TY - JOUR
T1 - Treatment patterns and outcomes according to cytogenetic risk stratification in patients with multiple myeloma
T2 - a real-world analysis
AU - Atrash, Shebli
AU - Flahavan, Evelyn M.
AU - Xu, Tao
AU - Ma, Esprit
AU - Karve, Sudeep
AU - Hong, Wan Jen
AU - Jirau-Lucca, Gilbert
AU - Nixon, Michael
AU - Ailawadhi, Sikander
N1 - Funding Information:
The de-identified data that support the findings of this study are subject to a license agreement with Flatiron Health; interested researchers should contact DataAccess@flatiron.com to determine licensing terms. Genentech, Inc. (a member of the Roche Group) provided financial support for this manuscript. Third-party medical writing assistance, under the direction of the authors, was provided by Rachel Dobb, PhD, and Andrea Bothwell, BSc, contract writer, of Ashfield MedComms, an Ashfield Health company, funded by F. Hoffmann-La Roche Ltd.
Funding Information:
The de-identified data that support the findings of this study are subject to a license agreement with Flatiron Health; interested researchers should contact DataAccess@flatiron.com to determine licensing terms. Genentech, Inc. (a member of the Roche Group) provided financial support for this manuscript. Third-party medical writing assistance, under the direction of the authors, was provided by Rachel Dobb, PhD, and Andrea Bothwell, BSc, contract writer, of Ashfield MedComms, an Ashfield Health company, funded by F. Hoffmann-La Roche Ltd.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/3
Y1 - 2022/3
N2 - A clearer understanding of the prognostic implications of t(11;14) in multiple myeloma (MM) is needed to inform current and future therapeutic options. We utilized real-world data from a US database to examine treatment patterns and outcomes in patients by t(11;14) status compared with high- and standard-risk subgroups across different lines of therapy (LoT). This retrospective, observational cohort study used de-identified patient-level information from adults with MM and first-line treatment initiation between January 2011 and January 2020, followed until February 2020. The high-risk cohort comprised patients with high-risk genetic abnormalities per mSMART criteria (including those with co-occurring t(11;14)). Among 6138 eligible patients, 6137, 3160, and 1654 received first-, second-, and third-line treatments, respectively. Of 645 patients who had t(11;14), 69.1% had t(11;14) alone, while 30.9% had co-occurring high-risk abnormalities. Altogether, 1624 and 2544 patients were classified as high- and standard-risk, respectively. In the absence of biomarker-driven therapy, treatment patterns remain similar across LoT in high-risk, t(11;14)+, and standard-risk subgroups. Across all LoT, patient outcomes in the high-risk subgroup were less favorable than those in the t(11;14)+ and standard-risk subgroups. Thus, there is an opportunity for novel therapeutics targeted to t(11;14) and other defined subgroups to personalize MM therapy and optimize patient outcomes.
AB - A clearer understanding of the prognostic implications of t(11;14) in multiple myeloma (MM) is needed to inform current and future therapeutic options. We utilized real-world data from a US database to examine treatment patterns and outcomes in patients by t(11;14) status compared with high- and standard-risk subgroups across different lines of therapy (LoT). This retrospective, observational cohort study used de-identified patient-level information from adults with MM and first-line treatment initiation between January 2011 and January 2020, followed until February 2020. The high-risk cohort comprised patients with high-risk genetic abnormalities per mSMART criteria (including those with co-occurring t(11;14)). Among 6138 eligible patients, 6137, 3160, and 1654 received first-, second-, and third-line treatments, respectively. Of 645 patients who had t(11;14), 69.1% had t(11;14) alone, while 30.9% had co-occurring high-risk abnormalities. Altogether, 1624 and 2544 patients were classified as high- and standard-risk, respectively. In the absence of biomarker-driven therapy, treatment patterns remain similar across LoT in high-risk, t(11;14)+, and standard-risk subgroups. Across all LoT, patient outcomes in the high-risk subgroup were less favorable than those in the t(11;14)+ and standard-risk subgroups. Thus, there is an opportunity for novel therapeutics targeted to t(11;14) and other defined subgroups to personalize MM therapy and optimize patient outcomes.
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U2 - 10.1038/s41408-022-00638-0
DO - 10.1038/s41408-022-00638-0
M3 - Article
C2 - 35322025
AN - SCOPUS:85127072101
VL - 12
JO - Blood Cancer Journal
JF - Blood Cancer Journal
SN - 2044-5385
IS - 3
M1 - 46
ER -