Reliability of Conclusions from Early Analyses of Real-World Data for Newly Approved Drugs in Advanced Gastric Cancer in the United States.
bias
gastric cancer
ramucirumab
real-world data
trastuzumab
Journal
Pragmatic and observational research
ISSN: 1179-7266
Titre abrégé: Pragmat Obs Res
Pays: New Zealand
ID NLM: 101688693
Informations de publication
Date de publication:
2020
2020
Historique:
received:
07
12
2019
accepted:
16
03
2020
entrez:
21
5
2020
pubmed:
21
5
2020
medline:
21
5
2020
Statut:
epublish
Résumé
As real-world data resources expand and improve, there will increasingly be opportunities to study the effectiveness of interventions. There is a need to ensure that study designs explore potential sources of bias and either acknowledge or mitigate them, in order to improve the accuracy of findings. The objective of this study was to understand newly approved drug utilization patterns in real-world clinical settings over time. This retrospective study included three sources of real-world data (claims, electronic health records, and recoded data from a quality care program) collected from patients diagnosed with gastric cancer who initiated therapy with either trastuzumab or ramucirumab. Linear regression was used to investigate trends in the use of these drugs for the care of patients with gastric cancer over time from Food and Drug Administration (FDA) approval. Eligible patients (n=1700) had consistent demographic and clinical characteristics over time. After regulatory approval, trastuzumab was used in later lines of therapy and then shifted to earlier lines (p=0.002), while ramucirumab utilization remained consistent over time after FDA approval (p=0.49). Ramucirumab augmentation, defined as the addition of the drug after initiation of a line of therapy, decreased over time (p=0.03), and trastuzumab augmentation remained consistent over time (p=0.58). Since treatment effectiveness may change across lines of treatment, bias may arise if there are changes in the use of the drug (such as line migration) during the time period of analysis using real-world data.
Sections du résumé
BACKGROUND
BACKGROUND
As real-world data resources expand and improve, there will increasingly be opportunities to study the effectiveness of interventions. There is a need to ensure that study designs explore potential sources of bias and either acknowledge or mitigate them, in order to improve the accuracy of findings. The objective of this study was to understand newly approved drug utilization patterns in real-world clinical settings over time.
METHODS
METHODS
This retrospective study included three sources of real-world data (claims, electronic health records, and recoded data from a quality care program) collected from patients diagnosed with gastric cancer who initiated therapy with either trastuzumab or ramucirumab. Linear regression was used to investigate trends in the use of these drugs for the care of patients with gastric cancer over time from Food and Drug Administration (FDA) approval.
RESULTS
RESULTS
Eligible patients (n=1700) had consistent demographic and clinical characteristics over time. After regulatory approval, trastuzumab was used in later lines of therapy and then shifted to earlier lines (p=0.002), while ramucirumab utilization remained consistent over time after FDA approval (p=0.49). Ramucirumab augmentation, defined as the addition of the drug after initiation of a line of therapy, decreased over time (p=0.03), and trastuzumab augmentation remained consistent over time (p=0.58).
CONCLUSION
CONCLUSIONS
Since treatment effectiveness may change across lines of treatment, bias may arise if there are changes in the use of the drug (such as line migration) during the time period of analysis using real-world data.
Identifiants
pubmed: 32431558
doi: 10.2147/POR.S241427
pii: 241427
pmc: PMC7205419
doi:
Types de publication
Journal Article
Langues
eng
Pagination
27-43Informations de copyright
© 2020 Hess et al.
Déclaration de conflit d'intérêts
LMH, AML, XIL, ZLC, LB and WS are employees of Eli Lilly and Company. MG is an employee of HealthCore, Inc., an independent research organization that received funding from Eli Lilly and Company for the conduct of the study. LW was an employee of HealthCore, Inc. when the study was conducted. The authors report no other conflicts of interest in this work.
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