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The hazard function represents one of the main quantities of interest in the analysis of survival data. We propose a general approach for parametrically modelling the dynamics of the hazard function using systems of autonomous ordinary differential equations (ODEs). This modelling approach can be used to provide qualitative and quantitative analyses of the evolution of the hazard function over time. Our proposal capitalises on the extensive literature on ODEs which, in particular, allows for establishing basic rules or laws on the dynamics of the hazard function via the use of autonomous ODEs. We show how to implement the proposed modelling framework in cases where there is an analytic solution to the system of ODEs or where an ODE solver is required to obtain a numerical solution. We focus on the use of a Bayesian modelling approach, but the proposed methodology can also be coupled with maximum likelihood estimation. A simulation study is presented to illustrate the performance of these models and the interplay of sample size and censoring. Two case studies using real data are presented to illustrate the use of the proposed approach and to highlight the interpretability of the corresponding models. We conclude with a discussion on potential extensions of our work and strategies to include covariates into our framework. Although we focus on examples of Medical Statistics, the proposed framework is applicable in any context where the interest lies in estimating and interpreting the dynamics of the hazard function., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Prior distributions, which represent one's belief in the distributions of unknown parameters before observing the data, impact Bayesian inference in a critical and fundamental way. With the ability to incorporate external information from expert opinions or historical datasets, the priors, if specified appropriately, can improve the statistical efficiency of Bayesian inference. In survival analysis, based on the concept of unit information (UI) under parametric models, we propose the unit information Dirichlet process (UIDP) as a new class of nonparametric priors for the underlying distribution of time-to-event data. By deriving the Fisher information in terms of the differential of the cumulative hazard function, the UIDP prior is formulated to match its prior UI with the weighted average of UI in historical datasets and thus can utilize both parametric and nonparametric information provided by historical datasets. With a Markov chain Monte Carlo algorithm, simulations and real data analysis demonstrate that the UIDP prior can adaptively borrow historical information and improve statistical efficiency in survival analysis., (© The Author(s) 2024. Published by Oxford University Press on behalf of The International Biometric Society.)

Background and Objectives: Mean survival time (MST) is used as the indicator of prognosis in patients with a colorectal cancer (CRC) recurrence. The present study aimed to visualize the changes in death risk after a CRC recurrence using hazard function analysis (HFA) to provide an alternative prognostic indicator to MST., Methods: The medical records of 725 consecutive patients with a recurrence following R0 radical surgery for CRC were retrospectively reviewed., Results: The five-year, post-recurrence survival rate was 37.8%, and the MST was 3.5 years while the risk of death peaked at 2.9 years post-recurrence. Seven variables were found to predict short-term survival, including the number of metastatic organs ≥ 2, non-surgical treatment for the recurrence, and a short interval before recurrence. In patients with a recurrence in one organ, the MST was four years, the peak time of death predicted by HFA was 2.9 years, and the five-year survival rate was 45.8%. In patients with a surgical resection of the recurrence, the MST was 8 years, the peak time of death was 3.3 years, and the five-year survival rate was 62%., Conclusions: The present study established a novel method of assessing changes in mortality risk over time using HFA in patients with a CRC recurrence., (© 2024. The Author(s).)

Objectives: The choice of therapeutic intervention for postoperative air leak varies between institutions. We aimed to identify the optimal timing and patient criteria for therapeutic intervention in cases of postoperative air leaks after lung resection., Methods: This study utilized data from a prospective multicenter observational study conducted in 2019. Among the 2187 cases in the database, 420 cases with air leaks on postoperative day 1 were identified. The intervention group underwent therapeutic interventions, such as pleurodesis or surgery, while the observation group was monitored without intervention. A comparison between the intervention group and the observation group were analyzed using the cumulative distribution and hazard functions., Results: Forty-six patients (11.0%) were included in the intervention group. The multivariate analysis revealed that low body mass index ( p = 0.019), partial resection ( p = 0.010), intraoperative use of fibrin glue ( p = 0.008), severe air leak on postoperative day 1 ( p < 0.001), and high forced expiratory volume in 1 s ( p = 0.021) were significant predictors of the requirement for intervention. The proportion of patients with persistent air leak in the observation group was 20% on postoperative day 5 and 94% on postoperative day 7. The hazard of air leak cessation peaked from postoperative day 3 to postoperative day 7., Conclusions: This research contributes valuable insights into predicting therapeutic interventions for postoperative air leaks and identifies scenarios where spontaneous cessation is probable. A validation through prospective studies is warranted to affirm these findings.

Aim: This study aimed to examine how malnutrition, as reflected by the Geriatric Nutritional Risk Index (GNRI), is associated with colorectal cancer (CRC) recurrence and cause of death., Methods: Consecutive stage I-III CRC patients (n = 601) were divided into two groups using GNRI 98 as the cutoff. The relationship of GNRI with overall survival (OS) and recurrence-free survival (RFS) was evaluated, followed by competing risk analysis to determine prognostic factors of non-CRC-related death, and hazard function analysis to examine changes in the risk of recurrence and death., Results: Median body mass index was lower in the low GNRI group than in the high GNRI group (19.8 vs. 23.5; p < 0.001). After adjusting for known prognostic factors, a low GNRI was independently associated with reduced OS/RFS, and was a significant predictor of non-CRC-related death. The risk of recurrence was higher and peaked earlier in the low GNRI group than in the high GNRI group, although after 3 years, both groups had a similar risk. Meanwhile, the low GNRI group had a higher risk of non-CRC-related death over the course of 5 years., Conclusion: It is important to consider preoperative nutritional status along with the cancer stage when developing strategies to improve outcomes for CRC patients., (© 2023 Wiley Periodicals LLC.)

Predicting recurrence patterns of hepatocellular carcinoma (HCC) can be helpful in developing surveillance strategies. This study aimed to use the hazard function to investigate recurrence hazard and peak recurrence time transitions in patients with HCC undergoing liver resection (LR). We enrolled 1204 patients with HCC undergoing LR between 2007 and 2018 at our institution. Recurrence hazard, patterns, and peak rates were analyzed. The overall recurrence hazard peaked at 7.2 months (peak hazard rate [pHR]: 0.0197), but varied markedly. In subgroups analysis based on recurrence risk factors, patients with a high radiographic tumor burden score (pHR: 0.0521), alpha-fetoprotein level ≥ 400 ng/ml (pHR: 0.0427), and pT3-4 (pHR: 0.0656) showed a pronounced peak within the first year after LR. Patients with cirrhosis showed a pronounced peak within three years after LR (pHR: 0.0248), whereas those with Barcelona Clinic Liver Cancer stage B (pHR: 0.0609) and poor tumor differentiation (pHR: 0.0451) showed multiple peaks during the 5-year follow-up period. In contrast, patients without these recurrence risk factors had a relatively flat hazard function curve. HCC recurrence hazard, patterns, and peak rates varied substantially depending on different risk factors of HCC recurrence., (© 2023. Italian Society of Surgery (SIC).)

