Lower Chance Of Survival Research Articles

Applications of different machine learning approaches in prediction of breast cancer diagnosis delay.

The increasing rate of breast cancer (BC) incidence and mortality in Iran has turned this disease into a challenge. A delay in diagnosis leads to more advanced stages of BC and a lower chance of survival, which makes this cancer even more fatal. The present study was aimed at identifying the predicting factors for delayed BC diagnosis in women in Iran. In this study, four machine learning methods, including extreme gradient boosting (XGBoost), random forest (RF), neural networks (NNs), and logistic regression (LR), were applied to analyze the data of 630 women with confirmed BC. Also, different statistical methods, including chi-square, p-value, sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC), were utilized in different steps of the survey. Thirty percent of patients had a delayed BC diagnosis. Of all the patients with delayed diagnoses, 88.5% were married, 72.1% had an urban residency, and 84.8% had health insurance. The top three important factors in the RF model were urban residency (12.04), breast disease history (11.58), and other comorbidities (10.72). In the XGBoost, urban residency (17.54), having other comorbidities (17.14), and age at first childbirth (>30) (13.13) were the top factors; in the LR model, having other comorbidities (49.41), older age at first childbirth (82.57), and being nulliparous (44.19) were the top factors. Finally, in the NN, it was found that being married (50.05), having a marriage age above 30 (18.03), and having other breast disease history (15.83) were the main predicting factors for a delayed BC diagnosis. Machine learning techniques suggest that women with an urban residency who got married or had their first child at an age older than 30 and those without children are at a higher risk of diagnosis delay. It is necessary to educate them about BC risk factors, symptoms, and self-breast examination to shorten the delay in diagnosis.

Survival and Duration Analysis of MSMEs in Chiang Mai, Thailand: Evidence from the Post-COVID-19 Recovery

This study attempts to reveal the consequences of coronavirus disease 2019 (COVID-19) on micro, small, and medium enterprises (MSMEs) in Chiang Mai, Thailand. A total of 786 MSMEs were surveyed during May and August 2022, corresponding to the period when the recovery of businesses and livelihoods from the ongoing COVID-19 crisis became more perceptible. The perceptions of COVID-19’s impact on MSMEs and their survivability are explored and investigated. To achieve this goal, a copula-based sample selection survival model is introduced. This idea of the model is extended from the concept of the Cox proportional hazards model and copula-based sample selection model, enabling us to construct simultaneous equations—namely, the probability-of-failure equation (selection equation) and the duration-of-survival equation (time-to-event or outcome equation). Several copula functions with different dependence patterns are considered to join the failure equation and the duration-of-survival equation. By comparing the Akaike and Bayesian information criteria values of the candidate copulas, we find that Farlie–Gumbel–Morgenstern (FGM) copula performs the best-fit joint function in our analysis. Empirically, the results from this best-fit model reveal that the survival probability of MSMEs in the next year is around 80%. However, some MSMEs may not survive more than three months after the interview. Finally, our results also reveal that the tourism MSMEs have a lower chance of survival than the commercial and manufacturing MSMEs. Notably, the business size and the support schemes from the government—such as the debt restructuring process, the tax payment deadline extension, and the reduced social security contributions—exhibited a role in lengthening the survival duration of the non-surviving MSMEs.

Recent antibiotic reduces cancer survival after immune checkpoint inhibitors by 12%, study results show

People with cancer, who have taken antibiotics in the year before starting therapy with immune checkpoint inhibitors (ICIs), have a reduced chance of the therapy working and a lower chance of survival, research suggests. A Canadian cohort study looked at records from 2,737 people who had taken ICIs for cancer between June 2012 and October 2018. […]

Delayed treatment initiation and its associated factors among cancer patients at Northwest Amhara referral hospital oncology units: A cross-sectional study

