Consistency Index Research Articles

Nomogram to Predict the Prognosis of Oligodendroglioma Patients Undergoing Postoperative Adjuvant Chemoradiotherapy

ObjectiveThe aim of this study was to develop a prognostic nomogram for predicting the prognosis of oligodendroglioma patients receiving combined chemoradiotherapy (CRT) after surgery. MethodsThe study used data from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2019. The patients were randomly divided into a development cohort (700 patients) and a validation cohort (244 patients) in a 7:3 ratio. The Cox hazards regression model was used to identify predictors, and a nomogram was constructed to visualize the prognosis. The performance of the prognostic nomogram was evaluated using the consistency index (C-index), clinical net benefit, and calibration. ResultsThe nomogram included five variables: age, marital status, tumor size, site of lesions, and surgery type. The C-index of the training set and validation set were 0.77 and 0.68, respectively. The calibration plots showed that the nomogram was in good agreement with the actual observation. The clinical decision curve indicated that the nomogram had a good clinical net benefit in oligodendroglioma patients receiving CRT after surgery. ConclusionsThis study established and verified a prognostic nomogram for a large cohort of oligodendroglioma patients receiving CRT after surgery based on the SEER database. The nomogram may help clinicians provide personalized treatment services and clinical decisions for patients.

A prognostic nomogram integrating carcinoembryonic antigen levels for predicting overall survival in elderly patients with stage II-III colorectal cancer.

With the aging of the population, colorectal surgeons will have to face more elderly colorectal cancer (CRC) patients in the future. We aim to analyze independent risk factors affecting overall survival in elderly (age ≥65 years) patients with stage II-III CRC and construct a nomogram to predict patient survival. A total of 3,016 elderly CRC patients with stage II-III were obtained from the SEER database. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analyses were used to screen independent prognostic factors, and a survival prediction nomogram was constructed based on the results. The consistency index (C-index), decision curve analysis (DCA), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to compare the predictive ability between the nomogram and tumor-node-metastasis (TNM) stage system. All patients were classified into high-risk and low-risk groups based on risk scores calculated by nomogram. The Kaplan-Meier method was used to compare the survival differences between two groups. The 3- and 5-year area under the curve (AUC) values of the prediction nomogram model were 76.6% and 74.8%, respectively. The AIC, BIC, and C-index values of the nomogram model were 6,032.502, 15,728.72, and 0.707, respectively, which were better than the TNM staging system. Kaplan-Meier survival analysis showed a significant survival difference between high-risk and low-risk groups (P<0.0001). We constructed a prediction nomogram for stage II-III elderly CRC patients by combining pre-treatment carcinoembryonic antigen (CEA) levels, which can accurately predict patient survival. This facilitates clinicians to accurately assess patient prognosis and identify high-risk patients to adopt more aggressive and effective treatment strategies.

Validation of intercultural competence scale in the Ethiopian context: Exploring the factor structure and psychometric properties among university students.

Although intercultural competence is a crucial factor for university students' academic achievement and inter-ethnic conflict resolution, psychometrically sound intercultural competence scale is not available in the Ethiopian context. The aim of the present study was to translate the original English version of intercultural competence into Amharic language and validate the scale in the Ethiopian context. In the processes of retaining culturally equivalent translated measure symmetrical approach was used. Data were collected from 476 (Male = 244 and Female = 232) arbitrarily selected university students with an age mean of 22.35 enrolled in undergraduate degree programs at Ambo University. The total sample was randomly split into two equal-sized group to execute exploratory factor analysis (EFA, N = 238) and confirmatory factor analysis (CFA, N = 238). The result of the study showed that both EFA and CFA supported a significantly correlated four-factor model of intercultural competence (Attitude, Awareness, Knowledge, and Skills). Moreover, the Amharic version of the intercultural competence scale showed good psychometric properties in terms of content validity, construct validity, internal consistency, and good fit indices to the data. This generally justifies the use of the Amharic version intercultural competence scale in the Ethiopian context. To satisfy the needs of the labor market, universities in Ethiopia should promote intercultural dialogues that improve the intercultural competence of university students.

Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea Severity in Children.

The clinical presentation of Obstructive Sleep Apnea (OSA) in children is insidious and harmful. Early identification of children with OSA, particularly those at a higher risk for severe symptoms, is essential for making informed clinical decisions and improving long-term outcomes. Therefore, we developed and validated a risk prediction model for severity in Chinese children with OSA to effectively identify children with moderate-to-severe OSA in a clinical setting. From June 2023 to September 2023, we retrospectively analyzed the medical records of 367 Children diagnosed with OSA through portable bedside polysomnography (PSG). Predictor variables were screened using the least absolute shrinkage and selection operator (LASSO) and logistic regression techniques to construct nomogram to predict the severity of OSA. Receiver operating characteristic curve (ROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were used to determine the discrimination, calibration, and clinical usefulness of the nomogram. A total of 367 children with a median age of 84 months were included in this study. Neck circumference, ANB, gender, learning problem, and level of obstruction were identified as independent risk factors for moderate-severe OSA. The consistency indices of the nomogram in the training and validation cohorts were 0.841 and 0.75, respectively. The nomogram demonstrated a strong concordance between the predicted probabilities and the observed probabilities for children diagnosed with moderate-severe OSA. With threshold probabilities ranging from 0.1 to 1.0, the predictive model demonstrated strong predictive efficacy and yielded improved net benefit for clinical decision-making. ROC analysis was employed to classify the children into high and low-risk groups, utilizing the Optimal Cutoff value of 0.39. A predictive model using LASSO regression was developed and validated for children with varying levels of OSA. This model identifies children at risk of developing OSA at an early stage.

Prognostic Factors and Construction of Nomogram Prediction Model of Lung Cancer Patients Using Clinical and Blood Laboratory Parameters.

This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model. A total of 322 LC patients were taken as the study subjects. They were randomly divided into a training set (n = 202) and a validation set (n = 120). Basic information and laboratory indicators were collected, and the progression-free survival (PFS) and overall survival (OS) were followed up. Single-factor and cyclooxygenase (COX) multivariate analyses were performed on the training set to construct a Nomogram prediction model, which was validated with 120 patients in the validation set, and Harrell's consistency was analyzed. Single-factor analysis revealed significant differences in PFS (P<0.05) between genders, body mass index (BMI), carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), treatment methods, treatment response evaluation, smoking status, presence of pericardial effusion, and programmed death ligand 1 (PD-L1) at 0 and 1-50%. Significant differences in OS (P<0.05) were observed for age, tumor location, treatment methods, White blood cells (WBC), uric acid (UA), CA125, pro-gastrin-releasing peptide (ProGRP), SCCA, cytokeratin fragment 21 (CYFRA21), and smoking status. COX analysis identified male gender, progressive disease (PD) as treatment response, and SCCA > 1.6 as risk factors for LC PFS. The consistency indices of the line chart models for predicting PFS and OS were 0.782 and 0.772, respectively. Male gender, treatment response of PD, and SCCA > 1.6 are independent risk factors affecting the survival of LC patients. The PFS line chart model demonstrates good concordance.

Characterization of the Ngouache Landslide by Geotechnical Survey (Bafoussam, Cameroon)

