Evaluation of Real-World Tumor Response Derived From Electronic Health Record Data Sources: A Feasibility Analysis in Patients With Metastatic Non-Small Cell Lung Cancer Treated With Chemotherapy
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View abstract on PubMed
Summary
This summary is machine-generated.Real-world data (RWD) can assess drug response in metastatic non-small cell lung cancer (mNSCLC). Clinician assessments showed consistency, enabling evaluation of real-world response rates and survival outcomes.
Area Of Science
- Oncology
- Real-World Evidence
- Health Informatics
Background
- Real-world data (RWD) offers insights into drug effectiveness but presents challenges in assessing treatment response.
- Evaluating real-world (rw) response requires standardized methods for capturing and analyzing diverse data attributes.
Purpose Of The Study
- To assess available data attributes for capturing, defining, and evaluating real-world response to treatment from RWD sources.
- To inform methods for consistent assessment of drug effectiveness using real-world data.
Main Methods
- Retrospective observational study using deidentified RWD from seven electronic health record data providers.
- Included 200 patients with metastatic non-small cell lung cancer (mNSCLC) treated with first-line platinum doublet chemotherapy.
- Evaluated availability of data components (images, reports, clinician assessments) and analyzed real-world response endpoints (rwRR, rwDOR, rwOS, rwTTD, rwTTNT).
Main Results
- Clinician assessments were more consistently available and timed than images or image reports across datasets.
- Real-world response rate (rwRR) showed relative consistency (median 46.5%) using clinician assessments.
- Median and directionality of rwOS, rwTTD, and rwTTNT were relatively consistent, but rwDOR varied across datasets.
Conclusions
- Feasible to align disparate RWD sources for evaluating real-world response endpoints using clinician-documented responses in mNSCLC.
- Heterogeneity in data component availability necessitates further work to standardize drug effectiveness evaluation in RWD.
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