In 2025, a nationwide shortage of long-acting injectable olanzapine (Zypadhera) forced treatment changes in patients at the Mental Health Day Hospital of Mataró (Spain). We retrospectively identified 23 consecutive patients receiving Zypadhera and recorded subsequent therapeutic alternatives, relapse, service disengagement and re-initiation of Zypadhera. Relapse or disengagement occurred in 39% of patients, with significantly fewer events observed among patients switched to oral olanzapine compared with long-acting injectable aripiprazole (log-rank P = 0.008). Female sex, younger age and tobacco use were associated with increased risk. This study highlights the need for contingency planning and careful selection of alternatives.

Autocratization typically results from measures aiming at seizing, strengthening, and consolidating political power. However, it is not without risks: it may produce adverse reactions from multiple actors and possibly lead to the fall of its perpetrators from power. What makes autocratizing incumbents more capable of surviving during such a perilous process? We argue that the adoption of ideological legitimation strategies makes incumbents more capable of surviving during autocratization in democratic and electoral authoritarian regimes. We test our argument through survival analysis of incumbents in power during processes of autocratization from 1900 to 2024. Though relatively understudied in the context of autocratization, our study highlights ideology as a key factor in the process of transformation of a political regime toward autocracy.

Individual patient data meta-analyses (IPDMAs) provide powerful tools for synthesizing evidence across studies, yet methods for addressing unmeasured confounding in observational IPDMAs with survival outcomes are rarely implemented. Instrumental variable (IV) approaches offer causal inference capabilities but face practical challenges in hierarchical data structures, particularly the lack of standard diagnostics for instrument strength in nonlinear mixed-effects models. We adapt and evaluate a frequentist mixed-effects two-stage residual inclusion (2SRI) framework for survival IPDMAs, extending traditional IV methods to accommodate study-level and temporal clustering while handling time-to-event outcomes through Cox proportional hazards models. Because classical F-statistics are unavailable for logistic mixed-effects first-stage models, we propose the Wald $\chi ^2$ statistic as a practical instrument-strength diagnostic and empirically characterize its relationship to estimator performance. Through a comprehensive simulation study with 48 scenarios—varying unmeasured confounding (weak to very strong), instrument–treatment association strength (0.3–1.0), and cross-study IV allocation patterns—we evaluated 2SRI against naive mixed-effects Cox models using bias, coverage, variance, and mean squared error. The design was anchored to realistic IPDMA structure (10 studies, $N \approx 4,357$) from pooled Ebola data, with 1,000 replications per scenario. Results show that under weak confounding, naive models dominate on all metrics. With moderate-to-strong confounding and realized Wald $\chi ^2$ exceeding 150–200, mixed-effects 2SRI substantially reduces bias and achieves near-nominal coverage, though with inflated variance. We provide empirical guideposts linking realized first-stage strength to expected performance, enabling analysts to judge when 2SRI will outperform conventional approaches in hierarchical survival IPDMAs. All simulations assume a common treatment effect across studies. Performance under heterogeneous effects remains to be established.

It is difficult to understand the safety profile of drugs based on a single clinical trial since clinical trials are often designed to prove efficacies, and sample size is not powered for safety assessment. Thus, meta-analysis would be a valuable tool to infer the safety profiles utilizing multiple studies. Individual clinical trials usually report the incidence proportions of adverse events (AEs) observed in the study. The follow-up duration may be study-specific, and furthermore different between the treatment groups within a single study. It often occurs in oncology clinical trials and if this is the case, it is hard to interpret the aggregated relative risk of AEs and compare the risk of AEs between the treatment groups with the standard meta-analysis techniques. The progression-free survival or the overall survival is often used as the primary endpoint in oncology clinical trials and the Kaplan–Meier estimates of the survival functions for the primary endpoint are often demonstrated graphically, which give us information of the follow-up duration of the AEs. We propose novel meta-analysis methods for AEs that address differences in follow-up durations by efficiently utilizing the Kaplan–Meier estimates of the primary endpoint. We adapt our approach using both simulated data and real data from a meta-analysis of bevacizumab. Simulation studies demonstrate that the proposed methods perform well when follow-up time differs between trials and groups.

This paper introduces a novel expectation-maximization (EM) algorithm for estimating general phase-type (PH) distributions from left-truncated and right-censored (LTRC) data, a common challenge in survival analysis. The proposed algorithm is highly efficient with computational complexity that scales with the number of nonzero elements in the generator matrix. This feature makes the estimation of high-dimensional, sparse PH models computationally tractable and enables the practical use of the computationally intensive extended information criterion for model selection. Numerical experiments demonstrate its significant speed advantage over a modern benchmark and the applicability of PH models to complex lifetime data.

