Hirangi Mukhi, BS

The past 5 decades have seen an incredible evolution in science, from the microcosm of our understanding of life through advances in the Human Genome Project (HGP) to the macrocosm of commercial space travel. Although there is tremendous excitement about boundaries of science stretching beyond human imagination, realizing the real-world impact of scientific advancement on the health outcomes of patients provides a reality check on how far we still must go.

The completion of the HGP1 has ushered in a new era in our understanding of cancer; specifically, the unraveling of the human genome has revealed that cancer is a complex set of diseases with the possibilities of genetically targeted treatment options and a greater understanding of genetic variations that can lead to high-risk disease. The field of oncology has witnessed rapid strides and perhaps benefited most with the understanding of complex interaction of epigenetics, environmental factors, and social determinants of health (SDOH).

This field is now seen as precision medicine (PM) or, to be more precise, the fi eld of precision oncology and personalized medicine. PM holds the promise of revolutionizing cancer prevention and treatment by combining genotype, phenotype, and social factors.

 The implementation of PM in cancer care permits a tailor-made approach that increases the chance of treatment response and reduces adverse events (AEs). The application of PM stretches far beyond an individualized approach to cancer care with a wider relevance and larger impact regarding population health outcomes.

When it comes to oncology, PM has progressively focused on the sequencing of cancer genomes. This has led to a better understanding of oncogenesis and actionable alterations. With the use of comprehensive genomic profi ling (CGP), the cost of sequencing the cancer genome has been reduced and spurred the development of targeted therapies. The depth and breadth of discoveries and innovation have enabled the detection of somatic driver mutations, resistance mechanisms, quantification of mutational burden, and germline mutations. CGP technology has led to whole exome sequencing (WES) to optimize our understanding of molecular pathological process and appropriate therapeutic options. In addition, CGP has catalyzed progressive developments in pharmacogenomics by uncovering variance in drug metabolism and by explaining differences in the efficacy and toxicity of identical regimens in ethnically diverse populations.

PM is an “approach to disease prevention and treatment to maximize effectiveness by considering individual variability in genes, environment, and lifestyle,” according to the PM Initiative Working Group.

 The goal of PM is to advance medical and scientific discoveries to offer more tailored, precise, and accurate health interventions to maximize benefi ts for patients.

 PM adopts diverse strategies in cancer medicine tailored to the unique biology of a patient’s disease. These strategies range from the application of CGP (either CGP or WES and/or pharmacogenomics) to identify a mutation to the use of targeted therapies to select site-agnostic approaches. PM’s importance is growing faster than our health care system can adapt. To fulfi l the desired goals and objectives, the oncology ecosystem needs to carry out a comprehensive strategy for success. PM holds the promise of improved effi ciency, better care, and the reduction of ineffective treatments and costs. However, there are potential pitfalls and health care inequities that may minimize global application and benefi ts from the PM-derived approach.

Lack of appropriate representation of members of minority communities in Genome-Wide Association Studies (GWAS)

. Clinical trial results may not be applicable to all populations. Further, diverse populations may not benefi t equally. To achieve the full potential of PM, it is important to develop a comprehensive catalog of mutations unique to each race and ethnicity, representing a realworld scenario. A 2017 study examined the populations included in GWAS. The study found that nearly 80% of individuals in GWAS were of European descent, 10% were of Asian descent, 2% of African descent, 1% of Hispanic descent, and less than 1% were of other populations.

 Health care inequity could deepen with PM. Failure to address systemic bias in health care provision and genetic databases will make existing disparities worse.

Payer-related factors: limited coverage/ health policy

. Payer policies are frequently a hindrance for access to testing. A study published in 

 reported that limited coverage and low reimbursement for the CGP testing pose a huge barrier, and broader reimbursement policies are needed to adopt pan-cancer CGP testing that benefi ts patients in clinical practice. Additionally, CGP is not covered equally across health care benefits.

Needs assessment to address cancer health disparities

. PM has increased racial disparity in cancer care6 in contrast to the theme of the Cancer Moonshot program. African American men often experience worse prostate cancer outcomes than White men, leading to racial disparities that could be partially explained by differences in genomic data.

 Prostate tumors of African American men manifest a unique immune repertoire and have significant enrichment of proinflammatory immune pathways that are associated with poorer outcomes.

 Collaborative and intensive efforts at all levels of research, from the funding of studies to the publication of findings, will be necessary to ensure that genomic research does not conserve historical inequities or curtail the contribution that genomics could make to the health of all humanity.

