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Article ; Online: The Rapid Rise in Cutaneous Melanoma Diagnoses.

Grossman, Douglas / Sweeney, Carol / Doherty, Jennifer A

2021 Volume 384, Issue 14, Page(s) e54

MeSH term(s)	Humans ; Incidence ; Melanoma/diagnosis ; Melanoma/epidemiology ; Skin Neoplasms/diagnosis ; Skin Neoplasms/epidemiology
Language	English
Publishing date	2021-04-07
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	207154-x
ISSN	1533-4406 ; 0028-4793
ISSN (online)	1533-4406
ISSN	0028-4793
DOI	10.1056/NEJMc2101980
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Article ; Online: Familial risk of epithelial ovarian cancer after accounting for gynaecological surgery: a population-based study.

Barnard, Mollie E / Meeks, Huong / Jarboe, Elke A / Albro, James / Camp, Nicola J / Doherty, Jennifer A

Journal of medical genetics

2022 Volume 60, Issue 2, Page(s) 119–127

Abstract: Background: Uptake of risk-reducing surgery has increased among women at high risk of epithelial ovarian cancer. We sought to characterise familial risk of epithelial ovarian cancer histotypes in a population-based study after accounting for ... ...

Abstract	Background: Uptake of risk-reducing surgery has increased among women at high risk of epithelial ovarian cancer. We sought to characterise familial risk of epithelial ovarian cancer histotypes in a population-based study after accounting for gynaecological surgeries, including bilateral oophorectomy. Methods: We compared risk of epithelial ovarian cancer in relatives of 3536 epithelial ovarian cancer cases diagnosed in 1966-2016 and relatives of 35 326 matched controls. We used Cox competing risk models, incorporating bilateral oophorectomy as a competing risk, to estimate the relative risk of ovarian cancer in first-degree (FDR), second-degree (SDR) and third-degree (TDR) relatives from 1966 to 2016. We also estimated relative risks in time periods before (1966-1994, 1995-2004) and after (2005-2016) formal recommendations were made for prophylactic oophorectomy among women with pathogenic variants in Results: The relative risks of epithelial ovarian cancer in FDRs, SDRs and TDRs of cases versus controls were 1.68 (95% CI 1.39 to 2.04), 1.51 (95% CI 1.30 to 1.75) and 1.34 (95% CI 1.20 to 1.48), respectively. Relative risks were greatest for high-grade serous, mucinous and 'other epithelial' histotypes. Relative risks were attenuated for case FDRs, but not for SDRs or TDRs, from 2005 onwards, consistent with the timing of recommendations for prophylactic surgery. Conclusion: Familial risk of epithelial ovarian cancer extends to TDRs, especially for high-grade serous and mucinous histotypes. Distant relatives share genes but minimal environment, highlighting the importance of germline inherited genetics in ovarian cancer aetiology. Increased ovarian cancer risk in distant relatives has implications for counselling and recommendations for prophylactic surgeries that, from our data, appear only to reach FDRs.
MeSH term(s)	Humans ; Female ; Carcinoma, Ovarian Epithelial/epidemiology ; Carcinoma, Ovarian Epithelial/genetics ; Genetic Predisposition to Disease ; Risk ; Ovarian Neoplasms/etiology ; Ovarian Neoplasms/genetics ; Ovariectomy
Language	English
Publishing date	2022-05-09
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	220881-7
ISSN	1468-6244 ; 0022-2593
ISSN (online)	1468-6244
ISSN	0022-2593
DOI	10.1136/jmedgenet-2021-108402
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Article: Improving Precision of Do Not Contact Codes: Results of a Manual Review to Inform Coding and Case Contact Procedures.

Lawson-Michod, Katherine A / Carter, Marjorie / Yoder, Valerie / McCarty, Rachel D / Bateman, Carrie / Millar, Morgan M / Doherty, Jennifer A

Journal of registry management

2023 Volume 49, Issue 4, Page(s) 126–131

Abstract: Introduction: Central cancer registries are responsible for managing appropriate research contacts and record releases. Do not contact (DNC) flags are used by some registries to indicate patients who should not be contacted or included in research. ... ...

