Abstract
Background
Although tyrosine kinase inhibitors (TKIs) are the standard first-line treatment for chronic myeloid leukemia (CML), their renal safety profiles need investigation. Herein, we report a case of flumatinib-associated acute kidney injury (AKI). We also conducted a disproportionality analysis to evaluate TKI-related renal risks using pharmacovigilance data.
Methods
This report described the case of a patient with CML who developed AKI during flumatinib treatment. A meta-analysis was subsequently performed to assess the incidence of flumatinib-associated renal adverse events. Adverse event reports for TKIs (imatinib, dasatinib, nilotinib, flumatinib, radotinib, bosutinib, and ponatinib) from 2004 to 2024 were retrieved from the FDA Adverse Event Reporting System (FAERS). Reporting odds ratios (RORs) with corresponding 95% confidence intervals (CIs) were calculated to evaluate the reporting associations of TKIs with AKI or renal-related adverse events.
Results
A 54-year-old woman developed severe AKI requiring dialysis after 5 months of flumatinib treatment, with a kidney biopsy confirming acute tubulointerstitial injury. Her kidney function completely recovered after flumatinib was discontinued and glucocorticoid therapy was initiated and remained stable after the therapeutic transition to imatinib during the 14-month follow-up period. A meta-analysis of 11 cohort studies showed a pooled incidence of flumatinib-related renal adverse events of 7% (95% CI, 4%–10%; I² = 71.0%). Analysis of the FAERS data revealed 117,520 reports of TKI-related adverse events, including 381 cases of AKI (0.32%) and 1,336 renal adverse events (1.14%). Compared with non-TKIs, TKIs were not associated with increased disproportionality signals for AKI (ROR = 0.31; 95% CI 0.28–0.34) or renal adverse events (ROR = 0.48; 95% CI 0.45–0.50). Among TKIs, dasatinib (ROR = 0.55; 95% CI 0.42–0.72) and nilotinib (ROR = 0.46; 95% CI 0.34–0.62) were associated with lower disproportionality signals for AKI, whereas bosutinib and ponatinib did not significantly increase disproportionality compared with imatinib.
Conclusions
TKIs, including flumatinib, may cause AKI; however, FAERS-based disproportionality analysis does not indicate an increased renal safety signal compared to non-TKIs. Among TKIs, dasatinib and nilotinib have lower reporting disproportionality than imatinib does, suggesting a potential therapeutic advantage of their use for patients with kidney diseases.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12882-025-04539-9.
Keywords: Tyrosine kinase inhibitors, Acute kidney injury, Renal adverse events, Case report, Pharmacovigilance study
Introduction
Chronic myeloid leukemia (CML) is a hematologic malignancy characterized by the clonal proliferation of hematopoietic stem cells, which leads to the overproduction of immature blood cells and impaired bone marrow function [1, 2]. The hallmark of CML is the presence of the Philadelphia chromosome, which is the product of a translocation between chromosomes 9 and 22 (t(9:22)), leading to the formation of the BCR-ABL fusion gene. This gene encodes the BCR-ABL fusion protein, which plays a central role in driving the malignant transformation of cells. CML accounts for approximately 15% of all leukemias, with most cases occurring in adults older than 65 years. In the United States, the estimated incidence in 2025 is 9,560 new cases and 1,290 deaths [3]. Globally, the incidence rate is approximately 2 per 100,000 individuals, and the prevalence is expected to exceed 10 million cases by 2040–2050 [4].
Tyrosine kinase inhibitors (TKIs) represent the cornerstone of CML therapy and target BCR-ABL kinase to inhibit downstream signaling pathways that drive proliferation and survival of malignant cells [5]. First- and second-generation BCR-ABL TKIs—including imatinib, dasatinib, bosutinib, and nilotinib—have significantly improved the 10-year survival rate of CML patients, from approximately 20% to 80%–90% over the past two decades [6–12]. Despite their effectiveness, long-term TKI use is associated with adverse effects, including hematologic, gastrointestinal, neurological, and cardiovascular complications. Renal adverse effects, although uncommon (5%–10% of cases), are likely underrepresented in clinical trials and real-world studies [13–15], and the relative renal risk profiles across TKIs remain poorly understood [16, 17].
