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Holland AM, Lorenz WR, Cavanagh JC, Smart NJ, Ayuso SA, Scarola GT, Kercher KW, Jorgensen LN, Janis JE, Fischer JP, Heniford BT. Comparison of Medical Research Abstracts Written by Surgical Trainees and Senior Surgeons or Generated by Large Language Models. JAMA Netw Open 2024; 7:e2425373. [PMID: 39093561 PMCID: PMC11297395 DOI: 10.1001/jamanetworkopen.2024.25373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 06/04/2024] [Indexed: 08/04/2024] Open
Abstract
Importance Artificial intelligence (AI) has permeated academia, especially OpenAI Chat Generative Pretrained Transformer (ChatGPT), a large language model. However, little has been reported on its use in medical research. Objective To assess a chatbot's capability to generate and grade medical research abstracts. Design, Setting, and Participants In this cross-sectional study, ChatGPT versions 3.5 and 4.0 (referred to as chatbot 1 and chatbot 2) were coached to generate 10 abstracts by providing background literature, prompts, analyzed data for each topic, and 10 previously presented, unassociated abstracts to serve as models. The study was conducted between August 2023 and February 2024 (including data analysis). Exposure Abstract versions utilizing the same topic and data were written by a surgical trainee or a senior physician or generated by chatbot 1 and chatbot 2 for comparison. The 10 training abstracts were written by 8 surgical residents or fellows, edited by the same senior surgeon, at a high-volume hospital in the Southeastern US with an emphasis on outcomes-based research. Abstract comparison was then based on 10 abstracts written by 5 surgical trainees within the first 6 months of their research year, edited by the same senior author. Main Outcomes and Measures The primary outcome measurements were the abstract grades using 10- and 20-point scales and ranks (first to fourth). Abstract versions by chatbot 1, chatbot 2, junior residents, and the senior author were compared and judged by blinded surgeon-reviewers as well as both chatbot models. Five academic attending surgeons from Denmark, the UK, and the US, with extensive experience in surgical organizations, research, and abstract evaluation served as reviewers. Results Surgeon-reviewers were unable to differentiate between abstract versions. Each reviewer ranked an AI-generated version first at least once. Abstracts demonstrated no difference in their median (IQR) 10-point scores (resident, 7.0 [6.0-8.0]; senior author, 7.0 [6.0-8.0]; chatbot 1, 7.0 [6.0-8.0]; chatbot 2, 7.0 [6.0-8.0]; P = .61), 20-point scores (resident, 14.0 [12.0-7.0]; senior author, 15.0 [13.0-17.0]; chatbot 1, 14.0 [12.0-16.0]; chatbot 2, 14.0 [13.0-16.0]; P = .50), or rank (resident, 3.0 [1.0-4.0]; senior author, 2.0 [1.0-4.0]; chatbot 1, 3.0 [2.0-4.0]; chatbot 2, 2.0 [1.0-3.0]; P = .14). The abstract grades given by chatbot 1 were comparable to the surgeon-reviewers' grades. However, chatbot 2 graded more favorably than the surgeon-reviewers and chatbot 1. Median (IQR) chatbot 2-reviewer grades were higher than surgeon-reviewer grades of all 4 abstract versions (resident, 14.0 [12.0-17.0] vs 16.9 [16.0-17.5]; P = .02; senior author, 15.0 [13.0-17.0] vs 17.0 [16.5-18.0]; P = .03; chatbot 1, 14.0 [12.0-16.0] vs 17.8 [17.5-18.5]; P = .002; chatbot 2, 14.0 [13.0-16.0] vs 16.8 [14.5-18.0]; P = .04). When comparing the grades of the 2 chatbots, chatbot 2 gave higher median (IQR) grades for abstracts than chatbot 1 (resident, 14.0 [13.0-15.0] vs 16.9 [16.0-17.5]; P = .003; senior author, 13.5 [13.0-15.5] vs 17.0 [16.5-18.0]; P = .004; chatbot 1, 14.5 [13.0-15.0] vs 17.8 [17.5-18.5]; P = .003; chatbot 2, 14.0 [13.0-15.0] vs 16.8 [14.5-18.0]; P = .01). Conclusions and Relevance In this cross-sectional study, trained chatbots generated convincing medical abstracts, undifferentiable from resident or senior author drafts. Chatbot 1 graded abstracts similarly to surgeon-reviewers, while chatbot 2 was less stringent. These findings may assist surgeon-scientists in successfully implementing AI in medical research.
