[MUSIC] In this lecture, you'll learn about the Bradford Hill criteria for causality. After you have listened to this lecture, you should be able to describe, the nine Bradford Hill criteria for causality, and give examples of each. You should also be able to list modern models of causality. In 1965, English epidemiologist and statistician, Sir Austin Bradford Hill identified the nine factors that constitute the current standards for determining causality. Hill's conclusions expanded upon criteria that had previously been set forth in the U.S. Surgeon General's 1964 Smoking and Health Report. And were developed to answer the question of whether cigarettes cause disease, especially lung cancer. It is important to note that satisfying these criteria may lend support for causality. But failing to meet some criteria, does not necessarily provide evidence against causality. Hill's causal criteria should be viewed as a guideline, not as a check list that must be satisfied for a causal relationship to exist. Bradford Hill himself was even critical of using them for determining causality. Hill stated in 1965, quote, what I do not believe, and this has been suggested, is that we can usefully lay down some hard and fast rules of evidence that must be obeyed before we can accept cause and effect. None of my nine viewpoints can bring indisputable evidence for or against the cause and effect hypotheses. And none can be required as sine qua non. What they can do with greater or less strength is to help us to make up our minds on the fundamental question, is there any other way of explaining the set of facts before us? Is there any other answer equally or more likely than cause and effect. End quote. This is from The Environment and Disease Association Or Causation in the Proceedings of the Royal Society of Medicine, May 1965. Hill's criteria outline the minimal conditions needed to establish a causal relationship. These criteria were developed as a research tool for the medical field, but may also be used in other fields. Hill stated in 1965 that quote, the cause of illness may be immediate and direct. It may be remote and indirect, underlying the observed association, end quote. This is from The Environment and Disease, Association or Causation, in the proceedings of the Royal Society of Medicine from May 1965. The first criterion is strength of association. Strength of association between the exposure of interest and the outcome is most commonly measured via risk ratios, rate ratios or odds ratios. Hill believed that causal relationships were more likely to demonstrate strong associations than were non-causal agents. Strong associations occur when an exposure is a strong risk factor, and there are few other risk factors for the disease. For example, Bradford Hill pointed out that smoking is a strong risk factor for lung cancer. Smokers are 15 to 30 times more likely to have lung cancer or die due to lung cancer when compared with people who do not smoke. In addition, studies have shown that the risk of lung cancer may be increased 20-fold or more when heavy smokers are compared with non-smokers. There are certainly examples of weak but causal associations, such as smoking and heart disease, where smokers are two to four times more likely to develop heart disease than non-smokers. In the case of heart disease, there are a number of other risk factors, including diet, sedentary lifestyle, and genetic predisposition that are as strong, or stronger, than smoking as risk factors. Another weak, but causal association, is exposure to environmental tobacco smoke, which has a risk ratio for lung cancer of 1.2. In this case, the risk ratio for exposure to smoke carcinogens is much lower than the risk ratio for exposure to active smoking. One should not assume that a strong association alone is indicative of causality, as the presence of strong confounding may erroneously lead to a strong causal association. The next tenet, consistency, refers to the reproducibility of study results in various populations and situations. Consistency is generally utilized to rule out other explanations for the development of a given outcome. However, the lack of consistency does not rule out a causal association, because some effects are only produced under specific combinations of causal components. These conditions may not have been met in some studies of other populations. For example, only 10% of heavy smokers develop lung cancer. The other causal components are still being investigated. In general, the greater the consistency, the more likely a causal association. Another criterion is specificity of association. This simply states that if a single risk factor consistently relates to a single effect, then it likely plays a causal role. For example, this one-to-one relationship exists with certain bacteria and the disease they cause. Tuberculosis is a good example. It is important, however, to note that there are few diseases that have only one causal agent, and since most diseases, even tuberculosis, is caused by a constellation of factors. Including poverty, crowding, low immunity, inadequate therapy, and the tubercle bacilli. The specificity of association criterion has also been proven to be invalid in a number of instances, with smoking being the classic example. Evidence clearly demonstrates that smoking does not lead solely to lung carcinogenesis, but to a myriad of other clinical disorders ranging from emphysema to heart disease. So, keeping all this in mind, some feel that it is the weakest of all guidelines in the list and may even be misleading. Temporality has been identified as being the most likely to be the essential element or condition for causality. For an exposure to be causal its presence must proceed the development of the outcome. Lack of temporality rules out causality. One example is the relationship between Atrial Fibrillation and Pulmonary Embolism. It is widely thought that Pulmonary Embolism caused Atrial Fibrillation. However, more recent evidence, and plausible biological hypotheses, suggest that the reverse could be true. Determining the proper course of care may hinge upon discovering if pulmonary emboli can indeed proceed, and thus perhaps cause the development of atrial fibrillation. Temporality is the only necessary criterion for causality. And finally, it is easier to establish a temporal relationship in a concurrent cohort study than in a case control study or retrospective cohort study. The next Bradford Hill criterion, the biological gradient criterion, relies on dose response, suggesting that as the dose of the exposure increases, the risk of disease increases. The presence of the dose-response relationship between an exposure and outcome provides good evidence for a causal relationship. However, its absence should not be taken as evidence against such a relationship. Some diseases do not display a dose response relationship with a causal exposure. They may demonstrate a threshold association where a given level of exposure is required for disease initiation, and any additional exposure does not affect