Prognostic Assessment Of Patients Research Articles

Evaluation of the value of combined thyroid function-related indexes in the prognosis prediction of patients with differentiated thyroid cancer.

This study aims to evaluate the prognostic significance of thyroid function-related indices in patients with differentiated thyroid cancer (DTC). This retrospective analysis included 90 patients diagnosed with DTC and treated at our hospital from January 2010 to January 2019. Patients were classified into 2 groups based on whole-body imaging results: 67 with a favorable prognosis and 23 with a poor prognosis. The study compared clinical data and thyroid function indices between these groups to assess their efficacy in prognostic prediction. Patients in the poor prognosis group had a higher occurrence of T3-4 stage cancer (P = .006) and ≥2 lymph node metastases (P = .019). Notably, levels of total thyroxine (TT4), thyroid-stimulating hormone (TSH), and thyroglobulin antibody (Tg-Ab) were significantly elevated in this group (P < .001 for each). Receiver operating characteristic analysis revealed substantial predictive accuracy for TT4, TSH, and Tg-Ab (area under curve of 0.747, 0.820, and 0.720, respectively). The columnar graphical model used for prediction demonstrated a high concordance index (C-index = 0.919), superior to single-indicator evaluations. Thyroid function indices, specifically TT4, TSH, and Tg-Ab, play a crucial role in the prognostic assessment of patients with DTC. The column-line diagram model effectively enhances prophetic prediction, aiding in clinical decision-making.

Pediatric diffuse intrinsic pontine glioma radiotherapy response prediction: MRI morphology and T2 intensity-based quantitative analyses.

An easy-to-implement MRI model for predicting partial response (PR) postradiotherapy for diffuse intrinsic pontine glioma (DIPG) is lacking. Utilizing quantitative T2 signal intensity and introducing a visual evaluation method based on T2 signal intensity heterogeneity, and compared MRI radiomic models for predicting radiotherapy response in pediatric patients with DIPG. We retrospectively included patients with brainstem gliomas aged ≤ 18 years admitted between July 2011 and March 2023. Applying Response Assessment in Pediatric Neuro-Oncology criteria, we categorized patients into PR and non-PR groups. For qualitative analysis, tumor heterogeneity vision was classified into four grades based on T2-weighted images. Quantitative analysis included the relative T2 signal intensity ratio (rT2SR), extra pons volume ratio, and tumor ring-enhancement volume. Radiomic features were extracted from T2-weighted and T1-enhanced images of volumes of interest. Univariate analysis was used to identify independent variables related to PR. Multivariate logistic regression was performed using significant variables (p < 0.05) from univariate analysis. Of 140 patients (training n = 109, and test n = 31), 64 (45.7%) achieved PR. The AUC of the predictive model with extrapontine volume ratio, rT2SRmax-min (rT2SRdif), and grade was 0.89. The AUCs of the T2-weighted and T1WI-enhanced models with radiomic signatures were 0.84 and 0.81, respectively. For the 31 DIPG test sets, the AUCs were 0.91, 0.83, and 0.81, for the models incorporating the quantitative features, radiomic model (T2-weighted images, and T1W1-enhanced images), respectively. Combining T2-weighted quantification with qualitative and extrapontine volume ratios reliably predicted pediatric DIPG radiotherapy response. Combining T2-weighted quantification with qualitative and extrapontine volume ratios can accurately predict diffuse intrinsic pontine glioma (DIPG) radiotherapy response, which may facilitate personalized treatment and prognostic assessment for patients with DIPG. Early identification is crucial for radiotherapy response and risk stratification in diffuse intrinsic pontine glioma. The model using tumor heterogeneity and quantitative T2 signal metrics achieved an AUC of 0.91. Using a combination of parameters can effectively predict radiotherapy response in this population.

Non-invasive tests for alcohol-associated liver disease.

