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This article explores how organizational mobility and foreign nationality affect a researcher’s chances of an internal career promotion in university systems that do not have rules preventing inbreeding and where teaching occurs mostly not in English but a local language. As a case study, we have examined the Flemish university system, the Dutch speaking part of Belgium, and developed expectations on the chances of promotion for mobile and foreign researchers compared to non-mobile and nationals. We use data for all postdoctoral and professorial staff between 1991 and 2017, for a total of 14,135 scientists. We calculated the chances of promotion with a competing risk model to take time into account and to disentangle the probability of two mutually exclusive risk events: promotion and leaving the university. The results show that international mobility and foreign nationality reduced the chances of promotion in the same university, and that mobile and foreign scientists were also more likely to leave any given university. These effects were particularly strong at an early stage: in the study period, 21.9% of non-mobile national postdocs became professor compared to just 1.2% of internationally mobile foreigners. These results would suggest that internationally mobile and foreign scientists struggle to advance in universities that lack rules preventing inbreeding and with little opportunity to teach in English.

PurposeTo evaluate the association of the different degrees of insomnia symptoms with subsequent incidence of type 2 diabetes mellitus (T2DM).MethodsThe data were extracted from Health and Retirement Study 2006–2014 waves. The association of insomnia symptoms with T2DM incidence was evaluated by the competing risk model with cumulative incidence function (death was considered a competing event) and Cox proportional hazard model with the Kaplan–Meier method. Population attributable fraction (PAF) was calculated. All analyses related to our study were conducted between November 2020 and January 2021.ResultsA total of 14,112 patients were included in this study, with an average follow-up of 6.4 years, and the incidence density was 17.9 per 1000 person-years. Insomnia symptoms were positively associated with T2DM incidence compared with those with no insomnia symptoms, regardless of competing risk model (≥ 1 symptoms: sub-distribution hazard ratio (SHR) 1.13; 95% confidence interval (CI) 1.02–1.26; P-trend = 0.012) and Cox proportional hazard model (≥ 1 symptoms: hazard ratio (HR) 1.13; 95% CI 1.02–1.26; P-trend = 0.013). The cumulative incidence function (Gray’s test, p < 0.001) and Kaplan–Meier estimate (log-rank test, p < 0.001) also presented this positive relationship. This positive association was more apparent in women and participants with ages from 50 to 65 years. The PAF was 4.1% with 95% CI (0.7–7.9%).ConclusionsInsomnia symptoms may be an important risk factor for the development of T2DM, which is unbiased by the death competing risk. These findings suggest that management of sleep problems may be an important part of strategies to prevent T2DM.

This study presents a latent class competing risks model to examine the influence of socio-demographics and life course events on car transaction behaviour. The types of car transaction and interval times between car transactions events are incorporated in a competing risk model. To capture unobserved behavioural heterogeneity across the population, the model classifies households into different segments. Results estimated based on retrospective survey data show significant heterogeneity exist in household car ownership decisions. The covariates are found to have different effects on car ownership decisions between different classes. Households in the class labelled “Young households without a car” are more sensitive to life course events related to household composition. Households labelled as “middle-aged and aged households with car(s)” are more sensitive to life course events related to job and house locations.

Objectives This study performed a competing‐risks analysis using data from the SEER database on penile cancer patients with the aim of identifying more accurate prognostic factors. Methods Data on patients with penile cancer were extracted from the SEER database. A univariate analysis used the cumulative incidence function and Gray's test, while multivariate analysis was performed using the Fine‐Gray model. Cumulative hazards were compared with a competing‐risks model constructed using Kaplan‐Meier estimation. Results The multivariate Fine‐Gray analysis indicated that being black (HR = 1.51, 95%CI: 1.10‐2.07, P = .01), AJCC stage II (HR = 1.94, 95%CI: 1.36‐2.77, P < .001), AJCC stage III (HR = 1.98, 95%CI: 1.34‐2.91, P < .001), tumor size > 5 cm (HR = 2.23, 95%CI: 1.33‐3.72, P < .05), and TNM stages N1 (HR = 2.49, 95%CI: 1.71‐3.61, P < .001), N2 (HR = 3.25, 95%CI: 2.18‐4.84, P < .001), N3 (HR = 5.05, 95%CI: 2.69‐9.50, P < .001), and M1 (HR = 2.21, 95%CI: 1.28‐3.84, P < .05) were statistically significant. The results obtained using multivariate Cox regression were different, while Kaplan‐Meier curve analysis led to an overestimation of the cumulative risk of the patient. Conclusions This study established a competing‐risks analysis model for the first time based on the SEER database for the risk assessment of penile cancer patients. The results may help clinicians to better understand penile cancer and provide these patients with more appropriate support. This study established a competing‐risks analysis model for the first time based on the SEER database for the risk assessment of penile cancer patients. The results may help clinicians to better understand penile cancer and provide these patients with more appropriate support.

The second stage of labour begins when the cervix is fully dilated and pushing begins until the fetus is delivered. A Caesarean delivery (CD) or operative vaginal delivery (OVD) is typically encouraged after the recommended time set by 'expert consensus'. This recommended time has been set out of concern for an increased chance of maternal and neonatal morbidities due to a prolonged second stage of labour, but without thorough consideration of heterogeneous risks for spontaneous vaginal delivery (SVD) and morbidities among women. To provide quantitative evidence for the recommendation, the first step is to compare the risks for SVD, CD or OVD, and the risks of maternal or neonatal morbidities simultaneously across the duration of the second stage of labour. To address such risk comparisons statistically, one needs to study the joint distribution for the time to delivery due to each mode and time to maternal or neonatal morbidity given information provided for each individual. We introduce a joint model which combines the competing risks data for delivery time and current status data for any type of maternal or neonatal morbidity given each woman's baseline characteristics. These two processes are assumed dependent through individual-specific frailty under the joint model. Our numerical studies include a simulation that reflects the structure of observed real data and a detailed real data analysis based on nearly 12000 spontaneous labours. Our finding indicates the necessity to incorporate maternal characteristic such as age or body mass index in assessing the probability for delivery due to SVD, CD or OVD and the onset of morbidities across the second stage of labour.

