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U. Pastorino



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    MINI 14 - Pre-Clinical Therapy (ID 119)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 1
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      MINI14.11 - Establishment of a Lung Cancer Patient-Derived Xenografts Panel (ID 2607)

      11:45 - 11:50  |  Author(s): U. Pastorino

      • Abstract
      • Presentation
      • Slides

      Background:
      Studies based on cell lines were found to be poor predictors of clinical effects and therefore in many cases translation of the results into the clinics failed. A major determinant for the poor performance of cell lines is the observation that cell lines do not reflect the whole complexity and heterogeneity of primary tumors. A growing body of work suggests that Patient-Derived Xenografts (PDX) represent a more informative cancer model, providing a faithful representation of the patient’s original tumor.

      Methods:
      PDX were obtained by direct implants of small tumor fragments (30mm[3]) in previously anesthetized SCID mice, and were subsequently passaged as tissue explants. PDX metabolic in vivo imaging was performed using weekly [18F]FDG-PET and coronal and 3D-reconstruction at different days. Analysis of mutations and copy number alterations of PDX and human constitutive and tumoural DNA was performed by SALSA MLPA® probe mix X050-A1 Lung Cancer (MRC Holland).

      Results:
      Tumor samples from 95 lung cancer patients (66 AC, 16 SCC and 13 other lung cancer histotypes (OL)) have been implanted in the flanks of SCID mice. Overall, 36 samples (37,9%) successfully grafted and were propagated for at least 3 passages in immunocompromised mice. Take rate was 34,8 % (23/66) in AC, 43,8% (7/16) in SCC and 46.1% (6/13) in OL (2 large cell carcinomas, 1 sarcomatoid carcinoma and 3 small cell carcinomas). A detailed immunohistochemical analysis of 27 PDX, at different passage in mice, confirmed that tumor histology, expression of specific markers (TTF-1, p40, Vimentin, Ki64 and Synaptophysin) and the amount of specific tumor cell subpopulations (i.e. CD133[+] Cancer Initiating Cells) were generally maintained in PDX. In vivo animal PET imaging showed that also metabolic activity of PDX was strictly correlated with parental tumor’s features, especially for tumours with a SUV~max~ level higher than 8 (R[2]=0.67, p<0.05). Mutation and copy number analyses, performed on 29 biological samples belonging to 11 different engrafted models, showed that genetic changes were maintained in PDX that well recapitulated the frequency of the major changes involved in lung cancer development (66.7% TP53; 60% CDKN2A, 40% LKB1, 40% KEAP1, 38.4% KRAS, 20% SWI/SNF, 20% PTEN, 8% ERBB2). Furthermore, we developed a freeze/thawing procedure on samples derived from PDXs that allows for 100% successfully thawing and established a large collection of more than 200 frozen PDX samples for future preclinical studies.

      Conclusion:
      The deep characterization of our established PDX panel confirmed that these mouse models recapitulate the parental primary tumors in terms of tumor histology, cellular and mutation pattern, metabolic activity and expression of specific markers for several passages in mice. All these data support the use of these “human in mouse” models for functional studies, highlighting the relevance of our PDX panel as a valuable platform for preclinical studies.

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    MINI 20 - Surgery (ID 137)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Treatment of Locoregional Disease – NSCLC
    • Presentations: 1
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      MINI20.05 - Discussant for MINI20.01, MINI20.02, MINI20.03, MINI20.04 (ID 3420)

      17:05 - 17:15  |  Author(s): U. Pastorino

      • Abstract
      • Presentation

      Abstract not provided

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    MS 24 - CT Screening: Minimize Harm/Cost and Risk Assessment (ID 42)

    • Event: WCLC 2015
    • Type: Mini Symposium
    • Track: Screening and Early Detection
    • Presentations: 1
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      MS24.03 - Role of PET Scan in Workup of Nodules (ID 1956)

