Evaluation Of Prognosis In Patients Research Articles

Platelet to Lymphocyte Ratio (PLR) Value in Normotency, Preeclampsia and Severe Preeclampsia

BACKGROUND : Hyperactivation of the inflammatory response in preeclampsia causes a significant increase in the number of leukocytes. Platelet to Lymphocyte Ratio (PLR) has been known as a marker of systemic inflammatory response. In preeclampsia, the role of PLR markers is still uncertain regarding the ability of clinical evaluation, differential diagnosis and evaluation of patient prognosis. AIMS : To analyze differences in platelet to lymphocyte ratio (PLR) values in normotensive, preeclampsia, and severe preeclampsia pregnancies METHOD : Analytical observational study with cross sectional design with 90 samples consisting of 30 normotensive pregnancies, 30 preeclampsia and 30 severe preeclampsia. Evaluation is carried out on the platelet to lymphocyte ratio (PLR) value. Analysis was carried out using the SPSS 32 edition application. Results are significant if p<0.05. RESULT : Comparison between the normotensive group versus preeclampsia versus severe preeclampsia showed that platelet levels decreased but not significantly (p=0.081), lymphocyte levels increased significantly (p<0.001) and PLR values decreased significantly (p<0.001) as the degree of severity increased preeclampsia. In the severe preeclampsia group, the lowest platelet levels, the highest lymphocyte levels and the lowest PLR values were obtained. Patients with a PLR value < 104.62 have an 8.43x (OR 8.43; CI95% 3.12-22.78) higher risk of experiencing severe preeclampsia compared to subjects with a PLR value > 104.62. CONCLUSION : The PLR value was significantly lowest in the severe preeclampsia group.

Construction and validation of a clinical prediction model for sepsis using peripheral perfusion index to predict in-hospital and 28-day mortality risk.

Sepsis is a clinical syndrome caused by infection, leading to organ dysfunction due to a dysregulated host response. In recent years, its high mortality rate has made it a significant cause of death and disability worldwide. The pathophysiological process of sepsis is related to the body's dysregulated response to infection, with microcirculatory changes serving as early warning signals that guide clinical treatment. The Peripheral Perfusion Index (PI), as an indicator of peripheral microcirculation, can effectively evaluate patient prognosis. This study aims to develop two new prediction models using PI and other common clinical indicators to assess the mortality risk of sepsis patients during hospitalization and within 28 days post-ICU admission. This retrospective study analyzed data from sepsis patients treated in the Intensive Care Unit of Peking Union Medical College Hospital between December 2019 and June 2023, ultimately including 645 patients. LASSO regression and logistic regression analyses were used to select predictive factors from 35 clinical indicators, and two clinical prediction models were constructed to predict in-hospital mortality and 28-day mortality. The models' performance was then evaluated using ROC curve, calibration curve, and decision curve analyses. The two prediction models performed excellently in distinguishing patient mortality risk. The AUC for the in-hospital mortality prediction model was 0.82 in the training set and 0.73 in the validation set; for the 28-day mortality prediction model, the AUC was 0.79 in the training set and 0.73 in the validation set. The calibration curves closely aligned with the ideal line, indicating consistency between predicted and actual outcomes. Decision curve analysis also demonstrated high net benefits for the clinical utility of both models. The study shows that these two prediction models not only perform excellently statistically but also hold high practical value in clinical applications. The models can help physicians accurately assess the mortality risk of sepsis patients, providing a scientific basis for personalized treatment.

Ultrasound radiomics in the assessment of breast cancer molecular subtypes: A systematic review and meta-analysis.

Accurate prediction of preoperative molecular subtypes of breast cancer is crucial for treatment planning and prognosisevaluation of patients. This systematic review aims to investigate the capacity of ultrasound radiomics in accuratelyidentifying the molecular subtypes of breast cancer. We conducted a thorough search of PubMed, Embase, and Cochrane databases to identify relevant research up until May 2024. We pooled sensitivity, specificity, positivelikelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the area under the curve (AUC) to summarize the abilityof ultrasound radiomics to predict Luminal type and triple negative breast cancer (TNBC) type in patient with breast cancer.Results: Our meta-analysis found that nine studies provided ultrasound radiomics predictions for TNBC. Pooled sensitivity,specificity, and AUC were 0.64, 0.89, and 0.86, respectively. Four studies have provided the ultrasound radiomics predictionof Luminal molecular subtype breast cancer. Pooled sensitivity, specificity, and AUC were 0.89, 0.79, and 0.90, respectively.There are two studies that predict Luminal A, Luminal B and Her 2+molecular subtype by ultrasound radiology, but theycannot be synthesized quantitatively because of the small number of studies. Ultrasound radiomics has a gooddiagnostic performance in predicting molecular subtypes in breast cancer.

