Clinical Longevity of Obturators in Patients with Jaw Defects: a Retrospective Cohort Study

OBJECTIVES

The primary objective of the present retrospective clinical study was to determine the survival time of obturators while analyzing possible influencing factors.

MATERIALS AND METHODS

This retrospective clinical cohort study analyzed the influence of various clinical factors on the survival probability of obturators and their follow-up outcomes using Kaplan‒Meier analysis.

RESULTS

A total of 76 patients with 115 obturators were included in the study (47 men and 29 women, mean age 58.1 ± 18.1 years). The mean observation time was 3.0 ± 4.5 years (maximum 26.3 years). A total of 40.9% (47) of all obturators observed had to be replaced. The survival rate after 5 years was 79.5% for telescopic-crown-retained tooth-supported obturators, 86.9% for telescopic-crown-retained implant-supported obturators, 58.8% for removable full denture obturators, 22.1% for clasp-retained obturators and 0.0% for splints. The type of attachment, attendance at a regular follow-up and defect cause significantly influenced the survival of the obturators (p < .05).

CONCLUSIONS

The findings obtained in this study support the recommendation of using implant-supported obturators. Telescopic-crown attachments, either tooth- or implant-supported, seem to be favorable in terms of survival time. Attendance at a strict follow-up program seems to have a major influence on the longevity of the obturators.

CLINICAL RELEVANCE

The use of implant-supported obturators to cover permanent oral and maxillofacial defects is highly recommended. Additionally, the use of telescopic-crown attachments seems to be favorable in terms of survival time. Clasp-retained obturators and surgical splints should be used primarily for temporary restorations due to their shorter survival times.

VariantSurvival: a tool to identify genotype-treatment response

Motivation: For a number of neurological diseases, such as Alzheimer's disease, amyotrophic lateral sclerosis, and many others, certain genes are known to be involved in the disease mechanism. A common question is whether a structural variant in any such gene may be related to drug response in clinical trials and how this relationship can contribute to the lifecycle of drug development. Results: To this end, we introduce VariantSurvival, a tool that identifies changes in survival relative to structural variants within target genes. VariantSurvival matches annotated structural variants with genes that are clinically relevant to neurological diseases. A Cox regression model determines the change in survival between the placebo and clinical trial groups with respect to the number of structural variants in the drug target genes. We demonstrate the functionality of our approach with the exemplary case of the SETX gene. VariantSurvival has a user-friendly and lightweight graphical user interface built on the shiny web application package.

Comparison between olanzapine and aripiprazole treatment for 104 weeks after hospital discharge in schizophrenia spectrum disorders: a multicenter retrospective cohort study in a real-world setting

RATIONALE

The long-term effectiveness of olanzapine and aripiprazole in real clinical conditions at flexible doses in patients after hospital discharge has not been evaluated yet.

OBJECTIVES

This study was a multicenter retrospective cohort study. Patients with schizophrenia (n = 398) were prescribed olanzapine (n = 303) or aripiprazole (n = 95) at hospital discharge. The continuation of olanzapine or aripiprazole at 26, 52, or 104 weeks after the hospital discharge were compared using a Cox proportional hazards model and adjusted for possible confounders.

RESULTS

The Kaplan-Meier survival curves revealed that the continuation of olanzapine at 26 (P = 0.001) and 52 weeks (P = 0.018) was significantly higher than that of aripiprazole but not at 104 weeks. Olanzapine was better than aripiprazole in efficacy at 26 (hazard ratio: 0.321, 95% confidence interval: 0.159-0.645, P = 0.001), 52 (hazard ratio: 0.405, 95% confidence interval: 0.209-0.786, P = 0.008), and 104 weeks (hazard ratio: 0.438, 95% confidence interval: 0.246-0.780, P = 0.005). Aripiprazole was better than olanzapine in tolerability at 104 weeks (hazard ratio: 4.574, 95% confidence interval: 1.415-14.787, P = 0.011). Rates after two years continuation of olanzapine and aripiprazole were not significantly different in patients with less than five years' duration of illness, but olanzapine was more commonly maintained for more than two years in those patients who had been ill for over five years' due to its greater efficacy.

CONCLUSION

Olanzapine treatment showed better continuation rates at 26 and 52 after hospital discharge than aripiprazole, whereas maintenance with the two antipsychotics did not differ significantly at 104 weeks, due reduced tolerability of long-term olanzapine treatment.

Statistical methods for handling nondetected results in food chemical monitoring data to improve food risk assessments

Chemical risk assessment is important for risk management, and estimates of chemical exposure must be as accurate as possible. Chemical concentrations in food below the limit of detection are known as nondetects and result in left-censored data. During statistical analysis, the method used for handling values below the limit of detection is important. Many risk assessors employ widely used substitution methods to treat left-censored data, as recommended by international organizations. The National Institute of Food and Drug Safety Evaluation of South Korea also recommends these methods, which are currently used for chemical exposure assessments. However, these methods have statistical limitations, and international organizations recommend more advanced alternative statistical approaches. In this study, we assessed the validity of currently used statistical methods for handling nondetects. To identify the most suitable statistical method for handling nondetection, we created virtual data and conducted simulation studies. Based on both simulation and case studies, the Maximum Likelihood Estimation (MLE) and Robust Regression on Order Statistics (ROS) methods were found to be the best options. The statistical values obtained from these methods were similar to those obtained from the commonly used 1/2 Limit of Detection (LOD) substitution method for nondetection treatment. In three case studies, we compared the various methods based on the root mean squared error. The data for all case studies were from the same source, to avoid heterogeneity. Across various sample sizes and nondetection rates, the mean and 95th percentile values for all treatment methods were similar. However, "lognormal maximum likelihood estimation" method was not suitable for estimating the mean. Risk assessors should consider statistical processing of monitoring data to reduce uncertainty. Currently used substitution methods are effective and easy to apply to large datasets with nondetection rates <80%. However, advanced statistical methods are required in some circumstances, and national guidelines are needed regarding their use in risk assessments.

Predictive value of serum lncRNA MALAT1 for the recurrence of persistent atrial fibrillation after radiofrequency ablation

Objective: The authors investigated the predictive value of MALAT1 for persistent atrial fibrillation (PAF) recurrence after radiofrequency ablation. Methods: Serum MALAT1 level was determined. The correlation between MALAT1 and high-sensitivity C-reactive protein/left atrial diameter (LAD) was analyzed. The predictive value of MALAT1 was evaluated. The postoperative recurrence rate in patients with high/low MALAT1 was compared. Independent risk factors for postoperative recurrence were analyzed. Results: MALAT1 was elevated in PAF patients and positively correlated with high-sensitivity C-reactive protein/LAD. MALAT1/high-sensitivity C-reactive protein/LAD were enhanced in patients with recurrent PAF. Patients with high MALAT1 had a higher recurrence rate. Upregulated MALAT1 was an independent risk factor for postoperative PAF recurrence. Conclusion: Serum MALAT1 level >2.03 predicts postoperative recurrence of PAF, and PAF patients with high MALAT1 have a higher risk of postoperative recurrence.

