Time to diagnosis and treatment of lung cancer: A systematic overview of risk factors, interventions and impact on patient outcomes.

Over half of patients with lung cancer are diagnosed at a stage when curative treatment is not possible, suggesting an earlier diagnosis could improve outcomes. This comprehensive overview summarises the evidence on 1) times to diagnosis and treatment, 2) their impact on patient outcomes, 3) risk factors and 4) interventions to reduce time intervals, and 5) key methodological issues in such studies. Eligible articles were relevant systematic or scoping reviews and meta-analyses, searched via PubMed, Embase, Web of Science, and Cochrane Library; published from database inception to 6 August 2020 (PROSPERO identifier: CRD42020203530). A total of 18 systematic and scoping reviews were included. Times to diagnosis and treatment significantly varied and were often longer than recommended in international guidelines. Results regarding the impact of time intervals on survival or tumour stage indicated mixed associations (positive, negative, or no); in each review, however, more studies reported either no or negative association. Risk factors were considerable, categorized at the disease, patient, healthcare provider and system levels. Interventions including fast-access diagnosis programs, patient navigation and multidisciplinary strategies were effective in reducing times to diagnosis and treatment. Methodological issues included large variations in interval definitions and summary measures, lack of addressing an important potential source of bias-the "waiting time paradox"-and few studies of trends over time of these intervals. The current evidence indicates that patients with lung cancer experience diagnosis and treatment delays given guidelines' recommendations, but there are inconsistent findings about the association between times to diagnosis and treatment and patient outcomes. This is partially due to variations in definitions of time intervals, and limitations in analytic approaches that fail to account for a potential waiting time paradox. The identified risk factors and effective interventions demonstrate the potential for improvements in addressing diagnostic and treatment delays, regionally and globally.

Duke Scholars

Author Xiaofei Wang Biostatistics & Bioinformatics, Division of Biostatistics