The heavy rainfall during the night of October 28-29, 2019, caused a landslide in the Ngouache 4 neighborhood in Bafoussam in the West Cameroon region. This landslide caused 43 deaths, several missing persons and the destruction of several houses and plantations. The present investigation attempts to find the causesof this landslide. First, the landslide area was identified and heavy dynamic penetrometer surveys were conducted. Next, intact and reworked samples were taken and, finally, slopes were measured on the slide area to determine the soil parameters. The results of the heavy dynamic penetrometer showed the presence of altered clay layers which, when saturated, exert hydrostatic pressure and unbalance the soil. The granulometric analysis noted a soil with more than 50% of grains of ϕ&gt;80µm with liquidity limits between (50-65.3%), a consistency index between (1.01-1.24), a low cohesion between (0.22-0.30 bars) for a high internal friction angle (20.72°-23.86°), slopes between 48° and 56° and a degree of saturation Sr between (80.5° and 139.9°). These characteristics associated with the large water columns of the night of October 28 to 29, 2019 demonstrated that the water had exerted a hydrostatic pressure having made the clay material reach the limit of plasticity to the creep and raised the level of the water table. Thistherefore promoted the saturation of the substrate yet the increase in the water content reduces the cohesion of the materials and that triggered the saturation at the origin of this deadly slide. The results of the present research may help the public authorities in the decision making regarding the characterization and the securing of risk zones.

Evaluation of Technological Properties of Mortars with the Addition of Plaster Byproduct

The incorporation of waste into construction materials is a potential topic for study and is seen as a solution for many industries that face the following impasse: the risk to the environment due to the accumulation of waste in yards. In view of this, during the production of lactic acid, which is widely used in industries, gypsum is produced as a byproduct, yielding one ton for each ton of lactic acid. Aiming at a functional destination for this byproduct, this study proposes its addition in mortars for covering walls and ceilings. The research proposal was a mortar in a 1:6 ratio (cement:sand) with the addition of 0, 3, 6 and 10% of industrial plaster byproduct. The cement used to prepare the mortar was CPII-E32. To characterize the raw materials, scanning electron microscopy, X-ray fluorescence and X-ray diffraction analysis were carried out. To evaluate the properties in the fresh state, a consistency index and mass density and entrained air tests were carried out. In the hardened state, mass density, axial compression strength, flexural tensile strength and water absorption via capillarity were evaluated after 28 days of age. Microstructural characterization techniques were also carried out on the reference mixtures and with 3% addition of the byproduct gypsum, such as scanning electron microscopy and X-ray diffraction. The results showed that the byproduct is hemihydrate and its addition improved the workability of the mortar. Mortars with the addition of byproduct gypsum showed a reduction in mechanical resistance. The most satisfactory results were for the mixes with a 3% addition, indicating greater resistance to axial compression and flexural traction, with 3.90 MPa and 1.14 MPa, respectively.

Strategi Pemilihan Supplier Mesin Turbocharger Menggunakan Metode Analytical Hierarchy Process dan Multi-Objective Optimization Method By Ratio Analysis

The right supplier selection is an important factor for PT. Central Turbo, which is currently facing problems related to the supplier selection system that is not accurate. The study aims to develop a decision support system for the selection of turbocharger suppliers. The method used is AHP-MOORA to measure the consistency of criteria and sub-criteria in determining the highest supplier ranking. The research procedure begins with the creation of a hierarchical structure, followed by the creation of an AHP matrix to determine the weight of the criteria, the calculation of the consistency index and ratio, the normalization of the matrix, and the determination of Yi/preference value in the MOORA analysis. The decision support system developed can help PT. Central Turbo in selecting the right turbocharger supplier. This system can evaluate supplier performance more objectively and efficiently, so that it can help the company to improve its competitiveness and customer satisfaction, by considering 3 criteria, namely product performance, supplier, and service. As a result, Fencheng Xindongli Turbocharger Co., Ltd was selected as the best supplier.

Xanthan gum produced from milk permeate and deproteinized cheese whey: A comparative analysis with commercial xanthan gums

