Application of the Socioecological Model to Regional Clinical Trials: A Paradigm-Shift to Advance Scientific Discovery and Prognostic Modeling

Author: Shawna L. Ehlers PhD, ABPP
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Tightly controlled, randomized clinical trials drive powerful scientific advancements and translation into healthcare advancements. Over the past 20 years, we have had the thrilling privilege of witnessing patients survive diseases that previous generations could not survive, due to a deeper understanding of biology, biologic mechanisms, and therapeutic targets. Oncology trials save lives.

Oncology trials increasingly include regional and international study sites and populations. This is demonstrated by Wilson et al1 in this issue, via analysis of multiarm trials sourced from the archive of FDA approvals for treatments of solid tumor malignancies. Although only 53% of the 147 studies analyzed in this paper included regional subgroup analyses, regional variations were found in approximately 18% of the studies examining overall and progression-free survival.

How do we explain regional and otherwise geo-coded variation in trial outcomes? Wilson et al1 provide a question guide for interpretation of regional variations and suggest improvements in trial design. Important improvements include adoption of standardized classification (eg, using WHO Regions or World-Bank Income Groups); prespecifying subgroup analyses within the format of the CONSORT checklist; reporting both absolute and relative values; reporting competing events, such as leading causes of death that might vary by region; and reporting subsequent treatments after trial that also might differ by region.

Importantly, this study highlights the utility of the socioecological framework and existing scientific studies that highlight known regional and other subgroup disparities in national studies. Progress lies in prognostic scoping across the “levels” of the socioecological model and the associated National Institute on Minority Health and Health Disparities (NIMHD) Research Framework2 to define “external” prognostic factors statistically controlled by randomized trial designs beyond biology. We must revisit the distinction between internal and external validity in the design of scientific studies and the importance of both types of validity in scientific advancement. The definition and analysis of an increasingly broader range of recognized prognostic variables has resulted in the inclusion of race, ethnicity, and biological sex as mandated variables in clinical trial data collection. Efforts are underway to expand the required set of collected prognostic variables, improve associated recruitment and retention of diverse trial participants to more accurately represent populations of patients with cancer, and mitigate documented disparities.36 Prognostic factors extend beyond the biology within us to the socioecological world around us.

Further analyses of socioecological prognostic factors have revealed structural disparities in health-associated resources, including healthcare quality and access.613 The patient before us at any moment might have shorter overall or progression-free survival associated with social status, discrimination and medical mistrust, stigma, neighborhood environmental pollution, geographic region and available resources, rurality and travel distance, poverty, and socioeconomic status generally. Interventions beyond biology might improve outcomes via behavioral or social mechanisms.8,1417 Our challenge is to reach beyond the normal boundaries of the clinical trial, beyond biology, to factors that interact with and impact biology.

The paradigm shift to include “real-world” socioecological context is a call for increased diversity not only in representative study populations and workforces but also in scientific thinking and design, scientific debate, and risk of “failure” inherent in trying new things (ie, learning). We can no longer superficially accept factors beyond biology as “controlled” via randomization. We must once again accept the challenge to explore a scientific world with limited understanding. We must better capture real-world diversity in patients and their environments to understand real-world statistical variability in outcomes, and start a second wave of trial advancements that save lives.

Wilson et al1 provide a list of questions and study design strategies to facilitate real-world interpretation and conduct of clinical trials. We can further challenge ourselves as a comprehensive cancer care community by asking “How do I expand prognostic modeling within my own work?” Some thoughts on this are below:

  1. Existing knowledge: What are the prognostic factors in your population of study or care? Use the Socio Ecological Model18,19 and associated NIMHD Research Framework2 to take an organized look beyond biology and your specialty scope of practice. Are factors such as tobacco use, travel distance from home to clinic, travel distance to specialty care, poverty, and insurance status known to impact outcomes in your work?

  2. Interdisciplinary team building: What interdisciplinary expertise do you need on your team to optimize understanding of these prognostic factors? Reach out to behavioral, social, organizational, environmental, and policy scientists within your organization, universities, or trial networks to build on common goals that benefit your patient population. Ask your organization to provide resources to and incentivize interdisciplinary team building.