Improved Survival Analyses Based on Characterized Time-Dependent Covariates to Predict Individual Chronic Kidney Disease Progression

Kidney diseases can cause severe morbidity, mortality, and health burden. Determining the risk factors associated with kidney damage and deterioration has become a priority for the prevention and treatment of kidney disease. This study followed 497 patients with stage 3-5 chronic kidney disease (CKD) who were treated at the ward of Taipei Veterans General Hospital from January 2006 to 2019 in Taiwan. The patients underwent 3-year-long follow-up sessions for clinical measurements, which occurred every 3 months. Three time-dependent survival models, namely the Cox proportional hazard model (Cox PHM), random survival forest (RSF), and an artificial neural network (ANN), were used to process patient demographics and laboratory data for predicting progression to renal failure, and important features for optimal prediction were evaluated. The individual prediction of CKD progression was validated using the Kaplan-Meier estimation method, based on patients' true outcomes during and beyond the study period. The results showed that the average concordance indexes for the cross-validation of the Cox PHM, ANN, and RSF models were 0.71, 0.72, and 0.89, respectively. RSF had the best predictive performances for CKD patients within the 3 years of follow-up sessions, with a sensitivity of 0.79 and specificity of 0.88. Creatinine, age, estimated glomerular filtration rate, and urine protein to creatinine ratio were useful factors for predicting the progression of CKD patients in the RSF model. These results may be helpful for instantaneous risk prediction at each follow-up session for CKD patients.

Predictors of mortality among drug-resistant tuberculosis patients in Kaduna State, Nigeria

Background

Specific death due to DR-TB has significantly contributed to tuberculosis (TB) mortality and overall global deaths.

Aim

This study examines the predictors of mortality among DR-TB patients in Kaduna State, Nigeria.

Subject and Method

This was a retrospective longitudinal study of DR-TB mortality carried out among 370 DR-TB patients from the 23 LGAs in Kaduna State. It involves a retrospective review of the MDR-TB records of the patients over a period of 10 years (2012-2021). Demographic and clinical data of all DR-TB patients enrolled in Kaduna State, Nigeria, between April 1, 2012, and March 31, 2021, were used. Survival analysis was performed with SPSS version 25, using Kaplan-Meier and Cox proportional hazard regression modeling, at 5% significance level.

Results

The majority of the patients, 255 (68.9%), were below the age of 40 years, while 53 (14.3%) of the patients died within the study period. Most deaths 26 (49.1%) were associated with HIV co-infection and the disease severity. Results for the Cox proportional model show that there was a significantly lower risk of death when a patient had MDR-TB compared to pre-XDR-TB (adjusted hazard ratio, AHR = 0.34, 95% CI = 0.16-0.72, P = 0.04). Both models show that age, sex, residence, or year of treatment had no significant association with survival or death.

Conclusion

HIV co-infection and DRTB with progression to more resistant and difficult-to-treat strains contributed to higher deaths. There is a need for concerted efforts from all DR-TB stakeholders to control the disease.

Changes in the probability of hysterectomy in the city of Mainz and Mainz-Bingen region, Germany

BACKGROUND

To assess the hysterectomy probability by calendar period and age, the overall and the age-specific prevalence of hysterectomy in women aged 30-65 years.

METHODS

Baseline data (2005-2007) from the population-based MARZY study conducted in Mainz and Mainz-Bingen, Germany, were analysed. 6429 women aged 30-65 years were asked whether they had undergone a hysterectomy and the date and indication of the procedure. We calculated the 5-year age-specific prevalence of hysterectomy and estimated the probability of undergoing a hysterectomy combining two approaches: 1) Kaplan-Meier and 2) Inverse probability weighting (IPW). We assessed potential changes over calendar periods by simulating survival curves, having hysterectomy as the event, employing a Cox proportional hazard model.

RESULTS

Data on hysterectomy were available for 4719 women. Of these, 961 (20.4%) had undergone a hysterectomy between 1960 and 2006. The hysterectomy prevalence was highest among the 60-64 year-olds (40.7%). The IPW-corrected probability of having a hysterectomy up to the age of 65 years was 36.4%. The age-specific probability of hysterectomy increased from 0.1% (20-24 years), peaking at 45-49 years (7.8%) and declining thereafter to less than 5% among women aged 50 and older. Over time, women were hysterectomised at an increasingly older age. Most hysterectomies (86.7%) were done due to benign disease.

CONCLUSIONS

A shift to older age at hysterectomy with an advancing calendar period likely reflects changes in clinical practice in Germany.

TRIAL REGISTRATION

Landesärztekammer Rheinland-Pfalz: 837.438.03 (4100).

Post hoc survival analyses using RNAseq data: handle with care

With the advent of next-generation sequencing technologies, there has been a dramatic increase in the availability of paired clinical and transcriptomic data in a variety of disease states. For basic science researchers, this has provided a valuable opportunity for querying the impact of the transcript levels of a gene on disease survival in humans. However, there are a multitude of methodological and technical considerations to evaluate before embarking on these analyses. Herein, we provide a brief description of statistical considerations involved in these analyses, geared toward basic scientists who may not necessarily routinely use such statistical models as part of their studies.

A series of two-sample non-parametric tests for quantile residual life time

Quantile residual lifetime (QRL) is of significant interest in many clinical studies as an easily interpretable quantity compared to other summary measures of survival distributions. In cancer or other chronic diseases, treatments are often compared based on the distributions or quantiles of the residual lifetime. Thus a common problem of interest is to test the equality of the QRL between two populations. In this paper, we propose two classes of tests to compare two QRLs; one class is based on the difference between two estimated QRLs, and the other is based on the estimating function of the QRL, where the estimated QRL from one sample is plugged into the QRL-estimating-function of the other sample. We outline the asymptotic properties of these test statistics. Simulation studies demonstrate that the proposed tests produced Type I errors closer to the nominal level and are superior to some existing tests based on both Type I error and power. Our proposed test statistics are also computationally less intensive and more straightforward compared to tests based on the confidence intervals. We applied the proposed methods to a randomized multicenter phase III trial for breast cancer patients.

An Empirical Study of Promotion Pressure among University Teachers in China Using Event History Analysis

OBJECTIVE

We sought to understand the status of promotion pressure among university teachers in China. This study explored the promotion duration and influencing factors among teachers in different disciplines of the social sciences.

METHODS

Using event history analysis, this study collected data regarding university teachers of China. The sample included 536 teachers who had been promoted from assistant to associate professor and 243 teachers promoted from associate to full professor. Our results revealed that the overall time required for promotion in the social sciences is relatively long. For those promoted from assistant to associate professor, the mean time for promotion was 14.155 years, with a median of 11 years, while for the transition from associate to full professor, the mean was 13.904 years with a median of nine years. Furthermore, in the survival function of the promotion duration, there is a stage pattern for both assistant to associate professor and associate to full professor. In addition, the Kaplan-Meier results showed that the mean promotion time in economics was the shortest. The Cox regression results indicated that males had a higher chance of promotion than females, and faculty members with doctoral degrees had a higher likelihood of promotion than those without. For those advancing from assistant to associate professor, the university of employment had significant positive effects on promotion. This paper provides empirical support for the current societal concerns regarding promotion pressure among university teachers.

Time to occurrence of necrotizing enterocolitis and its predictors among low birth weight neonates admitted at neonatal intensive care unit of felege hiwot compressive specialized hospital BahirDar, Ethiopia, 2021: A retrospective follow-up study

Background

Globally, the incidence of necrotizing enterocolitis (NEC) varies between 6 and 15% of all neonates admitted to the neonatal intensive care unit (NICU). Though necrotizing enterocolitis is a multifactorial and life-threatening disease, low birth prematurity is the single cause. Therefore, determining the time to presentation and its predictors of necrotizing enterocolitis were the main goals of this investigation.

Materials and methods

An institution-based retrospective follow-up study was conducted among 747 low birth weight (LBW) neonates admitted to the neonatal intensive care unit of Felege Hiwot comprehensive specialized Hospital from 1 January 2017 to 30 December 2019. The sample size was calculated by using the STATA package. Data were entered into Epi data version 3.1 and exported to STATA version 14 for analysis. The log-rank test and the Kaplan-Meier estimator were used to display the survival probability and differences between groups. At a significance threshold of 5%, Cox proportional hazard regression was performed to determine the net independent predictors of necrotizing enterocolitis.

