Development and evaluation of methods to examine sources of heterogeneity in DIF and response shift when analyzing patient-reported outcome data
Subjective concepts such as fatigue, anxiety, or quality of life are increasingly being used in biomedical research. These unobservable subjective concepts are measured by means of questionnaires, usually self-reported by patients. However, the analysis of these data can be challenging. Indeed, the direct comparison of questionnaire scores between different groups of individuals or over time assumes that all individuals interpret the questions in the same way and that this interpretation does not change over time. Yet, this assumption may be unmet. For example, some individuals may interpret the measured concept (and the associated items) differently because of their cultural, environmental, and personal characteristics, but also because of the experiences they went through.
This phenomenon is known as differential item functioning (DIF). In addition, following a major health event, some individuals may also change their interpretation of the items composing the questionnaire (response shift, RS). Both DIF and RS can threaten the accurate interpretation of patient-reported outcome measures. In addition, they are also phenomena that deserve to be studied. This thesis aims to propose and evaluate, by simulations, methodological developments to study the sources of heterogeneity of these two phenomena. This manuscript is composed of three main works: (i) the development of a method aiming at individualizing RS detection, (ii) the development of a method for detecting DIF in the presence of two binary covariates, and (iii) the study of the psychometric properties of the post-traumatic growth inventory (a phenomenon potentially related to RS)
Application of Rasch Measurement Theory to clinical research: Practical and theoretical aspects of a metrological approach for the evaluation of clinical trial endpoints
Metrology benefited to physical measures, on which most clinical trial endpoints are based on. As Patient-Reported Outcomes (PROs) measures are more and more used in clinical trials, it is urgent that they reach the same level of credibility and interpretability than traditional trial endpoints. The objective of this work was thus to explore how metrology can benefit to the evaluation of treatments as per the PRO endpoints from clinical trials. The Rasch model has previously shown numerous advantages in fulfilling metrological requirements. A first step of this work was to conceptualize the trial in the case of a PRO endpoint through a scientific model, based on metrological vocabulary: the clinical trial as a measurement system. From this, we list and categorize measurement uncertainty sources in clinical trials, in order to improve its expression with the trial PRO results. Finally, we present the results from a simulation study which suggest that calibration of PRO measures does not negatively impact the results from the trial. Proposals to improve measurement of patient experience in clinical trials are then made based on this work.
Analysis of the place of phase IV studies for drug risk assessment in vulnerable populations
During clinical development, the risk to the patient is monitored. However, when a health product is placed on the market, knowledge of its benefit-risk balance is only fragmentary. The post-marketing surveillance system, which makes it possible to update this balance, is based essentially on spontaneous reporting of adverse effects. What is the need for phase IV studies, in addition to clinical trial data and pharmacovigilance evaluation? The objective of our research is to study the complementary approach of phase IV studies and their interest in relation to phase III studies and pharmacovigilance data, by focusing on an example of a population that is little studied in clinical trials, the elderly, and old drugs, benzodiazepines and an effect occurring during long-term use, drug dependence. Our work shows that post-marketing studies are essential to know the risk and dependence profile of a drug, which evolves throughout its "life". Predicting possible situations of dependence, detour, etc. requires a good evaluation of the benefit-risk balance not only for medical use in the MA, but also in all off-label use situations, including non-medical use. These data are essential to understand the obstacles to the application of recommendations or regulations on proper use.
Discover older theses
Expression the cluster effect for binary outcomes
In cluster randomized trials, it is recommended to report a measure of intracluster correlation, such as the intraclass correlation coefficient (ICC), for each primary outcome.
Providing intracluster correlation estimates, which we can also call clustering estimates, may help in sample size calculation of future cluster randomized trials but also in interpreting the results of a trial. For instance, a lower intracluster correlation in the intervention arm as compared to the control one may reveal a better standardization in practices among clusters of the intervention arm, leading to a lower between-cluster heterogeneity in outcomes. Yet, when the outcome is binary, the ICC is known to be associated with the prevalence of the outcome. This may raise issues when using ICC estimates to plan a new study, because expected outcome prevalences may di er from those observed in the study from which the ICC estimates were derived. This association also challenges the interpretation of the ICC because ICC values no longer just depend on clustering level. The aim of this PhD thesis was to study several intracluster correlation measures to identify whether they depend on the outcome prevalence as the ICC does or not. We first focused on the R coefficient, a coefficient initially proposed by Rosner for ophthalmologic data and later extended by Crespi et al. who asserted that the R coefficient may be less influenced by the outcome prevalence than is the ICC. We showed by a simulation study that this assertion is false and that the R coefficient is probably even worse than the ICC as an intracluster correlation measure. We further studied other measures such as the variance partition coefficient, the median odds ratio or the tetrachoric correlation coefficient. We also proposed to consider the relative deviation of an ICC estimate to its theoretical maximum possible value. All these measures were studied in an extensive simulation study, whose conclusion was that all of them depend in some way on the outcome prevalence. Although some measures may be preferred in some situations, none outperforms the others in every situation, and none can be considered independent from the outcome prevalence. Assessing intracluster correlation independently from the outcome prevalence remains an open eld of research.
Which place for shared decision making in the context of kidney transplantation? A mixed-methods research exploring patient experience.
Although kidney transplantation provides a significant benefit over dialysis, question regarding the eligibility for transplantation, the impact of replacement treatment on their lives, make the mode of renal replacement therapy a difficult decision. Therefore, Health Authority suggests shared decision-making to help patients make timely treatment modality decision. Little is known about how patient perceive their participation in the shared decision-making process. This research aims to explore the experience of patients and the factors that influence them indecision-making situations, as well as to evaluate the impact of this experience on their future. This research is based on a mixed methods research (QUANTI > quali).
It combines an interpretive phenomenological analysis and an observational study design to measure decisional conflict perceived by patients on the waiting list and to explore the factors that influence decision regret, quality of life and adherence among transplant recipients. This study reports that the experience of waiting list was identified as a necessary step in their pathway. They experienced as an implicit decision that shapes patients' attitudes towards other decisions and influences their ability to cope with the uncertainty of living with chronic kidney disease. The challenge of considering all stages of shared medical decision-making is major in the context of kidney transplantation to support patient participation decision.
Assessing the evolution of patient experience before and after kidney transplantation : exploring measurement invariance
End-Stage Renal Disease (ESRD) requires renal replacement therapies: dialysis or kidney transplantation.
Today, it is well-known that ESRD treatments impact the quality of life (QoL) of patients. Patients may perceive and interpret questionnaires differently over time: this phenomenon is called response shift (RS). Thus, observed changes in QoL may reflect not only a real change in QoL, but also a different perception of the questionnaires by patients over time (RS). The questionnaire’ perception and RS may also differ between patients who have experienced dialysis or not (preemptive).
The first objective of this dissertation was to evaluate and compare changes in QoL for preemptive and dialysis patients on the waiting list for kidney transplantation. The second objective was detecting and taking into account RS (before and after kidney transplantation) and measurement non-invariance between groups (dialysis and preemptive patients). To meet these objectives, several works have been realized. Thus, we have identified that QoL of dialyzed patients was generally lower than that of preemptive patients during the waiting list period.
Plus, RS has been detected, and we have observed that QoL level of patients adjusted on RS, tended to increase after kidney transplantation. Adaptation of specific therapeutic education programs for patients who have experienced dialysis or not would improve QoL of patients.