      15:00 - 15:20  |  Author(s): U. Pastorino

      • Abstract
      • Presentation

      Abstract:
      Effective screening programs should detect all cancers and reduce as much as possible the probability of false-positive results, not representing malignant disease. In lung cancer screening, false-positive low-dose computed tomography (LDCT) results are even more crucial than in other fields, because of the magnitude of risks and costs related to invasive diagnostic examinations, and the need of potentially harmful surgical procedures. Long-term follow-up of nodules ≤ 5 mm at baseline CT has proven that these nodules don’t require additional workup, but for non-calcified nodules between 5 and 10 mm, surveillance of growth is mandatory to identify the relatively few malignant lesions. With the NLST diagnostic algorithm, based on diameter measurement, 24% of subjects had a positive LDCT but 96% of them proved to be false positives, with a positive predictive value (PPV) of only 3.6% at baseline, 2.4 first repeat and 5.2% at second repeat [1,2]. On the contrary, the diagnostic algorithm of Nelson trial, based on the automated assessment of 3D volumetry and doubling time, obtained a 36% PPV and a 99.9% negative predictive value (NPV) [3]. However, in the Nelson trial, where positron emission tomography (PET) was not included in the diagnostic algorithm, the frequency of invasive procedures for benign disease proved to be quite high (27%), and similar to the one observed in NLST trial (24%) [4]. Large meta-analyses have demonstrated the clinical value of PET in the differential diagnosis of undetermined pulmonary nodules detected by spiral CT, with a sensitivity rate of 96-97%, a specificity of 78-82% [5], and accuracy rate reaching 92% with the CT/PET fusion machine [6]. In 2000, our pilot study in Milan was the first screening protocol to include selective use of PET in the diagnostic algorhitm, thus showing that PET may be helpful in the management of CT detected nodules ≥ 7 mm. In the first five years of screening, PET was applied to only 1.4% of spiral CTs, with an overall sensitivity rate of 94%, specificity of 82%, and an accuracy rate of 88% [7,8]. In the Milan pilot trial, the cumulative frequency of surgical procedures for benign disease at 5 years was 15%. The MILD randomized trial has obtained similar results, in terms of frequency and diagnostic accuracy. From 2005 to 2015, a total of 113 PET were applied to 2376 individuals and 12,314 LDCTs, representing 4.8% of all screened individuals in 10 years, and 0.93% of all LDCTs. Excluding lung cancer cases, where PET would have been applied later for staging purposes, the true excess of PET examinations for screening purposes only reached a total 33 exams (1.4% of subjects, 0.3% of LDCTs). The sensitivity rate was 85%, specificity 80%, accuracy 83%, PPV 89% and NPV 74%. Of interest, only 3 patients underwent pulmonary resection for benign disease, out of 66 surgical procedures (5%) performed in the MILD trial. Such a low benign resection rate, is not only due to selective use of PET, but also to the active surveillance programme applied to non-solid lesions in the MILD trial. Beyond differential diagnosis, PET may play a role in prediction of outcome, and identification of indolent lung cancer. We have demonstrated in a previous paper, based on 34 lung cancer patients from the first pilot trial, that PET-SUV value can accurately predict long term survival and identify individuals with 100% 5-year survival [9]. In the MILD trial we have confirmed the value of metabolic profile as a predictor of outcome. The following figure illustrates the 5-year survival of 95 patients, from pilot and MILD trials. Figure 1 The possibility to combine metabolic profile with other biomarkers, such as circulating miRNAs [10], to identify indolent disease will require future investigations, to improve performance and reduce over-diagnosis of LDCT screening. 1 Aberle DR, Adams AM, Berg CD, et al. The National Lung Screening Trial Research Team (2011). Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 365:395-409. 2 Aberle DR, DeMello S, Berg CD, et al. (2013) Results of the Two Incidence Screenings in the National Lung Screening Trial. N Engl J Med 369:920-31. 3 van Klaveren RJ, Oudkerk M, Prokop M, et al. (2009) Management of lung nodules detected by volume CT scanning. N Engl J Med 361:2221-9. 4 Kramer BS, Berg CD, Aberle DR, Prorok PC. Lung cancer screening with low-dose helical CT: results from the National Lung Screening Trial (NLST). J Med Screen. 2011;18:109-111. 5 M.K. Gould, C.C. Maclean, W.G. Kuschner, et a. l(2001). Owens, Accuracy of positron emission tomography for diagnosis of pulmonary nodules and mass lesions: a meta-analysis. JAMA 285: 914–924. 6 Kim SK, Allen-Auerbach M, Goldin J, et al. (2007) Accuracy of PET/CT in characterization of solitary pulmonary lesions. J Nucl Med 48:214–220. 7 Pastorino U (2010) Lung Cancer Screening. British Journal of Cancer 102: 1681–1686 8 Veronesi G, Bellomi M, Veronesi U, et al. (2007) Role of positron emission tomography scanning in the management of lung nodules detected at baseline computed tomography screening. Ann Thorac Surg 84:959-66 9 Pastorino U, Landoni C, Marchianò A, et al. (2009) Fluorodeoxyglucose (FDG) uptake measured by positron emission tomography (PET) and standardised uptake value (SUV) predicts long-term survival of CT screening-detected lung cancer in heavy smokers. J Thor Oncol 11:1352-6 10. Sozzi G, Boeri M, Rossi M, et al: Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: A correlative MILD trial study. J Clin Oncol 32:768-773, 2014