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Affiliation(s)
- Alexis M. Holland
- Division of Gastrointestinal and Minimally Invasive Surgery, Department of Surgery, Atrium Health Carolinas Medical Center, Charlotte, North Carolina
| | - William R. Lorenz
- Division of Gastrointestinal and Minimally Invasive Surgery, Department of Surgery, Atrium Health Carolinas Medical Center, Charlotte, North Carolina
| | - Jack C. Cavanagh
- Department of Economics, Massachusetts Institute of Technology, Cambridge
| | - Neil J. Smart
- Division of Colorectal Surgery, Department of Surgery, Royal Devon & Exeter Hospital, Exeter, Devon, United Kingdom
| | - Sullivan A. Ayuso
- Division of Gastrointestinal and Minimally Invasive Surgery, Department of Surgery, Atrium Health Carolinas Medical Center, Charlotte, North Carolina
| | - Gregory T. Scarola
- Division of Gastrointestinal and Minimally Invasive Surgery, Department of Surgery, Atrium Health Carolinas Medical Center, Charlotte, North Carolina
| | - Kent W. Kercher
- Division of Gastrointestinal and Minimally Invasive Surgery, Department of Surgery, Atrium Health Carolinas Medical Center, Charlotte, North Carolina
| | - Lars N. Jorgensen
- Department of Clinical Medicine, University of Copenhagen, Bispedjerg & Frederiksberg Hospital, Copenhagen, Denmark
| | - Jeffrey E. Janis
- Division of Plastic and Reconstructive Surgery, The Ohio State University Wexner Medical Center, Columbus
| | - John P. Fischer
- Division of Plastic Surgery, University of Pennsylvania Health System, Philadelphia
| | - B. Todd Heniford
- Division of Gastrointestinal and Minimally Invasive Surgery, Department of Surgery, Atrium Health Carolinas Medical Center, Charlotte, North Carolina
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Elbialy A, Kappala D, Desai D, Wang P, Fadiel A, Wang SJ, Makary MS, Lenobel S, Sood A, Gong M, Dason S, Shabsigh A, Clinton S, Parwani AV, Putluri N, Shvets G, Li J, Liu X. Patient-Derived Conditionally Reprogrammed Cells in Prostate Cancer Research. Cells 2024; 13:1005. [PMID: 38920635 PMCID: PMC11201841 DOI: 10.3390/cells13121005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 05/31/2024] [Accepted: 06/03/2024] [Indexed: 06/27/2024] Open
Abstract
Prostate cancer (PCa) remains a leading cause of mortality among American men, with metastatic and recurrent disease posing significant therapeutic challenges due to a limited comprehension of the underlying biological processes governing disease initiation, dormancy, and progression. The conventional use of PCa cell lines has proven inadequate in elucidating the intricate molecular mechanisms driving PCa carcinogenesis, hindering the development of effective treatments. To address this gap, patient-derived primary cell cultures have been developed and play a pivotal role in unraveling the pathophysiological intricacies unique to PCa in each individual, offering valuable insights for translational research. This review explores the applications of the conditional reprogramming (CR) cell culture approach, showcasing its capability to rapidly and effectively cultivate patient-derived normal and tumor cells. The CR strategy facilitates the acquisition of stem cell properties by primary cells, precisely recapitulating the human pathophysiology of PCa. This nuanced understanding enables the identification of novel therapeutics. Specifically, our discussion encompasses the utility of CR cells in elucidating PCa initiation and progression, unraveling the molecular pathogenesis of metastatic PCa, addressing health disparities, and advancing personalized medicine. Coupled with the tumor organoid approach and patient-derived xenografts (PDXs), CR cells present a promising avenue for comprehending cancer biology, exploring new treatment modalities, and advancing precision medicine in the context of PCa. These approaches have been used for two NCI initiatives (PDMR: patient-derived model repositories; HCMI: human cancer models initiatives).
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Affiliation(s)
- Abdalla Elbialy
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Computational Oncology Unit, The University of Chicago Comprehensive Cancer Center, 900 E 57th Street, KCBD Bldg., STE 4144, Chicago, IL 60637, USA
| | - Deepthi Kappala
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
| | - Dhruv Desai
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
| | - Peng Wang
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
| | - Ahmed Fadiel
- Computational Oncology Unit, The University of Chicago Comprehensive Cancer Center, 900 E 57th Street, KCBD Bldg., STE 4144, Chicago, IL 60637, USA
| | - Shang-Jui Wang
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Department of Radiation Oncology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Mina S. Makary
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Division of Vascular and Interventional Radiology, Department of Radiology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Scott Lenobel
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Division of Musculoskeletal Imaging, Department of Radiology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Akshay Sood
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Department of Urology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Michael Gong
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Department of Urology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Shawn Dason
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Department of Urology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Ahmad Shabsigh
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Department of Urology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Steven Clinton
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
| | - Anil V. Parwani
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Departments of Pathology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Nagireddy Putluri
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Gennady Shvets
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14850, USA
| | - Jenny Li
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Departments of Pathology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Xuefeng Liu
- OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA; (A.E.)