Abstract	Introduction: Central cancer registries are responsible for managing appropriate research contacts and record releases. Do not contact (DNC) flags are used by some registries to indicate patients who should not be contacted or included in research. Longitudinal changes in DNC coding practices and definitions may result in a lack of code standardization and inaccurately include or exclude individuals from research. Purpose: We performed a comprehensive manual review of DNC cases in the Utah Cancer Registry to inform updates to standardization of DNC code definitions, and use of DNC codes for exclusion/inclusion in research. Methods: We identified 858 cases with a current or prior DNC flag in the SEER Data Management System (SEERDMS) or a research database, with cancers diagnosed from 1957-2021. We reviewed scanned images of correspondence with cases and physicians, incident forms, and comments in SEERDMS and research databases. We evaluated whether there was evidence to support the current DNC code, a different DNC code, or insufficient evidence for any code. Results: Of the 755 cases that had a current DNC flag and reason code in SEERDMS, the distribution was as follows: 58%, Conclusion:* The time and resource investment in manual review allowed us to identify and, in most cases, resolve discordance in DNC flags and reason codes, adding reason codes when they were missing. This process was valuable because it informed recommended changes to DNC code definitions and research handlings that will ensure more appropriate inclusion and exclusion of cancer cases in research.
MeSH term(s)	Humans ; SEER Program ; Neoplasms/epidemiology ; Registries ; Physicians ; Healthcare Common Procedure Coding System
Language	English
Publishing date	2023-06-01
Publishing country	United States
Document type	Review ; Journal Article
ISSN	1945-6123
ISSN	1945-6123
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Article ; Online: Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors.

Hippen, Ariel A / Omran, Dalia K / Weber, Lukas M / Jung, Euihye / Drapkin, Ronny / Doherty, Jennifer A / Hicks, Stephanie C / Greene, Casey S

Genome biology

2023 Volume 24, Issue 1, Page(s) 239

Abstract: Background: Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical ... ...

Abstract	Background: Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical strategy. Many algorithms can deconvolve these tumors using single-cell profiles to infer their composition. While experimental choices do not change the true underlying composition of the tumor, they can affect the measurements produced by the assay. Results: We generated a dataset of high-grade serous ovarian tumors with paired expression profiles from using multiple strategies to examine the extent to which experimental factors impact the results of downstream tumor deconvolution methods. We find that pooling samples for single-cell sequencing and subsequent demultiplexing has a minimal effect. We identify dissociation-induced differences that affect cell composition, leading to changes that may compromise the assumptions underlying some deconvolution algorithms. We also observe differences across mRNA enrichment methods that introduce additional discrepancies between the two data types. We also find that experimental factors change cell composition estimates and that the impact differs by method. Conclusions: Previous benchmarks of deconvolution methods have largely ignored experimental factors. We find that methods vary in their robustness to experimental factors. We provide recommendations for methods developers seeking to produce the next generation of deconvolution approaches and for scientists designing experiments using deconvolution to study tumor heterogeneity.
MeSH term(s)	Humans ; Female ; Gene Expression Profiling/methods ; Algorithms ; Sequence Analysis, RNA/methods ; Ovarian Neoplasms/genetics ; Transcriptome ; Tumor Microenvironment
Language	English
Publishing date	2023-10-20
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2040529-7
ISSN	1474-760X ; 1474-760X
ISSN (online)	1474-760X
ISSN	1474-760X
DOI	10.1186/s13059-023-03077-7
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Article ; Online: Metabolic obesity phenotypes and obesity-related cancer risk in the National Health and Nutrition Examination Survey.

