Interest in the use of medical cannabis for the treatment of drug-resistant epilepsy in children has grown over the last decade; however, little is known about its potential benefits and harms, cost-effectiveness, or the perspectives of key stakeholders. In this thesis, a health technology assessment approach was adopted to assess the intended and unintended consequences of medical cannabis use in the treatment of pediatric drug-resistant epilepsy. This thesis comprises three main sections: (1) a living systematic review of the benefits and harms of medical cannabis for the treatment of pediatric epilepsy, including drug-resistant forms; (2) an economic evaluation of the cost-effectiveness of medical cannabis for the treatment of pediatric drug-resistant epilepsy, and (3) qualitative exploration of the perspectives of neurologists and parents of children with drug-resistant epilepsy about the use of medical cannabis in this population. While neurologists generally perceived medical cannabis as a viable treatment option for drug-resistant epilepsy in children, particularly after other treatments have failed, they identified several gaps in the evidence base, including a lack of long-term studies and a lack of evidence related to cannabinoids other than cannabidiol. This is in keeping with the findings of the living systematic review, which support a beneficial role for medical cannabis in reducing seizures associated with drug-resistant epilepsy, although the certainty of the evidence was moderate at best. Parents described experiencing many barriers to accessing medical cannabis for their children, primarily related to finding a health care provider to authorize its use, the high cost of cannabis-based treatments, and a lack of reimbursement through public or private insurance programs. However, cannabinoid oil may be a more cost-effective treatment for some types of pediatric drug-resistant epilepsy compared with antiepileptic drugs currently reimbursed by some provincial insurance programs. These findings suggest that medical cannabis is a potentially effective and cost-effective treatment for drug-resistant epilepsy that may addresses an unmet need. However, additional studies are needed to address uncertainty related to the long-term benefits and harms of cannabis-based products, particularly with respect to products available in Canada.

Les revues systématiques sont des outils indispensables à la synthèse des connaissances en évaluation thérapeutique. Il est désormais fréquent que plusieurs traitements soient disponibles pour une même indication. L’objectif des patients et des cliniciens est alors de savoir quels sont, parmi l’ensemble des traitements disponibles, le(s) meilleur(s). Compte tenu de la nécessité de synthétiser les données disponibles pour tous les traitements et de maintenir cette synthèse à jour, notre objectif était d’évaluer les limites du système actuel de synthèse et de développer une méthodologie alternative. Nous avons d’abord évalué la capacité des revues systématiques à prendre en compte l’ensemble des preuves disponibles sur l’effet des multiples traitements. Nous avons utilisé l’exemple des traitements de deuxième ligne du cancer bronchique non à petites cellules métastatique non muté pour EGFR ou de statut inconnu. Nous avons montré que les 29 revues systématiques publiées jusque 2015 sur cette question, considérées collectivement, fournissaient une synthèse fragmentée et non à jour de la preuve disponible. Au moins 40% des 77 essais, des 45 traitements, des 54 comparaisons de traitements et des 28 636 patients n’étaient constamment pas pris en compte dans les revues systématiques. Nous avons discuté les raisons pour lesquelles le système de synthèse des données actuel ne permettait pas de couvrir l’ensemble des données disponibles. Nous avons ensuite développé une nouvelle forme de synthèse de la preuve disponible au cours du temps, la méta-analyse en réseau cumulative et dynamique. Elle consiste à passer d’une série de méta-analyses à une méta-analyse