Trends in Lung Cancer Incidence in a Healthcare Area

Molina, A.; García-Martínez, Lidia; Zapata-Alvarado, Julio; Alonso-Orcajo, Nieves; Fernández‐Villa, Tania; Martín, Vicente

doi:10.1016/j.arbr.2015.09.010

Cited by 5 publications

(5 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, biological factors such as gender and age have been shown to play a major role in the development and prognosis of lung cancers [ 60 ]. For example, women smokers have a greater risk for developing lung cancer compared to men who smoke, presumably due to underlying genetic and other biological differences between men and women [ 61 , 62 ]; the AC subtype predominates in women, whereas SCC is more common in men [ 63 ]; and individuals aged 65 and older are at greater risk of developing lung cancers [ 60 ]. The over-representation of samples from male patients, when compared with the two control groups, and the modest sample size in this pilot project limited our ability to explore the moderating effects of these biological factors on our findings.…”

Section: Discussionmentioning

confidence: 99%

A Pilot Analysis of Circulating cfRNA Transcripts for the Detection of Lung Cancer

et al. 2022

View full text Add to dashboard Cite

Lung cancers are the leading cause of cancer-related deaths worldwide. Studies have shown that non-small cell lung cancer (NSCLC), which constitutes the majority of lung cancers, is significantly more responsive to early-stage interventions. However, the early stages are often asymptomatic, and current diagnostic methods are limited in their precision and safety. The cell-free RNAs (cfRNAs) circulating in plasma (liquid biopsies) offer a non-invasive detection of spatial and temporal changes occurring in primary tumors since the early stages. To address gaps in the current cfRNA knowledge base, we conducted a pilot study for the comprehensive analysis of transcriptome-wide changes in plasma cfRNA in NSCLC patients. Total cfRNA was extracted from archived plasma collected from NSCLC patients (N = 12), cancer-free former smokers (N = 12), and non-smoking healthy volunteers (N = 12). Plasma cfRNA expression levels were quantified by using a tagmentation-based library preparation and sequencing. The comparisons of cfRNA expression levels between patients and the two control groups revealed a total of 2357 differentially expressed cfRNAs enriched in 123 pathways. Of these, 251 transcripts were previously reported in primary NSCLCs. A small subset of genes (N = 5) was validated in an independent sample (N = 50) using qRT-PCR. Our study provides a framework for developing blood-based assays for the early detection of NSCLC and warrants further validation.

show abstract

Section: Discussionmentioning

confidence: 99%

A Pilot Analysis of Circulating cfRNA Transcripts for the Detection of Lung Cancer

et al. 2022

View full text Add to dashboard Cite

show abstract

“…First, biological factors such as gender and age have been shown to play a major role in the development and prognosis of lung cancers [60]. For example, women smokers have greater risk for developing lung cancer compared to men who smoke, presumably due to underlying genetic and other biological differences between men and women [61, 62]; the AC subtype predominates in women, whereas SCC are more common in men [63]; and individuals aged 65 and older are at greater risk of developing lung cancers[60]. The over-representation of samples from male patients as compared to the two control groups, and the modest sample size in this pilot project limited our ability to explore moderating effects of these biological factors on our findings.…”

Section: Discussionmentioning

confidence: 99%

A pilot analysis of circulating cfRNA transcripts for the detection of lung cancer

Seneviratne

Shetty

Geng

et al. 2022

Preprint

View full text Add to dashboard Cite

Lung cancers are the leading cause of cancer-related deaths worldwide. Studies have shown that non-small cell lung cancer (NSCLC) which constitute majority of lung cancers, are significantly more re-sponsive to early-stage interventions. However, the early stages are often asymptomatic, and current diag-nostic methods are limited in their precision and safety. The cell-free RNAs (cfRNA) circulating in plasma (Liquid biopsies) offer non-invasive detection of spatial and temporal changes occurring in primary tumors since early stages. To address gaps in current cfRNA knowledge base, we conducted a pilot study for com-prehensive analysis of transcriptome-wide changes in plasma cfRNA in NSCLC patients. Total cfRNA was extracted from archived plasma collected from NSCLC patients (N=12; cases), cancer-free former smokers (N=12; control_smokers) and non-smoking healthy volunteers (N=12; control_healthy). Plasma cfRNA ex-pression levels in each sample were quantified by using a tagmentation-based library preparation and se-quencing. The comparisons of cfRNA expression levels between cases and the two control groups revealed a total of 2537 differentially expressed cfRNA enriched in 123 pathways in NSCLC patients. Of these, 222 tran-scripts were previously reported in primary NSCLCs. Our study provides a framework for developing a blood-based assay for early detection of NSCLC and warrants further validation.

show abstract

“…It is the third most common cancer, and the most frequent when considering both genders . Its incidence is increasing in women, probably as a result of greater tobacco exposure, labor integration, and hormonal factors . Tobacco consumption is the main risk factor for LC, given that more than 85% of cases occur among current or former smokers .…”

Section: Introductionmentioning

confidence: 99%

“…3 Its incidence is increasing in women, probably as a result of greater tobacco exposure, labor integration, and hormonal factors. 1,4,5 Tobacco consumption is the main risk factor for LC, given that more than 85% of cases occur among current or former smokers. 6 Residential radon exposure is the second highest risk factor, and the first highest in never smokers.…”

Section: Introductionmentioning

confidence: 99%

Predicting delays in lung cancer diagnosis and staging

et al. 2019

View full text Add to dashboard Cite

BackgroundDespite growing interest in increasing the efficiency and speed of the diagnosis, staging, and treatment of lung cancer (LC), the interval from signs and symptoms to diagnosis and treatment remains longer than recommended. The aim of this study was to analyze the factors that cause delays in the LC diagnosis/staging process and, consequently, delays in making therapeutic decisions.MethodsWe analyzed audit data from a prospective dataset of 1330 patients assessed at The Lung Cancer Rapid Diagnostic Unit from 26 June 2013 to 26 March 2016. The number and type of procedures and medical tests and the times of all procedures were recorded. Clinical and epidemiological variables and whether the diagnosis was performed on an inpatient or outpatient basis were also recorded.ResultsMalignancy was confirmed in 737 (55.4%) of the 1330 patients, with LC in 627 of these (85.2%). The mean interval to final diagnosis was 19.8 ± 13.9 days. Variables significantly related to a longer diagnostic time were the number of days until computed tomography (CT) was performed (odds ratio [OR], 95% confidence interval [CI] 1.347, 1.103–1.645; P = 0.003), until a histology sample was obtained (OR 1.243, 95% CI1.062–1.454; P = 0.007), and the total number of tests performed during the diagnostic and staging process (OR 1.823, 95% CI 1.046–3.177; P = 0.03).ConclusionsA greater number of tests and more days to CT and histology led to longer delay times. Optimization of these factors should reduce delays in the LC diagnosis process.

show abstract

Trends in Lung Cancer Incidence in a Healthcare Area

Cited by 5 publications

References 4 publications

A Pilot Analysis of Circulating cfRNA Transcripts for the Detection of Lung Cancer

A Pilot Analysis of Circulating cfRNA Transcripts for the Detection of Lung Cancer

A pilot analysis of circulating cfRNA transcripts for the detection of lung cancer

Predicting delays in lung cancer diagnosis and staging

Contact Info

Product

Resources

About