Impact of tumor size on overall survival and cancer-specific survival of early-onset colon and rectal cancer: a retrospective cohort study.

PURPOSE: This study aimed to investigate the impact of tumor size on survival in early-onset colon and rectal cancer. METHODS: Early-onset colon and rectal cancer patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Tumor size was analyzed as both continuous and categorical variables. Several statistical techniques, including restricted cubic spline (RCS), Cox proportional hazard model, subgroup analysis, propensity score matching (PSM), and Kaplan-Meier survival analysis, were employed to demonstrate the association between tumor size and overall survival (OS) and cancer-specific survival (CSS) of early-onset colon and rectal cancer. RESULTS: Seventeen thousand five hundred fifty-one (76.7%) early-onset colon and 5323 (23.3%) rectal cancer patients were included. RCS analysis confirmed a linear association between tumor size and survival. Patients with a tumor size > 5 cm had worse OS and CSS, compared to those with a tumor size ≤ 5 cm for both early-onset colon and rectal cancer. Notably, subgroup analysis showed that a smaller tumor size (≤ 50 mm) was associated with worse survival in stage II early-onset colon cancer, although not statistically significant. After PSM, Kaplan-Meier survival curves showed that the survival of patients with tumor size ≤ 50 mm was better than that of patients with tumor size > 50 mm. CONCLUSION: Patients with tumors larger than 5 cm were associated with worse survival in early-onset colon and rectal cancer. However, smaller tumor size may indicate a more biologically aggressive phenotype, correlating with poorer survival in stage II early-onset colon cancer.

Clinico-pathological study of esophageal mucoepidermoid carcinoma: a 10-year survival from a single center.

BACKGROUND: Mucoepidermoid Carcinoma of the Esophagus (MECE) is a relatively rare tumor type, with most of the current data derived from case reports or small sample studies. This retrospective study reports on the 10-year survival data and detailed clinicopathological characteristics of 48 patients with esophageal MEC. METHODS: Data were collected from 48 patients who underwent curative surgery for esophageal MEC at the Fourth Hospital of Hebei Medical University between January 1, 2004, and December 31, 2020. These were compared with contemporaneous cases of Esophageal Squamous Cell Carcinoma (ESCC) and Esophageal Adenocarcinoma (EAC). Using the Kaplan-Meier method and multivariate Cox regression analysis, we investigated the clinicopathological factors affecting the survival of patients with MEC. RESULTS: The incidence of MECE was predominantly higher in males, with a male-to-female ratio of approximately 7:1. The mid-thoracic segment emerged as the most common site of occurrence. A mere 6.3% of cases were correctly diagnosed preoperatively. The lymph node metastasis rate stood at 35.4%. The overall 1-year, 3-year, 5-year, and 10-year survival rates for all patients were 85.4%, 52.1%, 37.0%, and 31.0%, respectively. Post 1:1 propensity score matching, no significant statistical difference was observed in the Overall Survival (OS) between MEC patients and those with Esophageal Squamous Cell Carcinoma (ESCC) and Esophageal Adenocarcinoma (EAC) (P = 0.119, P = 0.669). Univariate analysis indicated that T staging and N staging were the primary factors influencing the prognosis of esophageal MEC. CONCLUSIONS: MECE occurs more frequently in males than females, with the mid-thoracic segment being the most common site of occurrence. The rate of accurate preoperative endoscopic diagnosis is low. The characteristic of having a short lesion length yet exhibiting significant extramural invasion may be a crucial clinicopathological feature of MECE. The OS of patients with MEC does not appear to significantly differ from those with esophageal squamous carcinoma and adenocarcinoma.

Real-world efficacy of adjuvant therapy for totally resected stage I lung adenocarcinoma patients with pathological high-risk factors: propensity score analysis.

BACKGROUND: We investigated the real-world efficacy of adjuvant therapy for stage I lung adenocarcinoma patients with pathological high-risk factors. METHODS: Study participants were enrolled from November 1, 2016 and December 31, 2020. Clinical bias was balanced by propensity score matching. Disease-free survival (DFS) outcomes were compared by Kaplan-Meier analysis. The Cox proportional hazards regression was used to identify survival-associated factors. p ≤ 0.05 was the threshold for statistical significance. RESULTS: A total of 454 patients, among whom 134 (29.5%) underwent adjuvant therapy, were enrolled in this study. One hundred and eighteen of the patients who underwent adjuvant therapy were well matched with non-treatment patients. Prognostic outcomes of the treatment group were significantly better than those of the non-treatment group, as revealed by Kaplan-Meier analysis after PSM. Differences in prevention of recurrence or metastasis between the targeted therapy and chemotherapy groups were insignificant. Adjuvant therapy was found to be positive prognostic factors, tumor size and solid growth patterns were negative. CONCLUSIONS: Adjuvant therapy significantly improved the DFS for stage I lung adenocarcinoma patients with high-risk factors. Larger prospective clinical trials should be performed to verify our findings.

