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CC BY-NC-ND 4.0 · Yearb Med Inform 2022; 31(01): 121-130
DOI: 10.1055/s-0042-1742511
Section 2: Cancer Informatics
Survey

Clinical Informatics Approaches to Understand and Address Cancer Disparities

Tafadzwa L. Chaunzwa‡   *
1   Department of Radiation Oncology, Dana-Farber Brigham Cancer Center, Harvard Medical School, Boston, MA, USA
2   Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA
,
Maria Quiles del Rey‡   *
1   Department of Radiation Oncology, Dana-Farber Brigham Cancer Center, Harvard Medical School, Boston, MA, USA
,
Danielle S. Bitterman
1   Department of Radiation Oncology, Dana-Farber Brigham Cancer Center, Harvard Medical School, Boston, MA, USA
2   Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA
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Summary

Objectives: Disparities in cancer incidence and outcomes across race, ethnicity, gender, socioeconomic status, and geography are well-documented, but their etiologies are often poorly understood and multifactorial. Clinical informatics can provide tools to better understand and address these disparities by enabling high-throughput analysis of multiple types of data. Here, we review recent efforts in clinical informatics to study and measure disparities in cancer.

Methods: We carried out a narrative review of clinical informatics studies related to cancer disparities and bias published from 2018-2021, with a focus on domains such as real-world data (RWD) analysis, natural language processing (NLP), radiomics, genomics, proteomics, metabolomics, and metagenomics.

Results: Clinical informatics studies that investigated cancer disparities across race, ethnicity, gender, and age were identified. Most cancer disparities work within clinical informatics used RWD analysis, NLP, radiomics, and genomics. Emerging applications of clinical informatics to understand cancer disparities, including proteomics, metabolomics, and metagenomics, were less well represented in the literature but are promising future research avenues. Algorithmic bias was identified as an important consideration when developing and implementing cancer clinical informatics techniques, and efforts to address this bias were reviewed.

Conclusions: In recent years, clinical informatics has been used to probe a range of data sources to understand cancer disparities across different populations. As informatics tools become integrated into clinical decision-making, attention will need to be paid to ensure that algorithmic bias does not amplify existing disparities. In our increasingly interconnected medical systems, clinical informatics is poised to untap the full potential of multi-platform health data to address cancer disparities.

Keywords

Healthcare disparities - cancer - clinical informatics - big data - algorithms

* Contributed equally




Publication History

Article published online:
04 December 2022

© 2022. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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  • References

  • 1 Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021 May;71(3):209-49.
    PubMed
  • 2 Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, et al. Global Cancer Observatory: Cancer Today. Lyon, France: International Agency for Research on Cancer [Internet] 2020. [cited 2022 Jan 1]. Available from: https://gco.iarc.fr/today/home
    PubMed
  • 3 Hill HE, Schiemann WP, Varadan V. Understanding breast cancer disparities-a multi-scale challenge. Ann Transl Med 2020 Jul;8(14):906.
    PubMed
  • 4 Hu S, Zhang W, Guo Q, Ye J, Zhang D, Zhang Y, et al. Prognosis and Survival Analysis of 922,317 Lung Cancer Patients from the US Based on the Most Recent Data from the SEER Database (April 15, 2021). Int J Gen Med 2021 Dec 10;14:9567-88.
    PubMed
  • 5 Surveillance, Epidemiology, and End Results (SEER) Program Populations (1969-2019), National Cancer Institute, DCCPS, Surveillance Research Program [Internet] 2021 [cited 2022 Jan 1]. Available from: www.seer.cancer.gov/popdata
    PubMed
  • 6 SEER*Explorer: An interactive website for SEER cancer statistics. Statistics. [Internet]. Surveillance Research Program, National Cancer Institute. [cited 2022 Apr 6]. Available from: https://seer.cancer.gov/explorer/
    PubMed
  • 7 Pastorino R, De Vito C, Migliara G, Glocker K, Binenbaum I, Ricciardi W, et al. Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. Eur J Public Health 2019 Oct 1;29(Supplement_3):23-7.
    PubMed
  • 8 Sherman RE, Anderson SA, Dal Pan GJ, Gray GW, Gross T, Hunter NL, et al. Real-World Evidence - What Is It and What Can It Tell Us? N Engl J Med 2016 Dec 8;375(23):2293-7.