Result

The overall incidence rate was 0.86 per 1,000 person-days (95% CI: 0.67, 1.14) with a 6.8% (95% i: 5.2, 8.9) proportion of necrotizing enterocolitis among low birth weight neonates. Preeclampsia [adjusted hazard ratio (AHR);1.92 (95% CI: 1.03-3.58)], premature rapture of membrane [AHR; 2.36 (95%, CI: 1.19-4.69)], perinatal asphyxia [AHR; 4.05 (95%, CI: 2.04-8.60)], gestational age between 28 and 32 weeks [AHR; 3.59 (95% CI: 1.01-8.83)], and birth weigh less than 1,000 g [AHR; 5.45 (95% CI: 3.84-9.12) were the independent predictors of necrotizing enterocolitis.

Conclusion

Within the first 1-7 days of a newborn's life, necrotizing enterocolitis was most common. It was discovered that preeclampsia, premature rupture of membrane, perinatal asphyxia, gestational age of 28-32 weeks, and birth weight less than 1,000 g were predictors of its occurrence.

Multivariant Transcriptome Analysis Identifies Modules and Hub Genes Associated with Poor Outcomes in Newly Diagnosed Multiple Myeloma Patients

The molecular mechanisms underlying chemoresistance in some newly diagnosed multiple myeloma (MM) patients receiving standard therapies (lenalidomide, bortezomib, and dexamethasone) are poorly understood. Identifying clinically relevant gene networks associated with death due to MM may uncover novel mechanisms, drug targets, and prognostic biomarkers to improve the treatment of the disease. This study used data from the MMRF CoMMpass RNA-seq dataset (N = 270) for weighted gene co-expression network analysis (WGCNA), which identified 21 modules of co-expressed genes. Genes differentially expressed in patients with poor outcomes were assessed using two independent sample t-tests (dead and alive MM patients). The clinical performance of biomarker candidates was evaluated using overall survival via a log-rank Kaplan-Meier and ROC test. Four distinct modules (M10, M13, M15, and M20) were significantly correlated with MM vital status and differentially expressed between the dead (poor outcomes) and the alive MM patients within two years. The biological functions of modules positively correlated with death (M10, M13, and M20) were G-protein coupled receptor protein, cell-cell adhesion, cell cycle regulation genes, and cellular membrane fusion genes. In contrast, a negatively correlated module to MM mortality (M15) was the regulation of B-cell activation and lymphocyte differentiation. MM biomarkers CTAG2, MAGEA6, CCND2, NEK2, and E2F2 were co-expressed in positively correlated modules to MM vital status, which was associated with MM's lower overall survival.

An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients' Age: A Retrospective Cohort Study

Characterization of breast cancer into intrinsic molecular profiles has allowed women to live longer, undergoing personalized treatments. With the aim of investigating the relation between different values of ki67 and the predisposition to develop a breast cancer-related IDE at different ages, we enrolled 900 patients with a first diagnosis of invasive breast cancer, and we partitioned the dataset into two sub-samples with respect to an age value equal to 50 years. For each sample, we performed a Kaplan−Meier analysis to compare the IDE-free survival curves obtained with reference to different ki67 values. The analysis on patients under 50 years old resulted in a p-value < 0.001, highlighting how the behaviors of patients characterized by a ki67 ranging from 10% to 20% and greater than 20% were statistically significantly similar. Conversely, patients over 50 years old characterized by a ki67 ranging from 10% to 20% showed an IDE-free survival probability significantly greater than patients with a ki67 greater than 20%, with a p-value of 0.01. Our work shows that the adoption of two different ki67 values, namely, 10% and 20%, might be discriminant in designing personalized treatments for patients under 50 years old and over 50 years old, respectively.

Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A

OBJECTIVE

Life expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. However, due to the resource-consuming nature of following a cohort prospectively, life expectancy is often assessed based upon retrospective death record reviews. This conventional approach may lead to potentially biased estimates, in particular when estimating life expectancy of rare diseases such as Morquio syndrome A. We investigated the accuracy of life expectancy estimation using death records by simulating the survival of individuals with Morquio syndrome A under four different scenarios.

RESULTS

When life expectancy was constant during the entire period, using death data did not result in a biased estimate. However, when life expectancy increased over time, as is often expected to be the case in rare diseases, using only death data led to a substantial underestimation of life expectancy. We emphasize that it is therefore crucial to understand how estimates of life expectancy are obtained, to interpret them in an appropriate context, and to assess estimation methods within a sensitivity analysis framework, similar to the simulations performed herein.

A Method to Identify Potential Prognostic Markers Across Distinct Tumor Types

The identification of novel biomarkers in cancer patients often requires both survival and gene expression analyses. The Kaplan-Meier survival analysis is one of the most common methods to assess the fraction of subjects living for a certain amount of time.Here, we describe a method for researchers to identify potential prognostic markers across distinct tumor types. We utilize The Cancer Genome Atlas (TCGA) as this is one of the most extensive and successful cancer genomics programs to date that includes expression data and clinical follow-up information for up to 33 distinct tumor types. Nevertheless, the method described here can also be applied to any open-source dataset where the RNA expression and clinical outcome are provided.We provide detailed practical instructions and advices for investigators to be able to successfully identify prognostic markers in cancer patients.

Impact of changes to cervical screening guidelines on age and interval at which women are tested: Population-based study

BACKGROUND

English cervical screening programme guidelines changed between 2009 and 2012. We explore the impact on the age and intervals at which women receive a cytology test.

METHODS

Eligible women were controls from a population-based case-control study in England. Tests taken between 1980 and 2017 were extracted from the call/recall database. Using the Kaplan-Meier estimator by birth cohort and age at (or time since) last test, we explore proportions tested since or prior to a given age, years since previous test, and interval following a negative test.

RESULTS

Screening histories from 46,037 women were included. Proportion tested by age 26 has increased from 55% among birth cohorts 1978-1979 to 67% among those born 1990-1991, despite more recent cohorts only having received one invitation (instead of two) prior to age 26. The proportion of women tested at aged 28 with a test three years earlier increased by 20% (from 36% in 1997-2006 to 56% in 2012-2017) whereas the proportion tested at ages 23-27 without a prior test increased from 34% to 80%. The age at last test prior to exiting the programme has decreased: among those born 1928-1931 86% had a test aged 60-65, but only 71% of those born 1947-1951.

CONCLUSION

Clear programme guidance alongside quality assurance has improved the cervical screening programme by standardising the age and intervals at which women are screened.

Applying State-of-the-Art Survival Extrapolation Techniques to the Evaluation of CAR-T Therapies: Evidence from a Systematic Literature Review

INTRODUCTION

Traditional statistical techniques for extrapolating short-term survival data for anticancer therapies assume the same mortality rate for noncured and "cured" patients, which is appropriate for projecting survival of non-curative therapies but may lead to an underestimation of the treatment effectiveness for potentially curative therapies. Our objective was to ascertain research trends in survival extrapolation techniques used to project the survival benefits of chimeric antigen receptor T cell (CAR-T) therapies.

METHODS

A global systematic literature search produced a review of survival analyses of CAR-T therapies, published between January 1, 2015 and December 14, 2020, based on publications sourced from MEDLINE, scientific conferences, and health technology assessment agencies. Trends in survival extrapolation techniques used, and the rationale for selecting advanced techniques, are discussed.