In this study, we produced xanthan gums from deproteinized whey and milk permeate and evaluated their rheological behavior, FT-IR spectral profiles, thermogravimetric decomposition, and coloration. Besides, commercial xanthan gums were also characterized and employed in a comparative analysis. All xanthan gum exhibited non-Newtonian behavior characterized by a decrease in viscosity with an increase in the shear rate. At a shear rate of 32 s−1, the viscosity values for XGC1, XGC2, and XGC3 were 308.16, 334.64, and 256.16 mPa s, while XGMP and XGDW exhibited viscosities of 146.82 and 77.82 mPa s, respectively. Flow indexes (n) were lesser than 1 confirming a pseudoplastic behavior for all xanthan gums. Greater consistency indices (K) were observed in commercial xanthan gums, reaching values higher than those biosynthesized. Both xanthan gums groups exhibited similar functional groups within the 1800 to 900 cm−1 wavelength regions as determined by FTIR-ATR analysis. However, they showed differences in bands from 800 to 500 cm−1. Principal component analysis (PCA) applied to the spectra effectively differentiated XGC3 from the other xanthan gums. Commercial xanthan gums exhibited similar thermal degradation profiles, characterized by two distinct stages of mass loss, while biosynthesized gums showed three stages. XGDW exhibited lower values for luminosity and whiteness indices compared to other gums. Our findings demonstrated differences in the viscosity, consistency, molecular structure, thermal degradation, and coloration of the evaluated xanthan, even within the group of commercial gums. XGMP stands out among biosynthesized xanthan gums owing to its similarity to commercial gums and its noteworthy characteristics for industrial applications.

Hetero atom-based metal complexes as emitters in organic light-emitting diodes

The new, more energy-efficient lighting systems and high-quality displays for new age digital devices is the demand of the current generation. In this regard, focused and deliberated research has been done on transition metal complexes as effective building blocks for organic light-emitting diodes (OLEDs). The activity of divalent metallic compounds was investigated through spotlighting Co (II), Ni (II), and Cu (II) metal ions with guanidinium naphthoate as blue phosphors in OLEDs. Using spectroscopic and diffraction techniques, the phosphors produced at the optimal temperature were studied both structurally and thermally. Additionally, the target compound's photophysical investigations in a variety of organic solvents with differing polarities were examined, and the findings were presented. Because of their quick photoluminescence response time and high emission quantum efficiency, Ni (II) complexes have drawn specific attention. Ni (II) complexes precisely exhibit thermally activated delayed fluorescence (TADF) and found to be the most promising materials for future lighting technology. We compared the efficiencies of various complexes in this study to provide an overview of the development of OLEDs. To affirm the pertinency of the synthesized compounds as phosphors, studies like photoluminescence, correlated color temperature, color purity, Duv, and the Television Lighting Consistency Index (TLCI) were performed and their photometric properties were also deliberated. Ni (II) shows an magnificent luminescence character and maximum coloring index for light sources and found to be an essential component for OLEDs.

Landslide vulnerability mapping using multi-criteria decision-making approaches: in Gacho Babba District, Gamo Highlands Southern Ethiopia

The landslide has been a life-threatening natural disaster in most districts of Gamo Highlands. This study was conducted to assess the status of landslide vulnerability in the Gacho Baba district of the Gamo zone in southern Ethiopia. The Geographic Information System Analytical Hierarchy Process and Weighted Linear Combination multi-criteria decision-making approaches were applied. Eight causative factors of landslide, namely, slope, elevation, aspect, distance from the stream, drainage density, soil type, distance from the road, and land use/cover were considered. The weight values of each causative factor were determined by previous studies, field observations, and experts’ judgment. The calculated weight of each causative factor is the slope (23%), elevation (21%), aspect (8%), stream distance and drainage density each (12%), soil type and road length each (9%), and land use/cover (6%). Moreover, the Consistency Index (0.13) and Consistency Ratio (0.08%) were calculated with acceptable values for comparison to weighted overlay analysis to produce a landslide vulnerability map of the study area. The result shows that the vast majority of the study district (86.6%) falls within a very high to moderate landslide susceptibility class and only (13.4%) falls within a very low and low susceptibility. This indicates that almost all the 11 villages in the district, are found within the high to moderate landslide vulnerability class which alerts responsible community and zonal disaster risk prevention and related offices to take action on the identified causative factors to reduce the occurrences of landslide hazard in the study district.

