Modeling the causal effect of treatment initiation time on survival: Application to HIV/TB co-infection

The timing of antiretroviral therapy (ART) initiation for HIV and tuberculosis (TB) co-infected patients needs to be considered carefully. CD4 cell count can be used to guide decision making about when to initiate ART. Evidence from recent randomized trials and observational studies generally supports early initiation but does not provide information about effects of initiation time on a continuous scale. In this article, we develop and apply a highly flexible structural proportional hazards model for characterizing the effect of treatment initiation time on a survival distribution. The model can be fitted using a weighted partial likelihood score function. Construction of both the score function and the weights must accommodate censoring of the treatment initiation time, the outcome, or both. The methods are applied to data on 4903 individuals with HIV/TB co-infection, derived from electronic health records in a large HIV care program in Kenya. We use a model formulation that flexibly captures the joint effects of ART initiation time and ART duration using natural cubic splines. The model is used to generate survival curves corresponding to specific treatment initiation times; and to identify optimal times for ART initiation for subgroups defined by CD4 count at time of TB diagnosis. Our findings potentially provide 'higher resolution' information about the relationship between ART timing and mortality, and about the differential effect of ART timing within CD4 subgroups.

Marginal structural model to evaluate the joint effect of socioeconomic exposures on the risk of developing end-stage renal disease in patients with type 1 diabetes: a longitudinal study based on data from the Swedish Childhood Diabetes Study Group

PURPOSE

Diabetic nephropathy is a severe complication of type 1 diabetes (T1D) that may lead to renal failure and end-stage renal disease (ESRD) demanding dialysis and transplantation. The etiology of diabetic nephropathy is multifactorial and both genes and environmental and life style-related factors are involved. In this study, we investigate the effect of the socioeconomic exposures, unemployment and receiving income support, on the development of ESRD in T1D patients, using a marginal structural model (MSM) in comparison with standard logistic regression models.

METHODS

The study is based on the Swedish Childhood Diabetes Register which in 1977 started to register patients developing T1D before 15 years of age. In the analyses, we include patients born between 1965 and 1979, developing diabetes between 1977 and 1994, and followed until 2013 (n = 4034). A MSM was fitted to adjust for both baseline and time-varying confounders.

RESULTS

The main results of the analysis indicate that being unemployed for more than 1 year and receiving income support are risk factors for the development of ESRD. Multiple exposures over time to these risk factors increase the risk associated with the disease.

CONCLUSIONS

Using a MSM is an advanced method well suited to investigate the effect of exposures on the risk of complications of a chronic disease with longitudinal data. The results show that socioeconomic disadvantage increases the risk of developing ESRD in patients with T1D.