Background and Objectives: This study examined the trend of hazards for postoperative recurrence of lung cancer according to pathologic stages., Methods: We reviewed the records of 1987 patients who underwent resection for lung cancer between 2007 and 2012. Postoperative recurrence and development of second primary lung cancer were analyzed to evaluate the trend of hazard rate., Results: Recurrence-free survival (RFS) probabilities at 5 postoperative years in patients with stage I/II/III disease were 87.8%/54.7%,/33.4%, respectively. The hazard rate of RFS was consistently low (<0.005) for stage I patients for 5 years after surgery. The hazard rate of RFS for stage II patients showed a peak of 0.016 at 12.4 months after surgery, and that for stage III patients had a higher peak of 0.029 at 13.7 months after surgery, after which they showed a gradual decrease. The hazard rate for the development of second primary lung cancer exceeded that of recurrence of first primary lung cancer after 72 months postoperatively., Conclusions: Short-interval postoperative surveillance might be unnecessary for stage I patients but should be considered in stage II/III patients. Screening of second primary lung cancer rather than surveillance of recurrence might be beneficial after more than 6 years postoperatively., (© 2023 Wiley Periodicals LLC.)

Objectives: When extrapolating time-to-event data the Bagust and Beale (B&B) approach uses the Kaplan-Meier survival function until a manually chosen time point, after which a constant hazard is assumed. This study demonstrates an objective statistical approach to estimate this time point., Methods: We estimate piecewise exponential models (PEMs), whereby the hazard function is partitioned into segments each with constant hazards. The boundaries of these segments are known as change points. Our approach determines the location and number of change points in PEMs from which the hazard in the final segment is used to model long-term survival. We reviewed previous applications of the B&B approach in National Institute for Health and Care Excellence Technology Appraisals (TAs) completed between July 2011 and June 2017. The time points after which constant hazards were assumed were compared between PEMs and the B&B approaches. When further survival data were published following the original TA, we compared these updated estimates to predicted survival from the PEM and other parametric models adjusted for general population mortality., Results: Six of the 59 TAs in this review considered the B&B approach. There was general agreement between the location of time points identified through the PEM and the B&B approaches. In 2 of the identified TAs the best fitting model to the data was a no-change-point model. Of the 3 TAs for which further survival data became available, PEM provided the closest prediction for survival outcomes in 2 TAs., Conclusions: PEMs are useful for survival extrapolation when a long-term constant hazard trend for the disease is clinically plausible., (Copyright © 2023. Published by Elsevier Inc.)

Objective: Surgical mortality has traditionally been assessed at arbitrary intervals out to 1 year, without an agreed optimum time point. The aim of our study was to investigate the time-varying risk of death after lobectomy to determine the optimum period to evaluate surgical mortality rate after lobectomy for lung cancer., Methods: We performed a retrospective study of patients undergoing lobectomy for lung cancer at our institution from 2015 to 2022. Parametric survival models were assessed and compared with a nonparametric kernel estimate. The hazard function was plotted over time according to the best-fit statistical distribution. The time points at which instantaneous hazard rate peaked and stabilized in the 1-year period after surgery were then determined., Results: During the study period, 2284 patients underwent lobectomy for lung cancer. Cumulative mortality at 30, 90, and 180 days was 1.3%, 2.9%, and 4.9%, respectively. Log-logistic distribution showed the best fit compared with other statistical distribution, indicated by the lowest Akaike information criteria value. The instantaneous hazard rate was greatest during the immediate postoperative period (0.129; 95% confidence interval, 0.087-0.183) and diminishes rapidly within the first 30 days after surgery. Instantaneous hazard rate continued to decrease past 90 days and stabilized only at approximately 180 days., Conclusions: In-hospital mortality is the optimal follow-up period that captures the early-phase hazard during the immediate postoperative period after lobectomy. Thirty-day mortality is not synonymous to "early mortality," as instantaneous hazard rate remains elevated well past the 90-day time point and only stabilizes at approximately 180 days after lobectomy., Competing Interests: E.L. reports personal fees from Covidien, Roche, Lilly Oncology, Boehringer Ingelheim, Medela, Ethicon, AstraZeneca, Beigene, Roche, and BMS; grants and personal fees from ScreenCell; and grants from Clearbridge Biomedics, Illumina, and Guardant Health, outside the submitted work. In addition, E.L. has patents P52435GB and P57988GB issued to Imperial Innovations. E.L. is Chief Investigator for VIOLET NIHR HTA (13/04/03), MARS 2 NIHR HTA (15/188/31), and RAMON NIHR HTA (131306); and founder of My Cancer Companion Healthcare Companion, Ltd. All other authors reported no conflicts of interest. The Journal policy requires editors and reviewers to disclose conflicts of interest and to decline handling or reviewing manuscripts for which they may have a conflict of interest. The editors and reviewers of this article have no conflicts of interest., (Crown Copyright © 2023 Published by Elsevier Inc. on behalf of The American Association for Thoracic Surgery.)

A designer of sustainable biocomposite structures and natural ropes needs to have a high confidence interval (95% CI) for mechanical characteristics data of performance materials, yet qualities for plant-based fibers are very diverse. A comprehensive study of the elements that enhance the performance of biocomposites or sustainable ropes created from vegetable fibers is necessary. The current study included five groups with varying numbers (N) of tests of 20, 40, 60, 80, and 100 on the mechanical characteristics at room temperatures. The purpose of this study was to determine how changing N affects the mechanical properties of sisal yarn. These properties include its strength, Young's modulus, and deformation at rupture. A significance testing program including more than 100 tests was performed. Owing to the heterogeneity of the plant yarn, each group received more than 20 samples at a gauge length (GL) of 100 mm. The tensile strength characteristics of sisal yarns produced a wide range of findings, as is common for natural fibers, necessitating a statistical analysis. Its dispersion was explored and measured using the statistical methods. The Weibull distribution with two parameters and a prediction model with a 95% confidence level for maximum likelihood (ML) and least squares (LS) were used to investigate and quantify its dispersion.

It is becoming increasingly accepted that timing tasks, and underlying temporal processes, can be partitioned on the basis of whether they require an explicit or implicit temporal judgement. Most neuroimaging studies of timing associated explicit timing tasks with activation of the supplementary motor area (SMA). However, transcranial magnetic stimulation (TMS) studies perturbing SMA functioning across explicit timing tasks have generally reported null effects, thus failing to causally link SMA to explicit timing. The present study probed the involvement of SMA in both explicit and implicit timing tasks within a single experiment and using High-Definition transcranial Random Noise Stimulation (HD-tRNS), a previously less used technique in studies of the SMA. Participants performed two tasks that comprised the same stimulus presentation but differed in the received task instructions, which might or might not require explicit temporal judgments. Results showed a significant HD-tRNS-induced shift of perceived durations (i.e., overestimation) in the explicit timing task, whereas there was no modulation of implicit timing by HD-tRNS. Overall, these results provide initial non-invasive brain stimulation evidence on the contribution of the SMA to explicit and implicit timing tasks., (Copyright © 2023 Elsevier B.V. All rights reserved.)

