CANCER EPIDEMIOLOGY, BIOMARKERS & PREVENTION | RESEARCH ARTICLE Timeliness of Lung Cancer Care and Area-Level Determinants in Victoria: A Bayesian Spatiotemporal Analysis Getayeneh Antehunegn Tesema 1,2 , Zemenu Tadesse Tessema 1,2 , Stephane Heritier 1 , Rob G. Stirling 3,4 , and Arul Earnest 1 � ABSTRACT Background: The reports have stated that the timeliness of lung cancer care varies significantly across different regions. According to the Victorian Lung Cancer Registry report, the timeliness of lung cancer care in Victoria has changed over time. Therefore, we aimed to quantify the extent of these spatial in- equalities over time and to identify area-level determinants contributing to these changes. Methods: The study analyzed lung cancer cases reported to the Victorian Lung Cancer Registry between 2011 and 2022. Bayesian spatiotemporal conditional autoregressive models were fitted, incorporating spatial random effects, temporal random effects, and spatiotemporal interactions. The best performing model was selected using the deviance information criterion. For the final best fit model, the adjusted RRs and their 95% credible intervals were reported. Results: More than half (51.24%) of patients with lung cancer experienced treatment delays, whereas approximately one third (30.98%) encountered diagnostic delays. Moderate spatiotempo- ral variations were observed in both delayed diagnosis and treatment. In the final best fit model for treatment delay, an increase in the percentage of smokers was significantly associated with a higher risk of treatment delay (RR ¼ 2.13; 95% credible interval, 1.13–4.20). Conclusions: Identifying high-risk areas provides useful in- formation for policymakers, helping in the reduction of delays in lung cancer diagnosis and treatment. Impact: This study has revealed spatiotemporal inequalities in diagnostic and treatment delays, providing valuable insights for identifying areas that should be prioritized to ensure timely care for lung cancer. Introduction Lung cancer is the second leading cause of cancer-related mor- tality worldwide (1). In 2020, more than 1.8 million deaths and 2.21 million new cases were reported globally (2). It continues to be a major global public health problem, including in Australia (3). Lung cancer represents 9.1% of all new cancer diagnoses in Aus- tralia and has the highest cancer mortality rate in both sexes (3, 4). Despite the ongoing cancer prevention efforts in Australia (5, 6), lung cancer remains the fifth most commonly diagnosed cancer and the leading cause of cancer death (6). It is the largest contributor to the overall cancer burden (7) and the fourth most common cancer in Victoria, accounting for 9% of all new cases diagnosed in 2021, among females and males. In 2021, approximately 1,746 males and 1,507 females were diagnosed with lung cancer, corresponding to an incidence rate of 26.3 new cases per 100,000 among males and 21.0 cases per 100,000 among females (8). Lung cancer treatment demands intricate, coordinated, and specialized services (9). Timely access to appropriate, affordable, and high-quality cancer care is crucial for improving patient survival and prognosis (10, 11). Although considerable efforts have been made to reduce and hasten the referral process for those suspected of having lung cancer, the majority of patients still present with advanced stage disease (12, 13). The timeliness of lung cancer care is a direct indicator of the accessibility and availability of healthcare services (14–16). Patient prognosis and treatment outcomes are poor when diag- nosis and treatment are delayed (12, 17). The majority of patients with lung cancer have been diagnosed late, owing to the lack of early detection of symptoms specific to lung cancer and the absence of an established lung cancer screening system to detect early-stage dis- ease (18). Delays in lung cancer care are strongly linked to an in- creased risk of mortality, distant metastasis, and poor treatment outcomes, including prolonged anxiety and distress (19–21). Previous research has shown that patients with lung cancer in remote areas experience poor access to optimal treatment (22). A recent study in Victoria reported a median time of 15 days from referral to diagnosis and 53 days to definitive treatment (23). Pa- tients in remote areas are diagnosed later than their metropolitan counterparts (24, 25). Current evidence demonstrates the presence of disparity in delayed care among patients with lung cancer based on the level of remoteness and the socioeconomic index of areas (SEIFA; refs. 7, 26, 27). The study demonstrated that patients with lung cancer who belonged to socioeconomically disadvantaged groups had a higher risk of delay in seeking cancer care. Studies have identified the determinants of delayed care for lung cancer at the individual level (28, 29). However, they failed to ac- count for the area-level determinants including SEIFA and re- moteness. Additionally, there is no published study on the spatiotemporal patterns of timeliness of lung cancer care in Victoria, Australia. Therefore, it is crucial to assess whether optimal care is delivered at an expected level across areas and over time. To address this knowledge gap, we conducted a spatiotemporal analysis of the 1 School of Public Health and Preventive Medicine, Monash University, Mel- bourne, Australia. 2 Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia. 3 Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia. 4 Department of Respiratory Medicine, Alfred Health, Melbourne, Australia. Corresponding Author: Arul Earnest, School of Public Health and Preventive Medicine, Monash University, Room 415, Level 4, 553 St Kilda Road, Mel- bourne, VIC 3004. E-mail: Arul.Earnest@monash.edu Cancer Epidemiol Biomarkers Prev 2025;34:308–16 doi: 10.1158/1055-9965.EPI-24-0205 ©2024 American Association for Cancer Research AACRJournals.org | 308 Downloaded from http://aacrjournals.org/cebp/article-pdf/34/2/308/3537228/epi-24-0205.pdf by Monash University Library user on 08 March 2025