  3. Quadruple aim of healthcare: Use the quadruple aim of healthcare20 to engage organizational and other stakeholders to define common goals. A broader conceptualization of trial outcomes has the potential to improve not only multiple patient trial outcomes but also the aggregate national reputation of your organization, healthcare costs, and clinician burnout.21,22

  4. Data collection: We have not achieved excellence in care until we include all known prognostic factors in study design and clinical evaluation/treatment planning. Adding even one prognostic factor improves prognostic modeling and can empower patients to recognize and seek resources for modifiable prognostic risk factors.

  5. Community and patient engagement: No one understands the patient experience better than the patient. Respect community and patient advocacy groups as unique experts in patient experience, following established guidance in community-engaged and participatory research.23 Act with humility and willingness to learn and understand. Ask questions such as, “We want to improve the way we deliver healthcare. If you could change anything, what would you change? How could we provide better care for everyone in the community?” Partner with community and patient groups to hire culturally-specific research coordinators and cancer navigators as the welcoming frontline to mitigate known factors of discrimination and medical mistrust, and thus improve timely access to equitable care.24,25 Integrate these frontline groups as team members to ensure team cohesion toward continual process improvements in equitable care.

The information in the study by Wilson et al1 provides an opportunity for us to advance the design and conduct of clinical trials and associated prognostic modeling and comprehensive cancer care. Challenge yourself and your teams to add at least one additional socioecological prognostic variable to your next study protocol, clinical evaluation template, or review template, joining the second wave of life-saving trial advancements.

References

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    Wilson BE, Pearson SA, Barton MB, Amir E. Regional variations in cancer trials. J Natl Compr Canc Netw 2022;20:879886.

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    National Institute on Minority Health and Health Disparities. NIMHD Minority Health and Health Disparities Research Framework. Accessed July 14, 2022. Available at: https://www.nimhd.nih.gov/about/overview/research-framework/nimhd-framework.html

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    Unger JM, Vaidya R, Hershman DL, et al. Systematic review and meta-analysis of the magnitude of structural, clinical, and physician and patient barriers to cancer clinical trial participation. J Natl Cancer Inst 2019;111:245255.

    • Crossref
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    Kacel EL, Pankey TL, Vencill JA, et al. Include, affirm, and empower: a paradigm shift in cancer clinical trials for sexual and gender diverse populations. Ann LGBTQ Public and Popul Health 2022;3:1840.

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    El Hayek S, Dakroub A, Beaini H, et al. Psycho-oncology in the Arab world: the time is now. Psychooncology 2022;31:148151.

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    Yang JD, Hainaut P, Gores GJ, et al. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nature Rev Gastroenterol Hepatol 2019;16:589604.

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    Unger JM, Moseley AB, Cheung CK, et al. Persistent disparity: socioeconomic deprivation and cancer outcomes in patients treated in clinical trials. J Clin Oncol 2021;39:13391348.

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    Levit LA, Byatt L, Lyss AP, et al. Closing the rural cancer care gap: three institutional approaches. JCO Oncol Pract 2020;16:422430.

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    Yaghjyan L, Cogle CR, Deng G, et al. Continuous rural-urban coding for cancer disparity studies: is it appropriate for statistical analysis? Int J Environ Res Public Health 2019;16:1076.

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    Henning-Smith C, Lahr M. Rural-urban difference in workplace supports and impacts for employed caregivers. J Rural Health 2019;35:4957.

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    Unger JM, Moseley A, Symington B, et al. Geographic distribution and survival outcomes for rural patients with cancer treated in clinical trials. JAMA Netw Open 2018;1:e181235.

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    Borno HT, Zhang L, Siegel A, et al. At what cost to clinical trial enrollment? A retrospective study of patient travel burden in cancer clinical trials. Oncologist 2018;23:12421249.

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    Bergin RJ, Emery J, Bollard RC, et al. Rural–urban disparities in time to diagnosis and treatment for colorectal and breast cancer. Cancer Epidemiol Biomarkers Prev 2018;27:10361046.

