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1.
Carcinogenesis ; 2021 Feb 26.
Artigo em Inglês | MEDLINE | ID: mdl-33640962

RESUMO

The U.S. Preventive Services Task Force (USPSTF) recently proposed to widen the current lung cancer screening guideline to include less-heavy smokers. We sought to incorporate both genetic and tobacco smoking data to evaluate the proposed new guideline in white smokers. We constructed a polygenic risk score (PRS) using lung cancer risk variants. Using data from 308,490 participants of European descent in the UK Biobank, a population-based cohort study, we estimated hazard ratios (HRs) of lung cancer associated with both tobacco smoking and PRS to identify individuals at a similar or higher risk than the group of heavy smokers who are recommended for screening under the USPSTF-2014 guideline (≥30 pack-years, either current or former smokers who quit within 15 years). During a median follow-up of 5.8 years, 1,449 incident cases of lung cancer were identified. We found a similar lung cancer risk for current smokers with 20-29 pack-years (HR=20.7, 95% confidence interval (CI): 16.3-26.4) and the "heavy smoker group" defined above (HR=19.9, 95% CI: 16.8-23.6) compared with never smokers. Current smokers with 20-29 pack-years did not reach a 6-year absolute risk of 0.0151, a suggested risk threshold for using low-dose computed tomography screening, until the age of 55 years. However, these smokers at high genetic risk (PRS ≥80%) reached this risk level at the age of 50. Our findings support the USPSTF proposal to lower the smoking pack-year eligibility to 20 pack-years for current smokers and suggest that PRS for lung cancer could be considered to identify high-risk smokers for screening.

2.
Transl Res ; 2021 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-33618009

RESUMO

Lung cancer screening detects early-stage cancers, but also a large number of benign nodules. Molecular markers can help in the lung cancer screening process by refining inclusion criteria or guiding the management of indeterminate pulmonary nodules. In this study, we developed a diagnostic model based on the quantification in plasma of complement-derived fragment C4c, cytokeratin fragment 21.1 (CYFRA 21-1) and C-reactive protein (CRP). The model was first validated in two independent cohorts, and showed a good diagnostic performance across a range of lung tumor types, emphasizing its high specificity and positive predictive value. We next tested its utility in two clinically relevant contexts: assessment of lung cancer risk and nodule malignancy. The scores derived from the model were associated with a significantly higher risk of having lung cancer in asymptomatic individuals enrolled in a computed tomography (CT)-screening program (OR=1.89; 95% CI=1.20 to 2.97). Our model also served to discriminate between benign and malignant pulmonary nodules (AUC: 0.86; 95% CI=0.80-0.92) with very good specificity (92%). Moreover, the model performed better in combination with clinical factors, and may be used to reclassify patients with intermediate-risk indeterminate pulmonary nodules into patients who require a more aggressive work-up. In conclusion, we propose a new diagnostic biomarker panel that may dictate which incidental or screening-detected pulmonary nodules require a more active work-up.

3.
BMC Health Serv Res ; 21(1): 33, 2021 Jan 07.
Artigo em Inglês | MEDLINE | ID: mdl-33413353

RESUMO

BACKGROUND: A systems-level approach to smoking cessation treatment may optimize healthcare provider adherence to guidelines. Institutions such as the Veterans Health Administration (VHA) are unique in their systematic approach, but comparisons of provider behavior in different healthcare systems are limited. METHODS: We surveyed general medicine providers and specialists in a large academic health center (AHC) and its affiliated VHA in the Mid-South in 2017 to determine the cross-sectional association of healthcare system in which the provider practiced (exposure: AHC versus VHA) with self-reported provision of evidence-based smoking cessation treatment (delivery of counseling plus smoking cessation medication or referral) at least once in the past 12 months (composite outcome). Multivariable logistic regression with adjustment for specialty was performed in 2017-2019. RESULTS: Of 625 healthcare providers surveyed, 407 (65%) responded, and 366 (59%) were analyzed. Most respondents practiced at the AHC (273[75%] vs VHA 93[25%]) and were general internists (215[59%]); pulmonologists (39[11%]); hematologists/oncologists (69[19%]); and gynecologists (43[12%]). Most respondents (328[90%]) reported the primary outcome. The adjusted odds of evidence-based smoking cessation treatment were higher among VHA vs. AHC healthcare providers (aOR = 4.3; 95% CI 1.3-14.4; p = .02). Health systems differed by provision of individual treatment components, including smoking cessation medication use (98% VHA vs. 90% AHC, p = 0.02) and referral to smoking cessation services (91% VHA vs. 65% AHC p = 0.001). CONCLUSIONS: VHA healthcare providers were significantly more likely to provide evidence-based smoking cessation treatment compared to AHC healthcare providers. Healthcare systems' prioritization of and investment in smoking cessation treatment is critical to improving providers' adherence to guidelines.

