Literature DB >> 36246306

Oncology Drug Effectiveness from Electronic Health Record Data Calibrated Against RCT Evidence: The PARSIFAL Trial Emulation.

David Merola1,2, Jessica Young2,3, Deborah Schrag4, Kueiyu Joshua Lin1,2,5, Nicholas Robert6, Sebastian Schneeweiss1,2.   

Abstract

Background: The use of electronic health records (EHR) data to assess drug effectiveness in clinical oncology practice is of great interest to regulators, clinicians, and payers. However, the utility of EHR data in clinical effectiveness studies may be limited by missing data, unmeasured confounding, and imperfect outcome surveillance. This study sought to emulate and compare the results of a randomized controlled trial investigating the efficacy of palbociclib with fulvestrant vs letrozole in advanced breast cancer.
Methods: This was a cohort study using longitudinal EHR data derived from outpatient oncology practices in the United States. Eligibility criteria from the PARSIFAL trial were emulated as closely as possible. Patients were included if they had hormone-positive, human epidermal growth factor receptor - 2 (HER-2) negative metastatic breast cancer and had no record of prior treatment for metastatic disease. Patients initiating first-line treatment with palbociclib and fulvestrant following their first record of metastasis were compared to those initiating palbociclib and letrozole on the same day. Treatments were ascertained by oncology medication ordering records in the data source. The primary outcome was death as recorded in the oncologists' EHR systems.
Results: There were 1886 eligible women in the study cohort. Although the 3-year survival was meaningfully lower in clinical practice (59%) compared to the randomized trial (78%), the relative effect size was a hazard ratio (HR) of 1.07 (95% CI: 0.86-1.35), similar to the randomized trial (HR = 1.00; 95% CI: 0.68-1.48).
Conclusion: Despite common challenges encountered in EHR-based studies, it is possible to achieve similar conclusions to emulated randomized trials with the application of analytic approaches that address missing data, confounding, and selection bias. This is a promising finding in light of other emulations and ongoing efforts to improve data from clinical practice and causal analytics.
© 2022 Merola et al.

Entities:  

Keywords:  comparative effectiveness research; healthcare databases; oncology; pharmacoepidemiology; real-world evidence

Year:  2022        PMID: 36246306      PMCID: PMC9563733          DOI: 10.2147/CLEP.S373291

Source DB:  PubMed          Journal:  Clin Epidemiol        ISSN: 1179-1349            Impact factor:   5.814


  26 in total

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