Characterizing the Feasibility and Performance of Real-World Tumor Progression End Points and Their Association With Overall Survival in a Large Advanced Non–Small-Cell Lung Cancer Data Set

Abstract

PURPOSELarge, generalizable real-world data can enhance traditional clinical trial results. The current study evaluates reliability, clinical relevance, and large-scale feasibility for a previously documented method with which to characterize cancer progression outcomes in advanced non–small-cell lung cancer from electronic health record (EHR) data.METHODSPatients who were diagnosed with advanced non–small-cell lung cancer between January 1, 2011, and February 28, 2018, with two or more EHR-documented visits and one or more systemic therapy line initiated were identified in Flatiron Health’s longitudinal EHR-derived database. After institutional review board approval, we retrospectively characterized real-world progression (rwP) dates, with a random duplicate sample to ascertain interabstractor agreement. We calculated real-world progression-free survival, real-world time to progression, real-world time to next treatment, and overall survival (OS) using the Kaplan-Meier method (index date was the date of first-line therapy initiation), and correlations between OS and other end points were assessed at the patient level (Spearman’s ρ).RESULTSOf 30,276 eligible patients,16,606 (55%) had one or more rwP event. Of these patients, 11,366 (68%) had subsequent death, treatment discontinuation, or new treatment initiation. Correlation of real-world progression-free survival with OS was moderate to high (Spearman’s ρ, 0.76; 95% CI, 0.75 to 0.77; evaluable patients, n = 20,020), and for real-world time to progression correlation with OS was lower (Spearman’s ρ, 0.69; 95% CI, 0.68 to 0.70; evaluable patients, n = 11,902). Interabstractor agreement on rwP occurrence was 0.94 (duplicate sample, n = 1,065) and on rwP date 0.85 (95% CI, 0.81 to 0.89; evaluable patients n = 358 [patients with two independent event captures within 30 days]). Median rwP abstraction time from individual EHRs was 18.0 minutes (interquartile range, 9.7 to 34.4 minutes).CONCLUSIONWe demonstrated that rwP-based end points correlate with OS, and that rwP curation from a large, contemporary EHR data set can be reliable, clinically relevant, and feasible on a large scale.

STK11 and KEAP1 mutations as prognostic biomarkers in an observational real-world lung adenocarcinoma cohort

“…We used real-world endpoints: real-world, progressionfree survival 19 (rwPFS) and overall survival (OS), 20 as previously defined. Briefly, the date of treatment initiation was taken as the start time and the event was censored at the date of last patient activity when no progression or mortality date was present.…”

Real‐world progression, treatment, and survival outcomes during rapid adoption of immunotherapy for advanced non–small cell lung cancer

“…Dates of death were based on a composite mortality variable comprised of structured and unstructured EHR data linked to commercial mortality data and the Social Security Administration's Death Master File; a sample cohort of patients with advNSCLC from a previous analysis yielded a median survival similar to that calculated using the National Death Index as a gold standard . Dates of real‐world progression (rwP) events were retrospectively captured from the EHR from clinician notes documenting progression of advNSCLC; methods for curating rwP were previously described and evaluated with a validation framework …”

“…16 Dates of real-world progression (rwP) events were retrospectively captured from the EHR from clinician notes documenting progression of advNSCLC; methods for curating rwP were previously described and evaluated with a validation framework. 2,17 Therapy lines for advNSCLC were based on EHR documentation of systemic anticancer treatments and were generated by rule-based algorithms indexed to the patient's advNSCLC diagnosis date. These rules are objective (based on literature, clinical guidelines, and deep clinical experience) and were applied to treatments actually received, irrespective of order sets or care plans (see Supporting Methods).…”

Concordance of real-world versus conventional progression-free survival from a phase 3 trial of endocrine therapy as first-line treatment for metastatic breast cancer

“…This layer of technology facilitates document classification and visual organization, text search within documents, and selective presentation of relevant documents to trained data abstractors (clinical oncology nurses and tumor registrars). Structured data such as diagnoses, lab values, and medication administrations were mapped to a common terminology and unstructured data (eg, physician notes, lab/radiology reports) underwent manual review [19]. All abstractors received training in the use of the platform as well as indication-specific training (operating procedures, best practice guidelines) prior to beginning the abstraction process.…”

“…The approach to rwP anchors on clinician-documented cancer progression based on an interpretation of the entire patient chart, including results of diagnostic procedures and tests (eg, radiology and pathology reports). [19] The date of cancer progression was defined as the date of the first source evidence for progression referenced by the clinician (eg, radiology report date) or the date of clinician note when no other corresponding evidence sources were documented. A parallel construct reflecting real-world progression-free survival (rwPFS) was calculated, measuring from the start of first-line letrozole therapy through the end of first-line therapy for patients receiving only first-line therapy and to the start of second-line therapy for all other patients.…”