4.
Chest ; 159(1): e53-e56, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33422242

RESUMO

CASE PRESENTATION: A 56-year-old man presented to the lung nodule clinic with abnormal chest imaging prompted by a chronic cough and hemoptysis. Approximately 2.5 years earlier, while kneeling beside his car fixing a flat tire, he fell backwards while holding the tire cap in his mouth, causing him to inhale sharply and aspirate the cap. He immediately developed an intractable cough productive of flecks of blood. He presented to an emergency room but left before being seen because of a long wait time and his lack of health-care insurance. He self-medicated for severe cough and chest discomfort with codeine, eventually developing a dependency. Approximately 3 weeks after aspirating the tire cap, his cough became productive, and he developed fever and chills. His symptoms improved transiently with antibiotics and additional narcotics. Ultimately, his chronic cough with intermittent hemoptysis affected his ability to work, and 30 months later he sought medical attention and was diagnosed with pneumonia and reactive airway disease. He was prescribed doxycycline, steroids, inhaled albuterol, and dextromethorphan, with initial improvement, but his symptoms recurred multiple times despite quitting smoking, leading to repeated medication courses.

5.
Ann Am Thorac Soc ; 2021 Jan 05.
Artigo em Inglês | MEDLINE | ID: mdl-33400907

RESUMO

RATIONALE: A prospective longitudinal cohort of individuals at high-risk of developing lung cancer was established to build a biorepository of carefully annotated biological specimens and low-dose computed tomography (LDCT) chest images for derivation and validation of candidate biomarkers for early detection of lung cancer. OBJECTIVE: The goal of this study is to characterize individuals with high-risk for lung cancer, accumulating valuable biospecimens and LDCT chest scan longitudinally over five years. METHODS: Participants 55-80 years of age and with a 5-year estimated risk of developing lung cancer greater than 1.5% were recruited and enrolled from clinics at Vanderbilt University Medical Center, the Veteran Affairs Medical Center, and Meharry Medical Center. Individual demographic characteristics were assessed via questionnaire at baseline. Participants underwent a LDCT scan, spirometry, sputum cytology, and research bronchoscopy at the time of enrollment. Participants will be followed yearly for five years. Positive LDCT scans are followed-up according to standard of care. The clinical, imaging and biospecimen data are collected prospectively and stored in a biorepository. Participants are offered smoking cessation counseling at each study visit. RESULTS: A total of 480 participants were enrolled at study baseline and consented to sharing of their data and biospecimens for research. Participants are followed with yearly clinic visits to collect imaging data and biospecimens. To date, a total of 19 cancers (13 adenocarcinomas, 4 squamous cell carcinoma, 1 large cell neuroendocrine and 1 small cell lung cancer) have been identified. CONCLUSION: We established a unique prospective cohort of individuals at high-risk for lung cancer, enrolled at three institutions for which full clinical data, well-annotated LDCT and biospecimens are being collected longitudinally. This repository will allow for the derivation of independent validation of clinical, imaging and molecular biomarkers of risk or diagnosis of lung cancer. Clinical trial registered with ClinicalTrials.gov (NCT01475500).