BackgroundCancer is one of the major non-communicable diseases that impose an enormous burden both in low and middle-income countries. A cancer patient’s chance of survival is mainly determined by the time to treatment initiation, and when it is delayed, there is a lower chance of survival. Therefore, the objective of this study was to assess the magnitude of delayed cancer treatment initiation and its associated factors among patients at the oncology units of Northwest Amhara referral hospitals. MethodsAn institution-based cross-sectional study was conducted among 423 cancer patients enrolled in treatment between April 3, 2018, and August 13, 2021, at Northwest Amhara referral hospital oncology units. A systematic random sampling technique was applied to select study participants. The data was analyzed with Stata 14.1. A binary logistic regression model was fitted to identify factors associated with delayed cancer treatment initiation at a p-value < 0.05. ResultsOut of 415 patients included in the analysis, 275 (66.3%) were females, and the median age was 46 years (IQR: 40–54 years). The magnitude of delayed cancer treatment initiation was nearly 43%, and associated with the lowest wealth index level (AOR = 2.26; 95% CI: 1.03–4.94), body mass index (BMI) ≥ 25 kg/m2 (AOR = 3.38; 95% CI: 1.11–10.31), presence of comorbid illness (AOR = 2.07; 95% CI: 1.33–3.22), and Eastern Cooperative Oncology Group (ECOG) performance score of two (AOR = 2.78; 95% CI: 1.29–5.94). ConclusionA significant proportion of cancer patients were delayed in starting treatment. But it could be addressed by providing information about the negative consequences of delay.

A more conservative test of sex differences in the treatment and outcome of in-hospital cardiac arrest

BackgroundStudies investigating sex disparities related to treatment and outcome of in-hospital cardiac arrest (IHCA) have produced divergent findings and have typically been unable to adjust for outstanding confounding variables. ObjectivesThe aim was to examine sex differences in treatment and survival following IHCA, using a comprehensive set of control variables including e.g., age, comorbidity, and patient-level socioeconomic status. MethodsThis retrospective study was based on data from the Swedish Register of Cardiopulmonary Resuscitation and Statistics Sweden. In the primary analyses, logistic regression models and ordinary least square regressions were estimated. ResultsThe study included 24,217 patients and the majority (70.4%) were men. In the unadjusted analyses, women had a lower chance of survival after cardiopulmonary resuscitation (CPR) attempt, at hospital discharge (with good neurological function) and at 30 days (p<0.01). In the adjusted regression models, female sex was associated with a higher chance of survival after the CPR attempt (B = 1.09, p<0.01) and at 30-days (B = 1.09, p<0.05). In contrast, there was no significant association between sex and survival to discharge with good neurological outcome. Except for treatment duration (B=-0.07, p<0.01), no significant associations between sex and treatment were identified. ConclusionsNo signs of treatment disparities or discrimination related to sex were identified. However, women had a better chance of surviving IHCA compared to men. The finding that women went from having a survival disadvantage (unadjusted analysis) to a survival advantage (adjusted analysis) attests to the importance of including a comprehensive set of control variables, when examining sex differences.

PATTERNS OF AGING CHANGES IN BODY WEIGHT AND BMI MAY PREDICT CHANCES OF ALZHEIMER'S DISEASE AND LONGEVITY

Abstract Background Lower bodyweight/BMI was previously linked to AD and frailty; however, the role of long-term changes in the bodyweight/BMI in both AD and longevity is not well understood, as is the role of APOE polymorphism in such changes. Methods Using longitudinal data from the Framingham Heart Study (FHS) and the Health and Retirement Study (HRS), we estimated trajectories of the weight and BMI at ages 40 to 75, and compared them between individuals who did and who did not develop AD at ages 75+. We also evaluated associations between APOE4 carrier status and key characteristics of the age-trajectories of weight/BMI, including the age at peak value of the bodyweight/BMI (AgeMax), and slope of the decline in bodyweight/BMI after reaching the maximum. Results Women with late-onset-AD had lower bodyweight/BMI values up to three decades before AD diagnosis. They reached the peak of bodyweight in their 50s, about 10 years earlier than AD-free women. Younger AgeMax was associated with lower survival chances after age 80 in women. APOE4 carriers showed earlier/faster declines in weight and BMI than non-carriers; however, relevance of this to AD was unclear. Conclusion Younger age at peak value of the bodyweight/BMI indicates higher chances of late-onset-AD, while older age can predict better survival later in life and may favor longevity in women. The earlier start of the decline in bodyweight/BMI values could be sign of accelerated aging, which may contribute to AD. Relevance of APOE4 effects on age-trajectories of weight/BMI to AD warrants further investigation.