A Competing Risk Nomogram for Prediction of Prognosis in Patients With Primary Squamous Cell Thyroid Carcinoma.

Objective: Primary squamous cell thyroid carcinoma (PSCTC) is an extremely rare carcinoma, accounting for less than 1% of all thyroid carcinomas. However, the factors contributing to PSCTC outcomes remain unclear. This study aimed to identify the prognostic factors and develop a prognostic predictive model for patients with PSCTC. Methods: The analysis included patients diagnosed with thyroid carcinoma between 1975 and 2016 from the Surveillance, Epidemiology, and End Results database. Prognostic differences among the 5 pathological types of thyroid carcinomas were analyzed. To determine prognostic factors in PSCTC patients, the Cox regression model and Fine-Gray competing risk model were utilized. Based on the Fine-Gray competing risk model, a nomogram was established for predicting the prognosis of patients with PSCTC. Results: A total of 198,757 thyroid carcinoma patients, including 218 PSCTC patients, were identified. We found that PSCTC and anaplastic thyroid cancer had the worst prognosis among the 5 pathological types of thyroid carcinoma (P < .001). According to univariate and multivariate Cox regression analyses, age (71-95 years) was an independent risk factor for poorer overall survival and disease-specific survival in PSCTC patients. Using Fine-Gray regression analysis, the total number of in situ/malignant tumors for patient (Number 1) (≥2) was identified as an independent protective factor for prognosis of PSCTC. The area under the curve, the concordance index (C-index), calibration curves and decision curve analysis revealed that the nomogram was capable of predicting the prognosis of PSCTC patients accurately. Conclusion: The competing risk nomogram is highly accurate in predicting prognosis for patients with PSCTC, which may help clinicians to optimize individualized treatment decisions.

Identification of Breast Cancer Subtypes Based on Endoplasmic Reticulum Stress-Related Genes and Analysis of Prognosis and Immune Microenvironment in Breast Cancer Patients.

Introduction: Endoplasmic reticulum stress (ERS) was a response to the accumulation of unfolded proteins and plays a crucial role in the development of tumors, including processes such as tumor cell invasion, metastasis, and immune evasion. However, the specific regulatory mechanisms of ERS in breast cancer (BC) remain unclear. Methods: In this study, we analyzed RNA sequencing data from The Cancer Genome Atlas (TCGA) for breast cancer and identified 8 core genes associated with ERS: ELOVL2, IFNG, MAP2K6, MZB1, PCSK6, PCSK9, IGF2BP1, and POP1. We evaluated their individual expression, independent diagnostic, and prognostic values in breast cancer patients. A multifactorial Cox analysis established a risk prognostic model, validated with an external dataset. Additionally, we conducted a comprehensive assessment of immune infiltration and drug sensitivity for these genes. Results: The results indicate that these eight core genes play a crucial role in regulating the immune microenvironment of breast cancer (BRCA) patients. Meanwhile, an independent diagnostic model based on the expression of these eight genes shows limited independent diagnostic value, and its independent prognostic value is unsatisfactory, with the time ROC AUC values generally below 0.5. According to the results of logistic regression neural networks and risk prognosis models, when these eight genes interact synergistically, they can serve as excellent biomarkers for the diagnosis and prognosis of breast cancer patients. Furthermore, the research findings have been confirmed through qPCR experiments and validation. Conclusion: In conclusion, we explored the mechanisms of ERS in BRCA patients and identified 8 outstanding biomolecular diagnostic markers and prognostic indicators. The research results were double-validated using the GEO database and qPCR.

Sex differences in prognosis factors in patients with lung cancer: A nationwide retrospective cohort study in Korea.

