Journal
LUNG CANCER
Volume 134, Issue -, Pages 34-41Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.lungcan.2019.05.023
Keywords
Time to treatment; Non-small cell lung cancer; Delay; Diagnostic; Treatment; Cancer registry
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Funding
- ZonMW [80-84600-98-1002]
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Objectives: Increased emphasis on molecular diagnostics can lead to increased variation in time to treatment (TTT) for patients with stage III and IV non-small cell lung cancer. This article presents the variation in TTT for advanced NSCLC patients observed in Dutch hospitals before the widespread use of immunotherapy. The aim of this article was to explore the variation in TTT between patients, as well as between hospitals. Material and methods: Based on the Netherlands Cancer Registry, we used patient-level data (n = 4096) from all 78 hospitals that diagnosed stage III or IV NSCLC in the Netherlands in 2016. To investigate how patient characteristics and hospital-level effects are associated with TTT (from diagnosis until start treatment), we interpreted regression model results for five common patient profiles to analyze the influence of age, gender, tumor stage, performance status, histology, and referral status as well as hospital-level characteristics on the TTT. Results and conclusions: 177 varies substantially between and within hospitals. The median TTT was 28 days with an inter-quartile range of 22 days. The hospital-level median TTT ranges from 17 to 68 days. TTT correlates significantly with tumor stage, performance status, and histology. The hospital-level effect, unrelated to hospital volume and type, affected TTT by several weeks at most. For most patients, TTT is within range as recommended in current guidelines. Variation in TTT seems higher for patients receiving either radiotherapy or targeted therapy, or for patients referred to another hospital and we hypothesize this is related to the complexity of the diagnostic pathway. With further advances in molecular diagnostics and precision oncology we expect variation in TTT to increase and this needs to be considered in designing optimal cancer care delivery.
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