en réseau unique, incluant l’ensemble des traitements disponibles pour une indication donnée, avec une mise à jour du réseau d’essais et de la synthèse des données dès que les résultats d’un nouvel essai deviennent disponibles. Elle débute par une méta-analyse en réseau initiale suivie d’une succession de mises à jour répétées à intervalles réguliers. Nous avons décrit les étapes méthodologiques, et développé le protocole d’une étude de preuve de concept, appliquée aux traitements de deuxième ligne du cancer bronchique non à petites cellules. Enfin, nous avons réalisé la méta-analyse en réseau initiale sur ce même exemple. Nous avons inclus 98 essais randomisés évaluant 60 traitements chez 34 179 patients. Nous avons montré que les traitements par immunothérapie (nivolumab et pembrolizumab) avaient un effet sur la survie globale supérieur aux chimiothérapies et thérapeutiques ciblées actuellement recommandées (nivolumab versus docetaxel HR=0,68 (IC95% 0,55-0,83) ; versus pemetrexed HR=0,65 (0,5-0,83) ; versus erlotinib HR=0,66 (0,51-0,84) and versus gefitinib HR=0,65 (0,51-0,82)). Les résultats étaient similaires pour le pembrolizumab. Pour la survie sans progression, le nivolumab avait aussi un effet supérieur aux quatre traitements recommandés. La méta-analyse en réseau cumulative et dynamique pourrait devenir l’outil permettant de changer de paradigme dans la synthèse des connaissances afin d’améliorer la prise de décision médicale. / Systematic reviews are essential tools to synthesize available evidence for therapeutic evaluation. Multiple treatments are now frequently available for a given condition. Patients and physicians want to know which one is the best among all treatments. Thus we need to retrieve and synthesize all available evidence across all treatments and furthermore to maintain it updated when new evidence and new treatments become available. Our objective was to evaluate the limits of the current ecosystem of evidence synthesis and to develop an alternative methodology. We have first assessed the capacity of systematic reviews to cover all available evidence of multiple treatments. We took the example of second-line treatments of advanced non-small cell lung cancer with EGFR wild-type or unknown status. We have shown that the 29 systematic reviews published in this condition up to 2015, considered collectively, failed to provide a complete and updated synthesis of all available evidence. Almost 40% of the 77 trials, of the 45 treatments, of the 54 treatment comparisons and of the 28,636 patients were always missing from systematic reviews. We have discussed the reasons why the ecosystem of evidence synthesis fails to encompass all available evidence. We then developed a new paradigm to synthesize evidence over time called live cumulative network meta-analysis. This new concept consists in switching from a series of standard meta-analyses to a single network meta-analysis covering all treatments and systematically updated as soon as the results of a new trial become available. Live cumulative network meta-analysis is initiated with a network meta-analysis which is iteratively updated. We have described the methodological steps, developed the protocol of a proof-of-concept study applied to second-line treatments of advanced non-small cell lung cancer. Finally, we have performed the initial network meta-analysis in this condition. We have included 98 trials including 34,179 patients and assessing 60 treatments. We have shown that nivolumab was more effective in term of overall survival compared to docetaxel HR=0.68 (IC95% 0.55-0.83), to pemetrexed HR=0.65 (0.5-0.83), to erlotinib HR=0.66 (0.51-0.84) and to gefitinib HR=0.65 (0.51-0.82). Similar results were found with pembrolizumab. In progression free survival, nivolumab had a more important treatment effect compared to the four recommended treatments. Live cumulative network meta-analysis should become a paradigmatic shift for systematic reviews and meta-analysis in order to improve medical decision making.

