Contribuer à l'amélioration du ciblage thérapeutique en oncologie par une nouvelle méthodologie des essais de phase II

On constate que la majorité des essais de phase III, conduits après des essais de phase II pourtant prometteurs, sont négatifs , la nouvelle thérapeutique se révélant finalement trop toxique ou insuffisamment efficace. L hétérogénéité de la population participant aux différentes phases de développement est une explication. Elle induirait une estimation erronée de la toxicité et, par dilution de l effet traitement, conduirait à arrêter l évaluation thérapeutique alors que peut être un sous-ensemble de cette population, définie à partir d une caractéristique particulière, pourrait en bénéficier.Dans cette thèse, nous proposons dans un premier temps une réflexion sur les aspects méthodologiques des essais de phase II qui permettraient d améliorer l identification précoce des thérapeutiques toxiques et des populations les plus sensibles et donc de ne planifier des essais de phase III que sur des populations encore mieux ciblées. Dans un second temps, nous présentons une nouvelle méthodologie d essai de phase II que nous avons développée pour prendre en compte l hétérogénéité de la population et son intérêt en pratique clinique courante. Avec cette méthode, qui est une extension du plan de Fleming à deux étapes, le développement des médicaments est moins fréquemment arrêté pour la population entière et moins de patients non sensibles à la nouvelle thérapeutique sont exposés à des molécules potentiellement toxiques, durant l étape 2 de l essai de phase II ou plus tard lors de l essai de phase III.The majority of phase III clinical trials, despite being conducted after promising phase II trials, are "negative," with the new therapy determined in the end to be too toxic or insufficiently efficacious. One explanation is the heterogeneity of the populations participating in various phases of development, which results in an erroneous estimation of the toxicity and thus a diluted therapeutic effect. This may lead to termination of evaluation of a therapy, even if a sub-population, defined by a particular characteristic, may stand to benefit from it. In this thesis, we propose a close examination of the methodological aspects of phase II trials which would permit improved early identification of toxic therapies and of responsive populations, so that phase III trials may be designed only with the best targeted populations in mind. We present as well a new phase II clinical trial methodology which we have developed to take into account trial population heterogeneity and its importance in current clinical practice. With this method, drug development is less often stopped for the entire phase II population and less non sensitive patients are exposed to toxic drugs in the second part of phase II trials, and next in phase III trials.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

A two-stage design for phase II trials with time-to-event endpoint using restricted follow-up

In phase II oncology trials, the use of new cytostatic drugs raises some questions regarding the endpoint. Time-to-event endpoints such as Progression-Free Survival have been recommended and led to new designs. In 2003, Case and Morgan proposed a design based on the comparison of the cumulative hazards at a clinically relevant timepoint. In 2013, Kwak proposed a design based on the one-sample log-rank test. If all the patients are followed from their entry time to the analysis date, the Kwak and Jung’s design leads to a smaller sample size as compared to the Case-Morgan’s design. However, the Case and Morgan’s design requires less information since it only needs to follow every patient during a fixed interval of time. We propose a trade-off between these two approaches that corresponds to an adaptation of Kwak and Jung’s design when the follow-up is expected to be restricted. Our proposal is based on the one-sample log-rank test as the Kwak and Jung’s design but it uses the same follow-up information as the Case-Morgan’s design. Simulation study shows that our proposal allows reducing the sample size as compared to the Case-Morgan’s design (median difference of 23% [15%-33%]). Type I and type II error rates are close to their nominal rates planned in the protocol. A real phase II clinical trial in cervical cancer illustrated the interest of this new design. Thus, our proposal can be recommended as an alternative to the Kwak’s design when patients’ follow-up is restricted

Incidence du cancer du sein parmi les salariées en activité des industries électriques et gazières (période 1990-2006) (application d une méthode de standardisation par le modèle de Poisson)

PARIS7-Xavier Bichat (751182101) / SudocSudocFranceF

Trajectories of Adherence to Low-Dose Aspirin Treatment Among the French Population

International audienceBACKGROUND: Previous studies have shown that adherence to low-dose aspirin (LDA) is suboptimal. However, these studies were based on an average measure of adherence during follow-up, ignoring its dynamic process over time. We described the trajectories of adherence to LDA treatment among the French population over 3 years of follow-up.METHODS: We identified a cohort of 11 793 new LDA users, aged ≥50 years in 2010, by using the French national health-care database. Patients included had at least 3 years of history in the database before study entry to exclude prevalent aspirin users and to assess baseline comorbidities. They were followed from the first date of LDA supply (the index date) until the first date among death, exit from the database, or 3 years after the index date. Adherence to LDA was assessed every 3 months by using the proportion of days covered (PDC) and dichotomized with a cutoff of PDC of 0.8. We used group-based trajectory modeling to identify trajectories of LDA adherence. Predictors of LDA adherence trajectory membership were identified by multinomial logistics regression.RESULTS: We identified 4 trajectories of adherence among new LDA users: the not-adherents (4737 [40.2%]), the delayed not-adherents (gradual decrease in adherence probability, 1601 [13.6%]), the delayed adherents (gradual increase in adherence probability, 1137 [9.6%]), and the persistent adherents (4318 [36.6%]). The probability of belonging to the not-adherent group was increased with female sex, low socioeconomic status, and polymedication and was reduced with a secondary indication for LDA use, such as diabetes, hypertension, and dementia, at least 4 consultations in the previous year, or 1 hospitalization or a cardiologist consultation in the 3 months before the index date.CONCLUSION: This study provides a dynamic picture of adherence behaviors among new LDA users and underlines the presence of critical trajectories that intervention could target to improve adherence

