Disparities in multiple myeloma: A global perspective on drug toxicity trends.

person Majid Jaberi-Douraki DATA Consortium, Computational Comparative Medicine, Department of Mathematics, Kansas State University–Olathe, Olathe, KS info_outline Majid Jaberi-Douraki, Xuan Xu, Beth Faiman, Gerald Wyckoff, Jim Riviere, Jack Khouri, Sandra Ann Mazzoni, Remya Ampadi Ramachandran, Nuwan Millagaha Gadara, Mobina Golmohammadi, Louis Williams, Christy Joy Samaras, Jason Neil Valent, Faiz Anwer, Shahzad Raza

Authors person Majid Jaberi-Douraki DATA Consortium, Computational Comparative Medicine, Department of Mathematics, Kansas State University–Olathe, Olathe, KS info_outline Majid Jaberi-Douraki, Xuan Xu, Beth Faiman, Gerald Wyckoff, Jim Riviere, Jack Khouri, Sandra Ann Mazzoni, Remya Ampadi Ramachandran, Nuwan Millagaha Gadara, Mobina Golmohammadi, Louis Williams, Christy Joy Samaras, Jason Neil Valent, Faiz Anwer, Shahzad Raza Organizations DATA Consortium, Computational Comparative Medicine, Department of Mathematics, Kansas State University–Olathe, Olathe, KS, Kansas State University–Olathe, Olathe, KS, Cleveland Clinic, Taussig Cancer Institute, Cleveland, OH, University of Missouri Kansas City, Kansas City, MO, Kansas State University, Olathe, KS, Cleveland Clinic Taussig Cancer Center, Cleveland, OH, Taussig Cancer Center, Cleveland Clinic, Ohio, OH, Cleveland Clinic Taussig Cancer Instititute, Cleveland, OH, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, Myeloma Program, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH Abstract Disclosures Research Funding No funding received None. Background: The FDA Adverse Event Reporting System (FAERS) is one of the largest pharmacovigilance databases containing information on adverse events (AEs) received from manufacturers, consumers and healthcare professionals. The purpose of this study is to evaluate the global disparities in multiple myeloma (MM) through data mining of FAERS. Methods: We examined AEs associated with FDA-approved MM drugs from 2003-2022 from FAERS and the Medical Dictionary for Regulatory Activities. Patient data were then stratified based on age, sex (F/M) and 6 geographical regions. We evaluated the reporting odds ratio (ROR) combined with a 95% confidence interval for the elevated incidence of AEs. Results: The data curation provided 381,378 patients with information from North America (NA), Europe (EU), Asia (AS), Africa (AF), Oceania (OC) and Latin America & the Caribbean (LA), merged from 129 countries and 27 phenotypic systems and organs categories when the number of AEs happened more than 0.1% of the total. Cardiotoxicities (n=23160) and vascular toxicities (n=26716) were seen more in NA (M) (ROR=1.16±0.02 and EU (M) (ROR=1.11± 0.03) compared to the rest of the World. Nephrotoxicity (n=17486) was reported more in AF (M) (ROR=2.92±0.41) compared to AS (M) (ROR≥1.17± 0.12), EU (M) (ROR≥1.34± 0.13) and NA (M) (ROR=1.09± 0.03). Peripheral neuropathies (n=14786) were frequent among EU (F) (ROR=1.09±0.07) and OC (M) (ROR=1.08± 0.04). Mortality was higher among AS and EU (ROR≥2.15± 0.93) compared to NA and OC. There were 18,222 secondary neoplasms in FAERS. Skin neoplasms (n=4650) more frequently occurred in OC and EU (ROR≥1.70 ±0.16). Breast neoplasms (n=694) were the highest in EU (F) (ROR=4.01+0.63) and lowest in OC (F) (ROR<1). Gastrointestinal neoplasms (n=1564) were more common among AS, EU and OC (M) with (ROR≥2.23±0.47). Lymphomas (n=542) were predominant in AS(M) (ROR=2.21±0.98) and OC (M) (ROR=3.35±2.23). Leukemias (n=3896) cases were significantly higher in EU (M) (ROR=4.08 ± 0.40) and EU (F) (3.11 ± 0.26) . Respiratory tract and mediastinal neoplasms (n=796) were more common in AS, EU and OC(M) where ROR≥1.36±0.33. More phenotypic characterization are tabulated below. Conclusions: FAERS can be used to assess cancer disparity from a global perspective. Our results indicates that certain AEs are influenced by gender and geographical location. These disparities in MM AEs may be the result of factors such as genetics, dosing/regimen, comorbidities, age and sex. These variables must be investigated for improved patient care, strategies for AE reduction, mortality reduction and optimal allocation of healthcare resources. Phenotypic Characterization Sex NA (n=308177) EU (n=40761) AS (n=16467) AF (n=363) OC (n=2166) LA (n=3919) Age F 70 69 71 59.5 68 67 M 69 68 69 60 68 65 Reproductive neoplasms F 2.1±1.2 4.95±2.5 4.2±1.6 Data not available 1.34±1.1 1.69±1.2 Prostate neoplasms M 2.11±0.98 4.39±0.65 1.25±0.39 2.80±2.40 3.53±0.49 1.35±0.84