Abstract
Despite its frequency and prognostic significance, acute kidney injury (AKI) remains poorly stratified across cancer types, limiting opportunities for targeted prevention. To address this gap, we conducted a series of retrospective, real-world matched cohort analyses using the TriNetX global health research network to evaluate early AKI risk across six malignancy populations: acute myeloid leukemia (AML), multiple myeloma (MM), MM with alcohol-related disorders (MM+Alcohol), diffuse large B-cell lymphoma (DLBCL) in diabetics, follicular lymphoma (FL) in diabetics, and chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). To our knowledge, this is among the first multi-cancer matched cohort studies to compare short-term AKI risk across hematologic malignancies using real-world data.
Each comparison used independent 1:1 propensity score–matched cohorts balanced for age, sex, race, and relevant comorbidities including hypertension, diabetes, and chronic kidney disease (where applicable). Patients with end-stage renal disease were excluded. AKI events were defined using ICD-10 codes (N17.x) and assessed beginning one day after treatment initiation, with no fixed end date.
In the AML versus MM comparison (n=3,806 and 5,673), AML patients had significantly higher AKI rates (29.5% vs 20.3%, p<0.001; OR 1.64, 95% CI 1.49–1.81). Among MM patients, those with alcohol-related disorders (n=6,381 per group) showed substantially elevated AKI incidence compared to matched peers without such disorders (35.7% vs 22.7%, p<0.001; OR 1.99, 95% CI 1.85–2.14).
Among diabetic lymphoma patients (n=16,017 per group), DLBCL had higher AKI rates than FL (30.4% vs 25.9%, p<0.001; OR 1.25, 95% CI 1.19–1.32). In a separate comparison of patients without diabetes or CKD, DLBCL (n=9,719) also showed greater AKI risk than CLL/SLL (22.9% vs 20.9%, p=0.001; OR 1.12, 95% CI 1.05–1.20).
AKI risk was highest in AML and MM+Alcohol cohorts, intermediate in DLBCL, and lowest in FL and CLL/SLL. These differences persisted despite matching on known renal risk factors, suggesting contributions from treatment toxicity, tumor biology, or supportive care variability. High-intensity chemotherapy in AML and proteasome inhibition in MM may contribute to AKI through tumor lysis, tubular injury, or intrarenal hypoperfusion. Alcohol-related comorbidity may further compound renal risk via dehydration, hepatic dysfunction, or nutritional depletion. Each matched analysis was conducted independently, and while patient overlap across unmatched source populations cannot be excluded, the likelihood of meaningful duplication is low. Due to reliance on administrative coding, AKI severity and reversibility could not be assessed.
In exploratory analyses, AKI was also associated with increased risk of transfusion and infection within high-risk cohorts, particularly among MM patients with alcohol-related comorbidity. These findings raise the possibility that early AKI may serve as a sentinel event in broader chemotherapy intolerance syndromes. Future work should examine whether a composite renal-heme-toxicity index can better stratify risk or guide supportive interventions. Integrating such indices into prospective trials may help tailor supportive care pathways and improve tolerability of curative-intent regimens.
Given AKI's association with hospitalization, delayed therapy, and mortality, these malignancy-specific differences have important downstream implications. A tumor-specific supportive care strategy—such as early nephrology referral, proactive fluid management, or tailored dosing—may reduce renal complications in high-risk groups such as AML, DLBCL, and MM with alcohol-related disorders. These findings also support embedding AKI risk profiles into electronic order sets, chemotherapy pathways, or risk calculators to guide real-time prevention. Future studies should explore whether this approach improves outcomes, minimizes treatment interruptions, and reduces preventable harm.
