Identification and Economic Evaluation of Differentiated Thyroid Cancer Care Consumption Patterns Using Sequence Analysis.

Objectives: This study aims to assess the impact of care consumption patterns and individual characteristics on the cost of treating differentiated thyroid carcinoma (DTC), in France, with a specific emphasis on socioeconomic position. Methods: The methodology involved a net cost approach utilising cases from the EVATHYR cohort and controls from the French National Health Insurance database. Care consumption patterns were created using Optimal Matching and clustering techniques. The individual characteristics influence on patterns was assessed using multinomial logistic regression. The individual characteristics and patterns influence on care costs was assessed using generalised estimating equations. Results: The findings revealed an average cost of €13,753 per patient during the initial 3 years. Regression models suggested the main predictors of high DTC specific care consumption tended to include having a high risk of cancer recurrence (OR = 4.97), being a woman (OR = 2.00), and experiencing socio-economic deprivation (OR = 1.26), though not reaching statistical significance. Finally, high DTC-specific care consumers also incurred higher general care costs (RR = 1.35). Conclusion: The study underscores the increased costs of managing DTC, shaped by consumption habits and socioeconomic position, emphasising the need for more nuanced DTC management strategies.

Multicolor flow cytometry in clinical samples for platelet signaling assessment.

Background: Availability of multichannel cytometers and specific commercial antibodies makes flow cytometry a new option to simultaneously assess multiple intracellular platelet signaling pathways for clinical purposes, in small volume of blood or low platelet count. Objectives: To describe a multicolor flow cytometry with fluorescent barcoding technique for screening signaling pathways downstream membrane receptors of major platelet agonists (adenosine diphosphate, thrombin, thromboxane, and collagen). Methods: By comparison with immunoblotting, we first selected the target phosphoproteins, AKT, P38MAPK, LIMK, and SPL76; the times of stimulation; and phosphoflow barcoding conditions. We then performed a clinical study on whole blood of patients without evidence of blood platelet disorder on standard biological screening, consulting for trivial or occasionally provoked bleeds without familial antecedent (bleeding of unknown origin, n = 23) or type-1 von Willebrand disease (n = 9). In addition, we included a small group of patients with definite platelet disorders (Glanzmann thrombasthenia, δ-storage pool deficiency, and immune glycoprotein VI-related disease with granule secretion defect). Results: The range, kinetics, and distribution of fluorescence intensity were established for each agonist-target protein combination. Principal component analysis indicates a correlation in response to a target phosphoprotein (AKT and P38MAPK) to different agonists but no correlation in the response of different target phosphoproteins to the same agonist. The heterogeneity of individual responses in the whole population displayed was analyzed using clustering algorithm. Patients with platelet storage pool deficiency were positioned as lowest responders on the heatmap. Conclusion: In complement of functional tests, this study introduces a new approach for rapid platelet signaling profiling in clinical practice.

Agent based modeling in health care economics: examples in the field of thyroid cancer.

Although they remain little used in the field of Health Care Economics, Agent Based Models (ABM) are potentially powerful decision-making tools that open up great prospects. The reasons for this lack of popularity are essentially to be found in a methodology that should be further clarified. This article hence aims to illustrate the methodology by means of two applications to medical examples. The first example of ABM illustrates the construction of a Baseline Data Cohort by means of a Virtual Baseline Generator. The aim is to describe the prevalence of thyroid cancer in the French population over the long term according to different scenarios of evolution of this population. The second study considers a setting where the Baseline Data Cohort is an established cohort of (real) patients: the EVATHYR cohort. The aim of the ABM is to describe the long-term costs associated with different scenarios of thyroid cancer management. The results are evaluated using several simulation runs in order to observe the variability of simulations and to derive prediction intervals. The ABM approach is very flexible since several sources of data can be involved and a large variety of simulation models can be calibrated to generate observations according to different evolution scenarios.

A time-dependent Poisson-Gamma model for recruitment forecasting in multicenter studies.