    PubMed
  • 9 Lerman MH, Holmes B, St Hilaire D, Tran M, Rioth M, Subramanian V, et al. Validation of a Mortality Composite Score in the Real-World Setting: Overcoming Source-Specific Disparities and Biases. JCO Clin Cancer Inform 2021 Apr;5:401-13.
    PubMed
  • 10 Peterson DJ, Ostberg NP, Blayney DW, Brooks JD, Hernandez-Boussard T. Machine Learning Applied to Electronic Health Records: Identification of Chemotherapy Patients at High Risk for Preventable Emergency Department Visits and Hospital Admissions. JCO Clin Cancer Inform 2021 Oct;5:1106-26.
    PubMed
  • 11 Ward E, Jemal A, Cokkinides V, Singh GK, Cardinez C, Ghafoor A, et al. Cancer disparities by race/ethnicity and socioeconomic status. CA Cancer J Clin 2004 Mar-Apr;54(2):78-93.
    PubMed
  • 12 Chhatre S, Malkowicz SB, Jayadevappa R. Continuity of care in acute survivorship phase, and short and long-term outcomes in prostate cancer patients. Prostate 2021 Dec;81(16):1310-9.
    PubMed
  • 13 Jones N, Marks R, Ramirez R, Rios-Vargas M. 2020 Census Illuminates Racial and Ethnic Composition of the Country [Internet] 2021 [cited 2022 Jan 1]. Available from: https://www.census.gov/library/stories/2021/08/improved-race-ethnicity-measures-reveal-united-states-population-much-more-multiracial.html
    PubMed
  • 14 Baron JM, Paranjape K, Love T, Sharma V, Heaney D, Prime M. Development of a “meta-model” to address missing data, predict patient-specific cancer survival and provide a foundation for clinical decision support. J Am Med Inform Assoc 2021 Mar 1;28(3):605-15.
    PubMed
  • 15 Ahn J, Harper S, Yu M, Feuer EJ, Liu B, Luta G. Variance Estimation and Confidence Intervals for 11 Commonly Used Health Disparity Measures. JCO Clin Cancer Inform 2018 Dec;2:1-19.
    PubMed
  • 16 Gold R, Sheppler C, Hessler D, Bunce A, Cottrell E, Yosuf N, et al. Using Electronic Health Record-Based Clinical Decision Support to Provide Social Risk-Informed Care in Community Health Centers: Protocol for the Design and Assessment of a Clinical Decision Support Tool. JMIR Res Protoc 2021 Oct 8;10(10):e31733.
    PubMed
  • 17 Callahan A, Polony V, Posada JD, Banda JM, Gombar S, Shah NH. ACE: the Advanced Cohort Engine for searching longitudinal patient records. J Am Med Inform Assoc 2021 Jul 14;28(7):1468-79.
    PubMed
  • 18 Caswell-Jin JL, Callahan A, Purington N, Han SS, Itakura H, John EM, et al. Treatment and Monitoring Variability in US Metastatic Breast Cancer Care. JCO Clin Cancer Inform 2021 May;5:600-14.
    PubMed
  • 19 Noyd DH, Berkman A, Howell C, Power S, Kreissman SG, Landstrom AP, et al. Leveraging Clinical Informatics Tools to Extract Cumulative Anthracycline Exposure, Measure Cardiovascular Outcomes, and Assess Guideline Adherence for Children With Cancer. JCO Clin Cancer Inform 2021 Oct;5:1062-75.
    PubMed
  • 20 Robinson TJ, Wilson LE, Marcom PK, Troester M, Lynch CF, Hernandez BY, et al. Analysis of Sociodemographic, Clinical, and Genomic Factors Associated With Breast Cancer Mortality in the Linked Surveillance, Epidemiology, and End Results and Medicare Database. JAMA Netw Open 2021 Oct 1;4(10):e2131020.
    PubMed
  • 21 Ganesh A, Katipally R, Pasquinelli M, Feldman L, Spiotto M, Koshy M. Increased Disparities in Patients Diagnosed with Metastatic Lung Cancer Following Lung CT Screening in the United States. Clin Lung Cancer 2022 Mar;23(2):151-8.
