Les études de pharmacoépidémiologie consistent à étudier l’effet de médicaments en vie réelle, et sont menées de plus en plus souvent sur bases de données médico-administratives. Ce sont principalement des études observationnelles, et sont donc soumises à des biais liés à des facteurs de confusion. Ces facteurs ne sont pas toujours recueillis dans les bases de données médico-administratives qui sont implémentées à d’autres fins que la recherche. Des plans expérimentaux self-controlled designs (où le patient est son propre témoin, et dont les principaux sont le case-crossover et le self-controlled case-series) permettent d’étudier l’effet transitoire d'expositions brèves sur des évènements à début brutal. Ils sont soumis à certaines conditions d’application. Ils ont la particularité de réaliser des comparaisons sur différentes périodes plutôt que sur différents groupes de patients, permettant ainsi de prendre en compte des facteurs de confusion, y compris non mesurés, et qui ne varient pas entre les périodes observées. Ces méthodes ont montré leur utilité pour pallier l’absence de randomisation, et leur utilisation est recommandée quand leurs conditions d’application sont remplies. Nous avons étudié la fréquence d’utilisation des self-controlled designs en pharmacoépidémiologie sur bases de données, les opportunités manquées d’utilisation et leur usage approprié au regard de leurs conditions d’application, ainsi que la qualité de l’information rapportée dans les articles. Nous avons montré que leur utilisation est rare, que 15% des articles correspondent à des situations d’opportunité où ces méthodes auraient pu être implémentées, que 34% des case-crossover et 13% des self-controlled case-series étaient appliqué de façon inapproprié, et que pour 16% des articles la méthode aurait pu être adaptée pour être valide. Un usage plus approprié permettrait de contribuer à l’investigation en pharmacoépidémiologie tout en bénéficiant des avantages de ces méthodes en particulier sur bases de données de santé. / Pharmacoepidemiology consists in the study of efficacy or safety of drugs in real life, with the use more and more frequently of medico-administrative databases. Study designs are generally observational, thus they are prone to confounding bias. Confounders are not systematically collected in databases, which are implemented for other purposes than research. Self-controlled designs (mainly represented by case-crossover and self-controlled case-series, and in which the patient acts as his own control), have been developed for the study of intermittent exposure with short-term effect on abrupt onset event. They require that validity assumptions being fulfilled. They consist in the comparison over different periods, rather than different groups of patients, thus allowing for confounding factors, also if not measured, which are invariant over observed periods. Such designs have been proved useful in observational studies in the absence of randomization, and their implementation is recommended in case of validity assumptions are fulfilled. We studied their frequency of use in pharmacoepidemiology in healthcare databases, missed opportunities for use, inappropriate use with respect to validity assumptions, as well as quality of reporting. We showed that self-controlled designs are rarely used, that opportunity for use was founds in 15% of articles where such methods could have been implemented, that 34% of case-crossover and 13% of self-controlled case series were inappropriately used, and that the method could have been adapted to be valid in 16% of articles. A more appropriate use of self-controlled designs could contribute to improve investigation in pharmacoepidemiology, while beneficiating from their advantages, especially in healthcare databases.

Objectives: This thesis included 6 manuscripts which focused on the analysis of adverse events following immunization (AEFIs), including general health services utilization (emergency room (ER) visits and hospital admissions) and specific diagnoses (e.g. febrile convulsions). The main objectives of this research were: 1) To demonstrate the utility of the self-controlled case series (SCCS) design coupled with health administrative data for studying the safety of vaccines; 2) Introducing an innovative approach using relative incidence ratios (RIRs) within an SCCS analysis to identify risk factors for AEFIs and to overcome the healthy vaccinee bias; and 3) To demonstrate how SCCS and RIR analyses of health services outcomes in health administrative data can provide important insights into underlying physiological and behavioural mechanisms. Data Sources: This work utilized Ontario health administrative data housed at the Institute for Clinical Evaluative Sciences (ICES). The study included all children born in Ontario, Canada between 2002 and 2011 (over 1 million children). Vaccinations were identified using OHIP fee for service billing codes for general vaccination. Admissions and ER visits for any reason were identified in the Discharge Abstract Database (DAD) and National Ambulatory Care Reporting System (NACRS). Primary reasons for admissions and ER visits were investigated using ICD-10-CA codes reported in the DAD and NACRS databases. Statistical Methods: The self-controlled case series design (SCCS) was used to calculate the relative incidence of admissions, ER visits and other AEFIs. To investigate relative incidence for AEFIs across risk groups of interest, as well as addressing the healthy vaccinee effect bias, RIRs were calculated. RIRs are the ratio of incidence ratios in a subgroup of interest relative to a designated reference group. Results and Conclusions: The combined approach of using the SCCS design and RIRs to identify risk factors and overcome the healthy vaccinee bias proved to be a powerful approach to studying vaccine safety. Future work will be important to characterize the performance and validity of the SCCS + RIR approach in the presence of increasing levels of confounding and differing manifestations of the healthy vaccinee bias, as well as to elucidate the biological and behavioural mechanisms underlying our findings.

Introduction: In 2007 Ontario implemented a grade 8 quadrivalent human papillomavirus (qHPV) vaccination program targeting the virus that causes cervical cancer. Despite being 6 years post-implementation, few post-licensure studies have assessed the safety of the qHPV vaccine in this adolescent population. Since autoimmune disorders are often targeted for post-marketing surveillance by regulatory agencies, it is important to assess the risk of developing an autoimmune disorder post-qHPV vaccination. Objectives: The objectives of this thesis were to assess the risk for developing an autoimmune disorder following qHPV vaccination, assess for effect modification by the presence of predisposing risk factors, identify the period of highest risk and explore the risk for individual autoimmune disorders. Methods: A population-based retrospective cohort of girls eligible for Ontario’s qHPV vaccination program was identified using population-based databases. The risk of autoimmune disorders following qHPV vaccination was ascertained using the self-controlled case series method. Results: The risk of developing a new autoimmune disorder, adjusted for age, seasonality, concurrent vaccines and infections was 1.28 (95% CI: 0.87 – 1.89), and this association was independent of a history of immune-mediated disorders (p=0.39). The risk was not increased during days 7-24 post-vaccination (adjusted RR = 0.87, 95% CI: 0.43 – 1.74), but appeared to increase thereafter (adjusted RR = 1.36, 95% CI: 0.77 – 2.41 and RR = 1.62, 95% CI 0.94 – 2.78 respectively, for days 25 – 42 and days 43 – 60), although these differences were non-significant. The risk may be increased for certain disorders including Bell’s palsy (RR = 2.30, 95% CI: 0.67 – 7.95), systemic autoimmune rheumatic disorders (RR = 1.84, 95% CI: 0.42 – 8.02), Hashimoto’s disease (RR = 1.39, 95% CI: 0.46 – 4.22), and juvenile rheumatoid arthritis (RR = 1.31, 95% CI: 0.83 – 2.08), although none of these associations were statistically significant. Conclusion: This thesis demonstrated that no statistically significant increased risk for autoimmune disorders following qHPV vaccination was detected. However, there remains some uncertainty about the safety of the qHPV vaccine for a subset of the autoimmune disorders. The results from this analysis need to be pooled with those of other studies to confirm whether these are true safety signals. / Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2014-04-23 22:30:41.428

京都大学 / 0048 / 新制・論文博士 / 博士(医学) / 乙第13376号 / 論医博第2210号 / 新制||医||1047(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 森田 智視, 教授 川上 浩司, 教授 佐藤 俊哉 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM