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1.
Artigo em Inglês | MEDLINE | ID: mdl-33431509

RESUMO

Medical imaging is the standard-of-care for early detection, diagnosis, treatment planning, monitoring, and image-guided interventions of lung cancer patients. Most medical images are stored digitally in a standardized Digital Imaging and Communications in Medicine format that can be readily accessed and used for qualitative and quantitative analysis. Over the several last decades, medical images have been shown to contain complementary and interchangeable data orthogonal to other sources such as pathology, hematology, genomics, and/or proteomics. As such, "radiomics" has emerged as a field of research that involves the process of converting standard-of-care images into quantitative image-based data that can be merged with other data sources and subsequently analyzed using conventional biostatistics or artificial intelligence (AI) methods. As radiomic features capture biological and pathophysiological information, these quantitative radiomic features have shown to provide rapid and accurate noninvasive biomarkers for lung cancer risk prediction, diagnostics, prognosis, treatment response monitoring, and tumor biology. In this review, radiomics and emerging AI methods in lung cancer research are highlighted and discussed including advantages, challenges, and pitfalls.

2.
Cancer Res ; 2021 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-33472890

RESUMO

Lung cancer is the leading cause of cancer death globally. An improved risk stratification strategy can increase efficiency of low-dose computed tomography (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. Based on 13,119 lung cancer patients and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK biobank data (N=335,931). Absolute risk was estimated based on age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial, N=50,772 participants). The lung cancer odds ratio (ORs) for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 (95%CI=1.92-3.00, P=1.80x10-14) in the validation set (trend p-value of 5.26 x 10-20). The OR per standard deviation of PRS increase was 1.26 (95%CI=1.20-1.32, P=9.69x10-23) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status and family history. Collectively, these results suggest that Individual's genetic background may inform the optimal lung cancer LDCT screening strategy.

3.
Lung Cancer ; 152: 58-65, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33352384

RESUMO

INTRODUCTION: The relationship between Body-Mass-Index (BMI) and lung cancer prognosis is heterogeneous. We evaluated the impact of sex, smoking and race on the relationship between BMI and overall survival (OS) in non-small-cell-lung-cancer (NSCLC). METHODS: Data from 16 individual ILCCO studies were pooled to assess interactions between BMI and the following factors on OS: self-reported race, smoking status and sex, using Cox models (adjusted hazard ratios; aHR) with interaction terms and adjusted penalized smoothing spline plots in stratified analyses. RESULTS: Among 20,937 NSCLC patients with BMI values, females = 47 %; never-smokers = 14 %; White-patients = 76 %. BMI showed differential survival according to race whereby compared to normal-BMI patients, being underweight was associated with poor survival among white patients (OS, aHR = 1.66) but not among black patients (aHR = 1.06; pinteraction = 0.02). Comparing overweight/obese to normal weight patients, Black NSCLC patients who were overweight/obese also had relatively better OS (pinteraction = 0.06) when compared to White-patients. BMI was least associated with survival in Asian-patients and never-smokers. The outcomes of female ever-smokers at the extremes of BMI were associated with worse outcomes in both the underweight (pinteraction<0.001) and obese categories (pinteraction = 0.004) relative to the normal-BMI category, when compared to male ever-smokers. CONCLUSION: Underweight and obese female ever-smokers were associated with worse outcomes in White-patients. These BMI associations were not observed in Asian-patients and never-smokers. Black-patients had more favorable outcomes in the extremes of BMI when compared to White-patients. Body composition in Black-patients, and NSCLC subtypes more commonly seen in Asian-patients and never-smokers, may account for differences in these BMI-OS relationships.

