Since 2013, the coverage of innovative and expensive drugs by the French National Health Insurance considers cost-effectiveness and budget impact, as assessed by the National Authority for Health (HAS) on the basis of an evaluation submitted by the firm. First CAR-T cell therapies were subject to economic evaluation in 2019 in France. We aim at describing the process and results of the economic evaluation of tisagenlecleucel and axicabtagene ciloleucel and the challenges these evaluations raised.

Primary evaluations were submitted by the firms to be reviewed by HAS. The final analyses were submitted to the Committee of Economic Evaluation and Public Health (CEESP), composed of independent economists, clinicians and patients’ representatives. The CEESP issued Opinions related to i) the methodological quality of economic evidence and ii) the cost-effectiveness and budget impact of the drugs under review.

The estimated incremental cost-utility ratio (ICUR) of tisagenlecleucel were rejected, being based on insufficient clinical evidence to estimate and extrapolate the long-term progression and to compare tisagenlecleucel with alternatives. Thus, the CEESP concluded that tisagenlecleucel was not proved cost-effective. The estimated ICUR of axicabtagene ciloleucel at 114,509EUR/QALY vs. chemotherapies was associated with an acceptable level of evidence despite being based on a frail indirect comparison and limited data on quality of life. In a context where France has no official cost-effectiveness threshold, the CEESP considered axicabtagene ciloleucel ICUR to be “very high” and questioned the collective acceptability of the claimed price.

The CEESP stressed that the main source of uncertainty surrounding the ICUR estimates of both drugs was related to the lack of hindsight on effectiveness, especially in terms of overall survival and safety.

The economic evaluation of CAR-T cell therapies highlights the sources of uncertainty underlying the decision and the risk of inefficient resource allocation driven by limited clinical data. It calls for payment schemes accounting for the uncertainty, and effective collection of relevant post-marketing data.

Adolescents with CHD require transition to specialised adult-centred care. Previous studies have shown that adolescents’ knowledge of their medical condition is correlated with transition readiness. Three-dimensional printed models of CHD have been used to educate medical trainees and patients, although no studies have focused on adolescents with CHD. This study investigates the feasibility of combining patient-specific, digital 3D heart models with tele-education interventions to improve the medical knowledge of adolescents with CHD.

Adolescent patients with CHD, aged between 13 and 18 years old, were enrolled and scheduled for a tele-education session. Patient-specific digital 3D heart models were created using images from clinically indicated cardiac magnetic resonance studies. The tele-education session was performed using commercially available, web-conferencing software (Zoom, Zoom Video Communications Inc.) and a customised software (Cardiac Review 3D, Indicated Inc.) incorporating an interactive display of the digital 3D heart model. Medical knowledge was assessed using pre- and post-session questionnaires that were scored by independent reviewers.

Twenty-two adolescents completed the study. The average age of patients was 16 years old (standard deviation 1.5 years) and 56% of patients identified as female. Patients had a variety of cardiac defects, including tetralogy of Fallot, transposition of great arteries, and coarctation of aorta. Post-intervention, adolescents’ medical knowledge of their cardiac defects and cardiac surgeries improved compared to pre-intervention (p < 0.01).

Combining patient-specific, digital 3D heart models with tele-education sessions can improve adolescents’ medical knowledge and may assist with transition to adult-centred care.

A novel paediatric disease, multi-system inflammatory syndrome in children, has emerged during the 2019 coronavirus disease pandemic.

To describe the short-term evolution of cardiac complications and associated risk factors in patients with multi-system inflammatory syndrome in children.

Retrospective single-centre study of confirmed multi-system inflammatory syndrome in children treated from 29 March, 2020 to 1 September, 2020. Cardiac complications during the acute phase were defined as decreased systolic function, coronary artery abnormalities, pericardial effusion, or mitral and/or tricuspid valve regurgitation. Patients with or without cardiac complications were compared with chi-square, Fisher’s exact, and Wilcoxon rank sum.

Thirty-nine children with median (interquartile range) age 7.8 (3.6–12.7) years were included. Nineteen (49%) patients developed cardiac complications including systolic dysfunction (33%), valvular regurgitation (31%), coronary artery abnormalities (18%), and pericardial effusion (5%). At the time of the most recent follow-up, at a median (interquartile range) of 49 (26–61) days, cardiac complications resolved in 16/19 (84%) patients. Two patients had persistent mild systolic dysfunction and one patient had persistent coronary artery abnormality. Children with cardiac complications were more likely to have higher N-terminal B-type natriuretic peptide (p = 0.01), higher white blood cell count (p = 0.01), higher neutrophil count (p = 0.02), severe lymphopenia (p = 0.05), use of milrinone (p = 0.03), and intensive care requirement (p = 0.04).

Patients with multi-system inflammatory syndrome in children had a high rate of cardiac complications in the acute phase, with associated inflammatory markers. Although cardiac complications resolved in 84% of patients, further long-term studies are needed to assess if the cardiac abnormalities (transient or persistent) are associated with major cardiac events.

To assess the relationship between food insecurity, sleep quality, and days with mental and physical health issues among college students.

An online survey was administered. Food insecurity was assessed using the ten-item Adult Food Security Survey Module. Sleep was measured using the nineteen-item Pittsburgh Sleep Quality Index (PSQI). Mental health and physical health were measured using three items from the Healthy Days Core Module. Multivariate logistic regression was conducted to assess the relationship between food insecurity, sleep quality, and days with poor mental and physical health.

Twenty-two higher education institutions.