Large-scale studies elucidating sex differences in factors impacting prognosis and sex-specific prognossis factors scoring in patients with lung cancer are insufficient. The present study aimed to develop a model to predict sex-specific prognosis factors in Korean patients with lung cancer. This nationwide cohort study included 96,255 patients aged ≥19 years diagnosed with lung cancer and underwent Korean National Health Insurance Service health examinations between January 1, 2005 and December 31, 2015 and followed until 2020. Factors associated with prognosis were estimated using multivariable Cox proportional hazards regression analyses, and separate prognosis scores were calculated for male and female patients. The sex-specific risk scoring models were validated with Kaplan-Meier survival curves and c-statistic. During a mean follow-up of 2.8 years, 60.5% of the patients died. In male patients with lung cancer, age ≥ 65 years (24 points) had the highest mortality risk score, followed by chemotherapy in combination with radiotherapy (16 points), chemotherapy (14 points), and radiotherapy (11 points). In female patients with lung cancer, chemotherapy in combination with radiotherapy (19 points) had the highest mortality risk score, followed by chemotherapy (16 points), age ≥ 65 years (13 points), and radiotherapy (13 points). The analysis of patients categorized into three risk groups based on risk scores revealed that the fatality rates within 5 years were 7%, 54%, and 89% in the low-, intermediate-, and high-risk groups for male patients and 3%, 46%, 85% in the low-, intermediate-, and high-risk groups for female patients, respectively. The c-statistic was 0.86 for male patients and 0.85 for female patients. The strongest fatality risk factors in lung cancer were age ≥ 65 years in male patients and chemotherapy in female patients. The present study developed sex-specific prognosis scoring models to predict fatality risk in patients with lung cancer.

Ambient air pollution as a time-varying covariate in the survival probability of childhood cancer patients in the upper Northern Thailand.

The objective of this study is to determine the possible association between exposure to air pollution and the risk of death from cancer during childhood in upper northern Thailand. Data were collected on children aged 0-15 years old diagnosed with cancer between January 2003 and December 2018 from the Chiang Mai Cancer Registry. Survival rates were determined by using Kaplan-Meier curves. Cox proportional hazard models were used to investigate associations of potential risk factors with the time-varying air pollution level on the risk of death. Of the 540 children with hematologic cancer, 199 died from any cause (overall mortality rate = 5.3 per 100 Person-Years of Follow-Up (PYFU); 95%CI = 4.6-6.0). Those aged less than one year old (adjusted hazard ratio [aHR] = 2.07; 95%CI = 1.25-3.45) or ten years old or more (aHR = 1.41; 95%CI = 1.04-1.91) at the time of diagnosis had a higher risk of death than those aged one to ten years old. Those diagnosed between 2003 and 2013 had an increased risk of death (aHR = 1.65; 95%CI = 1.13-2.42). Of the 499 children with solid tumors, 214 died from any cause (5.9 per 100 PYFU; 95%CI = 5.1-6.7). Only the cancer stage remained in the final model, with the metastatic cancer stage (HR = 2.26; 95%CI = 1.60-3.21) and the regional cancer stage (HR = 1.53; 95%CI = 1.07-2.19) both associated with an increased risk of death. No association was found between air pollution exposure and all-cause mortality for either type of cancer. A larger-scale analytical study might uncover such relationships.

Identification and validation of a prognostic anoikis-related gene signature in papillary thyroid carcinoma by integrated analysis of single-cell and bulk RNA-sequencing.

Papillary thyroid carcinoma (PTC) prognosis may be deteriorated due to the metastases, and anoikis palys an essential role in the tumor metastasis. However, the potential effect of anoikis-related genes on the prognosis of PTC was unclear. The mRNA and clinical information were obtained from the cancer genome atlas database. Hub genes were identified and risk model was constructed using Cox regression analysis. Kaplan-Meier (K-M) curve was applied for the survival analysis. Immune infiltration and immune therapy response were calculated using CIBERSORT and TIDE. The identification of cell types and cell interaction was performed by Seurat, SingleR and CellChat packages. GO, KEGG, and GSVA were applied for the enrichment analysis. Protein-protein interaction network was constructed in STRING and Cytoscape. Drug sensitivity was assessed in GSCA. Based on bulk RNA data, we identified 4 anoikis-related risk signatures, which were oncogenes, and constructed a risk model. The enrichment analysis found high risk group was enriched in some immune-related pathways. High risk group had higher infiltration of Tregs, higher TIDE score and lower levels of monocytes and CD8 T cells. Based on scRNA data, we found that 4 hub genes were mainly expressed in monocytes and macrophages, and they interacted with T cells. Hub genes were significantly related to immune escape-related genes. Drug sensitivity analysis suggested that cyclin dependent kinase inhibitor 2A may be a better chemotherapy target. We constructed a risk model which could effectively and steadily predict the prognosis of PTC. We inferred that the immune escape may be involved in the development of PTC.

