Vitiello B
Child and Adolescent Disorders Research Branch, National Institute of Mental Health, Rockville, Maryland, USA.
J Child Adolesc Psychopharmacol. 1997 Spring;7(1):3-8. doi: 10.1089/cap.1997.7.3.
Clinical trials in child psychiatry research have increased in complexity. Several factors have contributed to this change, including the need to compare multiple therapies, to re-create clinically relevant situations in research, to standardize treatment approaches, to account for the impact of comorbidity, to respond to the needs of individual patients, and to optimize treatment accordingly. To preserve the clinical and internal validity of the experimental interventions vis-à-vis their increasing complexity, researchers have started developing treatment algorithms. These deductive systems for handling data allow us to standardize and incorporate clinical judgment into study designs through the adoption of a stepwise decision making process. Treatment algorithms are different from treatment guidelines. Guidelines are general recommendations that apply to groups of patients with certain characteristics; they are not fully detailed and are created with the expectation that clinical judgment will be applied in individual cases. Algorithms are patient specific, are intended to capture all the relevant details of the clinical situation, and require minimal clinical judgment for their clinical application; they are designed to minimize the role of clinical judgment in research protocols. The entire multistep algorithm is tested in a clinical trial, not the single steps that constitute the algorithm, so proving the efficacy of an algorithm cannot replace a controlled assessment of the individual treatments embedded in the algorithm. Some characteristics, properties, and limitations of algorithms in child psychiatry and psychopharmacology research are presented along with two examples of algorithms currently used in child and adolescent psychopharmacology. Although treatment algorithms seldom have been used in pediatric psychiatry and psychopharmacology, there are indications that their use will increase in the near future and will allow the standardized introduction of clinical judgment into research design.
儿童精神病学研究中的临床试验复杂性有所增加。促成这一变化的因素有若干，包括需要比较多种疗法、在研究中重现临床相关情况、使治疗方法标准化、考虑共病的影响、回应个体患者的需求并据此优化治疗。为了在实验干预措施日益复杂的情况下保持其临床和内部有效性，研究人员已开始开发治疗算法。这些用于处理数据的演绎系统使我们能够通过采用逐步决策过程，将临床判断标准化并纳入研究设计。治疗算法不同于治疗指南。指南是适用于具有某些特征的患者群体的一般建议；它们并不详尽，其制定是期望在个别病例中应用临床判断。算法是针对患者个体的，旨在捕捉临床情况的所有相关细节，并且在临床应用中需要最少的临床判断；它们旨在尽量减少临床判断在研究方案中的作用。整个多步骤算法在临床试验中进行测试，而不是构成算法的单个步骤，因此证明一种算法的有效性并不能替代对算法中所包含的个体治疗进行对照评估。本文介绍了儿童精神病学和精神药理学研究中算法的一些特征、特性和局限性，并列举了目前在儿童和青少年精神药理学中使用的两种算法示例。尽管治疗算法在儿科精神病学和精神药理学中很少使用，但有迹象表明，在不久的将来其使用将会增加，并将使临床判断能够标准化地引入研究设计。