4.
Cancer Manag Res ; 12: 12225-12238, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33273859

RESUMO

Rationale and Objectives: Evaluate ability of radiological semantic traits assessed on multi-window computed tomography (CT) to predict lung cancer risk. Materials and Methods: A total of 199 participants were investigated, including 60 incident lung cancers and 139 benign positive controls. Twenty lung window features and 2 mediastinal window features were extracted and scored on a point scale in three screening rounds. Multivariate logistic regression analysis was used to explore the association of these radiological traits with the risk of developing lung cancer. The areas under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and positive predictive value (PPV) were computed to evaluate the best predictive model. Results: Combining mediastinal window-specific features with the lung window features-based model significantly improves performance compared to individual window features. Model performance is consistent both at baseline and the first follow-up scan, with an AUROC increased from 0.822 to 0.871 (p = 0.009) and from 0.877 to 0.917 (p = 0.008), respectively, for single to multi-window feature models. We also find that the multi-window CT based model showed better specificity and PPV, with PPV at the second follow-up scan improved to 0.953. Conclusion: We find combining window semantic features improves model performance in identifying cancerous nodules. We also find that lung window features are more informative compared to mediastinal features in predicting malignancy.

5.
BMC Med Genomics ; 13(1): 162, 2020 10 30.
Artigo em Inglês | MEDLINE | ID: mdl-33126877

RESUMO

BACKGROUND: Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenges. We addressed the computational burden encountered when detecting SNP interactions for survival analysis, such as age of disease-onset. To confront this problem, we developed a novel algorithm, called the Efficient Survival Multifactor Dimensionality Reduction (ES-MDR) method, which used Martingale Residuals as the outcome parameter to estimate survival outcomes, and implemented the Quantitative Multifactor Dimensionality Reduction method to identify significant interactions associated with age of disease-onset. METHODS: To demonstrate efficacy, we evaluated this method on two simulation data sets to estimate the type I error rate and power. Simulations showed that ES-MDR identified interactions using less computational workload and allowed for adjustment of covariates. We applied ES-MDR on the OncoArray-TRICL Consortium data with 14,935 cases and 12,787 controls for lung cancer (SNPs = 108,254) to search over all two-way interactions to identify genetic interactions associated with lung cancer age-of-onset. We tested the best model in an independent data set from the OncoArray-TRICL data. RESULTS: Our experiment on the OncoArray-TRICL data identified many one-way and two-way models with a single-base deletion in the noncoding region of BRCA1 (HR 1.24, P = 3.15 × 10-15), as the top marker to predict age of lung cancer onset. CONCLUSIONS: From the results of our extensive simulations and analysis of a large GWAS study, we demonstrated that our method is an efficient algorithm that identified genetic interactions to include in our models to predict survival outcomes.

6.
Nat Commun ; 11(1): 5228, 2020 10 16.
Artigo em Inglês | MEDLINE | ID: mdl-33067442

RESUMO

Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of strategy is based on heterogeneous biomarkers that can dynamically change during therapy. Thus, there is a compelling need to identify comprehensive biomarkers that can be used longitudinally to help guide therapy choice. Herein, we report a 18F-FDG-PET/CT-based deep learning model, which demonstrates high accuracy in EGFR mutation status prediction across patient cohorts from different institutions. A deep learning score (EGFR-DLS) was significantly and positively associated with longer progression free survival (PFS) in patients treated with EGFR-TKIs, while EGFR-DLS is significantly and negatively associated with higher durable clinical benefit, reduced hyperprogression, and longer PFS among patients treated with ICIs. Thus, the EGFR-DLS provides a non-invasive method for precise quantification of EGFR mutation status in NSCLC patients, which is promising to identify NSCLC patients sensitive to EGFR-TKI or ICI-treatments.


Assuntos
Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Aprendizado Profundo , Neoplasias Pulmonares/diagnóstico por imagem , Inibidores de Proteínas Quinases/administração & dosagem , Idoso , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Receptores ErbB/genética , Receptores ErbB/metabolismo , Feminino , Humanos , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/mortalidade , Masculino , Pessoa de Meia-Idade , Mutação , Tomografia Computadorizada com Tomografia por Emissão de Pósitrons , Intervalo Livre de Progressão
7.
Front Med ; 2020 Sep 05.
Artigo em Inglês | MEDLINE | ID: mdl-32889700

RESUMO

Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer (NSCLC) risk, biological mechanisms of these variants remain largely unknown. By integrating a large-scale genotype data of 15 581 lung adenocarcinoma (AD) cases, 8350 squamous cell carcinoma (SqCC) cases, and 27 355 controls, as well as multiple transcriptome and epigenomic databases, we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility variants. We identified 3064 credible risk variants for NSCLC, which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive sites. Transcription factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was SqCC-specific. Functional annotation and gene-based analysis implicated 894 target genes, including 274 specifics for AD and 123 for SqCC, which were overrepresented in somatic driver genes (ER = 1.95, P = 0.005). Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways, while SqCC genes were homologous recombination deficiency related. Our results illustrate the molecular basis of both well-studied and new susceptibility loci of NSCLC, providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.

8.
Patient Educ Couns ; 2020 Sep 22.
Artigo em Inglês | MEDLINE | ID: mdl-32981814

RESUMO

OBJECTIVES: Sexual and gender minority (SGM) individuals experience cancer-related health disparities and reduced quality of cancer care compared to the general population in part due to a lack of knowledgeable providers. This study explored oncologists' experiences and perspectives in providing patient-centered care for SGM individuals with cancer. METHODS: We conducted a qualitative analysis of oncologists' responses to four open-ended items on a national survey eliciting their experiences, reservations, and suggestions in treating SGM patients. RESULTS: Over 50 % of the 149 respondents of the national survey responded to at least one open-ended item. Many oncologists reported positive experiences reflecting personal growth and affirmative care practices, such as open, non-judgmental communication, compassion, competence, and supporting patients' identity. There was a notable lack of experience with transgender patients in particular. Lack of knowledge, interpersonal communication concerns (e.g., fear of offending patients), and microaggressions ("don't ask, don't tell") were identified as barriers to providing affirming care. CONCLUSIONS: Oncologists recognize their knowledge deficits and need strategies to overcome communication barriers and microaggressions among the cancer care team to provide SGM-affirming care. PRACTICE IMPLICATIONS: Curricula are needed to train oncologists in SGM healthcare needs and affirming communication skills to facilitate patient-centered care for SGM individuals with cancer.

9.
Genet Epidemiol ; 2020 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-32924180

RESUMO

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1ß pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

10.
Cancer Epidemiol Biomarkers Prev ; 29(12): 2556-2567, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-32917666

RESUMO

Imaging is a key technology in the early detection of cancers, including X-ray mammography, low-dose CT for lung cancer, or optical imaging for skin, esophageal, or colorectal cancers. Historically, imaging information in early detection schema was assessed qualitatively. However, the last decade has seen increased development of computerized tools that convert images into quantitative mineable data (radiomics), and their subsequent analyses with artificial intelligence (AI). These tools are improving diagnostic accuracy of early lesions to define risk and classify malignant/aggressive from benign/indolent disease. The first section of this review will briefly describe the various imaging modalities and their use as primary or secondary screens in an early detection pipeline. The second section will describe specific use cases to illustrate the breadth of imaging modalities as well as the benefits of quantitative image analytics. These will include optical (skin cancer), X-ray CT (pancreatic and lung cancer), X-ray mammography (breast cancer), multiparametric MRI (breast and prostate cancer), PET (pancreatic cancer), and ultrasound elastography (liver cancer). Finally, we will discuss the inexorable improvements in radiomics to build more robust classifier models and the significant limitations to this development, including access to well-annotated databases, and biological descriptors of the imaged feature data.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

