PubTransformer

A site to transform Pubmed publications into these bibliographic reference formats: ADS, BibTeX, EndNote, ISI used by the Web of Knowledge, RIS, MEDLINE, Microsoft's Word 2007 XML.

Survival Analysis - Top 30 Publications

The prognostic efficacy and improvements of the 7th edition Union for International Cancer Control tumor-node-metastasis classifications for Chinese patients with gastric cancer: Results based on a retrospective three-decade population study.

This study aimed to evaluate survival trends for patients with gastric cancer in northeast China in the most recent three decades and analyze the applicability of the UICC tumor-node-metastasis (TNM) classification 7th edition for Chinese patients with gastric cancer. A review of all inpatient and outpatient records of patients with gastric cancer was conducted in the first hospital of China Medical University and the Liaoning Cancer Hospital and Institute. All patients who met the inclusion criteria and were seen from January 1980 through December 2009 were included in the study. The primary outcome was 5-year survival, which was analyzed according to decade of diagnosis and TNM classifications. From 1980 through 2009, the 5-year survival rates for patients with gastric cancer (n=2414) increased from 39.1% to 57.3%. Decade of diagnosis was significantly associated with patient survival (p = 0.013), and the 5-year survival rate in the 2000s was remarkably higher than that in the 1980s and 1990s (p = 0.004 and 0.049, respectively). When classified according to the UICC TNM classification of gastric cancer 7th edition, the prognoses of stage IIIA and stage IIIB patients were not significantly different (p = 0.077). However, if stage T4b and stage N0 patients were classified as stage IIIA, the prognoses of stage IIIA and stage IIIB patients were significantly different (p < 0.001). Hence, there was a significant difference in survival during the three time periods in Northeast China. Classifying stage T4b and stage N0 patients as stage IIIA according to the 7th edition of UICC gastric cancer TNM classifications better stratified Chinese patients and predicted prognoses.

Kaplan-Meier curve.

Identifying survival-associated modules from the dysregulated triplet network in glioblastoma multiforme.

Long noncoding RNAs (lncRNAs) can act as competitive endogenous RNAs (ceRNAs) to compete with mRNAs for binding miroRNAs (miRNAs). The dysregulated triplets, composed by mRNAs, lncRNAs, and miRNAs, contributed to the development and progression of diseases, such as cancer. However, the roles played by triplet biomarkers are not fully understand in glioblastoma multiforme (GBM) patient survival.

Double-stenting in distal left main lesions: Let's crush.

Unprotected distal left main (ULM) lesions often require double-stenting. In the MITO Registry, a mini-crush stenting technique was safer than culotte stenting. Performing mini-crush arises as the best approach in patients with distal ULM lesions requiring elective double-stenting.

In head and neck cancer the number of dissected lymph nodes predicts mortality.

Epithelial-Mesenchymal Expression Phenotype of Primary Melanoma and Matched Metastases and Relationship with Overall Survival.

E-Cadherin and N-cadherin are important components of epithelial-mesenchymal transition (EMT). The majority of studies on EMT in melanoma have been performed with cultured cell lines or pooled melanoma samples. The goal of our study was to evaluate the expression of E-cadherin and N-cadherin in matched tissue samples from primary and metastatic sites of melanoma and to determine the correlation with survival outcome. We analyzed tissues from 42 melanoma primary lesions and their corresponding metastases, as well as 53 benign nevi, for expression levels of E-cadherin and N-cadherin using immunohistochemical methods. There were heterogenous expression patterns of E- and N-cadherin in both primary and metastatic melanomas. Overall, metastatic tumor showed a decrease in E-cadherin expression and an increase in N-cadherin expression compared to the primary tumor, although the difference did not reach statistical significance (p=0.24 and 0.28 respectively). A switch of membranous expression from E-cadherin to N-cadherin from primary to metastatic melanoma was seen in eight patients (19%). Aberrant E-cadherin expression (defined as negative to weak membranous E-cadherin or positive nuclear E-cadherin expression) was more frequently observed in metastatic than in primary melanomas (p=0.03). Multivariate analysis showed that absence of N-cadherin expression in primary melanomas and the presence of aberrant E-cadherin expression in primary melanomas and metastatic melanomas was associated with a significantly worse overall survival. Our data support the importance of E-cadherin and N-cadherin proteins in melanoma progression and patient survival.

A retrospective validation study of three models to estimate the probability of malignancy in patients with small pulmonary nodules from a tertiary oncology follow-up centre.

To estimate the probability of malignancy in small pulmonary nodules (PNs) based on clinical and radiological characteristics in a non-screening population that includes patients with a prior history of malignancy using three validated models.

Genetic and functional analyses do not explain the association of high PRC1 expression with poor survival of breast carcinoma patients.