6.
J Am Coll Radiol ; 2021 Jan 06.
Artigo em Inglês | MEDLINE | ID: mdl-33421372

RESUMO

OBJECTIVES: Lung cancer has the highest cancer-related mortality in the United States and among Veterans. Screening of high-risk individuals with low-dose CT (LDCT) can improve survival through detection of early-stage lung cancer. Organizational factors that aid or impede implementation of this evidence-based practice in diverse populations are not well described. We evaluated organizational readiness for change and change valence (belief that change is beneficial and valuable) for implementation of LDCT screening. METHODS: We performed a cross-sectional survey of providers, staff, and administrators in radiology and primary care at a single Veterans Affairs Medical Center. Survey measures included Shea's validated Organizational Readiness for Implementing Change (ORIC) scale and Shea's 10 items to assess change valence. ORIC and change valence were scored on a scale from 1 to 7 (higher scores representing higher readiness for change or valence). Multivariable linear regressions were conducted to determine predictors of ORIC and change valence. RESULTS: Of 523 employees contacted, 282 completed survey items (53.9% overall response rate). Higher ORIC scores were associated with radiology versus primary care (mean 5.48, SD 1.42 versus 5.07, SD 1.22, ß = 0.37, P = .039). Self-identified leaders in lung cancer screening had both higher ORIC (5.56, SD 1.39 versus 5.11, SD 1.26, ß = 0.43, P = .050) and change valence scores (5.89, SD 1.21 versus 5.36, SD 1.19, ß = 0.51, P = .012). DISCUSSION: Radiology health professionals have higher levels of readiness for change for implementation of LDCT screening than those in primary care. Understanding health professionals' behavioral determinants for change can inform future lung cancer screening implementation strategies.

7.
JNCI Cancer Spectr ; 4(5): pkaa028, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-33215060

RESUMO

Background: To address the US Food and Drug Administration's recent safety concern on robotic surgery procedures, we compared short- and long-term mortality for stage I non-small cell lung cancer (NSCLC) patients treated by robotic-assisted thoracoscopic surgical lobectomy (RATS-L) vs video-assisted thoracoscopic surgical lobectomy (VATS-L). Methods: From the National Cancer Database, we identified 18 908 stage I NSCLC patients who underwent RATS-L or VATS-L as the primary operation from 2010 to 2014. Cox proportional hazards models were used to estimate hazard ratios (HRs) for short- and long-term mortality using unmatched and propensity score-matched analyses. All statistical tests were 2-sided. Results: Patients treated by RATS-L had higher 90-day mortality than those with VATS-L (6.6% vs 3.8%, P = .03) if conversion to open thoracotomy occurred. After excluding first-year observation, multiple regression analyses showed RATS-L was associated with increased long-term mortality, compared with VATS-L, in cases with tumor size 20 mm or less: hazard ratio (HR) = 1.33 (95% confidence interval [CI] = 1.15 to 1.55), HR = 1.36 (95% CI = 1.17 to 1.58), and HR = 1.33 (95% CI = 1.11 to 1.61) for unmatched, N:1 matched, and 1:1 matched analyses, respectively, in the intention-to-treat analysis. Among patients without conversion to an open thoracotomy, the respective hazard ratios were 1.19 (95% CI = 1.10 to 1.29), 1.19 (95% CI = 1.10 to 1.29), and 1.17 (95% CI = 1.06 to 1.29). Similar associations were observed when follow-up time started 18 or 24 months postsurgery. No statistically significant mortality difference was found for patients with tumor size of greater than 20 mm. These associations were not related to case volume of VATS-L or RATS-L performed at treatment institutes. Conclusions: Patients with small (≤20 mm) stage I NSCLC treated with RATS-L had statistically significantly higher long-term mortality risk than VATS-L after 1 year postsurgery.

8.
Neurocomputing ; 397: 48-59, 2020 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-32863584

RESUMO

With the rapid development of image acquisition and storage, multiple images per class are commonly available for computer vision tasks (e.g., face recognition, object detection, medical imaging, etc.). Recently, the recurrent neural network (RNN) has been widely integrated with convolutional neural networks (CNN) to perform image classification on ordered (sequential) data. In this paper, by permutating multiple images as multiple dummy orders, we generalize the ordered "RNN+CNN" design (longitudinal) to a novel unordered fashion, called Multi-path x-D Recurrent Neural Network (MxDRNN) for image classification. To the best of our knowledge, few (if any) existing studies have deployed the RNN framework to unordered intra-class images to leverage classification performance. Specifically, multiple learning paths are introduced in the MxDRNN to extract discriminative features by permutating input dummy orders. Eight datasets from five different fields (MNIST, 3D-MNIST, CIFAR, VGGFace2, and lung screening computed tomography) are included to evaluate the performance of our method. The proposed MxDRNN improves the baseline performance by a large margin across the different application fields (e.g., accuracy from 46.40% to 76.54% in VGGFace2 test pose set, AUC from 0.7418 to 0.8162 in NLST lung dataset). Additionally, empirical experiments show the MxDRNN is more robust to category-irrelevant attributes (e.g., expression, pose in face images), which may introduce difficulties for image classification and algorithm generalizability. The code is publicly available.

