Clinical trial · Observational
DNA Hypomethylating Agents and Lenalidomide in Elderly Patients With Myeloid Malignancies in the US
Effectiveness of DNA Hypomethylating Agents and Lenalidomide in Elderly Patients With Myeloid Malignancies in the United States
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Why stopped (as posted): Study was a data review, no patient recruitment occurred.
Summary
Brief summary (as posted)
The study aims to comprehensively analyze data from a large and unselected older AML population in the US, both treated and untreated. These data will widen understanding of treatment decisions for the older Acute Myeloid Leukemia (AML) population. Through use of the SEER-Medicare Registry, the effectiveness and impact of HMA treatments as well as the effectiveness of lenalidomide will be studied.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Acute Myeloid Leukemia | Acute Myeloid Leukemia | CURATED_BROADER | 0.80 |
| Myelodysplastic Syndromes | Myelodysplastic Syndrome | ALIAS | 0.90 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (2)
- measure
- Number of Participants on hypomethylating agents (HMA) and the effectiveness of HMA in the SEER-Medicare MDS population
- timeFrame
- Analaysis restricted to patients alive at least 3 months after HMA approval. Patients will be followed from date of their first MDS claim (index date) through death or study end, whichever occurred first.
- description
- Study patterns \& determinants of HMA use in SEER-Medicare MDS population: Use of "2+BCBM" to ID registered \& unregistered MDS cases. Map out geographical distribution of HMA use based on MDS patients reclassified by SMMRS, which will yield the proportion of higher-risk (HR) \& lower-risk (LR) patients receiving HMA. Survival times to be analyzed using Cox models with time varying covariates. Predictors to be selected for both types of responses using learning interactions via hierarchical group-lasso regularization \& monotone spline transformations. Utilization of non-parametric random Forest \& random Survival Forest methods to build regression models \& assess goodness of fit \& functional form of the model-based results. Conduction of propensity score analyses of treatment effects as an alternative method for treatment-assignment bias correction. Propensity scores to be calculated using a generalized boosting method as implemented in the R package twang. Computations will be done in R.
- measure
- Develop predictive models of HMA treatment outcomes using SEER-Medicare data
- timeFrame
- Analaysis restricted to patients alive at least 3 months after HMA approval. Patients will be followed from date of their first MDS claim (index date) through death or study end, whichever occurred first.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 66 Years
Show eligibility criteria text
Inclusion Criteria: * patients with myeloid malignancies diagnosed during 2001-2011 at the age of 66 years or older * alive in September 2004 (i.e. 3 months after FDA approval of azacitidine for MDS) * known month of diagnosis, and not identified from death certificates or autopsy only * continuous Medicare Part A and B coverage, and were not enrolled in a health maintenance organization during the period of interest Exclusion Criteria: * Anyone under 66 years
References
Publications (0)
Data not yet available