Intraoperative radiotherapy might not serve as a standard therapy for retroperitoneal liposarcoma: insights from a population-based propensity score-matched study.

Difficulty in achieving complete resection leads to a poor prognosis for retroperitoneal soft tissue sarcoma, hence emphasizing the significance of adjuvant treatment. The benefit of preoperative radiotherapy for retroperitoneal liposarcoma was initially demonstrated by the STRASS trial. However, the impact of intraoperative radiotherapy (IORT) on retroperitoneal liposarcoma remains unexplored. Patients with retroperitoneal liposarcoma were identified in the Surveillance, Epidemiology, and End Results (SEER) database, treated between 2000 and 2019. Subsequently, a 1:1 propensity score-matched (PSM) analysis was conducted based on variables identified from a multivariate analysis. T-tests were used to assess differences in normally distributed continuous variables, while the rank-sum test was applied to variables that did not follow a normal distribution. The chi-squared test was utilized to evaluate differences in categorical variables. Ultimately, survival analysis was performed using SPSS to evaluate patient prognosis. A total of 2129 patients with retroperitoneal liposarcoma were included in our study. Age, sex, histology, grading, chemotherapy, and tumor size as independent prognostic risk factors for these patients through multivariate Cox regression analysis. Subsequently, 66 patients were included in the survival analysis through PSM, with 33 patients receiving IORT. Finally, the survival analysis revealed that there was no difference in overall survival among patients with retroperitoneal liposarcoma, regardless of whether they received IORT or not (p= 0.711). As an exploratory study, our findings suggest that patients may not derive benefit from intraoperative radiotherapy. These observations are intended to lay the groundwork for future prospective clinical studies.

Prognostic nomograms for young breast cancer: A retrospective study based on the SEER and METABRIC databases.

Young breast cancer (YBC) is a subset of breast cancer that is often more aggressive, but less is known about its prognosis. In this study, we aimed to generate nomograms to predict the overall survival (OS) and breast cancer-specific survival (BCSS) of YBC patients. Data of women diagnosed with YBC between 2010 and 2020 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly allocated into a training cohort (n = 15,227) and internal validation cohort (n = 6,526) at a 7:3 ratio. With the Cox regression models, significant prognostic factors were identified and used to construct 3-, 5-, and 10-year nomograms of OS and BCSS. Data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database were used as an external validation cohort (n = 90). We constructed nomograms incorporating 10 prognostic factors for OS and BCSS. These nomograms demonstrated strong predictive accuracy for OS and BCSS in the training cohort, with C-indexes of 0.806 and 0.813, respectively. The calibration curves verified that the nomograms have good prediction accuracy. Decision curve analysis demonstrated their practical clinical value for predicting YBC patient survival rates. Additionally, we provided dynamic nomograms to improve the operability of the results. The risk stratification ability assessment also showed that the OS and BCSS rates of the low-risk group were significantly better than those of the high-risk group. Here, we generated and validated more comprehensive and accurate OS and BCSS nomograms than models previously developed for YBC. These nomograms can help clinicians evaluate patient prognosis and make clinical decisions.

The value of nomogram analysis in prediction of cerebral spread of hepatic alveolar echinococcosis