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    MTE 21 - Early Detection of Central Airway Lesions: Biology and Practical Clinical Approaches (Ticketed Session) (ID 73)

    • Event: WCLC 2015
    • Type: Meet the Expert (Ticketed Session)
    • Track: Screening and Early Detection
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2015, 07:00 - 08:00, 703
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      MTE21.02 - Biomarkers for Early Detection of Lung Cancer (ID 2008)

      07:30 - 08:00  |  Author(s): U. Pastorino

      • Abstract
      • Presentation

      Abstract:
      Improvements in clinical management of lung cancer have been modest over the last 20 years, with an overall 5-year survival rate just above 10% in Europe and 16% in the United States. Treatment failure is mainly due to the presence of metastatic disease at diagnosis, occurring in 70% of all patients whereas in patients resected in stage IA the 5-year survival rate is higher than 70% [1]. Detection of lung cancer at an early stage offers the real potential to reduce mortality with new chances of cure. The outcomes of the National Lung Cancer Screening Trial (NLST) have highlighted favorable prospects for lung cancer low-dose CT screening (LDCT) but the cost benefit profile of screening is still matter of debate in the scientific community [2]. In particular, the high false positive rates of LDCT lead to multiple screening rounds, repeated radiation exposure, the use of invasive diagnostic follow–up procedures with associated morbidity as well as increased time and costs. In addition, LDCT screening showed a limited impact on the more aggressive lung cancers, achieving an overall mortality reduction of only 20%. Several studies have reported blood-based biomarkers for early detection of lung cancer but so far only few of them have proven useful in lung cancer clinical practice. Beside technical issues related to difficulties in protocol standardization and lack of large scale validation in clinical trials, genetic and biological tumor heterogeneity has likely limited the successful identification of tumor-specific markers. A ground-breaking way to identify novel and more reliable biomarkers is searching for candidates by looking not only at the tumor itself but also at the interplay between the tumor and the host with the aim to identify very early changes related to the biological reactivity of the host to a developing cancer. In this respect, epigenetic markers, above all circulating microRNAs (miRNAs), could represent ideal candidates since they act as extracellular messengers of biological signals derived from the cross-talk between the tumor and its surrounding microenvironment. MiRNA are short non-coding RNA emerged as critical regulators of gene expression playing a key role in physiological and pathological mechanism. Blood circulating miRNAs were also reported to be promising biomarkers for cancer detection and prognosis [3]. MiRNAs are released into the bloodstream by different mechanisms such as passive leakage of cellular miRNAs from broken cells or active secretion through microvesicles or protein complexes by several cell subtypes [4]. Although LDCT is currently the standard of care for early lung cancer detection, it results in a general over diagnosis of indolent nodules, thus increasing unnecessary confirmatory diagnostic procedures. Non-invasive circulating miRNA assays could overcome most of these problems by exploiting the synergy between the molecular and imaging tests to reduce the number of the false positives. Two groups, in 2011, identified specific plasma and serum miRNA signatures comparing samples from patients and disease free individuals collected in three independent LDCT screening trials [5;6]. Our group reported four signatures composed by reciprocal ratios among 24 miRNAs by comparing samples collected before (n=20) and at the time (n=19) of LDCT disease detection to those of 27 control samples belonging to the INT-IEO trial [7]. These signatures were initially validated in a subset of 88 samples collected from 22 patients and 54 controls enrolled in the MILD trial [8]. Three years later, the same group developed a miRNA signature classifier (MSC), containing the 24 miRNAs previously identified, and tested its performance in enlarged validation set composed of 85 patients and 1000 controls belonging to the MILD trial [9]. The results of this study showed that the combination of MSC and LDCT reduced LDCT false-positive rate from 19.4% to 3.7% and that the MSC risk groups were significantly associated with survival. In addition, MSC was high sensitive (87%) and specific (81%) and its predictive value was confirmed by time-dependency analysis. Bianchi et al. identified a 34 miRNA signature in serum samples from 59 patients