MétaCan
Menu
Back to cohort
Record W4417004176 · doi:10.1182/blood-2025-3338

Comparison of simulated exposure of inotuzumab ozogamicin with and without dose capping in overweight and obese patients with relapsed/refractory acute lymphoblastic leukemia

2025· article· en· W4417004176 on OpenAlexaff
Nathan Braniff, May Garrett, Jennifer Hibma, Erik Vandendries, Stephanie Dorman, Ying Chen

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsMerck Canada Inc. (Canada)
Fundersnot available
KeywordsBody surface areaRegimenDosingPharmacokineticsPhases of clinical researchPopulationAntibody-drug conjugateAcute lymphocytic leukemiaAntibody

Abstract

fetched live from OpenAlex

Abstract Introduction Inotuzumab ozogamacin (InO) is an antibody drug conjugate (ADC) consisting of a CD22-directed monoclonal antibody linked to a cytotoxic payload, calicheamicin. InO is approved for the treatment of patients with relapsed/refractory (R/R) CD22-positive B-cell precursor acute lymphoblastic leukemia (ALL). The labeled starting dose of InO is 1.8 mg/m2/cycle (0.8 mg/m2 on D1, and 0.5 mg/m2 on D8 and D15). While many approved ADCs are dosed based on body weight or body surface area (BSA) (Gogia et al. Cancers 2023; 15:3886), some also implement a maximum dose (dose capping), reducing the potential exposure and safety concerns for patients with larger body sizes. In this analysis, simulations using a final population pharmacokinetic (popPK) model were performed to compare the predicted exposure between the labeled regimen of 1.8 mg/m2/cycle and two capped dose regimens, specifically investigating whether dose capping is needed for InO. Methods A popPK model for InO (Garrett et al. J. of PK & PD 2019; 211-222) was updated to fit adult ALL data from three studies: NCT01363297 (N=72, 1.2–1.8 mg/m2/cycle, Phase 1/2), NCT01564784 (N=162, 1.8 mg/m2/cycle, Phase 3), and NCT03677596 (N=99, 1.2 mg/m2/cycle or 1.8 mg/m2/cycle, Phase 4). The final popPK model, using data from these 333 adult patients, was used to simulate exposure with the labeled and dose capping regimens. The exposure with the labeled regimen was compared to that with two modified dose capping regimens in which patients at or above a specified BSA threshold were simulated with a fixed dose. Two dose capping BSA thresholds were investigated, 1.97 m2 (N=105 >1.97 m2) and 2.14m2 (N=49 >2.14 m2), with thresholds corresponding to previously reported mean BSA values (DuBois formula) for overweight and obese populations, respectively (Verbraecken et al. Metabolism 2006; 55.4:515-524). Simulated InO serum concentrations were used to compute exposure metrics for comparison. The labeled and dose capping regimens were compared using four exposure metrics: cumulative area under the curve (cAUC) at the end of cycle 1 (Day 21, termed cAUC-C1) and cycle 4 (Day 105, termed cAUC-C4), along with the maximum concentration (Cmax, over Days 92-105) and trough concentration (Ctrough, computed on Day 105) for the third dose in cycle 4. The population was further subdivided by BMI <25 kg/m2 (N=152, healthy), 25–30 kg/m2 (N=116, overweight) and >30 kg/m2 (N=65, obese) to understand how regimens affected simulated exposure in overweight and obese subpopulations. Results In general, both capped regimens exhibited only minor reductions in simulated exposure relative to the labeled regimen. For patients with BSA values above the capping thresholds, capped regimens resulted in small percentage decreases in median exposure metrics relative to the labeled regimen, with reductions of 6.9% and 4.5% for Cmax, 8.9% and 3.8% for Ctrough, 3.2% and 3.0% for cAUC-C1, and 4.3% and 8.3% for cAUC-C4, for the >=1.97 m2 and >=2.14 m2 capped regimens, respectively. Patients below the BSA threshold in the capped regimens were simulated with the same dose as the labeled regimen and therefore had no predicted exposure differences. BMI-based partitioning of the population yielded similar findings. For the overweight subpopulation (25–30 kg/m2), the capped regimens had only minor decreases in the median simulated exposure metrics relative to the labeled regimen, with reductions of 0% and 0% for Cmax, 1.7% and 0% for Ctrough, 2.1% and 0% for cAUC-C1, and 1.3% and 0% cAUC-C4, in the >=1.97 m2 and >=2.14 m2 capped regimens, respectively. In the obese subpopulation (>30 kg/m2), the median decrease in exposure metrics in the capped regimens were also small relative to the labeled regimen: 14.7% and 8.5% for Cmax, 10.9% and 10.3% for Ctrough, 7.6% and 5.2% for cAUC-C1, and 14.2% and 12.5% for cAUC-C4, for the >=1.97 m2 and >=2.14 m2 caps, respectively. Conclusion The simulated InO exposures with dose capping were slightly reduced relative to the labeled regimen across BSA and BMI-based patient subpopulations, suggesting that dose capping is not needed. These results support the current labeled BSA-based dosing regimen starting at 1.8 mg/m2/cycle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.273
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicAcute Lymphoblastic Leukemia researchFrench-language works237,207