The Selection of Weapon Systems in The A2/AD (Not Access/Area Denial) Strategy at Indonesia's Strategic Choke Points by Using The Analytical Hierarchy Process (AHP) Method

This article utilizes the Analytical Hierarchy Process (AHP) method to decide how to choose an effective weapon system for the A2/AD (anti-access/area denial) strategy at the Sunda Strait, Indonesia's strategic choke point. The main discussion is limited to selecting the types of weapon systems considered effective in implementing A2/AD at Indonesia's strategic choke points. The next step is to decide which primary, secondary, and alternative criteria are the most important. Each of these will then be put together mathematically by measuring consistency using the Consistency Index (CI), the Consistency Ratio (CR), and the Consistency Hierarchy, which is the ranking as the result of the analysis. This method resulting in a weight for the navigation criteria of 66%, projection of 19%, and operability of 16%. Furthermore, in conclusion, the order of the best weapon systems is RBS15 MK4 with a weight of 66%, Brahmos II at 18%, and Neptune 360ST at 16%.

Development and Validation of a Nomogram Model for Individualizing the Risk of Osteopenia in Abdominal Obesity

Objective: This study was aimed to create and validate a risk prediction model for the incidence of osteopenia in individuals with abdominal obesity.Methods: Survey data from the National Health and Nutrition Examination Survey (NHANES) database for the years 2013–2014 and 2017–2018 was selected and included those with waist circumferences ≥102 m in men and ≥88 cm in women, which were defined as abdominal obesity. A multifactor logistic regression model was constructed using LASSO regression analysis to identify the best predictor variables, followed by the creation of a nomogram model. The model was then verified and evaluated using the consistency index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA).Results Screening based on LASSO regression analysis revealed that sex, age, race, body mass index (BMI), alkaline phosphatase (ALP) and Triglycerides (TG) were significant predictors of osteopenia development in individuals with abdominal obesity (P < 0.05). These six variables were included in the nomogram. In the training and validation sets, the C indices were 0.714 (95 % CI: 0.689–0.738) and 0.701 (95 % CI: 0.662–0.739), respectively, with corresponding AUCs of 0.714 and 0.701. The nomogram model exhibited good consistency with actual observations, as demonstrated by the calibration curve. The DCA nomogram showed that early intervention for at-risk populations has a net positive impact.Conclusion: Sex, age, race, BMI, ALP and TG are predictive factors for osteopenia in individuals with abdominal obesity. The constructed nomogram model can be utilized to predict the clinical risk of osteopenia in the population with abdominal obesity.

Investigation of the effect of the surfactant on the mixing of highly concentrated slurries of fine particles via SEM, RSM, and CFD

The main purpose of this research was to explore the likelihood of preparation of highly concentrated slurries of stabilized submicron CaCO3 particles using a surfactant in a pilot-scale mixing system. To achieve this goal, the effects of independent factors such as CaCO3 and surfactant (lecithin) concentrations, impeller type, and their interactions on power consumption, slurry rheological characteristics, and particle size were investigated. Employing the Eulerian-Granular multiphase model, a computational fluid dynamics model (CFD) was created. The validated CFD model was utilized to assess the degree of homogeneity for slurries agitated inside the mixing system. The lowest power consumption, the smallest particle size and consistency index, and the highest power-law index were achieved for highly concentrated slurries containing the optimal amount of lecithin (3.5 wt%) for the stabilization of fine CaCO3 particles. The high-shear sawtooth impeller was shown to be the most efficient impeller for mixing fine CaCO3 slurries containing lecithin.