Flumatinib mesylate, a second-generation TKI approved in China in 2019, offers an additional treatment option for Philadelphia chromosome-positive CML and acute lymphoblastic leukemia [18]. Although renal adverse effects, including acute kidney injury (AKI), have been observed in some patients treated with flumatinib [19], the underlying pathophysiology has not been previously confirmed by renal histopathology. In this study, we report the first biopsy-confirmed case of flumatinib-associated AKI, underscoring the need to evaluate the renal safety profile of BCR-ABL TKIs. To address this issue, we further performed a pharmacovigilance analysis using the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) to evaluate the potential association between various TKIs and the risk of AKI.
Methods
Data sources
In this study, data from FAERS, a publicly accessible pharmacovigilance database maintained by the U.S. FDA, were used to collect spontaneous reports of adverse drug reactions (ADRs). This database contains adverse event reports that the FDA has received from manufacturers as required by regulations and reports received directly from consumers and health care professionals since January 2004. Although other global databases, such as WHO-VigiBase and EudraVigilance, are valuable resources for pharmacovigilance, they were not accessed in this study because of institutional constraints.
Data processing
We extracted all ADR reports from the FAERS database from the first quarter of 2004 through the fourth quarter of 2024. These reports are coded according to the Preferred Term (PT) in the Medical Dictionary for Regulatory Activities (MedDRA, version 26.0), which categorizes terms into a five-level hierarchy. The PT provides a unique descriptor for each medical concept, facilitating consistent classification and analysis.
To identify cases of AKI, we used the MedDRA PT ‘Acute kidney injury’ as recommended by previous studies [20, 21]. Other related terms, such as ‘kidney dysfunction’ were excluded because they do not guarantee the presence of AKI. A total of 35 PTs for renal adverse effects in the MedDRA were extracted for extended analysis (including acute kidney injury, acute phosphate nephropathy, anuria, azotemia, continuous hemodiafiltration, dialysis, hemodialysis, toxic nephropathy, oliguria, peritoneal dialysis, prerenal failure, renal failure, renal impairment, kidney dysfunction, subacute kidney injury, increased blood creatinine, abnormal blood urea, decreased glomerular filtration rate, proteinuria, renal tubular injury, allergic nephritis, tubulointerstitial nephritis, renal tubular necrosis, renal tubular dysfunction, renal tubular disorder, renal tubular atrophy, renal tubular acidosis, renal replacement therapy, renal necrosis, renal ischemia, renal injury, abnormal renal function test, renal disorder, renal atrophy, end-stage renal disease, and chronic kidney disease).
We ensured the reliability of the dataset by implementing FDA-recommended deduplication methods. Reports with the same CASEID (number used to identify FAERS cases) in the DEMO (demographics) table were retained on the basis of the highest FDA_DT (date the case was received by the FDA) value. Reports with the same CASEID and FDA_DT were retained on the basis of the highest PRIMARYID (unique number used to identify the FAERS report) value. Reports with the same values in the CASEID, PRIMARYID, ADRs, Drug, and Indication fields were identified as duplicate reports, ensuring meticulous data processing.
Finally, after deduplication according to the above principles, the 28,629,064 ADRs caused by the suspected drug were imported into PostSQL 12.0 for secondary analysis. We subsequently extracted the data of the relevant TKI drugs on the basis of the drug names in the FDA public database of approved drugs and adverse reactions and fuzzily matched the trade names and generic names of the above drugs in the “drugname” field through PostSQL and screened out all reports on the suspected drug as TKI: IMATINIB (“GLIVEC”), DASATINIB (“SPRYCEL”), NILOTINIB (“TASIGNA”), FLUMATINIB, RADOTINIB (“SUPECT)”, BOSUTINIB (“BOSULIF”), ASCIMINIB (“SCEMBLIX”), and PONATINIB (“ICLUSING”).