    PubMed
  • 22 Dhawan S, Alattar AA, Bartek J Jr, Ma J, Bydon M, Venteicher AS, et al. Racial disparity in recommendation for surgical resection of skull base chondrosarcomas: A Surveillance, Epidemiology, and End Results (SEER) analysis. J Clin Neurosci 2021 Dec;94:186-91.
    PubMed
  • 23 Corona E, Yang L, Esrailian E, Ghassemi KA, Conklin JL, May FP. Trends in Esophageal Cancer Mortality and Stage at Diagnosis by Race and Ethnicity in the United States. Cancer Causes Control 2021 Aug;32(8):883-94.
    PubMed
  • 24 Yan BY, Barilla S, Strunk A, Garg A. Survival differences in acral lentiginous melanoma according to socioeconomic status and race. J Am Acad Dermatol 2022 Feb;86(2):379-86.
    PubMed
  • 25 Cheng JJ, Kim BJ, Kim C, Rodriguez de la Vega P, Varella M, Runowicz CD, Ruizet al. Association Between Race/Ethnicity and Survival in Women With Advanced Ovarian Cancer. Cureus 2021 Jun 30;13(6):e16070.
    PubMed
  • 26 Long Parma D, Schmidt S, Muñoz E, Ramirez AG. Gastric adenocarcinoma burden and late-stage diagnosis in Latino and non-Latino populations in the United States and Texas, during 2004-2016: A multilevel analysis. Cancer Med 2021 Sep;10(18):6468-79.
    PubMed
  • 27 Jawad MU, Bayne CO, Farhan S, Haffner MR, Carr-Ascher J, Alvarez E, et al. Prognostic factors, disparity, and equity variables impacting prognosis in bone sarcomas of the hand: SEER database review. J Surg Oncol 2021 Dec;124(8):1515-22.
    PubMed
  • 28 Sempokuya T, Patel KP, Azawi M, Ma J, Wong LL. Increased morbidity and mortality of hepatocellular carcinoma patients in lower cost of living areas. World J Clin Cases 2021 Aug 16;9(23):6734-46.
    PubMed
  • 29 Berkman AM, Andersen CR, Puthenpura V, Livingston JA, Ahmed S, Cuglievan B, et al. Disparities in the long-term survival of adolescent and young adult diffuse large B cell lymphoma survivors. Cancer Epidemiol 2021 Dec;75:102044.
    PubMed
  • 30 Picon H, Guddati AK. Analysis of Trends in Mortality in Patients with Lymphoepithelial Carcinoma of the Head and Neck. Int J Gen Med 2021 Sep 29;14:6245-50.
    PubMed
  • 31 Chiruvella V, Guddati AK. Analysis of Race and Gender Disparities in Mortality Trends from Patients Diagnosed with Nasopharyngeal, Oropharyngeal and Hypopharyngeal Cancer from 2000 to 2017. Int J Gen Med 2021 Oct 2;14:6315-23.
    PubMed
  • 32 Lorona NC, Malone KE, Li CI. Racial/ethnic disparities in risk of breast cancer mortality by molecular subtype and stage at diagnosis. Breast Cancer Res Treat 2021 Dec;190(3):549-58.
    PubMed
  • 33 Abdel-Rahman O. Bladder cancer mortality after a diagnosis of nonmuscle-invasive bladder carcinoma. Future Oncol 2019 Jul;15(19):2267-75.
    PubMed
  • 34 Punekar SR, Griffin MM, Masri L, Roman SD, Makarov DV, Sherman SE, et al. Socioeconomic Determinants of the Use of Molecular Testing in Stage IV Colorectal Cancer. Am J Clin Oncol 2021 Dec 1;44(12):597-602.
    PubMed
  • 35 Baig MZ, Filkins A, Khan M, Saif MW, Aziz H. Survival Benefits and Disparities in Adjuvant Radiation Therapy for Patients with Pancreatic Cancer. JOP 2021;22(2):36-41.
    PubMed
  • 36 Boyce-Fappiano D, Nguyen KA, Gjyshi O, Manzar G, Abana CO, Klopp AH, Kamrava M, et al. Socioeconomic and Racial Determinants of Brachytherapy Utilization for Cervical Cancer: Concerns for Widening Disparities. JCO Oncol Pract 2021 Dec;17(12):e1958-e1967.