BackgroundThe prognosis after brain metastasis of alveolar echinococcosis is inferior, but there is currently no effective method to predict brain metastasis. PurposeTo explore the value of a nomogram constructed based on a CT plain scan and enhanced imaging features combined with clinical indicators in predicting brain metastasis of hepatic alveolar echinococcosis (HAE). Materials and MethodsThe imaging characteristics and clinical indicators of 116 patients diagnosed with HAE in the Affiliated Hospital of Qinghai University from 2015 to 2022 were retrospectively collected. The data were randomly divided into a training set and a validation set according to 7:3, and the difference between the two groups was analyzed. Binary logistic regression analysis was used to obtain independent predictors of brain metastasis in HAE, and a prediction model was constructed based on this and expressed in the form of a nomogram. Receiver operating characteristic (ROC) curve and calibration curve (CRC) were used to evaluate model performance, and decision curve analysis (DCA) was used to assess the clinical value of the predictive model. ResultA total of 116 HAE patients were included (average age 38.07±15.09 years old, 54 males and 62 females, 81 patients (70 %) in the training set, and 35 patients (30 %) in the validation set). There was no statistically significant difference between CT plain scan and enhanced imaging features combined with clinical indicators between the training set and the validation set (p > 0.05). After statistical analysis, it was found that whether there is invasion of the inferior vena cava, whether there is invasion of the hepatic artery, and whether there is metastasis to other organs are independent predictors of brain metastasis in HAE. A prediction model was built based on these three variables. The area under the ROC curve (AUC), cutoff value, sensitivity, and specificity of the training set and validation set were 0.922 and 0.886, 0.6934 and 0.6643, 75.00 and 84.62, 94.34 and 81.82, respectively. CRC shows good consistency between the predicted probability and the actual value of the sample. DCA showed that the clinical value of the model was high. ConclusionThe nomogram constructed based on imaging features combined with clinical indicators can effectively predict whether HAE will develop brain metastasis, which is helpful for clinicians to quickly screen out high-risk patients with HAE developing brain metastases, evaluate patient prognosis, and is more conducive to the realization of individualized and precise medical decisions.

DNA methylation biomarkers for predicting lymph node metastasis in colorectal cancer.

Colorectal cancer is one of the most common cancers worldwide. Lymph node metastasis is an important marker of colorectal cancer progression and plays a key role in the evaluation of patient prognosis. Accurate preoperative assessment of lymph node metastasis is crucial for devising appropriate treatment plans. However, current clinical imaging methods have limitations in many aspects. Therefore, the discovery of a method for accurately predicting lymph node metastasis is crucial clinical decision-making. DNA methylation is a common epigenetic modification that can regulate gene expression, which also has an important impact on the development of colorectal cancer. It is considered to be a promising biomarker with good specificity and stability and has promising application in predicting lymph node metastasis in patients with colorectal cancer. This article reviews the characteristics and limitations of currently available methods for predicting lymph node metastasis in patients with colorectal cancer and discusses the role of DNA methylation as a biomarker.

A Prospective Study of the Association of IL6 with the Critical Unit and Their Effect on in-Hospital Mortality in Critically Ill Patients.

We previously proposed a new concept, the "critical unit", which covers the structural integrity and function of mitochondria and endothelium. Injury of the critical unit plays a key role in the development of critical illnesses. High levels of inflammation may lead to abnormalities of the critical unit, which is an important mechanism for critical illnesses, and both inflammation and critical unit dysfunction may affect patient prognosis. Here we evaluated the correlation between interleukin-6 (IL6) and the critical unit biomarkers in critically ill patients and the impact of both on prognosis. This study included adult patients admitted to the intensive care unit for various reasons from January 1st to May 31st, 2023. Baseline characteristics, intensive care unit parameters, and laboratory test and outcome data were obtained from the electronic medical records system. Critical unit parameters were measured using polymerase chain reaction and enzyme-linked immunosorbent assay methods. Correlations were examined between IL6, critical unit parameters, and various outcomes. In critically ill patients, IL6 was closely associated with all the critical unit biomarkers (activated partial thromboplastin time, sphingosine 1-phosphate, mitochondrial DNA, mitochondrial fission 1, and Parkin) and the prognoses of patients. A nomogram was constructed using the critical unit biomarkers to predict the in-hospital mortality of critically ill patients. The area under the curve for the mortality prediction model was 0.708. In sensitivity analyses, the predictive effect was better in the non-surgery and tumor groups compared with the surgery and non-tumor groups, with area under the curve values of 0.885 and 0.891, respectively. Our study innovatively integrated mitochondrial and endothelial markers in the critical unit to comprehensively evaluate patient prognosis, which may be a trend in the future assessment of critically ill patients. There are few such studies, and ours may promote the progress of related research.