11.
Int J Cancer ; 2020 Sep 11.
Artigo em Inglês | MEDLINE | ID: mdl-32914876

RESUMO

At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a positive causal effect for high BMI on occurrence of small-cell lung cancer (odds ratio (OR) = 1.60, 95% confidence interval (CI) = 1.24-2.06, P = 2.70 × 10-4 ). After adjustment of smoking behaviors using multivariable Mendelian randomization (MVMR), a direct causal effect on small cell lung cancer (ORMVMR = 1.28, 95% CI = 1.06-1.55, PMVMR = .011), and an inverse effect on lung adenocarcinoma (ORMVMR = 0.86, 95% CI = 0.77-0.96, PMVMR = .008) were observed. A weak increased risk of lung squamous cell carcinoma was observed for higher BMI in univariable Mendelian randomization (UVMR) analysis (ORUVMR = 1.19, 95% CI = 1.01-1.40, PUVMR = .036), but this effect disappeared after adjustment of smoking (ORMVMR = 1.02, 95% CI = 0.90-1.16, PMVMR = .746). These results highlight the histology-specific impact of BMI on lung carcinogenesis and imply mediator role of smoking behaviors in the association between BMI and lung cancer.

12.
Contemp Clin Trials Commun ; 19: 100597, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32613134

RESUMO

Biobanks have the potential to be robust resource for understanding potential cancer risks associated with gender-affirming interventions. In this narrative review, we synthesized the current published literature regarding the inclusion of TGD health data in cancer biorepositories and cancer research conducted on biospecimens. Of the 6986 initial results, 153 (2.2%) assessed the biological effects of gender-affirming interventions on TGD tissues. Within that category, only one paper examined transgender tissues in relation to cancer biobanks. Strategies are offered to address the inequities in TGD tissue-based research and diversify the field of biobanking as a whole.

13.
Sci Rep ; 10(1): 10528, 2020 06 29.
Artigo em Inglês | MEDLINE | ID: mdl-32601340

RESUMO

The National Lung Screening Trial (NLST) demonstrated that screening with low-dose computed tomography (LDCT) is associated with a 20% reduction in lung cancer mortality. One potential limitation of LDCT screening is overdiagnosis of slow growing and indolent cancers. In this study, peritumoral and intratumoral radiomics was used to identify a vulnerable subset of lung patients associated with poor survival outcomes. Incident lung cancer patients from the NLST were split into training and test cohorts and an external cohort of non-screen detected adenocarcinomas was used for further validation. After removing redundant and non-reproducible radiomics features, backward elimination analyses identified a single model which was subjected to Classification and Regression Tree to stratify patients into three risk-groups based on two radiomics features (NGTDM Busyness and Statistical Root Mean Square [RMS]). The final model was validated in the test cohort and the cohort of non-screen detected adenocarcinomas. Using a radio-genomics dataset, Statistical RMS was significantly associated with FOXF2 gene by both correlation and two-group analyses. Our rigorous approach generated a novel radiomics model that identified a vulnerable high-risk group of early stage patients associated with poor outcomes. These patients may require aggressive follow-up and/or adjuvant therapy to mitigate their poor outcomes.

14.
Cancer Control ; 27(1): 1073274820931808, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32496158

RESUMO

Although ibrutinib-associated atrial and ventricular arrhythmias have been well described, there is little information about ibrutinib's effects on other electrocardiographic parameters, particularly the QT interval. Using our database of 137 patients treated with ibrutinib, we retrospectively identified 21 patients in whom an electrocardiogram (ECG) was obtained both prior to and after ibrutinib exposure. All traditional ECG parameters as well as QT dispersion were manually measured by an electrophysiologist. Compared to baseline ECGs, post ibrutinib ECGs demonstrated QT interval shortening from 386 ms to 356 ms (P = .007), corrected QT interval shortening using Bazett's formula from 446 ms to 437 ms (P = .04), and corrected QT interval shortening using Fridericia's formula from 425 ms to 407 ms (P = .003). QT dispersion also increased post ibrutinib exposure compared to baseline (39.8 ms vs 57.3 ms, P = .002). There was no significant change in other ECG parameters. In conclusion, both the absolute and corrected QT intervals significantly shortened after ibrutinib exposure, while there was a significant increase in QT dispersion. These findings may point to a common underlying electrophysiologic mechanism of ibrutinib-associated arrhythmias.