Race and resource allocation: an online survey of US and UK adults’ attitudes toward COVID-19 ventilator and vaccine distribution

ObjectiveThis study aimed to assess US/UK adults’ attitudes towards COVID-19 ventilator and vaccine allocation.DesignOnline survey including US and UK adults, sampled to be representative for sex, age, race, household income...

THROMBOSIS DURING VENETOCLAX TREATMENT FOR ACUTE MYELOID LEUKEMIA WITH THE 3Q21Q26 SYNDROME: CRITICAL SURVEILLANCE URGENTLY NEEDED

Acute myeloid leukemia (AML) is associated with dismal outcomes, especially in older patients. The use of intensive chemotherapy currently represents the most common option for young/adult AML patients. Nevertheless, older patients are frequently ineligible for it or have a disease that is refractory to standard chemotherapy. As an alternative, azacitidine or decitabine monotherapy has been used, but hypomethylating agents have been associated with a low chance of survival. Since the results of Viale-A got published in August 2020, we have been living a new era in Hematology due to the possibility of treating elderly patients with AML suffering from comorbidities. The most frequent adverse events of the azacitidine-venetoclax combination were thrombocytopenia, neutropenia, and febrile neutropenia in 45%, 42%, and 42% of the cases, respectively. But now, in real clinical practice outside of a clinical trial, we have detected a few cases with rebound thrombocytosis during initial cycles of treatment. Describe an AML patient who presented thrombosis of the arm due to very high thrombocytosis of 1,550 x 109/L during the first cycle of azacitidine-venetoclax treatment. Our patient presented translocation involving the long arm of chromosome 3 at 3q26 in which myeloid disorders had already been identified as 3q21q26 syndrome. Very recently, Othman et al. reported the incidence of rebound thrombocytosis without clinical manifestation during azacitidine-venetoclax combination for AML treatment. No case presented had such high platelet count and thrombosis as presented herein. Othman et al. suggested rebound thrombocytosis would be due to the capability of blasts to hide thrombopoietin (TPO) via increased expression of TPO receptor MPL, but the mechanism underlying the thrombocytosis remains unclear. The 3q21q26 syndrome is rare but occurs in a high-risk myelodysplastic syndrome (MDS) or the setting of AML and is commonly associated with thrombocytosis. These chromosomal abnormalities result in aberrant expression of the protooncogene ecotropic virus integration site – 1 ( EVI1 ) located at 3q26.2, and through mechanisms not completely understood, myeloid and erythroid differentiation are profoundly suppressed while the megakaryocytic lineage shows marked hyperplasia. This case illustrates the importance of critical surveillance of platelet count during the initial cycle of venetoclax plus azacytidine.

Predictors of survival in elderly patients with coronavirus disease 2019 admitted to the hospital: derivation and validation of the FLAMINCOV score

ObjectiveTo identify predictors of 30-day survival in elderly patients with coronavirus disease 2019 (COVID-19). MethodsRetrospective cohort study including patients with COVID-19 aged ≥65 years hospitalized in six European sites (January 2020 to May 2021). Data on demographics, comorbidities, clinical characteristics, and outcomes were collected. A predictive score (FLAMINCOV) was developed using logistic regression. Regression coefficients were used to calculate the score. External validation was performed in a cohort including elderly patients from a major COVID-19 centre in Israel. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in the derivation and validation cohorts. Survival risk groups based on the score were derived and applied to the validation cohort. ResultsAmong 3010 patients included in the derivation cohort, 30-day survival was 74.5% (2242/3010). The intensive care unit admission rate was 7.6% (228/3010). The model predicting survival included independent functional status (OR, 4.87; 95% CI, 3.93–6.03), a oxygen saturation to fraction of inspired oxygen (SpO2/FiO2) ratio of >235 (OR, 3.75; 95% CI, 3.04–4.63), a C-reactive protein level of <14 mg/dL (OR, 2.41; 95% CI, 1.91–3.04), a creatinine level of <1.3 (OR, 2.02; 95% CI, 1.62–2.52) mg/dL, and absence of fever (OR, 1.34; 95% CI, 1.09–1.66). The score was validated in 1174 patients. The FLAMINCOV score ranges from 0 to 15 and showed good discrimination in the derivation (AUC, 0.79; 95% CI, 0.77–0.81; p < 0.001) and validation cohorts (AUC, 0.79; 95% CI, 0.76–0.81; p < 0.001). Thirty-day survival ranged from 39.4% (203/515) to 95.3% (634/665) across four risk groups according to score quartiles in the derivation cohort. Similar proportions were observed in the validation set. DiscussionThe FLAMINCOV score identifying elderly with higher or lower chances of survival may allow better triage and management, including intensive care unit admission/exclusion.