Analytical-solution-based interval fuzzy utility acquisition and decision making with interval-valued fuzzy preference relations based on additive consistency

Acquiring an analytical solution of interval fuzzy utility vectors (IFUVs) from interval-valued fuzzy preference relations (IVFPRs) plays a key role in improving the efficiency and performance of decision making with IVFPRs. This study devises formulas to compute uncertainty indices of interval-valued fuzzy assessments and IVFPRs, and builds uncertainty constraints among fuzzy assessments in an additively consistent IVFPR. By dividing all IVFPRs with the same size into two categories, least square models with constraints of uncertainty indices are set up and their analytical solutions are found to respectively acquire normalized IFUVs from the two categories of IVFPRs. The analytical solutions are then integrated into unified computational formulas acquiring normalized IFUVs from IVFPRs. On the basis of analytical-solution-based IFUVs, a distance based additive consistency index is devised and a novel acceptability concept is presented by taking both additive inconsistency acceptability and uncertainty acceptability into account. Subsequently, this paper proposes a multi-criteria decision making method with highlighting individual characteristics of alternatives. An illustration with one consistent IVFPR and three inconsistent IVFPRs is offered and a comparative study is implemented to validate the models presented. An annual-performance-evaluation-based outstanding teacher recommendation problem is utilized to show the practicality of the decision method proposed.

Nomograms predict survival in elderly women with triple-negative breast cancer: A SEER population-based study.

The effective treatment of breast cancer in elderly patients remains a major challenge. To construct a nomogram affecting the overall survival of triple-negative breast cancer (TNBC) and establish a survival risk prediction model. A total of 5317 TPBC patients with negative expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) who were diagnosed and received systematic treatment from 2010 to 2015 were collected from the American Cancer Surveillance, Epidemiology and End Results (SEER) database. They were randomly divided into training set (n= 3721) and validation set (n= 1596). Univariate and multivariate Cox regression analysis were used to identify prognostic features, and a nomogram was established to predict the probability of 1-year, 3-year and 5-year OS and BCSS. We used consistency index (C-index), calibration curve, area under the curve (AUC) and decision curve analysis (DCA) to evaluate the predictive performance and clinical utility of the nomogram. The C-indices of the nomograms for OS and BCSS in the training cohort were 0.797 and 0.825, respectively, whereas those in the validation cohort were 0.795 and 0.818, respectively. The receiver operating characteristic (ROC) curves had higher sensitivity at all specificity values as compared with the Tumor Node Metastasis (TNM) system. The calibration plot revealed a satisfactory relationship between survival rates and predicted outcomes in both the training and validation cohorts. DCA demonstrated that the nomogram had clinical utility when compared with the TNM staging system. This study provides information on population-based clinical characteristics and prognostic factors for patients with triple-negative breast cancer, and constructs a reliable and accurate prognostic nomogram.

Physicochemical properties and stability of oil-in-water emulsions stabilized by soy protein isolate and xanthan gum

The aim of this work was to determine rheological and disperse characteristics and stability of oil-in-water emulsions stabilized by soy protein isolate (SPI) and xanthan gum (XG), as natural components. The effects of their combination on emulsion stabilization have not been investigated yet. The existence of interactions between the two macromolecules were indicated by the influence of XG on SPI surface hydrophobicity and surface tension values. Increase in SPI concentration from 1 to 3 % shift of distribution curves towards smaller particle size, while the opposite effects of further increase of SPI was obtained. The emulsions stabilized by SPI showed shear-thinning flow behavior, which changed to thixotropic at 5 % of SPI concentration. The presence of XG in emulsions at low concentrations did not affect the size distribution of the droplets, while at 0.1 % of XG Sauter mean diameter value raised and distribution curves were shifted towards a higher particle size. The presence of XG at higher concentration resulted in thixotropic flow behavior of emulsions. Also, increase in XG concentration led to the increase in consistency index and extent of non-Newtonian behavior of emulsions and enhanced the influence of the elastic modulus and creaming stability of the systems.

Prediction of Particle Settling Velocity in Newtonian and Power-Law Fluids Using Artificial Neural Network Model

In petroleum engineering, accurately predicting particle settling velocity during various stages of a well’s life cycle is vital. This study focuses on settling velocities of both spherical and non-spherical particles in Newtonian and non-Newtonian fluids. Utilizing a dataset of 931 experimental observations, an artificial neural network (ANN) model with a 7-42-1 architecture is developed (one input layer, one hidden layer with 42 neurons, and one output layer). This model effectively incorporates particle settling orientation and the inclusion of the settling area ratio, enhancing its predictive accuracy. Achieving an average absolute relative error (AARE) of 8.51%, the ANN model surpasses traditional empirical correlations for settling velocities in both Newtonian and power-law fluids. Key influencing factors, such as the consistency index and particle equivalent diameter, were identified. This approach in ANN model construction and data analysis represents a significant advancement in understanding particle dynamics.