9.
Cancer Res ; 80(22): 4972-4985, 2020 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-32978168

RESUMO

Lung squamous carcinoma (LUSC) is a highly metastatic disease with a poor prognosis. Using an integrated screening approach, we found that miR-671-5p reduces LUSC metastasis by inhibiting a circular RNA (circRNA), CDR1as. Although the putative function of circRNA is through miRNA sponging, we found that miR-671-5p more potently silenced an axis of CDR1as and its antisense transcript, cerebellar degeneration related protein 1 (CDR1). Silencing of CDR1as or CDR1 significantly inhibited LUSC metastases and CDR1 was sufficient to promote migration and metastases. CDR1, which directly interacted with adaptor protein 1 (AP1) complex subunits and coatomer protein I (COPI) proteins, no longer promoted migration upon blockade of Golgi trafficking. Therapeutic inhibition of the CDR1as/CDR1 axis with miR-671-5p mimics reduced metastasis in vivo. This report demonstrates a novel role for CDR1 in promoting metastasis and Golgi trafficking. These findings reveal an miRNA/circRNA axis that regulates LUSC metastases through a previously unstudied protein, CDR1. SIGNIFICANCE: This study shows that circRNA, CDR1as, promotes lung squamous migration, metastasis, and Golgi trafficking through its complimentary transcript, CDR1.

10.
Med Image Anal ; 65: 101785, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32745977

RESUMO

The Long Short-Term Memory (LSTM) network is widely used in modeling sequential observations in fields ranging from natural language processing to medical imaging. The LSTM has shown promise for interpreting computed tomography (CT) in lung screening protocols. Yet, traditional image-based LSTM models ignore interval differences, while recently proposed interval-modeled LSTM variants are limited in their ability to interpret temporal proximity. Meanwhile, clinical imaging acquisition may be irregularly sampled, and such sampling patterns may be commingled with clinical usages. In this paper, we propose the Distanced LSTM (DLSTM) by introducing time-distanced (i.e., time distance to the last scan) gates with a temporal emphasis model (TEM) targeting at lung cancer diagnosis (i.e., evaluating the malignancy of pulmonary nodules). Briefly, (1) the time distance of every scan to the last scan is modeled explicitly, (2) time-distanced input and forget gates in DLSTM are introduced across regular and irregular sampling sequences, and (3) the newer scan in serial data is emphasized by the TEM. The DLSTM algorithm is evaluated with both simulated data and real CT images (from 1794 National Lung Screening Trial (NLST) patients with longitudinal scans and 1420 clinical studied patients). Experimental results on simulated data indicate the DLSTM can capture families of temporal relationships that cannot be detected with traditional LSTM. Cross-validation on empirical CT datasets demonstrates that DLSTM achieves leading performance on both regularly and irregularly sampled data (e.g., improving LSTM from 0.6785 to 0.7085 on F1 score in NLST). In external-validation on irregularly acquired data, the benchmarks achieved 0.8350 (CNN feature) and 0.8380 (with LSTM) on AUC score, while the proposed DLSTM achieves 0.8905. In conclusion, the DLSTM approach is shown to be compatible with families of linear, quadratic, exponential, and log-exponential temporal models. The DLSTM can be readily extended with other temporal dependence interactions while hardly increasing overall model complexity.

11.
J Thorac Dis ; 12(6): 3317-3330, 2020 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-32642255

RESUMO

The 2010's saw demonstration of the power of lung cancer screening to reduce mortality. However, with implementation of lung cancer screening comes the challenge of diagnosing millions of lung nodules every year. When compared to other cancers with widespread screening strategies (breast, colorectal, cervical, prostate, and skin), obtaining a lung nodule tissue biopsy to confirm a positive screening test remains associated with higher morbidity and cost. Therefore, non-invasive diagnostic biomarkers may have a unique opportunity in lung cancer to greatly improve the management of patients at risk. This review covers recent advances in the field of liquid biomarkers and computed tomographic imaging features, with special attention to new methods for combination of biomarkers as well as the use of artificial intelligence for the discrimination of benign from malignant nodules.

