective surgical method of periorbital rejuvenation, especially for beauty seekers with obvious tear trough deformities.

Development and validation of a nomogram to predict B-cell primary thyroid malignant lymphoma-specific survival: A population-based analysis.

B cell primary thyroid malignant lymphoma (BC-PTML) accounts for 95% of all cases of PTML. However, development of effective treatment and management strategies for BC-PTML is challenging owing to the rarity of this disease. This study assessed data from 1,152 patients in the Surveillance, Epidemiology, and End Results (SEER) database who were diagnosed with BC-PTML during 2000-2015. Patients were randomly divided into a training group (n=806) and a test group (n=346) at a ratio of 7:3 using the hold-out method. Kaplan-Meier analysis and log-rank tests were used to calculate the survival rate of patients. Subsequently, a stepwise Cox regression model was established to screen the prognostic factors of patients with BC-PTML, and these variables were used to construct a nomogram to predict 5-, 10-, and 15-year BC-PTML cancer-specific survival (CSS). The discrimination and calibration of the new model were evaluated using the concordance index (C-index) and calibration curves, and the accuracy and benefits of the model were assessed through comparison with the traditional Ann Arbor staging system using decision curve analysis (DCA). After stepwise regression, the optimal model included radiotherapy, primary site surgery, Ann Arbor Stage, chemotherapy, histological subtype, and age at diagnosis. The C-index, area under the receiver operating characteristic curve, and DCA suggested that the nomogram had improved discriminatory ability and clinical benefit compared with the Ann Arbor staging system. In summary, this study established an effective nomogram to predict CSS in patients with BC-PTML and assist clinicians in developing effective individualized treatment strategies.

Relationship between leisure-time physical activity and depressive symptoms under different levels of dietary inflammatory index.

Depressive symptoms are major public health problems. Leisure-time Physical activity (LPA) and dietary inflammatory preference are emerging factors that tends to affect the mental health status. There is limited evidence regarding the joint influence of LPA and dietary status on the prevalence of depression. This study was a cross-sectional study, which used a nationwide represented sample from the National Health and Nutrition Examination Survey (NHANES) to assess the relationship among LPA, diet status and depression. Depression and LPA status was reported by the 9-item Patient Health Questionnaire (PHQ-9) and Physical Activity Questionnaire (PAQ), respectively. To assess dietary inflammatory preferences, dietary inflammatory index (DII) was applied based on a 24-h dietary recall interview. A total of 11,078 subjects was included in this study and weighted participants were 89,682,020. Weighted multivariable linear regression showed that DII was negatively associated with LPA after full adjustment, with ß (95% CI): -0.487 (-0.647, -0.327). Weighted multivariable logistic regression showed that LPA was significantly associated with depressive symptoms after full adjustment, with odds ratios OR (95% CIs): 0.986 (0.977, 0.995). By DII stratification analysis, this phenomenon was also existed in groups with anti-inflammatory diet. Mediation effect analysis was further performed, which showed that DII significantly mediating the association between LPA and depression with proportion mediated as 3.94%. Our findings indicated the mediating role of DII in the association between LPA condition and incident depression. More well-designed studies are still needed to validate the causal relationship.

Development and validation of a nomogram model for cancer-specific survival of patients with poorly differentiated thyroid carcinoma: A SEER database analysis.

Background: This study aimed to establish and validate an accurate prognostic model, based on demographic and clinical parameters, for predicting the cancer-specific survival (CSS) of patients with poorly differentiated thyroid carcinoma (PDTC). Materials and methods: Patients diagnosed with PDTC between 2004 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Randomly split the data into training and validation sets. Kaplan-Meier analysis with the log-rank test was performed to compare the survival distribution among cases. Univariate and multivariate Cox proportional hazards regression analyses were used to identify independent prognostic factors, which were subsequently utilized to construct a nomogram for predicting the 5- and 10-year cancer-specific survival of patients with PDTC. The discriminative ability and calibration of the nomogram model were assessed using the concordance index and calibration plots, respectively. In addition, we performed a decision curve analysis to assess the clinical value of the nomogram. Simultaneously, we compared the predictive performance of the nomogram model against that of the American Joint Committee on Cancer (AJCC) T-, N-, M-stage. Results: A total of 970 eligible patients were randomly assigned to either a training cohort (n = 679) or a validation cohort (n = 291). The Kaplan-Meier analysis revealed that there were no significant differences in cumulative survival based on the race, radiation, and marital status of patients. The stepwise Cox regression model showed that the model was optimal when the following five variables were included: age, tumor size, T-, N-, and M-stage. A nomogram was developed as a graphical representation of the model and exhibited good calibration and discriminative ability in the study. Compared to the T-, N-, and M-stage, the C-index of nomogram (training group: 0.807, validation group: 0.802), the areas under the receiver operating characteristic curve of the training set (5-year AUC: 0.843, 10-year AUC:0.834) and the validation set (5-year AUC:0.878, 10-year AUC:0.811), and the calibration plots of this model all exhibited better performance. At last, compared with T-, N-, and M-stage, the decision curve analysis indicated that the nomogram had excellent clinical net benefit. Conclusions: The nomogram developed by us can accurately predict the CSS of PDTC patients. It can help clinicians determine appropriate treatment strategies for poorly differentiated thyroid carcinoma patients.

Saponins of Marsdenia Tenacissima promotes apoptosis of hepatocellular carcinoma cells through damaging mitochondria then activating cytochrome C/Caspase-9/Caspase-3 pathway.

