Biomarkers of Renal Health in Patients (pts) Treated with Fedratinib in the FREEDOM and FREEDOM2 Trials
Bibliographic record
Abstract
Introduction: Fedratinib (FEDR) is a Janus kinase 2 inhibitor shown to improve spleen size and symptoms for treatment-naive and post-ruxolitinib pts with myelofibrosis (MF). Some pts with MF treated with FEDR have elevated serum creatinine (SCr), an indicator of renal toxicity, leading to FEDR dose modifications (reductions or interruptions). Active tubular secretion accounts for approximately 10%-40% of creatinine clearance and is mediated by multiple solute carrier transporters; FEDR inhibits some of those transporters. Therefore, elevated SCr with FEDR treatment may not be indicative of renal toxicity. To examine this further, we report changes in SCr and 4 other biomarkers of kidney tubular health (cystatin-C, neutrophil gelatinase-associated lipocalin [NGAL], kidney injury molecule [KIM]-1, Tamm-Horsfall urinary glycoprotein [THP]) in pts with MF enrolled in the FREEDOM (NCT03755518) and FREEDOM2 (NCT03952039) trials. Methods: Pts from the phase 3b, single arm, open-label FREEDOM trial and the phase 3, randomized, open-label FREEDOM2 trial treated with FEDR (400 mg once daily) or best available therapy (BAT; FREEDOM2 only) who had available SCr and/or renal biomarker data evaluated for 6 treatment cycles were included. Pts in the BAT arm of FREEDOM2 who crossed over to FEDR after 6 treatment cycles were pooled into the FEDR group for analyses. SCr from baseline to end-of-cycle (EOC)6 or cycle (C)7 day (D)1 was summarized using the central lab-reported values. Serum biomarkers were analyzed using Rules Based Medicine, Austin, TX KidneyMAP® panel and summarized by visits (C1D1, EOC3 [FREEDOM2 only], and EOC6). The correlations between percent change of SCr and other renal biomarkers from baseline at EOC6 were plotted and the strength of association was evaluated using the Pearson correlation. Results: In the pooled analysis, 63 pts receiving BAT and 204 pts receiving FEDR had evaluable SCr at baseline (C1D1: FEDR n=204, BAT n=63; EOC3: FEDR n=169, BAT n=54; EOC6: FEDR n=129, BAT n=33). After initiating FEDR treatment, there was an increase in mean (standard deviation [SD]) SCr (μmol/L) from baseline (88.2 [26.1]) to C1D15 (115 [34.6]) that remained stable through EOC6 (C4D1, 111 [30.0]; C7D1, 107 [29.8]). At EOC6, pts had a greater mean percent increase in SCr from baseline with FEDR (28.4%) vs BAT (0.499%); SCr increase ≥ 30% at any time occurred in 162/204 (79.4%) pts with FEDR vs 14/63 (22.2%) pts with BAT. Among the 16 evaluable pts in follow-up, SCr levels started to decrease after stopping FEDR treatment. Alternative renal biomarkers, cystatin-C and NGAL, did not show a corresponding increase from baseline to EOC6 (cystatin-C mean [SD] at baseline, EOC3, and EOC6 was 1670 [552] ng/L, 1380 [437] ng/L, and 1450 [519] ng/L, respectively; for NGAL it was 1350 [810] pg/mL, 1000 [672] pg/mL, and 973 [654] pg/mL, respectively), and there was no decrease in THP indicative of renal injury (mean [SD] at baseline, EOC3, and EOC6 was 34.4 [17.6] μg/mL, 45.4 [21.7] μg/mL, and 46.3 [22.5] μg/mL, respectively). For KIM-1, pts treated with FEDR demonstrated a greater increase and interpatient variability compared with pts treated with BAT; however, most of the absolute KIM-1 levels remained below the normal range. There were no clinically meaningful differences in mean change from baseline at EOC6 between FEDR and BAT arms for cystatin C (-9.13% vs -4.51%), KIM-1 (122% vs 49.9%), NGAL (-17.9% vs -6.99%), or THP (35.3% vs 14.7%). Finally, in pts treated with FEDR, the change in SCr from baseline to EOC6 was not significantly correlated with the change in cystatin-C (r = 0.23, P = 0.09), KIM-1 (r = −0.11, P = 0.47), NGAL (r = −0.052, P = 0.7), or THP (r = 0.068, P = 0.62). Conclusions: Pts with MF treated with FEDR in the FREEDOM and FREEDOM2 trials had an approximately 30% increase in SCr in the first cycle after initiating treatment, which remained stable throughout treatment duration. There were no apparent trends in changes of cystatin-C, KIM-1, NGAL, or THP indicative of renal injury after 6 cycles of FEDR treatment, and no significant correlation of SCr with other renal biomarkers. These data indicate that increased SCr with FEDR treatment is likely caused by inhibition of renal transporters and is not a result of impaired renal function. These data should be considered when SCr is elevated to minimize unnecessary FEDR dose reductions and interruptions that could impact treatment efficacy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".