Data analysis
Disproportionality analysis was performed by using the ratio of reported ratios (ROR) and 95% confidence intervals (CI). We calculated the ROR and its 95% CI using the following formula to assess the potential association between AKI and TKIs [22].
 |
 |
where a = the number of reports of TKIs associated with an AKI adverse event,
b = the number of reports of all other drugs associated with an AKI adverse event.
c = the number of reports of TKIs associated with all other adverse events, and.
d = the number of reports of all other drugs associated with all other adverse events.
ADRs with at least three reports and an ROR lower limit exceeding one were considered to be significantly associated with an increased risk of AKI or renal adverse events.
Results
Clinical case
A 54-year-old woman was admitted with a two-week history of persistent vomiting. Her medical history included a CML diagnosis five months earlier and a ten-year history of diabetes mellitus. At the time of CML diagnosis, routine outpatient tests revealed a white blood cell (WBC) count of 50.5 × 109/L (70.4% neutrophils), a hemoglobin concentration of 106 g/L, and a platelet count of 1101 × 109/L. Bone marrow cytology confirmed CML, and chromosomal analysis revealed a Philadelphia chromosome translocation [46, XX, t(9; 22)(q34; q11)]. The BCR-ABL p210 copy number was 1,336,758. The patient was started on flumatinib 600 mg once daily. After 14 weeks of treatment, the WBC count was 9.7 × 109/L, the neutrophil count was 75.2%, the hemoglobin concentration was 105 g/L, the platelet count was 318 × 109/L, and the serum creatinine concentration was 77 µmol/L. Bone marrow cytology indicated a continued chronic phase of CML, and the BCR-ABL p210 copy number had decreased to 303.
Two weeks prior to admission, the patient developed persistent nausea and vomiting without oliguria. One day before admission, laboratory testing revealed a markedly elevated serum creatinine concentration of 516 µmol/L, necessitating urgent hospitalization (Fig. 1). On admission, laboratory investigations revealed a blood urea nitrogen concentration of 28 mmol/L, a creatinine concentration of 592 µmol/L, a sodium concentration of 132 mmol/L, a magnesium concentration of 0.65 mmol/L, and a potassium concentration of 3.38 mmol/L. Serum immunoglobulin G4 was negative. Urine output was 1700 mL/day, with proteinuria at a concentration of 0.81 g/day. Creatinine clearance was calculated at 5.2 mL/min, and the fractional excretion rates of sodium, potassium, and magnesium were 14.9%, 88.5%, and 41.4%, respectively.
Fig. 1.
Serum creatinine concentrations over time in a patient with flumatinib-associated acute kidney injury
Given the deterioration in renal function, flumatinib was discontinued, and supportive management was initiated. After five days of conservative treatment, the serum creatinine concentration modestly decreased to 524 µmol/L, while the blood urea nitrogen concentration decreased to 23 mmol/L. The patient subsequently underwent a single session of hemodialysis before kidney biopsy.
Renal histopathology revealed global glomerulosclerosis in 5 of 15 glomeruli, focal tubular necrosis, interstitial inflammation with fibrosis, and arteriolar wall thickening (Fig. 2). These findings were consistent with acute tubulointerstitial injury, prompting the initiation of methylprednisolone at a dosage of 40 mg daily. After eight days of corticosteroid therapy, the serum creatinine concentration decreased to 98 µmol/L, and renal function stabilized. At discharge, the serum creatinine concentration had decreased to 65 µmol/L, and the electrolyte concentration was within normal limits.
Fig. 2.
