Risk‐based selection from the general population in a screening trial: Selection criteria, recruitment and power for the Dutch‐Belgian randomised lung cancer multi‐slice CT screening trial (NELSON)

作者：Carola A. van Iersel, Harry J. de Koning, Gerrit Draisma, Willem P.Th.M. Mali, Ernst T. Scholten, Kristiaan Nackaerts, Mathias Prokop, J. Dik F. Habbema, Mathijs Oudkerk, Rob J. van Klaveren · 发表于：International Journal of Cancer · 年份：2006 · DOI：10.1002/ijc.22134 · 被引用次数：497 · 研究领域：Lung Cancer Diagnosis and Treatment、Global Cancer Incidence and Screening、Lung Cancer Treatments and Mutations

A method to obtain the optimal selection criteria, taking into account available resources and capacity and the impact on power, is presented for the Dutch-Belgian randomised lung cancer screening trial (NELSON). NELSON investigates whether 16-detector multi-slice computed tomography screening will decrease lung cancer mortality compared to no screening. A questionnaire was sent to 335,441 (mainly) men, aged 50-75. Smoking exposure (years smoked, cigarettes/day, years quit) was determined, and expected lung cancer mortality was estimated for different selection scenarios for the 106,931 respondents, using lung cancer mortality data by level of smoking exposure (US Cancer Prevention Study I and II). Selection criteria were chosen so that the required response among eligible subjects to reach sufficient sample size was minimised and the required sample size was within our capacity. Inviting current and former smokers (quit 15 cigarettes/day during >25 years or >10 cigarettes/day during >30 years was most optimal. With a power of 80%, 17,300-27,900 participants are needed to show a 20-25% lung cancer mortality reduction 10 years after randomisation. Until October 18, 2005 11,103 (first recruitment round) and 4,325 (second recruitment round) (total = 15,428) participants have been randomised. Selecting participants for lung cancer screening trials based on risk estimates is feasible and helpful to minimize sample size and costs. When pooling with Danish trial data (n = +/-4,000) ...