    PubMed
  • 37 Luo Y, Carretta H, Lee I, LeBlanc G, Sinha D, Rust G. Naïve Bayesian network-based contribution analysis of tumor biology and healthcare factors to racial disparity in breast cancer stage-at-diagnosis. Health Inf Sci Syst 2021 Sep 24;9(1):35.
    PubMed
  • 38 Woo C, Cioffi GN, Bej TA, Wilson B, Briggs JM, Markt SC, et al. Data Matching to Support Analysis of Cancer Epidemiology Among Veterans Compared With Non-Veteran Populations-An Exemplar in Brain Tumors. JCO Clin Cancer Inform 2021 Sep;5:985-94.
    PubMed
  • 39 Alba PR, Gao A, Lee KM, Anglin-Foote T, Robison B, Katsoulakis E, et al. Ascertainment of Veterans With Metastatic Prostate Cancer in Electronic Health Records: Demonstrating the Case for Natural Language Processing. JCO Clin Cancer Inform 2021 Sep;5:1005-14.
    PubMed
  • 40 Shiels MS, Haque AT, Haozous EA, Albert PS, Almeida JS, García-Closas M, et al. Racial and Ethnic Disparities in Excess Deaths During the COVID-19 Pandemic, March to December 2020. Ann Intern Med 2021 Dec;174(12):1693-9.
    PubMed
  • 41 Wang Q, Berger NA, Xu R. Analyses of Risk, Racial Disparity, and Outcomes Among US Patients With Cancer and COVID-19 Infection. JAMA Oncol. 2021 Feb 1;7(2):220-7.
    PubMed
  • 42 Kuderer NM, Choueiri TK, Shah DP, Shyr Y, Rubinstein SM, Rivera DR, et al; COVID-19 and Cancer Consortium. Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study. Lancet 2020 Jun 20;395(10241):1907-18.
    PubMed
  • 43 Rivera DR, Peters S, Panagiotou OA, Shah DP, Kuderer NM, Hsu CY, et al; COVID-19 and Cancer Consortium. Utilization of COVID-19 Treatments and Clinical Outcomes among Patients with Cancer: A COVID-19 and Cancer Consortium (CCC19) Cohort Study. Cancer Discov 2020 Oct;10(10):1514-27.
    PubMed
  • 44 Grivas P, Khaki AR, Wise-Draper TM, French B, Hennessy C, Hsu CY, et al. Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium. Ann Oncol 2021 Jun;32(6):787-800.
    PubMed
  • 45 Yim WW, Yetisgen M, Harris WP, Kwan SW. Natural Language Processing in Oncology: A Review. JAMA Oncol 2016 Jun 1;2(6):797-804.
    PubMed
  • 46 Bitterman DS, Miller TA, Mak RH, Savova GK. Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer. Int J Radiat Oncol Biol Phys 2021 Jul 1;110(3):641-55.
    PubMed
  • 47 Savova GK, Danciu I, Alamudun F, Miller T, Lin C, Bitterman DS, Tourassi G, et al. Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records. Cancer Res 2019 Nov 1;79(21):5463-70.
    PubMed
  • 48 Devlin J, Chang M-W, Lee K, Toutanova K. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding [Internet]. arXiv [cs.CL]. 2018. Available from: http://arxiv.org/abs/1810.04805
    PubMed
  • 49 Collin LJ, Yan M, Jiang R, Gogineni K, Subhedar P, Ward KC, et al. Receipt of Guideline-Concordant Care Does Not Explain Breast Cancer Mortality Disparities by Race in Metropolitan Atlanta. J Natl Compr Canc Netw 2021 Aug 16:jnccn20258.
    PubMed
  • 50 Agaronnik ND, Lindvall C, El-Jawahri A, He W, Iezzoni LI. Challenges of Developing a Natural Language Processing Method With Electronic Health Records to Identify Persons With Chronic Mobility Disability. Arch Phys Med Rehabil 2020 Oct;101(10):1739-46.