Kidney pathology of a patient with flumatinib-associated acute kidney injury. (A) Renal tissue edema with little inflammatory cell infiltration (HE, 20x); (B) Necrotic and detached renal tubular epithelial cells with exposed basement membranes (HE, 400x); (C) Normal glomeruli and tubular interstitial edema (PASM, 100x); (D) Cytoplasmic extravasation and nuclear fragmentation of renal tubular epithelial cells (EM, 5000x)
During the subsequent months, the patient’s serum creatinine concentration remained stable at 60–65 µmol/L, and the prednisone dosage was tapered. Nine months after discharge, she was transitioned to 400 mg of imatinib mesylate (Glivec) daily, and her renal function continued to remain stable (serum creatinine concentration of 56–70 µmol/L).
This case raises the following question: what is the incidence of renal adverse effects with flumatinib? We therefore conducted a concise meta-analysis to answer this question. This case also prompted further evaluation of the relative renal safety profile of BCR-ABL TKIs. We thus conducted a pharmacovigilance analysis using the FAERS database to assess the disproportionality of reported AKI and renal adverse events across different TKIs.
Incidence of renal adverse effects of flumatinib
To estimate the incidence of renal adverse events associated with flumatinib, we performed a systematic search in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, and ultimately included 11 studies (Supplementary Fig. 1). All were cohort studies conducted in China, of which three were published in English and eight in Chinese. Baseline characteristics of included studies were summarized in Supplementary Table 1. In total, 932 patients with CML were analyzed, with a median follow-up duration of 12 months (range, 3–24 months). The pooled incidence of renal adverse events was 7% (95% CI, 4%–10%; I2 = 71.0%) over the follow-up period (Fig. 3). A funnel plot showed no obvious evidence of publication bias (Supplementary Fig. 2), which was further supported by Egger’s test. Quality assessment using the Newcastle–Ottawa Scale indicated that most cohort studies were of moderate quality (Supplementary Table 2).
Fig. 3.
Forest plot of the incidence of renal adverse effects associated with flumatinib
FAERS database study
AKI and renal adverse effects in the FAERS database study
A total of 117,520 TKI-related ADR reports were identified in the FAERS database (Fig. 4), including 381 (0.32%) reports of AKI and 1,336 (1.14%) reports of renal adverse events (Table 1). The reported odds of AKI (ROR = 0.31, 95% CI = 0.28–0.35) or renal adverse effects (ROR = 0.48; 95% CI 0.45–0.51) associated with TKIs were not significantly greater than those associated with non-TKI medications (Table 1).
Fig. 4.
Study flow of the FAERS study. AKI, acute kidney injury; AE: adverse effect; ADR: adverse drug reaction
Table 1.
FAERS database study: TKI-related AKI and renal adverse events
| Generation | Drugs | Total ADRs | AKI, n (%) | ROR for AKI (95% CI) | Renal adverse effects, n (%) | ROR for renal adverse effects (95% CI) |
|---|---|---|---|---|---|---|
| 1 | Imatinib | 38,688 | 163 (0.42) | 0.407 (0.349–0.475) | 553 (1.43) | 0.605 (0.556–0.658) |
| 2 | Dasatinib | 34,225 | 80 (0.23) | 0.225 (0.181–0.281) | 279 (0.82) | 0.314 (0.275–0.360) |
| Nilotinib | 28,339 | 55 (0.19) | 0.187 (0.144–0.244) | 212 (0.75) | 0.329 (0.289–0.376) | |
| Flumatinib | 16 | 0 (0) | - | 0 (0) | - | |
| Radotinib | 4 | 0 (0) | - | 0 (0) | - | |
| Bosutinib | 8294 | 46 (0.55) | 0.537 (0.402–0.717) | 181 (2.18) | 0.931 (0.804–1.079) | |
| Asciminib | 1724 | 2 (0.12) | - | 50 (2.90) | 1.247 (0.941–1.652) | |
| 3 | Ponatinib | 6230 | 35 (0.56) | 0.544 (0.391–0.758) | 61 (0.98) | 0.413 (0.321–0.531) |
| Total TKI | 117,520 | 381 (0.32) | 0.312 (0.282–0.345) | 1336 (1.14) | 0.479 (0.454–0.505) | |
| All drugs | 28,629,064 | 294,389 (1.03) | - | 669,855 (2.34) | - |
Descriptive analysis of patients with TKI-associated AKI and renal adverse effects
Among the TKIs associated with AKI, the most frequently implicated agents were imatinib (42.8%), dasatinib (21.0%), nilotinib (14.4%), and bosutinib (12.1%). The affected population was predominantly male, with a median age of 63 years. The median time to the onset of AKI was 69.5 days (IQR 8.2–486). TKIs were the primary suspected drug in 62.7% of the patients with AKI. Reported indications included CML (42.2%), acute lymphoblastic leukemia (14.2%), unknown (10.2%), and gastrointestinal stromal tumor (6.0%). The rates of hospitalization and death among patients were 40.2% and 12.3%, respectively (Table 2).