IL-6 significantly correlated with the prognosis in low-grade glioma and the mediating effect of immune microenvironment.

To screen immune-related prognostic biomarkers in low-grade glioma (LGG), and reveal the potential regulatory mechanism. The differential expressed genes (DEGs) between alive and dead patients were initially identified, then the key common genes between DEGs and immune-related genes were obtained. Regarding the key DEGs associated with the overall survival (OS), their clinical value was assessed by Kaplan-Meier, RCS, logistic regression, ROC, and decision curve analysis methods. We also assessed the role of immune infiltration on the association between key DEGs and OS. All the analyses were based on the TGCA-LGG data. Finally, we conducted the molecular docking analysis to explore the targeting binding of key DEGs with the therapeutic agents in LGG. Among 146 DEGs, only interleukin-6 (IL-6) was finally screened as an immune-related biomarker. High expression of IL-6 significantly correlated with poor OS time (all P < .05), showing a linear relationship. The combination of IL-6 with IDH1 mutation had the most favorable prediction performance on survival status and they achieved a good clinical net benefit. Next, we found a significant relationship between IL-6 and immune microenvironment score, and the immune microenvironment played a mediating effect on the association of IL-6 with survival (all P < .05). Detailly, IL-6 was positively related to M1 macrophage infiltration abundance and its biomarkers (all P < .05). Finally, we obtained 4 therapeutic agents in LGG targeting IL-6, and their targeting binding relationships were all verified. IL6, as an immune-related biomarker, was associated with the prognosis in LGG, and it can be a therapeutic target in LGG.

THOC6 is a novel biomarker of glioma and a target of anti-glioma drugs: An analysis based on bioinformatics and molecular docking.

Glioma is a typical malignant tumor of the nervous system. It is of great significance to identify new biomarkers for accurate diagnosis of glioma. In this context, THOC6 has been studied as a highly diagnostic prognostic biomarker, which contributes to improve the dilemma in diagnosing gliomas. We used online databases and a variety of statistical methods, such as Wilcoxon rank sum test, Dunn test and t test. We analyzed the mutation, location and expression profile of THOC6, revealing the network of THOC6 interaction with disease. Wilcoxon rank sum test showed that THOC6 is highly expressed in gliomas (P < 0.001). Dunn test, Wilcoxon rank sum test and t test showed that THOC6 expression was correlated with multiple clinical features. Logistic regression analysis further confirmed that THOC6 gene expression was a categorical dependent variable related to clinical features of poor prognosis. Kaplan-Meier survival analysis showed that the overall survival (OS) of glioma patients with high expression of THOC6 was poor (P < 0.001). Both univariate (P < 0.001) and multivariate (P = 0.04) Cox analysis confirmed that THOC6 gene expression was an independent risk factor for OS in patients with glioma. ROC curve analysis showed that THOC6 had a high diagnostic value in glioma (AUC = 0.915). Based on this, we constructed a nomogram to predict patient survival. Enrichment analysis showed that THOC6 expression was associated with multiple signal pathways. Immuno-infiltration analysis showed that the expression of THOC6 in glioma was closely related to the infiltration level of multiple immune cells. Molecular docking results showed that THOC6 might be the target of anti-glioma drugs. THOC6 is a novel diagnostic factor and prognostic biomarker of glioma.

Choline metabolism reprogramming mediates an immunosuppressive microenvironment in non-small cell lung cancer (NSCLC) by promoting tumor-associated macrophage functional polarization and endothelial cell proliferation.