Alcohol consumption is a global phenomenon and a major contributor to alcohol-associated liver disease (ALD). Detecting individuals at risk of ALD has been challenging, with only a small fraction of patients being identified at early stages compared to other chronic liver diseases. In response to this challenge, non-invasive tests (NITs) have become essential tools for the detection of ALD, offering opportunities for early identification and intervention to mitigate the disease burden. Non-invasive alcohol consumption biomarkers are crucial in estimating individuals' recent alcohol intake, providing valuable insights into their drinking patterns. Various NITs have been investigated for the initial screening of asymptomatic individuals at risk of ALD, as well as for identifying specific stages of the disease. These NITs are applied in two main clinical scenarios: population-based stratification for identifying and predicting liver-related symptoms, and diagnosing and prognosticating compensated cirrhosis or advanced chronic liver disease in secondary or tertiary care settings. Moreover, NITs play a significant role in the prognostic assessment of patients with various manifestations of ALD, including alcohol-associated hepatitis, decompensated cirrhosis, and metabolic and alcohol-associated liver disease. These tests guide appropriate treatment decisions and predict outcomes. In this review, various NITs for the early detection and monitoring of alcohol consumption were discussed. Additionally, the evaluation of NITs for screening and predicting ALD and liver complications was addressed comprehensively. Future perspectives of NITs for ALD were explored, alongside a thorough discussion of the opportunities and challenges associated with NITs for ALD screening.

Ultra-high b-value DWI accurately identifies isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas.

To distinguish isocitrate dehydrogenase (IDH) genotypes and tumor subtypes of adult-type diffuse gliomas based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) in 2021 using standard, high, and ultra-high b-value diffusion-weighted imaging (DWI). This prospective study enrolled 70 patients with adult-type diffuse gliomas who underwent multiple b-value DWI. Apparent diffusion coefficient (ADC) values including ADCb500/b1000, ADCb500/b2000, ADCb500/b3000, ADCb500/b4000, ADCb500/b6000, ADCb500/b8000, and ADCb500/b10000 in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The ADC ratios of TP/NAWM were assessed for correlations with IDH genotypes, tumor subtypes, and Ki-67 status; diagnostic performances were compared. All ADCs were significantly higher in IDHmutant gliomas than in IDH wild-type gliomas (p < 0.01 for all); ADCb500/b8000 had the highest area under the curve (AUC) of 0.866. All ADCs were significantly lower in glioblastoma than in astrocytoma (p < 0.01 for all). ADCs other than ADCb500/b1000 were significantly lower in glioblastoma than in oligodendroglioma (p < 0.05 for all). ADCb500/b8000 and ADCb500/b10000 were significantly higher in oligodendroglioma than in astrocytoma (p = 0.034 and 0.023). The highest AUCs were 0.818 for ADCb500/b6000 when distinguishing glioblastoma from astrocytoma, 0.979 for ADCb500/b8000 and ADCb500/b10000 when distinguishing glioblastoma from oligodendroglioma, and 0.773 for ADCb500/b10000 when distinguishing astrocytoma from oligodendroglioma. Additionally, all ADCs were negatively correlated with Ki-67 status (p < 0.05 for all). Ultra-high b-value DWI can reliably separate IDH genotypes and tumor subtypes of adult-type diffuse gliomas using WHO CNS5 criteria. Ultra-high b-value diffusion-weighted imaging can accurately distinguish isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas, which may facilitate personalized treatment and prognostic assessment for patients with glioma. • Ultra-high b-value diffusion-weighted imaging can accurately distinguish subtle differences in water diffusion among biological tissues. • Ultra-high b-value diffusion-weighted imaging can reliably separate isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. • Compared with standard b-value diffusion-weighted imaging, high and ultra-high b-value diffusion-weighted imaging demonstrate better diagnostic performances.

Role of hippo pathway and cuproptosis-related genes in immune infiltration and prognosis of skin cutaneous melanoma.

Melanoma is the most lethal type of skin cancer with an increasing incidence. Cuproptosis is the most recently identified copper-dependent form of cell death that relies on mitochondrial respiration. The hippocampal (Hippo) pathway functions as a tumor suppressor by regulating Yes-associated protein/transcriptional coactivator with PDZ-binding motif (YAP/TAZ) activity. However, its role in cuproptosis remains unknown. In addition, the correlation of cuproptosis-related genes and Hippo pathway-related genes with tumor prognosis warrants further investigation. In the present study, we explored the correlation of cuproptosis-related genes and Hippo pathway-related genes with the prognosis of melanoma through analysis of data from a public database and experimental verification. We found eight Hippo pathway-related genes that were downregulated in melanoma and exhibited predictive value for prognosis. There was a significant positive correlation between cuproptosis-related genes and Hippo pathway-related genes in skin cutaneous melanoma. YAP1 expression was positively correlated with ferredoxin 1 (FDX1) expression in the GSE68599 dataset and A2058 cells. Moreover, YAP1 was positively and negatively correlated with M2 macrophages and regulatory T cell infiltration, respectively. In conclusion, the present study demonstrated the prognostic value of Hippo pathway-related genes (particularly YAP1) in melanoma, revealing the correlation between the expression of Hippo pathway-related genes and immune infiltration. Thus, the present findings may provide new clues on the prognostic assessment of patients with melanoma and a new target for the immunotherapy of this disease.