An important complexity in censored data is that only partial information on the variables of interest is observed. In recent years, a large family of asymmetric distributions and maximum likelihood estimation for the parameters in that family has been studied, in the complete data case. In this paper, we exploit the appealing family of quantile-based asymmetric distributions to obtain flexible distributions for modelling right censored survival data. The flexible distributions can be generated using a variety of symmetric distributions and monotonic link functions. The interesting feature of this family is that the location parameter coincides with an index-parameter quantile of the distribution. This family is also suitable to characterize different shapes of the hazard function (constant, increasing, decreasing, bathtub and upside-down bathtub or unimodal shapes). Statistical inference is done for the whole family of distributions. The parameter estimation is carried out by optimizing a non-differentiable likelihood function. The asymptotic properties of the estimators are established. The finite-sample performance of the proposed method and the impact of censorship are investigated via simulations. Finally, the methodology is illustrated on two real data examples (times to weaning in breast-fed data and German Breast Cancer data)., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The optimal surveillance period and frequency after curative resection for oesophageal squamous cell carcinoma (OSCC) remain unclear, and current guidelines are mainly based on traditional Kaplan-Meier analyses of cumulative incidence rather than risk analysis. The aim of this study was to determine a suitable follow-up surveillance program following oesophagectomy for OSCC using the hazard function., Methods: A total of 1187 patients who underwent curative resection for OSCC between 2000 and 2014 were retrospectively analyzed. The changes in the estimated hazard rates (HRs) of recurrence over time were analyzed according to tumour-node-metastasis stage., Results: Four hundred seventy-eight (40.2%) patients experienced recurrence during the follow-up period (median, 116.5 months). The risk of recurrence peaked at 9.2 months after treatment (HR = 0.0219) and then decreased to half the peak value at 24 months post-surgery. The HRs for Stage I and II patients were low (< 0.007) post-treatment. The HR for Stage III patients peaked at 9.9 months (HR = 0.031) and the hazard curve declined to a plateau at 30 months. Furthermore, the HR peaked at 10.8 months (HR = 0.052) in Stage IV patients and then gradually declined from 50 months., Conclusions: According to tumour-node-metastasis stage, changes in the HRs of postoperative recurrence in OSCC varied significantly. Intensive surveillance should be undertaken for 3 years in Stage III patients and for 4 years in Stage IV patients, followed by annual screening. For Stage I OSCC patients, a reduction in the surveillance intensity could be taken into consideration., (© 2022. The Author(s).)

Aim: Surgical treatment is the first-line treatment for patients with Barcelona Clinic Liver Cancer (BCLC) stage 0 or A1 hepatocellular carcinoma (HCC), and postoperative monitoring improves long-term survival. We aimed to establish a reasonable short-interval follow-up duration for patients with HCC., Methods: The cohort for this retrospective study included 1396 HCC patients with BCLC stage 0 or A1 disease who underwent curative resection from 2013 to 2016 at five centers in China. Hazard rates for recurrence were calculated using the hazard function., Results: The recurrence rates in patients with BCLC stage 0 and A1 HCC were 46.4% and 58.0%, respectively. The hazard curve for stage 0 patients was relatively flat, and the hazard rate was consistently low (peak hazard rate 0.0163). The hazard rate curve for recurrence was initially high (peak hazard rate 0.0441) in patients with BCLC stage A1 disease and showed a rapid decreasing trend within 1 year, followed by a slow decreasing trend, reaching a low level (<0.0163) at approximately 36 months. The time to low risk was 47, 41, and 51 months in patients with cirrhosis, hepatitis B virus (HBV) infection, and satellite lesions, respectively., Conclusions: A short-interval follow-up of 1 year is sufficient for HCC patients with BCLC stage 0 disease, whereas a short-interval follow-up time of 3 years should be considered for patients with stage A1 disease. The follow-up period should be appropriately prolonged for patients with cirrhosis, HBV infection, and satellite lesions., (© 2022 Japan Society of Hepatology.)

Purpose: The relationship between recurrence and systemic inflammation in the early postoperative period of colorectal cancer (CRC) is unclear, and no study has examined changes in recurrence risk resulting from postoperative inflammation. This study aimed to investigate the prognostic impact of severe postoperative inflammatory response after curative resection of CRC., Methods: Subjects were 422 consecutive CRC patients who underwent curative surgery between 2012 and 2016, with a follow-up period of 5 years after surgery. The prognostic impacts of high and low postoperative C-reactive protein (CRP) levels were examined, and temporal changes in recurrence risk were examined using hazard function analysis., Results: Patients were divided into high (n = 68) and low (n = 354) CRP groups using CRP 12.5 mg/dL as the cut-off based on receiver-operating characteristic (ROC) curve analysis. Multivariable analysis revealed that high CRP was a significant predictor of recurrence (hazard ratio: 2.21; p < 0.001). According to the hazard function of recurrence risk, the hazard rate of the low CRP group peaked at 8.4 months postoperatively (peak hazard rate: 0.0073/month) and decreased thereafter, while that of the high CRP group peaked at 5.6 months (0.0142/month) and was persistently higher than that of the low CRP group for the study duration., Conclusions: A severe inflammatory response in the early postoperative period of CRC increased the recurrence risk, and the recurrence hazard of patients with high CRP levels was earlier and persistently higher than that of patients with low CRP levels. CRC patients with high CRP levels may require more frequent follow-up., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

To optimize postoperative surveillance of lung cancer patients, we investigated the hazard function of tumor recurrence in patients with completely resected lung cancer. We analyzed the records of 12,897 patients in the 2010 Japanese Joint Committee of Lung Cancer Registry who underwent lobectomy to completely resect pathological stage I-III lung cancer. The risk of postoperative recurrence was determined using a cause-specific hazard function. The hazard function for recurrence exhibited a peak at approximately 9 months after surgery, followed by a tapered plateau-like tail extending to 60 months. The peak risk for intrathoracic recurrence was approximately two-fold higher compared with that of extrathoracic recurrence. Subgroup analysis showed that patients with stage IIIA adenocarcinoma had a continuously higher risk of recurrence compared with patients with earlier-stage disease. However, the risk of recurrence in patients with squamous cell carcinoma was not significantly different compared with that more than 24 months after surgery, regardless of pathological stage. In conclusion, the characteristics of postoperative tumor recurrence hazard in a large cohort of lung cancer patients may be useful for determining the time after surgery at which patients are at the highest risk of tumor recurrence. This information may improve stage-related management of postoperative surveillance.

