Trial · NCT07003295
Registered outcomes12
Each outcome the trial registered, primary first, in ClinicalTrials.gov's words.
1 to 12 of 12
Download this page as JSON| List | Outcome | Time frame | Description |
|---|---|---|---|
| Primary | Objective response rate | Up to 2 years | A Simon 2-stage optimal design will be used with a favorable response of 55% and unfavorable response of 25%. |
| Secondary | Complete response rate | Up to 2 years | Proportions will be estimated with Agresti-Coull 95% binomial confidence intervals. |
| Secondary | Progression-free survival (PFS) | Up to 24 months | Proportions will be estimated with Agresti-Coull 95% binomial confidence intervals. Will be estimated using the Kaplan Meier method. Estimates of PFS will be reported with a 95% confidence interval. |
| Secondary | Overall survival (OS) | Up to 24 months | Proportions will be estimated with Agresti-Coull 95% binomial confidence intervals. Will be estimated using the Kaplan Meier method. Estimates of OS will be reported with a 95% confidence interval. |
| Secondary | Incidence of grade 3-4 cytokine release syndrome | Up to 2 years | Proportions will be estimated with Agresti-Coull 95% binomial confidence intervals. Incidence will be described. |
| Secondary | Incidence of grade 3-4 neurologic toxicity | Up to 2 years | Proportions will be estimated with Agresti-Coull 95% binomial confidence intervals. Incidence will be described. |
| Secondary | Changes in glofitamab clearance | At baseline and up to 2 years | Pharmacokinetics (PK) of glofitamab will also be determined to assess exposure-response and clearance-response relationships. When appropriate, Bayesian logistic regression analysis will be performed to assess exposure-response and clearance-response relationships. Basic non-compartmental analyses will be performed with the concentration versus time data to summarize several pharmacokinetic parameters including observed maximum concentration and area under the observed concentration versus time curves. Descriptive statistics will be used to summarize these results. Nonlinear mixed-effects modeling will also be performed to develop a population PK model of glofitamab to describe PK properties, including absorption, distribution, and overall elimination. |
| Other | Relationship in circulating tumor deoxyribonucleic acid (ctDNA) in plasma, treatment response, and duration of response | On day 1 of cycles 1, 3, and 5 (cycle length = 21 days) | Descriptive statistics will be used to summarize the ctDNA results. |
| Other | Relationship between chimeric antigen receptor (CAR) T-cell levels in plasma, immunophenotype, treatment response, and duration of response | On day 1 of cycles 1, 3 and 5 (cycle length = 21 days) | Descriptive statistics will be used to summarize the CAR-T and T-cell immunophenotype results. |
| Other | Glofitamab PK | Before and 5-60 minutes after glofitamab infusions on day 8 of cycle 1 and day 1 of cycles 2-4, 6, 9, and 12 (cycle length = 21 days) | |
| Other | Relationship between fluorodeoxyglucose positron emission tomography/ computed tomography interlesional treatment response heterogeneity and survival outcomes | At baseline and after cycles 2, 5, 8, and 12 (cycle length = 21 days) | Responses will be assessed using 2014 revised response criteria as outlined by Cheson et al., 2014. |
| Other | Relationship between organ-specific changes in standardized uptake value (SUV) metrics and immune-related adverse events (AEs) | At baseline and after cycles 2, 5, 8, and 12 (cycle length = 21 days) | Images will be analyzed for changes in SUV metrics using the TRAQinform tool. Changes in SUV metrics (including max, mean, total) will be obtained in each lesion with metrics reported numerically, as well as graphically to understand treatment response heterogeneity (percent lesions for each response classification based on each SUV metric and change in lesion based on established limits of agreement). The automated organ segmentations will be used to quantify organ uptake, which will be correlated with occurrence of AEs in those organs. A TRAQinform profile based on an artificial intelligence model (random survival forest model generated in lymphoma) of survival will be used to explore predictive accuracy in patients treated with glofitamab. |
Source ClinicalTrials.govtrials-2026-11-12-0.5.0
Sources 3
- ClinicalTrials.gov's posted results, through CTTI's AACTFreely available. Acknowledgement requested
- ClinicalTrials.govNo license stated
- NIH RePORTER's clinical studies and project filesPublic domain
Each source's terms
- ClinicalTrials.gov's posted results, through CTTI's AACTClinicalTrials.gov data via Aggregate Analysis of ClinicalTrials.gov (AACT), CTTI. CTTI makes its materials freely available and requests acknowledgement. https://aact.ctti-clinicaltrials.org/documentation/299
- ClinicalTrials.govnone stated
- NIH RePORTER's clinical studies and project filesPublic domain (NIH RePORTER)
ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.
For software
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GET https://conductscience.org/api/trials/v1/NCT07003295/registered