INTRODUCTION: Lung cancer is a prevalent malignancy globally, and immunotherapy has revolutionized its treatment. However, resistance to immunotherapy remains a challenge. Abnormal cholinesterase (ChE) activity and choline metabolism are associated with tumor oncogenesis, progression, and poor prognosis in multiple cancers. Yet, the precise mechanism underlying the relationship between ChE, choline metabolism and tumor immune microenvironment in lung cancer, and the response and resistance of immunotherapy still unclear. METHODS: Firstly, 277 advanced non-small cell lung cancer (NSCLC) patients receiving first-line immunotherapy in Sun Yat-sen University Cancer Center were enrolled in the study. Pretreatment and the alteration of ChE after 2 courses of immunotherapy and survival outcomes were collected. Kaplan-Meier survival and cox regression analysis were performed, and nomogram was conducted to identify the prognostic and predicted values. Secondly, choline metabolism-related genes were screened using Cox regression, and a prognostic model was constructed. Functional enrichment analysis and immune microenvironment analysis were also conducted. Lastly, to gain further insights into potential mechanisms, single-cell analysis was performed. RESULTS: Firstly, baseline high level ChE and the elevation of ChE after immunotherapy were significantly associated with better survival outcomes for advanced NSCLC. Constructed nomogram based on the significant variables from the multivariate Cox analysis performed well in discrimination and calibration. Secondly, 4 choline metabolism-related genes (MTHFD1, PDGFB, PIK3R3, CHKB) were screened and developed a risk signature that was found to be related to a poorer prognosis. Further analysis revealed that the choline metabolism-related genes signature was associated with immunosuppressive tumor microenvironment, immune escape and metabolic reprogramming. scRNA-seq showed that MTHFD1 was specifically distributed in tumor-associated macrophages (TAMs), mediating the differentiation and immunosuppressive functions of macrophages, which may potentially impact endothelial cell proliferation and tumor angiogenesis. CONCLUSION: Our study highlights the discovery of ChE as a prognostic marker in advanced NSCLC, suggesting its potential for identifying patients who may benefit from immunotherapy. Additionally, we developed a prognostic signature based on choline metabolism-related genes, revealing the correlation with the immunosuppressive microenvironment and uncovering the role of MTHFD1 in macrophage differentiation and endothelial cell proliferation, providing insights into the intricate workings of choline metabolism in NSCLC pathogenesis.

Clinical Outcomes and Prognostic Factors in Stage III C Cervical Cancer Patients Treated with Radical Radiotherapy or Radiochemotherapy.

Objective: Since the update of the 2018 International Federation of Gynecology and Obstetrics (FIGO) staging criteria, there have been few reports on the prognosis of stage III C cervical cancer. Moreover, some studies have drawn controversial conclusions, necessitating further verification. This study aims to evaluate the clinical outcomes and determine the prognostic factors for stage III C cervical cancer patients treated with radical radiotherapy or radiochemotherapy. Methods: The data of 117 stage III C cervical cancer patients (98 III C1 and 19 III C2) who underwent radical radiotherapy or radiochemotherapy were retrospectively analyzed. We evaluated 3-year overall survival (OS) and disease-free survival (DFS) using the Kaplan-Meier method. Prognostic factors were analyzed using the Log-rank test and Cox proportional hazard regression model. The risk of para-aortic lymph node metastasis (LNM) in all patients was assessed through Chi-squared test and logistic regression analysis. Results: For stage III C1 and III C2 patients, the 3-year OS rates were 77.6% and 63.2% (P = .042), and the 3-year DFS rates were 70.4% and 47.4% (P = .003), respectively. The pretreatment location of pelvic LNM, histological type, and FIGO stage was associated with OS (P = .033, .003, .042, respectively); the number of pelvic LNM and FIGO stage were associated with DFS (P = .015, .003, respectively). The histological type was an independent prognostic indicator for OS, and the numbers of pelvic LNM and FIGO stage were independent prognostic indicators for DFS. Furthermore, a pelvic LNM largest short-axis diameter ≥ 1.5 cm and the presence of common iliac LNM were identified as high-risk factors influencing para-aortic LNM in stage III C patients (P = .046, .006, respectively). Conclusions: The results of this study validated the 2018 FIGO staging criteria for stage III C cervical cancer patients undergoing concurrent chemoradiotherapy. These findings may enhance our understanding of the updated staging criteria and contribute to better management of patients in stage III C.

Clinical significance of the lactate-to-albumin ratio on prognosis in critically ill patients with acute kidney injury.

OBJECTIVE: To explore the relationship between lactate-to-albumin ratio (LAR) at ICU admission and prognosis in critically ill patients with acute kidney injury (AKI). METHODS: A retrospective analysis was conducted. Patients were divided into low (<0.659) LAR and high LAR (≥0.659) groups. Least absolute shrinkage and selection operator regression analysis was conducted to select variables associated with the 30-day prognosis. Cox regression analyses were performed to assess the association between LAR and mortality. Kaplan-Meier curves were plotted to compare cumulative survival rates between high and low LAR groups. Subgroup analysis was employed to assess the stability of the results. ROC curve was used to determine the diagnostic efficacy of LAR on prognosis. RESULTS: A nonlinear relationship was observed between LAR and the risk of 30-day and 360-day all-cause mortality in AKI patients (p < 0.001). Cox regulation showed that high LAR (≥ 0.659) was an independent risk factor for 30-day and 360-day all-cause mortality in patients with AKI (p < 0.001). The Kaplan-Meier survival curves demonstrated a noteworthy decrease in cumulative survival rates at both 30 and 360 days for the high LAR group in comparison to the low LAR group (p < 0.001). Subgroup analyses demonstrated the stability of the results. ROC curves showed that LAR had a diagnostic advantage when compared with lactate or albumin alone (p < 0.001). CONCLUSION: High LAR (≥0.659) at ICU admission was an independent risk factor for both short-term (30-day) and long-term (360-day) all-cause mortality in patients with AKI.