Liver cancer is one of the most common cancers in the world and the second leading cause of death in cancer patients. There is an urgent need for an effective and less toxic treatment for liver cancer. Saponins of Marsdenia Tenacissima (SMT) as a potential anticancer drug has attracted extensive attention of researchers because of its effective biological activity. The effect of SMT on HepG2 Li-7 and L-02 cells was detected by CCK8 assay. At the same time, the apoptosis rate was detected by flow cytometer and laser confocal microscope, and the morphological changes of mitochondria were observed under electron microscope. The levels of bax, cytochrome c, caspase-9, caspase-3, cleaved caspase-3 and protein were detected using Western bolt. Finally, BALB/c was subcutaneously injected with H22 cells to form tumors, and SMT was intragastrically injected to detect the size of the transplanted tumor. SMT can induce apoptosis in vitro and reduce the size of transplanted tumor in vivo. Increases the rate of apoptosis through the cytochrome c pathway and regulates the expression of apoptosis-related proteins. These results suggest that SMT may be one of the potential candidates for the treatment of liver cancer.

Association between body composition and survival in head and neck cancer patients undergoing radiotherapy.

BACKGROUND: Body composition may influence the prognosis of head and neck cancer (HNC) patients. To find out the most crucial factors in this relationship, we explored the association between body composition and survival. METHODS: In this prospective longitudinal study, HNC patients who underwent radiotherapy (RT) from March 2017 to December 2018 were recruited. The association between body composition and survival was analyzed using Cox proportional hazard regression. RESULTS: Final analysis included 316 patients, with a median follow-up of 34.4 months. Multivariable analysis revealed that weight loss 6 months before RT and body composition changes during RT did not affect the survival outcome. However, patients with low appendicular skeletal muscle mass index (ASMI) before RT exhibited poor overall survival (OS). ASMI before RT was an independent prognostic factor for OS. CONCLUSIONS: Body composition loss was common during RT, and ASMI before RT independently influenced the survival outcomes of HNC patients.

A Predictive Model for the 10-year Overall Survival Status of Patients With Distant Metastases From Differentiated Thyroid Cancer Using XGBoost Algorithm-A Population-Based Analysis.

Purpose: To explore clinical and non-clinical characteristics affecting the prognosis of patients with differentiated thyroid cancer with distant metastasis (DTCDM) and establish an accurate overall survival (OS) prognostic model. Patients and methods: Study subjects and related information were obtained from the National Cancer Institute's surveillance, epidemiology, and results database (SEER). Kaplan-Meier analysis, log-rank test, and univariate and multivariate Cox analysis were used to screen for factors influencing the OS of patients with DTCDM. Nine variables were introduced to build a machine learning (ML) model, receiver operating characteristic (ROC) was used to evaluate the recognition ability of the model, calibration plots were used to obtain prediction accuracy, and decision curve analysis (DCA) was used to estimate clinical benefit. Results: After applying the inclusion and exclusion criteria, a total of 3,060 patients with DTCDM were included in the survival analysis from 2004 to 2017. A machine learning prediction model was developed with nine variables: age at diagnosis, gender, race, tumor size, histology, regional lymph node metastasis, primary site surgery, radiotherapy, and chemotherapy. After excluding patients who survived <120 months, variables were sub-coded and machine learning was used to model OS prognosis in patients with DTCDM. Patients 6-50 years of age had the highest scores in the model. Other variables with high scores included small tumor size, male sex, and age 51-76. The AUC and calibration curves confirm that the XGBoost model has good performance. DCA shows that our model can be used to support clinical decision-making in a 10-years overall survival model. Conclusion: An artificial intelligence model was constructed using the XGBoost algorithms to predict the 10-years overall survival rate of patients with DTCDM. After model validation and evaluation, the model had good discriminative ability and high clinical value. This model could serve as a clinical tool to help inform treatment decisions for patients with DTCDM.

Spleen bed laparoscopic splenectomy plus pericardial devascularization for elderly patients with portal hypertension.

Introduction: Laparoscopy splenectomy has been a preferred choice over open surgery, but limited studies dealing with laparoscopy splenectomy plus pericardial devascularization (LSPD) for elderly patients are available. Aim: To assess the safety and long-term efficacy of spleen bed LSPD for elderly patients with portal hypertension. Material and methods: A total of 132 elderly patients (age > 60 years) suffering from portal hypertension were operated on in the department. The patients were divided into 2 groups: those undergoing LSPD, and those undergoing open splenectomy plus pericardial devascularization (OSPD). Results and outcomes were compared retrospectively. Results: The clinical characteristics of the patients belonging to the two groups were studied. No significant difference between the characteristics of patients was reported and the clinical data revealed similarities in their characteristics. There was no significant difference in time taken for performing the operation (p > 0.05). The LSPD group showed less blood loss; started oral intake early; and the duration of post-operative hospital stay was also shorter (p < 0.05). Incidence rates of portal vein thrombosis; pancreatic leakage; pleural effusion; pulmonary infection; and delayed wound healing were also found to be lower in the LSPD group as compared to the OSPD group (p < 0.05). During a follow-up period of 6-70 months, no significant differences were found in the data for the two methods with respect to the incidence of rebleeding; hepatic encephalopathy; and survival (p > 0.05). Conclusions: It was concluded that spleen bed LSPD is a safe and feasible procedure for treating elderly patients. It had a better clinical effect than that of OSPD.