- Departments of Pathology, Urology, and Radiation Oncology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
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Kasper G, Momen M, Sorice KA, Mayhand KN, Handorf EA, Gonzalez ET, Devlin A, Brownstein K, Esnaola N, Fisher SG, Lynch SM. Effect of neighborhood and individual-level socioeconomic factors on breast cancer screening adherence in a multi-ethnic study. BMC Public Health 2024; 24:63. [PMID: 38166942 PMCID: PMC10763410 DOI: 10.1186/s12889-023-17252-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 11/16/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Although mammography can significantly reduce breast cancer mortality, many women do not receive their annual breast cancer screening. Differences in screening adherence exist by race/ethnicity, socioeconomic status (SES), and insurance status. However, more detailed investigations into the impact of neighborhood disadvantage and access to resources on screening adherence are lacking. METHODS We comprehensively examined the effect of individual social, economic, and demographic factors (n = 34 variables), as well as neighborhood level SES (nSES) indicators (n = 10 variables) on breast cancer screening adherence across a multi-ethnic population (n = 472). In this cross-sectional study, participants were surveyed from 2017 to 2018. The data was analyzed using univariate regression and LASSO for variable reduction. Significant predictors were carried forward into final multivariable mixed-effect logistic regression models where odds ratios (OR), 95% confidence intervals and p-values were reported. RESULTS Nineteen percent of participants were non-adherent to breast screening guidelines. Race/ethnicity was not associated with adherence; however, increasing age (OR = 0.97, 95%CI = 0.95-0.99, p = 0.01), renting a home (OR = 0.53, 95%CI = 0.30-0.94, p = 0.04), food insecurity (OR 0.46, 95%CI = 0.22-0.94, p = 0.01), and overcrowding (OR = 0.58, 95% CI = 0.32-0.94, p = 0.01) were significantly associated with lower breast cancer screening adherence. CONCLUSION Socioeconomic indicators at the individual and neighborhood levels impact low breast cancer screening adherence and may help to inform future screening interventions.
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Affiliation(s)
- Gillian Kasper
- Temple University School of Medicine, Philadelphia, PA, USA.
| | - Mahsa Momen
- Temple University School of Medicine, Philadelphia, PA, USA
| | - Kristen A Sorice
- Fox Chase Cancer Center, 4th Floor Young Pavilion, 333 Cottman Avenue, Philadelphia, PA, 19111, USA
| | - Kiara N Mayhand
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth A Handorf
- Fox Chase Cancer Center, 4th Floor Young Pavilion, 333 Cottman Avenue, Philadelphia, PA, 19111, USA
| | - Evelyn T Gonzalez
- Fox Chase Cancer Center, 4th Floor Young Pavilion, 333 Cottman Avenue, Philadelphia, PA, 19111, USA
| | - Amie Devlin
- Temple University School of Medicine, Philadelphia, PA, USA
| | | | | | - Susan G Fisher
- Temple University School of Medicine, Philadelphia, PA, USA
- Fox Chase Cancer Center, 4th Floor Young Pavilion, 333 Cottman Avenue, Philadelphia, PA, 19111, USA
| | - Shannon M Lynch
- Fox Chase Cancer Center, 4th Floor Young Pavilion, 333 Cottman Avenue, Philadelphia, PA, 19111, USA
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Iyer HS, Vaselkiv JB, Stopsack KH, Roscoe C, DeVille NV, Zhang Y, Penney KL, Balk SP, Fiorentino M, Hart JE, James P, De Vivo I, Mucci LA, Laden F, Rebbeck TR. Influence of Neighborhood Social and Natural Environment on Prostate Tumor Histology in a Cohort of Male Health Professionals. Am J Epidemiol 2023; 192:1485-1498. [PMID: 37139568 PMCID: PMC10948945 DOI: 10.1093/aje/kwad112] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 02/19/2023] [Accepted: 05/01/2023] [Indexed: 05/05/2023] Open
Abstract
