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Development and validation of a model to predict acute kidney injury following high-dose methotrexate in patients with lymphoma.
- Source :
-
Pharmacotherapy [Pharmacotherapy] 2024 Jan; Vol. 44 (1), pp. 4-12. Date of Electronic Publication: 2023 Nov 14. - Publication Year :
- 2024
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Abstract
- Study Objective: To develop and validate a model for predicting acute kidney injury (AKI) after high-dose methotrexate (HDMTX) exposure.<br />Design: Retrospective analysis.<br />Setting: Multisite integrated health system throughout Minnesota and Wisconsin.<br />Patients: Adult patients with lymphoma who received HDMTX as a 4-h infusion.<br />Measurements and Main Results: LASSO methodology was used to identify factors available at the outset of therapy that predicted incident AKI within 7 days following HDMTX. The model was then validated in an independent cohort. The incidence of AKI within 7 days following HDMTX was 21.6% (95% confidence interval (CI) 18.4%-24.8%) in the derivation cohort (435 unique patients who received a total of 1642 doses of HDMTX) and 15.6% (95% CI 5.3%-24.8%) in the validation cohort (55 unique patients who received a total of 247 doses of HDMTX). Factors significantly associated with AKI after HDMTX in the multivariable model included age ≥ 55 years, male sex, and lower HDMTX dose number. Other factors that were not found to be significantly associated with AKI on multivariable analysis, but were included in the final model, were body surface area, Charlson Comorbidity Index, and estimated glomerular filtration rate. The c-statistic of the model was 0.72 (95% CI 0.69-0.75) in the derivation cohort and 0.72 (95% CI 0.60-0.84) in the validation cohort.<br />Conclusion: This model utilizing identified sociodemographic and clinical factors is predictive of AKI following HDMTX administration in adult patients with lymphoma.<br /> (© 2023 Pharmacotherapy Publications, Inc.)
Details
- Language :
- English
- ISSN :
- 1875-9114
- Volume :
- 44
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Pharmacotherapy
- Publication Type :
- Academic Journal
- Accession number :
- 37926860
- Full Text :
- https://doi.org/10.1002/phar.2889