15.
JCO Oncol Pract ; 16(10): e1192-e1201, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32525751

RESUMO

PURPOSE: Biobanks usually do not collect transgender and gender-diverse (TGD) demographic information, hindering research on cancer risk and biological effects related to gender-affirming interventions. METHODS: In August 2019, 172 scientists involved in biobanking research at a single institution (H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL) were invited to complete a survey measuring knowledge and attitudes about TGD health and research practices. Quantitative and qualitative analyses were performed. RESULTS: Among 47 respondents, there was high agreement (77%) regarding the importance of collecting TGD identities and histories of gender-affirming treatments with biospecimens, which was contrasted by low self-reported rates of respondents' biorepositories allowing for the entry of TGD identities (14.9%) and histories of gender-affirming interventions (8.5%). There was high interest in receiving education regarding the unique cancer health needs of TGD patients (74%), and knowledge questions yielded high percentages of "neutral" and "don't know or prefer not to answer" responses. After completing the survey, confidence in knowledge of health needs for TGD patients decreased significantly (48.9% were confident during the presurvey assessment v 36.2% in the postsurvey assessment; P < .001). Qualitative analysis of open-ended questions indicated overall support of TGD data inclusion in biobanks along with perceived barriers to inclusion of such data in biobanks. CONCLUSION: To our knowledge, this was the first study of researchers to assess knowledge, attitudes, and research practices regarding TGD patients. Overall, there was limited knowledge about TGD health and cancer needs and low rates of TGD demographic data collection but a high interest in receiving education regarding this community.

17.
Tomography ; 6(2): 209-215, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32548298

RESUMO

Noninvasive diagnosis of lung cancer in early stages is one task where radiomics helps. Clinical practice shows that the size of a nodule has high predictive power for malignancy. In the literature, convolutional neural networks (CNNs) have become widely used in medical image analysis. We study the ability of a CNN to capture nodule size in computed tomography images after images are resized for CNN input. For our experiments, we used the National Lung Screening Trial data set. Nodules were labeled into 2 categories (small/large) based on the original size of a nodule. After all extracted patches were re-sampled into 100-by-100-pixel images, a CNN was able to successfully classify test nodules into small- and large-size groups with high accuracy. To show the generality of our discovery, we repeated size classification experiments using Common Objects in Context (COCO) data set. From the data set, we selected 3 categories of images, namely, bears, cats, and dogs. For all 3 categories a 5- × 2-fold cross-validation was performed to put them into small and large classes. The average area under receiver operating curve is 0.954, 0.952, and 0.979 for the bear, cat, and dog categories, respectively. Thus, camera image rescaling also enables a CNN to discover the size of an object. The source code for experiments with the COCO data set is publicly available in Github (https://github.com/VisionAI-USF/COCO_Size_Decoding/).

18.
Cancer Control ; 27(1): 1073274820924728, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32397742

RESUMO

Although penile carcinoma is a rare malignancy, there is still an unmet need to identify prognostic factors associated with poor survival. In this study, we utilized demographic and clinical information to identify the most informative variables associated with overall survival in patients with penile cancer. From a full model including all covariates found to be statistically significant in univariable analyses, we identified a parsimonious reduced model containing tumor site (penis glans: hazard ratio [HR] = 0.48; 95% CI: 0.28-0.85 and penis not otherwise specified: HR = 0.45; 95% CI: 0.25-0.84), undetermined tumor differentiation (HR = 0.48; 95% CI: 0.27-0.86), and TNM stage III/IV (HR = 2.83; 95% CI: 1.68-4.75). When all of the covariates from the full model were subjected to classification and regression tree analysis, we identified 6 novel risk groups. Of particular interest, we found marriage was associated with substantial improvement in survival among men with the same stage and disease site. Specifically, among single/widowed/divorced men with TNM stage 0-II and prepuce/penis corpus/overlapping lesions had worse survival (5-year survival = 18.2%) versus married men (5-year survival = 62.5%). Since marital status is linked to social support, these findings warrant a deeper investigation into the relationships between disease prognosis and social support in patients with penile carcinoma.