 There is the need to study more diverse populations using empirical examples and theoretical reasoning.

Appropriate patient diversity across all 3 elements is critical given that racial and/ or ethnic groups may experience disparate responses to certain drugs. This has the impact of reducing clinical efficacy and/or increasing the risk of AEs when drugs are brought to market after testing in a nonrepresentative clinical trial population.

To fulfill the promises of precision medicine so that the right care is delivered to the right patient at the right time, actionable solutions to the barriers listed above should be addressed and implemented. We started a pilot study at Carolina Blood and Cancer Care Associates (CBCCA) with the Community Oncology Alliance to develop best clinical practices to increase biomarker testing.

Research Scope The primary scope of this pilot is to develop best practices in incorporating biomarker testing in community cancer clinics by creating the Real-World Evidence (RWE) Registry by using CGP and NGS/WES testing to address cancer health disparities (CHD). This would create a road map of implementation of PM for identifying actionable mutations in an inclusive fashion. The research scope of this pilot covers 4 major areas necessary for creating best clinical practices.

Identify appropriate steps and strategy to achieve optimum testing for all patients with cancer, including all patients from minority populations, in accordance with approved guidelines 

identify barriers to biomarker testing) identify barriers and solution to implement PM in community cancer clinics 

: Oncologists and providers of the CBCCA serving an ethnically diverse population in rural South Carolina examined 1786 cancer patients in 2021. Patients were examined by 5 oncologists and 3 advanced practice practitioners. Of these, 1466 patients were followed for regular care. Also, 240 patients were seen for single consultation in hospital and were being followed by other specialists (urologists or other oncologists in the area) and were hospitalized when our team saw them). Seventy-one patients were lost to follow-up. Of the 1466 patients followed at clinic, 512 were survivors having routine follow-up care. Of the 954 patients followed for active cancer management, 510 were early stage or noninvasive and did not qualify for CGP testing based on payer criteria and FDA approval of tests. Of the 442 patients who met criteria, 42 refused to have additional testing done because they responded to ongoing treatment and/or had reservations. Finally, our team was able to get CGP testing done for 354 patients.

SDOH In terms of SDOH factors, 43.2% patients reported household incomes below $25,000 and the majority (57.8%) reported household incomes below $50,000 (FIGURE 1). A minority of patients (24.3%) had 4-year college degrees or higher (FIGURE 2); the highest educational attainment was high school graduate for 47.3%.

Household income below $50,000 was associated with financial and food insecurity: patients from lower-income households were more likely to report being worried about being able to pay bills often/always (19.4% vs 0%, respectively; Fisher exact 

 = .03) and were more likely to be either worried about running out of food (18.3% vs 0%; Fisher exact 

 = .02) or to have run of out of food (15.1% vs 0%; Fisher exact 

Of these patients, 133 had liquid biopsy and the rest (n = 221) had either somatic CGP panel or WES (FIGURE 3). Of patients who had liquid biopsy (FIGURE 4), 24 had actionable mutations. An additional 52 patients had CGP fi ndings indicative of germline implications. 

Of the 221 patients with tissue-based CGP testing, 38 had an actionable mutation with an FDA-approved drug. Within tissue-based testing, WES had detected a higher number of CGP findings with germline implications compared with somatic testing alone. An additional 64 patients had CGP findings suggestive of a mutation with an FDA-approved drug in another tumor type. In summary, our CGP testing rate for clinically appropriate utilization of CGP and biomarker testing (either tissue based or liquid biopsy) reached 84% of eligible patients. Of these patients tested for CGP, clinically actionable findings that resulted in change in management were seen in 23% for FDA-approved agent in the same tumor type and 28% in another tumor type. Additionally, 40% of patients had fi ndings indicating germline implications. The most common fi nding of germline implications was 

We believe this is the first study reflecting successful update in CGP. We observed an increase in the CGP testing rate in clinically appropriate situations. In RWE studies, as a community clinical practice, we were able to increase CGP testing rate to over 80% compared with the 25% to 40% reported in the literature. We suggest that universal CGP testing is important for patients with advanced cancer to address health disparities. Regarding ethnic minorities and a resistance to participating in RWE studies, we found the contrary. We did not find any significant difference in patients’ willingness to participate in these studies based on stereotypes that involved patients who are members of minority populations.