Microtubules are vitally important for eukaryotic cell division. Therefore, we evaluated the relevance of mitotic kinesin KIF14, protein-regulating cytokinesis 1 (PRC1), and citron kinase (CIT) for the prognosis of breast carcinoma patients. Transcript levels were assessed by quantitative real-time PCR in tissues from two independent groups of breast carcinoma patients and compared with clinical data. Tissue PRC1 protein levels were estimated using immunoblotting, and the PRC1 tagged haplotype was analyzed in genomic DNA. A functional study was performed in MDA-MB-231 cells in vitro. KIF14, PRC1, and CIT transcripts were overexpressed in tumors compared with control tissues. Tumors without expression of hormonal receptors or high-grade tumors expressed significantly higher KIF14 and PRC1 levels than hormonally-positive or low-grade tumors. Patients with high intra-tumoral PRC1 levels had significantly worse disease-free survival than patients with low levels. PRC1 rs10520699 and rs11852999 polymorphisms were associated with PRC1 transcript levels, but not with patientś survival. Paclitaxel-induced PRC1 expression, but PRC1 knockdown did not modify the paclitaxel cytotoxicity in vitro. PRC1 overexpression predicts poor disease-free survival of patients with breast carcinomas. Genetic variability of PRC1 and the protein interaction with paclitaxel cytotoxicity do not explain this association.

Effect of Prophylactic Antifungal Protocols on the Prognosis of Liver Transplantation: A Propensity Score Matching and Multistate Model Approach.

Background. Whether routine antifungal prophylaxis decreases posttransplantation fungal infections in patients receiving orthotopic liver transplantation (OLT) remains unclear. This study aimed to determine the effectiveness of antifungal prophylaxis for patients receiving OLT. Patients and Methods. This is a retrospective analysis of a database at Chang Gung Memorial Hospital. We have been administering routine antibiotic and prophylactic antifungal regimens to recipients with high model for end-stage liver disease scores (>20) since 2009. After propensity score matching, 402 patients were enrolled. We conducted a multistate model to analyze the cumulative hazards, probability of fungal infections, and risk factors. Results. The cumulative hazards and transition probability of "transplantation to fungal infection" were lower in the prophylaxis group. The incidence rate of fungal infection after OLT decreased from 18.9% to 11.4% (p = 0.052); overall mortality improved from 40.8% to 23.4% (p < 0.001). In the "transplantation to fungal infection" transition, prophylaxis was significantly associated with reduced hazards for fungal infection (hazard ratio: 0.57, 95% confidence interval: 0.34-0.96, p = 0.033). Massive ascites, cadaver transplantation, and older age were significantly associated with higher risks for mortality. Conclusion. Prophylactic antifungal regimens in high-risk recipients might decrease the incidence of posttransplant fungal infections.

Severe Spontaneous Echo Contrast/Auricolar Thrombosis in "Nonvalvular" AF: Value of Thromboembolic Risk Scores.

Patients with atrial fibrillation (AF) have an increased thromboembolic risk that can be estimated with risk scores and sometimes require oral anticoagulation therapy (OAT). Despite correct anticoagulation, some patients still develop left atrial spontaneous echo contrast (SEC) or thrombosis. The value of traditional risk scores (R2 CHADS2 , CHADS2 , and CHA2 DS2 -VASc) in predicting such events remains controversial.

Prognostic Role of Lactate Dehydrogenase Expression in Urologic Cancers: A Systematic Review and Meta-Analysis.

The prognostic role of lactate dehydrogenase (LDH) in urinary system cancer is still controversial. Thus, we conducted a meta-analysis to assess the prognostic significance of LDH for patients with urinary system cancer.

Supervised discretization can discover risk groups in cancer survival analysis.

Discretization of continuous variables is a common practice in medical research to identify risk patient groups. This work compares the performance of gold-standard categorization procedures (TNM+A protocol) with that of three supervised discretization methods from Machine Learning (CAIM, ChiM and DTree) in the stratification of patients with breast cancer. The performance for the discretization algorithms was evaluated based on the results obtained after applying standard survival analysis procedures such as Kaplan-Meier curves, Cox regression and predictive modelling. The results show that the application of alternative discretization algorithms could lead the clinicians to get valuable information for the diagnosis and outcome of the disease. Patient data were collected from the Medical Oncology Service of the Hospital Clínico Universitario (Málaga, Spain) considering a follow up period from 1982 to 2008.

Prognostic Factors for Survival in Patients Treated with Multimodal Therapy for Anaplastic Thyroid Cancer.

To identify predictors of survival after multimodal treatment including surgery plus postoperative radio(chemo)therapy) for anaplastic thyroid cancer.

