Real-World Outcomes of Patients with Metastatic Non-Small Cell Lung Cancer Treated with Programmed Cell Death Protein 1 Inhibitors in the Year Following U.S. Regulatory Approval.

BACKGROUND: Evidence from cancer clinical trials has strong internal validity but can be difficult to generalize to real-world patient populations. Here we analyzed real-world outcomes of patients with metastatic non-small cell lung cancer (mNSCLC) treated with programmed cell death protein 1 (PD-1) inhibitors in the first year following U.S. regulatory approval. MATERIALS AND METHODS: This retrospective study leveraged electronic health record (EHR) data collected during routine patient care in community cancer care clinics. The cohort included patients with mNSCLC who had received nivolumab or pembrolizumab for metastatic disease (n = 1,344) with >1 EHR-documented visit from January 1, 2011, to March 31, 2016. Patients with a > 90-day gap between advanced disease diagnosis and first EHR structured data entry were excluded. RESULTS: Estimated median overall survival (OS) was 8.0 months (95% confidence interval 7.4-9.0 months). Estimated median OS was 4.7 months (3.4-6.6) for patients with anaplastic lymphoma kinase rearrangement- and epidermal growth factor receptor mutation-positive tumors, and 8.6 months (7.7-10.6) for patients without such mutations. Age at PD-1 inhibitor initiation or line of therapy did not impact OS. CONCLUSION: This analysis suggests OS in real-world patients may be shorter than in conventional clinical trial patient cohorts, potentially due to narrow trial eligibility criteria. The lack of difference in OS by line of therapy or age at immunotherapy initiation suggests sustained benefit of PD-1 inhibitors in multitreated patients with mNSCLC and that age is not a predictor of outcome. Further studies are underway in patients with comorbidities, organ dysfunction, and multiple prior therapies. IMPLICATIONS FOR PRACTICE: This study evaluated data derived from electronic health records of patients with metastatic non-small cell lung cancer treated with programmed cell death protein 1 (PD-1) inhibitors in the year following regulatory approval. This real-world cohort had shorter overall survival (OS) indexed to PD-1 inhibitor initiation than reported in clinical trials. Late-line treatment did not influence OS, and patients aged >75 at immunotherapy initiation did not have worse outcomes than younger patients. As new therapies enter clinical practice, real-world data can complement clinical trial evidence providing information on generalizability and helping inform clinical treatment decisions.

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

BACKGROUND: Evidence 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. MATERIALS AND METHODS: We 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 (n = 1,344) 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. RESULTS: Median 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. CONCLUSION: During 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. IMPLICATIONS FOR PRACTICE: Evidence 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.

Opportunities and challenges in leveraging electronic health record data in oncology.

The widespread adoption of electronic health records (EHRs) and the growing wealth of digitized information sources about patients is ushering in an era of 'Big Data' that may revolutionize clinical research in oncology. Research will likely be more efficient and potentially more accurate than the current gold standard of manual chart review studies. However, EHRs as they exist today have significant limitations: important data elements are missing or are only captured in free text or PDF documents. Using two case studies, we illustrate the challenges of leveraging the data that are routinely collected by the healthcare system in EHRs (e.g., real-world data), specific challenges encountered in the cancer domain and opportunities that can be achieved when these are overcome.

Augmenting control arms with real-world data for cancer trials: Hybrid control arm methods and considerations.

Background: Hybrid controlled trials with real-world data (RWD), where the control arm is composed of both trial and real-world patients, could facilitate research when the feasibility of randomized controlled trials (RCTs) is challenging and single-arm trials would provide insufficient information. Methods: We propose a frequentist two-step borrowing method to construct hybrid control arms. We use parameters informed by a completed randomized trial in metastatic triple-negative breast cancer to simulate the operating characteristics of dynamic and static borrowing methods, highlighting key trade-offs and analytic decisions in the design of hybrid studies. Results: Simulated data were generated under varying residual-bias assumptions (no bias: HRRWD = 1) and experimental treatment effects (target trial scenario: HRExp = 0.78). Under the target scenario with no residual bias, all borrowing methods achieved the desired 88% power, an improvement over the reference model (74% power) that does not borrow information externally. The effective number of external events tended to decrease with higher bias between RWD and RCT (i.e. HRRWD away from 1), and with weaker experimental treatment effects (i.e. HRExp closer to 1). All dynamic borrowing methods illustrated (but not the static power prior) cap the maximum Type 1 error over the residual-bias range considered. Our two-step model achieved comparable results for power, type 1 error, and effective number of external events borrowed compared to other borrowing methodologies. Conclusion: By pairing high-quality external data with rigorous simulations, researchers have the potential to design hybrid controlled trials that better meet the needs of patients and drug development.

Development and Validation of a High-Quality Composite Real-World Mortality Endpoint.

OBJECTIVE: To create a high-quality electronic health record (EHR)-derived mortality dataset for retrospective and prospective real-world evidence generation. DATA SOURCES/STUDY SETTING: Oncology EHR data, supplemented with external commercial and US Social Security Death Index data, benchmarked to the National Death Index (NDI). STUDY DESIGN: We developed a recent, linkable, high-quality mortality variable amalgamated from multiple data sources to supplement EHR data, benchmarked against the highest completeness U.S. mortality data, the NDI. Data quality of the mortality variable version 2.0 is reported here. PRINCIPAL FINDINGS: For advanced non-small-cell lung cancer, sensitivity of mortality information improved from 66 percent in EHR structured data to 91 percent in the composite dataset, with high date agreement compared to the NDI. For advanced melanoma, metastatic colorectal cancer, and metastatic breast cancer, sensitivity of the final variable was 85 to 88 percent. Kaplan-Meier survival analyses showed that improving mortality data completeness minimized overestimation of survival relative to NDI-based estimates. CONCLUSIONS: For EHR-derived data to yield reliable real-world evidence, it needs to be of known and sufficiently high quality. Considering the impact of mortality data completeness on survival endpoints, we highlight the importance of data quality assessment and advocate benchmarking to the NDI.