In this article, the effects of regional autocratic linkage on the survival of autocratic regimes are analysed. Scholars have suggested that regional factors shape regime survival through processes of diffusion. However, in most accounts, diffusion is simply derived from characteristics of the region, such as the number or proportion of regional autocracies. In contrast, it is argued here that it is the actual linkages between countries that must be examined. Regional political, economic and social ties between autocratic regimes create domestic and external stakes in the regime, counterweigh democratisation pressure and facilitate autocratic learning. The study employs the average volume of trade, migration and diplomatic exchanges between autocratic regimes within a region as proxies for regional autocratic linkage, and asserts that regional autocratic linkage is on the rise. Applying Cox survival models on a dataset of regional autocratic linkage and regime survival between 1946 and 2009, it is found that regional autocratic linkage significantly reduces the likelihood of autocratic regime breakdown. These effects hold when the proportion of autocratic regimes within a region is controlled for, suggesting that one must look beyond the characteristics of the countries within a region and focus on the ties and linkages between them.

The objective of this article is to contribute to an understanding of the evolution of a population of social economy enterprises faced with the economic crisis, namely by referring to the case of Montreal. We apply a two-step approach. For one, we use an innovative discrete-time survival model that takes spatial heterogeneity into account. In a second step, this model is used to predict the survival of different forms of the social economy, according to various proposed typologies for identifying hybrid organizational forms. It is understood that certain organizational forms (professional social economy) have fared better than others (emerging social economy). Organizations combining several sources of financing and several forms of paid or volunteer work likewise have greater chances of survival.

The timing of labour market exit differs among socio-economic groups, but the differences by employment history type are not yet well understood. Taking a lifecourse perspective, this study examines to what extent employment patterns from early to mid career are associated with the timing of labour market exit in Belgium. It uses retrospective data from Wave 7 of the Survey of Health, Ageing and Retirement in Europe (SHARE) and applies sequence analysis and cluster analysis to identify five employment history types among 2,417 Belgian respondents aged 50–70: three characterised by continuous full-time work and differing with regard to their timing of labour market entry; the fourth characterised by continuous part-time work; and the fifth, considered the most vulnerable, characterised by discontinuous work. The study applies discrete-time survival analysis to estimate to what extent the timing of labour market exit differs by employment history type. Compared to the Discontinuous career-cluster (reference group), individuals in the Late entry, full-time work-cluster had lower odds of exiting the labour market at any age between 50 and 70, while individuals who also worked full-time almost continuously but entered the labour market early or medium-late had higher odds of exiting the labour market. The difference with the Part-time work-cluster is not statistically significant. The findings show substantial diversity in employment histories among Belgian older individuals and that employment history matters for the timing of labour market exit. In the context of changing retirement policies, ignoring the diversity in employment trajectories risks reinforcing existing social inequalities.

Co-optation is one of the most important concepts that have been discussed in recent years to explain the persistence of autocratic regimes. Institutions like parties, legislatures, and elections have all been shown to fulfil a co-optation function. However, a broader assessment of co-optation beyond an institutional focus has yet to be undertaken. This article addresses this lacuna and presents a comprehensive concept and operationalisation of co-optation in autocratic regimes. The article argues that co-optation is constituted by the compensation of the regime’s vulnerability to threats posed by powerful societal pressure groups. The article highlights how compensation of vulnerability can be achieved through institutional inclusion or material benefits, and how this has to be tailored to the respective pressure group’s requirements. I collect twenty-six indicators of vulnerability and compensation related to six societal pressure groups and aggregate them into an index of co-optation that reflects the structure of the theoretical concept. The index is evaluated by examining distributions within and across categories of autocratic legislatures, and by testing its effect on autocratic regime breakdown in a set of Cox survival models.

In this study, we investigate the impact of the age of prime ministers and ministers on the stability of governments across 21 democracies. We examine this issue by using Cox survival analysis, leveraging an original dataset and adopting a comparative perspective. The findings of the study document that younger prime ministers face a lower risk of government discretionary termination compared to their older counterparts. This effect does not appear to be statistically significant for cabinet ministers. By shedding light on this uncharted relationship, we contribute to the flourishing literature on youth representation in politics and the established research agenda on the factors affecting the survival in office of democratic governments. We conclude the study by discussing the implications of the findings for democracy and suggesting avenues for future research.