Adverse neighborhood social and natural (green space) environments may contribute to the etiology of prostate cancer (CaP), but mechanisms are unclear. We examined associations between neighborhood environment and prostate intratumoral inflammation in 967 men diagnosed with CaP with available tissue samples from 1986-2009 in the Health Professionals Follow-up Study. Exposures were linked to work or residential addresses in 1988. We estimated indices of neighborhood socioeconomic status (nSES) and segregation (Index of Concentration at the Extremes (ICE)) using US Census tract-level data. Surrounding greenness was estimated using seasonal averaged Normalized Difference Vegetation Index (NDVI) data. Surgical tissue underwent pathological review for acute and chronic inflammation, corpora amylacea, and focal atrophic lesions. Adjusted odds ratios (aORs) for inflammation (ordinal) and focal atrophy (binary) were estimated using logistic regression. No associations were observed for acute or chronic inflammation. Each interquartile-range increase in NDVI within 1,230 m of the participant's work or home address (aOR = 0.74, 95% confidence interval (CI): 0.59, 0.93), in ICE-income (aOR = 0.79, 95% CI: 0.61, 1.04), and in ICE-race/income (aOR = 0.79, 95% CI: 0.63, 0.99) was associated with lower odds of postatrophic hyperplasia. Interquartile-range increases in nSES (aOR = 0.76, 95% CI: 0.57, 1.02) and ICE-race/income (aOR = 0.73, 95% CI: 0.54, 0.99) were associated with lower odds of tumor corpora amylacea. Histopathological inflammatory features of prostate tumors may be influenced by neighborhood.
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Affiliation(s)
- Hari S Iyer
- Correspondence to Dr. Hari Iyer, Section of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, 120 Albany Street, New Brunswick, NJ 08901 (e-mail: )
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Purrington KS, Hastert TA, Madhav KC, Nair M, Snider N, Ruterbusch JJ, Schwartz AG, Stoffel EM, Peters ES, Rozek LS. The role of area-level socioeconomic disadvantage in racial disparities in cancer incidence in metropolitan Detroit. Cancer Med 2023. [PMID: 37184135 DOI: 10.1002/cam4.6065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/17/2023] [Accepted: 04/30/2023] [Indexed: 05/16/2023] Open
Abstract
BACKGROUND Neighborhood deprivation is associated with both race and cancer incidence, but there is a need to better understand the effect of structural inequities on racial cancer disparities. The goal of this analysis was to evaluate the relationship between a comprehensive measure of neighborhood-level social disadvantage and cancer incidence within the racially diverse population of metropolitan Detroit. METHODS We estimated breast, colorectal, lung, and prostate cancer incidence rates using Metropolitan Detroit Cancer Surveillance System and US decennial census data. Neighborhood socioeconomic disadvantage was measured by the Area Deprivation Index (ADI) using Census Bureau's American Community Survey data at the Public Use Microdata Areas (PUMA) level. Associations between ADI at time of diagnosis and cancer incidence were estimated using Poisson mixed-effects models adjusting for age and sex. Attenuation of race-incidence associations by ADI was quantified using the "mediation" package in R. RESULTS ADI was inversely associated with incidence of breast cancer for both non-Hispanic White (NHW) and non-Hispanic Black (NHB) women (NHW: per-quartile RR = 0.92, 95% CI 0.88-0.96; NHB: per-quartile RR = 0.94, 95% CI 0.91-0.98) and with prostate cancer incidence only for NHW men (per-quartile RR = 0.94, 95% CI 0.90-0.97). ADI was positively associated with incidence of lung cancer for NHWs and NHBs (NHW: per-quartile RR = 1.12, 95% CI 1.04-1.21; NHB: per-quartile RR = 1.37, 95% CI 1.25-1.51) and incidence of colorectal cancer (CRC) only among NHBs (per-quartile RR = 1.11, 95% CI 1.02-1.21). ADI significantly attenuated the relationship between race and hormone receptor positive, HER2-negative breast cancer (proportion attenuated = 8.5%, 95% CI 4.1-16.6%) and CRC cancer (proportion attenuated = 7.3%, 95% CI 3.7 to 12.8%), and there was a significant interaction between race and ADI for lung (interaction RR = 1.22, p < 0.0001) and prostate cancer (interaction RR = 1.09, p = 0.00092). CONCLUSIONS Area-level socioeconomic disadvantage is associated with risk of common cancers in a racially diverse population and plays a role in racial differences in cancer incidence.