19.
Nat Commun ; 11(1): 2220, 2020 05 11.
Artigo em Inglês | MEDLINE | ID: mdl-32393777

RESUMO

Few germline mutations are known to affect lung cancer risk. We performed analyses of rare variants from 39,146 individuals of European ancestry and investigated gene expression levels in 7,773 samples. We find a large-effect association with an ATM L2307F (rs56009889) mutation in adenocarcinoma for discovery (adjusted Odds Ratio = 8.82, P = 1.18 × 10-15) and replication (adjusted OR = 2.93, P = 2.22 × 10-3) that is more pronounced in females (adjusted OR = 6.81 and 3.19 and for discovery and replication). We observe an excess loss of heterozygosity in lung tumors among ATM L2307F allele carriers. L2307F is more frequent (4%) among Ashkenazi Jewish populations. We also observe an association in discovery (adjusted OR = 2.61, P = 7.98 × 10-22) and replication datasets (adjusted OR = 1.55, P = 0.06) with a loss-of-function mutation, Q4X (rs150665432) of an uncharacterized gene, KIAA0930. Our findings implicate germline genetic variants in ATM with lung cancer susceptibility and suggest KIAA0930 as a novel candidate gene for lung cancer risk.


Assuntos
Adenocarcinoma/genética , Proteínas Mutadas de Ataxia Telangiectasia/genética , Neoplasias Pulmonares/genética , Idoso , Alelos , Bases de Dados Genéticas , Grupo com Ancestrais do Continente Europeu/genética , Feminino , Predisposição Genética para Doença , Técnicas de Genotipagem , Mutação em Linhagem Germinativa , Heterozigoto , Humanos , Judeus/genética , Masculino , Pessoa de Meia-Idade , Mutação de Sentido Incorreto , Razão de Chances , Análise de Sequência com Séries de Oligonucleotídeos , Linhagem , RNA-Seq , Fatores de Risco
20.
J Clin Nurs ; 29(15-16): 2953-2966, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32320511

RESUMO

AIMS AND OBJECTIVES: To evaluate the knowledge and attitudes towards sexual and gender minority (SGM) oncology patients' needs among advanced practice providers (APPs). BACKGROUND: SGM individuals experience health disparities, in part due to lack of access to knowledgeable providers. Despite the important role of APPs in cancer care, less is known about their attitudes and knowledge towards SGM cancer patients. DESIGN: Cross-sectional study. METHODS: A survey of APPs at a National Cancer Institute-Designated Comprehensive Cancer Center assessed self-reported demographics, attitudes, knowledge and postsurvey confidence in knowledge of SGM oncology patient needs. Reporting of this study adheres to STROBE guidelines. RESULTS: Knowledge of health needs was low with an average of 2.56 (SD = 1.27) items answered correctly out of 6. The majority of APPs self-reported being comfortable treating SGM patients (93.6% and 87.2%, respectively), but less confident in knowledge of their health needs (68.0% and 53.8%, respectively). Although less than half of APPs believed education should be mandatory (44.9%), 79.5% were interested in education about SGMs' unique health needs. Political affiliation, medical specialty, licensure, and having SGM friends or family were associated with various attitude items, but not knowledge. Moderation analyses indicated that APPs who had greater overall knowledge scores were more likely to agree, on average, that knowing sexual orientation, gender identity and sex assigned at birth are important to providing quality oncology care. CONCLUSION: APPs report being comfortable providing care for SGMs with cancer, but knowledge gaps remain that may inhibit the quality of care provided. Given the interest in education, results would support the development of SGM-related healthcare training for oncology APPs. RELEVANCE TO CLINICAL PRACTICE: Targeted education for providers during training and continuing education is likely to improve the provision of quality care for SGMs with cancer.


Assuntos
Prática Avançada de Enfermagem/métodos , Atitude do Pessoal de Saúde , Conhecimentos, Atitudes e Prática em Saúde , Neoplasias/enfermagem , Minorias Sexuais e de Gênero/psicologia , Adulto , Estudos Transversais , Feminino , Humanos , Masculino , Autorrelato , Inquéritos e Questionários
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