Cross-talk between necroptosis-related lncRNAs to construct a novel signature and predict the immune landscape of lung adenocarcinoma patients.

Background: As a new style of cell death, necroptosis plays a crucial role in tumor immune microenvironment. LncRNAs have been identified to act as competitive RNAs to influence genes involved in necroptosis. Therefore, we aim to create a signature based on necroptosis-related lncRNAs to predict the prognosis and immune landscape of lung adenocarcinoma (LUAD) patients in this study. Methods: TCGA database was used to acquire RNA sequencing (RNA-Seq) data and clinical information for 59 lung normal samples and 535 lung adenocarcinoma samples. The Pearson correlation analysis, univariate cox regression analysis and least absolute shrinkage and selection operator (LASSO) cox regression were performed to construct the prognostic NRlncRNAs signature. Then we used Kaplan-Meier (K-M) analysis, time-dependent ROC curves, univariate and multivariate cox regression analysis, and nomogram to validate this signature. In addition, GO, KEGG, and GSVA were analyzed to investigate the potential molecular mechanism. Moreover, we analyzed the relationship between our identified signature and immune microenvironment, TMB, and some clinical characteristics. Finally, we detected the expression of the six necroptosis-related lncRNAs in cells and tissues. Results: We constructed a NRlncRNAs signature consisting of six lncRNAs (FRMD6-AS1, LINC01480, FAM83A-AS1, FRMD6-AS1, MED4-AS1, and LINC01415) in LUAD. LUAD patients with high risk scores had lower chance of survival with an AUC of 0.739, 0.709, and 0.733 for 1-year, 3-year, and 5-year respectively. The results based on GO, KEGG, and GSVA enrichment analysis demonstrated that NRlncRNAs signature-related genes were mainly correlated with immune pathways, metabolic-and cell growth-related pathways, cell cycle, and apoptosis. Moreover, the risk score was correlated with the immune status of LUAD patients. Patients with higher risk scores had lower ESTIMATE scores and higher TIDE scores. The risk score was positively correlated with TMB. LINC01415, FRMD6-AS1 and FAM83A-AS1 were significantly overexpressed in lung adenocarcinoma, while the expression levels of MED4-AS1 and LINC01480 were lower in lung adenocarcinoma. Conclusion: Overall, an innovative prognostic signature based on NRlncRNAs was developed for LUAD through comprehensive bioinformatics analysis, which can act as a predictor of immunotherapy and may provide guidance for clinicians.

From endoscopic resection to pancreatoduodenectomy: a narrative review of treatment modalities for the tumors of the ampulla of Vater.

Tumors of the ampulla of Vater are a rare set of lesions that arise at the confluence of the common bile duct (CBD) and the pancreatic duct. They can be benign or malignant, often not easy to discriminate before treatment. Malignant tumors have low chances of survival (overall 5-year survival between 0% and 60%) and surgery is still the only curative option. Prognostic factors are being investigated to tailor therapeutic approach and improve outcomes. Due to their location in a complex anatomical region, all treatment options are challenging and associated with relevant morbidity. In this review we discuss different excisional techniques for the treatment of ampullary tumors (AT). A review of medical databases (PubMed and Google Scholar) was conducted selecting most relevant articles in English language without a specific timeframe. After first selection, most relevant citations were identified through snowballing. Pancreatoduodenectomy (PD) is the gold standard in malignant tumors, achieving the most radical treatment, at the price of worse perioperative morbidity/mortality and quality of life. Trans-duodenal ampullectomy (TDA) was developed before endoscopic resection (ER) and maintains a role only in selected patients. ER is now the first choice for benign lesions and expanding towards early stages malignant AT. Pancreatodudenectomy remains the best option for the radical excision of malignant AT, recently being offered also via minimally invasive approach. However, in early-stage malignant tumors, ER is gaining importance with foreseeable further expansion. Transduodenal ampullectomy still has a role in selected patients, such as unfit for PD when ER is not possible mainly due to anatomical abnormalities.

