An Economic Evaluation For The First-line Therapy Of The Advanced Non Small Cell Lung Cancer

In foreign countries, the drug economics has been widely used in the screening,diagnosis and treatment of many diseases such as cardiovascular disease, cancer,AIDS, diabetes, however the theory research and method applications of drugeconomics are relatively less in domestic. With the gradually rising medical costs intoday’s world, efficacy and safety data can no longer be the sole criteria that guidetherapeutic decisions. The extravagant cost of cancer treatment has become one ofmodern society’s heaviest burdens. The growing demand for anti-cancer drugs andhigher costs of new treatments are forcing policy-makers to consider more efficientways of allocating limited health resources.In the present study, we used the principles and methods of decision sciences toperform a pharmacoeconomic evaluation of different first-line therapies for patientswith EGFR mutation of advanced non-small cell lung cancer (NSCLC), includingerlotinib, gefitinib, and paclitaxel/carboplatin (PC), to help clinicians choose asuitable chemotherapy for patients. The main contents are as follows:(1) We built the cost model according to the charging standard of JiangsuProvincial People’s Hospital. Based on the response evaluation criteria in solidtumors (RECIST) version1.1of WHO, we developed a Markov decision tree modelwith four health states: remission, stable, progressive, and dead. We estimated thetransition probabilities in the Markov model based on DEALE methods, using datafrom the randomized clinical trials. We used the health state utilities found in Nafees et al.’s study (2008).(2) We then determined the parameter inputs of the multi-state Markov model.The Markov analysis was performed to simulate the numbers of people in each of thestates till to5years. Based on the outputs of the Markov model, we decided whichtreatments are more cost-effective in relation to other alternatives.(3) We used deterministic sensitivity analysis and probabilistic sensitivity analysisto test the stability of the results. Deterministic sensitivity analysis was performedwith a one-way sensitivity analysis, and probabilistic analysis was performed with asecond-order Monte Carlo simulation method.The main results of the study are as follows:(1) The ICER for erlotinib compared with PC was￥25753.18/QALM and theICER for gefitinib compared with PC was￥28152.79/QALM. They were bothgreater than the willingness to pay (WTP). The inputs of the Markov model tested inone-way sensitivity analysis and probabilistic sensitivity analysis had very littleimpact on the overall cost effectiveness. From the perspective of cost-effectivenessanalysis, two molecular targeted drugs were not cost-effective when compared withPC. When erlotinib drug cost decreased by15%, erlotinib became morecost-effective than PC; and when gefitinib drug cost decreased by35%, gefitinibbecame more cost-effective than PC.(2) The ICER for gefitinib compared with erlotinib was￥72333.82/QALM, butthe sensitivity analysis had a great impact on the outputs of the model, so we couldnot decide which treatment is more cost-effective.