Forecasting recruitments is a key component of the monitoring phase of multicenter studies. One of the most popular techniques in this field is the Poisson-Gamma recruitment model, a Bayesian technique built on a doubly stochastic Poisson process. This approach is based on the modeling of enrollments as a Poisson process where the recruitment rates are assumed to be constant over time and to follow a common Gamma prior distribution. However, the constant-rate assumption is a restrictive limitation that is rarely appropriate for applications in real studies. In this paper, we illustrate a flexible generalization of this methodology which allows the enrollment rates to vary over time by modeling them through B-splines. We show the suitability of this approach for a wide range of recruitment behaviors in a simulation study and by estimating the recruitment progression of the Canadian Co-infection Cohort.

Agent-based modeling in medical research, virtual baseline generator and change in patients' profile issue.

Simulation studies are promising in medical research in particular to improve drug development. For instance, one can aim to develop In Silico Clinical Trial in order to challenge trial's design parameters in terms of feasibility and probability of success of the trial. Approaches based on agent-based models draw on a particularly useful framework to simulate patients evolution. In this paper, an approach based on agent-based modeling is described and discussed in the context of medical research. An R-vine copula model is used to represent the multivariate distribution of the data. A baseline data cohort can then be simulated and execution models can be developed to simulate the evolution of patients. R-vine copula models are very flexible tools which allow researchers to consider different marginal distributions than the ones observed in the data. It is then possible to perform data augmentation to explore a new population by simulating baseline data which are slightly different than those of the original population. A simulation study illustrates the efficiency of copula modeling to generate data according to specific marginal distributions but also highlights difficulties inherent to data augmentation.

Statistics, philosophy, and health: the SMAC 2021 webconference.

SMAC 2021 was a webconference organized in June 2021. The aim of this conference was to bring together data scientists, (bio)statisticians, philosophers, and any person interested in the questions of causality and Bayesian statistics, ranging from technical to philosophical aspects. This webconference consisted of keynote speakers and contributed speakers, and closed with a round-table organized in an unusual fashion. Indeed, organisers asked world renowned scientists to prepare two videos: a short video presenting a question of interest to them and a longer one presenting their point of view on the question. The first video served as a "teaser" for the conference and the second were presented during the conference as an introduction to the round-table. These videos and this round-table generated original scientific insights and discussion worthy of being shared with the community which we do by means of this paper.

Economic impact of generic antiretrovirals in France for HIV patients' care: a simulation between 2019 and 2023.

BACKGROUND: In a context where the economic burden of HIV is increasing as HIV patients now have a close to normal lifespan, the availability of generic antiretrovirals commonly prescribed in 2017 and the imminence of patent expiration are expected to provide substantial savings in the coming years. This article aims to assess the economic impact of these generic antiretrovirals in France and specifically over a five-year period. METHODS: An agent-based model was developed to simulate patient trajectories and treatment use over a five-year period. By comparing the results of costs for trajectories simulated under different predefined scenarios, a budget impact model can be created and sensitivity analyses performed on several parameters of importance. RESULTS: The potential economic savings from 2019 to 2023 generated by generic antiretrovirals range from €309 million when the penetration rate of generics is set at 10% to €1.5 billion at 70%. These savings range from €984 million to €993 million as the delay between patent and generic marketing authorisation varies from 10 to 15 years, and from €965 million to €993 million as the Negotiated Price per Unit (NPU) of generics at market-entry varies from 40 to 50% of the NPU for patents. DISCUSSION: This economic savings simulation could help decision makers to anticipate resource allocations for further innovation in antiretrovirals therapies as well as prevention, especially by funding the Pre-Exposure Prophylaxis (PrEP) or HIV screening.

Patient blood management in elective bypass cardiac surgery: A 2-step single-centre interventional trial to analyse the impact of an educational programme and erythropoiesis stimulation on red blood cell transfusion.