Background: The mortality rate in patients with ankylosing spondylitis (AS) and cervical fracture is relatively high., Objectives: This study aimed to investigate the instantaneous death risk and conditional survival (CS) in patients with AS and cervical fracture. We also studied the relationship between surgical timing and the incidence of complications., Methods: This national multicentre retrospective study included 459 patients with AS and cervical fractures between 2003 and 2019. The hazard function was used to determine the risk of instantaneous death. The five-year CS was calculated to show the dynamic changes in prognosis., Results: The instantaneous death risk was relatively high in the first 6 months and gradually decreased over time in patients with AS and cervical fracture. For patients who did not undergo surgery, the instantaneous risk of death was relatively high in the first 15 months and gradually decreased over time. For patients with American Spinal Injury Association impairment scale (ASIA) A and B, the 5-year CS was 55.3% at baseline, and improved steadily to 88.4% at 2 years. Odds ratios (ORs) for pneumonia, electrolyte disturbance, respiratory insufficiency, and phlebothrombosis decreased as the surgery timing increased., Conclusion: Deaths occurred mainly in the first 6 months after injury and gradually decreased over time. Our study highlights the need for continued surveillance and care in patients with AS with cervical fractures and provides useful survival estimates for both surgeons and patients. We also observed that early surgery can significantly increase functional recovery, and decrease the incidence of complications and rehospitalisation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Huang, Bai, Tan, Hao, Wu, Wang, Wang, Wang, Liu, Chen, Jiang, Ma, Liu, Liu, Cai, Lu, Mao, Wang, Fu, Zhao, Zang, Xie, Yu, Song, Sun, Xiang, Liu, Li, Liao and Wu.)

Measurements of response inhibition components of reactive inhibition and proactive inhibition within the stop-signal paradigm have been of particular interest to researchers since the 1980s. While frequentist nonparametric and Bayesian parametric methods have been proposed to precisely estimate the entire distribution of reactive inhibition, quantified by stop signal reaction times (SSRT), there is no method yet in the stop signal task literature to precisely estimate the entire distribution of proactive inhibition. We identify the proactive inhibition as the difference of go reaction times for go trials following stop trials versus those following go trials and introduce an Asymmetric Laplace Gaussian (ALG) model to describe its distribution. The proposed method is based on two assumptions of independent trial type (go/stop) reaction times and Ex-Gaussian (ExG) models. Results indicated that the four parametric ALG model uniquely describes the proactive inhibition distribution and its key shape features, and its hazard function is monotonically increasing, as are its three parametric ExG components. In conclusion, the four parametric ALG model can be used for both response inhibition components and its parameters and descriptive and shape statistics can be used to classify both components in a spectrum of clinical conditions.

In this work, we define cumulative residual q -Fisher (CRQF) information measures for the survival function (SF) of the underlying random variables as well as for the model parameter. We also propose q -hazard rate (QHR) function via q -logarithmic function as a new extension of hazard rate function. We show that CRQF information measure can be expressed in terms of the QHR function. We define further generalized cumulative residual χ2 divergence measures between two SFs. We then examine the cumulative residual q -Fisher information for two well-known mixture models, and the corresponding results reveal some interesting connections between the cumulative residual q -Fisher information and the generalized cumulative residual χ2 divergence measures. Further, we define Jensen-cumulative residual χ2 (JCR-χ2) measure and a parametric version of the Jensen-cumulative residual Fisher information measure and then discuss their properties and inter-connections. Finally, for illustrative purposes, we examine a real example of image processing and provide some numerical results in terms of the CRQF information measure.

Background and Aim: Although history of colorectal cancer (CRC) is a known risk factor for developing second CRC, the optimal surveillance protocol has not been established. Using hazard function analysis to evaluate changes in the hazard rate for the development of second primary CRCs or high-grade adenomas (HGAs), we aimed to clarify when and on whom to focus in order to effectively identify second primary colorectal neoplasms after initial surgery for CRC., Methods: We retrospectively enrolled 1823 consecutive patients with stage 0-III CRCs who underwent radical surgery between 2004 and 2015, and subsequent colonoscopic surveillance after surgery. The time-course changes in the risk rates for developing metachronous CRC and HGA after surgery were assessed., Results: A peak was observed at 1.22 years after surgery in the hazard function curve for secondary colorectal neoplasms, which decreased until 4 years, then plateaued. Older patients were at higher risk than younger patients, both showing a peak at 1 year. Another peak at 6 to 8 years was observed in younger patients. Male patients showed a higher risk than female patients, and patients with synchronous lesions showed a markedly higher hazard rate than those without, with two distinct peaks around 1 and 9 years after surgery., Conclusions: Intensive colonoscopic surveillance is recommended after surgery for CRC during the first 2 to 3 years, and if the patient is under 60 years old and has concomitant CRC or HGA, surveillance is also recommended at 6 to 8 years after surgery., (© 2021 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

Earlier exposure to binge drinking and tobacco use is associated with higher odds of substance use disorders. Using national youth data from the PATH study, we prospectively estimate the age of initiating past 30-day use of (1) cigarettes, e-cigarettes, and binge drinking, and (2) cigarettes, cigarillos, and binge drinking. Cox proportional hazard models were used to estimate differences in the age of initiation by sex, race/ethnicity, and previous use of other tobacco products. By age 21, 4.4% (95% CI: 3.7-5.2) and 2.0% (95% CI: 1.2-2.8) of youth reported initiation of past 30-day use outcomes (1) and (2), respectively. After controlling for sex and previous use of other tobacco products, statistically significant differences in the age of initiation by race/ethnicity were found for each outcome: Hispanic and non-Hispanic Black youth were less likely than non-Hispanic White youth to initiate past 30-day use of both outcomes (1) and (2) at earlier ages. Although the initiation of both outcomes remained relatively low by age 21, these incidences represent 1.56 million and 700,000 youth, respectively. This study provides the public with evidence to identify the particular ages at which education campaigns may be most effective to prevent youth from initiating these three substances. Further research is needed to estimate the age of initiation of other dual tobacco use patterns with binge drinking.

We introduce new shape-constrained classes of distribution functions on R , the bi- s *-concave classes. In parallel to results of Dümbgen et al. (2017) for what they called the class of bi-log-concave distribution functions, we show that every s -concave density f has a bi- s *-concave distribution function F for s * ≤ s /( s + 1). Confidence bands building on existing nonparametric confidence bands, but accounting for the shape constraint of bi- s *-concavity, are also considered. The new bands extend those developed by Dümbgen et al. (2017) for the constraint of bi-log-concavity. We also make connections between bi- s *-concavity and finiteness of the Csörgő - Révész constant of F which plays an important role in the theory of quantile processes.

The present experiments investigated properties of time-based interventions used to increase self-control. Rats received impulsive-choice assessments before and after interventions that consisted of different distributions of delays to reinforcement. In Experiment 1, rats received an intervention with an increasing hazard function where delays were more evenly distributed, a decreasing hazard function where delays were mostly short, or a constant hazard function where delays were exponentially distributed. Surprisingly, rats that received the decreasing hazard function made the most self-controlled choices. Response rates during intervention trials showed that rats anticipated reinforcement based on the shape of the distributions they received. In Experiment 2, rats received an intervention with a decreasing hazard function with a steep slope or a shallow slope. Both time-based interventions increased self-control and produced similar response-rate patterns, indicating that the slope of the decreasing hazard function may not play a strong role in intervention efficacy. While this research aligns with previous literature showing that time-based interventions improved self-control, exposure to short delays produced the biggest improvements. Ultimately, exposure to short delays may increase the subjective value of the larger-later choice while occasional long delays may promote the ability to wait, which may have important implications for translational applications., (© 2021 Society for the Experimental Analysis of Behavior.)

