[A short history of the concept of bias in epidemiology]

BACKGROUND

Bias is a major methodological issue for epidemiology. However, only a few studies have been dedicated to the past and present formulations of the concept of bias. Moreover, the classical definition of bias as systematic deviation from the truth of results or inferences, definition which can be found in dictionaries of epidemiology, does not seem to either match the way epidemiologists use it in practice, or correspond to the different definitions given throughout its history. It is consequently important to elucidate this paradox.

METHODS

In this historical and conceptual article, we study the different uses of the word "bias" in epidemiological literature, from classic articles in the 1950's about the link between smoking and lung cancer to the most recent epidemiology textbooks, the objective being to analyze the ways in which epidemiologists have defined, applied and modified this concept over time.

RESULTS

We show that D.L. Sackett's article on bias in analytic research, published in 1979, put an end, at least temporarily, to reflection in populational epidemiology that started thirty years before. More precisely, we show that Sackett's definition of bias corresponds more to the needs and goals of clinical epidemiology than to those of populational epidemiology. Concomitantly, populational epidemiologists such as K.J. Rothman redefined bias as a threat to the internal validity of a study, and epidemiological study as an "exercise in measurement of an effect rather than as a criterion-guided process for deciding whether an effect is present or not".

CONCLUSION

It is thereby important to draw a distinction between two notions pertaining to bias: an epidemiological concept of bias, viewed as the lack of internal validity of an observational study; and a medical concept of bias, defined as deviation from the truth. The former concerns the design and methodology of epidemiological studies; the latter is more general and impels epidemiologists and physicians to be skeptical, and even critical, towards their own inferences.

[How to measure real-world effectiveness?]

The new use of medico-administrative databases is a major change in the medical assessment field. Given the limits of the randomized clinical trials when it comes to accurately represent the heterogeneity and complexity of medical care in a real-world context, an increasing demand of observational studies comes from healthcare systems as decision tools. The lack of intervention generates real-world data and assesses both the care and the outcomes of patients in routine practice. Despite this external validity, the bias and confounding factors are a challenge to the internal validity of observational studies. An appropriate study design and statistical methods are necessary to neutralize them and consider a causal relationship between a treatment and a clinical outcome.

False-positive results in pharmacoepidemiology and pharmacovigilance

False-positive constitute an important issue in scientific research. In the domain of drug evaluation, it affects all phases of drug development and assessment, from the very early preclinical studies to the late post-marketing evaluations. The core concern associated with this false-positive is the lack of replicability of the results. Aside from fraud or misconducts, false-positive is often envisioned from the statistical angle, which considers them as a price to pay for type I error in statistical testing, and its inflation in the context of multiple testing. If envisioning this problematic in the context of pharmacoepidemiology and pharmacovigilance however, that both evaluate drugs in an observational settings, information brought by statistical testing and the significance of such should only be considered as additional to the estimates provided and their confidence interval, in a context where differences have to be a clinically meaningful upon everything, and the results appear robust to the biases likely to have affected the studies. In the following article, we consequently illustrate these biases and their consequences in generating false-positive results, through studies and associations between drug use and health outcomes that have been widely disputed.

[Benefits of using the cutometer to evaluate the effectiveness of skin treatments in plastic and maxillofacial surgery]

INTRODUCTION

Evaluating skin properties is often too subjective. Using the cutometer allows one to take objective measures of certain mechanic properties of the skin such as visco-elasticity. The aim of this article is to evaluate through a review of existing literature the advantages and the limits of the cutometer and to propose an improvement.

MATERIAL AND METHODS

The selection of articles has been conducted with the PubMed database in order to identify all publications concerning the cutometer up until September 2013. The analysis criteria were: (1) quantitative distribution of articles from the first publication until today; (2) qualitative distribution over the various medical fields. The articles have been organized in 3 groups: medical, surgical and burns; (3) list of biases in the interpretation of results and limits of this measuring tool.

RESULTS

One hundred and twenty-nine publications have been included. The first article regarding the cutometer was published in 1994. We observe an increase in the number of publications after 2005. Most of the articles were published in medical journals of dermatology or cosmetology (83%), only 9% of articles have been published in burn study journals and 8% in surgical journals. The pressure applied by the experimenter constitutes the main measure bias.

DISCUSSION

The use of an external device maintaining the probe with an invariable pressure corresponding to its own weight enables more reliable results all the while limiting the inter- and intra-individual variability.