Evaluation of Epidemiological Association PDF

Evaluation of Epidemiological Association Evaluation of Epidemiological Association *Apparent association can result from 1. Chance 2. Bias 3. Confounding variables **True associations other than the proposed Observed Association Could it be due to selection or measurement bias?...

Evaluation of Epidemiological Association Evaluation of Epidemiological Association *Apparent association can result from 1. Chance 2. Bias 3. Confounding variables **True associations other than the proposed Observed Association Could it be due to selection or measurement bias? No Could it be due to a confounding No  No Could it be a result of chance Probably not Could it be causal? Apply guidelines and make a judgement 1. Could the association have been observed by chance? Chance can be excluded by statistical tests through measuring a- P-value (Random error). b-95% confidence interval. 2. Could the association be due to bias? Bias is a systematic error. One Should evaluate how the study groups were selected, how the information about exposure and disease was collected, and how the data were analyzed. Bias : is deviation of the results or inferences from the truth ,or processes leading to such deviation ,it arises during process of collection,analysis,interpretation, publication or review of data that are different from the truth e.g., of bias *- Selection bias ** Information bias 3. Could other confounding variables have accounted for the observed relationship? A situation in which a measure of the effect of an exposure on risk of an outcome is distorted because of the association of the exposure with other factors that influence the outcome under study. ?associated Alcohol consumption Lung cance (exposure) (outcome) Associated Associated Cigarette smoking 4. Does the association represent a Cause-and-Effect relationship? This can be determined by the criteria of causality  Causality Cause and effect relationship Definition: A cause is a factor (characteristic behaviour, event ) that influences the occurrence of disease (effect) A cause is an act or event or a state of nature (factor) which initiates or permits, alone or in conjunction with other causes, a sequence of events resulting in an effect (diseases or health problem). A cause is a factor or habit whose reduction or removal leads to reduction of the incidence of the disease or health problem.  A cause of a disease is an event ,condition,characteristic or a combination of these factors which plays an important role in producing the disease Bradford Hill Criteria to judge the causal significance of the association between the factor (attribute or event) and an effect (outcome, disease..) are: 1. Strength of the association 2. Consistency of the association 3. Specificity of association 4. Time sequence 5. Coherence of explanation 6. Biologic gradient (Dose response) 7. Plausibility 8. Experiment( Reversibility) 9. Analogy 1- Strength of association: Relative risk is the most direct measure of strength of association. A strong association is less likely to be the result of errors. ⚫ Does exposure to the cause change disease incidence? ⚫ If not , there is no epidemiological basis for a conclusion on cause and effect.  Strength of association ⚫ Failure to demonstrate this does not, however, disprove a causal role. ⚫ The usual measure of the increase in incidence is the relative risk and the technical name for this criterion is the strength of the association. 2- consistency upon repetition: This term refers to whether the association between an agent and health effects has been observed by different persons in different places, circumstances, and times. e.g., The Surgeon General report cited that numerous prospective and retrospective studies that found an association between smoking and lung cancer. 3- Specificity: If the association is limited to specific exposure and to particular disease with no other association between the exposure and other types of disease. 4- Time sequence: Exposure preceding occurrence of disease. The shorter the duration between exposure to an agent and development of disease the more certain is the causal effect. 5- Coherence of explanation: The association must be supported with what is already known about the natural history and biology of the disease. Example: The association between tobacco and lung cancer is coherent with the experimentally known ability of tobacco extract to cause skin cancer in mice. 6-Dose-response Does the disease incidence vary with the level of exposure? If yes, the case for causality is advanced. The dose-response relation is also measured using the relative risk. 7- Plausibility: ⚫ Is there a biological mechanism by which the supposed cause can induce the effect?. 8- Experiment (reversibility): Presence of natural experiment ⚫ Does changing exposure change disease incidence? ⚫ Often there have been natural experiments. ⚫ Deliberate experimentation will be necessary. ⚫ Human experiments or trials are sometimes impossible on ethical grounds. ⚫ Causal understanding can be greatly advanced by laboratory and experimental observations. 9- Analogy: When such associations have already been demonstrated Example: The association between thalidomide and congenital malformation. Question Example of judging causality: smoking &lung cancer Does the supposed cause precede the disease Yes, clearly so (effect) (temporality) By how much does exposure to the cause raise Greatly and as much as 20 to 30 fold in the incidence of disease? smokers of 20 or more cigarettes per day (strength) Does varying exposure lead to varying disease? Yes, there is clear relationship and more smoking causes more disease (does-response) Does the cause lead to a rise in a few relevant No. Numerous diseases show an association diseases? with smoking (specificity)  causality: lung cancer Is the association consistent across different Yes. The association is demonstrable in men studies and between groups? and women, and across social groups. Is the way that the cause exerts its effect on Only partly. The tar in cigarettes contains disease understood? important carcinogens (biological plausibility) Does manipulating the level of exposure to the Yes. Reducing consumption of cigarettes cause change disease experience? reduces risk. Persuading people to smoke more would be unethical. Tobacco is carcinogenic to animals (experimental confirmation) Overall judgement Originally, bitterly contested, now accepted as causal Sources of Error in Epidemiologic Studies Random error Bias Confounding Reverse Causation  Henle-Koch postulates 1- The agent must be shown to be present in every case by isolation in culture. 2-The agent must not be found in cases of other disease. 3- The agent isolated must capaple of producing disease in experimental animals. Conditions do not satisfy Koch postulates 1-Most disease are multi-factorial with many contributory causes ( Heart dis.) 2-One exposure can cause several dis. (smoking) 3-Dis. is usually the result of interaction between host,agent and enviromental factors ( e,g., immunity,virulence,malnutrition)