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Keywords:

  • lung cancer;
  • computed tomography;
  • mean sojourn time;
  • Bayesian approach

Abstract

This study aimed to estimate the mean sojourn time (MST) and sensitivity of asymptomatic lung cancer (ALC) detected by computed tomography (CT) or chest X-ray (CXR). Translation of early diagnosis into mortality reduction by 2 detection modalities and inter-screening interval was projected using a Markov model. On the basis of systematic literature review, data from 6 prospective CT screening studies were retrieved. The MST in association with the natural history of lung cancer depicted by a 3-state Markov model was estimated with a Bayesian approach. To project mortality reduction attributed to screening, the model was further extended to 5 health states for the inclusion of prognostic part. The analysis was run with a 10-year time horizon of follow-up, mimicking the Dutch-Belgian randomized lung cancer screening trial (NELSON). Screening for lung cancer with CT had high sensitivity (median: 97%) and may advance 1 year earlier than CXR in detecting ALC. By simulating the scenario similar to NELSON study, CT screen may gain an extra of 0.019 year of life expectancy per person, yields 15% mortality reduction (relative risk (RR): 0.85, 95% confidence interval [95%CI: (0.58–1.01)]. Approximate 23% [RR: 0.77, 95%CI: (0.43–0.98)] mortality reduction would be achieved by annual CT screening program. The mortality findings in conjunction with higher sensitivity and shorter MST estimate given data on prevalent and incident (2nd) screen may provide a tentative evidence, suggesting that annual CT screening may be required in order to be effective in reducing mortality before the results of randomized controlled studies available. © 2008 Wiley-Liss, Inc.