[Budget impact of self-testing in the national cervical cancer screening program]. / Impact budgétaire de l'utilisation de l'autotest dans le cadre du programme national de dépistage du cancer du col de l'utérus.

OBJECTIVES: A nationwide screening program for cervical cancer (CC) was organized in 2018 as part of the 2014-2019 French cancer plan, with the objective of reducing CC incidence and mortality in France by reaching an 80 % coverage rate. As an alternative to pap smear, vaginal self-sampling (VSS) aimed at identifying high-risk HPV carriage could help to achieve this goal. The objective of the present study is to compare the respective budgetary impacts of several self-sampling strategies. METHOD: A budget impact model was developed to compare non-use of self-sampling in CC screening to the 5-year costs of 5 VSS strategies viewed from an all-payer perspective. While the first strategy was based on mailing the VSS kit with a reminder to participate in the screening program, the second was based on accompanying the mailed kit with an invitation to participate. The third and fourth strategies were based on providing health professionals with the kit, and thereby offering self-sampling as an alternative to pap smears for women undergoing CC screening and having previously received the kits. Finally, the fifth strategy was based on self-sampling as the one and only CC screening modality. The parameters of the model were based on past screening participation data and experiments in France on organized screening and VSS use. The costs included those of procedures associated with screening and program organization. RESULTS: All in all, the costs associated with cervical cancer screening would represent approximately 1 billion euros over 5 years. All strategies would be associated with participation ranging from 81% to 84%, which would represent an increase of 4.7% to 5.2% of lesions diagnosed by screening and a cost reduction between €30M and €87M over 5 years, with the exception of the strategy based on sending the kit (with the reminder associated or not) to the health professionals offering this option (+€23M and +€6M). CONCLUSIONS: In conclusion, the use of self-sampling as an alternative to pap smears for non-participating women would increase participation, with only a moderate budgetary impact and could, in some cases, even induce savings.

[Cost-effectiveness of transurethral resection of the bladder with blue light in patients with non muscle invasive bladder cancer in France]. / Coût-efficacité de la résection transurétrale de vessie en lumière bleue chez les patients atteints d'un cancer de la vessie non infiltrant en France.

OBJECTIVE: Photodynamic diagnosis after instillation of hexylaminolevulinate (Hexvix(®)) during transurethral resection of the bladder (TURB) helps in the detection of tumors and results in a reduction of recurrence. The medical and economic impact of fluorescence compared to conventional white light TURB needed to be analyzed in the French healthcare system. The aim of this study was to evaluate the medical and economic impact of the blue light TURB in the treatment of NMIBC. MATERIALS AND METHODS: A cost-utility model, based on data from the literature and expert opinions, combining a decision tree and a Markov model was used to simulate the initial management after a first TURB of all new patients diagnosed with symptoms consistent with NMIBC and outcomes at short and long terms. In this model, the initial TURB could be achieved either with fluorescence in addition to white light, or with white light only. The main criteria of the model was based on the quality adjusted life years (QALY). The economic evaluation focused on the direct costs. The test's results and costs were determined from diagnosis until death of patients. RESULTS: The use of photodynamic diagnosis during TURB resulted in an improvement in QALYs (0.075) and a reduction of € 670 of the costs compared to the conventional treatment with white light. Thus, the blue light resection was defined as a strategy called "dominant" over the TURB in white light. CONCLUSION: In the context of the French health system, the model of the study showed that the blue light cystoscopy during TURB was associated with increased QALYs and reduced health spending. This kind of result is rare in oncology. This health economic analysis confirms the interest of hexylaminolevulinate acid in initial management of NMIBC, according to studies conducted in United Kingdom, Italy and Poland.

Cost-effectiveness of sofosbuvir in the treatment of patients with hepatitis C.

In France, 190,306 patients were suffering from chronic hepatitis C in 2012. These patients have a decreased life expectancy and are susceptible to complications associated with chronic hepatitis. Current treatments are poorly tolerated and their effectiveness varies depending on the genotype of the virus. Sofosbuvir, a new class of treatment, has demonstrated in five phase III trials sustained viral response (SVR) rates of over 90% across genotypes, higher than current treatments and has a tolerance profile similar to placebo. The objective was to determine the cost-effectiveness of using sofosbuvir in the treatment of chronic HCV infection. A Markov model was used to compare treatment strategies with and without sofosbuvir. The model simulated the natural history of HCV infection. SVR rates were based on data from clinical trials. Utilities associated with different stages of disease were based on data from the literature. French direct medical costs were used. Price for sofosbuvir was the price used in the early access program for severe fibrosis stages. The incremental cost-effectiveness ratio for sofosbuvir versus current reference treatments was € 16,278/QALY and varied from 40,000 €/QALY for F0 stages to 12,080 €/QALY for F4 stages. The sensitivity analyses carried out confirmed the robustness of this result. Sofosbuvir is a cost-effective treatment option for patients with hepatitis C.

Parameters of control when facing stochastic demand: a DEA approach applied to Bangladeshi vaccination sites.

An aim of vaccination programs is near-complete coverage. One method for achieving this is for health facilities providing these services to operate frequently and for many hours during each session. However, if vaccine vials are not fully used, the remainder is often discarded, considered as waste. Without an active appointment schedule process, there is no way for facility staff to control the stochastic demand of potential patients, and hence reduce waste. And yet reducing the hours of operation or number of sessions per week could hinder access to vaccination services. In lieu of any formal system of controlling demand, we propose to model the optimal number of hours and sessions in order to maximize outputs, the number and type of vaccines provided given inputs, using Data Envelopment Analysis (DEA). Inputs are defined as the amount of vaccine wastage and the number of full-time equivalent staff, size of the facility, number of hours of operation and the number of sessions. Outputs are defined as the number and type of vaccines aimed at children and pregnant women. This analysis requires two models: one DEA model with possible reallocations between the number of hours and the number of sessions but with the total amount of time fixed and one model without this kind of reallocation in scheduling. Comparing these two scores we can identify the "gain" that would be possible were the scheduling of hours and sessions modified while controlling for all other types of inefficiency. By modeling an output-based model, we maintain the objective of increasing coverage while assisting decision-makers determining optimal operating processes.

Sensitivity of fetal anomaly detection as a function of time.

In this paper, we show that the ratio of the number of fetal anomalies detected by ultrasounds (US) to the total number of cases is not a consistent estimator of the US sensitivity. As Eddy pointed out, when the disease evolves over time, the sensitivity of a test also varies over time according to the development of the disease. To assess correctly the detection capability of a test, it is therefore necessary to estimate a time continuous function (sensitivity function) instead of a single parameter. From a methodological point of view, by considering the "detectability" time of a fetal anomaly as a random variable and parametrizing its distribution function, we estimate the probability that an anomaly is detected conditional upon the precise timing of actually performed US during pregnancy. We fit this model with Eurofetus data (about 7,300 abnormal fetuses), and we compare estimations for different kinds of anomalies (classification based on the system involved and/or severity of the handicap). To allow for heterogeneity of anomalies regarding the detectability time, we generally adopt mixture models. For instance, we select a bi-gamma distribution for major malformations and estimate that 63% of such anomalies are detectable quite early in pregnancy (conditional mean: 15.2 weeks of amenorrhea (WA) +/- 4.2 WA), the others becoming detectable later (30.3 WA +/- 6.4 WA). Such results are then integrated in a cost-effectiveness analysis.