RESULTS

Twenty publications were included, the majority of which (65%, N = 13) accounted for curative intent of CAR-T therapies through the use of advanced extrapolation techniques, i.e., mixture cure models [MCMs] (N = 10) or spline-based models (N = 3). The authors' rationale for using the MCM approach included (a) better statistical fits to the observed Kaplan-Meier curves (KMs) and (b) visual inspection of the KMs indicated that a proportion of patients experienced long-term remission and survival which is not inherently captured in standard parametric distributions.

DISCUSSION

Our findings suggest that an advanced extrapolation technique should be considered in base case survival analyses of CAR-T therapies when extrapolating short-term survival data to long-term horizons extending beyond the clinical trial duration.

CONCLUSION

Advanced extrapolation techniques allow researchers to account for the proportion of patients with an observed plateau in survival from clinical trial data; by only using standard-partitioned modeling, researchers may risk underestimating the survival benefits for the subset of patients with long-term remission. Sensitivity analysis with an alternative advanced extrapolation technique should be implemented and re-assessment using clinical trial extension data and/or real-world data should be conducted as longer-term data become available.

Associating the scale-up of insecticide-treated nets and use with the decline in all-cause child mortality in the Democratic Republic of Congo from 2005 to 2014

BACKGROUND

To reduce the malaria burden and improve the socioeconomic status of its citizens, the Democratic Republic of Congo scaled up key malaria control interventions, especially insecticide-treated nets (ITNs), between 2005 and 2014. Since then, the effects of these interventions on malaria mortality and morbidity have not been assessed. This study aimed to measure the impact of the National Malaria Control Programme's efforts and to inform future control strategies.

METHODS

The authors used data from the Demographic and Health Surveys 2007 and 2013-2014 to assess trends in all-cause childhood mortality (ACCM) against trends in coverage of malaria interventions at national and subnational levels. The authors used the plausibility argument to assess the impact of the malaria control interventions and used Kaplan-Meier survival probability and Cox proportional hazard models to examine the effect of ITN ownership on child survival. Contextual factor trends affecting child survival were also considered.

RESULTS

Countrywide, household ownership of at least one ITN increased, from 9% in 2007 to 70% in 2013-2014. All provinces experienced similar increases, with some greater than the national level. ITN use increased between 2007 and 2013-2014 among children under five (6% to 55%). Severe anaemia (haemoglobin concentration < 8 g/dl) prevalence among children aged 6-59 months significantly decreased, from 11% (95% confidence interval [CI] 9-13%) in 2007 to 6% (95% CI 5-7%) in 2013-2014. During the same period, ACCM declined, from 148 (95% CI 132-163) to 104 (95% CI 97-112) deaths per 1000 live births. The decline in ACCM was greater among children aged 6-23 months (relative reduction of 36%), compared to children aged 24-59 months (relative reduction of 12%). Cox regression indicated that household ownership of at least one ITN reduced the risk of mortality by 24% among children under five (risk ratio = 0.76, 95% CI 0.64-0.90). Contextual factor analysis revealed marginal improvements in socioeconomic indicators and other health interventions.

CONCLUSIONS

Given the patterns of the coverage of malaria control interventions, patterns in ACCM by province, and marginal improvements in contextual factors, the authors conclude that the malaria control interventions have plausibly contributed to the decrease in ACCM in the Democratic Republic of Congo from 2005 to 2014.

Association of Serum Nonesterified Fatty Acids with Cardiovascular Event in Patients with Chronic Kidney Disease

Background

Chronic kidney disease (CKD) has been suggested to be associated with a high risk of cardiovascular diseases (CVD). The study aimed to evaluate the prognostic significance of nonesterified fatty acid (NEFA), also well known as free fatty acid, on predicting cardiovascular events in patients with CKD.

Methods

A total of 957 hospitalized patients with CKD in a stable clinical condition were enrolled at baseline. Then, the serum NEFA levels were measured. These included patients were prospectively followed up for a median of 10.2 years (range=0.4–11.5 years). We assessed whether serum NEFA levels at baseline can predict cardiovascular event during the follow-up.

Results

A total of 278 (29.1%) patients experienced cardiovascular events during follow-up. The Kaplan–Meier curve demonstrated that patients with higher serum NEFA levels (≥19.8 mg/dl) had a higher rate of cardiovascular events than patients with lower NEFA levels (<19.8 mg/dl). Multivariate Cox regression analysis suggested that elevated serum NEFA levels (HR=1.62; 95% CI 1.40–2.16, P<0.001) were independently associated with increased risk of cardiovascular events after correction for clinical confounding factors.

Conclusion

Elevated serum NEFA levels were associated with higher risk of cardiovascular events and may be a new parameter predicting cardiovascular events in patients with CKD, which may strengthen its potential effect in clinical practice.

Microcephalic osteodysplastic primordial dwarfism type II is associated with global vascular disease

Background

Microcephalic osteodysplastic primordial dwarfism type II (MOPDII) is the most common form of primordial dwarfism, caused by bialleic mutations in the pericentrin gene (PCNT). Aside from its classic features, there are multiple associated medical complications, including a well-documented risk of neurovascular disease. Over the past several years, it has become apparent that additional vascular issues, as well as systemic hypertension and kidney disease may also be related to MOPDII. However, the frequency and extent of the vasculopathy was unclear. To help address this question, a vascular substudy was initiated within our Primordial Dwarfism Registry.

Results

Medical records from 47 individuals, living and deceased, ranging in age from 3 to 41years of age were interrogated for this purpose. Of the total group, 64% were diagnosed with moyamoya, intracranial aneurysms, or both. In general, the age at diagnosis for moyamoya was younger than aneurysms, but the risk for neurovascular disease was throughout the shortened lifespan. In addition to neurovascular disease, renal, coronary and external carotid artery involvement are documented. 43% of the total group was diagnosed with hypertension, and 17% had myocardial infarctions. A total of 32% of the entire cohort had some form of chronic kidney disease, with 4% of the total group necessitating a kidney transplant. In addition, 38% had diabetes/insulin resistance. Ages of diagnoses, treatment modalities employed, and location of vasculopathies were notated as available and applicable, as well as frequencies of other comorbidities.

Conclusions

It is now clear that vascular disease in MOPDII is global and screening of the cardiac and renal vessels is warranted along with close monitoring of blood pressure. We recommend a blood pressure of 110/70mmHg as a starting point for an upper limit, especially if the individual has a history of neurovascular disease, chronic kidney disease and/or diabetes. Additionally, providers need to be at high alert for the possibility of myocardial infarctions in young adults with MOPDII, so that appropriate treatment can be initiated promptly in an acute situation.

Modeling breast cancer survival and metastasis rates from moderate-sized clinical data

Predicting time-dependent survival probability of a breast cancer patient using information such as primary tumor size, grade, node spread status, and patient age at the time of surgery can be of immense help in managing life expectations and strategizing postoperative treatment. However, for moderate-sized clinical datasets the application of standard Kaplan-Meier theory to determine survival probability as a function of multiple cofactors can become challenging when continuous variables like tumor diameter and survival time are segmented into a large number of narrow intervals, a problem commonly termed the curse of dimensionality. We circumvent this problem by modeling the patient-to-patient distribution of primary tumor diameter with a realistic, right-skewed function, and then matching the diameter-marginalized survival with the mean Kaplan-Meier survival for the data. We apply this procedure on a recent clinical data from 1875 breast cancer patients and develop parameters that can be readily used to estimate post-surgery survival for an arbitrary time length. Finally, we show that the observed fraction of node-positive patients can be quantitatively explained within a simple tumor growth and metastasis framework. Employing two different tumor growth models from the literature (i.e., Gompertz and logistic growth models), we utilize the observed fraction-node-positive data to determine metastasis rates from the surface of a primary tumor and its patient-to-patient distribution.

