Outcomes of lung cancer screening among cancer survivors: An NCCN institution experience.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1595-1595
Author(s):  
Bradley Maller ◽  
Vani Nath Simmons ◽  
Margaret M Byrne ◽  
Tawee Tanvetyanon
Keyword(s):  
Lung Cancer ◽  
Cancer Survivors ◽  
False Positive ◽  
Lung Cancer Screening ◽  
National Lung Screening Trial ◽  
Increased Risk ◽  
Significant Difference ◽  
Annual Screening ◽  
Positive Results ◽  
Predicted Risk

1595 Background: In 2013, the USPTF recommended low-dose CT (LDCT) screening for individuals at high risk of lung cancer based on data from the National Lung Screening Trial. However, the trial excluded participants with cancer diagnosis < 5 years except for non-melanoma skin cancer, making it unclear whether the data will be generalizable to cancer survivors. This population, while at increased risk of secondary lung cancer, may be prone to false positive results due to anatomic defects or recurrent cancers. Our NCCN institution serves a large number of cancer survivors. We evaluated the outcomes of LDCT screening and the adherence to annual screening among cancer survivors, compared with individuals without cancer history (IWC). Methods: Prospectively maintained database of LDCT screening participants was analyzed. Eligibility was per NCCN criteria and cancer survivors needing regular chest CT were not offered LDCT. Participants were asked to complete a self-administered questionnaire on risk factors. Positive result was defined as Lung-RADS ≥3, corresponding to nodule ≥6 mm. Adherence to LDCT screening was defined as having T1 screening, excluding those < 18 months from T0 at time of analysis. Predicted risk of lung cancer was calculated per PLCOm2012 model. Results: To date, 454 subjects have undergone LDCT screening. Positive results occurred in 60 subjects (13.2%) at T0; lung cancer was diagnosed in 10 subjects (2.2%); and other cancers were diagnosed in 5 subjects (1.1%). There were 152 cancer survivors, including survivors of breast (52), prostate (26), bladder or kidney (19), lung (14), and head and neck cancer (13). The median time from cancer treatment to LDCT screening was 6 years (range 0-55). Cancer survivors were older than IWC: median age 67.4 vs. 63.5 years ( p< 0.001) and more likely to be active smokers: 37.5% vs. 29.5%, ( p= 0.09). The median predicted risk of lung cancer at 6 year was 5.5% vs. 3.2%, ( p= 0.15). No significant difference in the screening outcomes was found between groups. Among cancer survivors (N = 152), positive screening occurred in 15 (9.9%); lung cancer was diagnosed in 1 (0.7%); and other cancers were diagnosed in 3 subjects (1.9%). Non-adherence to LDCT screening occurred in 31 out of 152 cancer survivors (20.4%), compared with 81 out of 262 (30.9%) IWC, ( p= 0.02). Conclusions: About one-third of LDCT screenings at this NCCN institution occurred among cancer survivors. We found no evidence of increased false positive results. However, a higher rate of adherence to annual screening was observed among cancer survivors than IWC.

Effectiveness of Lung-RADS in Reducing False-Positive Results in a Diverse, Underserved, Urban Lung Cancer Screening Cohort

2019 ◽  
Vol 16 (4) ◽  
pp. 419-426 ◽  
Author(s):  
Mark Kaminetzky ◽  
Hannah S. Milch ◽  
Anna Shmukler ◽  
Abraham Kessler ◽  
Robert Peng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
False Positive ◽  
Lung Cancer Screening ◽  
Positive Results

scholarly journals Incidental renal tumours on low-dose CT lung cancer screening exams

2016 ◽  
Vol 24 (2) ◽  
pp. 104-109 ◽  
Author(s):  
Paul F Pinsky ◽  
Barbara Dunn ◽  
David Gierada ◽  
P Hrudaya Nath ◽  
Reginald Munden ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Renal Cancer ◽  
Low Dose ◽  
Lung Cancer Screening ◽  
National Lung Screening Trial ◽  
Renal Tumours ◽  
Chest X Ray ◽  
Low Dose Computed Tomography ◽  
Lung Screening