Nomograms confirm serum IL-6 and CRP as predictors of immune checkpoint inhibitor efficacy in unresectable hepatocellular carcinoma.

Immunotherapy based on immune checkpoint inhibitors (ICIs) has become the first-line treatment for unresectable hepatocellular carcinoma (uHCC). However, only a small portion of patients are responsive to ICIs. It is important to identify the patients who are likely to benefit from ICIs in clinical practice. We aimed to examine the significance of serum IL-6 and CRP levels in predicting the effectiveness of ICIs for uHCC. We retrospectively recruited 222 uHCC patients who received ICIs treatment (training cohort: 124 patients, validation cohort: 98 patients). In the training cohort, patients are categorized into the response group (R) and no-response group (NR). The levels of serum IL-6 and CRP were compared between the two groups. Internal validation was performed in the validation cohort. Survival analysis was carried out using the Kaplan-Meier method and Cox proportional hazard regression model. The nomograms were developed and assessed using the consistency index (C-index) and calibration curve. Serum levels of IL-6 and CRP were significantly lower in the R group than in the NR group (9.94 vs. 36.85 pg/ml, p< 0.001; 9.90 vs. 24.50 mg/L, p< 0.001, respectively). An ROC curve was employed to identify the optimal cut-off values for IL-6 and CRP in both groups, resulting in values of 19.82 pg/ml and 15.50 mg/L, respectively. Multivariate Cox regression analysis revealed that MVI (HR 1.751, 95%CI 1.059-2.894, p=0.029; HR 1.530, 95%CI 0.955-2.451, p=0.077), elevated IL-6 (HR 1.624, 95%CI 1.016-2.596, p=0.043; HR 2.146, 95%CI 1.361-3.383, p =0.001) and high CRP (HR 1.709, 95%CI 1.041-2.807, p=0.034; HR 1.846, 95%CI 1.128-3.022, p = 0.015) were independent risk factors for PFS and OS, even after various confounders adjustments. Nomograms are well-structured and validated prognostic maps constructed from three variables, as MVI, IL6 and CRP. Low levels of IL-6 and CRP have a positive correlation with efficacy for uHCC patients receiving ICIs.

A novel incomplete hesitant fuzzy information supplement and clustering method for large-scale group decision-making.

Clustering is an effective means to reduce the scaling of large-scale group decision-making (LSGDM). However, there are many problems with clustering methods, such as incomplete or ambiguous information usually provided by different decision makers. Traditional clustering methods may not be able to handle these situations effectively, resulting in incomplete decision-making information. Calculating the clustering centers may become very complex and time-consuming. Inappropriate distance weights may also lead to incorrect cluster assignments, and these problems will seriously affect the clustering results. This research provides a novel incomplete hesitant fuzzy information supplement and clustering approach for large-scale group decision-making in order to address the aforementioned difficulties. First, the approach takes into account the trust degradation and the inhibition of relationships of distrust in the process of trust propagation, and then it builds a global and local network of trust. A novel supplemental formula is provided that takes into account the decision-preference maker's as well as the trust-neighbor's information, allowing the decision-neighbor maker's recommendation to be realized. Therefore, an improved distance function can be proposed to calculate the weights by combining the relative standard deviation theory and selecting the selected clustering centers by using the density peaks in order to optimize the selection of clustering centers and reduce the complexity and scaling of the decision. Finally, an example is presented to demonstrate how the proposed method can be applied. The consistency index and comparison experiments are used to evaluate if the suggested approach is effective and reliable.