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    Eckerling A, Ricon-Becker I, Sorski L, et al. Stress and cancer: mechanisms, significance and future directions. Nat Rev Cancer 2021;21:767785.

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    Lutgendorf SK, Andersen BL. Biobehavioral approaches to cancer progression and survival: mechanisms and interventions. Am Psychol 2015;70:186.

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    Kennedy AE, Vanderpool RC, Croyle RT, Srinivasan S. An overview of the National Cancer Institute's initiatives to accelerate rural cancer control research. Cancer Epidemiol Biomarkers Prev 2018;27:12401244.

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    van der Kruk SR, Butow P, Mesters I, et al. Psychosocial well-being and supportive care needs of cancer patients and survivors living in rural or regional areas: a systematic review from 2010 to 2021. Supportive Care Cancer 2022;30:10211064.

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    • Export Citation
  • 18.

    Palafox NA, Reichhardt M, Taitano JR, et al. A socio-ecological framework for cancer control in the Pacific: a community case study of the US affiliated Pacific Island jurisdictions 1997–2017. Front Public Health 2018;6:313.

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    Kumar S, Quinn SC, Kim KH, et al. The social ecological model as a framework for determinants of 2009 H1N1 influenza vaccine uptake in the United States. Health Educ Behav 2012;39:229243.

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    Bodenheimer T, Sinsky C. From triple to quadruple aim: care of the patient requires care of the provider. Ann Fam Med 2014;12:573576.

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    • Export Citation
  • 22.

    Toffolutti V, Stuckler D, McKee M, et al. The employment and mental health impact of integrated Improving Access to Psychological Therapies: evidence on secondary health care utilization from a pragmatic trial in three English counties. J Health Serv Res Policy 2021;26:224233.

    • Crossref
    • PubMed
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  • 23.

    Wallerstein N, Duran B. Community-based participatory research contributions to intervention research: the intersection of science and practice to improve health equity. Am J Public Health 2010;100 (Suppl 1):S4046.

    • Crossref
    • PubMed
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    • Export Citation
  • 24.

    Phillips S, Villalobos AVK, Crawbuck GSN, Pratt-Chapman ML. In their own words: patient navigator roles in culturally sensitive cancer care. Support Care Cancer 2019;27:16551662.

    • Crossref
    • PubMed
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  • 25.

    Grimes C, Dankovchik J, Cahn M, Warren-Mears V. American Indian and Alaska Native cancer patients' perceptions of a culturally specific patient navigator program. J Prim Prev 2017;38:121135.

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SHAWNA L. EHLERS, PhD, ABPP

Shawna L. Ehlers, PhD, ABPP, is an Associate Professor of psychology and Co-Chair, Division and Outpatient Consultation, Department of Psychiatry and Psychology, at the Mayo Clinic Comprehensive Cancer Center. Her research is focused on the area of psycho-oncology and stem cell transplantation, and she conducts transdisciplinary patient-oriented research aimed at improving patient care and overall health.

Disclosures: The author has disclosed having no financial interests, arrangements, affiliations, or commercial interests with the manufacturers of any products discussed in this article or their competitors.

Correspondence: Shawna L. Ehlers, PhD, ABPP, Department of Psychiatry and Psychology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, MN 55902. Email: Ehlers.Shawna@mayo.edu

View associated content

  • 1.

    Wilson BE, Pearson SA, Barton MB, Amir E. Regional variations in cancer trials. J Natl Compr Canc Netw 2022;20:879886.

  • 2.

    National Institute on Minority Health and Health Disparities. NIMHD Minority Health and Health Disparities Research Framework. Accessed July 14, 2022. Available at: https://www.nimhd.nih.gov/about/overview/research-framework/nimhd-framework.html

    • Search Google Scholar
    • Export Citation
  • 3.

    Unger JM, Vaidya R, Hershman DL, et al. Systematic review and meta-analysis of the magnitude of structural, clinical, and physician and patient barriers to cancer clinical trial participation. J Natl Cancer Inst 2019;111:245255.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Kacel EL, Pankey TL, Vencill JA, et al. Include, affirm, and empower: a paradigm shift in cancer clinical trials for sexual and gender diverse populations. Ann LGBTQ Public and Popul Health 2022;3:1840.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    El Hayek S, Dakroub A, Beaini H, et al. Psycho-oncology in the Arab world: the time is now. Psychooncology 2022;31:148151.