12.
Ann Thorac Surg ; 2020 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-32682756

RESUMO

BACKGROUND: Granulomas caused by infectious lung diseases can present as indeterminate pulmonary nodules (IPN). This study aims to validate an enzyme immunoassay (EIA) for histoplasma immunoglobulins G and M (IgG, IgM) for diagnosing benign IPN in areas with endemic histoplasmosis. METHODS: Prospectively collected serum samples from patients at Vanderbilt University Medical Center (VUMC, n=204), University of Pittsburgh Medical Center (UPMC, n=71), and University of Cincinnati (UC, n=51) with IPN measuring 6-30mm were analyzed for histoplasma IgG and IgM with EIA. Diagnostic test characteristics were compared to results from VUMC pilot cohort (n=127). A multivariable logistic regression model was developed to predict granuloma in IPN. RESULTS: Cancer prevalence varied by cohort: VUMC pilot 60%, VUMC validation 65%, UPMC 35%, UC 75%. Across all cohorts, 19% of patients had positive IgG titers, 5% positive IgM, and 3% both positive IgG and IgM. Of patients with benign disease, 33% were positive for at least one antibody. All patients positive for both IgG and IgM antibodies at acute infection levels had benign disease (n=13), with a positive predictive value of 100%. The prediction model for granuloma in IPN demonstrated an area under receiver operating curve 0.84 and Brier score of 0.10. CONCLUSIONS: This study confirmed that histoplasma EIA testing can be useful for diagnosing benign IPN in areas with endemic histoplasmosis in a population at high risk for lung cancer. Integrating histoplasma EIA testing into the current diagnostic algorithm where histoplasmosis is endemic could improve management of IPN and potentially decrease unnecessary invasive biopsies.

13.
Cancer Cell ; 38(2): 229-246.e13, 2020 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-32707077

RESUMO

Tumor evolution from a single cell into a malignant, heterogeneous tissue remains poorly understood. Here, we profile single-cell transcriptomes of genetically engineered mouse lung tumors at seven stages, from pre-neoplastic hyperplasia to adenocarcinoma. The diversity of transcriptional states increases over time and is reproducible across tumors and mice. Cancer cells progressively adopt alternate lineage identities, computationally predicted to be mediated through a common transitional, high-plasticity cell state (HPCS). Accordingly, HPCS cells prospectively isolated from mouse tumors and human patient-derived xenografts display high capacity for differentiation and proliferation. The HPCS program is associated with poor survival across human cancers and demonstrates chemoresistance in mice. Our study reveals a central principle underpinning intra-tumoral heterogeneity and motivates therapeutic targeting of the HPCS.

14.
Am J Respir Crit Care Med ; 202(2): 241-249, 2020 07 15.
Artigo em Inglês | MEDLINE | ID: mdl-32326730

RESUMO

Rationale: The management of indeterminate pulmonary nodules (IPNs) remains challenging, resulting in invasive procedures and delays in diagnosis and treatment. Strategies to decrease the rate of unnecessary invasive procedures and optimize surveillance regimens are needed.Objectives: To develop and validate a deep learning method to improve the management of IPNs.Methods: A Lung Cancer Prediction Convolutional Neural Network model was trained using computed tomography images of IPNs from the National Lung Screening Trial, internally validated, and externally tested on cohorts from two academic institutions.Measurements and Main Results: The areas under the receiver operating characteristic curve in the external validation cohorts were 83.5% (95% confidence interval [CI], 75.4-90.7%) and 91.9% (95% CI, 88.7-94.7%), compared with 78.1% (95% CI, 68.7-86.4%) and 81.9 (95% CI, 76.1-87.1%), respectively, for a commonly used clinical risk model for incidental nodules. Using 5% and 65% malignancy thresholds defining low- and high-risk categories, the overall net reclassifications in the validation cohorts for cancers and benign nodules compared with the Mayo model were 0.34 (Vanderbilt) and 0.30 (Oxford) as a rule-in test, and 0.33 (Vanderbilt) and 0.58 (Oxford) as a rule-out test. Compared with traditional risk prediction models, the Lung Cancer Prediction Convolutional Neural Network was associated with improved accuracy in predicting the likelihood of disease at each threshold of management and in our external validation cohorts.Conclusions: This study demonstrates that this deep learning algorithm can correctly reclassify IPNs into low- or high-risk categories in more than a third of cancers and benign nodules when compared with conventional risk models, potentially reducing the number of unnecessary invasive procedures and delays in diagnosis.