Introduction Renal cancer incidence has increased markedly in the United States in recent decades, largely due to incidentally detected tumours from computed tomography imaging. Here, we analyze the potential for low-dose computed tomography lung cancer screening to detect renal cancer. Methods The National Lung Screening Trial randomized subjects to three annual screens with either low-dose computed tomography or chest X-ray. Eligibility criteria included 30 + pack-years, current smoking or quit within 15 years, and age 55–74. Subjects were followed for seven years. Low-dose computed tomography screening forms collected information on lung cancer and non-lung cancer abnormalities, including abnormalities below the diaphragm. A reader study was performed on a sample of National Lung Screening Trial low-dose computed tomography images assessing presence of abnormalities below the diaphragms and abnormalities suspicious for renal cancer. Results There were 26,722 and 26,732 subjects enrolled in the low-dose computed tomography and chest X-ray arms, respectively, and there were 104 and 85 renal cancer cases diagnosed, respectively (relative risk = 1.22, 95% CI: 0.9–1.5). From 75,126 low-dose computed tomography screens, there were 46 renal cancer diagnoses within one year. Abnormalities below the diaphragm rates were 39.1% in screens with renal cancer versus 4.1% in screens without (P < 0.001). Cases with abnormalities below the diaphragms had shorter median time to diagnosis than those without (71 vs. 160 days, P = 0.004). In the reader study, 64% of renal cancer cases versus 13% of non-cases had abnormalities below the diaphragms; 55% of cases and 0.8% of non-cases had a finding suspicious for renal cancer (P < 0.001). Conclusion Low-dose computed tomography screens can potentially detect renal cancers. The benefits to harms tradeoff of incidental detection of renal tumours on low-dose computed tomography is unknown.

Optimisation of volume-doubling time cutoff for fast-growing lung nodules in CT lung cancer screening reduces false-positive referrals

2013 ◽  
Vol 23 (7) ◽  
pp. 1836-1845 ◽  
Author(s):  
Marjolein A. Heuvelmans ◽  
Matthijs Oudkerk ◽  
Geertruida H. de Bock ◽  
Harry J. de Koning ◽  
Xueqian Xie ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
False Positive ◽  
Doubling Time ◽  
Lung Cancer Screening ◽  
Lung Nodules ◽  
Fast Growing ◽  
Volume Doubling Time ◽  
Volume Doubling

Radiomic Phenotyping of the Lung Parenchyma: Feasibility Study in a Screening Cohort

2021 ◽  
Author(s):  
Babak Haghighi ◽  
Hannah Horng ◽  
Peter B Noël ◽  
Eric Cohen ◽  
Lauren Pantalone ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
Low Dose ◽  
Lung Cancer Screening ◽  
Lung Parenchyma ◽  
Ct Scans ◽  
Lung Field ◽  
Reconstruction Algorithms ◽  
Low Dose Ct ◽  
Significant Difference

Abstract Rationale: High-throughput extraction of radiomic features from low-dose CT scans can characterize the heterogeneity of the lung parenchyma and potentially aid in identifying subpopulations that may have higher risk of lung diseases, such as COPD, and lung cancer due to inflammation or obstruction of the airways. We aim to determine the feasibility a lung radiomics phenotyping approach in a lung cancer screening cohort, while quantifying the effect of different CT reconstruction algorithms on phenotype robustness. Methods: We identified low-dose CT scans (n = 308) acquired with Siemens Healthineers scanners from patients who completed low-dose CT within our lung cancer screening program between 2015-2018 and had two different sets of image reconstructions kernel available (i.e., medium (I30f), sharp (I50f)) for the same acquisition. Following segmentation of the lung field, a total of 26 radiomic features were extracted from the entire 3D lung-field using a previously validated fully-automated lattice-based software pipeline, adapted for low-dose CT scans. The features extracted included gray-level histogram, co-occurrence, and run-length descriptors. Each feature was averaged for each scan within a range of lattice window sizes (W) ranging from 4-20mm. The extracted imaging features from both datasets were harmonized to correct for differences in image acquisition parameters. Subsequently, unsupervised hierarchal clustering was applied on the extracted features to identify distinct phenotypic patterns of the lung parenchyma, where consensus clustering was used to identify the optimal number of clusters (K = 2). Differences between? phenotypes for demographic and clinical covariates including sex, age, BMI, pack-years of smoking, Lung-RADS and cancer diagnosis were assessed for each phenotype cluster, and then compared across clusters for the two different CT reconstruction algorithms using the cluster entanglement metric, where a lower entanglement coefficient corresponds to good cluster alignment. Furthermore, an independent set of low-dose CT scans (n = 88) from patients with available pulmonary function data on lung obstruction were analyzed using the identified optimal clusters to assess associations to lung obstruction and validate the lung phenotyping paradigm. Results: Heatmaps generated by radiomic features identified two distinct lung parenchymal phenotype patterns across different feature extraction window sizes, for both reconstruction algorithms (P < 0.05 with K = 2). Associations of radiomic-based clusters with clinical covariates showed significant difference for BMI and pack-years of smoking (P < 0.05) for both reconstruction kernels. Radiomic phenotype patterns where similar across the two reconstructed kernels, specifically when smaller window sizes (W=4 and 8mm) were used for radiomic feature extraction, as deemed by their entanglement coefficient. Validation of clustering approaches using cluster mapping for the independent sample with lung obstruction also showed two statistically significant phenotypes (P < 0.05) with significant difference for BMI and smoking pack-years.ConclusionsRadiomic analysis can be used to characterize lung parenchymal phenotypes from low-dose CT scans, which appear reproducible for different reconstruction kernels. Further work should seek to evaluate the effect of additional CT acquisition parameters and validate these phenotypes in characterizing lung cancer screening populations, to potentially better stratify disease patterns and cancer risk.