Navigating Post-Operative Outcomes: A Comprehensive Reframing of an Original Graded Prognostic Assessment in Patients with Brain Metastases.

Graded Prognostic Assessment (GPA) has been proposed for various brain metastases (BMs) tailored to the primary histology and molecular profiles. However, it does not consider whether patients have been operated on or not and does not include surgical outcomes as prognostic factors. The residual tumor burden (RTB) is a strong predictor of overall survival. We validated the GPA score and introduced "volumetric GPA" in the largest cohort of operated patients and further explored the role of RTB as an additional prognostic factor. A total of 630 patients with BMs between 2007 and 2020 were included. The four GPA components were analyzed. The validity of the original score was assessed using Cox regression, and a modified index incorporating RTB was developed by comparing the accuracy, sensitivity, specificity, F1-score, and AUC parameters. GPA categories showed an association with survival: age (p < 0.001, hazard ratio (HR) 2.9, 95% confidence interval (CI) 2.5-3.3), Karnofsky performance status (KPS) (p < 0.001, HR 1.3, 95% CI 1.2-1.5), number of BMs (p = 0.019, HR 1.4, 95% CI 1.1-1.8), and the presence of extracranial manifestation (p < 0.001, HR 3, 95% CI 1.6-2.5). The median survival for GPA 0-1 was 4 months; for GPA 1.5-2, it was 12 months; for GPA 2.5-3, it was 21 months; and for GPA 3.5-4, it was 38 months (p < 0.001). RTB was identified as an independent prognostic factor. A cut-off of 2 cm3 was used for further analysis, which showed a median survival of 6 months (95% CI 4-8) vs. 13 months (95% CI 11-14, p < 0.001) for patients with RTB > 2 cm3 and <2 cm3, respectively. RTB was added as an additional component for a modified volumetric GPA score. The survival rates with the modified GPA score were: GPA 0-1: 4 months, GPA 1.5-2: 7 months, GPA 2.5-3: 18 months, and GPA 3.5-4: 34 months. Both scores showed good stratification, with the new score showed a trend towards better discrimination in patients with more favorable prognoses. The prognostic value of the original GPA was confirmed in our cohort of patients who underwent surgery for BM. The RTB was identified as a parameter of high prognostic significance and was incorporated into an updated "volumetric GPA". This score provides a novel tool for prognosis and clinical decision making in patients undergoing surgery. This method may be useful for stratification and patient selection for further treatment and in future clinical trials.

A matter of sex-persistent predictive value of MECKI score prognostic power in men and women with heart failure and reduced ejection fraction: a multicenter study.

A sex-based evaluation of prognosis in heart failure (HF) is lacking. We analyzed the Metabolic Exercise test data combined with Cardiac and Kidney Indexes (MECKI) score registry, which includes HF with reduced ejection fraction (HFrEF) patients. A cross-validation procedure was performed to estimate weights separately for men and women of all MECKI score parameters: left ventricular ejection fraction (LVEF), hemoglobin, kidney function assessed by Modification of Diet in Renal Disease, blood sodium level, ventilation vs. carbon dioxide production slope, and peak oxygen consumption (peakVO2). The primary outcomes were the composite of all-cause mortality, urgent heart transplant, and implant of a left ventricle assist device. The difference in predictive ability between the native and sex recalibrated MECKI (S-MECKI) was calculated using a receiver operating characteristic (ROC) curve at 2 years and a calibration plot. We retrospectively analyzed 7,900 HFrEF patients included in the MECKI score registry (mean age 61 ± 13 years, 6,456 men/1,444 women, mean LVEF 33% ± 10%, mean peakVO2 56.2% ± 17.6% of predicted) with a median follow-up of 4.05 years (range 1.72-7.47). Our results revealed an unadjusted risk of events that was doubled in men compared to women (9.7 vs. 4.1) and a significant difference in weight between the sexes of most of the parameters included in the MECKI score. S-MECKI showed improved risk classification and accuracy (area under the ROC curve: 0.7893 vs. 0.7799, p = 0.02) due to prognostication improvement in the high-risk settings in both sexes (MECKI score >10 in men and >5 in women). S-MECKI, i.e., the recalibrated MECKI according to sex-specific differences, constitutes a further step in the prognostic assessment of patients with severe HFrEF.