Five-year survival analysis and predictors of death in HIV-positive serology patients attending the Military Hospital of Nampula, Mozambique

An observational retrospective study was conducted over a 5-year period to assess survival and predictors of death in people with HIV-positive serology undergoing antiretroviral treatment with first-line regimens at the Military Hospital of Nampula, Mozambique. We collected data from 332 patient records. Kaplan-Meier boundary product estimator, log-rank, Gehan-Breslow, Tarone-Ware, time-dependent Cox models and estimates of hazard ratios (HR), with 95% confidence interval (CI) were calculated. Meantime survival for females and males was 54.8 months [95% CI 50.32-55.40] and 49.7 months [95% CI 45.89-53.53], respectively. Cox regressions indicated higher death rates significantly or potentially associated with: male sex (HR = 1.3; [95% CI 0.7-2.39]); suspected diagnosis reported only by the physician (HR = 3.6; [95% CI 1.8-7.4]); disease stages III (HR=1.2 [95% CI 0.3-3.6]) or IV (HR 1.4 [95% CI 0.4-5.8]); first TCD4+ lymphocyte count lower than 350 cells per ml (HR = 3.2; [95% CI 0.9-11.2]) or between 350-500 cells per ml (HR = 1.3; [95% CI 0.3-5.8]); or do not present cells count (HR = 3.6; [95% CI 1.2-10.2]). The above variables were significant for HIV prognosis and as predictors of death and should be considered in the clinical care of these patients.

Prognostic Significance of Sodium Iodide Symporter and Deiodinase Enzymes mRNA Expression in Gastric Cancer

Context

Thyroid hormones (THs) are critically important for development, homeostasis, and metabolic regulation in mammals. Iodine, one of the constituents of TH, is actively supplied by sodium iodide symporter (NIS) into the thyroid gland. TH is subsequently transported to distant organs where its activation and deactivation is catalyzed by isoforms of deiodinases (DIOs). NIS protein has been known to overexpress in cancer cases of the breast and gastrointestinal organs. Recent studies show a possible role of DIOs in various cancers.

Aims

In the present investigation, the prognostic significance of NIS and DIO-1, 2 and 3 was studied in gastric cancer using a data mining bioinformatic approach.

Methods

"The Kaplan-Meier plotter" database was used for direct in silico validation in clinically relevant 876 gastric cancer patients with >15 years of follow-up information. After obtaining KM survival plots, hazard ratio and log-rank P value were calculated.

Results

Increased expression of NIS and DIO 1-3 is significantly associated with worsen overall survival of gastric cancer patients followed for 20 years. Prognostic roles of NIS and individual DIOs were assessed in different types of gastric cancer classified based on morphologies, human epidermal growth factor receptor-2 receptor status, treatment choices, and different clinicopathological features.

Conclusions

Based on these analyses, the present study found the indication of prognostic values of these genes. This information will contribute to better understanding of managing complex and heterogeneous gastric cancer. Further, these findings may be beneficial as a companion diagnostic tool predicting more accurate gastric cancer prognosis.

Analysis of Lifespan in C. elegans: Low- and High-Throughput Approaches

Lifespan is the most straightforward surrogate measure of aging, as it is easily quantifiable. A common approach to measure Caenorhabditis elegans lifespan is to follow a population of animals over time and score viability based on movement. We previously developed an alternative approach, called the Replica Set method, to quantitatively measure lifespan of C. elegans in a high-throughput manner. The replica set method allows a single investigator to screen more treatments or conditions in the same amount of time without loss of data quality. The method requires common equipment found in most laboratories working with C. elegans and is thus simple to adopt. Unlike traditional approaches, the Replica Set method centers on assaying independent samples of a population at each observation point, rather than a single sample over time as with "traditional" longitudinal methods. The protocols provided here describe both the traditional experimental approach and the Replica Set method, as well as practical considerations for each.

Transformation model estimation of survival under dependent truncation and independent censoring

Truncation is a mechanism that permits observation of selected subjects from a source population; subjects are excluded if their event times are not contained within subject-specific intervals. Standard survival analysis methods for estimation of the distribution of the event time require quasi-independence of failure and truncation. When quasi-independence does not hold, alternative estimation procedures are required; currently, there is a copula model approach that makes strong modeling assumptions, and a transformation model approach that does not allow for right censoring. We extend the transformation model approach to accommodate right censoring. We propose a regression diagnostic for assessment of model fit. We evaluate the proposed transformation model in simulations and apply it to the National Alzheimer's Coordinating Centers autopsy cohort study, and an AIDS incubation study. Our methods are publicly available in an R package, tranSurv.

Proposals on Kaplan-Meier plots in medical research and a survey of stakeholder views: KMunicate

OBJECTIVES

To examine reactions to the proposed improvements to standard Kaplan-Meier plots, the standard way to present time-to-event data, and to understand which (if any) facilitated better depiction of (1) the state of patients over time, and (2) uncertainty over time in the estimates of survival.

DESIGN

A survey of stakeholders' opinions on the proposals.

SETTING

A web-based survey, open to international participation, for those with an interest in visualisation of time-to-event data.

PARTICIPANTS

1174 people participated in the survey over a 6-week period. Participation was global (although primarily Europe and North America) and represented a wide range of researchers (primarily statisticians and clinicians).

MAIN OUTCOME MEASURES

Two outcome measures were of principal importance: (1) participants' opinions of each proposal compared with a 'standard' Kaplan-Meier plot; and (2) participants' overall ranking of the proposals (including the standard).

RESULTS

Most proposals were more popular than the standard Kaplan-Meier plot. The most popular proposals in the two categories, respectively, were an extended table beneath the plot depicting the numbers at risk, censored and having experienced an event at periodic timepoints, and CIs around each Kaplan-Meier curve.

CONCLUSIONS

This study produced a high response number, reflecting the importance of graphics for time-to-event data. Those producing and publishing Kaplan-Meier plots-both authors and journals-should, as a starting point, consider using the combination of the two favoured proposals.

A comparison of survival analysis methods for cancer gene expression RNA-Sequencing data

Identifying genetic biomarkers of patient survival remains a major goal of large-scale cancer profiling studies. Using gene expression data to predict the outcome of a patient's tumor makes biomarker discovery a compelling tool for improving patient care. As genomic technologies expand, multiple data types may serve as informative biomarkers, and bioinformatic strategies have evolved around these different applications. For categorical variables such as a gene's mutation status, biomarker identification to predict survival time is straightforward. However, for continuous variables like gene expression, the available methods generate highly-variable results, and studies on best practices are lacking. We investigated the performance of eight methods that deal specifically with continuous data. K-means, Cox regression, concordance index, D-index, 25th-75th percentile split, median-split, distribution-based splitting, and KaplanScan were applied to four RNA-sequencing (RNA-seq) datasets from the Cancer Genome Atlas. The reliability of the eight methods was assessed by splitting each dataset into two groups and comparing the overlap of the results. Gene sets that had been identified from the literature for a specific tumor type served as positive controls to assess the accuracy of each biomarker using receiver operating characteristic (ROC) curves. Artificial RNA-Seq data were generated to test the robustness of these methods under fixed levels of gene expression noise. Our results show that methods based on dichotomizing tend to have consistently poor performance while C-index, D-index, and k-means perform well in most settings. Overall, the Cox regression method had the strongest performance based on tests of accuracy, reliability, and robustness.