Anaemia and iron deficiency are frequent in patients scheduled for cardiac surgery. Perioperative patient blood management (PBM) is widely recommended in current practice guidelines. The aim of this protocol is to analyse the effect of a global perioperative PBM programme on the red blood cell (RBC) transfusion ratio, morbidities and rehabilitation score in elective cardiac surgery.This study is a prospective, single-centre trial with a 2-step protocol, A and B, as follows: A: non-drug intervention: the caregiver is given a blood management educational programme; B: drug intervention: systematic correction of perioperative iron, vitamin deficiencies, and anaemia. This study was designed to enrol 900 patients (500 in group A and 400 in group B) in a rolling period starting at anaesthesia consultation and ending 3 months after surgery. The primary objective was a 20% reduction in RBC transfusion after implementation of PBM programmes (protocol A + B) when compared to our previous transfusion ratio in the first half of 2018 (30.4% vs 38%). The secondary objectives were to evaluate the impact for each step of the study on the RBC transfusion rate, morbidity and the quality of postoperative rehabilitation.The strength of this study is its evaluation of the effect of a global PBM programme on RBC transfusion in cardiac surgery through a 2-step protocol. We aim to assess for the first time the impact of non-drug and drug interventions on RBC transfusion, comorbidities and delayed rehabilitation parameters. TRIALS REGISTRATIONS: ClinicalTrials.gov, NCT04040023: registered 29 July 2019.

Real-world costs of illness of Hodgkin and the main B-Cell Non-Hodgkin lymphomas in France.

Background: Lymphomas are costly diseases that suffer from a lack of detailed economic information, notably in a real-world setting. Decision-makers are increasing the search for Real-World Evidence (RWE) to assess the impact, in real-life, of healthcare management and to support their public decisions. Thus, we aimed to assess the real-world net costs of the active treatment phases of adult Hodgkin Lymphoma (HL), Follicular Lymphoma (FL) and Diffuse Large B Cell Lymphoma (DLBCL).Methods: We performed a retrospective cohort study using population-based data from a national representative sample of the French population covered by the health insurance system. Cost analysis was performed from the French health insurance perspective and took into account direct and sick leave compensation costs (€2,018). Healthcare costs were studied over the active treatment phase. We used multivariate modeling to adjust cost differences between lymphoma subtypes.Results: Analyses were performed on 224 lymphoma patients and 896 controls. The mean additional monthly costs due to HL, FL and DLBCL patients were respectively €5,188, €3,242 and €7,659 for the active treatment phase. The main additional cost driver was principally inpatient stay (hospitalization costs and costly cancer-related drugs), followed by outpatient medication and productivity loss. When adjusted, DLBCL remains significantly the most costly lymphoma subtype.Conclusion: This study provides an accurate assessment of the main lymphoma subtypes related cost with high magnitude of details in a real-world setting. We underline where potential cost saving could be realized via the use of biosimilar medication, and where lymphoma management could be improved with the early management of adverse events.KEY POINTSThis is one of the first studies which assess the additional cost of lymphoma in Europe, according the main sub-types of lymphoma and with real-world database.The additional monthly cost due to HL, FL and DLBCL patients were respectively €5,188, €3,242 and €7,659 for the active treatment phase and the main additional cost driver was principally inpatient stay (i.e. hospitalization costs and additional inpatient medicines, notably rituximab), followed by outpatient medication and productivity loss.This study provides an accurate and detailed lymphoma subtype cost description and comparison which supply data for efficiency evaluations and will allow French health policy to improve lymphoma management.

On the Use of Optimal Transportation Theory to Recode Variables and Application to Database Merging.

Merging databases is a strategy of paramount interest especially in medical research. A common problem in this context comes from a variable which is not coded on the same scale in both databases we aim to merge. This paper considers the problem of finding a relevant way to recode the variable in order to merge these two databases. To address this issue, an algorithm, based on optimal transportation theory, is proposed. Optimal transportation theory gives us an application to map the measure associated with the variable in database A to the measure associated with the same variable in database B. To do so, a cost function has to be introduced and an allocation rule has to be defined. Such a function and such a rule is proposed involving the information contained in the covariates. In this paper, the method is compared to multiple imputation by chained equations and a statistical learning method and has demonstrated a better average accuracy in many situations. Applications on both simulated and real datasets show that the efficiency of the proposed merging algorithm depends on how the covariates are linked with the variable of interest.

Additional Costs of Polymyalgia Rheumatica With Giant Cell Arteritis.

