Review of patient-reported outcomes in EMPOWER-Lung 1 in patients with advanced non-small cell lung cancer treated with cemiplimab versus chemotherapy.

INTRODUCTION
Studies evaluating novel therapies for the treatment of cancer typically focus on tumor response and survival outcomes. More recently, patient‐reported outcomes (PROs) are recognized as increasingly important indicators of efficacy outcomes.
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In the clinical setting, assessment of PROs has been associated with patient benefits, such as improved symptom control, patient–physician communication, and satisfaction with care.
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Patients with advanced non‐small cell lung cancer (NSCLC) have a high symptom burden that adversely affects their quality of life (QoL) and functioning.
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,
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Treatments often focus on extending overall survival (OS); however, adverse effects from systemic treatments can negatively affect the QoL of patients with advanced NSCLC by causing distress and hampering further treatment.
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Therefore, when assessing therapies, it is necessary to consider PROs as a key component of benefit–risk profile evaluation.
Cemiplimab, a programmed cell death‐1 inhibitor, improved OS and progression‐free survival (PFS) versus platinum‐doublet chemotherapy in patients who had advanced NSCLC and programmed cell death‐ligand 1 (PD‐L1) expression ≥50% in the EMPOWER‐Lung 1 phase 3 clinical trial (ClinicalTrials.gov identifier NCT03088540).
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Safety data were consistent with what was previously observed with cemiplimab and other PD‐L1 inhibitors in advanced NSCLC and other tumor types, with grade 3–4 treatment‐emergent adverse events observed in 28% of patients who received at least one dose of cemiplimab in the study.
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PROs for the overall study population and in some subpopulations from the EMPOWER‐Lung 1 trial were previously reported and demonstrated improvements in global health status (GHS)/QoL, functioning, and symptom burden.
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Here, we review and summarize previous publications of the effects of cemiplimab monotherapy on PROs in the EMPOWER‐Lung 1 trial, among the overall patient population and in prespecified subgroups of patients within this same trial.

MATERIALS AND METHODS
This review article characterizes PRO findings for cemiplimab monotherapy versus chemotherapy overall and in prespecified subgroups of patients with NSCLC from the EMPOWER‐Lung 1 trial. The subgroups of interest were age,
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,
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geographic region,
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,
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PD‐L1 expression level,
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,
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histology,
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,
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Eastern Cooperative Oncology Group performance status (ECOG PS),
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,
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brain metastasis,
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,
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liver metastasis,
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,
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and locally advanced disease.
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,
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In addition, PRO findings by disease progression
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and objective response
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also are included. This study was performed in accordance with the principles of the Declaration of Helsinki and with Good Clinical Practice guidelines as defined by the International Conference on Harmonization.

EMPOWER‐Lung 1 study
In the phase 3 EMPOWER‐Lung 1 study, adults with advanced NSCLC were randomly assigned 1:1 to receive either cemiplimab 350 mg every 3 weeks or platinum‐doublet chemotherapy.
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The primary end points were OS and PFS, which were assessed in the intent‐to‐treat population and in a prespecified population with PD‐L1 expression ≥50%.
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Patient‐reported QoL was a predefined secondary end point and was analyzed in the prespecified population with ≥50% PD‐L1 expression. Patients were administered multiple PROs, including the European Organization for Research and Treatment of Cancer Quality of Life–Core 30 questionnaire
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at baseline and on day 1 of each treatment cycle for the first six cycles, and then on day 1 every three cycles. Details regarding study methodology, incorporating inclusion and exclusion criteria, have been previously published.
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PRO analyses
The focus of this review was on the GHS/QoL scale from the European Organization for Research and Treatment of Cancer Quality of Life–Core 30 questionnaire. The GHS/QoL scale score ranges from 0 to 100, with higher scores indicating better health‐related QoL. Previously reported PRO findings were based on analyses that included the following:A mixed model for repeated measures (MMRM) analysis to estimate least squares (LS) mean changes from baseline on all scales among patients who had a baseline and one or more postbaseline score.

The time to deterioration (TTD) based on a 10‐point threshold
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was evaluated using Kaplan–Meier analyses and a Cox proportional hazards model for computing hazard ratios (HRs); a stratified log‐rank test was used for comparing the TTD between treatment arms.

All analyses were conducted with SAS version 9.4 software (SAS Institute, Inc.). All p values are two‐sided with no multiplicity adjustments made.

