How to perform prespecified subgroup analyses when using propensity score methods in the case of imbalanced subgroups.

BACKGROUND: Looking for treatment-by-subset interaction on a right-censored outcome based on observational data using propensity-score (PS) modeling is of interest. However, there are still issues regarding its implementation, notably when the subsets are very imbalanced in terms of prognostic features and treatment prevalence. METHODS: We conducted a simulation study to compare two main PS estimation strategies, performed either once on the whole sample ("across subset") or in each subset separately ("within subsets"). Several PS models and estimands are also investigated. We then illustrated those approaches on the motivating example, namely, evaluating the benefits of facial nerve resection in patients with parotid cancer in contact with the nerve, according to pretreatment facial palsy. RESULTS: Our simulation study demonstrated that both strategies provide close results in terms of bias and variance of the estimated treatment effect, with a slight advantage for the "across subsets" strategy in very small samples, provided that interaction terms between the subset variable and other covariates influencing the choice of treatment are incorporated. PS matching without replacement resulted in biased estimates and should be avoided in the case of very imbalanced subsets. CONCLUSIONS: When assessing heterogeneity in the treatment effect in small samples, the "across subsets" strategy of PS estimation is preferred. Then, either a PS matching with replacement or a weighting method must be used to estimate the average treatment effect in the treated or in the overlap population. In contrast, PS matching without replacement should be avoided in this setting.

The effects of radio-frequency electromagnetic fields on T cell function during development.

With the widespread use of radio-frequency devices, it is increasingly important to understand the biological effects of the associated electromagnetic fields. Thus, we investigated the effects of radio-frequency electromagnetic fields (RF-EMF) on T cell responses during development due to the lack of science-based evidence for RF-EMF effects on developmental immune systems. Sprague Dawley (SD) rats were exposed to 2.14-GHz wideband code division multiple-access (W-CDMA) RF signals at a whole-body specific absorption rate (SAR) of 0.2 W/kg. Exposures were performed for a total of 9 weeks spanning in utero development, lactation and the juvenile period. Rats were continuously exposed to RF-EMF for 20 h/day, 7 days/week. Comparisons of control and exposed rats using flow cytometry revealed no changes in the numbers of CD4/CD8 T cells, activated T cells or regulatory T cells among peripheral blood cells, splenocytes and thymocytes. Expression levels of 16 genes that regulate the immunological Th1/Th2 paradigm were analyzed using real-time PCR in the spleen and thymus tissues of control and RF-EMF-exposed rats. Although only the Il5 gene was significantly regulated in spleen tissues, Il4, Il5 and Il23a genes were significantly upregulated in thymus tissues following exposure to RF-EMF. However, ELISAs showed no changes in serum IL-4 protein concentrations. These data indicate no adverse effects of long-term RF-EMF exposure on immune-like T cell populations, T cell activation, or Th1/Th2 balance in developing rats, although significant transcriptional effects were observed.