Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland.
Wing Tech, Inc., Menlo Park, California; Department of Industrial and Systems Engineering, University of Washington, Seattle, Washington.
J Thorac Oncol. 2017 Aug;12(8):1223-1232. doi: 10.1016/j.jtho.2017.04.030. Epub 2017 May 11.
The use of a bronchial genomic classifier has been shown to improve the diagnostic accuracy of bronchoscopy for suspected lung cancer by identifying patients who may be more suitable for radiographic surveillance as opposed to invasive procedures. Our objective was to assess the cost-effectiveness of bronchoscopy plus a genomic classifier versus bronchoscopy alone in the diagnostic work-up of patients at intermediate risk for lung cancer.
A decision-analytic Markov model was developed to project the costs and effects of two competing strategies by using test performance from the Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer-1 and Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer-2 studies. The diagnostic accuracy of noninvasive and invasive follow-up, as well as associated adverse event rates, were derived from published literature. Procedure costs were based on claims data and 2016 inpatient and outpatient reimbursement amounts. The model projected the number of invasive follow-up procedures, 2-year costs and quality-adjusted life-years (QALYs) by strategy, and resulting incremental cost-effectiveness ratio discounted at 3% per annum.
Use of the genomic classifier reduced invasive procedures by 28% at 1 month and 18% at 2 years, respectively. Total costs and QALY gain were similar with classifier use ($27,221 versus $27,183 and 1.512 versus 1.509, respectively), resulting in an incremental cost-effectiveness ratio of $15,052 per QALY.
Our analysis suggests that the use of a genomic classifier is associated with meaningful reductions in invasive procedures at about equal costs and is therefore a high-value strategy in the diagnostic work-up of patients at intermediate risk of lung cancer.
使用支气管基因组分类器可通过识别可能更适合放射监测而不是侵入性程序的患者，提高疑似肺癌支气管镜检查的诊断准确性。我们的目的是评估在肺癌中危患者的诊断性工作中，支气管镜检查加基因组分类器与单独支气管镜检查相比的成本效益。
使用 Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer-1 和 Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer-2 研究中的测试性能，开发了一个决策分析马尔可夫模型，以预测两种竞争性策略的成本和效果。非侵入性和侵入性随访的诊断准确性以及相关不良事件发生率来自已发表的文献。根据索赔数据和 2016 年住院和门诊报销金额确定程序成本。该模型预测了按策略进行的侵入性随访程序数量、2 年成本和质量调整生命年（QALY），并根据 3%的贴现率计算出增量成本效益比。
使用基因组分类器可分别在 1 个月和 2 年时减少 28%和 18%的侵入性随访程序。使用分类器时，总成本和 QALY 增益相似（分别为 27221 美元和 27183 美元，以及 1.512 和 1.509），增量成本效益比为每 QALY 15052 美元。
我们的分析表明，使用基因组分类器可显著减少侵入性程序，而成本相当，因此在肺癌中危患者的诊断性工作中是一种高价值策略。