RESULTS

Baseline demographics and characteristics
Overall patient demographics and clinical characteristics for the study population have been previously reported and are summarized in Table 1.
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Change from baseline in GHS/QoL scores by overall and subgroup populations
MMRM analysis of GHS/QoL by overall and prespecified subgroup populations generally favored cemiplimab versus chemotherapy (Figure 1).
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,
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,
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,
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A statistically significant difference in the overall change from baseline in GHS/QoL favoring cemiplimab versus chemotherapy was observed in the overall population (5.03; 95% confidence interval [CI], 2.11–7.96; p = .0008).
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Statistically significant differences also were observed in the following subgroups: both age subgroups younger than 65 years (6.35; 95% CI, 2.86–9.85; p = .0004) and 65 years and older (5.60; 95% CI, 1.56–9.64; p = .0069); the Asian subgroup (12.61; 95% CI, 4.44–20.77; p = .0032) and subgroup that included rest of the world (9.09; 95% CI, 0.89–17.29; p = .0305)
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; the subgroups with PD‐L1 expression from >60% to <90% (6.78; 95% CI, 2.20–11.36; p = .004) and PD‐L1 expression ≥90% (5.67; 95% CI, 1.37–9.96; p = .010)
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; both histology subgroups (squamous: 4.32; 95% CI, 0.55−8.08; p = .0247; nonsquamous: 5.12; 95% CI, 1.39–8.86; p = .0073)
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; and the ECOG PS 1 subgroup (5.03; 95% CI, 1.90–8.15; p = .0017).
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the overall LS mean change in patients with brain metastasis also favored cemiplimab over chemotherapy, with a difference of 9.35 (95% CI, 2.24–16.45; p = .0110
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; Figure 1). The overall change from baseline in GHS/QoL was more favorable with cemiplimab treatment among patients who had locally advanced disease compared with those who received chemotherapy (6.27; 95% CI, 0.62–11.93; p = .0302
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; Figure 1).