Oxidative stress-related genes score predicts prognosis and immune cell infiltration landscape characterization in breast cancer

BackgroundThe tumor microenvironment (TME) typically experiences oxidative stress (OS), marked by a high level of reactive oxygen species (ROS) that can impact tumor advancement and prognosis by modulating the behavior of tumor cells and various immune cells. Oxidative stress-related genes (OSRG) encompass a range of genes involved in ROS pathways, and their specific roles in breast cancer (BC) necessitate further investigation. MethodsUnivariate Cox analysis was performed on genes linked to the OS pathway in the Gene Set Enrichment Analysis (GSEA) database, leading to the identification of 29 significant OSRG in BC. OSRG was divided into three distinct clusters according to the expression and the OSRG score based on the differentially expressed genes (DEGs) was further calculated by principal component analysis (PCA). The correlation between OSRG score and BC clinical features, mutation characteristics, immune checkpoints and immune cell infiltration was analyzed. Establish a multiariable Cox regression model to predict OSRG score effects on clinical characteristics. ResultsSignificant differences were observed in survival analysis, enriched pathways, and immune infiltration among the three OSRG clusters based on 29 genes. Gene clusters were identified through the final selected 395 DEGs, revealing three distinct OSRG expression patterns. An OSRG score model was constructed using DEGs, demonstrating a significant association between high OSRG score and poor prognosis. Significantly, immune checkpoint-related genes exhibited a notable upregulation in the high OSRG score cohort. Additionally, a positive correlation was observed between the OSRG score and tumor mutation burden (TMB) in BC. The OSRG score holds potential implications for clinical immunotherapy in BC patients, and a nomogram was constructed with robust predictive capability for evaluating patient prognosis. ConclusionsThis study elucidated the features of OSRG within BC TME and their possible prognostic significance, offering valuable insights for the development of more targeted immunotherapy approaches for individuals with BC.

A dynamic online nomogram for predicting renal outcomes of idiopathic membranous nephropathy

BackgroundBecause spontaneous remission is common in IMN, and there are adverse effects of immunosuppressive therapy, it is important to assess the risk of progressive loss of renal function before deciding whether and when to initiate immunosuppressive therapy. Therefore, this study aimed to establish a risk prediction model to predict patient prognosis and treatment response to help clinicians evaluate patient prognosis and decide on the best treatment regimen.MethodsFrom September 2019 to December 2020, a total of 232 newly diagnosed IMN patients from three hospitals in Liaoning Province were enrolled. Logistic regression analysis selected the risk factors affecting the prognosis, and a dynamic online nomogram prognostic model was constructed based on extreme gradient boost, random forest, logistic regression machine learning algorithms. Receiver operating characteristic and calibration curves and decision curve analysis were utilized to assess the performance and clinical utility of the developed model.ResultsA total of 130 patients were in the training cohort and 102 patients in the validation cohort. Logistic regression analysis identified four risk factors: course ≥ 6 months, UTP, D-dimer and sPLA2R-Ab. The random forest algorithm showed the best performance with the highest AUROC (0.869). The nomogram had excellent discrimination ability, calibration ability and clinical practicability in both the training cohort and the validation cohort.ConclusionsThe dynamic online nomogram model can effectively assess the prognosis and treatment response of IMN patients. This will help clinicians assess the patient’s prognosis more accurately, communicate with the patient in advance, and jointly select the most appropriate treatment plan.

Construction and Validation of Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Patients with Primary Anaplastic Oligodendroglioma

Anaplastic oligodendroglioma (AOD) is a rare high-grade central nervous system tumor. The current research on prognostic prediction of AOD remains limited. This study aimed to identify prognostic factors and establish the nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with AOD. Patients diagnosed with AOD between 1992 and 2020 were extracted from the Surveillance, Epidemiology, and End Result database. We performed univariate and multivariate Cox regression analyses to identify independent prognostic factors based on the training group. Kaplan-Meier survival curves were used to compare the impact of various independent factors on patient prognosis. For OS and CSS, the nomograms were constructed and verified by the validation group. Harrell''s concordance index, receiver operating characteristic curves, calibration curves, and decision curve analyses were used to assess the discrimination, consistency, and clinical value of the nomograms. A total of 1202 AOD patients were enrolled, being randomly divided into training (n= 841) and validation (n= 361) groups (7:3 ratio). Univariate and multivariate Cox analysis identified 4 significant independent factors (tumor site, age, surgery, and chemotherapy). For OS and CSS, Harrell''s concordance index were 0.731 (0.705-0.757) and 0.728 (0.701-0.754) in the training group, 0.688 (0.646-0.731) and 0.684 (0.639-0.729) in the validation group, respectively. Receiver operating characteristic curves and Calibration curves showed good discrimination and consistency, respectively. In addition, the decision curve analyses curves showed the nomograms have good clinical benefits. We successfully established the nomograms to predict the OS and CSS for AOD patients. The nomograms showed good performance in prognostic prediction, assisting clinicians in evaluating patient prognosis and personalizing treatment plans.