    PubMed
  • 51 Perez EA, Jaffee EM, Whyte J, Boyce CA, Carpten JD, Lozano G,. Analysis of Population Differences in Digital Conversations About Cancer Clinical Trials: Advanced Data Mining and Extraction Study. JMIR Cancer 2021 Sep 23;7(3):e25621.
    PubMed
  • 52 Haddad T, Helgeson JM, Pomerleau KE, Preininger AM, Roebuck MC, Dankwa-Mullan I, et al. Accuracy of an Artificial Intelligence System for Cancer Clinical Trial Eligibility Screening: Retrospective Pilot Study. JMIR Med Inform 2021 Mar 26;9(3):e27767.
    PubMed
  • 53 Beck JT, Rammage M, Jackson GP, Preininger AM, Dankwa-Mullan I, Roebuck MC, et al. Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center. JCO Clin Cancer Inform 2020 Jan;4:50-9.
    PubMed
  • 54 Olusanya OA, Ammar N, Davis RL, Bednarczyk RA, Shaban-Nejad A. A Digital Personal Health Library for Enabling Precision Health Promotion to Prevent Human Papilloma Virus-Associated Cancers. Front Digit Health 2021 Jul 21;3:683161.
    PubMed
  • 55 Ak M, Toll SA, Hein KZ, Colen RR, Khatua S. Evolving Role and Translation of Radiomics and Radiogenomics in Adult and Pediatric Neuro-Oncology. AJNR Am J Neuroradiol 2022 Jun;43(6):792-801.
    PubMed
  • 56 Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 2014 Jun 3;5:4006. Erratum in: Nat Commun 2014;5:4644. Cavalho, Sara [corrected to Carvalho, Sara].
    PubMed
  • 57 Chaunzwa TL, Hosny A, Xu Y, Shafer A, Diao N, Lanuti M, et al. Deep learning classification of lung cancer histology using CT images. Sci Rep 2021 Mar 9;11(1):5471.
    PubMed
  • 58 Townsley CA, Selby R, Siu LL. Systematic review of barriers to the recruitment of older patients with cancer onto clinical trials. J Clin Oncol 2005 May 1;23(13):3112-24.
    PubMed
  • 59 Schroyen S, Adam S, Jerusalem G, Missotten P. Ageism and its clinical impact in oncogeriatry: state of knowledge and therapeutic leads. Clin Interv Aging 2014 Dec 31;10:117-25.
    PubMed
  • 60 Ahadi S, Zhou W, Schüssler-Fiorenza Rose SM, Sailani MR, Contrepois K, Avina M, et al. Personal aging markers and ageotypes revealed by deep longitudinal profiling. Nat Med 2020 Jan;26(1):83-90.
    PubMed
  • 61 Torres FS, Akbar S, Raman S, Yasufuku K, Schmidt C, Hosny A, et al. End-to-End Non-Small-Cell Lung Cancer Prognostication Using Deep Learning Applied to Pretreatment Computed Tomography. JCO Clin Cancer Inform 2021 Oct;5:1141-50.
    PubMed
  • 62 Permuth JB, Vyas S, Li J, Chen DT, Jeong D, Choi JW. Comparison of Radiomic Features in a Diverse Cohort of Patients With Pancreatic Ductal Adenocarcinomas. Front Oncol 2021 Jul 22;11:712950.
    PubMed
  • 63 Wachter S, Mittelstadt B, Russell C. Why Fairness Cannot Be Automated: Bridging the Gap Between EU Non-Discrimination Law and AI (March 3, 2020). Computer Law & Security Review 41; 2021. Available from: http://dx.doi.org/10.2139/ssrn.3547922
    PubMed
  • 64 Barrett LF, Adolphs R, Marsella S, Martinez AM, Pollak SD. Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements. Psychol Sci Public Interest 2019 Jul;20(1):1-68. Erratum in: Psychol Sci Public Interest 2019 Dec;20(3):165-6.