Winn, Maci / Karra, Prasoona / Freisling, Heinz / Gunter, Marc J / Haaland, Benjamin / Litchman, Michelle L / Doherty, Jennifer A / Playdon, Mary C / Hardikar, Sheetal

Endocrinology, diabetes & metabolism

2023 Volume 6, Issue 4, Page(s) e433

Abstract: Introduction: Body mass index (BMI) fails to identify up to one-third of normal weight individuals with metabolic dysfunction who may be at increased risk of obesity-related cancer (ORC). Metabolic obesity phenotypes, an alternate metric to assess ... ...

Abstract	Introduction: Body mass index (BMI) fails to identify up to one-third of normal weight individuals with metabolic dysfunction who may be at increased risk of obesity-related cancer (ORC). Metabolic obesity phenotypes, an alternate metric to assess metabolic dysfunction with or without obesity, were evaluated for association with ORC risk. Methods: National Health and Nutrition Examination Survey participants from 1999 to 2018 (N = 19,500) were categorized into phenotypes according to the metabolic syndrome (MetS) criteria and BMI: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO) and metabolically unhealthy overweight/obese (MUO). Adjusted multivariable logistic regression models were used to evaluate associations with ORC. Results: With metabolic dysfunction defined as ≥1 MetS criteria, ORC cases (n = 528) had higher proportions of MUNW (28.2% vs. 17.4%) and MUO (62.6% vs. 60.9%) phenotypes than cancer-free individuals (n = 18,972). Compared with MHNW participants, MUNW participants had a 2.2-times higher ORC risk [OR (95%CI) = 2.21 (1.27-3.85)]. MHO and MUO participants demonstrated a 43% and 56% increased ORC risk, respectively, compared to MHNW, but these did not reach statistical significance [OR (95% CI) = 1.43 (0.46-4.42), 1.56 (0.91-2.67), respectively]. Hyperglycaemia, hypertension and central obesity were all independently associated with higher ORC risk compared to MHNW. Conclusions: MUNW participants have a higher risk of ORC than other abnormal phenotypes, compared with MHNW participants. Incorporating metabolic health measures in addition to assessing BMI may improve ORC risk stratification. Further research on the relationship between metabolic dysfunction and ORC is warranted.
MeSH term(s)	Humans ; Overweight ; Nutrition Surveys ; Obesity/complications ; Metabolic Syndrome/epidemiology ; Metabolic Syndrome/etiology ; Metabolic Syndrome/diagnosis ; Phenotype ; Neoplasms/epidemiology ; Neoplasms/etiology
Language	English
Publishing date	2023-06-05
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	2398-9238
ISSN (online)	2398-9238
DOI	10.1002/edm2.433
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Article ; Online: Pathways to lung cancer diagnosis among individuals who did not receive lung cancer screening: a qualitative study.

McCarty, Rachel D / Barnard, Mollie E / Lawson-Michod, Katherine A / Owens, Makelle / Green, Sarah E / Derzon, Samantha / Karabegovic, Lea / Akerley, Wallace L / Watt, Melissa H / Doherty, Jennifer A / Grieshober, Laurie

BMC primary care

2023 Volume 24, Issue 1, Page(s) 203

Abstract: Background: Although early detection of lung cancer through screening is associated with better prognosis, most lung cancers are diagnosed among unscreened individuals. We therefore sought to characterize pathways to lung cancer diagnosis among ... ...