Evaluation of Prognosis in Patients with Lung Adenocarcinoma with Atypical Solid Nodules on Thin-Section CT Images.

Purpose To evaluate the clinicopathologic characteristics and prognosis of patients with clinical stage IA lung adenocarcinoma with atypical solid nodules (ASNs) on thin-section CT images. Materials and Methods Data from patients with clinical stage IA lung adenocarcinoma who underwent resection between January 2005 and December 2012 were retrospectively reviewed. According to their manifestations on thin-section CT images, nodules were classified as ASNs, subsolid nodules (SSNs), and typical solid nodules (TSNs). The clinicopathologic characteristics of the ASNs were investigated, and the differences across the three groups were analyzed. The Kaplan-Meier method and multivariable Cox analysis were used to evaluate survival differences among patients with ASNs, SSNs, and TSNs. Results Of the 254 patients (median age, 58 years [IQR, 53-66]; 152 women) evaluated, 49 had ASNs, 123 had SSNs, and 82 had TSNs. Compared with patients with SSNs, those with ASNs were more likely to have nonsmall adenocarcinoma (P < .001), advanced-stage adenocarcinoma (P = .004), nonlepidic growth adenocarcinoma (P < .001), and middle- or low-grade differentiation tumors (P < .001). Compared with patients with TSNs, those with ASNs were more likely to have no lymph node involvement (P = .009) and epidermal growth factor receptor mutation positivity (P = .018). Average disease-free survival in patients with ASNs was significantly longer than that in patients with TSNs (P < .001) but was not distinguishable from that in patients with SSNs (P = .051). Conclusion ASNs were associated with better clinical outcomes than TSNs in patients with clinical stage IA lung adenocarcinoma. Keywords: Adenocarcinoma, Atypical Solid Nodules, CT, Disease-free Survival, Lung, Prognosis, Pulmonary Supplemental material is available for this article. Published under a CC BY 4.0 license.

Research Advancements on the Correlation Between Spontaneous Intracerebral Hemorrhage of Different Etiologies and Imaging Markers of Cerebral Small Vessel Disease.

The purpose of this review is to identify the correlation between ICH and CSVD imaging markers under SMASH-U classification by searching and analyzing a large number of literatures in recent years, laying a theoretical foundation for future clinical research. At the same time, by collecting clinical data to evaluate patient prognosis, analyzing whether there are differences or supplements between clinical trial conclusions and previous theories, and ultimately guiding clinical diagnosis and treatment through the analysis of imaging biomarkers. In this review, by searching CNKI, Web of Science, PubMed, FMRS and other databases, the use of "spontaneous intracerebral hemorrhage", "hypertensive hemorrhagic cerebral small vessel disease", "cerebral small vessel disease imaging", "Based cerebral small vessel diseases", "SMASH the -u classification" and their Chinese equivalents for the main search term. We focused on reading and analyzing hundreds of relevant literatures in the last decade from August 2011 to April 2020, and also included some earlier literatures with conceptual data sources. After screening and ranking the degree of relevance to this study, sixty of them were cited for analysis and elaboration. In patients with ICH, the number of cerebral microbleeds in lobes, basal ganglia, and the deep brain is positively correlated with ICH volume and independently correlated with neurological functional outcomes; white matter hyperintensity severity is positively correlated with ICH recurrence risk; multiple lacunar infarction independently predict the risk of ICH; severe brain atrophy is an independent risk factor for a poor prognosis in the long term in patients diagnosed with ICH; and the number of enlarged perivascular spaces is correlated with ICH recurrence. However, small subcortical infarct and ICH are the subject of few studies. Higher CSVD scores are independently associated with functional outcomes at 90 days in patients diagnosed with ICH.