  • 6.

    Yang JD, Hainaut P, Gores GJ, et al. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nature Rev Gastroenterol Hepatol 2019;16:589604.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Unger JM, Moseley AB, Cheung CK, et al. Persistent disparity: socioeconomic deprivation and cancer outcomes in patients treated in clinical trials. J Clin Oncol 2021;39:13391348.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Levit LA, Byatt L, Lyss AP, et al. Closing the rural cancer care gap: three institutional approaches. JCO Oncol Pract 2020;16:422430.

  • 9.

    Yaghjyan L, Cogle CR, Deng G, et al. Continuous rural-urban coding for cancer disparity studies: is it appropriate for statistical analysis? Int J Environ Res Public Health 2019;16:1076.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Henning-Smith C, Lahr M. Rural-urban difference in workplace supports and impacts for employed caregivers. J Rural Health 2019;35:4957.

  • 11.

    Unger JM, Moseley A, Symington B, et al. Geographic distribution and survival outcomes for rural patients with cancer treated in clinical trials. JAMA Netw Open 2018;1:e181235.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Borno HT, Zhang L, Siegel A, et al. At what cost to clinical trial enrollment? A retrospective study of patient travel burden in cancer clinical trials. Oncologist 2018;23:12421249.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Bergin RJ, Emery J, Bollard RC, et al. Rural–urban disparities in time to diagnosis and treatment for colorectal and breast cancer. Cancer Epidemiol Biomarkers Prev 2018;27:10361046.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Eckerling A, Ricon-Becker I, Sorski L, et al. Stress and cancer: mechanisms, significance and future directions. Nat Rev Cancer 2021;21:767785.

  • 15.

    Lutgendorf SK, Andersen BL. Biobehavioral approaches to cancer progression and survival: mechanisms and interventions. Am Psychol 2015;70:186.

  • 16.

    Kennedy AE, Vanderpool RC, Croyle RT, Srinivasan S. An overview of the National Cancer Institute's initiatives to accelerate rural cancer control research. Cancer Epidemiol Biomarkers Prev 2018;27:12401244.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    van der Kruk SR, Butow P, Mesters I, et al. Psychosocial well-being and supportive care needs of cancer patients and survivors living in rural or regional areas: a systematic review from 2010 to 2021. Supportive Care Cancer 2022;30:10211064.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Palafox NA, Reichhardt M, Taitano JR, et al. A socio-ecological framework for cancer control in the Pacific: a community case study of the US affiliated Pacific Island jurisdictions 1997–2017. Front Public Health 2018;6:313.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Kumar S, Quinn SC, Kim KH, et al. The social ecological model as a framework for determinants of 2009 H1N1 influenza vaccine uptake in the United States. Health Educ Behav 2012;39:229243.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Bodenheimer T, Sinsky C. From triple to quadruple aim: care of the patient requires care of the provider. Ann Fam Med 2014;12:573576.

  • 21.

    Steel JL, Richards G, Billiar T, et al. Depression and health care utilization and costs in patients diagnosed with cancer [abstract]. J Clin Oncol 2019;37(Suppl):Abstract: e23128.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Toffolutti V, Stuckler D, McKee M, et al. The employment and mental health impact of integrated Improving Access to Psychological Therapies: evidence on secondary health care utilization from a pragmatic trial in three English counties. J Health Serv Res Policy 2021;26:224233.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Wallerstein N, Duran B. Community-based participatory research contributions to intervention research: the intersection of science and practice to improve health equity. Am J Public Health 2010;100 (Suppl 1):S4046.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Phillips S, Villalobos AVK, Crawbuck GSN, Pratt-Chapman ML. In their own words: patient navigator roles in culturally sensitive cancer care. Support Care Cancer 2019;27:16551662.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Grimes C, Dankovchik J, Cahn M, Warren-Mears V. American Indian and Alaska Native cancer patients' perceptions of a culturally specific patient navigator program. J Prim Prev 2017;38:121135.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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