Early lung-cancer detection with spiral CT and positron emission tomography in heavy smokers: 2-year results

Pastorino, Ugo; Bellomi, Massimo; Landoni, Claudio; Fiori, Elvio De; Arnaldi, Patrizia; Picchio, Maria; Pelosi, Giuseppe; Boyle, Peter; Fazio, Ferruccio

doi:10.1016/s0140-6736(03)14188-8

Cited by 416 publications

(323 citation statements)

References 29 publications

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“…The design and the 2 years results of the early detection trial have been reported in detail. 7 Concurrently, we conducted a case-control study that includes 29 tumor samples obtained from consecutive CT-detected and surgically resected lung cancer patients, of which 18 had tumor-sputum pairs available for the analysis, and 112 consecutive heavy smokers from the 1,035 study participants, who had a sample of sputum available and remained cancer free over the 4 years of the study. For each case, 4 cancer-free smokers were randomly selected from the cohort to obtain the best matching of control group by sex, age and smoking exposure (pack/years), with this order of priority.…”

Section: Patients and Collection Of Sputum And Tumor Samplesmentioning

confidence: 99%

“…The latter was compared to that observed in 112 cancer-free heavy smokers enrolled in the ongoing spiral CT trial. 7 We based our choice of the genes on the consideration that a panel of genes whose inactivation occurs at different stages of malignant transformation should be used in our longitudinal study. Thus, an early marker such as RARb2, an early/intermediate marker such as p16 INK4A and a later marker such as RASSF1 were evaluated.…”

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confidence: 99%

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Methylation profile in tumor and sputum samples of lung cancer patients detected by spiral computed tomography: A nested case–control study

Cirincione

Lintas

Conte

et al. 2005

Intl Journal of Cancer

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We evaluated the aberrant promoter methylation profile of a panel of 3 genes in DNA from tumor and sputum samples, in view of a complementary approach to spiral computed tomography (CT) for early diagnosis of lung cancer. The aberrant promoter methylation of RARb2, p16 INK4A and RASSF1A genes was evaluated by methylation-specific PCR in tumor samples of 29 CTdetected lung cancer patients, of which 18 had tumor-sputum pairs available for the analysis, and in the sputum samples from 112 cancer-free heavy smokers enrolled in a spiral CT trial. In tumor samples from 29 spiral CT-detected patients, promoter hypermethylation was identified in 19/29 (65.5%) cases for RARb2, 12/29 (41.4%) for p16 INK4A and 15/29 (51.7%) for RASSF1A. Twenty-three of twenty-nine (79.3%) samples of the tumors exhibited methylation in at least 1 gene. In the sputum samples of 18 patients, methylation was detected in 8/18 (44.4%) for RARb2 and 1/18 (5%) for both RASSF1A and p16 INK4A . At least 1 gene was methylated in 9/18 (50%) sputum samples. Promoter hypermethylation in sputum from 112 cancer-free smokers was observed in 58/112 (51.7%) for RARb2 and 20/112 (17.8%) for p16, whereas methylation of the RASSF1A gene was found in only 1/112 (0.9%) sputum sample. Our study indicates that a high frequency of hypermethylation for RARb2, p16 INK4A and RASSF1A promoters is present in spiral CT-detected tumors, whereas promoter hypermethylation of this panel of genes in uninduced sputum has a limited diagnostic value in early lung cancer detection. ' 2005 Wiley-Liss, Inc.Key words: lung cancer; methylation; sputum; spiral CT Lung cancer is the leading cause of cancer deaths in the world. Although surgical resection still represents the best curative approach for this neoplasm, its efficacy strictly depends on the stage of disease presentation. Earlier diagnosis of patients with lung cancer is expected to increase the number of potentially resectable tumors. 1 Several large prospective randomized trials have demonstrated that conventional sputum cytology and chest radiography are not effective in detecting early lung cancer and reducing lung cancer mortality. 2 In this respect, over the last decade, spiral computed tomography (CT) has been tested as a powerful and fast imaging technique to detect tumors of less than 1 cm in diameter, with a proportion of detection of Stage I tumors greater than 80%, opening new possibilities for the early detection of lung cancer. 3,4 However, because of the complex algorithm of high-resolution CT employed in order to achieve the maximal performance of this approach 3 and to achieve the background noise created by the high detection rate of noncalcified nodules, 5 questions have been raised about the challenge of differential diagnosis, efficacy and costs of spiral CT screening. 6 In 2000, a prospective trial of early lung cancer detection was launched in Milan, using repeated yearly low-dose spiral CT, selective use of positron emission tomography and analysis of molecular markers in a large cohort of 1,035 high-...