A Multi-Center Randomized Controlled Study Using ΔPCO2/Ca-vO2 as the Target to Guide Early Tissue Hypoperfusion in Sepsis in Plateau Areas

Objective: To explore the value of using the venous-arterial carbon dioxide partial pressure difference and the arterial-venous oxygen content difference ratio (ΔPCO2/Ca-vO2) as targets to guide early tissue hypoperfusion in sepsis in plateau areas. Methods: 90 sepsis patients admitted to the Third People’s Hospital of Xining and Golmud People’s Hospital from June 2017 to December 2022 were selected as the research subjects, and they were divided into the ScvO2 (central venous oxygen saturation) group and the ΔPCO2/Ca-vO2 group, with 45 cases in each group. The two groups were treated with early shock resuscitation according to different protocols. The hemodynamic characteristics of the two groups of patients before and after resuscitation were observed, and the volume responsiveness was evaluated. The ROC (receiver operating characteristic) curve was used to analyze the significance of ΔPCO2/Ca-vO2, ScvO2, lactate, lactate clearance, and urine output in evaluating patient prognosis and the correlation between ΔPCO2/Ca-vO2 and the above indicators was explored. Results: Compared with before resuscitation, after fluid resuscitation, the heart rate (HR), mean arterial pressure (MAP), central venous pressure (CVP), cardiac index (CI), lactate, lactate clearance rate, and urine output of the two groups of patients were significantly improved (P &lt; 0.05); in terms of therapeutic effect, the 28-day mortality rate, 6-hour fluid balance, and lactic acid clearance of the ΔPCO2/Ca-vO2 group were better than the ScvO2 group. The ROC characteristic curve showed that the ΔPCO2/Ca-vO2 value can effectively predict the prognosis of patients (AUC = 0.907, sensitivity was 97%, specificity was 72.4%, and critical value was 1.84). ΔPCO2/Ca-vO2 significantly correlated with ScvO2, lactic acid, and lactic acid clearance rate. Conclusion: The ΔPCO2/Ca-vO2 value can be used to guide fluid resuscitation in early hypoperfusion in sepsis in plateau areas, improve patients’ hemodynamics, reduce lactate indicators, and increase urine output. ΔPCO2/Ca-vO2 level &gt; 1.84 can effectively improve patient prognosis.&#x0D; Corrigendum available at: https://www.doi.org/10.26689/jcnr.v8i2.6467

Nomogram for predicting the overall survival and cancer-specific survival of patients with intraductal carcinoma of the prostate

PurposeIntraductal carcinoma of the prostate (IDC-P) is a histological subtype that differs from conventional acinar adenocarcinoma in terms of its origin, appearance, and pathological features. For IDC-P, there is currently no recognized best course of action, and its prognosis is unclear. The goal of this study is to analyze independent prognostic factors in IDC-P patients and to develop and validate a nomogram to predict overall survival (OS) and cancer-specific survival (CSS).MethodsClinical data for IDC-P patients were collected from the Surveillance, Epidemiology, and End Results database. To identify the independent variables influencing prognosis, multivariate Cox regression analysis was performed. A nomogram model was created utilizing these variables after comparing the variations in OS and CSS among various subgroups using Kaplan‒Meier curves. Internal validation of the nomograms was verified using the bootstrap resampling method.ResultsThe study included 280 IDC-P patients in total. Marital status, summary stage, grade, and the presence of lung metastases were significant factors impacting OS, and CSS was significantly influenced by marital status, summary stage, AJCC stage, the presence of lung metastases, the presence of bone metastases, and PSA according to univariate and multivariate Cox regression models (P < 0.05). Nomogram models were created to estimate OS and CSS using these parameters. The OS prediction model’s C-index was 0.744, whereas the CSS prediction model’s C-index was 0.831.ConclusionWe developed and verified nomogram models for the prediction of 1-, 3-, and 5-year OS and CSS in patients with IDC-P. These nomograms serve as a resource for evaluating patient prognosis, therapy, and diagnosis, ultimately improving clinical decision-making accuracy.

The integration of multi-omics analysis and machine learning for the identification of prognostic assessment and immunotherapy efficacy through aging-associated genes in lung cancer.