Table 2.
Characteristics of AKI and renal adverse effects associated with TKI drugs
| AKI (N = 381) | Renal adverse effects (N = 1336) | |
|---|---|---|
| Drugs, n (%) | ||
| Imatinib | 163 (42.8) | 553 (41.4) |
| Dasatinib | 80 (21.0) | 279 (20.9) |
| Nilotinib | 55 (14.4) | 212 (15.9) |
| Bosutinib | 46 (12.1) | 181 (13.5) |
| Asciminib | 2 (0.5) | 50 (3.7) |
| Ponatinib | 35 (9.2) | 61 (4.6) |
| Drug role, n (%) | ||
| Primary suspect | 239 (62.7) | 1019 (76.3) |
| Secondary suspect | 142 (37.3) | 317 (23.7) |
| Sex, n (%) | ||
| Male | 212 (55.6) | 720 (53.9) |
| Female | 134 (35.2) | 478 (35.8) |
| Unknown | 35 (9.2) | 138 (10.3) |
| Median age, year | 63 | 66 |
| Age groups, n (%) | ||
| < 18 | 36 (9.4) | 64 (4.8) |
| 18–64 | 118 (31.0) | 352 (26.3) |
| > 64 | 137 (36.0) | 491 (36.8) |
| Unknown | 90 (23.6) | 429 (32.1) |
| Reporting Countries (Top 8), n (%) | ||
| United States 131 (34.4) | United States 473 (35.4) | |
| France 47 (12.3) | Japan 129 (9.7) | |
| Japan 28 (7.3) | France 100 (7.5) | |
| Italy 21 (5.5) | Australia 56 (4.2) | |
| Australia 18 (4.7) | United Kingdom 40 (3.0) | |
| Canada 17 (4.5) | Canada 38 (2.8) | |
| United Kingdom 14 (3.7) | Germany 36 (2.7) | |
| Germany 13 (3.4) | Italy 36 (2.7) | |
| Indications, n (%) | ||
| Chronic myeloid leukemia | 161 (42.2) | 688 (51.5) |
| Acute lymphoblastic leukemia | 54 (14.2) | 81 (6.1) |
| Gastrointestinal stromal tumors | 23 (6.0) | 70 (5.2) |
| Unknown | 39 (10.2) | 168 (12.6) |
| Not available | 23 (6.0) | 122 (9.1) |
| Outcomes, n (%) | ||
| Death | 47 (12.3) | 147 (11.0) |
| Life-Threatening | 19 (5.0) | 30 (2.2) |
| Hospitalization | 153 (40.2) | 357 (26.7) |
| Required Intervention to Prevent Permanent Impairment/Damage | 0 (0) | 3 (0.2) |
| Disability | 2 (0.5) | 2 (0.1) |
| Other Serious (Important Medical Event) | 157 (41.2) | 670 (50.1) |
| Not available | 3 (0.8) | 125 (9.4) |
| Time of occurrence (day) | 69.5 (8.2, 486) | 61.5 (15.0, 365) |
In terms of renal adverse events, the distributions of the implicated agents were similar: imatinib (41.4%), dasatinib (20.9%), nilotinib (15.9%), and bosutinib (13.6%). The median patient age was 66 years, and the median time to event onset was 61.5 days (IQR 15.0–365). TKIs were the primary suspected causative agent of AKI in 76.2% of the patients. The most common indication was CML (51.5%), followed by acute lymphoblastic leukemia (6.1%) and gastrointestinal stromal tumors (5.2%). Hospitalization and death occurred in 26.7% and 11.0% of the patients, respectively (Table 2).