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Section: Patients and Collection Of Sputum And Tumor Samplesmentioning

confidence: 99%

mentioning

confidence: 99%

Methylation profile in tumor and sputum samples of lung cancer patients detected by spiral computed tomography: A nested case–control study

Cirincione

Lintas

Conte

et al. 2005

Intl Journal of Cancer

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“…Selection criteria for single armed lung cancer screening studies and ongoing and planned trials show some variability in smoking exposure and age selection criteria. 4,[8][9][10][11][12][13][14][15][16][17] This variability can cause differences in characteristics of the trial population and cancer detection rates. Purpose of this study was to describe a method to come to an optimum selection and recruitment of the eligible population for a lung cancer screening trial, taking into account available resources and screening capacity and the influence that selection criteria have on the estimated lung cancer mortality and the power of such a trial.…”

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confidence: 99%

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)

Iersel

Koning

Draisma

et al. 2006

Intl Journal of Cancer

440

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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 10 years ago) who smoked >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 5 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 5 64,000) NELSON is the only trial without screening in controls that is expected to have 80% power to show a lung cancer mortality reduction of at least 25% 10 years after randomisation. ' 2006 Wiley-Liss, Inc.Key words: lung cancer; screening; computed tomography; power; risk estimation Lung cancer is the most common cause of cancer-related death in men and the second most common cause of cancer-related death in women in Europe. 1 Because lung cancer is often in an advanced stage at the time of diagnosis, 5-year-survival is only 15% or less. 2 Japanese studies and the US Early Lung Cancer Action Project (ELCAP) showed that in a high-risk population more lung cancers can be detected by spiral computed tomography (CT) screening than by chest X-ray screening. 3,4 These and other observational studies with spiral CT screening showed that 55-85% of CTdetected lung cancers at baseline screening in a high-risk population of current and former smokers are at a surgically removable stage (stage I). 5 Although these results seem promising, observational studies are prone to lead-time, length-time and overdiagnosis bias. Only in a randomised design, disease-specific mortality between the screened and the unscreened population, instead of survival, can be compared. Lead-time, length-time and overdiagnosis do not bias the analysis in such comparisons. 6 Therefore, in the United States the National Lung Screening Trial (NLST) was launched in 2002 7 and in the Netherlands and Belgium, the NEL-SON trial, a Dutch acronym for ÔDutch-Belgian lu...

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“…On CT, lung cancer commonly manifests as a non-calcified pulmonary nodule. The increasing use of CT for pulmonary applications, including its potential use as a screening tool for early lung cancer detection, has magnified the need to develop better non-invasive methods for distinguishing benign from malignant nodules (2)(3)(4)(5)(6)(7)(8)(9).…”

Section: Introductionmentioning

confidence: 99%

“…Swensen et al found that 51% of low dose screening CT examinations revealed lung nodules (4). Only 1-10% of indeterminate nodules will eventually be diagnosed as malignant (2,3,(6)(7)(8)(9); the vast majority of cancers being larger than 4 mm diameter at first detection. While most nodules detected on screening are sub-centimeter in diameter, and the mean size of CT-detected cancers detected ranges from 13.4 mm to 18 mm (4, 6, 7 and 9), it is still important to develop reliable noninvasive methods for identifying malignant lesions.…”

Section: Introductionmentioning

confidence: 99%

Pulmonary nodule characterization: A comparison of conventional with quantitative and visual semi-quantitative analyses using contrast enhancement maps

Petkovska

Shah

McNitt-Gray

et al. 2006

European Journal of Radiology

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Purpose-To determine whether conventional nodule densitometry or analysis based on contrast enhancement maps of indeterminate lung nodules imaged with contrast-enhanced CT can distinguish benign from malignant lung nodules.Materials and Method-Thin section, contrast-enhanced CT (baseline, and post-contrast series acquired at 45, 90,180, and 360 seconds) was performed on 29 patients with indeterminate lung nodules (14 benign, 15 malignant). A thoracic radiologist identified the boundary of each nodule using semi-automated contouring to form a 3D region-of-interest (ROI) on each image series. The post-contrast series having the maximum mean enhancement was then volumetrically registered to the baseline series. The two series were subtracted volumetrically and the subtracted voxels were quantized into seven color-coded bins, forming a contrast enhancement map (CEM). Conventional nodule densitometry was performed to obtain the maximum difference in mean enhancement values for each nodule from a circular ROI. Three thoracic radiologists performed visual semi-quantitative analysis of each nodule, scoring each map for (a) magnitude and (b) heterogeneity of enhancement throughout the entire volume of the nodule on a 5-point scale. Receiver operator characteristic (ROC) analysis was conducted on these features to evaluate their diagnostic efficacy. Finally, 14 quantitative texture features were calculated for each map. A statistical analysis was performed to combine the 14 texture features to a single factor. ROC analysis of the derived aggregate factor was done as an indicator of malignancy. All features were analyzed for differences between benign and malignant nodules.Results-Using 15 HU as a threshold, 93% (14/15) of malignant and 79% (11/14) of benign nodules demonstrated enhancement. The ROC curve when higher values of enhancement indicate malignancy was generated and area under the curve (AUC) was 0.76. The visually scored magnitude of enhancement was found to be less effective in distinguishing malignant from benign lesions, with an average AUC of 0.62. The visually scored pattern of enhancement was found to be more effective

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Early lung-cancer detection with spiral CT and positron emission tomography in heavy smokers: 2-year results

Cited by 416 publications

References 29 publications

Methylation profile in tumor and sputum samples of lung cancer patients detected by spiral computed tomography: A nested case–control study

Methylation profile in tumor and sputum samples of lung cancer patients detected by spiral computed tomography: A nested case–control study

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)

Pulmonary nodule characterization: A comparison of conventional with quantitative and visual semi-quantitative analyses using contrast enhancement maps

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