Time to clinically meaningful deterioration of GHS/QoL by overall and subgroup populations
TTD analysis of GHS/QoL favored cemiplimab in most prespecified subgroups (Figure 2).
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A statistically significant delay in TTD favoring cemiplimab was observed in GHS/QoL in the subgroup younger than 65 years (HR, 0.52; 95% CI, 0.30–0.91; p = .0195)
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and the subgroup with PD‐L1 expression ≥90% (HR, 0.42; 95% CI, 0.20–0.86; p = .0152
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,
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; Figure 2). A numerical trend favoring cemiplimab was observed in GHS/QoL in the ECOG PS 1 subgroup (HR, 0.66; 95% CI, 0.41–1.08; p = .0949)
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and in the subgroup with PD‐L1 expression from >60% to <90% (HR, 0.62; 95% CI, 0.33–1.17; p = .1336).
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A favorable trend toward cemiplimab was also observed in TTD analysis of GHS/QoL for the overall population (HR, 0.70; 95% CI, 0.48–1.04; p = .0725).
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Change from baseline in GHS/QoL scores by disease progression and objective response
For the two treatment arms combined (the overall population), GHS/QoL scores significantly improved in patients without disease progression versus those with disease progression (difference in LS mean change from baseline, −8.86; 95% CI, −11.61 to −6.12; p < .0001; Figure 3A).
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This pattern was also observed in the cemiplimab (difference in LS mean change from baseline, −8.44; 95% CI, −11.99 to −4.89; p < .0001) and platinum‐doublet chemotherapy (difference in LS mean change from baseline, −8.35; 95% CI, −12.39 to −4.32; p < .0001) arms separately (Figure 3A).
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For the two treatment arms combined (overall population), an overall change from baseline in GHS/QoL significantly favored patients with versus those without an objective response (difference in LS means, 9.71; 95% CI, 6.90–12.52; p < .0001; Figure 3B).
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Overall change from baseline in GHS/QoL significantly favored patients with versus those without an objective response in both the cemiplimab arm (difference in LS means, 9.36; 95% CI, 5.76–12.95; p < .0001) and the chemotherapy arm (difference in LS means, 7.68; 95% CI, 3.65–11.71; p = .0002; Figure 3B).
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Time to clinically meaningful deterioration of GHS/QoL by disease progression and objective response
For the two treatment arms combined (overall population), a significantly higher risk of deterioration (or faster deterioration) in GHS/QoL was observed in patients who had disease progression versus those without (HR, 3.43; 95% CI, 2.13–5.53; p < .0001; Figure 4A).
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Likewise, a significantly greater delay in TTD for GHS/QoL in patients without versus those with disease progression was also observed in the cemiplimab arm (HR, 2.93; 95% CI, 1.64–5.25; p = .0001) and the platinum‐doublet chemotherapy arm (HR, 4.56; 95% CI, 1.79–11.62; p = .0005) separately (Figure 4A).
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Among patients with versus those without an objective response, a significantly greater delay in the TTD of GHS/QoL was observed for the two treatment arms combined (overall population: HR, 0.29; 95% CI, 0.18–0.47; p < .0001; Figure 4B).
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Likewise, a significantly greater delay in the TTD of GHS/QoL among patients who had an objective response was observed in both the cemiplimab arm (HR, 0.33; 95% CI, 0.18–0.58; p < .0001) and the chemotherapy arm compared with those who did not have an objective response (HR, 0.25; 95% CI, 0.11–0.60; p = .0008) (Figure 4B).
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DISCUSSION
The American Society of Clinical Oncology Value Framework in the advanced disease setting and the European Society for Medical Oncology Magnitude of Clinical Benefit Scale guidance highlight the importance of a comprehensive assessment of the value of medicine that includes not only efficacy and safety but also QoL.
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The improvement, maintenance, and/or delay in the deterioration of QoL are important goals in patients who have advanced NSCLC, for whom treatment is palliative. To our knowledge, this is the first review conducted of PROs of treatment with an immune checkpoint inhibitor in advanced NSCLC across a broad list of subgroups.
Our study reviews PRO data from various patient subgroups from EMPOWER‐Lung 1. Patients with advanced NSCLC with PD‐L1 expression ≥50% who received first‐line cemiplimab monotherapy demonstrated a favorable improvement in PROs compared with chemotherapy across a diverse set of clinically relevant subgroups. Results from these subgroup analyses were consistent with the previously reported PRO results in the overall study population.
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Significant improvements favoring cemiplimab compared with chemotherapy were observed in GHS/QoL in the overall patient population and in most of the subgroups. Significant delays in TTD of GHS/QoL also favored cemiplimab compared with chemotherapy in some subgroups.
Approximately 26% of patients with advanced NSCLC have brain metastases, with detrimental effects on patients' QoL.
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The significant overall improvements in GHS/QoL among patients in the EMPOWER‐Lung 1 trial who had treated, clinically stable brain metastases substantiates cemiplimab monotherapy as a suitable treatment option for this subgroup.
Clinical outcomes for patients with squamous NSCLC treated with immunotherapy are generally poorer than for patients with nonsquamous NSCLC, and those with squamous histology have fewer treatment options. Patients with squamous NSCLC typically have disease characteristics like older age, more extensive disease burden, and an unfavorable localization of the tumor at diagnosis.
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The significant overall improvements in GHS/QoL among the EMPOWER‐Lung 1 subgroup of patients with squamous histology further expands the clinical evidence base for cemiplimab as an effective treatment for patients with advanced NSCLC of squamous histology.
In addition, a poorer ECOG PS has been associated with worse outcomes and substantial burden on QoL from lung cancer.
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Although 73% and 27% of patients in EMPOWER‐Lung 1 had an ECOG PS of 1 and 0, respectively, the consistently favorable overall improvement and delayed TTD in GHS/QoL observed in both of these subgroups from EMPOWER‐Lung 1 further support a QoL benefit with cemiplimab.
A limitation of this study was the relatively small numbers of patients in the brain metastasis, liver metastasis, and locally advanced disease subgroups. Therefore, there were not enough deterioration events to perform TTD analyses in these subgroups. Also, whereas some estimated HRs strongly favored cemiplimab over chemotherapy (e.g., an HR of 0.66 in the ECOG PS 1 subgroup), they did not reach statistical significance. This is likely because of the small sample sizes, which is a common issue in subgroup analyses. With the advent of the potential of artificial intelligence to improve health care decision‐making, future research could integrate findings from research like ours to develop artificial intelligence‐supported predictive tools in oncology using real‐world PRO data. Such artificial intelligence‐supported PRO tools may assist clinicians in tailoring therapeutic decisions for patients receiving immunotherapies, enhancing the personalization of patient‐centered care.
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Collectively, these data support the additional benefit of first‐line cemiplimab monotherapy in GHS/QoL overall and for multiple subpopulations of patients who have advanced NSCLC with PD‐L1 expression ≥50%. Previous reports have described the clinical benefit of cemiplimab in the overall study population as well as in multiple patient subgroups, such as patients who have brain metastasis, locally advanced disease, and squamous histology.
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Results of the analyses described in the current report provide more insight into the effect of cemiplimab on QoL among patients with different baseline characteristics, highlighting the importance of investigating patients' QoL in addition to survival and tumor regression benefits and bolstering support for future PRO studies in the real‐world setting.
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AUTHOR CONTRIBUTIONS

