Laurent Remontet

Background: Hospital professionals face mental health challenges caused by the high demands of their work. Mindfulness meditation (MM) is a nonpharmacological practice with promising effects in promoting mental health and well-being across various hospital professionals. However, the benefits obtained from its implementation in the context of real work in hospital departments are understudied. Objective: The aims of this pilot study are to implement and evaluate, at both the individual and collective levels, the exploratory outcomes of a workplace-based mindfulness intervention developed participatively for hospital teams in a French university hospital. The feasibility of the implementation of the intervention, the influence of the work environment, and the mechanisms through which it produces its effects will also be assessed. Methods: For this prospective interventional study, a preliminary co-construction with the stakeholders (a task force with professionals and management) made it possible to develop and adapt the intervention to the needs and capacities of the professionals, using the intervention mapping model for health program planning. Inclusion and an MM information meeting were proposed to 8 hospital departments, which were then randomized into 2 parallel cluster groups (intervention or control group). In the intervention group, an MM test session was proposed before committing to the MM program (10 one-hour sessions) for a maximum of 15 professionals per department. A convergent mixed methods design with concomitant quantitative and qualitative data collection was used, before integration of findings. Quantitative evaluation was based on a comparison of “before-after” measurements, with a comparison between intervention and control groups. The primary exploratory outcome was the evolution of psychological flourishing at work, which was measured using the adapted and validated French-language scale Psychological Flourishing at Work (EEPMT-8), to which the Professional Life Satisfaction Scale (ÉSVP-5) was added, to form a new 13-item Psychological Flourishing at Work Scale (EEPMT-13). Realist evaluation by qualitative methods explored the influence of contexts on the implementation (barrier and facilitators), and the links between context, mechanisms, and effects of MM. The study was approved by the Sud-Est VI ethics committee (Clermont Ferrand, France). Results: Funding was obtained in October 2021 and June 2024. This study was conducted from May 2024 to June 2025. As of May 2024, 108 participants were enrolled. Analyses are in progress. Results are expected to be published by the end of 2026. Conclusions: Participative approaches are essential for a challenged, tailored implementation of a workplace-based mindfulness intervention in hospital teams. The evaluation of the intervention with mixed methods and the characterization of both individual and organizational levels are aligned with the recommendations to evaluate a complex intervention in a workplace; challenges include the use of an innovative primary endpoint and methodological pluralism to plan for scalability at a subsequent stage.

Background: The excess mortality observed in Acute Myeloblastic Leukaemia (AML) patients, partly attributed to unequal access to curative treatments, could be linked to care pathways.Methods: We included 1039 AML incident cases diagnosed between 2012-2016 from the 3 French blood cancer registries (3,625,400 inhabitants). We describe patients according to age, the medical entry unit and access to the specialised haematology unit (SHU) during follow-up. Multivariate logistic regression model was done to determine the association between covariables and access to SHU. A total of 713 patients (69%) had access to SHU during care.Results: The most common care pathway concerned referral from the general practitioner to SHU, n = 459(44%). The univariate analysis observed a downward trend for the most deprived patients. Patients who consulted in SHU were younger (66 years vs. 83, p < 0.001), and 92% had access to cytogenetic analysis (vs. 54%, p < 0.001). They also had less poor prognosis AML-subtypes (AML-MRC, t-AML/MDS and AML-NOS) (38% vs. 69%); 77% with de novo AML (vs. 67%, p < 0.003)], more favourable cytogenetic prognostic status (23% vs. 6%, p < 0.001), less comorbidities (no comorbidity = 55% vs. 34%, p < 0.001) and treatments proposed were curative 68% (vs. 5.3%, p < 0.001). Factors limiting access to SHU were age over 80 years (OR, 0.14; 95% CI, 0.04-0.38), severe comorbidities (OR, 0.39; 95% CI, 0.21-0.69), emergency unit referral (OR, 0.28; 95% CI, 0.18-0.44) and non-SHU referral (OR, 0.12; 95% CI, 0.07-0.18). Consultation in an academic hospital increased access to SHU by 8.87 times (95% CI, 5.64-14.2).Conclusion: The high proportion of access to cytogenetic testing and curative treatment among patients admitted to SHU, and the importance of early treatment in AML underlines the importance of access to SHU for both diagnosis and treatment.

Background: In cancer net survival analyses, if life tables (LT) are not stratified based on socio-demographic characteristics, then the social gradient in mortality in the general population is ignored. Consequently, the social gradient estimated on cancer-related excess mortality might be inaccurate. We aimed to evaluate whether the social gradient in cancer net survival observed in France could be attributable to inaccurate LT. Methods: Deprivation-specific LT were simulated, applying the social gradient in the background mortality due to external sources to the original French LT. Cancer registries’ data from a previous French study were re-analyzed using the simulated LT. Deprivation was assessed according to the European Deprivation Index (EDI). Net survival was estimated by the Pohar–Perme method and flexible excess mortality hazard models by using multidimensional penalized splines. Results: A reduction in net survival among patients living in the most-deprived areas was attenuated with simulated LT, but trends in the social gradient remained, except for prostate cancer, for which the social gradient reversed. Flexible modelling additionally showed a loss of effect of EDI upon the excess mortality hazard of esophagus, bladder and kidney cancers in men and bladder cancer in women using simulated LT. Conclusions: For most cancers the results were similar using simulated LT. However, inconsistent results, particularly for prostate cancer, highlight the need for deprivation-specific LT in order to produce accurate results.

