(T-069) Assessment of Disease Similarity among Different Racial and/or Ethnic Groups in Oncology: ABC Framework

Eun Kyoung Chung, Department of Pharmacy, College of Pharmacy, Kyung Hee University – Pharm.D., Ph.D, Kyung Hee University, Seoul, Republic of Korea; Dong Hyun Kim, Department of Regulatory Science, College of Pharmacy, Kyung Hee University – Pharm.D., Kyung Hee University, Seoul, Republic of Korea

Objectives: We suggest a quantitative framework in oncology to assess disease similarity across different racial and ethnic groups. The aim of this framework was identifying variabilities in disease progression and/or treatment responses among races/ethnicities. Based on this framework, our objective was to establish a regulatory algorithm for determining the need for additional studies to evaluate the effects of racial and/or ethnic diversities on the pharmacokinetics/pharmacodynamics of drugs upon approval.

Methods: We evaluated prostate, breast, and liver cancer based on the prevalence of specific cancer types. Disease similarity was evaluated by reviewing the similarities and differences in pathophysiology, treatment responses, and clinical management approaches among different populations based on literature. The differences in disease progression or response to intervention were quantified or qualified. Extrinsic factors(e.g., environment, medical practices) and intrinsic factors(e.g., genetics, physiology) contributing to ethnic differences in cancer prognosis and treatment response were reviewed. Evidence of disparities was assessed by the “Availability of Biomarkers and Clinical evidence(ABC)” criteria for quantifying inter-racial and/or inter-ethnic differences. The strength of evidence was graded from A(highest) to C(lowest) with A rating granted to confirmative large clinical studies and C grade to small epidemiological association studies for genetic/ethnic differences.

Results: Based on our ABC criteria, disease similarity was evaluated as the following spectrum structure; different, dissimilar, similar, and same. Prostate cancer was evaluated as 'different' due to a higher frequency of genetic mutations, especially in African American/Black(AA/B) patients, as suggested by a retrospective study. This difference was considered as clinical and biomarker-based evidence for racial and/or ethnic differences. Breast cancer was categorized as 'dissimilar', exhibiting intrinsic ethnic differences, especially in Asian and Black patients, with evidence supported by a large cohort study. This racial difference in disease progression was reproduced in clinical studies, but not in biomarker-based studies. Liver cancer was suggested to be 'dissimilar' in terms of genetic mutations, especially in AA/B, supported in a large-scale gene-level copy number study. Additionally, an epidemiologic study supported differences extrinsic factors. These differences in liver cancer were interpreted as clinical evidence; however, biomarkers for these differences were not identified yet.

Conclusions: The ABC algorithm could be successfully applied to evaluate disease similarity in different racial and/or ethnic groups. Based on the disease similarity assessment results, the need for additional studies(i.e., possible extrapolation or new clinical trials in specific racial/ethnic groups) may be determined. Future studies may be needed outside the scope of oncology.

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