In our study, we found actionable mutation resulting in change of management in up to 25% of patients where targeted therapy could be offered. Additional observations included signifi cant patients with germline implications, the most common being 

 deletion. We plan to expand this study from its original scope so that it is implemented across the community practice. 

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Articles

Although there is tremendous excitement about boundaries of science stretching beyond human imagination, realizing the real-world impact of scientific advancement on the health outcomes of patients provides a reality check on how far we still must go.

Incorporating Biomarker Testing in Community Cancer Clinics: A Real-World Pilot Study

The rapid progression of novel immune-based treatment strategies in solid tumors—beginning with the approval of immune checkpoint inhibitors (ICIs) for melanoma in 2011 and subsequent approval of numerous agents in the ICI therapeutic category—has revolutionized treatment of advanced cancers that were deemed invariably fatal until the past decade.

 Faster development of novel biomarker-driven targeted therapies has accelerated hope and optimism about converting advanced solid tumors into chronic diseases. These advances have also led to the recognition of other clinical challenges, including unforeseen observations and complications associated with choosing the sequencing of appropriate therapeutic interventions as well as the management of drug-related complications.

One critical enigma facing clinicians is how to differentiate between pseudoprogression (PSP), true disease progression (TDP), and hyperprogression (HPD). These phenomena are observed in patients treated with ICIs targeting CTLA-4, PD-1, or PD-L1 that are approved for use across multiple types of advanced cancers. The lack of consensus or an analytic framework to decipher and differentiate between early indications of PSP, TDP, and HPD may expose patients to avoidable harm.

Another challenge centers around selecting the most appropriate therapeutic intervention when broad-based genomic profiling results reveal multiple actionable biomarkers vs actionable genomic driver mutations such as those found in 

, and a number of other targetable pathogenic genomic alterations. Selecting the right drug at the right time for patients is further complicated by these considerations:

The disparate timing of receiving results from PD-1/PD-L1 immunohistochemistry testing vs next-generation sequencing (NGS) testing 

 Determining the adequacy of NGS panel testing with negative results, whether using a whole exome sequencing or comprehensive genomic profiling approach

For this review we will confine our discussion to the clinical impact associated with the determination of PSP, TDP, and HPD following ICI therapy. Even the definitions of TDP, PSP, and HPD have not reached uniform consensus, so we will focus on clinical implications.

Although an accurate consensus has not been reached on defining PSP or HPD, differentiating between those clinical states is critically important. PSP indicates efficacy of ICI therapy, whereas HPD portrays ineffective treatment with ICIs resulting in a rapid negative clinical outcome in most cases. PSP is a type of response to ICI therapy accompanied by an apparent initial increase in tumor size or new lesions, which potentially appear upon radiological assessment, followed by an eventual decrease in tumor burden. Although this response favors patients receiving ICI therapy, a lack of awareness can lead to premature discontinuation of treatment because of an incorrect clinical interpretation of disease progression.

The incidence of ICI therapy–associated PSP varies from 3.70% to 15% in different tumor types.

 PSP is a relatively uncommon response defined as an initial increase of tumor size followed by a measurable response to treatment. ICI therapy–associated PSP results from an exacerbated immune cell infiltration in the tumor bed (T cells expressing CD103+ and CD8+).

Another postulated mechanism of PSP described by Cohen et al11 occurred in a case of PSP involving brain metastases in a patient with melanoma after treatment with pembrolizumab (Keytruda). The histology revealed an inflammatory reaction identified as isolated clusters of tumor cells surrounded by reactive astrocytosis and inflammatory cells.

 PSP associated with ICI therapy carried a higher likelihood of 1-year survival when compared with TPD.

 Failure to distinguish PSP from TPD may result in premature discontinuation of treatment with ICI, leading to adverse outcomes. It is crucial to distinguish between TPD and PSP.

HPD can be defined as an accelerated tumor growth pattern after exposure to ICI therapy, with an increase in the absolute mass of tumor cells in a relatively short time. Possible explanations of HPD in response to ICI may include the expansion of PD-1–positive regulatory T cells, exhaustion of compensatory T cells, modulation of protumorigenic immune cell subsets, and activation of aberrant inflammation cell cycle signaling.