enrolled in the COSMOS trial compared to 69 disease free individuals divided in training and testing sets. Globally, the test showed an AUC of 89% in the testing set, and it was also able to rule out cancer in 79% of benign lung nodules. In addition, the 34 miRNA signature did not discriminate benign or malignant breast nodules, emphasizing the specificity of the test for lung cancer. Finally, the test did not classify pre-disease plasma samples, thus limiting the capability of the test to predict the development of the disease. Very recently, the same group refined their signature to 13 miRNAs which was validated in an independent set of 1008 subjects enrolled in the COSMOS trial [10]. Interestingly, this signature displays overlap of five miRNAs with the MSC signature (38.5%), an encouraging finding given the well known difficulty in validating expression signatures in different studies and given the differences in samples collection between these two studies (i.e. plasma vs serum). More recently, taking advantage of two screening programs with a total follow up of 23,967 person-years and a median time follow-up of 5.9 years, we analyzed the prognostic value of MSC in 84 in lung cancer patients identified in LDCT screening programs. In addition, to test the ability of the plasma MSC to monitor the disease status and recurrence during follow up, the MSC test was employed to analyze 86 longitudinally-collected plasma samples obtained from patients before and after surgical resection of primary lung tumors with a follow up time up to 4.1 years. We demonstrated that the three MSC risk groups were associated with significant differences in overall survival for the 84 subjects examined, also when adjusting for tumor stage. Moreover, the MSC risk level significantly decreased in subjects who remained disease free whereas in all relapsing patients increase of the MSC risk level was observed at the time of detection of a second primary tumor or of metastatic progression. The results presented highlight the clinical usefulness of circulating miRNAs as diagnostic, prognostic and monitoring tool in lung cancer. References 1. Goldstraw P, Crowley J, Chansky K et al. The IASLC Lung Cancer Staging Project: proposals for the revision of the TNM stage groupings in the forthcoming (seventh) edition of the TNM Classification of malignant tumours. J Thorac Oncol 2007;2:706-14. 2. Aberle DR, Adams AM, Berg CD et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365:395-409. 3. Boeri M, Pastorino U, Sozzi G. Role of microRNAs in lung cancer: microRNA signatures in cancer prognosis. Cancer J 2012;18:268-74. 4. Schwarzenbach H, Nishida N, Calin GA, Pantel K. Clinical relevance of circulating cell-free microRNAs in cancer. Nat Rev Clin Oncol 2014;11:145-56. 5. Boeri M, Verri C, Conte D et al. MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer. Proc Natl Acad Sci U S A 2011;108:3713-8. 6. Bianchi F, Nicassio F, Marzi M et al. A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer. EMBO Mol Med 2011;3:495-503. 7. Pastorino U, Bellomi M, Landoni C, De Fiori E, Arnaldi P, Picchio M, et al. Early lung-cancer detection with spiral CT and positron emission tomography in heavy smokers: 2-year results. Lancet 2003; 362(9384):593-597 8. Pastorino U, Rossi M, Rosato V et al. Annual or biennial CT screening versus observation in heavy smokers: 5-year results of the MILD trial. Eur J Cancer Prev 2012;21:308-15. 9. Sozzi G, Boeri M, Rossi M et al. Clinical Utility of a Plasma-Based miRNA Signature Classifier Within Computed Tomography Lung Cancer Screening: A Correlative MILD Trial Study. J Clin Oncol 2014;32:768-73 10. Montani F, Marzi MJ, Dezi F et al. miR-Test: A Blood Test for Lung Cancer Early Detection. J Natl Cancer Inst 2015; 107(6): djv063.

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    ORAL 06 - Next Generation Sequencing and Testing Implications (ID 90)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 1
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      ORAL06.01 - Genomic Characterization of Large-Cell Neuroendocrine Lung Tumors (ID 1667)

      11:05 - 11:16  |  Author(s): U. Pastorino

      • Abstract
      • Slides

      Background:
      Neuroendocrine lung tumours account for 25% of all lung cancer cases, and they range from low-aggressive pulmonary carcinoids (PCA) to highly malignant small-cell lung cancer (SCLC) and large-cell neuroendocrine lung carcinoma (LCNEC). The last two are strongly associated with heavy smoking and are typically detected at a clinically advanced stage, having a poor survival. Comprehensive genomic analyses in lung neuroendocrine tumours are difficult because of limited availability of tissue. While more effort has been done in the context of SCLC, the detailed molecular features of LCNEC remain largely unknown.

