Journal article
Utilization of real-world data in assessing treatment effectiveness for diffuse large B-cell lymphoma
American journal of hematology, Vol.98(1), pp.180-192
01/2023
DOI: 10.1002/ajh.26767
PMCID: PMC10092365
PMID: 36251361
Abstract
Direct comparisons of the effectiveness of the numerous novel therapies in the diffuse large B-cell lymphoma (DLBCL) treatment landscape in a range of head-to-head randomized phase 3 trials would be time-consuming and costly. Comparative effectiveness studies using real-world data (RWD) represent a complementary approach. Recently, several studies of relapsed/refractory (R/R) DLBCL have used RWD to create observational cohorts to compare patient outcomes with cohorts derived from single-arm phase 2 trials. Using propensity score methods to balance clinically and prognostically relevant baseline covariates, closely matched patient-level cohorts can be generated. By incorporating appropriate measures to assess covariate balance and address potential bias in comparative effectiveness study designs, robust comparative analyses can be performed. Results from such studies have been used to supplement regulatory approval of therapies assessed in single-arm trials. While RWD studies have a greater susceptibility to bias compared to randomized controlled trials, well-designed and appropriately analyzed studies can provide complementary real-world evidence on treatment effectiveness.
Details
- Title: Subtitle
- Utilization of real-world data in assessing treatment effectiveness for diffuse large B-cell lymphoma
- Creators
- Grzegorz Nowakowski - Division of Hematology Mayo Clinic Rochester Minnesota USAMatthew J Maurer - Division of Hematology Mayo Clinic Rochester Minnesota USAJames R Cerhan - Mayo Clinic in FloridaDebarshi Dey - MorphoSysLaurie H Sehn - University of British Columbia
- Resource Type
- Journal article
- Publication Details
- American journal of hematology, Vol.98(1), pp.180-192
- DOI
- 10.1002/ajh.26767
- PMID
- 36251361
- PMCID
- PMC10092365
- ISSN
- 0361-8609
- eISSN
- 1096-8652
- Language
- English
- Date published
- 01/2023
- Academic Unit
- Epidemiology
- Record Identifier
- 9984368207402771
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