The Intersection of Tobacco Use, Health Disparities, and Inequalities in Lung Cancer Treatment and Survival

AbstractTobacco use and socioeconomic status are related with each other and important determinants of disparities and inequalities to access to care. There is overall reduction in number of smokers but still most number of smokers is represented by people from low socioeconomic status, with less number of these people having an access to the treatment centers. Patients who are tobacco users have shown to be less likely to receive any form of treatment for lung cancer, whether that be chemotherapy, radiotherapy, or surgery. As there is less awareness about signs and symptoms of lung cancer, lower socioeconomic patients are likely to report to hospitals at advanced stages or many times as a medical emergency. We are well aware that patients with advanced lung cancer have lower chances of survival in view of incomplete response to treatment. As there is an intersection between tobacco use, health disparities, and inequalities and lung cancer treatment and survival, this issue needs better focus and attention to minimize disparities and inequalities in access to care and outcomes.

GPX2 and BMP4 as Significant Molecular Alterations in The Lung Adenocarcinoma Progression: Integrated Bioinformatics Analysis.

ObjectivesNon-small cell lung adenocarcinoma (NSCLC) is the most common type of lung cancer, which is considered as the most lethal and prevalent cancer worldwide. Recently, molecular changes have been implicated to play a significant role in the cancer progression. Despite of numerous studies, the molecular mechanism of NSCLC pathogenesis in each sub-stage remains unclear. Studying these molecular alterations gives us a chance to design successful therapeutic plans which is aimed in this research.Materials and Methods In this bioinformatics study, we compared the expression profile of 7 minor stages of NSCLC adenocarcinoma, including GSE41271, GSE42127, and GSE75037, to clarify the relation of molecular alterations and tumorigenesis. At first, 99 common differentially expressed genes (DEG) were obtained. Then, functional enrichment analysis and protein-protein interaction (PPI) network construction were performed to uncover the association of significant cellular and molecular changes. Finally, gene expression profile interactive analysis (GEPIA) was employed to validate the results by RNA-seq expression data. Results Primary analysis showed that BMP4 was downregulated through the tumor progression to the stage IB and GPX2 was upregulated in the course of final tumor development to the stage IV and distant metastasis. Functional enrichment analysis indicated that BMP4 in the TGF-β signaling pathway and GPX2 in the glutathione metabolism pathway may be the key genes for NSCLC adenocarcinoma progression. GEPIA analysis revealed a correlation between BMP4 downregulation and GPX2 upregulation and lung adenocarcinoma (LUAD) progression and lower survival chances in LUAD patients which confirm microarray data. ConclusionTaken together, we suggested GPX2 as an oncogene by inhibiting apoptosis, promoting EMT and increasing glucose uptake in the final stages and BMP4 as a tumor suppressor via inducing apoptosis and arresting cell cycle in the early stages through lung adenocarcinoma (ADC) development to make them candidate genes to further cancer therapy investigations.

Fertility decline and the emergence of excess female survival in post-reproductive ages in Italy

In Italy, at least in the cohorts born up to the beginning of the twentieth century, women’s mortality in post-reproductive ages was influenced by fertility, with large progenies (and, to a lesser extent, childlessness) leading to markedly lower survival chances. This relationship proved strong enough to affect the female-to-male ratio in old age as fertility declined. In this paper, we show that various measures of extra female survival at high ages are closely connected to the fertility transition in Italy, and to its peculiar historical and geographical evolution.

