Estimates of individualized treatment effects from combination therapies in observational studies

La réalisation d'un essai thérapeutique randomisé peut être difficile à mettre en place pour estimer sans biais l'effet causal d'une stratégie thérapeutique. Dans ce cas, l’étude observationnelle constitue une alternative pour évaluer l’effet causal d’un traitement. Quatre types de difficultés méthodologiques nous intéressent dans ce type d’étude : 1) le biais d’indication ; 2) La présence des facteurs de confusion temps-dépendantes (TD) ; 3) la relation variant dans le temps entre un traitement TD et un effet ; 4) dans la vie réelle, les patients prennent parfois plusieurs traitements, de façon séquentielle ou simultanée. Dans ces conditions, l’évaluation de l’effet propre à chaque traitement constitue un défi méthodologique. L’objectif de cette thèse est de proposer un cadre méthodologique qui permet d’estimer correctement les effets propres aux traitements dans un contexte de multithérapie dans une étude observationnelle en tenant compte de ces difficultés méthodologiques. Nous avons évalué la performance du modèle marginal structurel de Cox pour estimer les effets individuels et conjoints de deux traitements et démontré qu'il a des bonnes performances en présence des facteurs de confusion TD et d'une interaction entre les deux traitements. Nous avons également comparé la performance du modèle marginal structurel de Cox à exposition cumulée pondérée à celle du modèle de Cox à exposition cumulée pondérée standard pour estimer les effets variant dans le temps en présence de confusion temps dépendante et démontré qu'il a une meilleure performance et qu'il peut être appliqué aux données réelles quelque soit la force de confusion temps dépendante.Randomized controlled trials cannot be implemented in all situations for estimating effects of therapeutic strategies. Observational studies would then constitute an alternative for evaluating treatment effects. We have a specified interest in four types of methodological difficulties for such studies: 1) confounding by indication ; 2) presence of time-dependent confounding ; 3) The relationship between a given time-dependent treatment and its effect may vary over time ; 4) In real life, patients often receive multiple treatments, sequentially or simultaneously. In this context, the evaluation of individual effects of treatment is a methodological challenge. The overall objective of this thesis was to propose a methodological framework in which these methodological difficulties are accommodated, allowing the individual effects of treatments to be correctly estimated within the context of multi-treatments in an observational study. We evaluated the performance of the marginal structural Cox model when estimating the individual and joint effects of two treatments and showed that it performed well in the presence of three different scenarios of time-dependent confounding. We also showed the importance of estimating the interaction term when exploring the treatment effect from combination therapy. We compared the performance of weighted cumulative exposure marginal structural Cox model with that of a conventional TD WCE Cox model for estimating time-varying effects of treatments without bias in the presence of TD confounding. Our results showed that the WCE Cox MSM performed better and can be applied to real data whatever the strength of time dependent confounding

Letter: tenofovir may be superior to entecavir for treatment-naïve chronic hepatitis B patients-authors' reply.

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Performance of the marginal structural cox model for estimating individual and joined effects of treatments given in combination

International audienceBACKGROUND:The Marginal Structural Cox Model (Cox-MSM), an alternative approach to handle time-dependent confounder, was introduced for survival analysis and applied to estimate the joint causal effect of two time-dependent nonrandomized treatments on survival among HIV-positive subjects. Nevertheless, Cox-MSM performance in the case of multiple treatments has not been fully explored under different degree of time-dependent confounding for treatments or in case of interaction between treatments. We aimed to evaluate and compare the performance of the marginal structural Cox model (Cox-MSM) to the standard Cox model in estimating the treatment effect in the case of multiple treatments under different scenarios of time-dependent confounding and when an interaction between treatment effects is present.METHODS:We specified a Cox-MSM with two treatments including an interaction term for situations where an adverse event might be caused by two treatments taken simultaneously but not by each treatment taken alone. We simulated longitudinal data with two treatments and a time-dependent confounder affected by one or the two treatments. To fit the Cox-MSM, we used the inverse probability weighting method. We illustrated the method to evaluate the specific effect of protease inhibitors combined (or not) to other antiretroviral medications on the anal cancer risk in HIV-infected individuals, with CD4 cell count as time-dependent confounder.RESULTS:Overall, Cox-MSM performed better than the standard Cox model. Furthermore, we showed that estimates were unbiased when an interaction term was included in the model.CONCLUSION:Cox-MSM may be used for accurately estimating causal individual and joined treatment effects from a combination therapy in presence of time-dependent confounding provided that an interaction term is estimated

The Dynamic Effect of Direct-acting Antiviral Treatments on the Risk of Hepatocellular Carcinoma in Patients with Cirrhosis and Chronic Hepatitis C

