A patient's decision to accept treatment recommended by his dental health care provider will be strongly influenced by the quality of the information he is given. Estimates of prognosis and treatment predictability must be based on the evidence available from the literature and the practitioners' own experience. Thorough, accurate, and relevant clinical and adjunctive diagnostic data will be a major influence in the development of the patient's individualized treatment strategy. Some clinical findings such as severity of disease for age, deepening pockets accompanied by loss of clinical attachment, frequent bleeding on probing, and bone loss can be considered as risk and prognosis factors. "Hard" data implicating specific clinical or diagnostic findings as risk factors or markers are difficult to find because there are few randomized longitudinal trials available. A new approach which attempts to focus on reducing the risk of undesirable outcomes while improving the probability of successful outcomes following treatment has been referred to as the Treatment Predictability Model. A key feature of this approach is the focus on individual patient circumstances and preferences through the use of decision analysis techniques. A large scale, long-term project utilizing a practice-based research network (PBRN) provided some descriptive information about factors that could distinguish between responders and nonresponder patients undergoing treatment for advanced periodontitis. Bacterial colonization, level of post-treatment plaque control, and smoking were major predictive variables in this group of periodontitis patients. The predictive treatment approach may be one way to develop evidence that will improve the predictability of outcomes for individual patients.
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