Influence of perineural invasion in predicting overall survival and disease-free survival in patients With locally advanced gastric cancer.

The aim of the present study was to evaluate the prognostic significance of perineural invasion (PNI) in locally advanced gastric cancer patients who underwent D2 gastrectomy and adjuvant chemotherapy.

A Long-Term Prediction Model of Beijing Haze Episodes Using Time Series Analysis.

The rapid industrial development has led to the intermittent outbreak of pm2.5 or haze in developing countries, which has brought about great environmental issues, especially in big cities such as Beijing and New Delhi. We investigated the factors and mechanisms of haze change and present a long-term prediction model of Beijing haze episodes using time series analysis. We construct a dynamic structural measurement model of daily haze increment and reduce the model to a vector autoregressive model. Typical case studies on 886 continuous days indicate that our model performs very well on next day's Air Quality Index (AQI) prediction, and in severely polluted cases (AQI ≥ 300) the accuracy rate of AQI prediction even reaches up to 87.8%. The experiment of one-week prediction shows that our model has excellent sensitivity when a sudden haze burst or dissipation happens, which results in good long-term stability on the accuracy of the next 3-7 days' AQI prediction.

Predicting Coronary Heart Disease Using Risk Factor Categories for a Japanese Urban Population, and Comparison with the Framingham Risk Score: The Suita Study.

Early post-operative acute phase response in patients with early graft dysfunction is predictive of 6-month and 12-month mortality in liver transplant recipients.

Early allograft dysfunction (EAD) after liver transplantation is mostly a reversible event caused by factors related to ischemia/reperfusion (I/R) injury. EAD represents a hepatic injury associated with pre- and early post-transplant inflammatory cytokine responses. Aim of the present study was to evaluate the prognostic and diagnostic value of CRP in liver transplant recipients with EAD.

Expression of major histocompatibility complex class Ⅰ chain-related protein A and B in operable lung adenocarcinoma and its clinical significance.

To explore the expression of major histocompatibility complex classⅠchain-related protein A and B (MICA/B) in operable lung adenocarcinoma and its clinical significance.

Fluorodeoxyglucose Uptake in Advanced Non-small Cell Lung Cancer With and Without Pulmonary Lymphangitic Carcinomatosis.

To assess the correlation between advanced non-small cell lung cancer (NSCLC) with or without pulmonary lymphangitic carcinomatosis (PLC) and fluorodeoxyglucose (FDG) uptake and its effect on survival outcomes.

Body Mass Index makes headlines - When is mortality rate lowest?.

"People with obesity live longer" - headlines like these are common. Recently published epidemiological studies however provide new food for thought: how is a body mass index (BMI) in the overweight range associated with total mortality? There are many studies showing that a BMI outside the normal range is associated with a higher total mortality. In contrast, there are indications that a BMI in the overweight range is associated with a lower mortality rate. These observations should be interpreted with caution, because of the limitations of the BMI as a measure of overweight and obesity and because the results are based on cohort data. There is currently no reason to deviate from the recommendations regarding the indications for weight loss of the German Obesity Association.

Assessment of risk of sudden cardiac death in patients with hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a hereditary disease characterized by left ventricular hypertrophy with or without concomitant outflow tract obstruction. Identification of patients with HCM who are at high risk of sudden cardiac death (SCD) is crucial as those patients are likely to benefit from an implantable cardioverter defibrillator (ICD). Based on the HCM Risk-SCD study published in 2013, that included 3675 HCM patients with 24 313 years of follow up, a new clinical risk prediction model for sudden cardiac death was developed. This model was included in the recently released 2014 ESC guidelines. This review summarizes the changes in the prediction model and the resulting recommendations and discusses potential risks and limitations of the new score.

Effect of Automatic Inpatient Fall Prediction Using Routinely Captured EMR Data: Preliminary Results.

The increasing adoption of electronic medical record (EMR) systems including nursing documentation worldwide provides opportunities for improving patient safety by the automatic prediction of adverse events using EMR data. An inpatient fall is a preventable adverse event that can be managed more effectively and efficiently through a data-driven predictive approach. This study implemented a new approach and explored its effects in neurologic inpatient units. The results suggest that integrating an automatic fall prediction system with the EMR system could reduce inpatient falls.

Analyzing 30-Day Readmission Rate for Heart Failure Using Different Predictive Models.

The Center for Medicare and Medical Services in the United States compares hospital's readmission performance to the facilities across the nation using a 30-day window from the hospital discharge. Heart Failure (HF) is one of the conditions included in the comparison, as it is the most frequent and the most expensive diagnosis for hospitalization. If risk stratification for readmission of HF patients could be carried out at the time of discharge from the index hospitalization, corresponding appropriate post-discharge interventions could be arranged. We, therefore, sought to compare two different risk prediction models using 48 clinical predictors from electronic health records data of 1037 HF patients from one hospital. We used logistic regression and random forest as methods of analyses and found that logistic regression with bagging approach produced better predictive results (C-Statistics: 0.65) when compared to random forest (C-Statistics: 0.61).

