No abstract

A surrogate endpoint can be used instead of the most relevant clinical endpoint to assess the efficiency of a new treatment. Before being used, a surrogate endpoint must be validated based on appropriate methods. Numerous validation approaches have been proposed with the most popular used in a context of meta‐analysis, based on a two‐step analysis strategy. For two failure‐time endpoints, two association measurements are usually used, Kendall's τ at the individual level and the adjusted coefficient of determination ( ) at the trial level. However, is not always available due to model estimation constraints. We propose a one‐step validation approach based on a joint frailty model, including both individual‐level and trial‐level random effects. Parameters have been estimated using a semiparametric penalized marginal log‐likelihood method, and various numerical integration approaches were considered. Both individual‐ and trial‐level surrogacy were evaluated using a new definition of Kendall's τ and the coefficient of determination. Estimators' performances were evaluated using simulation studies and satisfactory results were found. The model was applied to individual patient data meta‐analyses in gastric cancer to assess disease‐free survival as a surrogate for overall survival, as part of the evaluation of adjuvant therapy.

Canine rabies is endemic in Cameroon, but human rabies exposures and cases are likely underreported because of inadequate surveillance. In 2014, the surveillance network in the West region of Cameroon was reinforced by introducing a new anti-rabies center, a framework for data collection and evaluation, provisions for sample collecting and laboratory confirmation, and training for health professionals. The objective of this observational cohort study was to describe the incidence and characteristics of reported exposures and human and animal rabies cases following this reinforcement of the existing rabies surveillance system. The surveillance network consisted of local, regional, and national health and veterinary authorities in 11 of the 20 West region districts, and was completely integrated within the existing national rabies surveillance network. Animal exposures and suspected rabies exposures, the suspected rabid animals involved, and laboratory confirmation of human and animal rabies cases were recorded in a centralized information database. Between January 2014 and June 2016, the network recorded 1340 animal exposure cases for an overall incidence rate of 38.2 animal exposures per 100,000 people, four confirmed rabies-positive animals, and one confirmed human rabies case out of four clinically suspected cases. In contrast, 62 animal exposures and an overall incidence rate of 6.1 exposures per 100,000 people were reported for the West region districts not participating in the reinforced surveillance. Of the 925 animal exposure victims for whom a detailed case report form was completed, 703 were considered to be at risk of rabies and only 428 (61%) of these received any post-exposure prophylaxis in the form of rabies vaccine. Obstacles encountered within the network included low rates of animal sample submission and animal follow-up by veterinarians. Reinforced rabies surveillance in the West region of Cameroon has provided the most accurate estimate of the region’s disease and exposure burdens to date, and indicates that animal exposures are substantially underreported. The reinforced network also signaled that greater access to post-exposure prophylaxis is needed. Integration of regions not covered by the surveillance network and efforts to improve engagement of veterinary services will be needed to reveal the true burden of rabies in Cameroon.

In a meta‐analysis framework, the classical approach for the validation of time‐to‐event surrogate endpoint is based on a two‐step analysis. This approach often raises estimation issues. Recently, we proposed a one‐step validation approach based on a joint frailty model. This approach was quite time consuming, despite parallel computing, due to individual‐level frailties used to take into account heterogeneity in the data at the individual level. We now propose an alternative one‐step approach for evaluating surrogacy, using a joint frailty‐copula model. The model includes two correlated random effects treatment‐by‐trial interaction and a shared random effect associated with the baseline risks. At the individual level, the joint survivor functions of time‐to‐event endpoints are linked using copula functions. We used splines for the baseline hazard functions. We estimated parameters and hazard function using a semiparametric penalized marginal likelihood method, considering various numerical integration methods. Both individual‐level and trial‐level surrogacy were evaluated using Kendall's tau and coefficient of determination. The performance of the estimators was evaluated using simulation studies. The model was applied to individual patient data meta‐analyses in advanced ovarian cancer to assess progression‐free survival as a surrogate for overall survival, as part of the evaluation of new therapy. The model showed good performance and was quite robust regarding the integration methods and data variation, regardless of the surrogacy evaluation criteria. Kendall's Tau was better estimated using the Clayton copula model compared to the joint frailty model. The proposed model reduces the convergence and model estimation issues encountered in the two‐step approach.