    PubMed
  • 65 Furl N, Jonathon Phillips P, O’Toole AJ. Face recognition algorithms and the other-race effect: computational mechanisms for a developmental contact hypothesis. Cognitive Science [Internet]. 2002;26(6):797–815. Available from: http://dx.doi.org/10.1207/s15516709cog2606_4
    PubMed
  • 66 Lahoti P, Gummadi KP, Weikum G. iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making [Internet]. 2019 IEEE 35th International Conference on Data Engineering (ICDE). 2019. Available from: http://dx.doi.org/10.1109/icde.2019.00121
    PubMed
  • 67 Buolamwini J, Friedler SA, Wilson C. Gender shades: Intersectional accuracy disparities in commercial gender classification [Internet]. [cited 2022 Apr 8]. Available from: http://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf
    PubMed
  • 68 Barocas S, Selbst AD. Big Data’s Disparate Impact [Internet]. 104 California Law Review 671. 2016. Available from: http://dx.doi.org/10.2139/ssrn.2477899
    PubMed
  • 69 Eubanks, V. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin’s Publishing Group; 2018.
    PubMed
  • 70 Wang H, Chen H, Duan S, Hao D, Liu J. Radiomics and Machine Learning With Multiparametric Preoperative MRI May Accurately Predict the Histopathological Grades of Soft Tissue Sarcomas. J Magn Reson Imagin 2020 Mar;51(3):791-7.
    PubMed
  • 71 Taha B, Li T, Boley D, Chen CC, Sun J. Detection of Isocitrate Dehydrogenase Mutated Glioblastomas Through Anomaly Detection Analytics. Neurosurgery 2021 Jul 15;89(2):323-8.
    PubMed
  • 72 Davis MB. Genomics and Cancer Disparities: The Justice and Power of Inclusion. Cancer Discov 2021 Apr;11(4):805-9.
    PubMed
  • 73 Zavala VA, Bracci PM, Carethers JM, Carvajal-Carmona L, Coggins NB, Cruz-Correa MR, et al. Cancer health disparities in racial/ethnic minorities in the United States. Br J Cancer 2021 Jan;124(2):315-32.
    PubMed
  • 74 Wojcik GL, Graff M, Nishimura KK, Tao R, Haessler J, Gignoux CR, et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature 2019 Jun;570(7762):514-8.
    PubMed
  • 75 Sherman RM, Forman J, Antonescu V, Puiu D, Daya M, Rafaels N, et al. Assembly of a pan-genome from deep sequencing of 910 humans of African descent. Nat Genet 2019 Jan;51(1):30-5. Erratum in: Nat Genet 2019 Feb;51(2):364.
    PubMed
  • 76 Davis M, Martini R, Newman L, Elemento O, White J, Verma A, et al. Identification of Distinct Heterogenic Subtypes and Molecular Signatures Associated with African Ancestry in Triple Negative Breast Cancer Using Quantified Genetic Ancestry Models in Admixed Race Populations. Cancers (Basel) 2020 May 13;12(5):1220.
    PubMed
  • 77 Marker KM, Zavala VA, Vidaurre T, Lott PC, Vásquez JN, Casavilca-Zambrano S, et al; COLUMBUS Consortium. Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Is Associated with Indigenous American Ancestry in Latin American Women. Cancer Res 2020 May 1;80(9):1893-901.
    PubMed
  • 78 Shukla P, Singh KK. The mitochondrial landscape of ovarian cancer: emerging insights. Carcinogenesis 2021 May 28;42(5):663-71.
    PubMed
  • 79 Faisal FA, Murali S, Kaur H, Vidotto T, Guedes LB, Salles DC, et al. CDKN1B Deletions are Associated with Metastasis in African American Men with Clinically Localized, Surgically Treated Prostate Cancer. Clin Cancer Res 2020 Jun 1;26(11):2595-602.
    PubMed
  • 80 Mahal BA, Alshalalfa M, Kensler KH, Chowdhury-Paulino I, Kantoff P, Mucci LA, et al. Racial Differences in Genomic Profiling of Prostate Cancer. N Engl J Med 2020 Sep 10;383(11):1083-5.
    PubMed
  • 81 Yamoah K, Asamoah FA, Abrahams AOD, Awasthi S, Mensah JE, Dhillon J, et al. Prostate tumors of native men from West Africa show biologically distinct pathways-A comparative genomic study. Prostate 2021 Dec;81(16):1402-10.
    PubMed
  • 82 Rayford W, Beksac AT, Alger J, Alshalalfa M, Ahmed M, Khan I, et al. Comparative analysis of 1152 African-American and European-American men with prostate cancer identifies distinct genomic and immunological differences. Commun Biol 2021 Jun 3;4(1):670.
