Sean Khozin

Real-world Data for Clinical Evidence Generation in Oncology

Conventional cancer clinical trials can be slow and costly, often produce results with limited external validity, and are difficult for patients to participate in. Recent technological advances and a dynamic policy landscape in the United States have created a fertile ground for the use of real-world data (RWD) to improve current methods of clinical evidence generation. Sources of RWD include electronic health records, insurance claims, patient registries, and digital health solutions outside of conventional clinical trials. A definition focused on the original intent of data collected at the point of care can distinguish RWD from conventional clinical trial data. When the intent of data collection at the point of care is research, RWD can be generated using experimental designs similar to those employed in conventional clinical trials, but with several advantages that include gains in efficient execution of studies with an appropriate balance between internal and external validity. RWD can support active pharmacovigilance, insights into the natural history of disease, and the development of external control arms. Prospective collection of RWD can enable evidence generation based on pragmatic clinical trials (PCTs) that support randomized study designs and expand clinical research to the point of care. PCTs may help address the growing demands for access to experimental therapies while increasing patient participation in cancer clinical trials. Conducting valid real-world studies requires data quality assurance through auditable data abstraction methods and new incentives to drive electronic capture of clinically relevant data at the point of care.

Biometric monitoring devices for assessing end points in clinical trials: developing an ecosystem.

Biometric monitoring devices for assessing end points in clinical trials: developing an ecosystem

Characteristics of Real‐World Metastatic Non‐Small Cell Lung Cancer Patients Treated with Nivolumab and Pembrolizumab During the Year Following Approval

BACKGROUNDnEvidence from cancer clinical trials can be difficult to generalize to real-world patient populations, but can be complemented by real-world evidence to optimize personalization of care. Further, real-world usage patterns of programmed cell death protein 1 (PD-1) inhibitors following approval can inform future studies of subpopulations underrepresented in clinical trials.nnnMATERIALS AND METHODSnWe performed a multicenter analysis using electronic health record data collected during routine care of patients treated in community cancer care clinics in the Flatiron Health network. Real-world metastatic non-small cell lung cancer (NSCLC) patients who received nivolumab or pembrolizumab in the metastatic setting (nu2009=u20091,344) were selected from a starting random sample of 55,969 NSCLC patients with two or more documented visits from January 1, 2011, through March 31, 2016. The primary study outcome measurement was demographic and treatment characteristics of the cohort.nnnRESULTSnMedian age at PD-1 inhibitor initiation was 69 years (interquartile range 61-75). Patients were 56% male, 88% smokers, 65% nonsquamous histology, and 64% diagnosed at stage IV. Of 1,344 patients, 112 (8%) were tested for programmed death-ligand 1 expression. Overall, 50% received nivolumab or pembrolizumab in the second line, with a substantial proportion of third and later line use that began to decline in Q4 2015.nnnCONCLUSIONnDuring the year following U.S. regulatory approval of PD-1 inhibitors for treatment of NSCLC, real-world patients receiving nivolumab or pembrolizumab were older at treatment initiation and more had smoking history relative to clinical trial cohorts. Studies of outcomes in underrepresented subgroups are needed to inform real-world treatment decisions.nnnIMPLICATIONS FOR PRACTICEnEvidence gathered in conventional clinical trials used to assess safety and efficacy of new therapies is not necessarily generalizable to real-world patients receiving these drugs following regulatory approval. Real-world evidence derived from electronic health record data can yield complementary evidence to enable optimal clinical decisions. Examined here is a cohort of programmed cell death protein 1 inhibitor-treated metastatic non-small cell lung cancer patients in the first year following regulatory approval of these therapies in this indication. The analysis revealed how the real-world cohort differed from the clinical trial cohorts, which will inform which patients are underrepresented and warrant additional studies.

Real-World Evidence In Support Of Precision Medicine: Clinico-Genomic Cancer Data As A Case Study

The majority of US adult cancer patients today are diagnosed and treated outside the context of any clinical trial (that is, in the real world). Although these patients are not part of a research study, their clinical data are still recorded. Indeed, data captured in electronic health records form an ever-growing, rich digital repository of longitudinal patient experiences, treatments, and outcomes. Likewise, genomic data from tumor molecular profiling are increasingly guiding oncology care. Linking real-world clinical and genomic data, as well as information from other co-occurring data sets, could create study populations that provide generalizable evidence for precision medicine interventions. However, the infrastructure required to link, ensure quality, and rapidly learn from such composite data is complex. We outline the challenges and describe a novel approach to building a real-world clinico-genomic database of patients with cancer. This work represents a case study in how data collected during routine patient care can inform precision medicine efforts for the population at large. We suggest that health policies can promote innovation by defining appropriate uses of real-world evidence, establishing data standards, and incentivizing data sharing.

Concurrent Molecular Alterations in Tumors With Germ Line Epidermal Growth Factor Receptor T790M Mutations

Data from epidemiologic and genome-wide association studies support the role of inherited predisposition in lung carcinogenesis, even after adjustment for age, sex, and smoking habits.1,2 Because lung cancer is most often diagnosed at advanced stages when there are no curative therapies, there is a critical need to identify patients who are at inherited risk. Identification of such patients is especially important because screening tests have been shown to reduce death from lung cancer in high-risk individuals.3 Germline epidermal growth factor receptor (EGFR) T790M is a rare mutation, which is associated with familial lung cancer; only 10 cases have thus far been reported, usually in association with concurrent somatic gain-of-function EGFR mutations.4–9 We describe 2 contrasting presentations of germline EGFR T790M mutation, including a previously undescribed patient with a concurrent KRAS mutation, and discuss the potential pathogenesis of lung cancer in these patients.

Core Clinical Data Elements for Cancer Genomic Repositories: A Multi-stakeholder Consensus

The Center for Medical Technology Policy and the Molecular Evidence Development Consortium gathered a diverse group of more than 50 stakeholders to develop consensus on a core set of data elements and values essential to understanding the clinical utility of molecularly targeted therapies in oncology.

Clinician Perspectives on Current Issues in Lung Cancer Drug Development

&NA; Recent advances in molecularly targeted therapy and immunotherapy offer a glimmer of hope for potentially realizing the dream of personalized therapy for lung cancer. This article highlights current questions in clinical trial design, enrollment strategies and patient focused drug development, with particular emphasis on unique issues in trials of targeted therapy and immunotherapy.