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Affiliation(s)
- Kristen S Purrington
- Department of Oncology, Wayne State University School of Medicine, Michigan, Detroit, USA
- Population Studies and Disparities Research Program, Barbara Ann Karmanos Cancer Institute, Michigan, Detroit, USA
| | - Theresa A Hastert
- Department of Oncology, Wayne State University School of Medicine, Michigan, Detroit, USA
- Population Studies and Disparities Research Program, Barbara Ann Karmanos Cancer Institute, Michigan, Detroit, USA
| | - K C Madhav
- Department of Internal Medicine, Yale School of Medicine, Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Connecticut, New Haven, USA
| | - Mrudula Nair
- Department of Oncology, Wayne State University School of Medicine, Michigan, Detroit, USA
| | - Natalie Snider
- Department of Oncology, Wayne State University School of Medicine, Michigan, Detroit, USA
| | - Julie J Ruterbusch
- Department of Oncology, Wayne State University School of Medicine, Michigan, Detroit, USA
- Population Studies and Disparities Research Program, Barbara Ann Karmanos Cancer Institute, Michigan, Detroit, USA
| | - Ann G Schwartz
- Department of Oncology, Wayne State University School of Medicine, Michigan, Detroit, USA
- Population Studies and Disparities Research Program, Barbara Ann Karmanos Cancer Institute, Michigan, Detroit, USA
| | - Elena M Stoffel
- Division of Gastroenterology, Department of Internal Medicine, University of Michigan Health System, Michigan, Ann Arbor, USA
| | - Edward S Peters
- Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Laura S Rozek
- Department of Oncology, Georgetown University School of Medicine, District of Columbia, Washington, USA
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Sorice KA, Fang CY, Wiese D, Ortiz A, Chen Y, Henry KA, Lynch SM. Systematic review of neighborhood socioeconomic indices studied across the cancer control continuum. Cancer Med 2022; 11:2125-2144. [PMID: 35166051 PMCID: PMC9119356 DOI: 10.1002/cam4.4601] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/03/2021] [Accepted: 12/28/2021] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND There is extensive interest in understanding how neighborhood socioeconomic status (nSES) may affect cancer incidence or survival. However, variability regarding items included and approaches used to form a composite nSES index presents challenges in summarizing overall associations with cancer. Given recent calls for standardized measures of neighborhood sociodemographic effects in cancer disparity research, the objective of this systematic review was to identify and compare existing nSES indices studied across the cancer continuum (incidence, screening, diagnosis, treatment, survival/mortality) and summarize associations by race/ethnicity and cancer site to inform future cancer disparity studies. METHODS Using PRISMA guidelines, peer-reviewed articles published between 2010 and 2019 containing keywords related to nSES and cancer were identified in PubMed. RESULTS Twenty-four nSES indices were identified from 75 studies. In general, findings indicated a significant association between nSES and cancer outcomes (n = 64/75 studies; 85.33%), with 42/64 (65.63%) adjusting for highly-correlated individual SES factors (e.g., education). However, the direction of association differed by cancer site, race/ethnicity, and nSES index. CONCLUSIONS This review highlights several methodologic and conceptual issues surrounding nSES measurement and potential associations with cancer disparities. Recommendations pertaining to the selection of nSES measures are provided, which may help inform disparity-related disease processes and improve the identification of vulnerable populations in need of intervention.