Assuntos
Aprendizado Profundo , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/fisiopatologia , Nódulos Pulmonares Múltiplos/diagnóstico por imagem , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Algoritmos , Humanos , Neoplasias Pulmonares/epidemiologia , Redes Neurais de Computação , Estados Unidos/epidemiologia
15.
Front Oncol ; 10: 349, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32257951

RESUMO

Lung cancer is one of the deadliest diseases in the world and is the leading cause of cancer-related deaths. Among the histological types, adenocarcinoma is the most common, and it is characterized by a high degree of heterogeneity at many levels including clinical, behavioral, cellular and molecular. While most lung cancers are known for their aggressive behavior, up to 18.5% of lung cancers detected by CT screening are indolent and put patients at risk for overdiagnosis and overtreatment. The cellular and molecular underpinnings of tumor behavior remain largely unknown. In the recent years, the study of intratumor heterogeneity has become an attractive strategy to understand tumor progression. This review will summarize some of the current known determinants of lung adenocarcinoma behavior and discuss recent efforts to dissect its intratumor heterogeneity.

16.
Nature ; 580(7802): 245-251, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-32269342

RESUMO

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.


Assuntos
DNA Tumoral Circulante/análise , DNA Tumoral Circulante/genética , Detecção Precoce de Câncer/métodos , Genoma Humano/genética , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/genética , Mutação , Estudos de Coortes , Feminino , Hematopoese/genética , Humanos , Pulmão/metabolismo , Pulmão/patologia , Neoplasias Pulmonares/sangue , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes
17.
J Am Coll Radiol ; 17(2): 208-215, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31499025

RESUMO

BACKGROUND: Detection of early-stage lung cancer improves during subsequent rounds of screening with low-dose CT and potentially leads to saving lives with curative treatment. Therefore, adherence to annual lung screening is important. We hypothesized that adherence to annual screening would increase after hiring of a dedicated program coordinator. METHODS: We performed a mixed-methods study in a retrospective cohort of patients who underwent lung screening at our academic institution between January 1, 2014, and March 31, 2018. Patients with baseline lung screening examinations performed between January 1, 2014, and September 30, 2016, with Lung CT Screening Reporting & Data System 1 or 2 scores and a 12-month follow-up recommendation were included. We tracked patient adherence to annual follow-up lung screening over time (before and after hiring of a program coordinator) and conducted a cross-sectional survey of patients nonadherent to annual follow-up to elicit quantitative and qualitative feedback. RESULTS: Of the 319 patients who completed baseline lung screening with normal results, 189 (59%) were adherent to annual follow-up recommendations and 130 (41%) were nonadherent. Patient adherence varied over time: 21.7% adherence (10 of 46) before hiring a program coordinator and 65.6% adherence (179 of 273) after the program coordinator's hire date. Patients reported the following reasons for nonadherence to annual lung screening: lack of transportation, financial cost, lack of communication by physicians, and lack of current symptoms. CONCLUSIONS: Adherence to annual lung screening after normal baseline studies increased significantly over time. Hiring a full-time program coordinator was likely associated with this increased in adherence.