 HPD may be observed as a rapid escalation in the size and bulk of masses of measurable tumor volume, the appearance of numerous new lesions, and/or rapid deterioration in organ function leading to symptomatic disease progression (similar to jaundice from a rise in bilirubin and liver enzymes), and/or shortness of breath from the progression of metastases in the lungs or deterioration of brain metastases leading to worsening central nervous system symptoms. Efforts have been made to define HPD based on tumor growth rate (TGR), tumor growth kinetics (TGK), and other RECIST parameters to better define HPD. However, such efforts are often in isolation and limited to institution-based criteria.

 published a study after exhaustive and systematic analysis to define HPD. They concluded that the clinical interpretation of HPD appears diverse, with the incidence of HPD varying from 5.9% to 43.1% across studies examined in their meta-analysis. They also highlighted the critical unmet need for establishing uniform and clinically relevant criteria based on currently available evidence to define HPD. One of the most compelling reasons to identify true HPD is the association of patients with HPD with extremely poor prognosis. Several studies reported worse progression-free survival and overall survival in the subgroup analysis of patients with HPD.

 Earlier identification of patients with HPD could lead to quicker adjustment of therapeutic selection to improve the dismal clinical outcomes currently associated with HPD. Because there remains no clear consensus around the definition of HPD at the time of writing this article, we simply define HPD as resulting in the rapid clinical acceleration of tumor growth resulting in shortened patient survival.

With the rapid strides in immune-based treatment options in patients with advanced solid tumors in the past decade, we have seen significant clinical improvement in patient quality of life and quantitative improvement of clinical outcomes. However, increased utilization of ICI therapies has also led to the recognition of new clinical challenges associated with a small but not insignificant number of patients, where failure to distinguish between TPD, PSP, and HPD clearly has an impact on patient lives. It is critical that our research communities start paying more attention to and providing clinical guidance around the following issues:

Recognition of HPD as a critical clinical phenomenon and not just a concept characterized by acceleration of measurable and quantifiable disease by radiologic assessment 

With the reported incidence of HPD being higher compared with PSP, emphasizing the importance of identifying HPD as early as possible, because it can occur within weeks of starting ICI therapy and result in higher mortality 

Establish clear criteria that may facilitate and support conclusive assessment of HPD vs either true PD or PSP, which may include assessment of TGR, TGK, number and increase in metastatic lesions, growth in the size of the target lesions, and additional RECIST-defined criteria

Create a consensus of baseline timing of imaging studies prior to starting ICI treatment as it can impact interpretation of subsequent studies either as a standard of care or symptom directed protocols to make it easier to correlate to pretreatment findings to distinguish between TPD, PSP, and HPD 

Continue research to establish whether HPD is related to specific cancer subtypes or other patient comorbidities, including preexisting conditions

 Identify whether HPD is therapeutic agent specific or class specific (ie, like anti– CTLA, anti–PD-1, or anti–PD-L1 therapies)

Although ICI approaches are now a mainstay in therapy, challenges to optimal benefit, such as PSP, TDP, and HPD, require continued vigilance.

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Advances in the field have also led to the recognition of other clinical challenges, including unforeseen observations and complications associated with choosing the sequencing of appropriate therapeutic interventions as well as the management of drug-related complications.

Differentiating Pseudoprogression From Hyperprogression in Patients Treated With Immunotherapies

Precision Medicine (PM) is “an approach to disease prevention and treatment that seeks to maximize effectiveness by considering individual variability in genes, environment, and lifestyle,” according to the Precision Medicine Initiative (PMI).

 After former President Obama announced the PMI in his State of the Union address on January 20, 2015—“to bring us closer to curing diseases like cancer and diabetes and to give all of us access to the personalized information we need to keep ourselves and our families healthier”—the National Health Institute and other global agencies commenced a group under the PMI called the PMI Cohort Program.

The goal of PM is to advance medical and scientific discoveries to offer more tailored, precise, and accurate health interventions to maximize the health benefits for patients.

 Essential components of PM include the integration of information from several different sources, including genetic and genomic profiles, imaging data, records from wearable health-tracking devices and lifestyle choices, germline data, and pharmacogenomics. The access and application of these data and associated bioinformatics, using computing power and technological expertise to translate PM into personalized health care, are key.

For community practices, using PM will be greatly beneficial to patients and the practice. To maximize these benefits, PM needs to be integrated into the fabric of the community setting. All professionals in a practice will have to be involved in the development of a PM system, including physicians, pharmacists, lab personnel, nurses, and the patients. Although there have been obstacles to implementing diagnostic and screening tests, these can be overcome and will provide more options for patients with cancer.

