ISPOR EU RWD

Real-world evidence research presented at International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Europe

Last updated: December 15, 2020

Understanding the Impact of Assessment Frequency on the Study of Adverse Effects (AEs) using Oncology Electronic Health Records (EHRs)

Qixing Liang et al.

Qixing Liang et al.

Real-world data from electronic health records (EHRs) can provide valuable insights into real-world adverse effects (rwAEs) of therapy. Yet, the schedule of adverse effect assessments in routine care can vary and should be considered when comparing to trial data. Researchers from Flatiron Health sought to develop a patient-level metric to quantify the frequency of documentation of rwAE assessment in oncology EHR-derived datasets, and evaluate its utility in a cohort of patients with metastatic breast cancer (mBC) receiving palbociclib.

Why this matters

EHR-derived data can provide information of unparalleled depth, the patient journey captured in the EHR chart, however, is a reflection of the regimen of routine care visits, as frequent or sparse as they may be.

This study proposes a framework applicable to the evaluation of real-word safety profiles, to ascertain the frequency of assessments and its comparability to protocol-based schedules, and the effect that any differences may have on observed incidence of adverse effects. As RWD is deployed to understand both effectiveness and safety, grasping the context surrounding data generation will enable rigorous applications and analyses.

View the virtual poster on the ISPOR website
rwAEs
Prevalence of rwAEs by level of assessment frequency in patients with mBC receiving palbociclib, vs patients in PALOMA-2, palbociclib arm

Real-world data from electronic health records (EHRs) can provide valuable insights into real-world adverse effects (rwAEs) of therapy. Yet, the schedule of adverse effect assessments in routine care can vary and should be considered when comparing to trial data. Researchers from Flatiron Health sought to develop a patient-level metric to quantify the frequency of documentation of rwAE assessment in oncology EHR-derived datasets, and evaluate its utility in a cohort of patients with metastatic breast cancer (mBC) receiving palbociclib.

Why this matters

EHR-derived data can provide information of unparalleled depth, the patient journey captured in the EHR chart, however, is a reflection of the regimen of routine care visits, as frequent or sparse as they may be.

This study proposes a framework applicable to the evaluation of real-word safety profiles, to ascertain the frequency of assessments and its comparability to protocol-based schedules, and the effect that any differences may have on observed incidence of adverse effects. As RWD is deployed to understand both effectiveness and safety, grasping the context surrounding data generation will enable rigorous applications and analyses.

View the virtual poster on the ISPOR website

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Deriving International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk categories using Oncology Electronic Health Records (EHRs)

Raina Mathur et al.

Raina Mathur et al.

International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk score is used to categorize patients with advanced renal cell carcinoma (aRCC) as having favorable, intermediate, or poor risk disease based on well-characterized clinical and laboratory prognostic variables. These categories inform first line treatment decisions and can characterize anticipated survival in patients. Unfortunately, IMDC risk categories are not consistently documented in routine clinical care. Researchers from Flatiron Health aimed to derive these risk categories using both structured and unstructured data from electronic health records.

Why this matters

In oncology, the landscape of relevant prognostic factors varies by disease. In aRCC, the IMDCC score is a key stratification factor and may be helpful to inform treatment decisions.

Making this variable available in real-world datasets enables more clinically-informed analytic approaches in aRCC studies. Furthermore, this derivation method illustrates an approach to maximize the utility of EHR-derived data, combining structured and unstructured data processing to enhance the clinical depth and meet disease-specific research challenges.

View the full virtual poster on the ISPOR website
rw OS by derived IMDC risk
Real-world overall survival by derived IMDC risk category in the IO combination cohort

International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk score is used to categorize patients with advanced renal cell carcinoma (aRCC) as having favorable, intermediate, or poor risk disease based on well-characterized clinical and laboratory prognostic variables. These categories inform first line treatment decisions and can characterize anticipated survival in patients. Unfortunately, IMDC risk categories are not consistently documented in routine clinical care. Researchers from Flatiron Health aimed to derive these risk categories using both structured and unstructured data from electronic health records.

Why this matters

In oncology, the landscape of relevant prognostic factors varies by disease. In aRCC, the IMDCC score is a key stratification factor and may be helpful to inform treatment decisions.

Making this variable available in real-world datasets enables more clinically-informed analytic approaches in aRCC studies. Furthermore, this derivation method illustrates an approach to maximize the utility of EHR-derived data, combining structured and unstructured data processing to enhance the clinical depth and meet disease-specific research challenges.

View the full virtual poster on the ISPOR website

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