PurposeThis paper analyses the collapse of credit booms into soft landings or systemic banking crises.Design/methodology/approachA discrete-time competing risks duration model is employed to disentangle the factors behind the length of benign and harmful credit booms.FindingsThe results show that economic growth and monetary authorities play the major role in explaining the differences in the length and outcome of credit booms. Moreover, both types of credit expansions display positive duration dependence, i.e. both are more likely to end as they grow older, but hard landing credit booms have proven to be longer than those that land softly.Originality/valueThis paper contributes to our understanding of what affects the length of credit booms and why some end up creating havoc and others do not. In particular, it calls the attention to the important role that Central Bank independence plays regarding credit booms length and outcome.

The conventional survival analysis model on HIV/AIDS prognosis is the Cox proportional hazard model, which deals with only one event type, death, regardless of the cause. Few studies have used a competing risk model to evaluate the predictors of AIDS-related mortality. To estimate the influence of antiretroviral therapy (ART) initiation time and baseline CD4 + cell counts on acquired immunodeficiency syndrome (AIDS)-related death among former plasma donors. A retrospective cohort study was conducted involving 11,905 human immunodeficiency virus (HIV) or AIDS patients in a high-risk area of Henan province in China between 1995 and 2016. Demographic and clinical data were collected. Sub-distribution hazard ratios (sHRs) for AIDS-related mortality with baseline CD4 + cell counts and ART initiation time were determined using a competing risk model. Patients who initiated ART within 90 days of HIV/AIDS diagnosis (sHR: 0.24, 95% CI: 0.22-0.27) or had baseline CD4 + counts of >500 cells/μL (sHR: 0.23, 95% CI: 0.19-0.28) were associated with lower AIDS-related mortality risk. Patients with ART initiation time >1 year but CD4 + counts >350 cells/μL (sHR: 4.42, 95% CI: 3.30-5.91) had a higher AIDS-related mortality risk than those with ART initiation time >90 days but CD4 + counts ≤350 cells/μL (sHR: 4.33, 95% CI: 3.58-5.23). Our results demonstrate that patients with high CD4 + cell counts and late ART had a 9% higher risk of AIDS-related death than those with low CD4 + cell counts and early ART. This study confirms the great significance of immediate ART initiation among former plasma donor HIV patients in China.

Using a data set of Norwegian firms, an examination is made of the relationship between firms’ R&D activities and their survival. A firm may exit the market through closure, or merger and acquisition (M&A). The analysis is based on a discrete time competing risks model with unobserved heterogeneity. We find that product-innovative firms have a higher probability of exit due to M&A, but only if they also introduce new products into their market. This highlights the importance of differentiating between different groups of product-innovative firms. None of the R&D and innovation activities considered has significant effects on the probability of firm closure.

This study investigates the demographic characteristics and academic performances of foreign students with an Italian educational background in a cohort of 1st-year Bachelor students enrolled at Sapienza University of Rome, in the a.y. 2012/2013, comparing them to Italian and to International students. First, we employed a discrete-time competing risk hazard model to analyse differences in academic performances between Italian, foreign students with an Italian educational background and foreign students with a foreign educational background. Second, we applied regression trees to investigate final grades and the time-to-degree completion of Bachelor’s degree holders. Results show differences in the academic performances of foreign students with an Italian educational background compared to Italian students. Policies are needed, these results suggest, that strengthen opportunities for students from a migrant background since high school.

Male breast cancer (MBC) is rare, and due to the absence of male-specific screening programs, many patients are diagnosed at advanced stages and older ages. This study aims to analyze the long-term trend of MBC incidence and develop a competing risk model to improve survival rates. MBC data from the Surveillance, Epidemiology, and End Results (SEER) database (1975–2019) were analyzed using the Age-Period-Cohort (APC) model to examine trends in age, period, and birth cohort effects of MBC incidence. A competing risk model was used to build a nomogram predicting breast cancer-specific survival (BCSS) for MBC patients, with model accuracy assessed using the concordance index (C-index) and calibration curves. These results were compared with the nomogram established by Cox model. Comparisons were made with traditional AJCC staging system using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). APC analysis showed MBC incidence increases with age, while period and birth cohort effects were not significant. A total of 2,057 patients were included in the competing risk analysis, which identified factors like older age, estrogen receptor (ER) negative, progesterone receptor (PR) negative, and advanced AJCC stage as being associated with shorter survival. The competing risk model demonstrated excellent predictive ability, surpassing the AJCC staging system in both accuracy and clinical utility. In contrast, the Cox regression model overestimated the risk of endpoint events and failed to provide accurate effect estimates. The high incidence and poor prognosis of MBC in the elderly population emphasize the need for improved screening and early diagnosis in high-risk groups. Our competing risk model, compared to the Cox model, more accurately reflects real-world conditions. Additionally, we have developed a competing risk nomogram to assist in identifying high-risk individuals and guiding clinical decision-making.