Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening

Horeweg, Nanda; Rosmalen, Joost van; Heuvelmans, Marjolein A; Aalst, Carlijn M. van der; Vliegenthart, Rozemarijn; Scholten, Ernst Th.; Haaf, Kevin ten; Nackaerts, Kristiaan; Lammers, Jan‐Willem J.; Weenink, Carla; Groen, Harry J.M.; Ooijen, Peter M. A. van; Jong, Pim A. de; Bock, Geertruida H. de; Mali, Willem P.Th.M.; Koning, Harry J. de; Oudkerk, Matthijs

doi:10.1016/s1470-2045(14)70389-4

Cited by 408 publications

(346 citation statements)

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“…Information on growth patterns of lung cancer is of great importance, since after the introduction and continual improvement of CT, and the more recent introduction of lung cancer screening by LDCT, a large number of nodules with smaller dimensions is detected, most being benign [2][3][4]. For those smallto-intermediate sized pulmonary nodules, the definitive diagnosis still remains a dilemma for radiologists.…”

Section: Discussionmentioning

confidence: 99%

“…For intermediate-sized nodules, the decision for (invasive) workup usually depends on growth rate. The malignant potential of these nodules is often suggested by rapid growth rate in terms of a short VDT [4,20]. The use of VDT, however, is based on the assumption of an exponential growth pattern of lung cancers.…”

Section: Discussionmentioning

confidence: 99%

“…In vivo information on lung cancer growth patterns, from small nodules barely detectable by imaging techniques (∼15 mm 3 ) to histologically proven lung cancers, is therefore scarce. With the introduction of low-dose computed tomography (LDCT) lung cancer screening, small-to-intermediate sized nodules, usually benign, are found in the majority of screenees [2][3][4]. Follow-up CTs are performed to determine nodule growth, in order to differentiate between benign and malignant nodules.…”

Section: Introductionmentioning

confidence: 99%

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Quantification of growth patterns of screen-detected lung cancers: The NELSON study

et al. 2017

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a b s t r a c tObjectives: Although exponential growth is assumed for lung cancer, this has never been quantified in vivo. Aim of this study was to evaluate and quantify growth patterns of lung cancers detected in the Dutch-Belgian low-dose computed tomography (CT) lung cancer screening trial (NELSON), in order to elucidate the development and progression of early lung cancer. Materials and methods: Solid lung nodules found at ≥3 CT examinations before lung cancer diagnosis were included. Lung cancer volume (V) growth curves were fitted with a single exponential, expressed as V = V 1 exp(t/ ), with t time from baseline (days), V 1 estimated baseline volume (mm 3 ), and estimated time constant. The R 2 coefficient of determination was used to evaluate goodness of fit. Overall volumedoubling time for the individual lung cancer is given by * log(2). Results: Forty-seven lung cancers in 46 participants were included. Forty participants were male (87.0%); mean age was 61.7 years (standard deviation, 6.2 years). Median nodule size at baseline was 99.5 mm 3 (IQR: 46.8-261.8 mm 3 ). Nodules were followed for a median of 770 days (inter-quartile range: 383-1102 days) before lung cancer diagnosis. One cancer (2.1%) was diagnosed after six CT examinations, six cancers (12.8%) were diagnosed after five CTs, 14 (29.8%) after four CTs, and 26 cancers (55.3%) after three CTs. Lung cancer growth could be described by an exponential function with excellent goodness of fit (R 2 0.98). Median overall volume-doubling time was 348 days (inter-quartile range: 222-492 days). Conclusion: This study based on CT lung cancer screening provides in vivo evidence that growth of cancerous small-to-intermediate sized lung nodules detected at low-dose CT lung cancer screening can be described by an exponential function such as volume-doubling time.© 2017 Elsevier B.V. All rights reserved.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantification of growth patterns of screen-detected lung cancers: The NELSON study

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“…Recently the NELSON trial has provided a recommendation for calculating indeterminate nodule risk based on their own trial data which also included volumetric measurements (25). Data from the NELSON CT screening trial was utilized to quantify how nodule diameter, volume, and volume doubling time affect the probability of developing lung cancer within two years of a CT scan and based on this they proposed thresholds for management protocols.…”

Section: Risk Models To Evaluate "Indeterminate Nodules"mentioning

confidence: 99%

Risk prediction models in lung cancer: The methodology for identifying high risk individuals for future lung cancer computed tomography (CT) screening programs

Field¹,

Marcus²

2015

AACR Education book

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The results of the US National Lung Screening Trial (NLST) were published in 2011 and are considered a landmark event in lung cancer research (1). This randomized study of 53,454 individuals showed that computed tomography (CT) scans are able to reduce lung cancer mortality by 20 percent through early detection, although with important cost and morbidity due to overdiagnosis and treatment of benign nodules. (2) Several European lung cancer screening trials have also been initiated, with the largest being the NELSON trial in the Netherlands (3) and the plan is to pool data from a number of European trials (4). Clearly, screening tools that are able to identify lung cancers at an early stage have much potential to reduce the enormous burden on lung cancer mortality (5). There are now discussions on how implementation may be put in place across the world, within differing health care systems (6). The success of lung cancer screening will be dependent upon identifying populations at sufficient risk in order to maximize the benefit-to-harm ratio of the intervention.The recommendation from the US Preventive Task Forces is based on the US NLST trial, includes screening all individuals between the ages of 55 and 80 with a smoking history of 30 pack-years or more (one pack-year is 20 cigarettes/day for one year or 10 cigarettes/day for two years, etc.) (7). An in-depth analysis of the NLST showed that there were significant differences in the number of lung cancer cases detected based on underlying risk, even though all participants had satisfied the criteria for participation in the study and were considered at high risk: 60 percent of participants at highest risk for lung-cancer death (quintiles 3 through 5) accounted for 88 percent of the prevented deaths, whereas the 20 percent of participants at lowest risk (quintile 1) accounted for only 1 percent of prevented lung-cancer deaths (8). Risk Prediction ModelsThus, accurate selection of high-risk individuals for lung cancer screening requires robust methods for risk prediction (Fig. 1). The discriminative performance of a risk model depends

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“…It's of note that the probability was not significantly different between the NELSON participants with nodules <100 mm 3 compared to those with no CT detected nodules in the trial (0.6% vs. 0.4%). However, individuals with 100-300 mm 3 nodal volume had a higher probability of developing lung cancer (2.4%) and were considered indeterminate with intermediate risk; whilst the participants with nodules greater than 300 mm 3 had a significantly greater risk compared to no nodules (16.9%) and thus had a very high probability of developing lung cancer (21). A very important message was provided on examining the NELSON volume doubling time data; the 2-year probability of developing lung cancer in patients with nodules measuring 50-100 mm 3 (or 4-5 mm diameter) was extremely low and did not significantly differ from patients with no CT scan detected nodules.…”

mentioning

confidence: 99%

Risk assessment in relation to the detection of small pulmonary nodules

Field¹,

Marcus²,

Oudkerk³

2017

Transl. Lung Cancer Res.

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Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening

Cited by 408 publications

References 30 publications

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

Risk prediction models in lung cancer: The methodology for identifying high risk individuals for future lung cancer computed tomography (CT) screening programs

Risk assessment in relation to the detection of small pulmonary nodules

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