Publications
Using real-world evidence to generate real-world insights is a core tenant of the Syapse Learning Health Network. In partnership with our network partners, together, we have shared research on real-world treatment patterns in breast and non-small cell lung cancer. The highlights of our collective research can be found below.
Looking for a more comprehensive list of our past, and present work, you can view it here.
This study tested whether a composite mortality score could overcome gaps and potential biases in individual real-world mortality data sources. Complete and accurate mortality data are necessary to calculate important outcomes in oncology, including overall survival. However, in the United States, there is not a single complete and broadly applicable mortality data source. It is further likely that available data sources are biased in their coverage of sex, race, age, and socioeconomic status (SES).
Evolution of the Cancer Registrar in the Era of Informatics (March 2021)
The purpose of this article is the role of the registrar in the collection and reporting of critical cancer data and how registrars are currently using informatics to enhance their work. This article describes how informatics can be leveraged in the future and how registrars play a vital role in meeting the increasing demands placed on them to provide timely, meaningful, and accurate data for the cancer community.
The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments.
We compared treatment associated pneumonitis (TAP) related to immune checkpoint inhibitors (ICI) or chemotherapies (chemo) in advanced non-small cell lung cancer (aNSCLC) patients (pts) with and without (+/-) past medical history (PMH) of Pn, using data from clinical trials (CT) and real world data (RWD).
With nearly six years of prescribing experience since US approval of Palbociclib, there is now adequate follow-up to evaluate real-world effectiveness of Palbociclib Plus an Aromatase (PAL+AI) treatment patterns. This retrospective single-arm study described real-world treatment patterns and clinical outcomes of patients with hormone receptor–positive/human epidermal growth factor receptor 2–negative (HR+/HER2–) A/MBC who received PAL+AI as first-line (1L) therapy in US practices.
Considerations for Use of Real-World Evidence in Oncology (October 2020)
Informed by several pilot projects leveraging a common protocol (established in the RWE 1.0 Pilot Project and expanded upon in subsequent pilots, described below) among multiple real-world data partners, US and international populations, and oncology-specific disease settings, Friends of Cancer Research (Friends) and collaborators identified implications of dataset specifics and patient characteristics on real-world endpoints and recommendations for developing a RWE framework to encourage and guide future RWE studies that leverage multiple data sources to answer a single question through a harmonized protocol.
Reports suggest worsened outcomes in patients with cancer and COVID-19, varying by geography and local peak dynamics. Cancer in patients diagnosed with COVID-19 associated with increased risk of severe events with even greater risk among patients with metastatic disease and those with recent treatment1 and higher incidence of COVID-19 reported among Black Americans.
Clinical trials show improved survival for advanced non-small cell lung cancer (aNSCLC) patients whose tumors are positive for PD-L1 expression when treated with immune checkpoint inhibitors (ICI), including pembrolizumab (Pb) and nivolumab (Nb). It is unclear whether relatively higher PD-L1 expression by tumor proportion score (TPS) is associated with better response to treatment, and whether this can be generalized to a real-world setting.
Higher PD-L1 score ≥ 50% predicts for greater benefit to immune checkpoint inhibitor (ICI) therapy in first line (1L) treatment of aNSCLC. It has recently been reported that PD-L1 score ≥ 90% predicts for even greater benefit to 1L ICI monotherapy (Aguilar et al., 2019). We examined pooled clinical trial databases to examine the relationship between high PD-L1 expression across multiple ICI monotherapies in 1L and second line (2L) treatment of aNSCLC.
Immune checkpoint inhibitor (ICI) therapy has become a mainstay of lung cancer treatment. However, not all NSCLC patients (pts) benefit, a subset paradoxically experiences accelerated tumor growth while on immunotherapy. Hyperprogression (HP) refers to accelerated tumor growth on ICI with worsening clinical status.
Friends of Cancer Research convened 9 data partners to identify data elements and common definitions for real world (rw) endpoints to evaluate populations typically excluded from clinical trials. Here we report on rwOS by frontline treatment and comorbidities.
Leveraging data from a collaboration with 9 data partners, Friends of Cancer Research convened the Real-world Evidence Pilot 2.0, to examine trends and real world (rw) data endpoints in immunotherapy (IO) use for the front line treatment of aNSCLC.