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Affiliation(s)
- Kristen A. Sorice
- Cancer Prevention and ControlFox Chase Cancer CenterPhiladelphiaPAUSA
| | - Carolyn Y. Fang
- Cancer Prevention and ControlFox Chase Cancer CenterPhiladelphiaPAUSA
| | - Daniel Wiese
- Geography and Urban StudiesTemple UniversityPhiladelphiaPAUSA
| | - Angel Ortiz
- Cancer Prevention and ControlFox Chase Cancer CenterPhiladelphiaPAUSA
| | - Yuku Chen
- Cancer Prevention and ControlFox Chase Cancer CenterPhiladelphiaPAUSA
| | - Kevin A. Henry
- Geography and Urban StudiesTemple UniversityPhiladelphiaPAUSA
| | - Shannon M. Lynch
- Cancer Prevention and ControlFox Chase Cancer CenterPhiladelphiaPAUSA
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Llanos AAM, Li J, Tsui J, Gibbons J, Pawlish K, Nwodili F, Lynch S, Ragin C, Stroup AM. Variation in Cancer Incidence Rates Among Non-Hispanic Black Individuals Disaggregated by Nativity and Birthplace, 2005-2017: A Population-Based Cancer Registry Analysis. Front Oncol 2022; 12:857548. [PMID: 35463326 PMCID: PMC9024350 DOI: 10.3389/fonc.2022.857548] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 03/16/2022] [Indexed: 01/25/2023] Open
Abstract
ObjectivesCompared to other racial and ethnic groups, little to no disaggregated cancer incidence data exist for subgroups of non-Hispanic Blacks (NHBs), despite heterogeneity in sociodemographic characteristics and cancer risk factors within this group. Our objective was to examine age-adjusted cancer incidence by nativity and birthplace among NHB cancer cases diagnosed in New Jersey.MethodsRace, ethnicity, and birthplace data from the New Jersey State Cancer Registry were used to classify NHB cancer cases diagnosed between 2005-2017. Thirteen waves of population estimates (by county, nativity, gender, age-group) were derived from the American Community Survey using Integrated Public-Use Microdata to approximate yearly demographics. Age-adjusted cancer incidence rates (overall and by site) by birthplace were generated using SEER*Stat 8.3.8. Bivariate associations were assessed using chi-square and Fisher’s exact tests. Trend analyses were performed using Joinpoint 4.7.ResultsBirthplace was available for 62.3% of the 71,019 NHB cancer cases. Immigrants represented 12.3%, with African-born, Haitian-born, Jamaican-born, ‘other-Caribbean-born’, and ‘other-non-American-born’ accounting for 18.5%, 17.7%, 16.5%, 10.6%, and 36.8%, respectively. Overall, age-adjusted cancer incidence rates were lower for NHB immigrants for all sites combined and for several of the top five cancers, relative to American-born NHBs. Age-adjusted cancer incidence was lower among immigrant than American-born males (271.6 vs. 406.8 per 100,000) and females (191.9 vs. 299.2 per 100,000). Age-adjusted cancer incidence was lower for Jamaican-born (114.6 per 100,000) and other-Caribbean-born females (128.8 per 100,000) than African-born (139.4 per 100,000) and Haitian-born females (149.9 per 100,000). No significant differences in age-adjusted cancer incidence were observed by birthplace among NHB males. Age-adjusted cancer incidence decreased for all sites combined from 2005-2017 among American-born males, immigrant males, and American-born females, while NHB immigrant female rates remained relatively stable.ConclusionsThere is variation in age-adjusted cancer incidence rates across NHB subgroups, highlighting the need for more complete birthplace information in population-based registries to facilitate generating disaggregated cancer surveillance statistics by birthplace. This study fills a knowledge gap of critical importance for understanding and ultimately addressing cancer inequities.
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Affiliation(s)
- Adana A. M. Llanos
- Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY, United States
- Cancer Population Science, Herbert Irving Comprehensive Cancer Center, New York, NY, United States
- *Correspondence: Adana A. M. Llanos,
| | - Jie Li
- New Jersey State Cancer Registry, New Jersey Department of Health, Trenton, NJ, United States
| | - Jennifer Tsui
- Department of Population and Public Health, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Joseph Gibbons
- Department of Sociology, San Diego State University, San Diego, CA, United States
| | - Karen Pawlish
- New Jersey State Cancer Registry, New Jersey Department of Health, Trenton, NJ, United States
| | - Fechi Nwodili
- Rutgers University School of Arts and Sciences, Douglass Residential College, New Brunswick, NJ, United States
| | - Shannon Lynch
- Cancer Prevention and Control Program, Fox Chase Cancer Center-Temple Health, Philadelphia, PA, United States
| | - Camille Ragin
- Cancer Prevention and Control Program, Fox Chase Cancer Center-Temple Health, Philadelphia, PA, United States
| | - Antoinette M. Stroup
- New Jersey State Cancer Registry, New Jersey Department of Health, Trenton, NJ, United States
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, NJ, United States
- Cancer Prevention and Control, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
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Adebola TM, Fennell HWW, Druitt MD, Bonin CA, Jenifer VA, van Wijnen AJ, Lewallen EA. Population-Level Patterns of Prostate Cancer Occurrence: Disparities in Virginia. CURRENT MOLECULAR BIOLOGY REPORTS 2022; 8:1-8. [PMID: 35909818 PMCID: PMC9337710 DOI: 10.1007/s40610-022-00147-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Prostate cancer is the most common cancer and the second leading cause of cancer-related deaths among men in the United States. In Virginia, which is a representative, ethnically diverse state of more than 8 million people that was established nearly 400 years ago, prostate cancer has the highest rate of new detection for any type of cancer. All men are at risk of developing prostate cancer regardless of demographics, but some men have an increased mortality risk due to cancer metastasis. Notably, one in five African American men will be diagnosed with prostate cancer in their lifetime and they have the highest prostate cancer mortality rate of any ethnic group in the United States, including Virginia. A person's genetic profile and family history are important biological determinants of prostate cancer risk, but modifiable environmental factors (e.g., pollution) appear to be correlated with patterns of disease prevalence and risk. In this review, we examine current perspectives on population-level spatial patterns of prostate cancer in Virginia. For context, recent, publicly available data from the Centers for Disease Control and Prevention are highlighted and presented in spatial format. In addition, we explore possible co-morbidities of prostate cancer that may have demographic underpinnings highlighted in recent health disparity studies.