Kiosk 8R-FA-01 - Cardiovascular Magnetic Resonance for Precise Prognostic Assessment in Patients with Excessive Trabeculation of the Left Ventricle

Kiosk 8R-FA-01 - Cardiovascular Magnetic Resonance for Precise Prognostic Assessment in Patients with Excessive Trabeculation of the Left Ventricle

Advances in circulating tumor cells for early detection, prognosis and metastasis reduction in lung cancer.

Globally, lung cancer stands as the leading type of cancer in terms of incidence and is the major source of mortality attributed to cancer. We have outlined the molecular biomarkers for lung cancer that are available clinically. Circulating tumor cells (CTCs) spread from the original location, circulate in the bloodstream, extravasate, and metastasize, forming secondary tumors by invading and establishing a favorable environment. CTC analysis is considered a common liquid biopsy method for lung cancer. We have enumerated both in vivo and ex vivo techniques for CTC separation and enrichment, examined the advantages and limitations of these methods, and also discussed the detection of CTCs in other bodily fluids. We have evaluated the value of CTCs, as well as CTCs in conjunction with other biomarkers, for their utility in the early detection and prognostic assessment of patients with lung cancer. CTCs engage with diverse cells of the metastatic process, interfering with the interaction between CTCs and various cells in metastasis, potentially halting metastasis and enhancing patient prognosis.

Case Report: Mutation in TNNI3(c. 544G&gt;A): a novel likely pathogenic mechanism of neonatal dilated cardiomyopathy

BackgroundDilated cardiomyopathy (DCM) is a rare disease that causes heart failure due to malfunction of the heart muscle characterized by left ventricular dilation and poor systolic function. Genetic screening leads to advantages in early diagnosis and prognostic assessment of patients with suspected inherited cardiomyopathies. Here, we report a case of neonatal dilated cardiomyopathy due to a mutation of the TNNI3 gene, which has not been published in neonatal dilated cardiomyopathy before.Case presentationThe patient was a 22-day-old newborn boy with poor ability to respond to stimuli, presenting with shortness of breath over 11 days. He presented with irregular fever, tachypnea, difficulty in ventilator withdrawal, and mild edema of both lower limbs, and III/6SM could be heard in the precardiac area. He presented repeated weaning difficulties during hospitalization with intractable low EF heart insufficiency. Doppler echocardiography showed refractory low ejection fraction, cardiac enlargement, cardiac insufficiency, mild pulmonary hypertension, and mitral and tricuspid insufficiency with mild valve regurgitation. Whole-exome sequencing showed a mutation in the TNNI3 gene, c. 544G&amp;gt;A (p.Glu182Lys). Thus, he was diagnosed with neonatal DCM. There was no mutation in the parents, the child died 2 weeks after discharge.ConclusionsTNNI3 mutation is a novel likely pathogenic mechanism of neonatal dilated cardiomyopathy. Therefore, systematic use of diagnostic tools, advanced risk models, and a deeper understanding of the mechanism are required to reduce morbidity and mortality in this disease.

A Microfluidics-Based Multiplex SERS Immunoassay Device for Analysis of Acute Ischemic Stroke Biomarkers.

