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  1. 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
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Leveraging Natural Language Processing to Extract Features of Colorectal Polyps From Pathology Reports for Epidemiologic Study.

    Benson, Ryzen / Winterton, Candace / Winn, Maci / Krick, Benjamin / Liu, Mei / Abu-El-Rub, Noor / Conway, Mike / Del Fiol, Guilherme / Gawron, Andrew / Hardikar, Sheetal

    JCO clinical cancer informatics

    2023  Volume 7, Page(s) e2200131

    Abstract: Purpose: Histopathologic features are critical for studying risk factors of colorectal polyps, but remain deeply embedded within unstructured pathology reports, requiring costly and time-consuming manual abstraction for research. In this study, we ... ...

    Abstract Purpose: Histopathologic features are critical for studying risk factors of colorectal polyps, but remain deeply embedded within unstructured pathology reports, requiring costly and time-consuming manual abstraction for research. In this study, we developed and evaluated a natural language processing (NLP) pipeline to automatically extract histopathologic features of colorectal polyps from pathology reports, with an emphasis on individual polyp size. These data were then linked with structured electronic health record (EHR) data, creating an analysis-ready epidemiologic data set.
    Methods: We obtained 24,584 pathology reports from colonoscopies performed at the University of Utah's Gastroenterology Clinic. Two investigators annotated 350 reports to determine inter-rater agreement, develop an annotation scheme, and create a reference standard for performance evaluation. The pipeline was then developed, and performance was compared against the reference for extracting polyp location, histology, size, shape, dysplasia, and the number of polyps. Finally, the pipeline was applied to 24,225 unseen reports and NLP-extracted data were linked with structured EHR data.
    Results: Across all features, our pipeline achieved a precision of 98.9%, a recall of 98.0%, and an F1-score of 98.4%. In patients with polyps, the pipeline correctly extracted 95.6% of sizes, 97.2% of polyp locations, 97.8% of histology, 98.3% of shapes, and 98.3% of dysplasia levels. When applied to unseen data, the pipeline classified 12,889 patients as having polyps, 4,907 patients without polyps, and extracted the features of 28,387 polyps. Tubular adenomas were the most common subtype (55.9%), 8.1% of polyps were advanced adenomas, and the mean polyp size was 0.57 (±0.4) cm.
    Conclusion: Our pipeline extracted histopathologic features of colorectal polyps from colonoscopy pathology reports, most notably individual polyp sizes, with considerable accuracy. This study demonstrates the utility of NLP for extracting polyp features and linking these data with EHR data to create an epidemiologic data set to study colorectal polyp risk factors and outcomes.
    MeSH term(s) Humans ; Colonic Polyps/diagnosis ; Colonic Polyps/epidemiology ; Colonic Polyps/pathology ; Colorectal Neoplasms/diagnosis ; Colorectal Neoplasms/epidemiology ; Colorectal Neoplasms/pathology ; Natural Language Processing ; Adenoma/diagnosis ; Adenoma/epidemiology ; Adenoma/pathology ; Epidemiologic Studies ; Hyperplasia
    Language English
    Publishing date 2023-02-28
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 2473-4276
    ISSN (online) 2473-4276
    DOI 10.1200/CCI.22.00131
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: New-Onset Diabetes after an Obesity-Related Cancer Diagnosis and Survival Outcomes in the Women's Health Initiative.

    Karra, Prasoona / Hardikar, Sheetal / Winn, Maci / Anderson, Garnet L / Haaland, Benjamin / Krick, Benjamin / Thomson, Cynthia A / Shadyab, Aladdin / Luo, Juhua / Saquib, Nazmus / Strickler, Howard D / Chlebowski, Rowan / Arthur, Rhonda S / Summers, Scott A / Holland, William L / Jalili, Thunder / Playdon, Mary C

    Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

    2023  Volume 32, Issue 10, Page(s) 1356–1364

    Abstract: Background: Individuals diagnosed with an obesity-related cancer (ORC survivors) are at an elevated risk of incident diabetes compared with cancer-free individuals, but whether this confers survival disadvantage is unknown.: Methods: We assessed the ... ...