College students (n 17 686) enrolled at one of twenty-two participating universities.

Compared with food-secure students, those classified as food insecure (43·4 %) had higher PSQI scores indicating poorer sleep quality (P < 0·0001) and reported more days with poor mental (P < 0·0001) and physical (P < 0·0001) health as well as days when mental and physical health prevented them from completing daily activities (P < 0·0001). Food-insecure students had higher adjusted odds of having poor sleep quality (adjusted OR (AOR): 1·13; 95 % CI 1·12, 1·14), days with poor physical health (AOR: 1·01; 95 % CI 1·01, 1·02), days with poor mental health (AOR: 1·03; 95 % CI 1·02, 1·03) and days when poor mental or physical health prevented them from completing daily activities (AOR: 1·03; 95 % CI 1·02, 1·04).

College students report high food insecurity which is associated with poor mental and physical health, and sleep quality. Multi-level policy changes and campus wellness programmes are needed to prevent food insecurity and improve student health-related outcomes.

Without a robust evidence base to support recommendations for medical services at mass gatherings (MGs), levels of care will continue to vary and preventable morbidity and mortality will exist. Accordingly, researchers and clinicians publish case reports and case series to capture and explain some of the health interventions, health outcomes, and host community impacts of MGs. Streamlining and standardizing post-event reporting for MG medical services and associated health outcomes could improve inter-event comparability, thereby supporting and promoting growth of the evidence base for this discipline. The present paper is focused on theory building, proposing a set of domains for data that may support increasingly comprehensive, yet lean, reporting on the health outcomes of MGs. This paper is paired with another presenting a proposal for a post-event reporting template.

The conceptual categories of data presented are based on a textual analysis of 54 published post-event medical case reports and a comparison of the features of published data models for MG health outcomes.

A comparison of existing data models illustrates that none of the models are explicitly informed by a conceptual lens. Based on an analysis of the literature reviewed, four data domains emerged. These included: (i) the Event Domain, (ii) the Hazard and Risk Domain, (iii) the Capacity Domain, and (iv) the Clinical Domain. These domains mapped to 16 sub-domains.

Data modelling for the health outcomes related to MGs is currently in its infancy. The proposed illustration is a set of operationally relevant data domains that apply equally to small, medium, and large-sized events. Further development of these domains could move the MG community forward and shift post-event health outcomes reporting in the direction of increasing consistency and comprehensiveness.

Currently, data collection and analysis related to understanding health outcomes arising from MGs is not informed by robust conceptual models. This paper is part of a series of nested papers focused on the future state of post-event medical reporting.

Case reports are commonly used to report the health outcomes of mass gatherings (MGs), and many published reports of MGs demonstrate substantial heterogeneity of included descriptors. As such, it is challenging to perform rigorous comparisons of health services and outcomes between similar and dissimilar events. The degree of variation in published reports has not yet been investigated.

Examine patterns of post-event medical reporting in the existing literature and identify inconsistencies in reporting.

A systematic review of case reports was conducted. Included were English studies, published between January 2009 and December 2018, in Prehospital and Disaster Medicine (PDM) or Current Sports Medicine Reports (CSMR). Analysis of each paper was used to develop a list of 27 categories of data.

Seventy-five studies were initially reviewed with 54 publications meeting the inclusion criteria. Forty-two were full case reports (78%) and 12 were conference proceedings (22%). Of the 27 categories of data studied, only 13 were consistently reported in more than 50% of publications. Reporting patterns included inconsistent use of terminology/language and variable retrievability of reports. Reporting on event descriptors, hazard and risk analysis, and clinical outcomes were also inconsistent.

Case reports are essential tools for researchers and event team members such as medical directors and event producers. The authors found that current case reports, in addition to being inconsistent in content, were generally descriptive rather than explanatory; that is, focused on describing the outcomes as opposed to exploring possible connections between context and health outcomes.

This paper quantifies and demonstrates the current state of heterogeneity in MG event reporting. This heterogeneity is a significant impediment to the functional use of published reports to further the science of MG planning and to improve health outcomes. Future work based on the insights gained from this analysis will aim to align and standardize reporting to improve the quality and value of event reporting.

Standardizing and systematizing the reporting of health outcomes from mass gatherings (MGs) will improve the quality of data being reported. Setting minimum standards for case reporting is an important strategy for improving data quality. This paper is one of a series of papers focused on understanding the current state, and shaping the future state, of post-event case reporting.

Multiple data sources were used in creating a lean, yet comprehensive list of essential reporting fields, including a: (1) literature synthesis drawn from analysis of 54 post-event case reports; (2) comparison of existing data models for MGs; (3) qualitative analysis of gaps in current case reports; and (4) set of data domains developed based on the preceding sources.

Existing literature fails to consistently report variables that may be essential for not only describing the health outcomes of a given event, but also for explaining those outcomes. In the context of current and future state reporting, 25 essential variables were identified. The essential variables were organized according to four domains, including: (i) Event Domain; (ii) Hazard and Risk Domain; (iii) Capacity Domain; and (iv) Clinical Domain.

The authors propose a first-generation template for post-event medical reporting. This template standardizes the reporting of 25 essential variables. An accompanying data dictionary provides background and standardization for each of the essential variables. Of note, this template is lean and will develop over time, with input from the international MG community. In the future, additional groups of variables may be helpful as “overlays,” depending on the event category and type.

This paper presents a template for post-event medical reporting. It is hoped that consistent reporting of essential variables will improve both data collection and the ability to make comparisons between events so that the science underpinning MG health can continue to advance.