The aim of this paper is to develop a weighted functional linear Cox regression model that accounts for the association between a failure time and a set of functional and scalar covariates. We formulate the weighted functional linear Cox regression by incorporating a comprehensive three-stage estimation procedure as a unified methodology. Specifically, the weighted functional linear Cox regression uses a functional principal component analysis to represent the functional covariates and a high-dimensional Cox regression model to capture the joint effects of both scalar and functional covariates on the failure time data. Then, we consider an uncensored probability for each subject by estimating the important parameter of a censoring distribution. Finally, we use such a weight to construct the pseudo-likelihood function and maximize it to acquire an estimator. We also show our estimation and testing procedures through simulations and an analysis of real data from the Alzheimer's Disease Neuroimaging Initiative.

How quickly participants respond to a "go" after a "warning" signal is partly determined by the time between the two signals (the foreperiod) and the distribution of foreperiods. According to Multiple Trace Theory of Temporal Preparation (MTP), participants use memory traces of previous foreperiods to prepare for the upcoming go signal. If the processes underlying temporal preparation reflect general encoding and memory principles, transfer effects (the carryover effect of a previous block's distribution of foreperiods to the current block) should be observed regardless of the sensory modality in which signals are presented. Despite convincing evidence for transfer effects in the visual domain, only weak evidence for transfer effects has been documented in the auditory domain. Three experiments were conducted to examine whether such differences in results are due to the modality of the stimulus or other procedural factors. In each experiment, two groups of participants were exposed to different foreperiod distributions in the acquisition phase and to the same foreperiod distribution in the transfer phase. Experiment 1 used a choice-reaction time (RT) task, and the warning signal remained on until the go signal, but there was no evidence for transfer effects. Experiments 2 and 3 used a simple- and choice-RT task, respectively, and there was silence between the warning and go signals. Both experiments revealed evidence for transfer effects, which suggests that transfer effects are most evident when there is no auditory stimulation between the warning and go signals.

The brain predicts the timing of forthcoming events to optimize responses to them. Temporal predictions have been formalized in terms of the hazard function, which integrates prior beliefs on the likely timing of stimulus occurrence with information conveyed by the passage of time. However, how the human brain updates prior temporal beliefs is still elusive. Here we investigated electroencephalographic (EEG) signatures associated with Bayes-optimal updating of temporal beliefs. Given that updating usually occurs in response to surprising events, we sought to disentangle EEG correlates of updating from those associated with surprise. Twenty-six participants performed a temporal foreperiod task, which comprised a subset of surprising events not eliciting updating. EEG data were analyzed through a regression-based massive approach in the electrode and source space. Distinct late positive, centro-parietally distributed, event-related potentials (ERPs) were associated with surprise and belief updating in the electrode space. While surprise modulated the commonly observed P3b, updating was associated with a later and more sustained P3b-like waveform deflection. Results from source analyses revealed that neural encoding of surprise comprises neural activity in the cingulo-opercular network (CON) and parietal regions. These data provide evidence that temporal predictions are computed in a Bayesian manner, and that this is reflected in P3 modulations, akin to other cognitive domains. Overall, our study revealed that analyzing P3 modulations provides an important window into the Bayesian brain. Data and scripts are shared on OSF: https://osf.io/ckqa5/., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2021. Published by Elsevier Inc.)

Background: Previous studies of stage III colon cancer using the hazard function demonstrated that the risk of recurrence in patients with adjuvant chemotherapy never exceeded that of patients without adjuvant chemotherapy. However, it is unclear whether the same can be said for rectal cancer patients and whether adjuvant chemotherapy reduces recurrence. This study aimed to compare the recurrence hazard of stage III rectal cancer with that of colon cancer by adjuvant chemotherapy status using the hazard function, a method that allows for the assessment of instantaneous risk of recurrence over time., Methods: This retrospective nationwide study consisted of 10,356 patients with stage III colorectal cancer who underwent curative resection between January 1997 and December 2012 in Japan. Recurrence hazards of rectal and colon cancers were compared between patients treated with adjuvant chemotherapy and those who were not. Analyses in which recurrence was divided into local and distant recurrence were also performed., Results: The hazard rate of recurrence in rectal cancer patients with adjuvant chemotherapy was consistently lower throughout the follow-up period, and the peak time of recurrence later, compared to patients without adjuvant chemotherapy (peaked at 15.7 vs. 7.1 months). Adjuvant chemotherapy also strongly suppressed distant recurrence but not local recurrence in rectal cancer patients. Similar results were observed in colon cancer patients., Conclusions: Our results using nationwide real-world data in Japan suggest that, similar to what is observed in colon cancer patients, adjuvant chemotherapy delays the peak of recurrence and suppresses distant recurrence in stage III rectal cancer patients.

HBeAg loss during nucleos(t)ide analogue (Nuc) therapy is significantly higher in patients with hepatitis flare (ALT ≥ 5-times upper limited of normal). It is not clear whether ALT level higher above the hepatitis flare leads to greater HBeAg loss rate nor its durability. This study aimed to investigate the impact of pretherapy ALT level on HBeAg loss in each year of Nuc treatment. Entecavir or Tenofovir treated HBeAg-positive chronic hepatitis B (CHB) patients were recruited consecutively. Patients with prior treatment history that experienced HBeAg seroconversion and reversion were excluded. Pretherapy age, gender, cirrhosis, genotype, ALT, HBsAg and HBV DNA levels were analysed. The hazard function was calculated for the probability of HBeAg loss in each year. Of the 290 patients, the 3-year cumulative HBeAg loss rate was 58.1%, higher in patients with hepatitis flare than those without (67.6% vs. 39.6%, P < 0.001). The HBeAg loss rate in the first year correlated positively with higher ALT levels at a stepwise fashion. The hazard function in patients with hepatitis flare was 0.74 at half year, then dropped to 0.33 by the first year and was lower thereafter to a rate closer to that of the patients without hepatitis flare. In conclusion, the impact of pretherapy ALT levels on HBeAg loss rate was not long-lasting and was effective mainly in the first year of Nuc therapy. Strategies such as adding an immune-modulating agent may help enhance HBeAg loss rate after the first year of Nuc therapy for those who remained HBeAg positive. Word count: 249 (<250)., (© 2020 John Wiley & Sons Ltd.)

This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time-dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative., (© 2020 John Wiley & Sons Ltd.)

In this Methods article, we discuss and illustrate a unifying, principled way to analyze response time data from psychological experiments-and all other types of time-to-event data. We advocate the general application of discrete-time event history analysis (EHA) which is a well-established, intuitive longitudinal approach to statistically describe and model the shape of time-to-event distributions. After discussing the theoretical background behind the so-called hazard function of event occurrence in both continuous and discrete time units, we illustrate how to calculate and interpret the descriptive statistics provided by discrete-time EHA using two example data sets (masked priming, visual search). In case of discrimination data, the hazard analysis of response occurrence can be extended with a microlevel speed-accuracy trade-off analysis. We then discuss different approaches for obtaining inferential statistics. We consider the advantages and disadvantages of a principled use of discrete-time EHA for time-to-event data compared to (a) comparing means with analysis of variance, (b) other distributional methods available in the literature such as delta plots and continuous-time EHA methods, and (c) only fitting parametric distributions or computational models to empirical data. We conclude that statistically controlling for the passage of time during data analysis is equally important as experimental control during the design of an experiment, to understand human behavior in our experimental paradigms., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2020.)

