Cause

 Clinicians are confronted frequently with information about possible causal relationships. Example: Relationship between the cigarette smoking habits of obstetricians and vigor of babies. they delivered

 Cause:anything producing an effect or a result  Cause is discussed under such heading as “etiology “,” pathogenesis”,”mechanism”, “risk factors”.  Cause is important to practicing physicians primarily because it guides their approach to three clinical tasks: prevention, diagnosis and treatment.  Belief in a causal relationship underlies every therapeutic intervention in clinical medicine.

 Koch set forth postulate for determining that infectious agent is the cause of a disease. Basic to his approach was the assumption that a particular disease has one cause and a particular cause results in one disease. The organism must be present in every case of the disease; it must be isolated and grown in pure culture; it must cause a specific disease when inoculated into an animal; it must then be recovered from the animal and identified.

 Usually many factors act together to cause disease in what has been called the “web of causation.”  A causal web is well understood in conditions such as coronary artery disease, but is also true for infectious disease, where presence of the organism is a necessary cause for disease to occur but not necessarily a sufficient cause

 When biomedical scientists study cause, they usually search for the underlying pathogenetic mechanism or final common pathway of disease.  Disease is also determined by less specific,more remote cause, or risk factors such as peoples behavior or characteristic of their environments.

 Even when the pathogenetic mechanism is not clear, knowledge of strong risk factors may still lead to effective treatment and preventions.  For many diseases, both pathogenetic mechanism and nonspecific risk factors have been important in the spread and control of the disease.

 In fact, social and economic improvements influencing host susceptibility,such as less crowded living space and better nutrition may have played a more prominent role in the decline in TB rates in developed countries than treatments created through the biomedical pathogenentic research model.

 When more than one cause acts together, the resulting risk may be greater or less than would be expected by simply combining the effects of the effects of the separate causes. this is called interaction. Clinicians call this phenomenon synergism when the joint effect is greater than the sum of the effects of the individual causes and antagonism when it is less. Sometimes, the term biologic interaction is used to distinguish it from statistical interaction.

 Interaction is often expressed as effect modification when the strength of the relationship between two variables is different according to the level of some third variable, called an effect modifier.

 It is only possible to increase ones conviction of a cause-and-effect relationship by means of empiric evidence to the point at which for all intents and purposes, cause is established  A postulated cause-and-effect relationship should be examined in as many different ways as possible

 Two factors _ the suspected cause and the effect- obviously must be associated if they are to be considered as causally related however, not all association are causal.  Selection and measurement biases and chance can give rise to apparent associations that do not exist in nature.

 When considering a possible causal relationship, the strength of the research design used to establish the relationship is an important piece of evidence.  The best evidence for a cause-and –effect relationship come from well conducted randomized controlled trials, with adequate numbers of patients, blinding of therapists,patients and researchers ;limited or no loss to follow_up ; and carefully standardized methods of measurement and analysis.

 Clinicians ordinarily rely on RCTs to provide evidence about causal relationship for treatments and prevention.  In general,the further one departs from randomized trials,the less the research design protects against possible biases and the weaker the evidence is for a cause-and- effect relationship.  Well-conducted cohort studies are the next best design.  Weakest of all studies are case series.

 Studies in which exposure to a risk factor is characterized by the average exposure of the group to which individuals belong are called aggregate risk studies (ecological studies ). Example:relationship between wine consumption and cardiac mortality in developed countries.

 Aggregate risk studies are rarely definitive in and of themselves. The main problem is a potential bias called the ecological fallacy, which affected individuals in a generally exposed group may not them selves have been the ones exposed to the risk factor.

 In a time-series study, the effect is measured at various points in time before and after the purported cause has been introduced  If changes in the purported cause are followed by changes in the purported effect,the associations is less likely to be spurious.  An advantage of a time_series analysis is that it can distinguish between changes occurring over time from the effects of the intervention.

 In a time-series study, the suspected cause is introduced into several different groups at different times. Measurements are then made among the groups to determine whether the effect occurred in the same sequential manner in which the suspected cause was introduced.

 In 1965 the British statistician proposed a set of features that should be sought when deciding whether a relationship between some environmental factor and a sickness is causal or just an association.

 Causes should obviously precede effects.  Sometimes,however, the principal can be overlooked when interpreting cross-sectional and case-control studies,in which both the purported cause and the effect are measured at the same point in time.  Although it is absolutely necessary for a cause to precede an effect, an appropriate temporal sequence alone is weak evidence for cause.

 A strong association between a purported cause,as expressed by a large relative or absolute risk, is better evidence for a causal relationship than a weak association. Thus, the strength of association between smoking and lung cancer is much greater than smoking and renal cancer.

 A dose-response relationship is present if increasing the exposure to the purported cause is followed by a larger and larger effect.  Although a dose-response curve is good evidence for a causal relationship, especially when coupled with a large relative or absolute risk, its existence does not exclude confounding factors.

 A factor is more likely to be a cause of disease when ever its removal results in a decreased risk of disease.  Reversible associations are strong, but not infallible, evidence of a causal relationship. confounding could conceivably explain a reversible association.

 When several studies,conducted at different times indifferent settings and with diffirent kinds of patients, all come to the same conclusion, evidence for a causal relationship is strengthened.  It is often the case that different studies produce different results. Lack of consistency does not necessaily mean that the results of a particular study are in valid. one good study should outweigh several poor ones.

 The assertion that cause and effect is consistent with our knowledge of the mechanism of disease, as it is currently understood, is often given considerable weight when causation is being assessed.  It is important to remember, however, that what is considered biologically plausible depends on the state of medical knowledge at the time.

 It is more often found for acute infectious disease(such as polio myelitis and tetanus) and for genetic disease(such as FAP, ochronosis, and PKU).  The presence of specificity is strong evidence for cause,but the absence of specificity is weak evidence for cause,but the absence of specificity is weak evidence against a cause- and-effect relationship.

 The argument for a cause-and-effect relationship is strengthened when examples exist of well-established causes that are analogous to the one in question.  In general,analogy is weak evidence for cause.

 When determining cause, one must consider the evidence from all available studies.After examining the research design and quality and the elements for and against cause,the case for causality can be strengthened or eroded. This calls for a good deal of judgment, especially when the evidence from different studies is conflicting.

 All relevant studies are reviewed according to specific criteria. This systematic review is then used to determine the strength of the evidence for the causal relationship.