A sequential Cox approach for estimating the causal effect of treatment in the presence of time-dependent confounding applied to data from the Swiss HIV Cohort Study

When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

Falsely high ankle-brachial index predicts major amputation in critical limb ischemia

Falsely high ankle-brachial index (ABI) values are associated with an adverse clinical outcome in diabetes mellitus. The aim of the present study was to verify whether such an association also exists in patients with chronic critical limb ischemia (CLI) with and without diabetes. A total of 229 patients (74 +/- 11 years, 136 males, 244 limbs with CLI) were followed for 262 +/- 136 days. Incompressibility of lower limb arteries (ABI > 1.3) was found in 45 patients, and was associated with diabetes mellitus (p = 0.01) and renal insufficiency (p = 0.035). Limbs with incompressible ankle arteries had a higher rate of major amputation (p = 0.002 by log-rank). This association was confirmed by multivariate Cox regression analysis (relative risk [RR] 2.67; 95% CI 1.27-5.64, p = 0.01). The relationship between ABI > 1.3 and amputation rate persisted after subjects with diabetes and renal insufficiency had been removed from the analysis (RR 3.85; 95% CI 1.25-11.79, p = 0.018). Dividing limbs with measurable ankle pressure according to tertiles of ABI, the group in the second tertile (0.323 < or = ABI < or = 0.469) had the lowest amputation rate (4/64, 6.2%), and a U-shaped association between the occurrence of major amputation and ABI was evident. No association was found between ABI and mortality. In conclusion, this study demonstrates that falsely high ABI is an independent predictor of major amputation in patients with CLI.