Vickers Andrew J, Basch Ethan, Kattan Michael W
Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA.
Ann Intern Med. 2008 Aug 5;149(3):200-3. doi: 10.7326/0003-4819-149-3-200808050-00010.
The act of diagnosis requires that patients be placed in a binary category of either having or not having a certain disease. Accordingly, the diseases of particular concern for industrialized countries--such as type 2 diabetes, obesity, or depression--require that a somewhat arbitrary cut-point be chosen on a continuous scale of measurement (for example, a fasting glucose level >6.9 mmol/L [>125 mg/dL] for type 2 diabetes). These cut-points do not adequately reflect disease biology, may inappropriately treat patients on either side of the cut-point as 2 homogenous risk groups, fail to incorporate other risk factors, and are invariable to patient preference. This article discusses risk prediction as an alternative to diagnosis: Patient risk factors (blood pressure, age) are combined into a single statistical model (risk for a cardiovascular event within 10 years) and the results are used in shared decision making about possible treatments. The authors compare and contrast the diagnostic and risk prediction approaches and attempt to identify the types of medical problem to which each is best suited.
诊断行为要求将患者归为患有或未患有某种特定疾病的二元类别。因此,工业化国家特别关注的疾病——如2型糖尿病、肥胖症或抑郁症——需要在连续的测量尺度上选择一个多少有些随意的切点(例如,2型糖尿病的空腹血糖水平>6.9毫摩尔/升[>125毫克/分升])。这些切点不能充分反映疾病生物学特性,可能会不适当地将切点两侧的患者视为两个同质的风险组,未能纳入其他风险因素,并且与患者偏好无关。本文讨论风险预测作为诊断的替代方法:将患者的风险因素(血压、年龄)合并到一个单一的统计模型中(10年内发生心血管事件的风险),并将结果用于关于可能治疗的共同决策。作者比较并对比了诊断方法和风险预测方法,并试图确定每种方法最适合的医疗问题类型。