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KeywordsClinical Predictors Biomedical Factors Behavior Medicine Clinical Risk Factors Predict Health Outcomes
This term often refers to biomedical factors known to influence or predict health outcomes. These are taken into account in clinical practice, when estimating a patient’s prognosis. Additionally, clinical predictors are considered in clinical research, when trying to test new etiological or prognostic factors, and there is a need to statistically control for known or previously empirically established clinical predictors, which could possibly explain the role of the new tested factor(s). In behavior medicine, this is often the common approach, when testing the effects of a psychosocial factor on health outcomes. Often, it is crucial to statistically control for the effects of known clinical predictors in behavior medicine, as clinical risk factors are either important in predicting prognosis or since they may be associated with and partly explain the prognostic effects of psychosocial factors. For example, in coronary heart disease, clinical risk factors can include left ventricular ejection fraction, extent and number of occluded vessels, troponin levels, and comorbidities. In cancer, clinical risk factors can include performance level, tumor stage, and treatments. In surgery, clinical risk factors can include age, severity of surgery, and comorbidities.
Chida et al. (2008), in their meta-analysis of over 160 studies, tested and found that psychosocial factors significantly predicted prognosis in cancer, and this was maintained also when statistically controlling for confounders, which included clinical predictors such as stage or treatment in some studies. One example in heart disease is the study by Denollet et al. (1996) showing that type D personality (high distress and social inhibition) predicted mortality from coronary heart disease, independent of clinical risk factors. Testing for such factors provides important strength to the claim that psychosocial factors predict health outcomes, independent of biomedical factors. This then justifies the need to consider and intervene in modifying psychosocial factors beyond targeting biomedical clinical predictors alone.