Abstract	Background: Although early detection of lung cancer through screening is associated with better prognosis, most lung cancers are diagnosed among unscreened individuals. We therefore sought to characterize pathways to lung cancer diagnosis among unscreened individuals. Methods: Participants were individuals with lung cancer who did not undergo asymptomatic lung cancer screening (n = 13) and healthcare providers who may be involved in the pathway to lung cancer diagnosis (n = 13). We conducted semi-structured interviews to identify themes in lung cancer patients' narratives of their cancer diagnoses and providers' personal and/or professional experiences of various pathways to lung cancer diagnoses, to identify delays in diagnosis. We audio-recorded, transcribed, and coded interviews in two stages. First, we conducted deductive coding using three time-period intervals from the Models of Pathways to Treatment framework: appraisal, help-seeking, and diagnostic (i.e., excluding pre-treatment). Second, we conducted inductive coding to identify themes within each time-period interval, and classified these themes as either barriers or facilitators to diagnosis. Coding and thematic summarization were completed independently by two separate analysts who discussed for consensus. Results: Eight of the patient participants had formerly smoked, and five had never smoked. We identified eight barrier/facilitator themes within the three time-period intervals. Within the appraisal interval, the barrier theme was (1) minimization or misattribution of symptoms, and the facilitator theme was (2) acknowledgment of symptoms. Within the help-seeking interval, the barrier theme was (3) hesitancy to seek care, and the facilitator theme was (4) routine care. Within the diagnosis interval, barrier themes were (5) health system challenges, and (6) social determinants of health; and facilitator themes were (7) severe symptoms and known risk factors, and (8) self-advocacy. Many themes were interrelated, including minimization or misattribution of symptoms and hesitancy to seek care, which may collectively contribute to care and imaging delays. Conclusions: Interventions to reduce hesitancy to seek care may facilitate timely lung cancer diagnoses. More prompt referral to imaging-especially computed tomography (CT)-among symptomatic patients, along with patient self-advocacy for imaging, may reduce delays in diagnosis.
MeSH term(s)	Humans ; Lung Neoplasms/diagnosis ; Early Detection of Cancer ; Qualitative Research ; Health Personnel
Language	English
Publishing date	2023-10-03
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2731-4553
ISSN (online)	2731-4553
DOI	10.1186/s12875-023-02158-7
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Article ; Online: Accuracy of patient race and ethnicity data in a central cancer registry.

Codden, Rachel R / Sweeney, Carol / Ofori-Atta, Blessing S / Herget, Kimberly A / Wigren, Kacey / Edwards, Sandra / Carter, Marjorie E / McCarty, Rachel D / Hashibe, Mia / Doherty, Jennifer A / Millar, Morgan M

Cancer causes & control : CCC

2023 Volume 35, Issue 4, Page(s) 685–694

Abstract: Purpose: Race and Hispanic ethnicity data can be challenging for central cancer registries to collect. We evaluated the accuracy of the race and Hispanic ethnicity variables collected by the Utah Cancer Registry compared to self-report.: Methods: ... ...

Abstract	Purpose: Race and Hispanic ethnicity data can be challenging for central cancer registries to collect. We evaluated the accuracy of the race and Hispanic ethnicity variables collected by the Utah Cancer Registry compared to self-report. Methods: Participants were 3,162 cancer survivors who completed questionnaires administered in 2015-2022 by the Utah Cancer Registry. Each survey included separate questions collecting race and Hispanic ethnicity, respectively. Registry-collected race and Hispanic ethnicity were compared to self-reported values for the same individuals. We calculated sensitivity and specificity for each race category and Hispanic ethnicity separately. Results: Survey participants included 323 (10.2%) survivors identifying as Hispanic, a lower proportion Hispanic than the 12.1% in the registry Hispanic variable (sensitivity 88.2%, specificity 96.5%). For race, 43 participants (1.4%) self-identified as American Indian or Alaska Native (AIAN), 32 (1.0%) as Asian, 23 (0.7%) as Black or African American, 16 (0.5%) Pacific Islander (PI), and 2994 (94.7%) as White. The registry race variable classified a smaller proportion of survivors as members of each of these race groups except White. Sensitivity for classification of race as AIAN was 9.3%, Asian 40.6%, Black 60.9%, PI 25.0%, and specificity for each of these groups was > 99%. Sensitivity and specificity for White were 98.8% and 47.4%. Conclusion: Cancer registry race and Hispanic ethnicity data often did not match the individual's self-identification. Of particular concern is the high proportion of AIAN individuals whose race is misclassified. Continued attention should be directed to the accurate capture of race and ethnicity data by hospitals.
MeSH term(s)	Humans ; United States ; Ethnicity ; Hispanic or Latino ; Black or African American ; Registries ; White ; Neoplasms/epidemiology
Language	English
Publishing date	2023-11-29
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1064022-8
ISSN	1573-7225 ; 0957-5243
ISSN (online)	1573-7225
ISSN	0957-5243
DOI	10.1007/s10552-023-01827-3
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Article ; Online: Pre-diagnosis neutrophil-to-lymphocyte ratio and mortality in individuals who develop lung cancer.