Development of a graphical user interface software for the prediction of chronic kidney disease

Chronic Kidney Disease (CKD) is a severe kidney damage that is difficult to diagnose at the early stages due to the absence of clear symptoms. Late diagnosis of CKD is a common problem in low-income countries and is often associated with lower chances of survival. This study was designed to develop a user-friendly web-based graphical user interface (GUI) software for the prediction of CKD using artificial neural networks (ANNs). The model was developed using Python programming language and trained with 1200 instances of CKD datasets obtained from the University of California Irvine (UCI) machine learning repository. This dataset was split into 80% for training and 20% for testing achieved through an iterative process. A GUI software was developed based on the model using Django, an open-source python web development framework. The model achieved an accuracy of 95.83%, a precision of 100%, a specificity of 100%, and a sensitivity of 89.80%. The GUI software was effectively used to predict CKD and could be of immense benefit as a point of care application for early CKD prediction

Development of a Machine Learning Model Using Limited Features to Predict 6-Month Mortality at Treatment Decision Points for Patients With Advanced Solid Tumors.

PURPOSEPatients with advanced solid tumors may receive intensive treatments near the end of life. This study aimed to create a machine learning (ML) model using limited features to predict 6-month mortality at treatment decision points (TDPs).METHODSWe identified a cohort of adults with advanced solid tumors receiving care at a major cancer center from 2014 to 2020. We identified TDPs for new lines of therapy (LoTs) and confirmed mortality at 6 months after a TDP. Using extreme gradient boosting, ML models were developed, which used or derived features from a limited set of electronic health record data considering the literature, clinical relevance, variability, availability, and predictive importance using Shapley additive explanations scores. We predicted and observed 6-month mortality after a TDP and assessed a risk stratification strategy with different risk thresholds to support communication of chance of survival.RESULTSFour thousand one hundred ninety-two patients were included. Patients had 7,056 TDPs, for which the 6-month mortality increased from 17.9% to 46.7% after starting first to sixth LoT, respectively. On the basis of internal validation, models using both 111 (Full) or 45 (Limited-45) features accurately predicted 6-month mortality (area under the curve ≥ 0.80). Using a 0.3 risk threshold in the Limited-45 model, the observed 6-month survival was 34% (95% CI, 28 to 40) versus 81% (95% CI, 81 to 82) among those classified with low or higher chance of survival, respectively. The positive predictive value of the Limited-45 model was 0.66 (95% CI, 0.60 to 0.72).CONCLUSIONWe developed and validated a ML model using a limited set of 45 features readily derived from electronic health record data to predict 6-month prognosis in patients with advanced solid tumors. The model output may support shared decision making as patients consider the next LoT.

An Intervention in Congruence for End-of-Life Treatment Preference: A Randomized Trial.

There is a gap in family knowledge of their adolescents' end-of-life (EOL) treatment preferences. We tested the efficacy of Family Centered Advance Care Planning for Teens with Cancer (FACE-TC) pediatric advance care planning (to increase congruence in EOL treatment preferences. Adolescents with cancer/family dyads were randomized into a clinical trial from July 2016 to April 2019 at a 2:1 ratio: intervention (n = 83); control (n = 43) to either 3 weekly sessions of FACE-TC (Lyon Advance Care Planning Survey; Next Steps: Respecting Choices Interview; Five Wishes, advance directive) or treatment as usual (TAU). Statement of Treatment Preferences measured congruence. Adolescents' (n = 126) mean age was 16.9 years; 57% were female and 79% were White. FACE-TC dyads had greater overall agreement than TAU: high 34% vs 2%, moderate 52% vs 45%, low 14% vs 52%, and P < .0001. Significantly greater odds of congruence were found for FACE-TC dyads than TAU for 3 of 4 disease-specific scenarios: for example, "a long hospitalization with low chance of survival," 78% (57 of 73) vs 45% (19 of 42); odds ratio, 4.31 (95% confidence interval, 1.89-9.82). FACE-TC families were more likely to agree to stop some treatments. Intervention adolescents, 67% (48 of 73), wanted their families to do what is best at the time, whereas fewer TAU adolescents, 43% (18 of 42), gave families this leeway (P = .01). High-quality pediatric advance care planning enabled families to know their adolescents' EOL treatment preferences.