Sensitive and accurate methods for early detection of acute ischemic stroke (AIS) are essential for timely treatment and prognostic assessment of patients. In this study, we report a microfluidics-based ultrasensitive surface-enhanced Raman scattering (SERS) immunoassay device for the quantitative determination of multiplex biomarkers in AIS. By preparing 5,5'-dithiobis-2-nitrobenzoic acid (DTNB) antibody-modified gold nanoparticles (AuNPs) on SERS devices as SERS probes, the biomarkers in whole blood of AIS were accurately captured and further visualized for SERS signal intensity quantitative analysis of six biomarkers in the blood samples. It is worth mentioning that the limit of detection (LOD) of the method can reach the level of fg/mL, with excellent sensitivity and selectivity. Meanwhile, the analytical comparison with ELISA method showed that the detection results of both methods were consistent, which verified the feasibility of the assembled device. The SERS immunoassay device detection provides a powerful strategy for the prediction, early diagnosis and dynamic monitoring of prognosis of AIS with a wide range of clinical practice prospects.

Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms.

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.

Differences in apparent diffusion coefficient histogram analysis according to EGFR mutation status in brain metastasis due to lung adenocarcinoma.

The etiology, clinicopathological features, and prognosis of cancer in cases with EGFR mutations are different from those without mutations.OBJECTİVE:This study aims to evaluate the differences in ADC histogram analysis in brain metastases with EGFR mutation status in lung adenocarcinoma cases and the relationship between ADC histogram analysis differences and overall survival. In this retrospective case-control study, 30 patients (8 EGFR+/22 EGFR-) and 51 brain metastases (15 EGFR+/36 EGFR-) were included. ROI markings are first performed from each section, including metastasis in ADC mapping using FIREVOXEL software. Next, ADC histogram parameters are calculated. Overall survival analysis after brain metastasis (OSBM) is defined as the time from initial brain metastasis diagnosis to the time of death or last follow-up. Patient-based (by evaluating the largest lesion) and lesion-based (by evaluating all measurable lesions) statistical analyses are then performed. In the lesion-based analysis, skewness values are lower in EGFR+ patients, which is statistically significant (p = 0.012). The two groups have no significant difference regarding other ADC histogram analysis parameters, mortality, and overall survival (p > 0.05). In the ROC analysis, the most appropriate skewness cut-off value is determined as 0.321 to distinguish the EGFR mutation difference, and this value is statistically significant (sensitivity: 66.7%, specificity: 80.6%, AUC: 0.730) (p = 0.006).CONCLUSİON:The findings of this study provide valuable insights into the differences in ADC histogram analysis according to EGFR mutation status in brain metastases due to lung adenocarcinoma. The identified parameters, especially skewness, are potentially non-invasive biomarkers for predicting mutation status. Incorporating these biomarkers into routine clinical practice may aid treatment decision-making and prognostic assessment for patients. Further validation studies and prospective investigations are warranted to confirm the clinical utility of these findings and establish their potential for personalized therapeutic strategies and patient outcomes.

Nomogram for predicting cardiac death and heart transplantation in arrhythmogenic right ventricular cardiomyopathy.

In this study, we aimed to develop and validate a competing risk nomogram for predicting cardiac death and heart transplantation (HT) in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). We retrospectively enrolled 149 consecutive patients with ARVC diagnosed at our institution between 2008 and 2022. Cox proportional hazards model was primarily used to identify variables associated with cardiac death and HT. On the basis of these indicators, a competing risk nomogram was developed to predict the 1, 3, and 5 year probabilities of cardiac death and HT. The area under the receiver operating characteristic curve (AUC), Harrell's C-index, and calibration curves were used to evaluate and internally validate the performance of the model. Decision curve analysis was performed to assess the clinical utility of the nomogram. Of the 149 patients with ARVC, the mean age was 38.77 ± 15.94 years, and most of the patients were men (67.11%, 100/149). Fourteen patients experienced cardiac death and nine underwent HT, during a median follow-up period of 5.8 years (interquartile range, 0.62-5.56 years). Multivariable COX analysis revealed that extent of TWI in the anterior and inferior leads (P = 0.0057), right atrial diameter on transthoracic echocardiography (P = 0.0498), RVEF (P = 0.1036), and LVEF (P < 0.001) all showed statistical significance. The 1-, 3-, and 5-year cumulative incidence of cardiac death and HT were 3.35%, 8.05%, and 11.4%, respectively. The area under the receiver operating characteristic curve of the nomogram for predicting cardiac death and HT at 1, 3, and 5years after diagnosis of ARVC were 0.860, 0.935, and 0.956. The value of Harrell's C-index is 0.9273 (95% confidence interval 0.8954-0.9590; P<0.001), indicating that the model had good discriminative ability in internal validation. Decision curve analysis revealed that our model was clinically useful within the entire range of potential treatment thresholds in most cases. The cumulative incidence of the primary outcomes was significantly different between the three risk groups according to nomogram-derived scores (P<0.001). On the basis of a retrospective review of patients with ARVC at a single centre, we developed a novel nomogram for predicting the risk of cardiac death and HT after ARVC diagnosis. This competing risk nomogram based on four readily available clinical parameters (right atrial diameter, right and left ventricular ejection fraction, and T-wave inversion) is a potentially useful tool for individualized prognostic assessment in patients with ARVC.

