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 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).2
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.3 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.4 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.5 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.6,7 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 JCO Precision Oncology by Hsiao et al8 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.9 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.9 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.10,11 There is the need to study more diverse populations using empirical examples and theoretical reasoning.12 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.13,14
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.
Results: 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 P = .03) and were more likely to be either worried about running out of food (18.3% vs 0%; Fisher exact P = .02) or to have run of out of food (15.1% vs 0%; Fisher exact P = .02) in the past 12 months.
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 p53 deletion.
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 p53 deletion. We plan to expand this study from its original scope so that it is implemented across the community practice.
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