Objectives: Stage I non-small cell lung cancer (NSCLC) can be treated with either Stereotactic Body Radiotherapy (SBRT) or Video Assisted Thoracic Surgery (VATS) resection. To support decision making, not only the impact on survival needs to be taken into account, but also on quality of life, costs and cost-effectiveness. Therefore, we performed a cost-effectiveness analysis comparing SBRT to VATS resection with respect to quality adjusted life years (QALY) lived and costs in operable stage I NSCLC. Materials and methods: Patient level and aggregate data from eight Dutch databases were used to estimate costs, health utilities, recurrence free and overall survival. Propensity score matching was used to minimize selection bias in these studies. A microsimulation model predicting lifetime outcomes after treatment in stage I NSCLC patients was used for the cost-effectiveness analysis. Model outcomes for the two treatments were overall survival, QALYs, and total costs. We used a Dutch health care perspective with 1.5 % discounting for health effects, and 4 % discounting for costs, using 2018 cost data. The impact of model parameter uncertainty was assessed with deterministic and probabilistic sensitivity analyses. Results: Patients receiving either VATS resection or SBRT were estimated to live 5.81 and 5.86 discounted QALYs, respectively. Average discounted lifetime costs in the VATS group were €29,269 versus €21,175 for SBRT. Difference in 90-day excess mortality between SBRT and VATS resection was the main driver for the difference in QALYs. SBRT was dominant in at least 74 % of the probabilistic simulations. Conclusion: Using a microsimulation model to combine available evidence on survival, costs, and health utilities in a cost-effectiveness analysis for stage I NSCLC led to the conclusion that SBRT dominates VATS resection in the majority of simulations.@en

Non-small cell lung cancer (NSCLC) survival is compared between patients treated in all academic (n = 1289) versus all non-academic (n = 12,698) Dutch hospitals, using Kaplan-Meier estimates and a Cox proportional hazards model. For 1009 patients, treatment patterns are described. Diagnosis in an academic hospital is associated with decreased mortality. Possibilities for improvement of NSCLC care are suggested. Background The aims of this study are to analyze differences in survival between academic and non-academic hospitals and to provide insight into treatment patterns for non-small cell lung cancer (NSCLC). Results show the state of NSCLC survival and care in the Netherlands. Methods The Netherlands Cancer Registry provided data on NSCLC survival for all Dutch hospitals. We used the Kaplan-Meier estimate to calculate median survival time by hospital type and a Cox proportional hazards model to estimate the relative risk of mortality (expressed as hazard ratios) for patients diagnosed in academic versus non-academic hospitals, with adjustment for age, gender, and tumor histology, and stratifying for disease stage. Data on treatment patterns in Dutch hospitals was obtained from 4 hospitals (2 academic, 2 non-academic). A random sample of patients diagnosed with NSCLC from January 2009 until January 2011 was identified through hospital databases. Data was obtained on patient characteristics, tumor characteristics, and treatments. Results The Cox proportional hazards model shows a significantly decreased hazard ratio of mortality for patients diagnosed in academic hospitals, as opposed to patients diagnosed in non-academic hospitals. This is specifically true for primary radiotherapy patients and patients who receive systemic treatment for non-metastasized NSCLC. Conclusion Patients diagnosed in academic hospitals have better median overall survival than patients diagnosed in non-academic hospitals, especially for patients treated with radiotherapy, systemic treatment, or combinations. This difference may be caused by residual confounding since the estimates were not adjusted for performance status. A wide variety of surgical, radiotherapeutic, and systemic treatments is prescribed.@en