A nomogram based on nutritional and inflammatory parameters to predict DMFS and identify beneficiaries of adjuvant chemotherapy in IVA-stage nasopharyngeal carcinoma.

OBJECTIVE: This study aims to develop a nomogram integrating inflammation (NLR), Prognostic Nutritional Index (PNI), and EBV DNA (tumor burden) to achieve personalized treatment and prediction for stage IVA NPC. Furthermore, it endeavors to pinpoint specific subgroups that may derive significant benefits from S-1 adjuvant chemotherapy. METHODS: A total of 834 patients diagnosed with stage IVA NPC were enrolled in this study and randomly allocated into training and validation cohorts. Multivariate Cox analyses were conducted to identify independent prognostic factors for constructing the nomogram. The predictive and clinical utility of the nomogram was assessed through measures including the AUC, calibration curve, DCA, and C-indexes. IPTW was employed to balance baseline characteristics across the population. Kaplan-Meier analysis and log-rank tests were utilized to evaluate the prognostic value. RESULTS: In our study, we examined the clinical features of 557 individuals from the training cohort and 277 from the validation cohort. The median follow-up period was 50.1 and 49.7 months, respectively. For the overall cohort, the median follow-up duration was 53.8 months. The training and validation sets showed 3-year OS rates of 87.7% and 82.5%, respectively. Meanwhile, the 3-year DMFS rates were 95.9% and 84.3%, respectively. We created a nomogram that combined PNI, NRI, and EBV DNA, resulting in high prediction accuracy. Risk stratification demonstrated substantial variations in DMFS and OS between the high and low risk groups. Patients in the high-risk group benefited significantly from the IC + CCRT + S-1 treatment. In contrast, IC + CCRT demonstrated non-inferior 3-year DMFS and OS compared to IC + CCRT + S-1 in the low-risk population, indicating the possibility of reducing treatment intensity. CONCLUSIONS: In conclusion, our nomogram integrating NLR, PNI, and EBV DNA offers precise prognostication for stage IVA NPC. S-1 adjuvant chemotherapy provides notable benefits for high-risk patients, while treatment intensity reduction may be feasible for low-risk individuals.

Aspartate Transaminase-to-Albumin Ratio (ATAR), a Novel Prognostic Index, Predicts Outcomes in Patients with Small-Cell Lung Cancer.

BACKGROUND: Small cell lung cancer (SCLC) is characterized by high invasion rates, rapid progression, and poor prognoses. Thus, identifying SCLC patients at high risk of progression and death is critical to improve long-term survival. In this study, the aspartate transaminase-to-albumin ratio (ATAR) was examined as a prognostic factor for SCLC patients. METHODS: We screened 196 SCLC patients from December 2013 to September 2022 at the Sichuan Cancer Hospital. The data was collected from patients' medical information as well as from their blood results during diagnosis. Using the Youden index as a cutoff value, patients were divided into high-risk（> 0.54) and low-risk (≤ 0.54) ATAR groups. We analyzed the prognostic factors for overall survival (OS) using the Kaplan-Meier method, univariate and multivariate analyses, Cox regression, and the C-index. RESULTS: There were 109 (55.6%) smokers among the patients, and the median OS was 17.55 months. The Kaplan-Meier analysis indicated that patients with high-risk ATAR had significantly lower OS (p < 0.0001). A multivariate analysis demonstrated that elevated ATAR is an independent adverse predictor of OS (p < 0.001, HR = 1.907). Our study found that ATAR is an independent predictor of survival outcomes in SCLC, which was superior to ALB, PNI, and SII in predicting outcomes in low-risk and high-risk groups (all p < 0.05). Models combining ATAR with ALB, PNI, and SII showed more powerful prognostic value than their corresponding original models. Moreover, the prognostic indicator ATAR can significantly stratify stage I - II and III - IV SCLC patients (p ＜ 0.05). CONCLUSIONS: Peripheral blood ATAR prognostic index can be used as an independent predictor of SCLC patients before treatment.