      Methods:
      We conducted 6.0 SNP array analyses of 60 LCNEC tumours, exome sequencing of 55 tumor-normal pairs, genome sequencing of 11 tumour-normal pairs, transcriptome sequencing of 69 tumours, and expression arrays on 60 tumors. Data analyses were performed using in house developed and published pipelines.

      Results:
      Analyses of chromosomal gene copy number revealed amplifications of MYCL1, FGFR1, MYC, IRS2 and TTF1. We also observed deletions of CDKN2A and PTPRD. TTF1 amplifications are characteristic of lung adenocarcinoma (AD); CDKN2A deletions are frequent alterations in both AD and squamous-cell lung carcinoma (SQ); FGFR1 amplifications are found in SQ and, less frequently, in SCLC; and MYCL1 and IRS2 amplifications are frequent events in SCLC. Similar to the copy number data, we found patterns of mutations characteristic of other lung cancer subtypes: TP53 was the most frequently mutated gene (75%) followed by RB1 (27%), and inactivation of both TP53 and RB1, which is the hallmark of SCLC, occurred in 20% of the cases. Mutations in STK11 and KEAP1-NFE2L2 (frequently seen in AD and SQ) were found in 23% and 22% of the specimens, respectively. Interestingly, mutations in RB1 and STK11/KEAP1 occurred in a mutually exclusive fashion (p-value=0.016). Despite the heterogeneity observed at the mutation level, analysis of the pattern of expression of LCNEC in comparison with the other lung cancer subtypes (AD, SQ, SCLC, and PCA) points to LCNEC as being an independent entity. An average mutation rate of 10.7 mutations per megabase was detected in LCNEC, which is in line with the rate observed in other lung tumours associated with smoking. We found that, similar to SCLC, the mutation signatures associated with APOBEC family of cytidine deaminases, smoking, and age (based on Alexandrov et al 2013) were the predominant ones in LCNEC. However, the contribution of the individual SCLC and LCNEC samples to these three signatures was quite different, and we are currently exploring it.

      Conclusion:
      Taking into account somatic copy number and mutation data, we distinguished two well-defined groups of LCNEC: an SCLC-like group, carrying alterations in MYCL1, ISR2, and in both RB1 and TP53; and a group resembling AD and SQ, with alterations in CDKN2A, TTF1, KEAP1-NFE2L2, and STK11. Although these results suggest that LCNEC might be a mix of different lung cancer subtypes, mutation clonality and expression analyses show that they are likely to be a separate entity, sharing molecular characteristics with the other lung cancer subtypes. Their heterogeneity suggests that LCNEC might represent an evolutionary trunk that can branch to SCLC or AD/SQ.

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    P1.06 - Poster Session/ Screening and Early Detection (ID 218)

    • Event: WCLC 2015
    • Type: Poster
    • Track: Screening and Early Detection
    • Presentations: 1
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      P1.06-017 - Small Cell Lung Cancer in Lung Cancer Screening: Frequency and Outcome (ID 2476)

      09:30 - 09:30  |  Author(s): U. Pastorino

      • Abstract
      • Slides

      Background:
      Only 30% of small cell lung cancers (SCLC) are diagnosed as limited stage (LS-SCLC), whereas the majority of cases show extensive stage disease (ES-SCLC). Specific frequency and outcome of SCLC within lung cancer screening trials have not been described. The purpose of this study was to describe the frequency and outcome of SCLC in lung cancer screening trials with annual or biennial LDCT controls.

      Methods:
      The population was selected from two lung cancer screening trials (one pilot study and one randomized controlled study) based on serial low-dose computed tomography (LDCT). Subjects with diagnosis of SCLC were selected and the stage of the disease was assessed at the time of diagnosis, as follows: a) TNM staging system; b) 2-stage staging system (e.g. LS-SCLC or ES-SCLC). Survival curves were estimated using Kaplan-Meier method and were compared by log-rank test.

