Only 60-70% of fertilized eggs may result in a live birth, and very early fetal loss mainly goes unnoticed. Outcomes that can only be ascertained in live-born children will be missing for those who do not survive till birth. In this article, we illustrate a common bias structure (leading to 'live-birth bias') that arises from studying the effects of prenatal exposure to environmental factors on long-term health outcomes among live births only in pregnancy cohorts. To illustrate this we used prenatal exposure to perfluoroalkyl substances (PFAS) and attention-deficit/hyperactivity disorder (ADHD) in school-aged children as an example. PFAS are persistent organic pollutants that may impact human fecundity and be toxic for neurodevelopment. We simulated several hypothetical scenarios based on characteristics from the Danish National Birth Cohort and found that a weak inverse association may appear even if PFAS do not cause ADHD but have a considerable effect on fetal survival. The magnitude of the negative bias was generally small, and adjusting for common causes of the outcome and fetal loss can reduce the bias. Our example highlights the need to identify the determinants of pregnancy loss and the importance of quantifying bias arising from conditioning on live birth in observational studies.

The relationship between smoking and melanoma remains unclear. Among the different results is the paradoxical finding that smoking was shown to be inversely associated with the risk of malignant melanoma in some large cohort and case-control studies, even after control for suspected confounding variables. Smoking is a known risk factor for many non-communicable diseases, including coronary heart disease, stroke, as well as other malignancies; it has been shown to be positively associated with other types of skin cancer, and there remains no clear biologic explanation for a possible protective effect on malignant melanoma. In this paper, we propose a plausible mechanism of bias from smoking-related competing risks that may explain or contribute to the inverse association between smoking and melanoma as spurious. Using directed acyclic graphs for formalization and visualization of assumptions, and Monte Carlo simulation techniques, we demonstrate how published inverse associations might be compatible with selection bias resulting from uncontrolled or unmeasured common causes of competing outcomes of smoking-related diseases and malignant melanoma. We present results from various scenarios assuming a true null as well as a true positive association between smoking and malignant melanoma. Under a true null assumption, we find inverse associations due to the biasing mechanism to be compatible with published results in the literature, especially after the addition of unmeasured confounding variables. This study could be seen as offering a cautionary note in the interpretation of published smoking-melanoma findings.

The CQ index reliably and validly captures dialysis patient experience. Overall, most care aspects showed limited room for improvement, mainly because patients participating in our study rated their experience to be optimal. To evaluate items with high priority, but with which relatively few patients have experience, more qualitative instruments should be considered.