Hsa_Circ_0002762 may be a New Marker for the Gastric Cancer Diagnosis and Prognosis.

BACKGROUND: The global incidence and mortality rate of gastric carcinoma (GC) persists at elevated levels, often manifesting no overt symptoms in its early stages. Hsa_circ_0002762 has been identified as an important modulator in cervical cancer. This study aims to explore its role in the context of GC. METHODS: A quantitative real-time polymerase chain reaction (qPCR) was implemented to assess the expression level of hsa_circ_0002762. The over-expression was confirmed through an examination of 28 cases of gastric cancer and their corresponding adjacent tissues. In addition, plasma samples from 78 healthy individuals, from 45 benign gastritis patients, and from 106 gastric cancer patients were collected, and the diagnostic efficacy was assessed by analyzing the receiver operating characteristic (ROC) curve. Simultaneously, postoperative specimens from 36 GC cases were collected, and a Kaplan-Meier survival analysis curve was used to evaluate the prognosis of GC. RESULTS: The study revealed an up-regulation in the expression of hsa_circ_0002762 in gastric cancer plasma and tissues. The area under the receiver operating characteristic (ROC) curve for serum hsa_circ_0002762 was 0.784 (95% CI: 0.719 - 0.851), indicating a higher diagnostic efficiency compared to CEA (0.687, 95% CI: 0.611 - 0.763) and CA199 (0.699, 95% CI: 0.625 - 0.744). Combining these three biomarkers demonstrated an increased sensitivity in the diagnostic effectiveness. Finally, postoperative dynamic monitoring revealed a practical utility in predicting the clinical prognosis using serum has_circ_0002762. CONCLUSIONS: The findings from our study suggest that hsa_circ_0002762 holds promise as a novel diagnostic and prognostic marker for individuals with GC.

CD3, CD8, IFN-γ, tumor and stroma inflammatory cells as prognostic indicators for surgically resected SCLC: evidences from a 10-year retrospective study and immunohistochemical analysis.

Current clinical guidelines limit surgical intervention to patients with cT1-2N0M0 small cell lung cancer (SCLC). Our objective was to reassess the role of surgery in SCLC management, and explore novel prognostic indicators for surgically resected SCLC. We reviewed all patients diagnosed with SCLC from January 2011 to April 2021 in our institution. Survival analysis was conducted using the Kaplan-Meier method, and independent prognostic factors were assessed through the Cox proportional hazard model. In addition, immunohistochemistry (IHC) staining was performed to evaluate the predictive value of selected indicators in the prognosis of surgically resected SCLC patients. In the study, 177 SCLC patients undergoing surgical resection were ultimately included. Both univariate and multivariate Cox analysis revealed that incomplete postoperative adjuvant therapy emerged as an independent risk factor for adverse prognosis (p < 0.001, HR 2.96). Survival analysis revealed significantly superior survival among pN0-1 patients compared to pN2 patients (p < 0.0001). No significant difference in postoperative survival was observed between pN1 and pN0 patients (p = 0.062). Patients with postoperative stable disease (SD) exhibited lower levels of tumor inflammatory cells (TIC) (p = 0.0047) and IFN-γ expression in both area and intensity (p < 0.0001 and 0.0091, respectively) compared to those with postoperative progressive disease (PD). Conversely, patients with postoperative SD showed elevated levels of stromal inflammatory cells (SIC) (p = 0.0453) and increased counts of CD3+ and CD8+ cells (p = 0.0262 and 0.0330, respectively). Survival analysis indicated that high levels of SIC, along with low levels of IFN-γ+ cell area within tumor tissue, may correlate positively with improved prognosis in surgically resected SCLC (p = 0.017 and 0.012, respectively). In conclusion, the present study revealed that the patients with pT1-2N1M0 staging were a potential subgroup of SCLC patients who may benefit from surgery. Complete postoperative adjuvant therapy remains an independent factor promoting a better prognosis for SCLC patients undergoing surgical resection. Moreover, CD3, CD8, IFN-γ, TIC, and SIC may serve as potential indicators for predicting the prognosis of surgically resected SCLC.

Hospitalization and mortality in Asian autoimmune bullous dermatosis patients: A 17-year retrospective study.