Evaluating the systemic immune-inflammation index for in-hospital and long-term mortality in elderly non-ST-elevation myocardial infarction patients

This investigation aimed to evaluate the predictive value of the systemic immune-inflammation index (SII) for in-hospital and long-term mortality in elderly patients with non-ST-elevation myocardial infarction (NSTEMI). This retrospective investigation included 314 consecutive elderly NSTEMI patients in a tertiary center. SII is computed as (neutrophils × platelets)/lymphocytes. Based on the increased SII values, we classified the research sample into three tertile groups as T1, T2, and T3. The in-hospital and long-term mortality were defined as the primary outcomes. Patients in the T3 group had lower chances of survival in the in-hospital and long-term periods compared with those in the T2 and T1 groups. According to the multivariable Cox regression models, SII independently related with in-hospital (hazard ratio (HR): 1.001, 95% CI: 1.000-1.1003, p = 0.038) and long-term mortality (HR: 1.004, 95% CI: 1.002-1.006, p < 0.001). To predict long-term mortality, the optimal SII value was > 2174 with 80% sensitivity and 85.4% specificity. SII had a slightly lower but statistically non-inferior discriminative ability for long-term mortality compared with the Charlson comorbidity index (CCI) in the receiver operating characteristic curve comparison (AUC: 86.2 vs. AUC: 890, p > 0.05). Additionally, combining SII with traditional risk factors and the CCI revealed a significant improvement in C-statistics. This investigation may be the first to demonstrate that SII is independently linked with in-hospital and long-term mortality in elderly NSTEMI patients.

Melatonin suppresses the metastatic potential of osteoblastic prostate cancers by inhibiting integrin α2 β1 expression.

Advanced prostate cancer often develops into bone metastasis, which is characterized by aberrant bone formation with chronic pain and lower chances of survival. No treatment exists as yet for osteoblastic bone metastasis in prostate cancer. The indolamine melatonin (N-acetyl-5-methoxytryptamine) is a major regulator of the circadian rhythm. Melatonin has shown antiproliferative and antimetastatic activities but has not yet been shown to be active in osteoblastic bone lesions of prostate cancer. Our study investigations reveal that melatonin concentration-dependently decreases the migratory and invasive abilities of two osteoblastic prostate cancer cell lines by inhibiting FAK, c-Src, and NF-κB transcriptional activity via the melatonin MT1 receptor, which effectively inhibits integrin α2 β1 expression. Melatonin therapy appears to offer therapeutic possibilities for reducing osteoblastic bone lesions in prostate cancer.

Construction of survival-related co-expression modules and identification of potential prognostic biomarkers of osteosarcoma using WGCNA.

BackgroundOsteosarcoma (OS) is a primary malignant bone tumor. Patients with different immune characteristics respond differently to chemotherapy and have a lower chance of survival. The potential pathogenesis and therapeutic targets of OS must be investigated further.MethodsOS expression profile data and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and the Gene Expression Omnibus (GEO) databases. The immune-related gene set was obtained from the ImmPort database, and the immune-related gene expression profiles were used for non-negative matrix factorization (NMF) cluster analysis of patients in the 2 databases to find the best clustering number. In the TARGET database, OS patients were classified into low-risk and high-risk groups based on the differences in their survival rates. Weighted correlation network analysis (WGCNA) was applied to the low-risk and high-risk groups to determine the module with the lowest conservatism in order to differentiate the prognosis of the 2 groups.ResultsA total of 500 key genes associated with poor prognosis were identified. Gene Ontology (GO) enrichment analysis revealed that the biological processes of these genes were primarily focused on the regulation of small guanosine triphosphatase (GTPase) mediated signal transduction, collagen-containing extracellular matrix, and Rho GTPase binding. A random survival forest identified EPHB3, TEAD1, and KRR1P1 as key genes. Their expression level was linked to overall survival. We discovered that the core genes were associated to immune cell infiltration. Simultaneously, paired survival analysis of two genes revealed differences in survival. We also reverse-predicted the main genes and developed their competitive endogenous RNA (ceRNA) network. Finally, utilizing the CellMiner database, we observed that the genes TEAD1 and EPHB3 were connected to drug sensitivity.ConclusionsIn this study, we identified the modules and key genes related to the poor prognosis of OS patients by using WGCNA, and verified their impact on the prognosis of OS patients and their role in the immune microenvironment of OS. In addition, targeted gene related antitumor drugs were screened out. The discoveries may lead to novel molecular targets and treatment methods for OS patients.KeywordsOsteosarcoma (OS); weighted gene co-expression network analysis (WGCNA); gene