Background: Since its emergence in December 2019, SARS-CoV-2, the coronavirus responsible for COVID-19, has spread across the globe, infected millions of people and caused several million deaths. One promising intervention to combat the ongoing COVID-19 pandemic is mesenchymal stem/stromal cells (MSCs). Many trials were registered at the onset of the pandemic to determine the safety and efficacy of MSCs in COVID-19 patients. However, currently published studies are underpowered to provide an estimate of safety and efficacy on their own. Thus, a living systematic review (SR) is needed to establish the benefits and drawbacks of MSCs for COVID-19 on a relevant timescale. Methods: Systematic literature searches were conducted on Feb 3rd, 2021 and November 15th, 2021 to identify all English-language, full-text, clinical studies examining MSCs to treat COVID-19. (PROSPERO:CRD42021225431). Findings/Conclusions: Our first search identified nine studies (4 controlled) examining the use of MSC derived products to treat COVID-19 patients. This first iteration of our SR revealed that MSCs were safe and reduced mortality in patients suffering from COVID-19. However, risk of bias (RoB) and poor adherence to ISCT cell product characterization guidelines limited the strength of our conclusions. In the second iteration of our living SR, we only included controlled studies to strengthen our conclusions. We identified eleven controlled studies (5 RCTs). MSCs continued to demonstrate safety and efficacy at reducing mortality at study endpoint (RR: 0.50 [0.34 to 0.75, 95% CI, p=0.0006, I2=0%]). However, we continued to encounter barriers which prevented us from drawing more definitive conclusions. A master protocol appears necessary to facilitate the accelerated accumulation of high-quality evidence where standardized outcome reporting and consistent product characterization allow for a more definitive and timely estimate regarding the safety and efficacy of this cell-based therapy for COVID-19.

Background: The coronavirus disease 2019 (COVID-19) presents diagnostic evaluation and patient management challenges, including uncertainty regarding the role of imaging tests. This series of reviews from the suite of Cochrane ‘living systematic reviews’ aims to evaluate the accuracy of chest imaging (computed tomography (CT), X-ray and ultrasound) for diagnosis and management of individuals with suspected COVID-19. Methods: The Bern COVID-19 Living Database, Cochrane COVID-19 Register, and CDC Library were searched through 30 September 2020 (for review version 3) and 17 February 2021 (for review version 4). Diagnostic accuracy studies involving participants with suspected COVID-19 were included. Screening, data extraction, and risk of bias assessments (using the QUADAS-2 tool) were completed independently, in duplicate. Pooled accuracy estimates and 95% confidence intervals (CIs) were determined using a bivariate random effects model. Results: In the third version of the review, chest CT (41 studies, 16133 participants, 8110 (50%) cases) had a pooled sensitivity of 87.9% (95%CI 84.6-90.6) and specificity of 80.0% (74.9-84.3). Chest X-ray (9 studies, 3694 participants, 2111 (57%) cases) had a pooled sensitivity of 80.6% (69.1-88.6) and specificity of 71.5% (59.8-80.8). Ultrasound of the lungs (5 studies, 446 participants, 211 (47%) cases) had a pooled sensitivity of 86.4% (72.7-93.9) and specificity of 54.6% (35.3-72.6). Indirect comparisons showed that chest CT gave higher specificity (P=0.0052) and similar sensitivity (P=0.77) compared to ultrasound. There were no differences (P≥0.05) in accuracy between CT and X‐ray, or X‐ray and ultrasound. In the fourth version of the review, chest CT (69 studies, 28285 participants, 14342 (51%) cases) had a pooled sensitivity of 86.9% (83.6-89.6) and specificity of 78.3% (73.7-82.3). Chest X‐ray (17 studies, 8530 participants, 5303 (62%) cases) had a pooled of sensitivity=73.1% (64.1-80.5) and specificity of 73.3% (61.9-82.2). Ultrasound of the lungs (15 studies, 2410 participants, 1158 (48%) cases) had a pooled sensitivity of 88.9% (84.9-92.0) and specificity of 72.2% (58.8-82.5). Indirect comparisons showed that chest CT and ultrasound had similar sensitivities (P=0.42), and each gave higher sensitivities than X-ray (P=0.0003 and P=0.001, respectively). All modalities had similar specificities (P≥0.05). Conclusion: The most recent evidence indicates that both chest CT and ultrasound of the lungs are sensitive and moderately specific for diagnosing individuals with suspected COVID-19, while chest X-ray is moderately sensitive and moderately specific. Chest CT and ultrasound may be useful for ruling out COVID‐19, but not for distinguishing COVID-19 from other illnesses. Research assessing the prognostic value of imaging for predicting morbidity and mortality in individuals with COVID-19 is underway and will also be published in the suite of Cochrane ‘living' systematic reviews.