Association of NAT-2 gene polymorphisms toward lung cancer susceptibility and prognosis in North Indian patients treated with platinum-based chemotherapy

2021 ◽  
Author(s):  
Harleen Kaur Walia ◽  
Navneet Singh ◽  
Siddharth Sharma
Keyword(s):  
Lung Cancer ◽  
Prognostic Factor ◽  
Cancer Susceptibility ◽  
Healthy Controls ◽  
Slow Acetylator ◽  
Mutant Genotype ◽  
Platinum Based Chemotherapy ◽  
Increased Risk ◽  
Significant Difference ◽  
Potential Prognostic Factor

Aim: The present study has been carried out to evaluate the association of the N-acetyl transferase 2 ( NAT2) variants in North Indian lung cancer patients and healthy controls. Furthermore, we have also determined the effect of the polymorphic variants of the NAT2 gene on the clinical outcomes and overall survival among lung cancer (LC) subjects treated with platinum-based doublet chemotherapy. Methods: This case-control study comprised a total of 550 cases and 550 healthy controls. The genotyping was carried out using polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) and the statistical analysis was carried out using MedCalc. Results: There was a lack of any significant association for both 590G>A and 803A>G polymorphisms toward risk for LC, but 857G>A polymorphism exhibited a risk toward LC (p = 0.005). Whereas, variant alleles for the 481C>T polymorphism had a decreased risk for LC (p = 0.0003). Further, 857G>A polymorphism conferred a positive association between genotype and ADCC (p = 0.001) and 481C>T polymorphism had a decreased risk for SQCC (OR = 0.39, p = 0.0006) and SCLC (p = 0.001) subjects. The smokers carrying mutant genotype for the 481C>T polymorphism had a decreased risk toward LC (p < 0.0001) even in light (p = 0.002) as well as heavy smokers (p = 0.001). In case of females, 2.59-fold and 3.66-fold increased risk of LC development was observed in subjects with intermediate and slow acetylator for the 857G>A polymorphism. Whereas, in case of males this polymorphism depicts a reduced risk for LC. On the other hand, 803A>G depicted a 2.82-fold risk of LC in case of female subjects who were slow acetylators. Our study exhibits a significant difference in the overall haplotype distribution between cases and controls. In our study overall, (857G>A, 481C>T, 803A>G) was found to be best model, but was not significant using MDR. Considering the CART results 481C>T polymorphism came out to be the most significant factor in determining the LC risk. For the 803A>G polymorphism, a threefold odds of lymph node invasion were observed for mutant genotype, the recessive model exhibited an odd of 2.8. 590G>A appears to be a potential prognostic factor for OS of SCLC patients after irinotecan therapy as the survival time for such patients was better. Conclusion: These results suggest that NAT2 variant genotype for 590G>A and 803A>G was not found to modulate risk toward LC, but 857G>A polymorphism exhibited a risk toward LC and 481C>T polymorphism had a decreased risk for LC. NAT2 590G>A appears to be a potential prognostic factor for OS of SCLC patients after irinotecan therapy and 481C>T came out to be significant factor using CART.

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