Vitamin D and Mitosis Evaluation in Endometriosis: A Step toward Discovering the Connection?

(1) Background: The effects of serum vitamin D levels, the vitamin D receptor (VDR), and phosphohistone H3 (PHH3) in endometriosis were investigated in two cohorts of women with this pathology: those receiving hormonal treatment and those without treatment. (2) Methods: In 60 cases of women with endometriosis (26 with progestin treatment and 34 without), paraffin-embedded endometriosis tissue samples retrieved after surgery were immunohistochemically (IHC) analyzed to determine the expression statuses of VDR and PHH3. In addition, serum levels of 25(OH) vitamin D were assessed for each patient. (3) Results: The serum 25(OH) vitamin D evaluations revealed higher levels of 25(OH) vitamin D in women with treatment compared with those without. The positive IHC indexes of VDR and PHH3 in these two groups were compared. Vitamin D receptor levels were positively correlated with PHH3 levels, both being increased in patients without treatment. (4) Conclusions: Serum 25(OH) vitamin D levels and IHC analysis of VDR and PHH3 can be used as additional tools for risk stratification and prognostic assessment in patients with endometriosis.

Integrating scRNA and bulk-RNA sequencing develops a cell senescence signature for analyzing tumor heterogeneity in clear cell renal cell carcinoma.

Cellular senescence (CS) plays a critical role in cancer development, including clear cell renal cell carcinoma (ccRCC). Traditional RNA sequencing cannot detect precise molecular composition changes within tumors. This study aimed to analyze cellular senescence's biochemical characteristics in ccRCC using single RNA sequencing (ScRNA-seq) and traditional RNA sequencing (Bulk RNA-seq). Researchers analyzed the biochemical characteristics of cellular senescence in ccRCC using ScRNA-seq and Bulk RNA-seq. They combined these approaches to identify differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Genes from these pathways were used to identify molecular subtypes associated with senescence, and a new risk model was constructed. The function of the gene DUSP1 in ccRCC was validated through biological experiments. The combined analysis of ScRNA-seq and Bulk RNA-seq revealed significant differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Researchers identified genes from these pathways to identify molecular subtypes associated with senescence, constructing a new risk model. Different subgroups showed significant differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity. Senescence signature markers are practical biomarkers and predictors of molecular typing in ccRCC. Differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity between different subgroups indicate that this approach could provide valuable insights into senescence-related treatment options and prognostic assessment for patients with ccRCC. The function of the gene DUSP1 in ccRCC was validated through biological experiments, confirming its feasibility as a novel biomarker for ccRCC. These findings suggest that targeted therapies based on senescence-related mechanisms could be an effective treatment option for ccRCC.

Machine learning was used to predict risk factors for distant metastasis of pancreatic cancer and prognosis analysis.

The mechanisms of distant metastasis in pancreatic cancer (PC) have not been elucidated, and this study aimed to explore the risk factors affecting the metastasis and prognosis of metastatic patients and to develop a predictive model. Clinical data from patients meeting criteria from 1990 to 2019 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and two machine learning methods, random forest and support vector machine, combined with logistic regression, were used to explore risk factors influencing distant metastasis and to create nomograms. The performance of the model was validated using calibration curves and ROC curves based on the Shaanxi Provincial People's Hospital cohort. LASSO regression and Cox regression models were used to explore the independent risk factors affecting the prognosis of patients with distant PC metastases. We found that independent risk factors affecting PC distant metastasis were: age, radiotherapy, chemotherapy, T and N; the independent risk factors for patient prognosis were: age, grade, bone metastasis, brain metastasis, lung metastasis, radiotherapy and chemotherapy. Together, our study provides a method for risk factors and prognostic assessment for patients with distant PC metastases. The nomogram we developed can be used as a convenient individualized tool to facilitate aid in clinical decision making.

