Comparative analysis of 5 lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials

Abstract

Background The National Lung Screening Trial (NLST) demonstrated that low-dose CT screening is an effective way of reducing lung cancer (LC) mortality. However, optimal screening strategies have not been determined yet and it is uncertain whether lighter smokers than those in NLST may also benefit from screening. To address these questions, it is necessary to first develop LC natural history models that can reproduce NLST outcomes and simulate screening programs at the population level. Methods Five independent LC screening models were developed using common inputs and calibration targets derived from NLST and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). Imputation of missing smoking, histology and stage information for a small fraction of individuals and diagnosed LCs in both trials was performed. Models were calibrated to LC incidence, mortality or both outcomes simultaneously. Results Initially, all models were calibrated to NLST and validated against PLCO. Models validated well against PLCO individuals who would have been eligible to NLST. However, all models required further calibration to PLCO to adequately capture LC outcomes in PLCO never and light smokers. Final versions of all models produced incidence and mortality outcomes in the presence and absence of screening consistent with both trials. Conclusions We developed five distinct LC screening simulation models based on the evidence in NLST and PLCO. Our analyses demonstrate that NLST and PLCO have produced consistent results. The resulting models can be important tools to generate additional evidence to determine the effectiveness of low-dose CT lung cancer screening strategies.

Personalizing annual lung cancer screening for patients with chronic obstructive pulmonary disease: A decision analysis

“…Additional information from modeling studies may provide insight into how the NLST results may translate to the general population. 40-41 …”

“…Model outputs are calibrated to observed outcomes and tumor registry data from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. 18 Additional details of the LCPM and model inputs have been previously described 19-20 and are available online 14 and summarized in the Appendix (see eAppendix, eTable 1, eFigure 1). In the sections below, we describe the approach used to incorporate spirometry-defined COPD as a risk factor for LC.…”

Should Never-Smokers at Increased Risk for Lung Cancer Be Screened?

“…MISCAN-Lung has been calibrated to the NLST, the Prostate, Lung, Colorectal and Ovarian Cancer Screening trial (PLCO), and data from the Surveillance, Epidemiology and End Results (SEER) Program, from which it derived information on the preclinical duration of lung cancer and CT screening effectiveness. 26, 27 Lung cancer incidence and mortality in never-smokers in the PLCO were among the calibration targets of the model. 26, 27 MISCAN-Lung aided in informing the USPSTF on their recommendations for lung cancer screening.…”

“…26, 27 Lung cancer incidence and mortality in never-smokers in the PLCO were among the calibration targets of the model. 26, 27 MISCAN-Lung aided in informing the USPSTF on their recommendations for lung cancer screening. 25, 28 …”

Recent progress and future direction of cancer epidemiological research in Japan

“…In order to substitute this deficit, various types of simulation models are developed. For example, Cancer Intervention and Surveillance Modeling Network (CISNET) cover several cancer sites in this aspect and actually provide data on guideline developments or cancer control planning (15). This type of research is still very immature in Japan and the funding agency should have initiatives to promote it by combining multidisciplinary research groups.…”