scholarly journals Differential Frequency in Imaging‐Based Outcome Measurement: Bias in Real‐World Oncology Comparative‐Effectiveness Studies

2021 ◽  
Author(s):  
Blythe J. S. Adamson ◽  
Xinran Ma ◽  
Sandra D. Griffith ◽  
Elizabeth M. Sweeney ◽  
Somnath Sarkar ◽  
...  
Keyword(s):  
Real World ◽  
Comparative Effectiveness ◽  
Outcome Measurement ◽  
Measurement Bias ◽  
Effectiveness Studies

scholarly journals BBCIC Research Network Analysis of First-Cycle Prophylactic G-CSF Use in Patients Treated With High–Neutropenia Risk Chemotherapy

2021 ◽  
Author(s):  
Pamala A. Pawloski ◽  
Cara L. McDermott ◽  
James H. Marshall ◽  
Vanita Pindolia ◽  
Catherine M. Lockhart ◽  
...  
Keyword(s):  
Adverse Events ◽  
Real World ◽  
Comparative Effectiveness ◽  
Scientific Evidence ◽  
Descriptive Analysis ◽  
Safety Data ◽  
The United States ◽  
Research Network ◽  
Comparative Safety ◽  
Effectiveness Studies

Background: Chemotherapy-induced febrile neutropenia (FN) is prevented or minimized with granulocyte colony-stimulating factors (G-CSFs). Several G-CSF biosimilars are approved in the United States. The Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) is a nonprofit initiative whose objective is to provide scientific evidence on real-world use and comparative safety and effectiveness of biologics and biosimilars using the BBCIC distributed research network (DRN). Patients and Methods: We describe real-world G-CSF use in patients with breast or lung cancer receiving first-cycle chemotherapy associated with high FN risk. We assessed hospitalizations for FN, availability of absolute neutrophil counts, and G-CSF–induced adverse events to inform future observational comparative effectiveness studies of G-CSF reference products and their biosimilars. A descriptive analysis of 5 participating national health insurance plans was conducted within the BBCIC DRN. Results: A total of 57,725 patients who received at least one G-CSF dose were included. Most (92.5%) patients received pegfilgrastim. FN hospitalization rates were evaluated by narrow (<0.5%), intermediate (1.91%), and broad (2.99%) definitions. Anaphylaxis and hyperleukocytosis were identified in 1.15% and 2.28% of patients, respectively. This analysis provides real-world evidence extracted from a large, readily available database of diverse patients, characterizing G-CSF reference product use to inform the feasibility of future observational comparative safety and effectiveness analyses of G-CSF biosimilars. We showed that the rates of FN and adverse events in our research network are consistent with those reported by previous small studies. Conclusions: Readily available BBCIC DRN data can be used to assess G-CSF use with the incidence of FN hospitalizations. Insufficient laboratory result data were available to report absolute neutrophil counts; however, other safety data are available for assessment that provide valuable baseline data regarding the effectiveness and safety of G-CSFs in preparation for comparative effectiveness studies of reference G-CSFs and their biosimilars.

A Comparison of Imputation Methods for Missing Risk Factor Data from Large Real-world Electronic Medical Records for Comparative Effectiveness Studies (Preprint)

2018 ◽  
Author(s):  
Sanjoy Paul ◽  
Olga Montvida ◽  
Joanne Tropea ◽  
Joanne Tropea
Keyword(s):  
Risk Factor ◽  
Electronic Medical Records ◽  
Real World ◽  
Medical Records ◽  
Comparative Effectiveness ◽  
Outcome Data ◽  
Complete Case ◽  
Risk Factor Data ◽  
Factor Data ◽  
Effectiveness Studies

UNSTRUCTURED Background: Evaluation of appropriate methodologies for imputation of missing risk factor or outcome data from electronic medical records (EMRs) is crucial but lacking for comparative effectiveness studies. Robust imputation of missing data relies on the understanding of the predictors of missingness in the risk factor data, especially in patients with chronic diseases. These two aspects have not been explored simultaneously to support methodological developments in clinical epidemiological studies with real-world data. Methods: Using disease-biomarker data (glycated haemoglobin, HbA1c) from large EMR database in patients with diabetes, exploratory analyses were conducted to ascertain the possible predictors of missingness. Three approaches based on multiple imputation (MI) technique, namely two-fold MI, MI by chained equations, and MI with Monte Carlo Markov Chain, were evaluated in terms of their robustness in imputing missing data. The value of using imputed data for drawing robust inferences on comparative effectiveness of two anti-diabetes therapies were compared with the complete-case analyses. Results: Older patients and patients with higher disease-severity were less likely to have missing HbA1c data longitudinally over 12 months, while gender and pre-existing comorbidities were not associated with the likelihood of missingness. No significant differences in the distributions of follow-up imputed data with the three methods were observed. Conclusion: While complete case analyses were prone to bias by indication, use of three MI techniques for large proportion of missing primary outcome data under unknown patterns of missingness appeared to be valid, and able to provide consistent and reliable clinical inferences.

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