Subgroup effects despite homogeneous heterogeneity test results

Background. Statistical tests of heterogeneity are very popular in meta-analyses, as heterogeneity might indicate subgroup effects. Lack of demonstrable statistical heterogeneity, however, might obscure clinical heterogeneity, meaning clinically relevant subgroup effects. Methods. A qualitative, visual method to explore the potential for subgroup effects was provided by a modification of the forest plot, i.e., adding a vertical axis indicating the proportion of a subgroup variable in the individual trials. Such a plot was used to assess the potential for clinically relevant subgroup effects and was illustrated by a clinical example on the effects of antibiotics in children with acute otitis media. Results. Statistical tests did not indicate heterogeneity in the meta-analysis on the effects of amoxicillin on acute otitis media (Q = 3.29, p = 0.51; I2 = 0%; T2 = 0). Nevertheless, in a modified forest plot, in which the individual trials were ordered by the proportion of children with bilateral otitis, a clear relation between bilaterality and treatment effects was observed (which was also found in an individual patient data meta-analysis of the included trials: p-value for interaction 0.021). Conclusions. A modification of the forest plot, by including an additional (vertical) axis indicating the proportion of a certain subgroup variable, is a qualitative, visual, and easy-to-interpret method to explore potential subgroup effects in studies included in meta-analyse

Outcome Following Percutaneous Transluminal Coronary Angioplasty Performed Before 1990

The goal of this follow-up study was to assess the long-term survival of all patients having undergone a first PTCA between 1981 and 1990 and to relate the outcome to the baseline clinical and angiographic state. Although PTCA has become a widely accepted therapeutic choice for revascularization, the authors lacked information on long-term outcome. Data was collected by questionnaire, the end points being a second PTCA, MI, CABG, death or any of these events. The survival curves were constructed using the Kaplan-Meier method. Multivariate analysis was performed by a Cox proportional hazards model. Complete follow-up data were collected for 1,071 patients for a mean period of 7.4 years (SEM +/- 1.98 months) with a range of 0 to 14 years. Mean age was 57 years. PTCA was successful in 85% of patients. In-hospital event rates were death 1.3%, MI 4.4%, and emergency CABG 2.9%. Overall survival at 14 years was 69% (SEM +/- 9.6%) and event-free survival was 47% (SEM +/- 5.8%). MI rate was 11%, CABG 15%, and 20% of patients underwent repeat PTCA. Presence of cardiovascular risk factors, poor left ventricular ejection fraction, and prior CABG were significantly associated with poorer event-free survival. The short-term observations are consistent with results reported by the other follow-up studies. In addition, the study found a total survival rate 14 years after a first PTCA of 69% and 47% of the cohort remained event free