David R. Gandara: Investigation, resources, and writing–review and editing. Mahmut Gümüş: Investigation, resources, and writing–review and editing. Saadettin Kilickap: Investigation, resources, and writing–review and editing. Ahmet Sezer: Investigation, resources, and writing–review and editing. Igor Bondarenko: Investigation, resources, and writing–review and editing. Mustafa Özgüroğlu: Investigation, resources, and writing–review and editing. Miranda Gogishvili: Investigation, resources, and writing–review and editing. Eric Yan: Conceptualization, methodolgy, writing–original draft, writing–review and editing, visualization, supervision, project administration, and funding acquisition. Xue Jia: Validation and writing–review and editing. Eric Kim: Writing–review and editing. Frank Seebach: Writing–review and editing. Ruben G. W. Quek: Conceptualization, methodology, writing–original draft, writing–review and editing, visualization, supervision, project administration and funding acquisition,

CONFLICT OF INTEREST STATEMENT
David R. Gandara reports institutional research support from Amgen Inc., Astex, AstraZeneca, Exact Sciences, IO Biotech, Genentech, Guardant Health, and OncoHost; personal/consulting fees from AdaGene, Foundation Medicine Inc., Henlius USA, and Sanofi; and advisory board fees from AbbVie, Janssen Pharmaceuticals, Merck, Mirati Therapeutics, Regeneron Pharmaceuticals Inc., and Revolution Medicine outside the submitted work. Mahmut Gümüş reports institutional research funding from Amgen and F. Hoffmann‐La Roche; institutional honoraria from MSD Oncology; personal/consulting or advisory fees from AbbVie, Amgen, Daiichi Sankyo Company, Eli Lilly and Company, Gen Ilac, Janssen Pharmaceuticals, Novartis, and Roche; speakers' bureau fees from MSD Oncology, Novartis, and Roche; support for other professional activities from Astellas Pharma, AstraZeneca, Bristol Myers Squibb Company, Gilead Sciences (aka Gilead Foundation), Merck, Novartis, Pfizer, Regeneron Pharmaceuticals Inc., and Takeda Oncology; and travel, accommodations, and expenses from Amgen, AstraZeneca, F. Hoffmann‐La Roche, Pfizer, Regeneron Pharmaceuticals Inc., and Sandoz outside the submitted work. Saadettin Kilickap reports personal/consulting or advisory fees from at MSD Oncology, Pfizer, Roche, and Takeda; and speakers' bureau fees from MSD Oncology, Pfizer, and Roche outside the submitted work. Ahmet Sezer reports institutional research funding from Merck Serono, MSD Oncology, Novartis, Pfizer, and Regeneron Pharmaceuticals, Inc.; institutional honoraria from Pfizer and Roche; speakers' bureau fees from Amgen, Bristol Myers Squibb Company, Pfizer, and Roche; and travel, accommodations, and expenses from Amgen, Bristol Myers Squibb Company, and Roche outside the submitted work. Miranda Gogishvili reports honoraria from Regeneron Pharmaceuticals, Inc., outside the submitted work. Mustafa Özgüroğlu reports personal/consulting or advisory fees from AstraZeneca and MSD Oncology; speakers' bureau fees from AstraZeneca; travel, accommodations, and expenses from AstraZeneca; and honoraria from Astellas Pharma, Janssen Oncology, and Novartis outside the submitted work. Eric Yan is an employee of Cyan Global, Inc. Xue Jia is an employee of Parexel International. Eric Kim, Frank Seebach, and Ruben G. W. Quek are employees of Regeneron Pharmaceuticals, Inc., and own shares in the company. The remaining authors disclosed no conflicts of interest.