International audienceThere is still some controversy over a potentially increased short-term risk of developing hepatocellular carcinoma (HCC) after the initiation of direct-acting antiviral (DAA) therapy, even though a decreased long-term risk of HCC has been reported following a sustained virological response in patients with chronic hepatitis C virus (HCV) infection. We characterized the time-varying effect of DAAs on the risk of the occurrence of HCC in patients with cirrhosis and HCV infection. We analysed patients with cirrhosis and chronic HCV infection from the ANRS CO22 HEPATHER cohort study. We excluded patients with active HBV coinfection, liver transplantation or a past history of HCC. We used a flexible weighted effect cumulative exposure Cox model to characterize the time-varying effect of DAAs on the risk of HCC. A total of 3595 patients, mean age 59.3 years old, 65% men, were eligible for the study. Median follow-up was 36.8 months (IQR 24.6-47.1). DAAs were started during follow-up in 3292 patients. Three hundred and fifty-six HCCs were reported (275 treated, 81 untreated). Overall, a constant decrease in the risk of occurrence of HCC (vs untreated) was found from the start of treatment. Results were similar in patients without a history of decompensated cirrhosis (DC). Analysis of patients with a past history of DC showed a nonsignificant increase in the occurrence of HCC over the first 6 months, while the HR was significantly decreased at 14 months. These findings support the urgent initiation of DAAs in all patients

The Dynamic Effect of Direct-acting Antiviral Treatments on the Risk of Hepatocellular Carcinoma in Patients with Cirrhosis and Chronic Hepatitis C

International audienceThere is still some controversy over a potentially increased short-term risk of developing hepatocellular carcinoma (HCC) after the initiation of direct-acting antiviral (DAA) therapy, even though a decreased long-term risk of HCC has been reported following a sustained virological response in patients with chronic hepatitis C virus (HCV) infection. We characterized the time-varying effect of DAAs on the risk of the occurrence of HCC in patients with cirrhosis and HCV infection. We analysed patients with cirrhosis and chronic HCV infection from the ANRS CO22 HEPATHER cohort study. We excluded patients with active HBV coinfection, liver transplantation or a past history of HCC. We used a flexible weighted effect cumulative exposure Cox model to characterize the time-varying effect of DAAs on the risk of HCC. A total of 3595 patients, mean age 59.3 years old, 65% men, were eligible for the study. Median follow-up was 36.8 months (IQR 24.6-47.1). DAAs were started during follow-up in 3292 patients. Three hundred and fifty-six HCCs were reported (275 treated, 81 untreated). Overall, a constant decrease in the risk of occurrence of HCC (vs untreated) was found from the start of treatment. Results were similar in patients without a history of decompensated cirrhosis (DC). Analysis of patients with a past history of DC showed a nonsignificant increase in the occurrence of HCC over the first 6 months, while the HR was significantly decreased at 14 months. These findings support the urgent initiation of DAAs in all patients

The Dynamic Effect of Direct-acting Antiviral Treatments on the Risk of Hepatocellular Carcinoma in Patients with Cirrhosis and Chronic Hepatitis C

International audienceThere is still some controversy over a potentially increased short-term risk of developing hepatocellular carcinoma (HCC) after the initiation of direct-acting antiviral (DAA) therapy, even though a decreased long-term risk of HCC has been reported following a sustained virological response in patients with chronic hepatitis C virus (HCV) infection. We characterized the time-varying effect of DAAs on the risk of the occurrence of HCC in patients with cirrhosis and HCV infection. We analysed patients with cirrhosis and chronic HCV infection from the ANRS CO22 HEPATHER cohort study. We excluded patients with active HBV coinfection, liver transplantation or a past history of HCC. We used a flexible weighted effect cumulative exposure Cox model to characterize the time-varying effect of DAAs on the risk of HCC. A total of 3595 patients, mean age 59.3 years old, 65% men, were eligible for the study. Median follow-up was 36.8 months (IQR 24.6-47.1). DAAs were started during follow-up in 3292 patients. Three hundred and fifty-six HCCs were reported (275 treated, 81 untreated). Overall, a constant decrease in the risk of occurrence of HCC (vs untreated) was found from the start of treatment. Results were similar in patients without a history of decompensated cirrhosis (DC). Analysis of patients with a past history of DC showed a nonsignificant increase in the occurrence of HCC over the first 6 months, while the HR was significantly decreased at 14 months. These findings support the urgent initiation of DAAs in all patients

Additional file 3: Tables S2. of Performance of the marginal structural cox model for estimating individual and joined effects of treatments given in combination

Multivariate parameter estimates for covariate association with the risk of anal cancer in HIV-infected persons: comparison of weighted Cox MSM and standard time dependent Cox models. (DOCX 22 kb

Performance of Algorithms for Identifying Patients With Chronic Hepatitis B or C Infection in the French Health Insurance Claims Databases Using the ANRS CO22 HEPATHER Cohort

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Performance of Algorithms for Identifying Patients With Chronic Hepatitis B or C Infection in the French Health Insurance Claims Databases Using the ANRS CO22 HEPATHER Cohort

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Outcome of very high-risk patients treated by Sotrovimab for mild-to-moderate COVID-19 Omicron, a prospective cohort study (the ANRS 0003S COCOPREV study)

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