      Results:
      5,134 subjects were recruited and, thereafter, followed up for a median time of 8.3 years, with 45,141 person-year of clinical follow up. Ten SCLC were reported with incidence of SCLC 22/100,000 person-year, notably, 8 in the LDCT arms with incidence of 24/100,000. SCLC was diagnosed in 3/1643 women and 7/3385 men, age at diagnosis 65 years (range 53-73), and cumulative tobacco consumption of 82 pack-years (range 30-113). The proportion of SCLC among all lung cancers diagnosed in the screening was 10/164. Six out of the 8 SCLC reported in LDCT arms were screen-detected, whereas 2 SCLC were non-screen-detected. Median standard uptake value (SUV) by [18]F-Fluorodeoxyglucose Positron Emission Tomography was 10 (range 5.5-14.4). According to TNM classification, all but 1 SCLC were advanced stage at the time of diagnosis, whereas according to the 2-stage system 5 LS-SCLC and 5 ES-SCLC were observed. The prevalence of LS-SCLC was 62.5% in LDCT arm, in particular, 66.7% among screen-detected and 50% non-screen-detected. The 2 SCLC reported in control group were both ES-SCLC. Six of the 10 subjects died from SCLC, with median overall survival of 21.2 months (95% CI 7.4 – nc months; Figure). Median overall survival was 12-month longer for LS-SCLC (p = 0.02). Survival at 5 years was 0%. Figure 1.



      Conclusion:
      SCLC was diagnosed with higher proportion of LS-SCLC in LDCT-based screening trials, as compared to data from the literature. Median overall survival of LS-SCLC was slightly longer than ES-SCLC, allegedly related to diagnosis anticipation. None of these patients was alive at 5 years.

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    PLEN 04 - Presidential Symposium Including Top 4 Abstracts (ID 86)

    • Event: WCLC 2015
    • Type: Plenary
    • Track: Plenary
    • Presentations: 1
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      PLEN04.07 - Stopping Smoking Reduces Mortality in Low-Dose Computed Tomography (LDCT) Screening Volunteers (ID 2458)

      11:51 - 12:03  |  Author(s): U. Pastorino

      • Abstract
      • Presentation
      • Slides

      Background:
      The National Lung Screening Trial (NLST) has achieved a 7% reduction in mortality from any cause with low-dose computed tomography (LDCT) screening, as compared with the chest radiography arm. Other randomized trials are under way, comparing LDCT screening with no intervention in heavy smokers populations. None of these studies is designed to investigate the impact of smoking habits on screening outcome. In the present study, we have tested the effect of stopping smoking on the overall mortality of volunteers undergoing LDCT screening.

      Methods:
      Between 2000 and 2010, 3381 heavy smokers aged more than 50 years were enrolled in two LDCT screening programmes. Sixty-nine percent were males with median age of 58 years and median smoking exposure of 40 pack-years. Based on the last follow-up information, subjects were divided in two groups: current smokers throughout the screening period, and former smokers. The latter group included ex-smokers at the time of baseline screening (early quitters), and those who stopped smoking during the screening period (late quitters).The effect of smoking on mortality was adjusted according to the following covariates: gender, age, body-mass index (BMI), lung function (FEV1 %) and pack years at baseline.

      Results:
      With a median follow-up time of 9.7 years, and a total of 32,857 person/years (P/Y) follow-up, a total of 151 deaths were observed in the group of 1797 current smokers (17,846 P/Y) and 109 in 1584 former smokers (15,011 P/Y). As compared to current smokers, the Relative Risk (RR) of death of former smokers was 0.77 (95% CI, 0.60 to 0.99, p = 0.0416), corresponding to a 23% reduction of total mortality. Excluding 239 subjects who had stopped smoking from less than 2 years from the end-point of follow-up, RR was 0.64 (95% CI, 0.48 to 0.84, p = 0.0016), with a 36% mortality reduction. A similar risk reduction was observed in the subset of 476 late quitters (27 deaths, 4,777 P/Y), with a RR of 0.60 (95% CI, 0.40 to 0.91, p = 0.0158).

      Conclusion:
      Stopping smoking is associated with a significant reduction of the overall mortality of heavy smokers enrolled in LDCT screening programs. The benefit of stopping smoking appears to be 3 to 5-fold greater than the one achieved by earlier detection in the NLST trial.

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    PRC 04 - Press Conference 4 (ID 199)

    • Event: WCLC 2015
    • Type: Press Conference
    • Track: Other
    • Presentations: 1
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      Abstract – Stopping Smoking Reduces Mortality in Low-Dose Computed Tomography (LDCT) Screening Volunteers - Dr. Ugo Pastorino, Director Thoracic Surgery, IRCCS Istituto Nazionale dei Tumori Foundation, Milan, Italy (ID 3636)

      10:01 - 10:09  |  Author(s): U. Pastorino

      • Abstract
      • Presentation

      Abstract not provided

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