In this article, we model alternately occurring recurrent events and study the effects of covariates on each of the survival times. This is done through the accelerated failure time models, where we use lagged event times to capture the dependence over both the cycles and the two events. However, since the errors of the two regression models are likely to be correlated, we assume a bivariate error distribution. Since most event time distributions do not readily extend to bivariate forms, we take recourse to copula functions to build up the bivariate distributions from the marginals. The model parameters are then estimated using the maximum likelihood method and the properties of the estimators studied. A data on respiratory disease is used to illustrate the technique. A simulation study is also conducted to check for consistency., (© 2020 Walter de Gruyter GmbH, Berlin/Boston.)

The report addresses the role of the hazard function in the analysis of disease-free survival data in breast cancer. An investigation on local recurrences after mastectomy provided evidence that uninterrupted growth is inconsistent with clinical findings and that tumor dormancy could be assumed as working hypothesis to understand the clinical course of the disease. Additionally, it was deemed that the lag-time between primary tumor removal and tumor recurrence is dynamically dependent on the subclinical metastasis development within the host-tumor system and, therefore, may be informative about the biology of the disease. Accordingly, the hazard function, which estimates the event risk pattern through the time, was adopted to analyze survival data. The multipeak pattern of the hazard function suggested that the process metastasis development has discontinuous features. A new paradigm of breast cancer metastatic development was proposed, involving the notions of tumor homeostasis, tumor quiescence in specific metastatic microscopic phases and surgery-related acceleration of the metastatic process. All analyses by prognostic factors (e.g., by menopausal status) or treatment modalities (e.g., by adjuvant chemotherapy) or other parameters (e.g., site of metastasis), provided coherent data in agreement with the model. The hazard rate function allowed addressing several clinical questions including meaning of ipsilateral breast tumor recurrence (IBTR), oncologic effect of delayed breast reconstruction, surgery related metastasis acceleration, possible role of anti-inflammatory drugs and body mass index (BMI) to modulate the recurrence risk. We conclude that the hazard function is a powerful tool to investigate the post-surgical course of early breast cancer and other operable tumors and to make inferences on their biology.

Survival (time-to-event) analysis is commonly used in clinical research. Key features of performing a survival analysis include checking proportional hazards assumptions, reporting CIs for hazards ratios and relative risks, graphically displaying the findings, and analyzing with consideration of competing risks. This article provides a brief overview of important statistical considerations for survival analysis. Censoring schemes, different methods of survival function estimation, and ways to compare survival curves are described. We also explain competing risk and how to model survival data in the presence of it. Different kinds of bias that influence survival estimation and avenues to model the data under these circumstances are also described. Several analysis techniques are accompanied by graphical representations illustrating proper reporting strategies. We provide a list of guiding statements for researchers and reviewers., (Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

The hazard function plays an important role in cancer patient survival studies, as it quantifies the instantaneous risk of death of a patient at any given time. Often in cancer clinical trials, unimodal hazard functions are observed, and it is of interest to detect (estimate) the turning point (mode) of hazard function, as this may be an important measure in patient treatment strategies with cancer. Moreover, when patient cure is a possibility, estimating cure rates at different stages of cancer, in addition to their proportions, may provide a better summary of the effects of stages on survival rates. Therefore, the main objective of this paper is to consider the problem of estimating the mode of hazard function of patients at different stages of cervical cancer in the presence of long-term survivors. To this end, a mixture cure rate model is proposed using the log-logistic distribution. The model is conveniently parameterized through the mode of the hazard function, in which cancer stages can affect both the cured fraction and the mode. In addition, we discuss aspects of model inference through the maximum likelihood estimation method. A Monte Carlo simulation study assesses the coverage probability of asymptotic confidence intervals., Competing Interests: No potential conflict of interest was reported by the author(s)., (© 2020 Informa UK Limited, trading as Taylor & Francis Group.)

Background: Patients infected with the Human Immunodeficiency Virus (HIV) are susceptible to many diseases. In these patients, the occurrence of one disease alters the chance of contracting another. Under such circumstances, methods for competing risks are required. Recently, competing risks analyses in the scope of flexible parametric models have risen to address this requirement. These lesser-known analyses have considerable advantages over conventional methods., Methods: Using data from Multi Centre AIDS Cohort Study (MACS), this paper reviews and applies methods of competing risks flexible parametric models to analyze the risk of the first disease (AIDS or non-AIDS) among HIV-infected patients. We compared two alternative subdistribution hazard flexible parametric models (SDH FPM 1 and SDH FPM 2) with the Fine & Gray model. To make a complete inference, we performed cause-specific hazard flexible parametric models for each event separately as well., Results: Both SDH FPM 1 and SDH FPM 2 provided consistent results regarding the magnitude of coefficients and risk estimations compared with estimations obtained from the Fine & Gray model, However, competing risks flexible parametric models provided more efficient and smoother estimations for the baseline risks of the first disease. We found that age at HIV diagnosis indirectly affected the risk of AIDS as the first event by increasing the number of patients who experience a non-AIDS disease prior to AIDS among > 40 years. Other significant covariates had direct effects on the risks of AIDS and non-AIDS., Discussion: The choice of an appropriate model depends on the research goals and computational challenges. The SDH FPM 1 models each event separately and requires calculating censoring weights which is time-consuming. In contrast, SDH FPM 2 models all events simultaneously and is more appropriate for large datasets, however, when the focus is on one particular event SDH FPM 1 is more preferable.

Context: There is a lack of research that prospectively estimates the age of initiation of electronic cigarette use in U.S. youth. Younger ages of initiation of tobacco product use are associated with greater exposure to nicotine, and recently e-cigarette use has been associated with subsequent cigarette initiation. This study sought to estimate the distribution of the age of first reporting of e-cigarette use outcomes among youth never e-cigarette users overall, by sex and by race/ethnicity, prospectively., Methods: Secondary analysis of the Population Assessment of Tobacco and Health (PATH) youth dataset (ages 12-17) across waves 1 (2013-2014), 2 (2014-2015), 3 (2015-2016), and 4 (2016-2017) were conducted. Four outcomes are presented, age of first report of: (i) susceptibility to use, (ii) ever use, (iii) past 30-day use, and (iv) "fairly regular" e-cigarette use. Each outcome was prospectively estimated using participant age when they entered the study and the number of weeks between the last report of never use and the first report of each outcome across waves. Weighted survival analyses for interval censoring accounting for the complex survey design were implemented., Results: Among youth non-susceptible to e-cigarettes, 50.2% became susceptible to e-cigarette use by age 18. There were no statistically significant differences in the age of first report of susceptibility to e-cigarette use by sex or by race/ethnicity in this nationally representative sample of U.S. youth. Among never users, 41.7%, 23.5% and 10.3% initiated ever, past 30-day and "fairly regular" e-cigarette use by the age of 18, respectively. Less than 10% initiated ever e-cigarette use between the ages of 18 and 21. Boys had a higher risk of first reporting ever, past 30-day and "fairly regular" e-cigarette use at earlier ages than girls. Non-Hispanic Blacks and Other racial/ethnic groups were less likely than Non-Hispanic Whites to initiate ever e-cigarette use at earlier ages, and there was no difference between Non-Hispanic Whites and Hispanics. Hispanic, Non-Hispanic Black and Other racial/ethnic youth were less likely to first report past 30-day use and "fairly regular" e-cigarette use at earlier ages than Non-Hispanic White youth., Conclusion: This paper provides information on specific ages of the first report of e-cigarette use behaviors by sex and by race/ethnicity that can be used to culturally tailor e-cigarette interventions on specific windows of opportunity before youth begin using e-cigarettes or escalating their use., Competing Interests: Conflict of Interests: The authors have no conflicts of interest to disclose except Dr. Harrell is a consultant in litigation involving the vaping industry.