OBJECTIVE: To assess and compare direct costs between patients with giant cell arteritis (GCA) that is associated or not associated with polymyalgia rheumatic (PMR), and to identify the additional cost drivers due to PMR. METHODS: A population-based, retrospective cohort study using the French National Health Insurance System Database was conducted. Cost analysis was performed from the French health insurance perspective and direct medical and nonmedical costs were taken into account (based on 2014 costs [€]). Costs were analyzed according to different components and divided into 6-month periods to assess care consumption. Longitudinal multivariate analyses, using generalized estimating equations, were used to adjust the effect of PMR on the mean cost over time. RESULTS: Analyses were performed on 100 incident patients with GCA, 54 of whom had PMR. The cumulative additional cost due to PMR was €8,801 for 3 years, and €10,532 for 5 years. The significant additional costs occurred especially during the second and third years of follow-up, amounting to €1,769 between 12 and 18 months (P = 0.02), €1,924 between 18 and 24 months (P = 0.17), €1,458 between 24 and 30 months (P = 0.08), and €1,307 between 30 and 36 months (P = 0.07). The most important cost drivers were inpatient stays, paramedic procedures, and medications. Multivariate analyses showed a significant effect of PMR on mean cost during the first 3 years of follow-up (relative risk 1.76 [95% confidence interval 1.03-2.99], P = 0.038). CONCLUSION: To our knowledge, this study is the first to accurately assess the cost of PMR care in patients with GCA and to highlight that PMR is largely responsible for the high cost of GCA.

The GMO90+ Project: Absence of Evidence for Biologically Meaningful Effects of Genetically Modified Maize-based Diets on Wistar Rats After 6-Months Feeding Comparative Trial.

The GMO90+ project was designed to identify biomarkers of exposure or health effects in Wistar Han RCC rats exposed in their diet to 2 genetically modified plants (GMP) and assess additional information with the use of metabolomic and transcriptomic techniques. Rats were fed for 6-months with 8 maize-based diets at 33% that comprised either MON810 (11% and 33%) or NK603 grains (11% and 33% with or without glyphosate treatment) or their corresponding near-isogenic controls. Extensive chemical and targeted analyses undertaken to assess each diet demonstrated that they could be used for the feeding trial. Rats were necropsied after 3 and 6 months. Based on the Organization for Economic Cooperation and Development test guideline 408, the parameters tested showed a limited number of significant differences in pairwise comparisons, very few concerning GMP versus non-GMP. In such cases, no biological relevance could be established owing to the absence of difference in biologically linked variables, dose-response effects, or clinical disorders. No alteration of the reproduction function and kidney physiology was found. Metabolomics analyses on fluids (blood, urine) were performed after 3, 4.5, and 6 months. Transcriptomics analyses on organs (liver, kidney) were performed after 3 and 6 months. Again, among the significant differences in pairwise comparisons, no GMP effect was observed in contrast to that of maize variety and culture site. Indeed, based on transcriptomic and metabolomic data, we could differentiate MON- to NK-based diets. In conclusion, using this experimental design, no biomarkers of adverse health effect could be attributed to the consumption of GMP diets in comparison with the consumption of their near-isogenic non-GMP controls.

Stopping or maintaining oral anticoagulation in patients undergoing photoselective vaporization of the prostate (SOAP) surgery for benign prostate obstruction: study protocol for a multicentre randomized controlled trial.