Exaggeration of PFS by blinded, independent, central review (BICR)

BACKGROUND

Recent published studies have shown meaningful discrepancies between local investigator and blinded, independent, central review (BICR) assessed median progression-free survival (PFS). When the local review but not BICR shows progression, generally, no further assessments are carried out and patients are censored in the BICR analysis, leading to violation of the statistical assumptions of independence between censoring and outcome used in survival analysis methods.

METHODS

We carried out a simulation study to assess methodological reasons behind these discrepancies and corroborated our findings in a case study of three BRCA-mutated ovarian cancer trials. We briefly outline possible methodological solutions that may lead to improved estimation of the BICR medians.

RESULTS

The Kaplan-Meier (KM) curve for the BICR PFS can often be exaggerated. The degree of bias is largest when there is reasonably strong correlation between BICR and local PFS, especially when PFS is long compared with assessment frequency. This can result in an exaggeration of the medians and their difference; however, the hazard ratio (HR) is much less susceptible to bias. Our simulation shows that when the true BICR median PFS was 19 months, and patients assessed every 12 weeks, the estimated KM curves were materially biased whenever the correlation between BICR and local PFS was 0.4 or greater. This was corroborated by case studies where, in the active arm, the BICR median PFS was between 6 and 11 months greater than the local median PFS. Further research is required to find improved methods for estimating BICR survival curves.

CONCLUSIONS

In general, when there is a difference between local and BICR medians, the true BICR KM curve is likely to be exaggerated and its true median will probably lie somewhere between the observed local and BICR medians. Presentation of data should always include both BICR and local results whenever a BICR is carried out.

Interim analysis of binary outcome data in clinical trials: a comparison of five estimators

In clinical trials, where the outcome of interest is the occurrence of an event over a fixed time period, estimation of the event proportion at interim analysis can form a basis for decision-making such as early trial termination, sample size re-estimation, and/or dropping inferior treatment arms. In addition to derivation of mean squared error under an exponential time-to-event distribution, we performed a simulation study to examine the performance of five estimators of the event proportion when time to the event is assessable. The simulation results showed advantages of the Kaplan-Meier estimator over others in terms of robustness, and the bias and variability of the event proportion estimate. An example was given to illustrate how the estimators affect dropping treatment arms in a multi-arm multi-stage adaptive trial. We recommended the use of the Kaplan-Meier estimator and discourage the use of other estimators that discard the inherent time-to-event information.

A 23-year study of mortality and development of co-morbidities in patients with obesity undergoing bariatric surgery (laparoscopic gastric banding) in comparison with medical treatment of obesity

Background and aim

Several studies have shown that bariatric surgery reduces long term mortality compared to medical weight loss therapy. In a previous study we have demonstrated that gastric banding (LAGB) is associated with reduced mortality in patients with and without diabetes, and with reduced incidence of obesity co-morbidities (cardiovascular disease, diabetes, and cancer) at a 17 year follow-up. The aim of this study was to verify at a longer time interval (23 years) mortality and incidence of co-morbidities in patients undergoing LAGB or medical weight loss therapy.

Patients and methods

As reported in the previous shorter-time study, medical records of obese patients [body mass index (BMI) > 35 kg/m² undergoing LAGB (n = 385; 52 with diabetes) or medical treatment (controls, n = 681; 127 with diabetes), during the period 1995–2001 (visit 1)] were collected. Patients were matched for age, sex, BMI, and blood pressure. Identification codes of patients were entered in the Italian National Health System Lumbardy database, that contains life status, causes of death, as well as exemptions, prescriptions, and hospital admissions (proxies of diseases) from visit 1 to June 2018. Survival was compared across LAGB patients and matched controls using Kaplan–Meier plots adjusted Cox regression analyses.

Results

Final observation period was 19.5 ± 1.87 years (13.4–23.5). Compared to controls, LAGB was associated with reduced mortality [HR = 0.52, 95% CI 0.33–0.80, p = 0.003], significant in patients with diabetes [HR = 0.46, 95% CI 0.22–0.94, p = 0.034], borderline significant in patients without diabetes [HR = 0.61, 95% CI = 0.35–1.05, p = 0.076]. LAGB was associated with lower incidence of diabetes (15 vs 75 cases, p = 0.001), of CV diseases (61 vs 226 cases, p = 0.009), of cancer (10 vs 35, p = 0.01), and of renal diseases (0 vs 35, p = 0.001), and of hospital admissions (92 vs 377, p = 0.001).

Conclusion

The preventive effect of LAGB on mortality is maintained up to 23 years, even with a decreased efficacy compared with the shorter-time study, while the preventive effect of LAGB on co-morbidities and on hospital admissions increases with time.

Electronic supplementary material

The online version of this article (10.1186/s12933-018-0801-1) contains supplementary material, which is available to authorized users.

Asymptotic convergence in distribution of the area bounded by prevalence-weighted Kaplan-Meier curves using empirical process modelling

The Kaplan-Meier product-limit estimator is a simple and powerful tool in time to event analysis. An extension exists for populations stratified into cohorts where a population survival curve is generated by weighted averaging of cohort-level survival curves. For making population-level comparisons using this statistic, we analyse the statistics of the area between two such weighted survival curves. We derive the large sample behaviour of this statistic based on an empirical process of product-limit estimators. This estimator was used by an interdisciplinary National Institutes of Health-Social Security Administration team in the identification of medical conditions to prioritize for adjudication in disability benefits processing.

Risk factors associated with post-loading implant loss of removable and fixed implant-supported prostheses in edentulous jaws

PURPOSE

This study analyzed risk factors for post-loading implant loss in cases of implant-supported prostheses applied to edentulous jaws of Japanese patients.

METHODS

In total, 245 dental implant fixtures placed in 54 edentulous jaws of 46 patients performed at Niigata University Hospital were retrospectively analyzed. Kaplan-Meier curves were used to estimate the cumulative survival rate (SR) of implants, and multiple Cox regression analysis was used to identify predictive factors of implant loss. The following risk factors for implant failure were examined: age, sex, survival time, implant length, implant location, smoking habit, bone density, bone augmentation, opposing dentition, loading period, and type of final restoration. The Cochran-Mantel-Haenszel test was used to examine difference in survival curves of the extracted predictors.

RESULTS

Sixteen implants failed during the observation period (SR=92.8 %). Multiple Cox regression analysis revealed that male sex [hazard ratio (HR)=16.1; p=0.007] and use of maxillary removable restorations (HR=12.7; p<0.000) were risk factors for implant failure. Other factors had no significant effect on implant failure. The SR of implants for males (SR=86.9%) was significantly lower than that for females (SR=99.1%). The SR of implants for maxillary removable restorations (SR=76.4%) was significantly lower than for maxillary fixed restorations (SR=99.1%) and mandibular fixed restorations (SR=97.8%).

CONCLUSIONS

Maxillary implants with removable restorations and male sex were risk factors for implant failure among Japanese edentulous patients.

Outcome of Secondary Stroke Prevention in Patients Taking Non-Vitamin K Antagonist Oral Anticoagulants

BACKGROUND

Since non-vitamin K antagonist oral anticoagulants (NOACs) were released for clinical use, many studies have investigated its effectiveness in stroke prevention. In this study, to determine whether or not there is a difference in outcome in secondary stroke prevention between warfarin and NOACs, patients with embolic stroke with newly prescribed anticoagulants were prospectively analyzed.

METHODS

Patients with acute ischemic stroke, who newly started anticoagulant therapy, were consecutively asked to participate in this study. Enrolled patients (76.3 ± 11.0 years old) were classified into warfarin (n = 48), dabigatran (n = 73), rivaroxaban (n = 49), and apixaban (n = 65). The outcome in 1 year was prospectively investigated at outpatient clinic or telephone interview. Recurrence of stroke and death was considered as the critical incidence.