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Affiliation(s)
- Tunde M Adebola
- Department of Biological Sciences, Hampton University, Hampton, VA, USA
| | | | - Michael D Druitt
- Department of Biological Sciences, Hampton University, Hampton, VA, USA
| | - Carolina A Bonin
- Department of Biological Sciences, Hampton University, Hampton, VA, USA
| | | | | | - Eric A Lewallen
- Department of Biological Sciences, Hampton University, Hampton, VA, USA
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Ashing KT, Jones V, Bedell F, Phillips T, Erhunmwunsee L. Calling Attention to the Role of Race-Driven Societal Determinants of Health on Aggressive Tumor Biology: A Focus on Black Americans. JCO Oncol Pract 2022; 18:15-22. [PMID: 34255546 PMCID: PMC8758120 DOI: 10.1200/op.21.00297] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Blacks have the highest incidence and mortality from most cancers. The reasons for these disparities remain unclear. Blacks are exposed to adverse social determinants because of historic and contemporary racist polices; however, how these determinants affect the disparities that Blacks experience is understudied. As a result of discriminatory community policies, like redlining, Blacks have higher exposure to air pollution and neighborhood deprivation. Studies investigating how these factors affect tumor biology are emerging. We highlight the literature that connects racism-related community exposure to the tumor biology in breast, lung, prostate, and colorectal cancer. Further investigations that clarify the link between adverse social determinants that result from systemic racism and aggressive tumor biology are required if health equity is to be achieved. Without recognition that racism is a public health risk with carcinogenic impact, health care delivery and cancer care will never achieve excellence. In response, health systems ought to establish corrective actions to improve Black population health and bring medical justice to marginalized racialized groups.
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Affiliation(s)
- Kimlin T. Ashing
- Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte, CA,African-Caribbean Cancer Consortium, Fox Chase Cancer Center, Philadelphia, PA,Kimlin T. Ashing, PhD, CCARE—Department of Population Sciences, City of Hope Comprehensive Cancer Center, 1500 E Duarte Rd, Duarte, CA 91010-3000; e-mail:
| | - Veronica Jones
- African-Caribbean Cancer Consortium, Fox Chase Cancer Center, Philadelphia, PA
| | - Fornati Bedell
- Division of Urology and Urologic Oncology, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Tanyanika Phillips
- Department of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Loretta Erhunmwunsee
- Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte, CA,Department of Surgery, City of Hope Comprehensive Cancer Center, Duarte, CA
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Effect of Neighborhood and Individual-Level Socioeconomic Factors on Colorectal Cancer Screening Adherence. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18094398. [PMID: 33919106 PMCID: PMC8122519 DOI: 10.3390/ijerph18094398] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/14/2021] [Accepted: 04/16/2021] [Indexed: 02/07/2023]
Abstract
Despite the effectiveness of screenings in reducing colorectal cancer (CRC) mortality, ~25% of US adults do not adhere to screening guidelines. Prior studies associate socioeconomic status (SES) with low screening adherence and suggest that neighborhood deprivation can influence CRC outcomes. We comprehensively investigated the effect of neighborhood SES circumstances (nSES), individual SES, and race/ethnicity on adherence to CRC screening in a multiethnic cross-sectional study. Participant surveys assessing 32 individual-level socioeconomic and healthcare access measures were administered from 2017 to 2018. Participant data were joined with nine nSES measures from the US Census at the census tract level. Univariate, LASSO, and multivariable mixed-effect logistic regression models were used for variable reduction and evaluation of associations. The total study population included 526 participants aged 50–85; 29% of participants were non-adherent. In the final multivariable model, age (p = 0.02) and Non-Hispanic Black race (p = 0.02) were associated with higher odds of adherence. Factors associated with lower adherence were home rental (vs. ownership) (p = 0.003), perception of low healthcare quality (p = 0.006), no routine checkup within two years (p = 0.002), perceived discrimination (p = 0.02), and nSES deprivation (p = 0.02). After comprehensive variable methods were applied, socioeconomic indicators at the neighborhood and individual level were found to contribute to low CRC screening adherence.