18.
Am J Respir Crit Care Med ; 201(6): 697-706, 2020 03 15.
Artigo em Inglês | MEDLINE | ID: mdl-31747302

RESUMO

Rationale: We have a limited understanding of the molecular underpinnings of early adenocarcinoma (ADC) progression. We hypothesized that the behavior of early ADC can be predicted based on genomic determinants.Objectives: To identify genomic alterations associated with resected indolent and aggressive early lung ADCs.Methods: DNA was extracted from 21 ADCs in situ (AISs), 27 minimally invasive ADCs (MIAs), and 54 fully invasive ADCs. This DNA was subjected to deep next-generation sequencing and tested against a custom panel of 347 cancer genes.Measurements and Main Results: Sequencing data was analyzed for associations among tumor mutation burden, frequency of mutations or copy number alterations, mutation signatures, intratumor heterogeneity, pathway alterations, histology, and overall survival. We found that deleterious mutation burden was significantly greater in invasive ADC, whereas more copy number loss was observed in AIS and MIA. Intratumor heterogeneity establishes early, as in AIS. Twenty-one significantly mutated genes were shared among the groups. Mutation signature profiling did not vary significantly, although the APOBEC signature was associated with ADC and poor survival. Subclonal KRAS mutations and a gene signature consisting of PIK3CG, ATM, EPPK1, EP300, or KMT2C mutations were also associated with poor survival. Mutations of KRAS, TP53, and NF1 were found to increase in frequency from AIS and MIA to ADC. A cancer progression model revealed selective early and late drivers.Conclusions: Our results reveal several genetic driver events, clonality, and mutational signatures associated with poor outcome in early lung ADC, with potential future implications for the detection and management of ADC.


Assuntos
Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/fisiopatologia , Biomarcadores Tumorais/genética , Detecção Precoce de Câncer/métodos , Predisposição Genética para Doença , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/fisiopatologia , Adulto , Idoso , Estudos de Coortes , Feminino , Genômica , Humanos , Masculino , Pessoa de Meia-Idade , Mutação
19.
Clin Imaging ; 73: 151-161, 2020 Dec 26.
Artigo em Inglês | MEDLINE | ID: mdl-33422974

RESUMO

INTRODUCTION: The Veterans Affairs Partnership to increase Access to Lung Screening (VA-PALS) is an enterprise-wide initiative to implement lung cancer screening programs at VA medical centers (VAMCs). VA-PALS will be using implementation strategies that include program navigators to coordinate screening activities, trainings for navigators and radiologists, an open-source software management system, tools to standardize low-dose computed tomography image quality, and access to a support network. VAMCs can utilize strategies according to their local needs. In this protocol, we describe the planned program evaluation for the initial 10 VAMCs participating in VA-PALS. MATERIALS AND METHODS: The implementation of programs will be evaluated using the Consolidated Framework for Implementation Research to ensure broad contextual guidance. Program evaluation measures have been developed using the Reach, Effectiveness, Adoption, Implementation and Maintenance framework. Adaptations of screening processes will be assessed using the Framework for Reporting Adaptations and Modifications to Evidence Based Interventions. Measures collected will reflect the inner settings, estimate and describe the population reached, adoption by providers, implementation of the programs, report clinical outcomes and maintenance of programs. Analyses will include descriptive statistics and regression to evaluate predictors and assess implementation over time. DISCUSSION: This theory-based protocol will evaluate the implementation of lung cancer screening programs across the Veterans Health Administration using scientific frameworks. The findings will inform plans to expand the VA-PALS initiative beyond the original sites and can guide implementation of lung cancer screening programs more broadly.

20.
Transl Lung Cancer Res ; 8(5): 636-648, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31737499

RESUMO

Background: Our previous studies have identified a serum-based 4-microRNA (4-miRNA) signature that may help distinguish patients with lung cancer (LC) from non-cancer controls (NCs). Here, we used an extended independent cohort of 398 subjects to further validate the diagnostic ability of this 4-miRNA signature. Methods: Using quantitative reverse transcription polymerase chain reaction (qRT-PCR), expression of the 4-miRNAs was assessed in a total of 398 sera that included 213 LC patients and 185 NCs. A logistic regression model using training-test sets, receiver operating characteristic (ROC) curve analysis and t-test were used to test the impact of varying expression of these miRNAs on its diagnostic accuracy for LC. The cell proliferation and colony formation affected by these miRNAs, as well as gene ontology (GO) analysis of miRNA target genes were performed. Results: The levels of the 4-miRNAs were significantly higher in the serum of patients with LCs as compared to NCs. Using a logistic regression prediction model based on training and test sets analysis, we obtained the area under the curve (AUC) of 0.921 [95% confidence interval (CI), 0.876-0.966] on the test set with specificity 90.6%, sensitivity 77.9%, accuracy 84.1%, positive predictive value (PPV) 89.8% and negative predictive value (NPV) 79.5%. Conclusions: We have verified that this serum 4-miRNA signature could provide a promising noninvasive biomarker for the prediction of LC, particularly in patients with indeterminate lung nodules on screening CT scans.

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