Differences in Gut Microbiota between Healthy Individuals and Patients with Perianal Abscess before and after Surgery.

Surgery is the most important treatment for perianal abscesses. However, the gut microbiota of patients with perianal abscess and the effects of perianal abscess on the gut microbiota after surgery are unknown. In this study, significant changes in interleukin 6 and tumor necrosis factor-α in the blood of healthy subjects, patients with perianal abscesses, and patients after perianal abscess surgery were identified. 16S rRNA gene sequencing technology was used to detect the changes in the gut microbiota among 30 healthy individuals and 30 patients with perianal abscess before and after surgery. Venn diagrams and alpha diversity analyses indicated differences in the abundance and uniformity of gut microbiota between the healthy individuals and patients with perianal abscesses before and after surgery. Beta diversity analysis indicated that the grouping effects among the control, abscess, and surgery groups were good. The classification and compositional analysis showed significant differences in the gut microbiota between healthy individuals and patients with perianal abscesses before and after surgery. LEfSe analysis, random forest analysis, and ROC curve analysis showed that Klebsiella (AUC = 0.7467) and Bilophila (AUC = 0.72) could be potential biomarkers for the diagnosis of perianal abscess. The functional prediction results showed that the differential microbiota is significantly enriched in the pathways related to nutrition and drug metabolism. This study may have important implications for the clinical management and prognostic assessment of patients with perianal abscesses.

Prognostic assessment in patients operated for brain metastasis from systemic tumors.

Established models for prognostic assessment in patients with brain metastasis do not stratify for prior surgery. Here we tested the prognostic accuracy of the Graded Prognostic Assessment (GPA) score model in patients operated for BM and explored further prognostic factors. We included 285 patients operated for brain metastasis at the University Hospital Zurich in the analysis. Information on patient characteristics, imaging, staging, peri- and postoperative complications and survival were extracted from the files and integrated into a multivariate Cox hazard model. The GPA score showed an association with outcome. We further identified residual tumor after surgery (p = 0.007, hazard ratio (HR) 1.6, 95% confidence interval (CI) 1.1-2.3) steroid use (p = 0.021, HR 1.7, 95% CI 1.1-2.6) and number of extracranial metastasis sites (p = 0.009, HR 1.4, 95% CI 1.1-1.6) at the time of surgery as independent prognostic factors. A trend was observed for postoperative infection of the subarachnoid space (p = 0.102, HR 3.5, 95% CI 0.8-15.7). We confirm the prognostic capacity of the GPA score in a cohort of operated patients with brain metastasis. However, extent of resection and steroid use provide additional aid for the prognostic assessment in these patients.

Application of Quantitative Computed Tomographic Perfusion in the Prognostic Assessment of Patients with Aneurysmal Subarachnoid Hemorrhage Coexistent Intracranial Atherosclerotic Stenosis

The comorbidity of aneurysmal subarachnoid hemorrhage (aSAH) with intracranial atherosclerotic stenosis (ICAS) has been suggested to increase the risk of postoperative ischemic stroke. Logistic regression models were established to explore the association between computed tomography perfusion (CTP) parameters and 3-month neurological outcomes and delayed cerebral ischemia (DCI). Prognostic-related perfusion parameters were added to the existing prognostic prediction models to evaluate model performance improvement. Tmax > 4.0 s volume > 0 mL was significantly associated with 3-month unfavorable neurological outcomes after adjusting for potential confounders (OR 3.90, 95% CI 1.11-13.73), whereas the stenosis degree of ICAS was not. Although the cross-validated area under the curve (AUC) was similar after the addition of the Tmax > 4.0 s volume > 0 mL (SAHIT: p = 0.591; TAPS: p = 0.379), the continuous net reclassification index (cNRI) and integrated discrimination index (IDI) showed that the perfusion parameters significantly improved the performance of the two models (p < 0.001 for all comparisons). Patients with coexistent aSAH and ICAS, Tmax > 4.0 s volume > 0 mL is an independent factor of 3-month neurological outcomes. A quantitative assessment of cerebral perfusion may help accurately screen patients with poor outcomes due to the coexistence of aSAH and ICAS.