BACKGROUND: Lower urinary tract symptoms related to benign prostatic obstruction (BPO) are frequent in men aged > 50 years. Based on the use of innovative medical devices, a number of transurethral ablative techniques have recently been developed for the surgical treatment of BPO. In recent years, GreenLight photoselective vaporization of the prostate (PVP) has been considered as a non-inferior alternative to transurethral resection of the prostate. The GreenLight PVP is usually considered as an interesting surgical option for patients treated via oral anticoagulants (OACs) with regard to its haemostatic properties. The aim of this study was to assess the impact of maintaining OAC treatment in patients undergoing PVP. METHODS: This study is a multicentre, open-label, randomized controlled trial (RCT) designed to show the non-inferiority of PVP surgery in patients with BPO treated with OACs. This study is designed to enrol 386 OAC-treated patients (treated with vitamin K antagonists and direct oral anticoagulants) who are undergoing PVP for BPO. Patients will be randomized (1:1) to either maintain or stop OAC treatment during the perioperative course. The intervention group will maintain OAC treatment until the day before surgery and resume OAC treatment the day after surgery, whereas the control group will stop OAC treatment (with or without low-molecular-weight heparin bridging therapy) according to the anaesthesia guidelines. The primary outcome of interest to be assessed is the 30-day complications rate according to the Clavien-Dindo classification. The secondary endpoint will examine the 30-day rate of haemorrhagic and thrombotic events. This study will provide 80% power to show non-inferiority, defined as not worse than a 10% (non-inferiority margin) inferior change in the proportion of patients with good outcomes (Clavien-Dindo score < 2), using two-tailed 95% confidence intervals. DISCUSSION: This first multicentre RCT in the field is underway to evaluate the safety and efficacy of PVP in patients with ongoing OAC therapy. The study results could influence the perioperative management of OACs in BPO surgery with a high level of evidence. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03297281 . Registered on 29 September 2017.

Incremental Costs in Giant Cell Arteritis.

OBJECTIVE: To assess and compare direct costs between giant cell arteritis (GCA) patients and matched controls and to identify incremental cost drivers. METHODS: We carried out a population-based, retrospective cohort study using the French National Health Insurance System database. Cost analysis was performed from the French health insurance perspective and took into account direct medical and nonmedical costs (2014, €). Costs were evaluated according to different cost components and divided into periods of 6 months for the accurate assessment of care consumption. Longitudinal multivariate regression analyses using generalized estimating equations were used to adjust the effect of GCA on the mean cost over time. RESULTS: Analyses were performed on 96 incident GCA patients and 563 matched controls. The cumulative incremental cost due to GCA was €6,406 and €7,236 for 3 and 5 years, respectively. Total incremental costs were significant for the first 18 months, amounting to €1,342 for the first 6 months, €1,498 between 6 and 12 months, and €1,165 between 12 and 18 months (P = 0.012, P = 0.065, and P = 0.029, respectively). The most important cost drivers were paramedical procedures, inpatient stays, medication, and medical procedures. Multivariate analysis shows the significant effect of GCA on mean cost during the first 3 years of followup (relative risk [RR] 1.72 [95% confidence interval (95% CI) 1.31-2.27], P < 0.001) with significant cost reductions (RR 0.70 [95% CI 0.49-0.99], P = 0.05) at the end of followup. CONCLUSION: This study provides an accurate assessment of GCA costs during a 5-year period and gives useful information for future cost-effectiveness studies based on new expensive biotherapies.

Using Poisson-gamma model to evaluate the duration of recruitment process when historical trials are available.

At the design of clinical trial operation, a question of a paramount interest is how long it takes to recruit a given number of patients. Modelling the recruitment dynamics is the necessary step to answer this question. Poisson-gamma model provides very convenient, flexible and realistic approach. This model allows predicting the trial duration using data collected at an interim time with very good accuracy. A natural question arises: how to evaluate the parameters of recruitment model before the trial begins? The question is harder to handle as there are no recruitment data available for this trial. However, if there exist similar completed trials, it is appealing to use data from these trials to investigate feasibility of the recruitment process. In this paper, the authors explore the recruitment data of two similar clinical trials (Intergroupe Francais du Myélome 2005 and 2009). It is shown that the natural idea of plugging the historical rates estimated from the completed trial in the same centres of the new trial for predicting recruitment is not a relevant strategy. In contrast, using the parameters of a gamma distribution of the rates estimated from the completed trial in the recruitment dynamic model of the new trial provides reasonable predictive properties with relevant confidence intervals. Copyright © 2017 John Wiley & Sons, Ltd.

Interest of the trajectory method for the evaluation of outcomes after in utero drug exposure: example of anxiolytics and hypnotics.