Recent years revealed key molecules in lung cancer research, yet their exact roles in disease onset and progression remain uncertain. Lung cancer's heterogeneity complicates prognosis prediction. This study integrates pivotal molecules to evaluate patient prognosis and immunotherapy efficacy. The WGCNA algorithm identified module genes linked to immunity. The Lasso-Cox method built a prognostic model for outcome prediction. GO and KEGG analyses explored gene pathways. ssGSEA quantified immune cell types and functions. The riskScore predicts the effectiveness of immunotherapy based on its correlation with DNA repair and immune checkpoint genes. Single-cell sequencing examined key gene expression across cell types. Using WGCNA, we identified the MEbrown module related to immunity. Lasso-Cox selected "BLK," "ITGB4," "PRKCH," and "SNAI1" for the prognostic model. MF analysis revealed enriched functions including antigen binding, GTPase regulator activity. In terms of BP, processes like immune signaling and mitotic division were enriched. CC enrichment included immunoglobulin complexes and chromosomal regions. Enriched pathways encompassed Cell cycle, Focal adhesion, Cellular senescence, and p53 signaling. ssGSEA evaluated immune cell abundance. RiskScore correlated with CTLA4 and PD1 through MMR and immune checkpoint analysis. Single-cell analysis indicated gene expression across cell types for BLK, ITGB4, PRKCH, and SNAI1. In summary, our developed prognostic model utilizing age-related genes effectively predicts lung cancer prognosis and the efficacy of immune therapy.

Calculated haemorheological profile and laboratory parameters in new diagnosed multiple myeloma patients: retrospective analysis according to survival.

Multiple myeloma is a malignant haematological neoplasm characterised by clonal proliferation of plasma cells, with a complex clinical picture, and a significant impact on patient survival, in which the prognosis evaluation of patients is of great importance. In this single-centre retrospective analysis, performed in a group of newly diagnosed multiple myeloma patients, we examined several clinical and laboratory parameters in order to evaluate their trend according to survival of patients. We collected data from 190 newly diagnosed multiple myeloma evaluated at the Hematology Division of the 'Paolo Giaccone' University Hospital of Palermo from 1 January 2017 to 30 September 2022. Specifically, we performed our analysis in the entire cohort of patients and also in the specific disease isotype. We evaluated simple and low-cost laboratory and haemorheological parameters, the latter obtained in a calculated way. The primary endpoint was to evaluate the trend and the differences of these parameters in the study population, divided into two specific groups, deceased and survivors after a specific observation period of almost 7 years. In the entire cohort of multiple myeloma patients, we observed a mortality rate of 40%, of whom 36.4% were men and 43.1% were women. Among the patients who died, in comparison with those who survived, it is significantly evident the increase in age, in red cell distribution width (RDW), RDW%/albumin ratio and in the RDW%/haemoglobin ratio; moreover, in the same patients subgroup, we observed a reduction in haematocrit, total serum protein, calculated whole blood viscosity (evaluated according to the de Simone formula), serum albumin, albumin/fibrinogen ratio and in haemoglobin levels. The obtained data can represent a possible starting point for subsequent targeted analyses, aimed at studying the prognostic value of each individual parameter considered, favouring an increasingly complete and immediate prognostic evaluation of patients.

Correlation between serum IL-22 and IL-27 levels and vasculopathy in diabetic nephropathy patients.

To explore the correlation between serum interleukin-22 (IL-22) and interleukin-27 (IL-27) levels and vasculopathy in patients with diabetic nephropathy (DN). A total of 104 DN patients treated at the Shanxi University of Traditional Chinese Medicine Affiliated Hospital were selected as the observation group, with another 104 healthy individuals, serving as the control group in this retrospective study. The baseline data and the serum levels of IL-22 and IL-27 were compared between the two groups. The observation group was divided into three subgroups based on their urinary albumin excretion rate (UAER): clinical albuminuria group (microangiopathy, 29 patients), microalbuminuria group (51 patients), and normal albuminuria group (24 patients). Logistic regression was used to analyze the factors influencing the occurrence of microangiopathy. According to whether they had major adverse cardiovascular events (MACE) during 6-month follow-up, the DN patients were divided into a MACE group (n = 39) and a non-MACE group (n = 65). The serum levels of IL-22 and IL-27 were then compared between the two groups. The clinical utility of IL-22 and IL-27 in the assessment of microangiopathy and prognosis was evaluated through receiver operating characteristic (ROC) curve analysis. Compared to the control group, the observation group exhibited significantly higher serum levels of fasting blood glucose, glycated hemoglobin, total cholesterol, triglycerides, low-density lipoprotein, uric acid, blood creatinine, cystatin C, IL-22 and IL-27, but lower glomerular filtration rate (all P<0.05). There were significant differences among different albuminuria groups in terms of duration of disease, serum levels of fasting blood glucose, low-density lipoprotein, cystatin C, IL-22, IL-27, and glomerular filtration rate (all P<0.05). Correlation analysis showed that the serum levels of IL-22 and IL-27 were positively correlated with the duration of disease and serum levels of fasting blood glucose, low-density lipoprotein, uric acid, blood creatinine and cystatin C. However, they were negatively correlated with glomerular filtration rate (P<0.05). The logistic regression analysis indicated that the glomerular filtration rate and serum levels of cystatin C, IL-22, and IL-27 were independent risk factors for the occurrence of microangiopathy. Compared to non-MACE group, the MACE group presented with higher serum IL-22 and IL-27 levels. ROC curve analysis showed that the AUC (Area Under the Curve) for combined detection (>0.9) of serum IL-22 and IL-27 levels was higher than that (>0.8) for each alone in assessing microangiopathy in DN patients. Additionally, the AUC for using serum IL-22 and IL-27 levels, whether individually or in combination, exceeded 0.7 when evaluating patient prognosis. Elevated serum IL-22 and IL-27 levels are closely associated with the severity of the DN and can serve as auxiliary indicators for assessing microangiopathy and prognosis in DN patients.