the outcome. As an example of exposure response gradient, there is the gradient of lung cancer by current amount smoked. However, some exposures do not cause disease until the exposure threshold is reached. For example, skin burns and UV radiation, and cataracts and ionizing radiation require that a certain exposure threshold level of UV or ionizing radiation be reached before disease initiation. The dose response relationship is one of the strongest guidelines, because a confounder is unlikely to cause the same disease gradient as a primary exposure. Support for the next Bradford Hill criterion, plausibility, generally comes from basic laboratory science. It is not unusual for epidemiologic conclusions to be reached in the absence of evidence from a laboratory. Particularly in situations where the epidemiologic results are the first evidence of a relationship between an exposure and an outcome. However, one can further support a causal relationship with the addition of a reasonable biological mode of action. Even though hard data may not yet be available. Laboratory experimental evidence increases our confidence in drawing causal conclusions, but is not essential. Arguments about biologic plausibility about an observed exposure response association are too often based only on prior beliefs and the experience of the laboratory scientists. For example, arguments environmental tobacco smoke cannot cause lung cancer because the doses are much below those causing cancer in animals. Some associations lacking in laboratory experimental support. For example, that some viruses can cause cancer as observed more than 30 years ago, have been subsequently been confirmed in epidemiologic studies. Coherence represents the idea that for a causal association to be supported, any new data should not be an opposition to the current evidence. That is, providing evidence against causality. However one should be cautious in making definite conclusions regarding causation, since it is possible that conflicting information is incorrect or highly biased. The guideline is also interpreted to be satisfied when exposure is shown to result in a cluster of related health events. As an example of a cluster of related health events consider that smoking causes inflammation of the respiratory tract, release of damaging free radicals, conversion of cells to pre-neoplastic states, transformation of cultured cells to cancer, activation of oncogenes, and lung cancer in humans. The coherence guideline is more demanding than mere biologic plausibility in that the evidence here must be extensive, cutting across disciplinary lines, all of which mutually support a causal association between exposure and health outcome. Experimental evidence is another Bradford Hill criterion. Today's understanding of Hill's criterion of experimental evidence results from many areas: the laboratory, epidemiologic studies, preventive, and clinical trials. Ideally, epidemiologists would like experimental evidence obtained from a well-controlled study. Specifically randomized trials. These types of studies can support causality by demonstrating that altering the cause alters the effect. For example, we can control sun exposure to examine effects on skin cancer. We could randomize individuals to high sun exposure and some to low sun exposure. By altering the cause, sun exposure, we could then examine potential changes and effects on skin cancer development. Randomized trials are the most persuasive studies, to establish causality. As they tend to balance unmeasured confounders between exposed and unexposed. But their use is limited to risk factors that can ethically be randomized among subjects. Even randomized interventions involving a complex exposure may result in difficulty in pinpointing the specific causal agent, for example, a change in diet. Or in our example on sun exposure and skin cancer, we could control sun exposure to examine the affects on skin cancer, but what about those over age 40 who have had a lot of prior sun exposure? Or, those who have gotten second-degree burns every summer for years. The final Bradford Hill criterion is analogy. When a factor is suspected of causing an effect, then others factors similar or analogous to the supposed cause should also be considered and identified as a possible cause, or otherwise eliminated from the investigation. Analogy is perhaps one of the weaker of the criteria, in that analogy is speculative in nature, and is dependent upon the subjective opinion of the researcher. Absence of analogies should not be taken as evidence against causation. In addition to assessing the components of Hill's list, it is also critically important to have a thorough understanding of the literature to determine if any other plausible explanations have been considered and tested previously. Note that this is not one of the guidelines cited by Hill, but considering alternative explanations is important. Because we have greater confidence that potential confounders were adequately controlled when multiple studies address the confounders and still agree in finding an exposure response association. Often, a single study cannot provide this assurance, even if it is well-designed and conducted. For example, the first studies of smoking and lung cancer were viewed skeptically until they were confirmed by many subsequent studies. Thus, in the case of smoking and lung cancer, there was a need for the Surgeon General's Committee on Smoking and Health, in 1964, to critically review all of the evidence. Some researchers consider these five guidelines to be the most important ones. These guidelines are to be used to evaluate the body of knowledge on an exposure response relationship, not merely applied to one or two studies. Temporality is generally considered to be necessary. But the absence of one or more of the other four guidelines does not negate the possibility of a causal relationship. Even well established causes may be later shown to be inaccurately characterized, or further evidence may seriously challenge the judgement that causality exists. By their nature, scientific conclusions, however valid at one time, are subject to challenge, when new methods of generating data present new evidence contrary to this established conclusions. Causal criteria like Bradford Hills are just one approach to assessing causal relationships. Just remember that causal criteria should be viewed as a set of guidelines, and not a check list. The consequences of defining exposure as causal, need to be considered before taking any action. You have to ask yourself what if the evidence was misleading? In addition to Bradford Hill's Guidelines for Causality, several more recent models for understanding causality have been developed. These include Causal Pis, Counterfactual Models, and Directed Acyclic Graphs. For the purposes of this class, we will only mention these models here, but we have provided some suggested readings for those students interested in further exploring these models. This concludes the lecture on the Bradford Hill criteria for causality.