Alfa Institute of Biomedical Sciences, Athens, Greece.
Microb Drug Resist. 2010 Dec;16(4):303-8. doi: 10.1089/mdr.2009.0134. Epub 2010 Jun 7.
The optimal control group for case-control studies examining antibiotics as risk factors for the emergence of antimicrobial resistance is patients selected randomly from the total hospital population, while the selection of patients with a susceptible bacterium is deemed suboptimal. We sought to theoretically elaborate on potential parameters that introduce bias associated with the use of randomly selected control subjects, based on personal experience and data from the literature. In addition, we considered parameters that introduce potential bias associated with the definition of case patients. Parameters that may introduce potential bias associated with the randomly selected control subjects are use of antibiotics in the community (background exposure), availability of an antibiotic in a country, ability to purchase specific antibiotics or health care, the bacterial resistance pattern in the country, in vitro evaluation issues, source of admitting patients (nursing home or community), type of hospital to which patients are admitted (general or disease specific), and ward of hospital to which patients are admitted. Parameters that may introduce potential bias associated with the case definition are multidrug resistance versus resistance to only one antibiotic, resistance phenotype of the microbe, multistep versus one-step development of resistance, appropriateness versus adequacy of antibiotic treatment, antibiotic synergy, details regarding the daily dose and duration of administration of the specific antibiotic, and use of other antibiotics. In conclusion, selection of control subjects from the hospital population is also associated with bias. The most acceptable solutions to evaluate the risk factors for antimicrobial resistance are probably the case-control-control study design and the case-case-control study design.
对于研究抗生素作为抗菌药物耐药性出现的危险因素的病例对照研究，最佳的对照组是从医院的全部人群中随机选择的患者，而选择具有敏感性细菌的患者则被认为是不理想的。我们试图根据个人经验和文献中的数据，从理论上阐述与使用随机选择的对照受试者相关的潜在偏倚参数。此外，我们还考虑了与病例患者定义相关的可能引入潜在偏倚的参数。可能与随机选择的对照受试者相关的引入潜在偏倚的参数包括：社区中抗生素的使用（背景暴露）、国家中抗生素的供应情况、购买特定抗生素或医疗保健的能力、国家中细菌耐药模式、体外评估问题、患者入院的来源（疗养院或社区）、患者入院的医院类型（综合或特定疾病）以及患者入院的病房。与病例定义相关的可能引入潜在偏倚的参数包括：对一种抗生素的耐药性与多种药物耐药性、微生物的耐药表型、耐药性的多步发展与一步发展、抗生素治疗的适当性与充足性、抗生素协同作用、特定抗生素的每日剂量和疗程的详细信息以及其他抗生素的使用。总之，从医院人群中选择对照受试者也与偏倚有关。评估抗菌药物耐药性危险因素的最可接受的解决方案可能是病例对照对照研究设计和病例病例对照研究设计。