In many circumstances, the increase in life expectancy when certain causes of death are eliminated is sought. These calculations are typically based on the assumption that the causes in question are simply omitted, which is equivalent to the causes being taken out of consideration, from the outset, with certainty. In this paper, we propose models whereby probability distributions for the cures of specific causes of death over time can be incorporated so as to more accurately predict the increase in life expectancy that would ensue. The theoretical results are applied to a real data set involving Diabetes and HIV-related deaths from Denver, Colorado, United States of America, between the years 1990 and 2015 inclusive., (© The Author(s) 2020.)

The log-normal distribution is widely used to model non-negative data in many areas of applied research. In this paper, we introduce and study a family of distributions with non-negative reals as support and termed the log-epsilon-skew normal (LESN) which includes the log-normal distributions as a special case. It is related to the epsilon-skew normal developed in Mudholkar and Hutson (2000) the way the log-normal is related to the normal distribution. We study its main properties, hazard function, moments, skewness and kurtosis coefficients, and discuss maximum likelihood estimation of model parameters. We summarize the results of a simulation study to examine the behavior of the maximum likelihood estimates, and we illustrate the maximum likelihood estimation of the LESN distribution parameters to two real world data sets.

Starting procedures in racing sports consist of a warning (e.g., "Set") followed by a target (e.g., "Go") signal. During this interval (the foreperiod), athletes engage in temporal preparation whereby they prepare to respond to the target as quickly as possible. Despite a long history, the cognitive mechanisms underlying this process are debated. Recently, it has been suggested that traces of previous temporal durations drive temporal preparation performance rather than the traditional explanation that performance is related to the currently perceived hazard function. Los and colleagues used visual stimuli for the warning and target signals. As racing sports typically rely upon auditory stimuli, we investigated the role of memory on temporal preparation in the auditory domain. Experiment 1 investigated long-term transfer effects. In an acquisition phase, two groups of participants were exposed to different foreperiod distributions. One week later, during a transfer phase, both groups received the same distribution of foreperiods. There was no evidence for transfer effects. Therefore, Experiment 2 examined short-term transfer effects in which acquisition and transfer phases were completed in the same testing session. There was some evidence for transfer effects, but this was limited, suggesting that there may be modality-specific memory differences.

Odorant molecules stimulate olfactory receptor neurons, and axons of these neurons project into the main olfactory bulb where they synapse onto mitral and tufted cells. These project to the primary olfactory cortex including the anterior olfactory nucleus (AON), the piriform cortex, amygdala, and the entorhinal cortex. The properties of mitral cells have been investigated extensively, but how odor information is processed in subsequent brain regions is less well known. In the present study, we recorded the electrical activity of AON neurons in anesthetized rats. Most AON cells fired in bursts of 2-10 spikes separated by very short intervals (<20 ms), in a period linked to the respiratory rhythm. Simultaneous recordings from adjacent neurons revealed that the rhythms of adjacent cells, while locked to the same underlying rhythm, showed marked differences in phase. We studied the responses of AON cells to brief high-frequency stimulation of the lateral olfactory tract, mimicking brief activation of mitral cells by odor. In different cells, such stimuli evoked transient or sustained bursts during stimulation or, more commonly, post-stimulation bursts after inhibition during stimulation. This suggests that, in AON cells, phase shifts occur as a result of post-inhibitory rebound firing, following inhibition by mitral cell input, and we discuss how this supports processing of odor information in the olfactory pathway. Cells were tested for their responsiveness to a social odor (the bedding of a strange male) among other simple and complex odors tested. In total, 11 cells responded strongly and repeatedly to bedding odor, and these responses were diverse, including excitation (transient or sustained), inhibition, and activation after odor presentation, indicating that AON neurons respond not only to the type of complex odor but also to temporal features of odor application., (© 2019 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.)

Background: Incidence density ratios (IDRs) are frequently used to account for varying follow-up times when comparing the risks of adverse events in two treatment groups. The validity of the IDR as approximation of the hazard ratio (HR) is unknown in the situation of differential average follow up by treatment group and non-constant hazard functions. Thus, the use of the IDR when individual patient data are not available might be questionable., Methods: A simulation study was performed using various survival-time distributions with increasing and decreasing hazard functions and various situations of differential follow up by treatment group. HRs and IDRs were estimated from the simulated survival times and compared with the true HR. A rule of thumb was derived to decide in which data situations the IDR can be used as approximation of the HR., Results: The results show that the validity of the IDR depends on the survival-time distribution, the difference between the average follow-up durations, the baseline risk, and the sample size. For non-constant hazard functions, the IDR is only an adequate approximation of the HR if the average follow-up durations of the groups are equal and the baseline risk is not larger than 25%. In the case of large differences in the average follow-up durations between the groups and non-constant hazard functions, the IDR represents no valid approximation of the HR., Conclusions: The proposed rule of thumb allows the use of the IDR as approximation of the HR in specific data situations, when it is not possible to estimate the HR by means of adequate survival-time methods because the required individual patient data are not available. However, in general, adequate survival-time methods should be used to analyze adverse events rather than the simple IDR.

We examined whether time to onset of paresthesia was associated with indicators of severity of World Trade Center (WTC) exposure. We analyzed data from 3411 patients from the Bellevue Hospital-WTC Environmental Health Center. Paresthesia was defined as present if the symptom occurred in the lower extremities with frequency "often" or "almost continuous." We plotted hazard functions and used the log-rank test to compare time to onset of paresthesia between different exposure groups. We also used Cox regression analysis to examine risk factors for time-to-paresthesia after 9/11/2001 and calculate hazard ratios adjusted for potential confounders. We found significantly elevated hazard ratios for paresthesia for (a) working in a job that required cleaning of WTC dust in the workplace; and (b) being heavily exposed to WTC dust on September 11, 2001, after adjusting for age, race/ethnicity, depression, anxiety, post-traumatic stress disorder, and body mass index. These observational data are consistent with the hypothesis that exposure to WTC dust or some other aspect of cleaning WTC dust in the workplace, is associated with neuropathy and paresthesia. Further neurological evaluations of this and other WTC-exposed populations is warranted.