Social inequalities are an important prognostic factor in cancer survival, but little is known regarding digestive cancers specifically. We aimed to provide in-depth analysis of the contextual social disparities in net survival of patients with digestive cancer in France, using population-based data and relevant modeling. Digestive cancers (n = 54,507) diagnosed between 2006–2009, collected through the French network of cancer registries, were included (end of follow-up 30 June 2013). Social environment was assessed by the European Deprivation Index. Multidimensional penalized splines were used to model excess mortality hazard. We found that net survival was significantly worse for individuals living in a more deprived environment as compared to those living in a less deprived one for esophageal, liver, pancreatic, colon and rectal cancers, and for stomach and bile duct cancers among females. Excess mortality hazard was up to 57% higher among females living in the most deprived areas (vs. least deprived) at 1 year of follow-up for bile duct cancer, and up to 21% higher among males living in the most deprived areas (vs. least deprived) regarding colon cancer. To conclude, we provide a better understanding of how the (contextual) social gradient in survival is constructed, offering new perspectives for tackling social inequalities in digestive cancer survival.

Cure models have been widely developed to estimate the cure fraction when some subjects never experience the event of interest. However these models were rarely focused on the estimation of the time–to–cure i.e. the delay elapsed between the diagnosis and ”the time from which cure is reached”, an important indicator, for instance to address the question of access to insurance or loans for subjects with personal history of cancer. We propose a new excess hazard regression model that includes the time–to–cure as a covariate dependent parameter to be estimated. The model is written similarly to a Beta probability distribution function and is shown to be a particular case of the non‐mixture cure models. Parameters are estimated through a maximum likelihood approach and simulation studies demonstrate good performance of the model. Illustrative applications to three cancer data sets are provided and some limitations as well as possible extensions of the model are discussed. The proposed model offers a simple and comprehensive way to estimate more accurately the time–to–cure. This article is protected by copyright. All rights reserved

Background: Cancer-incidence and mortality-trend analyses require appropriate statistical modelling. In countries without a nationwide cancer registry, an additional issue is estimating national incidence from local-registry data. The objectives of this study were to (i) promote the use of multidimensional penalized splines (MPS) for trend analyses; (ii) estimate the national cancer-incidence trends, using MPS, from only local-registry data; and (iii) propose a validation process of these estimates.Methods: We used an MPS model of age and year for trend analyses in France over 1990–2015 with a projection up to 2018. Validation was performed for 22 cancer sites and relied essentially on comparison with reference estimates that used the incidence/health-care ratio over the period 2011–2015. Alternative estimates that used the incidence/mortality ratio were also used to validate the trends.Results: In the validation assessment, the relative differences of the incidence estimates (2011–2015) with the reference estimates were <5% except for testis cancer in men and < 7% except for larynx cancer in women. Trends could be correctly derived since 1990 despite incomplete histories in some registries. The proposed method was applied to estimate the incidence and mortality trends of female lung cancer and prostate cancer in France.Conclusions: The validation process confirmed the validity of the national French estimates; it may be applied in other countries to help in choosing the most appropriate national estimation method according to country-specific contexts. MPS form a powerful statistical tool for trend analyses; they allow trends to vary smoothly with age and are suitable for modelling simple as well as complex trends thanks to penalization. Detailed trend analyses of lung and prostate cancers illustrated the suitability of MPS and the epidemiological interest of such analyses.

The proportional hazards model represents the most commonly assumed hazard structure when analysing time to event data using regression models. We study a general hazard structure which contains, as particular cases, proportional hazards, accelerated hazards, and accelerated failure time structures, as well as combinations of these. We propose an approach to apply these different hazard structures, based on a flexible parametric distribution (exponentiated Weibull) for the baseline hazard. This distribution allows us to cover the basic hazard shapes of interest in practice: constant, bathtub, increasing, decreasing, and unimodal. In an extensive simulation study, we evaluate our approach in the context of excess hazard modelling, which is the main quantity of interest in descriptive cancer epidemiology. This study exhibits good inferential properties of the proposed model, as well as good performance when using the Akaike Information Criterion for selecting the hazard structure. An application on lung cancer data illustrates the usefulness of the proposed model.

Cancer survival trend analyses are essential to describe accurately the way medical practices impact patients’ survival according to the year of diagnosis. To this end, survival models should be able to account simultaneously for non-linear and non-proportional effects and for complex interactions between continuous variables. However, in the statistical literature, there is no consensus yet on how to build such models that should be flexible but still provide smooth estimates of survival. In this article, we tackle this challenge by smoothing the complex hypersurface (time since diagnosis, age at diagnosis, year of diagnosis, and mortality hazard) using a multidimensional penalized spline built from the tensor product of the marginal bases of time, age, and year. Considering this penalized survival model as a Poisson model, we assess the performance of this approach in estimating the net survival with a comprehensive simulation study that reflects simple and complex realistic survival trends. The bias was generally small and the root mean squared error was good and often similar to that of the true model that generated the data. This parametric approach offers many advantages and interesting prospects (such as forecasting) that make it an attractive and efficient tool for survival trend analyses.