Myelodysplastic Syndromes
Conditions
Keywords
myelodysplastic syndromes, MDS, computational biology, relapsed, refractory
Brief summary
This open-label, randomized, parallel group phase II study will investigate the efficacy of computational biology-informed treatment vs. standard of care treatment for patients with relapsed or refractory myelodysplastic syndromes (MDS).
Detailed description
It is hypothesized that personalized treatment informed by computational biology simulation technology will improve treatment outcomes for patients with relapsed or refractory MDS.
Interventions
DRUGFDA-approved drug or combination of drugs
Patients assigned to this arm will receive an FDA-approved drug or combination of drugs. Dosing and treatment schedule will follow the package insert for the selected drug(s).
DRUGFLAG induction
Patients will receive 30 mg/m2 per day intravenously of fludarabine for 5 days and 2000 mg/m2 per day intravenously of cytarabine for 5 days. 5 mg/kg per day of granulocyte colony stimulating factor (G-CSF) may be given subcutaneously beginning on Day 1 of each treatment until absolute granulocyte count \> 500/ microliter for 3 days.
DRUG7 + 3 induction
Patients will receive 100-200 mg/m2 per day intravenously of cytarabine for 7 days, plus either 45-60 mg/m2 per day intravenously of daunorubicin or 9-12 mg/m2 per day intravenously of idarubicin for 3 days.
DRUGLow-dose cytarabine
Patients will receive 20 mg/m2 per day subcutaneously of cytarabine for 10 days every 28 days.
OTHERSupportive care alone
Patients will receive one or more of the following: blood product transfusions, antibiotics, granulocyte colony-stimulating factor (G-CSF), erythropoietic stimulating factors, and iron chelation.
DEVICEComputational biology simulations software
Genetic testing results for each patient randomized to this arm will be used by a computational biology simulations software program to generate a personalized map of dysregulated metabolic pathways contributing to the patient's disease. This map will then be used to digitally screen for potentially therapeutic FDA-approved drugs or drug combinations to target the dysregulated metabolic pathways.
Sponsors
Gateway for Cancer Research
Cellworks Group Inc.
University of Florida
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 99 Years
Healthy volunteers
No
Inclusion criteria
* Provide written informed consent * Must be at least 18 years of age * Diagnosis of MDS, as defined by World Health Organization (WHO) 2008, that has relapsed after any duration of time from last best response or is refractory to induction therapy (defined as 4 cycles of treatment with a hypomethylating agent, 2 cycles of lenalidomide, 1 cycle of low intensity chemotherapy, or 1 cycle of high intensity chemotherapy) * ECOG performance status of 0-2 * Women of child-bearing potential (i.e., women who are pre-menopausal or not surgically sterile) may participate, provided they meet the following conditions: 1. Must agree to use physician-approved contraceptive methods (e.g., abstinence, intrauterine device, oral contraceptive, double barrier device) throughout the study and for 3 months following the last dose of study treatment; and 2. Must have a negative serum or urine pregnancy test within 7 days prior to beginning treatment on this trial * Males with female partners of child-bearing potential must agree to use physician approved contraceptive methods (e.g., abstinence, condoms, vasectomy) throughout the study and should avoid conceiving children for 6 months following the last dose of study treatment.
Exclusion criteria
* Must not have acute myeloid leukemia (AML), as defined by WHO 2008 * Pregnant and nursing subjects are excluded because the effects of study treatments on a fetus or nursing child are unknown * Must not have had treatment with any anti-cancer therapy (investigational or standard) within the previous 21 days prior to the first dose of study drug or less than full recovery (no worse than CTCAE v4.0 grade 1) from the clinically significant toxic effects of that treatment.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Difference in overall response, as measured by International Working Group (IWG) 2006 criteria for response in MDS | 4 months | Difference in overall response (number of patients who achieve complete response, partial response, stable disease, or hematologic improvement per IWG 2006 criteria) between patients treated with computational biology-informed therapy vs. those treated with standard of care regimens |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Difference in blood transfusion rate between patients treated with computational biology-informed therapy and those treated with standard of care regimens | 7 months | — |
| Difference in time to progression to acute myeloid leukemia (AML), as measured by IWG 2006 criteria for response in MDS, between patients treated with computational biology-informed therapy and those treated with standard of care regimens | 4 months | — |
| Difference in time to disease relapse, as measured by IWG 2006 criteria for response in MDS, between patients treated with computational biology-informed therapy and those treated with standard of care regimens | 4 months | — |
| Difference in time to best response, as measured by IWG 2006 criteria for response in MDS, between patients treated with computational biology-informed therapy and those treated with standard of care regimens | 4 months | — |
| Difference in change in myeloblast percentage between patients treated with computational biology-informed therapy and those treated with standard of care regimens | 4 months | — |
| Difference in safety and feasibility, as measured by CTCAE v4.0 criteria | 5 months | Difference in safety and feasibility, as measured by CTCAE v4.0 criteria, between patients treated with computational biology-informed treatment and those who receive a standard of care regimen |
| Difference in time to death between patients treated with computational biology-informed therapy and those treated with standard of care regimens | 3 years | — |
Other
| Measure | Time frame |
|---|---|
| Laboratory correlations between computational model and actual intracellular pathway activation status | 4 months |
| Clinical correlations between pharmacogenotypes and drug efficacy (as measured by IWG 2006 criteria for response in MDS) | 4 months |
| Clinical correlations between pharmacogenotypes and drug-related adverse events (as measured by CTCAE v4.0 criteria) | 5 months |
| Differences in mutant allele frequencies between patients treated with computational biology-informed therapy and those treated with standard of care regimens | 4 months |
Countries
United States
Outcome results
None listed