Next-generation sequencing (NGS), which is rapidly replacing Sanger sequencing, has matured enough as a technology and found its place both in clinical practice and research. In addition, whole exome sequencing (WES) and/or whole genome sequencing (WGS) are becoming part of daily operation for oncologists and hematologists for exploring clinical trials and drug development for malignancies. The cost efficiency of NGS has improved significantly due to technological, scientific, and operational advances. The cost of deciphering the entire human genome has dropped from $10,000 in 2011 to approximately $1000 in 2021.

 Other drivers of PM include more accurate sequencing, a growing number of targeted therapies, and the recognition of biodiversity in the human genome— especially in oncology and rheumatic illnesses.

Even in monetary aspects, the global market for PM is growing rapidly. Market research estimated the 2016 global market at $44 billion in revenue, and this revenue is forecast to more than triple to $140 billion by 2026.

The rapid strides in sequencing techniques, bioinformatics, and PM have not been matched with efforts of implementation in day-to-day practice. Factors like integration into practice guidelines, lack of consensus and standardization between different stakeholders regarding minimum number of mutational analysis, germline studies, platforms for testing, and payer coverage threaten realization of PM.

In addition to factors mentioned above, the biggest challenge for success in PM adoption is lack of diversity in the knowledge of genomics and bioinformatics in research and studies. Minority communities often face discrimination in health care and receive poor medical treatment.

 Outreach to these communities, especially in the research field, has also been characterized by a long history of exploitation, abuse, and marginalization.

 Although hesitancy from ethnic minorities is frequently cited as an excuse for the lack of representative data in PM and clinical trials, real-life observation is somewhat different, with researchers observing that willingness to participate did not differ significantly between ethno-racial groups.

 They also argued that underrepresentation of minority populations is more likely due to the research design of the study or limited accessibility.

Results from genome-wide association studies (GWAS) representing 1.7 million samples conducted in 2009 showed that 96% of participants were of European ancestry. Seven years later, the same GWAS analysis revealed that despite the colossal 35 million samples collected, 81% of participants were still of European ancestry. Clearly, racial and ethnic diversity of the samples still had a long way to go.10 The successful implementation of PM requires the clinical integration of the following (FIGURE 1):

Molecular testing of patients for actionable mutations

Interpretation of molecular profiling results and identification of matched therapies

Identification of patients for clinical trials

The creation of a longitudinal journey to understand pharmacogenomics

Equitable access to genomic and genetic as well as treatment data

With so many testing options, including NGS, WES, WGS, and whole transcriptome sequencing, healthcare providers now face a complex decision: whether to outsource this testing to centralized laboratories, implement it in their own labs, or create a hybrid model bringing part of the testing in house and using tertiary labs with full bioinformatics and sophisticated testing for thousands of genes for support. With the advent of NGS panels, genomic profiling has become leaner, cheaper, and more user friendly. Everything is quicker in house, with much less chance of losing important material or information. One of the best arguments for in-house genomic profiling is the control it affords over the preanalytical parameters, tissue specimen selection, and sample quality.

For many community oncologists, the latter option to create a collaborative model may enhance the uptake of appropriate molecular testing and address an unmet need, as most of the underserved, marginalized population is served by small- to medium-sized community cancer clinics. We must focus on doing those routine tests quickly, cost effectively, and as locally as possible in collaboration with tertiary labs that have additional testing capabilities and bioinformatics.

Additionally, centralized testing in a collaborative model is another very valuable option. When an FDA-approved treatment option is not available based on local minipanel testing results, additional testing with a much larger panel may provide options for clinical trials for new drug development. This testing may also identify germline mutations, such as BRCA1/2 or other homologous repair defects, and identify other family members at risk. This would allow others to implement appropriate clinical interventions to monitor their risk for disease. A bioinformatics platform will enhance assimilation of genomic, pharmacogenomics, and germline data to create a longitudinal journey and ultimately bring health care equity, address disparities, and enhance new drug developments. Benefits of insourcing NGS include the following (FIGURE 2):

In summary, even though the field of PM is still evolving and changing, driver mutation and biomarker-guided therapies have already improved treatment options for thousands of patients with cancer and thousands more are eligible for clinical trials. Because of limitations in access to overall testing, limited uptake of testing—at the most, 25% in non–small cell lung cancer in Caucasians and 14% in ethnic minorities—and skewed data disproportionately representative of Caucasians, the success of PM is not likely to be accomplished unless we explore different ways to approach testing. These include:

Making widespread testing accessible locally;

Improving access to testing for minorities;

Performing additional testing at tertiary centers when an actionable mutation is not identified; and

Adding germline testing (if NGS panel only includes somatic testing)

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The goal of precision medicine is to advance medical and scientific discoveries to offer more tailored, precise, and accurate health interventions to maximize the health benefits for patients.