    Abstract Background: Individuals diagnosed with an obesity-related cancer (ORC survivors) are at an elevated risk of incident diabetes compared with cancer-free individuals, but whether this confers survival disadvantage is unknown.
    Methods: We assessed the rate of incident diabetes in ORC survivors and evaluated the association of incident diabetes with all-cause and cancer-specific mortality among females with ORC in the Women's Health Initiative cohort (N = 14,651). Cox proportional hazards regression models stratified by exposure-risk periods (0-1, >1-3, >3-5, >5-7, and >7-10 years) from ORC diagnosis and time-varying exposure (diabetes) analyses were performed.
    Results: Among the ORC survivors, a total of 1.3% developed diabetes within ≤1 year of follow-up and 2.5%, 2.3%, 2.3%, and 3.6% at 1-3, 3-5, 5-7, and 7-10 years of follow-up, respectively, after an ORC diagnosis. The median survival for those diagnosed with diabetes within 1-year of cancer diagnosis and those with no diabetes diagnosis in that time frame was 8.8 [95% confidence interval (CI), 7.0-14.5) years and 16.6 (95% CI, 16.1-17.0) years, respectively. New-onset compared with no diabetes as a time-varying exposure was associated with higher risk of all-cause (HR, 1.27; 95% CI, 1.16-1.40) and cancer-specific (HR, 1.17; 95% CI, 0.99-1.38) mortality. When stratified by exposure-risk periods, incident diabetes in ≤1 year of follow-up was associated with higher all-cause (HR, 1.76; 95% CI, 1.40-2.20) and cancer-specific (HR0-1, 1.82; 95% CI, 1.28-2.57) mortality, compared with no diabetes diagnosis.
    Conclusions: Incident diabetes was associated with worse cancer-specific and all-cause survival, particularly in the year after cancer diagnosis.
    Impact: These findings draw attention to the importance of diabetes prevention efforts among cancer survivors to improve survival outcomes.
    MeSH term(s) Female ; Humans ; Risk Factors ; Women's Health ; Obesity/complications ; Obesity/epidemiology ; Diabetes Mellitus/epidemiology ; Proportional Hazards Models ; Neoplasms/diagnosis ; Neoplasms/epidemiology ; Neoplasms/complications
    Language English
    Publishing date 2023-08-16
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 1153420-5
    ISSN 1538-7755 ; 1055-9965
    ISSN (online) 1538-7755
    ISSN 1055-9965
    DOI 10.1158/1055-9965.EPI-23-0278
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 3693: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  4. Article ; Online: Metabolic dysfunction and obesity-related cancer: Results from the cross-sectional National Health and Nutrition Examination Survey.

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

    Cancer medicine

    2022  Volume 12, Issue 1, Page(s) 606–618

    Abstract: Background: Metabolic syndrome (MetS), a group of risk factors that define metabolic dysfunction in adults, is strongly associated with obesity and is an emerging risk factor for cancer. However, the association of MetS and degree of metabolic ... ...