Comparative disproportionality of AKI across TKIs
Comparative disproportionality analyses are shown in Fig. 5. Dasatinib demonstrated significantly lower reporting disproportionality for both AKI (ROR = 0.55; 95% CI 0.42–0.72) and renal adverse effects (ROR = 0.57; 95% CI 0.49–0.66) than imatinib did. Nilotinib also had lower disproportionality for AKI (ROR = 0.46; 95% CI 0.34–0.62) and renal adverse effects (ROR = 0.52; 95% CI 0.44–0.61). Bosutinib did not increase the disproportionality of AKI (ROR = 1.32, 95% CI 0.95–1.83) but did increase the disproportionality of renal adverse events (ROR = 1.54, 95% CI 1.30–1.82). Ponatinib was not associated with increased reporting of AKI (ROR = 1.34, 95% CI 0.93–1.93) but was associated with reduced disproportionality for renal adverse effects (ROR = 0.68, 95% CI 0.52–0.89).
Fig. 5.
Disproportionality signals of acute kidney injury and renal adverse events reported among TKIs in the FAERS database. TKI: tyrosine kinase inhibitors
Stratified analysis by age (≥ 65 vs. < 65 years), sex, and indication (CML vs. non-CML) revealed generally consistent results (Fig. 6). Notably, compared with imatinib, dasatinib and nilotinib resulted in lower RORs for AKI and renal adverse events in patients aged ≥ 65 years and those with non-CML indications. In contrast, bosutinib was disproportionally more common than imatinib among patients receiving TKIs for CML.
Fig. 6.
Stratification analysis of the disproportionality signals of acute kidney injury and renal adverse events associated with BCR-ABL TKIs. Reporting odds ratios (RORs) and 95% confidence intervals (CIs) for AKI and renal adverse events were calculated across subgroups defined by age (≥ 65 vs. < 65 years), sex (male vs. female), and indication (CML vs. non-CML). Dasatinib and nilotinib consistently demonstrated lower disproportionality signals across most subgroups than imatinib did, whereas bosutinib resulted in elevated RORs, primarily among patients with CML
Discussion
This study presents the first biopsy-confirmed case of flumatinib-associated acute tubulointerstitial injury. Renal function improved following corticosteroid therapy and remained stable after treatment was switched to imatinib. This observation prompted a pharmacovigilance analysis using the FAERS database to evaluate the reporting disproportionality of AKI and renal adverse events across various TKIs. Overall, compared with non-TKIs, the reporting signal for AKI or renal adverse effects associated with TKIs was not increased for TKIs. However, the interdrug variability was substantial. Notably, the reporting rates for AKI due to dasatinib and nilotinib were significantly lower than those for imatinib, which supports that the renal safety profile of these drugs are more favorable for patients with preexisting kidney conditions.
Compared with imatinib, flumatinib, a novel second-generation TKI developed in China [18, 23], incorporates three key structural modifications [24]: substitution of a benzene ring with a pyridine ring, addition of trifluoromethyl groups, and preservation of the amide bond orientation. These modifications increase BCR-ABL kinase binding affinity and selectivity [25]. Although flumatinib is approved in China, biopsy-confirmed cases of flumatinib-induced AKI have not previously been reported, despite their clinical incidence of 6.7% [19]. Our case confirmed that flumatinib-induced AKI manifests as acute tubulointerstitial injury accompanied by electrolyte abnormalities, contributing novel pathological evidence to the literature on TKI-associated nephrotoxicity. We also calculated a pooled renal adverse effects incidence of 7% via a meta-analysis, despite the follow-up in these studies being relatively short.
