Evaluating the clinical trends and benefits of low-dose computed tomography in lung cancer patients

Despite guideline recommendations, utilization of low-dose computed tomography (LDCT) for lung cancer screening remains low. The driving factors behind these low rates and the real-world effect of LDCT utilization on lung cancer outcomes remain limited.

We identified patients diagnosed with non-small cell lung cancer (NSCLC) from 2015 to 2017 within the Veterans Health Administration. Multivariable logistic regression assessed the influence of LDCT screening on stage at diagnosis. Lead time correction using published LDCT lead times was performed. Cancer-specific mortality (CSM) was evaluated using Fine-Gray regression with non-cancer death as a competing risk. A lasso machine learning model identified important predictors for receiving LDCT screening.

Among 4664 patients, mean age was 67.8 with 58-month median follow-up, 95% CI = [7-71], and 118 patients received ≥1 screening LDCT before NSCLC diagnosis. From 2015 to 2017, LDCT screening increased (0.1%-6.6%, mean = 1.3%). Compared with no screening, patients with ≥1 LDCT were more than twice as likely to present with stage I disease at diagnosis (odds ratio [OR] 2.16 [95% CI 1.46-3.20]) and less than half as likely to present with stage IV (OR 0.38 [CI 0.21-0.70]). Screened patients had lower risk of CSM even after adjusting for LDCT lead time (subdistribution hazard ratio 0.60 [CI 0.42-0.85]). The machine learning model achieved an area under curve of 0.87 and identified diagnosis year and region as the most important predictors for receiving LDCT. White, non-Hispanic patients were more likely to receive LDCT screening, whereas minority, older, female, and unemployed patients were less likely.

Utilization of LDCT screening is increasing, although remains low. Consistent with randomized data, LDCT-screened patients were diagnosed at earlier stages and had lower CSM. LDCT availability appeared to be the main predictor of utilization. Providing access to more patients, including those in diverse racial and socioeconomic groups, should be a priority.