    Abstract Background: Metabolic syndrome (MetS), a group of risk factors that define metabolic dysfunction in adults, is strongly associated with obesity and is an emerging risk factor for cancer. However, the association of MetS and degree of metabolic dysfunction with obesity-related cancer is unknown.
    Methods: Using National Health and Nutrition Examination Survey data from 1999 to 2018, we identified 528 obesity-related cancer cases and 18,972 cancer-free participants. MetS was defined as the presence of or treatment for ≥3 of hyperglycemia, hypertension, hypertriglyceridemia, low HDL-cholesterol, and abdominal obesity. A metabolic syndrome score (MSS) was computed as the total number of abnormal MetS parameters to determine the severity of metabolic dysfunction. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression models, adjusting for sociodemographic and lifestyle factors.
    Results: About 45.7% of obesity-related cancer cases were classified as having MetS compared with only 33.0% of cancer-free participants. Overall, MetS and MSS were not associated with obesity-related cancer. However, MSS was associated with higher obesity-related cancer risk among participants under 50 years of age (OR [95% CI] = 1.28 [1.08-1.52]). When evaluating MSS categorically, compared with healthy participants with no abnormal MetS parameters (MSS = 0), participants with one or two abnormal parameters had a statistically significant higher risk of obesity-related cancer (OR [95% CI] = 1.73 [1.06-2.83]).
    Conclusions: Metabolic dysfunction is associated with a higher risk of obesity-related cancer, particularly in young adults under 50 years of age, and among participants with one or two abnormal metabolic parameters. A more accurate indicator of metabolic dysfunction, beyond metabolic syndrome, is needed to better assist in stratifying individuals for obesity-related cancer risk.
    MeSH term(s) Young Adult ; Humans ; Metabolic Syndrome/epidemiology ; Nutrition Surveys ; Cross-Sectional Studies ; Obesity/complications ; Obesity/epidemiology ; Risk Factors ; Neoplasms/etiology ; Neoplasms/complications
    Language English
    Publishing date 2022-06-19
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2659751-2
    ISSN 2045-7634 ; 2045-7634
    ISSN (online) 2045-7634
    ISSN 2045-7634
    DOI 10.1002/cam4.4912
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Metabolic dysfunction and obesity-related cancer: Beyond obesity and metabolic syndrome.

    Karra, Prasoona / Winn, Maci / Pauleck, Svenja / Bulsiewicz-Jacobsen, Alicja / Peterson, Lacie / Coletta, Adriana / Doherty, Jennifer / Ulrich, Cornelia M / Summers, Scott A / Gunter, Marc / Hardikar, Sheetal / Playdon, Mary C

    Obesity (Silver Spring, Md.)

    2022  Volume 30, Issue 7, Page(s) 1323–1334

    Abstract: Objectives: The metabolic dysfunction driven by obesity, including hyperglycemia and dyslipidemia, increases risk for developing at least 13 cancer types. The concept of "metabolic dysfunction" is often defined by meeting various combinations of ... ...

    Abstract Objectives: The metabolic dysfunction driven by obesity, including hyperglycemia and dyslipidemia, increases risk for developing at least 13 cancer types. The concept of "metabolic dysfunction" is often defined by meeting various combinations of criteria for metabolic syndrome. However, the lack of a unified definition of metabolic dysfunction makes it difficult to compare findings across studies. This review summarizes 129 studies that evaluated variable definitions of metabolic dysfunction in relation to obesity-related cancer risk and mortality after a cancer diagnosis. Strategies for metabolic dysfunction management are also discussed.
    Methods: A comprehensive search of relevant publications in MEDLINE (PubMed) and Google Scholar with review of references was conducted.
    Results: Metabolic dysfunction, defined as metabolic syndrome diagnosis or any number of metabolic syndrome criteria out of clinical range, inflammatory biomarkers, or markers of metabolic organ function, has been associated with risk for, and mortality from, colorectal, pancreatic, postmenopausal breast, and bladder cancers. Metabolic dysfunction associations with breast and colorectal cancer risk have been observed independently of BMI, with increased risk in individuals with metabolically unhealthy normal weight or overweight/obesity compared with metabolically healthy normal weight.
    Conclusion: Metabolic dysfunction is a key risk factor for obesity-related cancer, regardless of obesity status. Nonetheless, a harmonized definition of metabolic dysfunction will further clarify the magnitude of the relationship across cancer types, enable better comparisons across studies, and further guide criteria for obesity-related cancer risk stratification.
    MeSH term(s) Biomarkers ; Body Mass Index ; Humans ; Metabolic Syndrome/complications ; Neoplasms/complications ; Neoplasms/etiology ; Obesity/metabolism ; Risk Factors
    Chemical Substances Biomarkers
    Language English
    Publishing date 2022-07-01
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, N.I.H., Extramural
    ZDB-ID 2230457-5
    ISSN 1930-739X ; 1071-7323 ; 1930-7381
    ISSN (online) 1930-739X
    ISSN 1071-7323 ; 1930-7381
    DOI 10.1002/oby.23444
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4061: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MG 87: Show issues

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