The Impact of EuroSCORE II Risk Factors on Prediction of Long-Term Mortality.

The European System for Cardiac Operation Risk Evaluation (EuroSCORE) II has not been tested yet for predicting long-term mortality. This study was undertaken to evaluate the relationship between EuroSCORE II and long-term mortality and to develop a new algorithm based on EuroSCORE II factors to predict long-term survival after cardiac surgery.

Thyroid cancer.

Thyroid cancer is the fifth most common cancer in women in the USA, and an estimated over 62 000 new cases occurred in men and women in 2015. The incidence continues to rise worldwide. Differentiated thyroid cancer is the most frequent subtype of thyroid cancer and in most patients the standard treatment (surgery followed by either radioactive iodine or observation) is effective. Patients with other, more rare subtypes of thyroid cancer-medullary and anaplastic-are ideally treated by physicians with experience managing these malignancies. Targeted treatments that are approved for differentiated and medullary thyroid cancers have prolonged progression-free survival, but these drugs are not curative and therefore are reserved for patients with progressive or symptomatic disease.

Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices.

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Imported chikungunya cases in an area newly colonised by Aedes albopictus: mathematical assessment of the best public health strategy.

We aimed to identify the optimal strategy that should be used by public health authorities against transmission of chikungunya virus in mainland France. The theoretical model we developed, which mimics the current surveillance system, predicted that without vector control (VC), the probability of local transmission after introduction of viraemic patients was around 2%, and the number of autochthonous cases between five and 15 persons per hectare, depending on the number of imported cases. Compared with this baseline, we considered different strategies (VC after clinical suspicion of a case or after laboratory confirmation, for imported or autochthonous cases): Awaiting laboratory confirmation for suspected imported cases to implement VC had no significant impact on the epidemiological outcomes analysed, mainly because of the delay before entering into the surveillance system. However, waiting for laboratory confirmation of autochthonous cases before implementing VC resulted in more frequent outbreaks. After analysing the economic cost of such strategies, our study suggested implementing VC immediately after the notification of a suspected autochthonous case as the most efficient strategy in settings where local transmission has been proven. Nevertheless, we identified that decreasing reporting time for imported cases should remain a priority.

Application of Cox and Parametric Survival Models to Assess Social Determinants of Health Affecting Three-Year Survival of Breast Cancer Patients.

Breast cancer is one of the most common causes of cancer mortality in Iran. Social determinants of health are among the key factors affecting the pathogenesis of diseases. This cross-sectional study aimed to determine the social determinants of breast cancer survival time with parametric and semi-parametric regression models. It was conducted on male and female patients diagnosed with breast cancer presenting to the Cancer Research Center of Shohada-E-Tajrish Hospital from 2006 to 2010. The Cox proportional hazard model and parametric models including the Weibull, log normal and log-logistic models were applied to determine the social determinants of survival time of breast cancer patients. The Akaike information criterion (AIC) was used to assess the best fit. Statistical analysis was performed with STATA (version 11) software. This study was performed on 797 breast cancer patients, aged 25-93 years with a mean age of 54.7 (±11.9) years. In both semi-parametric and parametric models, the three-year survival was related to level of education and municipal district of residence (P<0.05). The AIC suggested that log normal distribution was the best fit for the three-year survival time of breast cancer patients. Social determinants of health such as level of education and municipal district of residence affect the survival of breast cancer cases. Future studies must focus on the effect of childhood social class on the survival times of cancers, which have hitherto only been paid limited attention.

Using Survival Analysis to Evaluate Medical Equipment Battery Life.

As hospital medical device managers obtain more data, opportunities exist for using the data to improve medical device management, enhance patient safety, and evaluate costs of decisions. As a demonstration of the ability to use data analytics, this article applies survival analysis statistical techniques to assist in making decisions on medical equipment maintenance. The analysis was performed on a large amount of data related to failures of an infusion pump manufacturer's lithium battery and two aftermarket replacement lithium batteries from one hospital facility. The survival analysis resulted in statistical evidence showing that one of the third-party batteries had a lower survival curve than the infusion pump manufacturer's battery. This lower survival curve translates to a shorter expected life before replacement is needed. The data suggested that to limit unexpected failures, replacing batteries at a two-year interval, rather than the current industry recommendation of three years, may be warranted. For less than $5,400 in additional annual cost, the risk of unexpected battery failures can be reduced from an estimated 28% to an estimated 7%.