Methods for Evaluating Causality in Observational Studies

Abstract

Background: In clinical medical research, causality is demonstrated by randomized controlled trials (RCTs). Often, however, an RCT cannot be conducted for ethical reasons, and sometimes for practical reasons as well. In such cases, knowledge can be derived from an observational study instead. In this article, we present two methods that have not been widely used in medical research to date. Methods: The methods of assessing causal inferences in observational studies are described on the basis of publications retrieved by a selective literature search. Results: Two relatively new approaches-regression-discontinuity methods and interrupted time series-can be used to demonstrate a causal relationship under certain circumstances. The regression-discontinuity design is a quasi-experimental approach that can be applied if a continuous assignment variable is used with a threshold value. Patients are assigned to different treatment schemes on the basis of the threshold value. For assignment variables that are subject to random measurement error, it is assumed that, in a small interval around a threshold value, e.g., cholesterol values of 160 mg/dL, subjects are assigned essentially at random to one of two treatment groups. If patients with a value above the threshold are given a certain treatment, those with values below the threshold can serve as control group. Interrupted time series are a special type of regression-discontinuity design in which time is the assignment variable, and the threshold is a cutoff point. This is often an external event, such as the imposition of a smoking ban. A before-and-after comparison can be used to determine the effect of the intervention (e.g., the smoking ban) on health parameters such as the frequency of cardiovascular disease. Conclusion: The approaches described here can be used to derive causal inferences from observational studies. They should only be applied after the prerequisites for their use have been carefully checked.

Health-Related Quality of Life and Frequency of Physical Activity in Spanish Students Aged 8–14

“…The main limitation of this study is that cause-effect association cannot be obtained. However, observational studies can help in suggesting hypotheses about those causal relationships that shall be tested in further studies [74]. In our case, experiments regarding PA and HRQoL should be carried out, focusing on how variables could be influenced (such as individuals' characteristics or socioeconomic status), how regular physical activity could improve it (exploring needed mechanisms) and to what extent the start of secondary education negatively interacts with physical activity levels among the studied population.…”

Comment on “Abuse and Misuse of Pregabalin and Gabapentin: A Systematic Review Update”

“…From the perspective of evidence-based medicine (EBM), level I experimental studies use randomized, prospective experimental designs to confirm causal relationships [2] not unequivocally derivable from non-experimental observational studies [3]. Although regulatory approval/disapproval does not always require randomized trials at every level of decision making, whenever randomization is not possible, the effect of various predictors and confounders must be taken into account in the planning of the study and in data analysis [3][4][5][6]. We are not aware of studies that have done so sufficiently to support presumptions of a causal connection between GP-use/misuse and related harms including psychological dependence and death.…”

“…Table 1 in [1]). Well-powered and controlled [3][4][5][6] prospective trials comparing the occurrence of psychological dependence and deaths in an opioid-dependent sample versus a general population-based sample are needed to identify possible key effect modifiers.…”

“…From our clinician point of view, GPs are a highly useful and rather safe pharmacological armamentarium not only for neuropathic pain and some neuropsychiatric disorders, but also in the world of addiction medicine. More evidence from sufficiently controlled prospective observational [3][4][5][6] or, if possible, randomized clinical studies about their addictive and harms potential are required before further unfounded castigation (with resultant supply diminishment threat and potential attendant harms).…”

Ongoing challenges in unravelling the association between COVID-19 and Guillain-Barré syndrome

“…Furthermore, we would address some statistical issues concerning the paper by Keddie et al 1 In particular, Pearson’s correlation is far from being the gold standard to prove a causal relationship in observational studies whilst more complex methods would be more suitable. 9 Similarly, when the authors claimed that an ‘ r = 0.06, 95% CI: −0.56 to +0.63, P = 0.86’ should support a lack of correlation, 1 they did not take into account that, based on this confidence interval (CI), higher correlation coefficients might also be possible when larger and/or different samples are considered. Moreover, Keddie et al 1 calculated an occurrence rate of GBS of 0.016 cases per 1000 COVID-19 infections.…”