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Lewis DD, Cropp CD. The Impact of African Ancestry on Prostate Cancer Disparities in the Era of Precision Medicine. Genes (Basel) 2020; 11:E1471. [PMID: 33302594 PMCID: PMC7762993 DOI: 10.3390/genes11121471] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 11/24/2020] [Accepted: 11/26/2020] [Indexed: 12/24/2022] Open
Abstract
Prostate cancer disproportionately affects men of African ancestry at nearly twice the rate of men of European ancestry despite the advancement of treatment strategies and prevention. In this review, we discuss the underlying causes of these disparities including genetics, environmental/behavioral, and social determinants of health while highlighting the implications and challenges that contribute to the stark underrepresentation of men of African ancestry in clinical trials and genetic research studies. Reducing prostate cancer disparities through the development of personalized medicine approaches based on genetics will require a holistic understanding of the complex interplay of non-genetic factors that disproportionately exacerbate the observed disparity between men of African and European ancestries.
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Affiliation(s)
- Deyana D. Lewis
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, Baltimore, MD 21224, USA
| | - Cheryl D. Cropp
- Department of Pharmaceutical, Social and Administrative Sciences, Samford University McWhorter School of Pharmacy, Birmingham, AL 35229, USA;
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Lynch SM, Handorf E, Sorice KA, Blackman E, Bealin L, Giri VN, Obeid E, Ragin C, Daly M. The effect of neighborhood social environment on prostate cancer development in black and white men at high risk for prostate cancer. PLoS One 2020; 15:e0237332. [PMID: 32790761 PMCID: PMC7425919 DOI: 10.1371/journal.pone.0237332] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 07/23/2020] [Indexed: 12/24/2022] Open
Abstract
INTRODUCTION Neighborhood socioeconomic (nSES) factors have been implicated in prostate cancer (PCa) disparities. In line with the Precision Medicine Initiative that suggests clinical and socioenvironmental factors can impact PCa outcomes, we determined whether nSES variables are associated with time to PCa diagnosis and could inform PCa clinical risk assessment. MATERIALS AND METHODS The study sample included 358 high risk men (PCa family history and/or Black race), aged 35-69 years, enrolled in an early detection program. Patient variables were linked to 78 nSES variables (employment, income, etc.) from previous literature via geocoding. Patient-level models, including baseline age, prostate specific antigen (PSA), digital rectal exam, as well as combined models (patient plus nSES variables) by race/PCa family history subgroups were built after variable reduction methods using Cox regression and LASSO machine-learning. Model fit of patient and combined models (AIC) were compared; p-values<0.05 were significant. Model-based high/low nSES exposure scores were calculated and the 5-year predicted probability of PCa was plotted against PSA by high/low neighborhood score to preliminarily assess clinical relevance. RESULTS In combined models, nSES variables were significantly associated with time to PCa diagnosis. Workers mode of transportation and low income were significant in White men with a PCa family history. Homeownership (%owner-occupied houses with >3 bedrooms) and unemployment were significant in Black men with and without a PCa family history, respectively. The 5-year predicted probability of PCa was higher in men with a high neighborhood score (weighted combination of significant nSES variables) compared to a low score (e.g., Baseline PSA level of 4ng/mL for men with PCa family history: White-26.7% vs 7.7%; Black-56.2% vs 29.7%). DISCUSSION Utilizing neighborhood data during patient risk assessment may be useful for high risk men affected by disparities. However, future studies with larger samples and validation/replication steps are needed.
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Affiliation(s)
- Shannon M. Lynch
- Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
- * E-mail:
| | - Elizabeth Handorf
- Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
| | - Kristen A. Sorice
- Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
| | - Elizabeth Blackman
- Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
| | - Lisa Bealin
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
| | - Veda N. Giri
- Cancer Risk Assessment and Clinical Cancer Genetics Program, Departments of Medical Oncology, Cancer Biology, and Urology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America
| | - Elias Obeid
- Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
| | - Camille Ragin
- Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
| | - Mary Daly
- Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America
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