Evaluating the impact of varied compliance to lung cancer screening recommendations using a microsimulation model

Abstract

Background The US preventive services task force (USPSTF) recently recommended that individuals aged 55–80 with heavy smoking history be annually screened by low-dose computed tomography (LDCT), thereby extending the stopping age from 74 to 80 compared to the national lung screening trial (NLST) entry criterion. This decision was made partly with model-based analyses from cancer intervention and surveillance modeling network (CISNET), which assumed perfect compliance to screening. Methods As part of CISNET, we developed a microsimulation model for lung cancer (LC) screening and calibrated and validated it using data from NLST and the prostate, lung, colorectal, and ovarian cancer screening trial (PLCO), respectively. We evaluated population-level outcomes of the lifetime screening program recommended by the USPSTF by varying screening compliance levels. Results Validation using PLCO shows that our model reproduces observed PLCO outcomes, predicting 884 LC cases [Expected(E)/Observed(O) = 0.99; CI 0.92–1.06] and 563 LC deaths (E/O = 0.94 CI 0.87–1.03) in the screening arm that has an average compliance rate of 87.9% over four annual screening rounds. We predict that perfect compliance to the USPSTF recommendation saves 501 LC deaths per 100,000 persons in the 1950 U.S. birth cohort; however, assuming that compliance behaviors extrapolated and varied from PLCO reduces the number of LC deaths avoided to 258, 230, and 175 as the average compliance rate over 26 annual screening rounds changes from 100 to 46, 39, and 29%, respectively. Conclusion The implementation of the USPSTF recommendation is expected to contribute to a reduction in LC deaths, but the magnitude of the reduction will likely be heavily influenced by screening compliance.

Determinants Associated With Longitudinal Adherence to Annual Lung Cancer Screening: A Retrospective Analysis of Claims Data

“…Similar stage I lung cancer detection (58%), reduced lung cancer mortality (25% at 10 years), and adherence to screening (90%) were recently reported in another large study [4]. Microsimulation modeling predicts a halving of screening benefit when annual screening adherence falls below 50% [8]. Similarly, stage shift from late-to earlystage disease is reduced as the screening interval is increased [9].…”

Supportive Care in Radiotherapy Based on a Mobile App: Prospective Multicenter Survey

“…Several studies have shown that patient compliance plays a special role in the successful implementation of mHealth initiatives [ 19 ]. Clinical experience in oncology shows patient compliance to be worse in subgroups with lifestyle-related risk factors (eg, heavy smoking and alcohol abuse), potentially making such patients less eligible for mHealth-based support [ 20 , 21 ]. However, evidence exists that offering mHealth support in addition to close clinical surveillance may improve patient compliance, particularly in the abovementioned subgroups, by providing regular prompts and reminders and facilitating adherence to prescribed exercises or supportive regimens [ 22 - 24 ].…”

Patterns and Factors Associated With Adherence to Lung Cancer Screening in Diverse Practice Settings

“… 6 , 7 , 8 , 9 However, for LCS to achieve similar long-term effectiveness in real-world practice, successful completion of multiple steps, including individuals returning for annual LDCT screening, is vital. 10 …”