Estimation of conditional and marginal odds ratios using the prognostic score

International audienceIntroduced by Hansen in 2008, the prognostic score (PGS) has been presented as ‘the prognostic analogue of the propensity score’ (PPS). PPS-based methods are intended to estimate marginal effects. Most previous studies evaluated the performance of existing PGS-based methods (adjustment, stratification and matching using the PGS) in situations in which the theoretical conditional and marginal effects are equal (i.e., collapsible situations). To support the use of PGS framework as an alternative to the PPS framework, applied researchers must have reliable information about the type of treatment effect estimated by each method. We propose four new PGS-based methods, each developed to estimate a specific type of treatment effect. We evaluated the ability of existing and new PGS-based methods to estimate the conditional treatment effect (CTE), the (marginal) average treatment effect on the whole population (ATE), and the (marginal) average treatment effect on the treated population (ATT), when the odds ratio (a non-collapsible estimator) is the measure of interest. The performance of PGS-based methods was assessed by Monte Carlo simulations and compared with PPS-based methods and multivariate regression analysis. Existing PGS-based methods did not allow for estimating the ATE and showed unacceptable performance when the proportion of exposed subjects was large. When estimating marginal effects, PPS-based methods were too conservative, whereas the new PGS-based methods performed better with low prevalence of exposure, and had coverages closer to the nominal value. When estimating CTE, the new PGS-based methods performed as well as traditional multivariate regression

Progression-Free Survival as a Surrogate for Overall Survival in Oncology Trials: A Methodological Systematic Review

International audienceAbstract Background Progression-free survival (PFS) is a surrogate endpoint widely used for overall survival (OS) in oncology. Validation of PFS as a surrogate must be done for each indication and each intervention. We aimed to identify all studies evaluating the validity of PFS as a surrogate for OS in oncology, and to describe their methodological characteristics. Methods We conducted a systematic review by searching MEDLINE via PubMed and the Cochrane Library with no limitation on time, selected relevant studies and extracted data in duplicate on how surrogacy was evaluated (meta-analytic approach, assessment of correlation and level of evaluation). Results We identified 91 studies evaluating the validity of PFS as a surrogate for OS in 24 cancer localisations. Although a meta-analytic approach was used in 83 (91%) studies, the methods used to validate PFS as a surrogate of OS were heterogeneous across studies. Of the 47 studies concluding that PFS is a good surrogate for OS, for 15 (32%), there was no quantitative argument for surrogacy. Conclusions Although most studies used a meta-analytic approach as recommended, our methodological review highlights heterogeneity in methods and reporting, which stresses the importance of developing and applying clear recommendations in this area

A Rescue Strategy for Handling Unevaluable Patients in Simon’s Two Stage Design

<div><p>For phase II oncology trials, Simon’s two-stage design is the most commonly used strategy. However, when clinically unevaluable patients occur, the total number of patients included at each stage differs from what was initially planned. Such situations raise concerns about the operating characteristics of the trial design. This paper evaluates three classical <i>ad hoc</i> strategies and a novel one proposed in this work for handling unevaluable patients. This latter is called the <i>rescue</i> strategy which adapts the critical stopping rules to the number of unevaluable patients at each stage without modifying the planned sample size. blue Simulations show that none of these strategies perfectly match the original target constraints for type I and II error rates. Our <i>rescue</i> strategy is nevertheless the one which best approaches the target error rates requirement. A re-analysis of one real phase II clinical trials on metastatic cancer illustrates the use of the proposed strategy.</p></div

Simulation results of the Weibull <i>rescue</i> strategy using Weibull failure times and uniform censoring times.

<p>Simulation results of the Weibull <i>rescue</i> strategy using Weibull failure times and uniform censoring times.</p

Bias obtained by each strategies according to the simulated data distributions on optimal Simon’s design with <i>π</i> = 40%.

<p>EU: exponential failure time and uniform censoring times, EE: exponential failure times and exponential censoring times, WU: Weibull failure times and uniform censoring times, WE: Weibull failure times and exponential censoring times, LU: log-logistic failure times and uniform censoring times, LE: log-logistic failure times and exponential censoring times.</p><p>Bias obtained by each strategies according to the simulated data distributions on optimal Simon’s design with <i>π</i> = 40%.</p