A practical online prediction platform to predict the survival status of laryngeal squamous cell carcinoma after 5 years

ObjectiveCurrently, there are few practical tools for predicting the prognosis of laryngeal squamous cell carcinoma (LSCC). This study aims to establish a model and a convenient online prediction platform to predict whether LSCC patients will survive 5 years after diagnosis, providing a reference for further evaluation of patient prognosis. MethodsThis is a retrospective study based on data collected from two centers. Center 1 included 117 LSCC patients with survival prognosis data, and center 2 included 33 patients, totaling 150 patients. All data were divided into independent training sets (60 %) and testing sets (40 %). Eight machine learning (ML) algorithms were used to establish models with 11 clinical parameters as input features. The accuracy, sensitivity, specificity, and receiver operating characteristic curve (ROC) of the testing set were used to evaluate the models, and the best model was selected. The model was then developed into a website-based 5-year survival status prediction platform for LSCC. In addition, we also used the SHapley Additive exPlanations (SHAP) tool to conduct interpretability analysis on the parameters of the model. ResultsThe LSCC 5-year survival status prediction model using the support vector machine (SVM) algorithm achieved the best results, with accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of 85.0 %, 87.5 %, 75.0 %, and 81.2 % respectively. The online platform for predicting the 5-year survival status of LSCC based on this model was successfully established. The SHAP analysis shows that the clinical stage is the most important feature of the model. ConclusionThis study successfully established a ML model and a practical online prediction platform to predict the survival status of laryngeal cancer patients after 5 years, which may help clinicians to better evaluate the prognosis of LSCC. Level of evidence3.

Expression of PTP4A1 in circulating tumor cells and its efficacy evaluation in patients with early- and intermediate-stage esophageal cancer.

The objective of this study is to investigate the expression of protein tyrosine phosphatase type I (PTP4A1) in circulating tumor cells (CTCs) in patients with early- and intermediate-stage esophageal cancer and its clinical value in evaluating patient prognosis. Tissue and peripheral blood samples were collected from patients with esophageal cancer, as well as their clinical data. Follow-up was performed on all patients. PTP4A1 expression in the CTCs of patients were analyzed by regression analysis, and its correlation with the clinical characteristics of esophageal cancer was discussed. The numbers of mixed tumor cells and T-CTCs were significantly correlated with lymph node metastasis. Advanced tumor-node metastasis (TNM) stage (odds ratio = 12.063) and lymph node metastasis (odds ratio = 13.541) were influencing factors of PTP4A1+MCTC expression disorders in patients with esophageal cancer. The receiver operating characteristic curve showed that TNM stage and lymph node metastasis had a high predictive efficiency for PTP4A1+MCTCs, with an area under the ROC curve of 0.725. PTP4A1+mixed tumor cells had strong predictive value for the efficacy of neoadjuvant therapy, with a sensitivity of 94.7% and a specificity of 63.6%. Advanced TNM stage and lymph node metastasis are influencing factors for increased CTCs and poor expression of PTP4A1 in patients with esophageal cancer.