Our research leverages real-world data from our international network. Here, you will find collaborative, observational insights of community health systems and hospitals across the United States and South Korea. Our hope is that the information published here impacts the real-world, where cancer care is delivered, and our learnings help deliver better treatments, regimens and outcomes for patients.
Immune checkpoint inhibitors alone or in combination with chemotherapy have become standard of care for patients with advanced non-small cell lung cancer (aNSCLC) without driver mutations. This study investigates the real-world performance of immunotherapies in the treatment of patients with aNSCLC.
Mutation-specific tyrosine kinase inhibitors (TKIs) have demonstrated efficacy among patients (pts) with advanced non-small cell lung cancer (aNSCLC) with sensitizing gene alterations (GA). It is unclear how effective immune checkpoint inhibitor (ICI) therapy is among NSCLC pts with sensitizing GA, particularly after TKI failure or resistance.
Natural language processing (NLP) in pathology reports to extract biomarker information is an ongoing area of research. MetaMap is a natural language processing tool developed and funded by the National Library of Medicine to map biomedical text to the Unified Medical Language System Metathesaurus by applying specific tags to clinically relevant terms. Although results are useful without additional postprocessing, these tags lack important contextual information.
The understanding of the impact of COVID-19 in patients with cancer is evolving, with need for rapid analysis.
Immune checkpoint inhibitor (ICI) therapy has become a mainstay of non-small cell lung cancer (NSCLC) treatment. However, not all patients (pts) benefit with a subset paradoxically experiencing accelerated tumor growth while on ICI. Hyperprogression (HP) refers to accelerated tumor growth on ICI with worsening clinical status. Various gene alterations may be associated with HP including MDM2/MDM4 amplifications, EGFR alterations, and STK11/LKB1 mutations. Kato et al. (doi: 10.1158/1078-0432.CCR-16-3133) showed HP in 6/6 pts with MDM2/MDM4 amplification and in 2/10 pts with EGFR alterations. This report describes HP in pts with NSCLC treated with ICIs in a large health system.
Friends of Cancer Research (FOCR), the United States Food and Drug Administration (FDA), ASCO and five data partners, including Syapse, used electronic health record-sourced datasets to conduct parallel analyses in RWD. The study assessed estimates of real-world overall survival among patients taking platinum doublet chemotherapy (chemo) or pembrolizumab in combination with chemo (IO+chemo) in first-line treatment for metastatic non-small cell lung cancer (mNSCLC). A range of observed results highlights the complexity of RWD, including differences in sample size, underlying patient variability across datasets, and missing covariate data. The harmonization process and observed results underscore the importance of a well-articulated research question and a pre-specified analytic plan to guide data harmonization, standardization, and analysis.
For advanced NSCLC, evidence from clinical trials indicates the superiority of pembrolizumab (P) than chemotherapy (C) in PD-L1 positive patients and superiority of P+C than C among PD-L1 unselected patients. Meta-analysis from different clinical trials stated P+C failed to improve overall survival (OS) or progression-free survival (PFS) compared with P alone. This study, developed in partnership with Henry Ford Health System, used real-world data of PD-L1+ patients with advanced NSCLC to compare treatment effect of P with P+C, finding that, among patients with PD-L1+ advanced NSCLC, there is no significant difference in rwOS for patients with 1L treatment of P+C or P alone.
Treatment response to anti-cancer therapies for advanced lung cancer is usually assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST), which is not generally applied in real-world settings. With real-world evidence increasingly being used to support promising treatment, this study, developed in partnership with Advocate Aurora Health, evaluated the feasibility of assessing real-world lung cancer response by RECIST-based measurement of lesions on archived radiologic films and assessed its concordance with treatment response based on oncologist narratives in electronic health record (EHR). This study is an important step in demonstrating the potential to approximate real-world RECIST-based treatment response using EHR abstraction of oncologists’ documentation.
Patients (pts) with lung cancer and other cancers treated with immune checkpoint inhibitors (ICI) may experience immune related adverse events (irAE). These can present with variable severity and with single- or multi-organ involvement including pneumonitis, colitis, hepatitis, and myocarditis/pericarditis. The incidence of myocarditis has been reported between 0.06% and 2.4% and is associated with a high mortality (25% to 50%). This retrospective review of real-world data (RWD) investigates myocarditis as a high-grade adverse event in pts with lung cancer treated with ICIs.
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).
BRAF, KRAS, NRAS and MSI/MMR testing in mCRC patients (pts) recommended by NCCN since 20151 Molecular testing rates previously reported in academic centers and independent community practices2,3 Knowledge gap exists in community health systems (HS), accounting ~50% of US cancer care
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.
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.
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.
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).