Poster Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2023

Time from diagnosis to treatment, risk factors and prognostic impact: a cohort study for patients with lung tumours (#414)

Jianrong Zhang 1 , Damien McCarthy 1 , Sally Philip 1 , Chris Kearney 1 , Maarten IJzerman 1 , Jon Emery 1
  1. University of Melbourne, Melbourne, VIC, Australia

Aims: To comprehensively investigate treatment interval (TI) from pathological diagnosis to treatment initiation in patients with lung tumours, including its length, risk factors and prognostic impact.

 

Methods: This cohort study is part of a data-linkage project including the AURORA registry dataset based on the Peter MacCallum Cancer Centre and St. Vincent Hospital in Victoria. Multivariate Cox regressions were applied to identify risk factors for longer TI and evaluate TI’s impact on overall survival (OS), both adjusted for sex, age, ethnicity, year, histopathology, stage, hospital site, and treatment type.

 

Results: A total of 2805 patients diagnosed in 2012-2020 were included, with a median follow-up of 554 days. The median length of TI was 16 (95%CI 15-18) days, demonstrating a decreasing tendency from 2012-2014 (hazard ratio (HR)=0.75 [0.62-0.90]), 2015-2017 (HR=0.91 [0.75-1.10]) to 2020 (HR=1.12 [0.93-1.35]) (compared to 2018-2019). Identified risk factors were: South Asian (HR=0.66 [0.45-0.97]) vs. White, neoplastic comorbidities (HR=0.90 [0.81-1.00]), stages I (HR=0.47 [0.40-0.55]), II (HR=0.56 [0.46-0.68]), III (HR=0.63 [0.55-0.71]) vs. stage IV, multi-disciplinary meeting (MDM) (HR=0.78 [0.69-0.88]). Among the above characteristics, exploratory analyses indicated: years of 2012-2014 (HR=1.46 [1.23-1.74]), 2015-2017 (HR=1.35 [1.14-1.61]) and 2020 (HR=1.55 [1.07-2.22]) associated with a worse OS; while MDM (HR=0.83 [0.71-0.96]) with a better OS, in addition to stages I, II & III. The impact of TI on OS demonstrated as a U shape: TIs before and after week 8 were towards the risk of death, especially during week 1 (HR=1.63 [1.15-2.30]), week 2 (HR=1.42 [1.00-2.02]) and week 3 (HR=1.50 [1.06-2.12]).

 

Conclusions: Informative results on the length and risk factors of the time to lung cancer treatment could provide valuable insights into policy-making and clinical practice regarding how to reduce the time interval for a better outcome. The observed “waiting time paradox” in the prognostic impact suggests patients with more severe diseases were treated earlier.