Grieshober, Laurie / Graw, Stefan / Barnett, Matt J / Goodman, Gary E / Chen, Chu / Koestler, Devin C / Marsit, Carmen J / Doherty, Jennifer A

Cancer causes & control : CCC

2021 Volume 32, Issue 11, Page(s) 1227–1236

Abstract: Purpose: The neutrophil-to-lymphocyte ratio (NLR) is a marker of systemic inflammation that has been reported to be associated with survival after chronic disease diagnoses, including lung cancer. We hypothesized that the inflammatory profile reflected ... ...

Abstract	Purpose: The neutrophil-to-lymphocyte ratio (NLR) is a marker of systemic inflammation that has been reported to be associated with survival after chronic disease diagnoses, including lung cancer. We hypothesized that the inflammatory profile reflected by pre-diagnosis NLR, rather than the well-studied pre-treatment NLR at diagnosis, may be associated with increased mortality after lung cancer is diagnosed in high-risk heavy smokers. Methods: We examined associations between pre-diagnosis methylation-derived NLR (mdNLR) and lung cancer-specific and all-cause mortality in 279 non-small lung cancer (NSCLC) and 81 small cell lung cancer (SCLC) cases from the β-Carotene and Retinol Efficacy Trial (CARET). Cox proportional hazards models were adjusted for age, sex, smoking status, pack years, and time between blood draw and diagnosis, and stratified by stage of disease. Models were run separately by histotype. Results: Among SCLC cases, those with pre-diagnosis mdNLR in the highest quartile had 2.5-fold increased mortality compared to those in the lowest quartile. For each unit increase in pre-diagnosis mdNLR, we observed 22-23% increased mortality (SCLC-specific hazard ratio [HR] = 1.23, 95% confidence interval [CI]: 1.02, 1.48; all-cause HR = 1.22, 95% CI 1.01, 1.46). SCLC associations were strongest for current smokers at blood draw (Interaction Ps = 0.03). Increasing mdNLR was not associated with mortality among NSCLC overall, nor within adenocarcinoma (N = 148) or squamous cell carcinoma (N = 115) case groups. Conclusion: Our findings suggest that increased mdNLR, representing a systemic inflammatory profile on average 4.5 years before a SCLC diagnosis, may be associated with mortality in heavy smokers who go on to develop SCLC but not NSCLC.
MeSH term(s)	Humans ; Lung Neoplasms/diagnosis ; Lymphocytes ; Neutrophils ; Prognosis ; Proportional Hazards Models ; Smoking/adverse effects
Language	English
Publishing date	2021-07-08
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1064022-8
ISSN	1573-7225 ; 0957-5243
ISSN (online)	1573-7225
ISSN	0957-5243
DOI	10.1007/s10552-021-01469-3
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Article ; Online: Building a tobacco user registry by extracting multiple smoking behaviors from clinical notes.

Palmer, Ellen L / Hassanpour, Saeed / Higgins, John / Doherty, Jennifer A / Onega, Tracy

BMC medical informatics and decision making

2019 Volume 19, Issue 1, Page(s) 141

Abstract: Background: Usage of structured fields in Electronic Health Records (EHRs) to ascertain smoking history is important but fails in capturing the nuances of smoking behaviors. Knowledge of smoking behaviors, such as pack year history and most recent ... ...