The exact pathophysiological mechanisms underlying TKI-associated AKI remain incompletely understood [26]. One plausible mechanism involves the inhibition of platelet-derived growth factor receptors and stem cell factor receptors, which are highly expressed on podocytes and tubular epithelial cells and are essential for cell survival [26, 27]. By blocking tyrosine kinase signaling, TKIs may disrupt normal physiological processes within these cells, leading to nephrotoxicity and glomerulosclerosis through oxidative stress, inflammation, and apoptosis [18, 28, 29]. Moreover, imatinib has stronger selectivity for platelet-derived growth factor receptors inhibition than for C-KIT or BCR-ABL, a profile more pronounced than that of nilotinib or dasatinib, which may explain its greater nephrotoxicity [30]. In our patient, renal function failed to recover within 5 days after cessation of flumatinib but improved rapidly following corticosteroid initiation, suggesting an immune-mediated process. The median time to AKI onset (69 days) further supports the possibility of delayed hypersensitivity. Further research is needed to clarify the underlying mechanisms involved.
The incidence of TKI-related AKI remains a clinical concern. Prior studies report AKI rates of 4%–7% in patients receiving imatinib [10]. A longitudinal study of 105 CML patients receiving imatinib revealed that 7% developed AKI and 12% experienced chronic renal failure [31]. A real-world study in Africa [32] revealed nephrotoxicity in 13.1% of patients on BCR-ABL TKIs, including AKI in 1.5% of patients, which is lower than the 4%–7% rate reported in other studies (Yilmaz et al.: 4% [28], Marcolino et al.: 7% [31]). In our FAERS analysis, AKI and renal adverse events accounted for 0.32% and 1.14% of all TKI-related ADRs, respectively, suggesting a complementary perspective. Notably, compared with non-TKIs, TKIs were not associated with elevated reporting signals for AKI, suggesting that AKI and renal adverse events may be incidental (e.g., anaphylactic reactions) rather than directly caused by nephrotoxic drugs, where a clear dose‒response relationship is expected.
Comparative data on renal toxicity across TKIs remain limited. Yilmaz et al. reported AKI rates of 6%, 1%, and 2% for imatinib, dasatinib, and nilotinib, respectively, in 468 patients [28]. Our findings align with expert opinion [16] and signal data [26], indicating that dasatinib and nilotinib have more favorable renal safety signals than imatinib. Dasatinib, which is primarily metabolized in the liver by cytochrome P450 3A4 and has limited renal excretion, is associated with a low incidence of acute renal failure (< 1%) [33]. Given its minimal renal clearance, nilotinib is less likely to increase creatinine levels than imatinib is (5% vs. 13% [9]). In contrast, bosutinib and ponatinib may carry increased renal risks [26]. A phase I/II study of second-line bosutinib for chronic-phase CML reported a 21% incidence of renal adverse events over five years [34], whereas a study comparing bosutinib with imatinib in patients with newly diagnosed chronic-phase CML indicated an incidence of 10.4% [35]. Our FAERS study also showed that the signal for renal adverse effects was greater for bosutinib than imatinib. Although the underlying mechanisms remain unclear, this difference may be associated with a greater frequency of bosutinib-associated diarrhea (75–87%), which may lead to fluid loss and urinary concentration, thereby increasing the risk of renal adverse events [34, 35]. Ponatinib, a third-generation TKI, inhibits vascular endothelial growth factor receptors, which may impair glomerular filtration and promote hypertension-induced renal damage (AKI: 2% vs. 0% with imatinib [36]). However, the AKI signals for bosutinib and ponatinib identified in this study were not greater than that for imatinib in the total population, diverging from the findings of the WHO pharmacovigilance study [26]. This discrepancy underscores the need for additional real-world evidence to clarify comparative AKI risk among TKIs.