RESULTS

The prevalence of risk factors was not different among all medicines. Patients with dabigatran showed significantly younger onset age (P < .001: 72.2 years old) and milder neurologic deficits than patients on other medicines (P < .001). Cumulative incident rates were 7.1%, 15.3%, 19.0%, and 29.7% for dabigatran, apixaban, rivaroxaban, and warfarin, respectively. Dabigatran showed relatively better outcome compared with warfarin (P = .069) and rivaroxaban (P = .055). All patients on NOACs presented lower cumulative stroke recurrence compared with warfarin.

CONCLUSION

Even in the situation of secondary stroke prevention, noninferiority of NOACs to warfarin might be demonstrated.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes

Background:

Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes.

Materials and Methods:

This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model (P < 0.20) were entered into the multivariate Cox and parametric models (P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS).

Results:

Using Kaplan–Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy (P < 0.05).

Conclusion:

According to AIC, “log-normal” model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges

The Kaplan-Meier (K-M) method is currently the preferred approach to derive an efficacy estimate from anti-malarial trial data. In this approach event times are assumed to be continuous and estimates are generated on the assumption that there is only one cause of failure. In reality, failures are captured at pre-scheduled time points and patients can fail treatment due to a variety of causes other than the primary endpoint, commonly termed competing risk events. Ignoring these underlying assumptions can potentially distort the derived efficacy estimates and result in misleading conclusions. This review details the evolution of statistical methods used to derive anti-malarial efficacy for uncomplicated Plasmodium falciparum malaria and assesses the limitations of the current practices. Alternative approaches are explored and their implementation is discussed using example data from a large multi-site study.

A retrospective analysis comparing APCEDEN® dendritic cell immunotherapy with best supportive care in refractory cancer

AIM

A retrospective survival benefit analysis of APCEDEN^®, APAC BIOTECH Pvt Ltd 69, Jacranda Marg, DLF PHASE II, Gurugram, Haryana, India, an autologous dendritic cell-based product for management of refractory solid malignancies, was performed in comparison with a control group.

METHODS

Subjects (retrospective data) whose survival data, geographical region, age, gender, ECOG performance status and stage of disease that could be matched with the treatment group were considered for analysis.

RESULTS

The analysis suggests a significant survival benefit of 199 days for the APCEDEN therapy treatment group when compared with the control group (356 vs 157 days). The event-free survival time of APCEDEN therapy was 439 days in patients who demonstrated an objective response at first evaluation as per immune-related response criteria.

CONCLUSION

APCEDEN demonstrated highly convincing survival benefits when compared with the control group.

A prognostic 4-lncRNA expression signature for lung squamous cell carcinoma

The outcomes of Lung squamous cell carcinoma (LUSC) is still challenging to evaluate or predict. We aimed to screen prognostic lncRNAs and to mine their roles in LUSC. RNA-Seq data of primary lung cancer were extracted from the Cancer Genome Atlas. Generally, changed lncRNAs in cancer samples were screened and analyzed in univariate survival analysis for identification of prognostic lncRNAs. Robust likelihood-based survival model was generated and random sampling iterations were performed 1000 times to calculate the frequency of feature key lncRNAs. Clustering and multivariate survival analysis of these lncRNAs was used to evaluate their functions and impacts on prognosis. Finally, the stability and validity of the optimal clustering model were verified. In total, we obtained 5664 generally changed lncRNAs among primary lung cancer samples, including 289 identified relating to prognosis in univariate survival analysis. Robust likelihood-based survival modelling for 1000 iterations generated 11 feature lncRNAs with frequency larger than 300. Their interacting proteins were found participating in DNA repairing and cell proliferation. Among stable assembly of 11 lncRNAs, a 4-lncRNA model was selected finally with high stability and feasibility. The ideal 4-lncRNA model can cluster patient samples with significant difference, providing new avenues for the prognostic predication of LUSC.

Identification of a prognostic 5-Gene expression signature for gastric cancer

PURPOSE

Gastric cancer (GC) is a major tumor throughout the world with remaining high morbidity and mortality. The aim is to generate a gene model to assess the prognoses risk of patients with GC.

METHODS

Gene expression profiling of gastric cancer patients, GSE62254 (300 samples) and GSE26253 (432 samples), was downloaded from Gene Expression Omnibus (GEO) database. Univariate survival analysis and LASSO (Least Absolute Shrinkage and Selectionator operator) (1000 iterations) of differentially expressed genes in GSE62254 was assessed using survival and glmnet in R package, respectively. Kaplan-Meier analysis on the clustering algorithm from each regression model was performed to calculate the influence to the prognosis. Random samples in GSE26253 were analyzed in multivariate and univariate survival analysis for one thousand times to calculate statistical stability of each regression model.

RESULTS

A total of 854 Genes were identified differentially expressed in GSE62254, among which 367 Genes were found influencing the prognoses. Six gene clusters were selected with good stability. Hereinto, five or more genes in 11-Gene model, TRPC1, SGCE, TNFRSF11A, LRRN1, HLF, CYS1, PPP1R14A, NOV, NBEA, CES1 and RGN, was available to evaluate the prognostic risk of GC patients in GSE26253 (P = 0.00445). The validity and reliability was validated.

CONCLUSION

In conclusion, we successfully generated a stable 5-Gene model, which could be utilized to predict prognosis of GC patients and would contribute to postoperational treatment and follow-up strategies.

Age alone is not a predictor for survival in glioblastoma

Over half of glioblastoma (GBM) cases are diagnosed in patients older than 65 years. Their median overall survival (OS) is 4-5 months, compared with 12-14 months in patients younger than 70 years. This retrospective audit aims to identify patterns of care and survival of patients diagnosed with GBM at a single institution in Melbourne, Australia. Consecutive histological diagnoses of adult primary GBM from January 2010 to December 2012 were retrospectively identified from medical records. Demographic, treatment and survival characteristics were recorded until death, with follow-up to January 1st 2015. Survival was estimated by Kaplan-Meier method. Planned, sub-group analyses were conducted using multivariate Cox proportional hazards model to identify differences between elderly and younger cohorts, as well as ECOG. 165 patients were identified (36 % aged ≥70 years). Those ≥70 years had a poorer performance status (ECOG 3-4: 27 vs 10 %, p = .005); poorer median OS (2.6 vs 11.5 months, p < .001); and were less likely to receive adjuvant treatment (no treatment: 40 vs 16 %, p < .001) compared with patients <70 years. Age was not a significant predictor of poorer os (HR 1.0; 0.99-1.03; p > .05), after adjusting for other clinical factors. Significant predictors of poorer os were poor performance status (p = .001), bilateral tumours (p = .04), biopsy only (p = .001), and no adjuvant treatment (p < .001). In patients diagnosed with GBM, those older than 70 years often present with poor performance status, are less likely to receive adjuvant treatment and have inferior os compared with younger patients. Treatment recommendations should be based on performance status/fitness, not age alone.