    PubMed
  • 83 Sinha S, Mitchell KA, Zingone A, Bowman E, Sinha N, Schäffer AA, et al. Higher prevalence of homologous recombination deficiency in tumors from African Americans versus European Americans. Nat Cancer 2020 Jan;1(1):112-21.
    PubMed
  • 84 Mitchell KA, Nichols N, Tang W, Walling J, Stevenson H, Pineda M, et al. Recurrent PTPRT/JAK2 mutations in lung adenocarcinoma among African Americans. Nat Commun 2019 Dec 16;10(1):5735. Erratum in: Nat Commun 2020 Jan 30;11(1):700.
    PubMed
  • 85 Qian J, Nie W, Lu J, Zhang L, Zhang Y, Zhang B, et al. Racial differences in characteristics and prognoses between Asian and white patients with nonsmall cell lung cancer receiving atezolizumab: An ancillary analysis of the POPLAR and OAK studies. Int J Cancer 2020 Jun 1;146(11):3124-33.
    PubMed
  • 86 Mancini F, Giorgini L, Teveroni E, Pontecorvi A, Moretti F. Role of Sex in the Therapeutic Targeting of p53 Circuitry. Front Oncol 2021 Jul 8;11:698946.
    PubMed
  • 87 Ding M, Wu J, Sun R, Yan L, Bai L, Shi J, et al. Androgen receptor transactivates KSHV noncoding RNA PAN to promote lytic replication-mediated oncogenesis: A mechanism of sex disparity in KS. PLoS Pathog 2021 Sep 20;17(9):e1009947.
    PubMed
  • 88 Li CH, Prokopec SD, Sun RX, Yousif F, Schmitz N; PCAWG Tumour Subtypes and Clinical Translation, Boutros PC; PCAWG Consortium. Sex differences in oncogenic mutational processes. Nat Commun 2020 Aug 28;11(1):4330.
    PubMed
  • 89 Ye Y, Jing Y, Li L, Mills GB, Diao L, Liu H, et al. Sex-associated molecular differences for cancer immunotherapy. Nat Commun 2020 Apr 14;11(1):1779.
    PubMed
  • 90 Han R, Sun W, Huang J, Shao L, Zhang H. Sex-biased DNA methylation in papillary thyroid cancer. Biomark Med 2021 Feb;15(2):109-20.
    PubMed
  • 91 Riviere P, Luterstein E, Kumar A, Vitzthum LK, Deka R, Sarkar RRet al. Survival of African American and non-Hispanic white men with prostate cancer in an equal-access health care system. Cancer 2020 Apr 15;126(8):1683-90.
    PubMed
  • 92 Panigrahi GK, Praharaj PP, Kittaka H, Mridha AR, Black OM, Singh R, et al. Exosome proteomic analyses identify inflammatory phenotype and novel biomarkers in African American prostate cancer patients. Cancer Med 2019 Mar;8(3):1110-23.
    PubMed
  • 93 Ferrarini A, Di Poto C, He S, Tu C, Varghese RS, Kara Balla A, et al. Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma. J Proteome Res 2019 Aug 2;18(8):3067-76.
    PubMed
  • 94 Wei LQ, Cheong IH, Yang GH, Li XG, Kozlakidis Z, Ding L, et al. The Application of High-Throughput Technologies for the Study of Microbiome and Cancer. Front Genet 2021 Jul 28;12:699793.
    PubMed
  • 95 Chen J, Douglass J, Prasath V, Neace M, Atrchian S, Manjili MH, et al. The microbiome and breast cancer: a review. Breast Cancer Res Treat 2019 Dec;178(3):493-6.
    PubMed
  • 96 Chen D, Wu J, Jin D, Wang B, Cao H. Fecal microbiota transplantation in cancer management: Current status and perspectives. Int J Cancer 2019 Oct 15;145(8):2021-31.
    PubMed
  • 97 Fernández MF, Reina-Pérez I, Astorga JM, Rodríguez-Carrillo A, Plaza-Díaz J, Fontana L. Breast Cancer and Its Relationship with the Microbiota. Int J Environ Res Public Health 2018 Aug 14;15(8):1747.