Management of TKI-associated AKI typically involves immediate cessation of the offending drug. In selected cases, such as AKI related to tumor lysis syndrome, temporary continuation may be considered. However, switching to an alternative TKI is generally suggested for patients with persistent AKI or biopsy-confirmed acute tubulointerstitial injury [37]. Dose reduction of the same TKI is not advised because it may fail to halt disease progression [25]. In our patient, renal function remained stable following the transition to imatinib, supporting the feasibility and safety of switching TKIs in patients who experience renal complications.
This study is the first to report biopsy-confirmed flumatinib-induced AKI with a pharmacovigilance analysis of TKI-associated renal adverse events using the FAERS database. Nevertheless, several limitations should be acknowledged. First, the FAERS database includes primarily U.S.-based reports, and differences in drug availability, clinical practice, and population demographics may limit its generalizability to other regions, including China. Second, pharmacovigilance analyses capture associations but not causality, and other factors (demographics, comorbidities, drug exposure duration) may confound these results. Disproportionality measures such as the ROR reflect reporting patterns, not incidence or risk, and are influenced by underreporting, lack of denominator data, variable diagnostic thresholds, and incomplete documentation. Third, missing information on key covariates, including drug dose, comorbidities, and baseline renal function, limits our ability to confound our suggestive results. Finally, the extremely limited case volume for flumatinib in FAERS prevented meaningful drug-specific signal detection for this agent. The lack of a signal of flumatinib may reflect underreporting rather than true safety.
In conclusion, TKIs, including flumatinib, may cause AKI. However, disproportionality analysis based on FAERS data does not indicate an increased renal safety signal compared with non-TKIs, and the absence of a signal for flumatinib likely reflects underreporting rather than true safety. Among TKIs, the reporting rates of renal events are lower for dasatinib and nilotinib than for imatinib, suggesting a potential therapeutic advantage of their use for patients with kidney disease. Prospective mechanistic and population-based studies are warranted to validate these observations and inform personalized TKI selection.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
Not applicable.
Abbreviations
- CML
Chronic myeloid leukemia
- TKIs
Tyrosine kinase inhibitors
- ADR
Adverse drug reaction
- AKI
Acute kidney injury
- FAERS
FDA adverse event reporting system
- FDA
U.S. food and drug administration
- MedDRA
Medical dictionary for regulatory activities
- PT
Preferred term
- ROR
Reporting odds ratio
- CI
Confidence interval
- WBC
White blood cell
- PS
Primary suspect (drug)
Author contributions
SYN, DLL, and WBY contributed to the study’s conception, design, statistical analysis, and manuscript drafting. HYF, and WBY conduct a systematic review. ZJF, MHJ, ZM, HZM, HYF, and WBY were involved in clinical diagnosis, data acquisition, and manuscript review for important intellectual content. All the authors provided approval for the final version to be published and agreed to be accountable for all the aspects of the work.
Funding
This work is funded by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions (CN), Chunhui Project Foundation of the Education Department of China Grant (No. HZKY20220176), and Jiangsu Province Hospital Clinical Capacity Enhancement Project (JSPH-MC-2022-18). The funders played no role in the study design; collection, analysis, or interpretation of the data; writing of the report; or any restrictions regarding the submission of the report for publication.
Data availability
The article’s data will be shared upon reasonable request by the corresponding author.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the First Affiliated Hospital Ethics Committee of Nanjing Medical University. Individual consent in the pharmacovigilance study was not needed because the data were anonymized.
Consent for publication
Written informed consent was obtained from the patient to publish this case report.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Yanni Shi and Lingling Deng are the co-first authors of this article.
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