Limited data exist on the factors associated with hospitalization and mortality in Asian inpatients with autoimmune bullous dermatoses (AIBDs). This study aimed to elucidate the risk factors affecting hospitalization and mortality rates in Asian patients with AIBDs. A retrospective analysis of patients with AIBDs treated at Siriraj Hospital during a 17-year period was performed using the International Classification of Diseases 10th revision codes. The characteristics of inpatients and outpatients were compared, and mortality rates and associated factors were identified. The study included 360 AIBD patients (180 inpatients, 180 outpatients). Inpatients were significantly younger than outpatients. The identified risk factors for hospitalization were malignancy (odds ratio [OR] 2.83, 95% confidence interval [CI] 1.13-8.04; p = 0.034), moderate to severe disease (OR 2.52, 95% CI 1.49-4.34; p < 0.001), systemic corticosteroid use ≥15 mg/day (OR 2.27, 95% CI 1.21-4.41; p = 0.013) and oral cyclophosphamide treatment (OR 9.88, 95% CI 3.82-33.7; p < 0.001). Kaplan-Meier analysis revealed mortality rates of 26%, 36% and 39% for inpatients with pemphigus at 1, 3 and 5 years, respectively. For inpatients with pemphigoid, the corresponding rates were 28%, 38% and 47%. Infections, particularly pneumonia, were the predominant cause of death in both conditions. This study confirmed that both Asian ethnicity and healthcare disparities may be correlated with adverse outcomes in patients with AIBDs. Pemphigus mortality rates were substantially greater in Asian patients than in Caucasian patients. Continuous monitoring of factors contributing to hospitalization and mortality is imperative to improve treatment outcomes.

Effect of chemotherapy on prognosis in patients with primary pancreatic signet ring cell carcinoma: A large real-world study based on machine learning.

BACKGROUND: Primary pancreatic signet ring cell carcinoma (PSRCC), an extremely rare histologic variant of pancreatic cancer, has a poor prognosis. This study aimed to investigate the prognostic value of chemotherapy in PSRCC. METHODS: Patients with PSRCC between 2000 and 2019 were identified using the Surveillance Epidemiology and End Results (SEER) database. The main outcomes in this study were cancer-specific survival (CSS) and overall survival (OS). The baseline characteristics of patients were compared using Pearson's Chi-square test. Kaplan-Meier analysis was used to generate the survival curves. Least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression models, and Random Survival Forest model were used to analyze the prognostic variables for OS and CSS. The variance inflation factors (VIFs) were used to analyze whether there was an overfitting problem. RESULTS: A total of 588 patients were identified. Chemotherapy was an independent prognostic factor for OS and CSS, and significantly associated with OS (HR = 0.33, 95% CI = 0.27-0.40, P <0.001) and CSS (HR = 0.32, 95% CI = 0.26-0.39, P <0.001). CONCLUSIONS: Chemotherapy showed beneficial effects on OS and CSS in patients with PSRCC and should be recommended in clinical practice.

Time to Death and Its Predictors among Neonates Hospitalized with Sepsis in Eastern Ethiopia.

Background: Although neonatal sepsis is a major public health problem contributing to 30-50% of neonatal deaths in low- and middle-income countries, data on predictors of time to death are limited in Eastern Ethiopia. This study is aimed at determining predictors of time to death among neonates with sepsis admitted in public hospitals in Eastern Ethiopia. Methods: An institutional-based retrospective cohort study was conducted among 415 neonates admitted to referral hospitals in Eastern Ethiopia with sepsis from January 1, 2021, to December 31, 2021. Data were collected from medical records by using structured checklist and entered using EpiData 3.1 and analyzed using Stata 17. The Kaplan-Meier curves and log-rank tests were used to describe survival experience among different categories. The proportional hazard assumption and goodness of fit for the Cox regression model were checked. The Cox regression model was used to identify the significant predictors. Hazard ratios (HRs) with 95% confidence intervals (CI) were calculated. Finally, statistical significance was set at a p value < 0.05 in the Cox regression analysis. Results: Of the 415 neonates with neonatal sepsis, 71 (17.1%) (95% CI: 13.60-21.08) died at discharge, with a median time to death of 14 days. The overall incidence rate of mortality was 36.5 per 1000 neonate days. Low birthweight (AHR = 2.50; 95% CI: 1.15-5.44), maternal age ≥ 35 years (AHR = 3.17; 95% CI: 1.11, 9.04), low fifth-minute Apgar score (AHR: 2.32; 95% CI: 1.30-4.14), and late initiation of breastfeeding (AHR = 4.82; 95% CI: 1.40-16.65) were independent predictors of mortality among neonates with sepsis. Conclusions: Almost one in five neonates with sepsis died at discharge. Low birthweight, maternal age ≥ 35 years, low fifth-minute Apgar score, and late initiation of breastfeeding were predictors of mortality.