The Role of In-Office Next Generation Sequencing to Advance Precision Medicine in Community Oncology

The potential for precision medicine to revolutionize care in the development of new treatments has only just begun. Translating these initial successes (eg, targeted therapies in lung cancer) to a larger scale will require a coordinated and sustained national effort and must include careful attention to the broader public health impact. The lack of inclusion of ethnic minorities and socially disadvantaged population subgroups in this resource-intense era of genomic research and development has the troubling potential to further widen existing health disparities. Given the investment of resources and potential impact on health, it is imperative that future research include diverse populations, moving beyond race to take into consideration ancestry, sociocultural environment, and genomic adaptation. This will ensure that scientific advances are impactful for all population groups by harnessing innovations in precision medicine to help reduce and eventually eliminate health disparities.

Rapid strides in the development of omics (proteomics, genomics, etc) have overshadowed the enormous variation represented by individual ethnicity and race. The data collected, gathered, and analyzed by multiple commercial and other agencies to individualize treatment approaches (defined as personalized medicine) in pursuit of improved outcomes have not kept pace with the fundamental human right of equity in health care access, but rather seem to be driven by privilege.


Precision medicine is “an approach to disease treatment and prevention that seeks to maximize effectiveness by taking into account individual variability in genes, environment, and lifestyle.”

 Its potential to revolutionize care in the development of new treatments has only just begun. Precision medicine gives clinicians tools to better understand the complex biological and environmental mechanisms underlying a patient’s health, disease, or condition, and will enable them to predict which treatments will be most effective. Advances in precision medicine have already led to new discoveries and several new treatments that are tailored to an individual’s specific characteristics, such as one’s genetic makeup or the genetic profile of an individual tumor. These innovations are leading to a transformation in cancer treatment. Because of these advances, patients with breast, lung, or colorectal cancers, as well as melanomas and leukemia, now routinely undergo molecular testing as part of their disease evaluation and treatment management. These efforts enable clinicians to select treatments that can improve survival and reduce possible adverse effects.

The goal of precision medicine is to advance medical and scientific discoveries while offering more tailored, precise, and accurate health interventions, thus maximizing health benefits for patients while reducing adverse effects and overall cost of care.

 With such an approach, individual well-being is monitored proactively; that is, precision medicine is predictive, personalized, preventive, and participatory.

 The defining features and goals of precision medicine appear to make it complementary to the scope of health equity defined by the World Health Organization,

 which states that “ideally everyone should have a fair opportunity to provide patients with preventive and therapeutic interventions based on their individual needs (eg, their susceptibility profile to some diseases),” given the overall continuity of the clinical objectives.

A study by Hinco Jasper Gierman, PhD, and colleagues, showed that despite rapid strides in biomarkerdriven targeted therapies in lung cancer, only 22% of all patients with advanced non–small cell lung cancer have their tissues checked for driver mutations with available FDA-approved treatments (FIGURE).

 This finding is in concurrence with the fact that most community cancer clinics provide care to patients in rural locations. These clinics do not have access to sophisticated clinical trials, adding to health care disparities.

With the promises and premises of improving population health, precision medicine also entails the risk of exacerbating health inequalities, particularly between racial and ethnic minority groups.8 Minority communities frequently face discrimination in health care and receive poor medical treatment across the globe.

Outreach to minority communities—especially in the research field—has also been characterized by a long history of exploitation, abuse, and marginalization.

 The relatively lower participation rate of minority groups in health research is not simply a matter of distrust and unwillingness, but extends far beyond these superficial excuses.

In a review of enrollment decisions of more 

than 70,000 individuals for participation 

in health research, Wendler and colleagues 

showed that willingness to participate did 

not differ significantly between ethnoracial 

groups and argued that underrepresentation of 

minority populations is more likely due to the 

research design of the study or to limited accessibility.

 Aside from its cause, the lower participation 

to most genetic databases used for research 

purposes containing data on participants of 

analysis of genome-wide association studies 

(GWAS) representing 1.7 million samples conducted 

Hirangi Mukhi, BS | Authors

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