    PubMed
  • 98 Farhana L, Antaki F, Murshed F, Mahmud H, Judd SL, Nangia-Makker P, et al. Gut microbiome profiling and colorectal cancer in African Americans and Caucasian Americans. World J Gastrointest Pathophysiol 2018 Sep 29;9(2):47-58.
    PubMed
  • 99 Kann BH, Hosny A, Aerts HJW. Artificial intelligence for clinical oncology. Cancer Cell [Internet] 2021;39(7):916–27. Available from: http://dx.doi.org/10.1016/j.ccell.2021.04.002
    PubMed
  • 100 Huynh E, Hosny A, Guthier C, Bitterman DS, Petit SF, Haas-Kogan DA, et al. Artificial intelligence in radiation oncology. Nat Rev Clin Oncol [Internet] 2020;17(12):771–81. Available from: http://dx.doi.org/10.1038/s41571-020-0417-8
    PubMed
  • 101 Lu MT, Raghu VK, Mayrhofer T, Aerts HJWL, Hoffmann U. Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model. Ann Intern Med 2020 Nov 3;173(9):704-13.
    PubMed
  • 102 Xu Z, Wang X, Zeng S, Ren X, Yan Y, Gong Z. Applying artificial intelligence for cancer immunotherapy. Acta Pharm Sin B 2021 Nov;11(11):3393-405.
    PubMed
  • 103 Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med 2019 Oct 29;17(1):195.
    PubMed
  • 104 Singh RP, Hom GL, Abramoff MD, Campbell JP, Chiang MF; AAO Task Force on Artificial Intelligence. Current Challenges and Barriers to Real-World Artificial Intelligence Adoption for the Healthcare System, Provider, and the Patient. Transl Vis Sci Technol 2020 Aug 11;9(2):45.
    PubMed
  • 105 Barda N, Yona G, Rothblum GN, Greenland P, Leibowitz M, Balicer R, et al. Addressing bias in prediction models by improving subpopulation calibration. J Am Med Inform Assoc 2021 Mar 1;28(3):549-58.
    PubMed
  • 106 Hendrix N, Hauber B, Lee CI, Bansal A, Veenstra DL. Artificial intelligence in breast cancer screening: primary care provider preferences. J Am Med Inform Assoc 2021 Jun 12;28(6):1117-24.
    PubMed
  • 107 Hébert-Johnson U, Kim MP, Reingold O, Rothblum GN. Calibration for the (Computationally-Identifiable) Masses [Internet]. arXiv [cs.LG] 2017. Available from: http://arxiv.org/abs/1711.08513
    PubMed
  • 108 Coombes CE, Abrams ZB, Li S, Abruzzo LV, Coombes KR. Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia. J Am Med Inform Assoc 2020 Jul 1;27(7):1019-27.
    PubMed
  • 109 Polite BN, Adams-Campbell LL, Brawley OW, Bickell N, Carethers JM, Flowers CR, et al. Charting the Future of Cancer Health Disparities Research: A Position Statement From the American Association for Cancer Research, the American Cancer Society, the American Society of Clinical Oncology, and the National Cancer Institute. J Clin Oncol 2017 Sep 10;35(26):3075-82.
    PubMed
  • 110 Char DS, Shah NH, Magnus D. Implementing Machine Learning in Health Care - Addressing Ethical Challenges. N Engl J Med 2018 Mar 15;378(11):981-3.
    PubMed
  • 111 Crowley RJ, Tan YJ, Ioannidis JPA. Empirical assessment of bias in machine learning diagnostic test accuracy studies. J Am Med Inform Assoc 2020 Jul 1;27(7):1092-101.
    PubMed
  • 112 Block RG, Puro J, Cottrell E, Lunn MR, Dunne MJ, Quiñones AR, et al. Recommendations for improving national clinical datasets for health equity research. J Am Med Inform Assoc 2020 Nov 1;27(11):1802-7.
    PubMed
  • 113 Ma C, Sridharan M, Al-Sayegh H, Li A, Guo D, Auclair M, et al. Building a Harmonized Datamart by Integrating Cross-Institutional Systems of Clinical, Outcome, and Genomic Data: The Pediatric Patient Informatics Platform (PPIP). JCO Clin Cancer Inform 2021 Feb;5:202-15.
    PubMed