Explicit and implicit measures of timing were compared between young and older participants. In both tasks, participants were initially familiarized with a reference interval by responding to the second of two beeps separated by a fixed interval. During the subsequent testing phase, this inter-stimulus interval was variable. In the explicit task, participants were instructed to judge interval duration, whereas in the implicit task they were told to respond as quickly as possible to the second beep. Cognitive abilities were assessed with neuropsychological tests. Results showed that in both explicit and implicit timing tasks, temporal performance peaked around the reference interval and did not differ between young and older participants. This indicates an accurate representation of duration that did not decline with normal aging. However, some age-related differences were observed in performance depending on the task used. In the explicit timing task, the variability of duration judgments was greater in older than young participants, though this was directly related to older participants' lower attentional capacity. In the implicit timing task, young participants' reaction times (RTs) were slower to targets appearing either earlier or later than the trained interval. Conversely, while older participants RTs were also slowed by early targets, their RTs to late targets were as fast as those to targets appearing at the trained interval. We hypothesize that with age, and irrespective of cognitive ability, there is increasing reliance on temporal information conveyed by the probability of target appearance as a function of elapsing time ("hazard function") than that conveyed by the statistical likelihood of previously experienced temporal associations., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Attention resources can be allocated in both space and time. Exogenous temporal attention can be driven by rhythmic events in our environment which automatically entrain periods of attention. Temporal expectancies can also be generated by the elapse of time, leading to foreperiod effects (the longer between a cue and imperative target, the faster the response). This study investigates temporal attention in touch and the influence of spatial orienting. In experiment 1, participants used bilateral tactile cues to orient endogenous spatial attention to the left or right hand where a unilateral tactile target was presented. This facilitated response times for attended over unattended targets. In experiment 2, the cue was unilateral and non-predictive of the target location resulting in inhibition of return. Importantly, the cue was rhythmic and targets were presented early, in synchrony or late in relation to the rhythmic cue. A foreperiod effect was observed in experiment 1 that was independent from any spatial attention effects. In experiment 2, in synchrony were slower compared to out of synchrony targets but only for cued and not uncued targets, suggesting the rhythm generates periods of exogenous inhibition. Taken together, temporal and spatial attention interact in touch, but only when both types of attention are exogenous. If the task requires endogenous spatial orienting, space and time are independent., (Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.)

The accelerated failure time model is widely used for analyzing censored survival times often observed in clinical studies. It is well-known that the ordinary maximum likelihood estimators of the parameters in the accelerated failure time model are generally sensitive to potential outliers or small deviations from the underlying distributional assumptions. In this paper, we propose and explore a robust method for fitting the accelerated failure time model to survival data by bounding the influence of outliers in both the outcome variable and associated covariates. We also develop a sandwich-type variance-covariance function for approximating the variances of the proposed robust estimators. The finite-sample properties of the estimators are investigated based on empirical results from an extensive simulation study. An application is provided using actual data from a clinical study of primary breast cancer patients.

Objective: Hazard perception (HP) is typically defined as the ability to read the road and anticipate hazardous situations. Several studies have shown that HP is a driving skill that correlates with traffic crashes. Measuring HP differences between various groups of drivers typically involves a paradigm in which participants observe short videos of real-world traffic scenes taken from a driver's or a pedestrian's perspective and press a response button each time they identify a hazard. Young, inexperienced drivers are considered to have poor HP skills compared to experienced drivers, as evident by their slower response times (RTs) to road hazards. Nevertheless, though several studies report RT differences between young, inexperienced and experienced drivers, other studies did not find such differences. We have already suggested that these contradictory findings may be attributed to how cases of no response-that is, a situation where a participant did not respond to a hazard-are being treated. Specifically, we showed that though survival analysis handles cases of no response appropriately, common practices fail to do so. These methods often replace a case of no response with the mean RT of those who responded or any other central tendency parameters. The present work aims to show that treating cases of no response appropriately as well as selecting a distribution that fits the RT data is more than just a technical phase in the analysis., Method: This work used simulation of predefined distributions and real-world data., Results: It was demonstrated that selecting the appropriate distribution and treating nonresponse cases appropriately affect the shape and characteristics of the density, survival, and hazard functions., Conclusions: The suggested process has the ability to provide researchers with additional information regarding the nature of the traffic scenes that enables differentiating between various hazardous situations and between various users with different characteristics such as age or experience.

Background: In Sub-Saharan Africa, HIV endemic has substantially contributed to the increasing tuberculosis (TB) incidence. The joint effect of the HIV and TB pestilences has confronted the feeble systems of healthcare in resource-limited countries., Methods: The aim of this study was to determine the pathological attributes, outcomes of TB treatment, and the contributing factors of unsuccessful results among TB/HIV patients. A retrospective cohort study of all confirmed adult TB/HIV coinfected hospitalized patients with drug-resistant TB reported for the treatment in two different hospitals from 2010 to 2016 in Eastern Cape, South Africa. Cox proportional hazard model was used in identifying the predictors of unsuccessful treatment., Results: Unsuccessful treatment outcomes among TB/HIV coinfected patients with treatment category were (95% confidence interval [CI]: 0.988-1.318) age, smoking (1.047; 95% CI: 0.892-1.229), pregnancy (1.940; 95% CI: 0.793-4.743), CD 4+ count (1.163; 95% CI: 0.993-1.361), and patients with comorbidity diseases such as diabetes, liver diseases, renal failure, hepatitis, and silicosis were all significantly associated with unsuccessful treatment. The preantiretroviral treatment (ART) females appear to have significantly better survival than pre-ART males., Conclusion: The study showed that the unsuccessful treatment outcomes among TB/HIV coinfected patients were slightly below the WHO target. The key predictors of unsuccessful TB treatment outcomes among the TB/HIV coinfected patients were associated with pregnancy, productive age group, gender, contraception, and comorbidity diseases., Competing Interests: None

This article mainly focuses on analyzing covariate data from incident and prevalent cohort studies and a prevalent sample with only baseline covariates of interest and truncation times. Our major task in both research streams is to identify the effects of covariates on a failure time through very general single-index survival regression models without observing survival outcomes. With a strict increase of the survival function in the linear predictor, the ratio of incident and prevalent covariate densities is shown to be a non-degenerate and monotonic function of the linear predictor under covariate-independent truncation. Without such a structural assumption, the conditional density of a truncation time in a prevalent cohort is ensured to be a non-degenerate function of the linear predictor. In light of these features, some innovative approaches, which are based on the maximum rank correlation estimation or the pseudo least integrated squares estimation, are developed to estimate the coefficients of covariates up to a scale factor. Existing theoretical results are further used to establish the n -consistency and asymptotic normality of the proposed estimators. Moreover, extensive simulations are conducted to assess and compare the finite-sample performance of various estimators. To illustrate the methodological ideas, we also analyze data from the Worcester Heart Attack Study and the National Comorbidity Survey Replication., (© 2017, The International Biometric Society.)