Abstract	Background: Usage of structured fields in Electronic Health Records (EHRs) to ascertain smoking history is important but fails in capturing the nuances of smoking behaviors. Knowledge of smoking behaviors, such as pack year history and most recent cessation date, allows care providers to select the best care plan for patients at risk of smoking attributable diseases. Methods: We developed and evaluated a health informatics pipeline for identifying complete smoking history from clinical notes in EHRs. We utilized 758 patient-visit notes (from visits between 03/28/2016 and 04/04/2016) from our local EHR in addition to a public dataset of 502 clinical notes from the 2006 i2b2 Challenge to assess the performance of this pipeline. We used a machine-learning classifier to extract smoking status and a comprehensive set of text processing regular expressions to extract pack years and cessation date information from these clinical notes. Results: We identified smoking status with an F1 score of 0.90 on both the i2b2 and local data sets. Regular expression identification of pack year history in the local test set was 91.7% sensitive and 95.2% specific, but due to variable context the pack year extraction was incomplete in 25% of cases, extracting packs per day or years smoked only. Regular expression identification of cessation date was 63.2% sensitive and 94.6% specific. Conclusions: Our work indicates that the development of an EHR-based Smokers' Registry containing information relating to smoking behaviors, not just status, from free-text clinical notes using an informatics pipeline is feasible. This pipeline is capable of functioning in external EHRs, reducing the amount of time and money needed at the institute-level to create a Smokers' Registry for improved identification of patient risk and eligibility for preventative and early detection services.
MeSH term(s)	Algorithms ; Cigarette Smoking/epidemiology ; Datasets as Topic ; Electronic Health Records ; Humans ; Machine Learning ; Medical Informatics ; Natural Language Processing ; Registries
Language	English
Publishing date	2019-07-25
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	1472-6947
ISSN (online)	1472-6947
DOI	10.1186/s12911-019-0863-3
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Article: Molecular subtypes of high-grade serous ovarian cancer across racial groups and gene expression platforms.

Davidson, Natalie R / Barnard, Mollie E / Hippen, Ariel A / Campbell, Amy / Johnson, Courtney E / Way, Gregory P / Dalley, Brian K / Berchuck, Andrew / Salas, Lucas A / Peres, Lauren C / Marks, Jeffrey R / Schildkraut, Joellen M / Greene, Casey S / Doherty, Jennifer A

bioRxiv : the preprint server for biology

2023

Abstract: Introduction: High-grade serous carcinoma (HGSC) gene expression subtypes are associated with differential survival. We characterized HGSC gene expression in Black individuals and considered whether gene expression differences by race may contribute to ... ...

Abstract	Introduction: High-grade serous carcinoma (HGSC) gene expression subtypes are associated with differential survival. We characterized HGSC gene expression in Black individuals and considered whether gene expression differences by race may contribute to poorer HGSC survival among Black versus non-Hispanic White individuals. Methods: We included newly generated RNA-Seq data from Black and White individuals, and array-based genotyping data from four existing studies of White and Japanese individuals. We assigned subtypes using K-means clustering. Cluster- and dataset-specific gene expression patterns were summarized by moderated t-scores. We compared cluster-specific gene expression patterns across datasets by calculating the correlation between the summarized vectors of moderated t-scores. Following mapping to The Cancer Genome Atlas (TCGA)-derived HGSC subtypes, we used Cox proportional hazards models to estimate subtype-specific survival by dataset. Results: Cluster-specific gene expression was similar across gene expression platforms. Comparing the Black study population to the White and Japanese study populations, the immunoreactive subtype was more common (39% versus 23%-28%) and the differentiated subtype less common (7% versus 22%-31%). Patterns of subtype-specific survival were similar between the Black and White populations with RNA-Seq data; compared to mesenchymal cases, the risk of death was similar for proliferative and differentiated cases and suggestively lower for immunoreactive cases (Black population HR=0.79 [0.55, 1.13], White population HR=0.86 [0.62, 1.19]). Conclusions: A single, platform-agnostic pipeline can be used to assign HGSC gene expression subtypes. While the observed prevalence of HGSC subtypes varied by race, subtype-specific survival was similar.
Language	English
Publishing date	2023-12-02
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.11.01.565179
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