Product limit estimation for capturing of pressure distribution dynamics

Measurement of contact pressures at the wheelchair-seating interface is a critically important approach for laboratory research and clinical application in monitoring risk for pressure ulceration. As yet, measures obtained from pressure mapping are static in nature: there is no accounting for changes in pressure distribution over time, despite the well-known interaction between time and pressure in risk estimation. Here, we introduce the first dynamic analysis for distribution of pressure data, based on the Kaplan-Meier (KM) Product Limit Estimator (PLE) a ubiquitous tool encountered in clinical trials and survival analysis. In this approach, the pressure array-over-time data set is sub-sampled two frames at a time (random pairing), and their similarity of pressure distribution is quantified via a correlation coefficient. A large number (here: 100) of these frame pairs is then sorted into descending order of correlation value, and visualized as a KM curve; we build confidence limits via a bootstrap computed over 1000 replications. PLEs and the KM have robust statistical support and extensive development: the opportunities for extended application are substantial. We propose that the KM-PLE in particular, and dynamic analysis in general, may provide key leverage on future development of seating technology, and valuable new insight into extant datasets.

Midterm survivorship and clinical outcome of INDUS knee prosthesis: 5 year followup study

BACKGROUND

INDUS knee implant has been designed as per the anatomical morphology of the Indian population and has shown good clinical outcome in short term studies. The purpose of the present study was to report the midterm survivorship and clinical outcome of this implant.

MATERIALS AND METHODS

Two hundred and twenty three primary total knee arthroplasties in 209 consecutive patients using the INDUS knee prosthesis were prospectively enrolled. There were 145 females (155 knees) and 64 males (68 knees) with a mean age of 69.95 years (range 42-86 years). Annual followup with clinical and radiological examination was conducted, and a survivorship analysis was done using the Kaplan-Meier analysis.

RESULTS

Mean followup was 5.8 years (range 5-6.5 years). Eleven patients died while eight were lost to followup and a total of 204 knees were available for followup. The mean knee flexion improved from preoperative 110.4° ± 11.24° (range 60°-130°) to 128.17° ± 8.32° (range 100°-140°) at the final followup. The mean knee score improved from 40.1 ± 10.7 to 90.3 ± 5.34 while the function score improved from 44.35 ± 12.9 to 89.58 ± 7.43. Two patient developed infection and required revision. The Kaplan-Meier analysis reported a survivorship of 98.6% (confidence interval 95.7-99.6%) at the end for 5 years for INDUS knee prosthesis.

CONCLUSION

INDUS knee prosthesis has excellent survivorship with a good clinical outcome and low failure rate.

Age at hysterectomy as a predictor for subsequent pelvic organ prolapse repair

INTRODUCTION AND HYPOTHESIS

The aim of this study was to investigate the association between patient age at the time of hysterectomy and subsequent pelvic organ prolapse (POP) surgery.

METHODS

We gathered data on all benign hysterectomies and POP surgeries performed in Denmark on Danish women from 1977 to 2009 from the Danish National Patient Registry. The cohort consisted of 154,882 hysterectomized women, who were followed up for up to 32 years. Survival analysis for each age group at hysterectomy was performed using Kaplan-Meier product limit methods.

RESULTS

For all hysterectomized women, we found that low age at hysterectomy yielded a lower risk of subsequent POP surgery than did hysterectomy at an older age. This difference diminished after stratification by indication; all non-POP hysterectomies had a low cumulative incidence at 8-11 % at the end of the follow-up period. For all women hysterectomized, the predominant compartment for POP surgery was the posterior. Women hysterectomized when aged over 66 years had a higher proportion of POP surgery in the apical compartment than in the other age groups (p = 0.000).

CONCLUSION

Our findings indicate that age at hysterectomy only marginally influences the risk of subsequent POP surgery for women hysterectomized for indications other than POP. If POP is the indication for hysterectomy, the risk of undergoing subsequent POP surgery increases substantially.

Prolonging the survival of Tsc2 conditional knockout mice by glutamine supplementation

The genetic disease tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by loss of function mutations in either TSC1 (hamartin) or TSC2 (tuberin), which serve as negative regulators of mechanistic target of rapamycin complex 1 (mTORC1) activity. TSC patients exhibit developmental brain abnormalities and tuber formations that are associated with neuropsychological and neurocognitive impairments, seizures and premature death. Mechanistically, TSC1 and TSC2 loss of function mutations result in abnormally high mTORC1 activity. Thus, the development of a strategy to inhibit abnormally high mTORC1 activity may have therapeutic value in the treatment of TSC. mTORC1 is a master regulator of growth processes, and its activity can be reduced by withdrawal of growth factors, decreased energy availability, and by the immunosuppressant rapamycin. Recently, glutamine has been shown to alter mTORC1 activity in a TSC1-TSC2 independent manner in cells cultured under amino acid- and serum-deprived conditions. Since starvation culture conditions are not physiologically relevant, we examined if glutamine can regulate mTORC1 in non-deprived cells and in a murine model of TSC. Our results show that glutamine can reduce phosphorylation of S6 and S6 kinase, surrogate indicators of mTORC1 activity, in both deprived and non-deprived cells, although higher concentrations were required for non-deprived cultures. When administered orally to TSC2 knockout mice, glutamine reduced S6 phosphorylation in the brain and significantly prolonged their lifespan. Taken together, these results suggest that glutamine supplementation can be used as a potential treatment for TSC.

Single nucleotide polymorphisms in the mitochondrial displacement loop and age at onset of non-Hodgkin lymphoma

OBJECTIVE

Single nucleotide polymorphisms (SNPs) accumulated frequently in the mitochondrial displacement loop (D-loop) in many cancers. We had identified cancer risk-associated SNPs in the D-loop of non-Hodgkin lymphoma (NHL) patients previously, in this study, we investigated the association of age at onset and D-loop SNPs in NHL patients.

MATERIALS AND METHODS

The D-loop region of mtDNA was sequenced for 133 NHL patients recorded at the Fourth Hospital of Hebei Medical University. The Kaplan-Meier method was used to identify age at onset-associated SNPs in the D-loop of NHL patients. The Cox proportional hazards model was used to identify independent risk factors for age at onset.

RESULTS

The SNP sites of nucleotides 146C/T, 151T/C, 194T/C, 315C/C insert, 523Del/A, and 525Del/C were identified for their association with age at onset, by the logrank test. In an overall multivariate analysis, allele 146 (relative risk, 0.403; 95% confidence interval [CI]: 0.182-0.895) (P = 0.026), allele 151 (relative risk, 0.378; 95% CI: 0.165-0.868) (P = 0.022), and allele 315 (relative risk, 3.554; 95% CI: 1.344-9.400) (P = 0.011) were identified as independent predictors for age at onset in NHL patients.

CONCLUSION

SNPs in the D-loop can predict age at onset in NHL patients. Analysis of the D-loop SNPs can help identify NHL patient subgroups at high risk of early onset.

Sensitivity Analyses Comparing Time-to-Event Outcomes Existing Only in a Subset Selected Postrandomization

In some randomized studies, researchers are interested in determining the effect of treatment assignment on outcomes that may exist only in a subset chosen after randomization. For example, in preventative human immunodeficiency virus (HIV) vaccine efficacy trials, it is of interest to determine whether randomization to vaccine affects postinfection outcomes that may be right-censored. Such outcomes in these trials include time from infection diagnosis to initiation of antiretroviral therapy and time from infection diagnosis to acquired immune deficiency syndrome. Here we present sensitivity analysis methods for making causal comparisons on these postinfection outcomes. We focus on estimating the survival causal effect, defined as the difference between probabilities of not yet experiencing the event in the vaccine and placebo arms, conditional on being infected regardless of treatment assignment. This group is referred to as the always-infected principal stratum. Our key assumption is monotonicity-that subjects randomized to the vaccine arm who become infected would have been infected had they been randomized to placebo. We propose nonparametric, semiparametric, and parametric methods for estimating the survival causal effect. We apply these methods to the first Phase III preventative HIV vaccine trial, VaxGen's trial of AIDSVAX B/B.