PURPOSE: The aim of this study was to examine the potential benefit to take into account duration and intensity of drug exposure using the recently published method based on individual drug trajectories. This approach was used to define profiles of exposure to anxiolytics/hypnotics during pregnancy and to evaluate the potential effect on newborn health. METHODS: The study was performed in EFEMERIS database (54 918 mother-children pairs). An estimation of adaptation to extrauterine life was assessed using several criteria especially cardio-respiratory symptoms. A proxy variable called "neonatal pathology" was created. The occurrence of this event was studied using two approaches: The Standard Method comparing exposed and unexposed newborns, The Trajectory Method comparing the different profiles of exposure. RESULTS: Around 5% of newborns (n = 2768) were identified to be exposed to anxiolytics or hypnotics during pregnancy. Using the Standard Method, 6.2% of exposed newborns developed a "neonatal pathology" against 4.8% of unexposed newborns (odds ratios [OR] = 0.9[0.8-1.2], p = 0.7). With the Trajectory Method taking into account evolution of exposure during pregnancy and treatment intensity, four profiles of pregnant women were identified. A significant difference in the rates of "neonatal pathologies" was observed between profiles (p = 0.0002). Newborns of the two profiles exposed in utero to high constant level of anxiolytics or hypnotics were more at risk of developing "neonatal pathology" than unexposed newborns (OR1  = 2.0 [1.0-3.9] and OR2  = 7.6 [2.8-20.5]). CONCLUSIONS: The present study demonstrates the interest of this method based on individual drug trajectories for the evaluation of outcomes in pharmaco-epidemiological studies and more specifically during pregnancy. Copyright © 2017 John Wiley & Sons, Ltd.

How to deal with the Poisson-gamma model to forecast patients' recruitment in clinical trials when there are pauses in recruitment dynamic?

Recruiting patients is a crucial step of a clinical trial. Estimation of the trial duration is a question of paramount interest. Most techniques are based on deterministic models and various ad hoc methods neglecting the variability in the recruitment process. To overpass this difficulty the so-called Poisson-gamma model has been introduced involving, for each centre, a recruitment process modelled by a Poisson process whose rate is assumed constant in time and gamma-distributed. The relevancy of this model has been widely investigated. In practice, rates are rarely constant in time, there are breaks in recruitment (for instance week-ends or holidays). Such information can be collected and included in a model considering piecewise constant rate functions yielding to an inhomogeneous Cox model. The estimation of the trial duration is much more difficult. Three strategies of computation of the expected trial duration are proposed considering all the breaks, considering only large breaks and without considering breaks. The bias of these estimations procedure are assessed by means of simulation studies considering three scenarios of breaks simulation. These strategies yield to estimations with a very small bias. Moreover, the strategy with the best performances in terms of prediction and with the smallest bias is the one which does not take into account of breaks. This result is important as, in practice, collecting breaks data is pretty hard to manage.

How to take into account exposure to drugs over time in pharmacoepidemiology studies of pregnant women?

PURPOSE: The aim of this study was to develop a new pharmacoepidemiological method to take into account intensity and evolution of drug exposure, applied to pregnant women. METHODS: Pregnant women were classified according to their drug exposure, in three steps: Conversion of prescription data into exposure variables (using ATC-DDD) Construction of individual trajectories of exposure Clustering of individual trajectories of exposure (using the R package Kml) We applied this method to psychotropic drugs prescribed during pregnancy. The present study involved women, included in the EFEMERIS database, who gave birth in Haute-Garonne (France) between 2004 and 2010 (N = 54 918). RESULTS: Exposure to psychotropic drugs of 3708 pregnant women was studied (6.7%). The pregnant women could be classified into four groups with homogeneous trajectories of exposure: low constant exposure during pregnancy (Cluster A: 70.8% of women); decreasing exposure during the first trimester of pregnancy and low constant exposure thereafter (Cluster B: 19.6%); moderate constant exposure (Cluster C: 8.2%); and high albeit decreasing exposure (Cluster D: 1.4%). CONCLUSIONS: The proposed new method enabled us to describe more precisely women's exposure to drugs during pregnancy, and to distinguish different profiles of exposure. This method could be used to investigate specific outcomes related to duration and intensity of drug exposure during pregnancy, and also to study adverse drug reactions throughout life. Copyright © 2016 John Wiley & Sons, Ltd.