Immune checkpoint inhibitors improve outcomes compared to chemotherapy in lung cancer. Tumor PD-L1 receptor expression is being studied as a predictive biomarker. The objective of this study was to assess the cost-effectiveness and economic impact of second-line treatment with nivolumab, pembrolizumab, and atezolizumab with and without the use of PD-L1 testing for patient selection.
We developed a decision-analytic model to determine the cost-effectiveness of PD-L1 assessment and second-line immunotherapy versus docetaxel. The model used outcomes data from randomized clinical trials (RCTs) and drug acquisition costs from the United States. Thereafter, we used epidemiologic data to estimate the economic impact of the treatment.
We included four RCTs (2 with NIVOLUMAB, 1 with PEMBROLIZUMAB, and 1 with ATEZOLIZUMAB). The incremental QALY for nivolumab was 0.417 among squamous tumors and 0.287 among non-squamous tumors and the ICER were $155,605 and $187,685, respectively. The QALY gain in the base case for atezolizumab was 0.354 and the ICER was $215,802. Compared with treating all patients, the selection of patients by PD-L1 expression improved incremental QALY by up to 183% and decreased the ICER by up to 65%. Pembrolizumab was studied only in patients whose tumors expressed PD-L1. The QALY gain was 0.346 and the ICER was $98,421. Patient selection also reduced the budget impact of immunotherapy.
The use of PD-L1 expression as a biomarker increases cost-effectiveness of immunotherapy but also diminishes the number of potential life-years saved.
Pharmacology, Toxicology and Pharmaceutical Science
18
13%
Biochemistry, Genetics and Molecular Biology
11
8%
Economics, Econometrics and Finance
9
6%
Nursing and Health Professions
4
3%
Other
15
10%
Unknown
46
32%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 23. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 September 2026.
All research outputs
#2,099,656
of 34,536,218 outputs
Outputs from Annals of Oncology
#1,264
of 10,383 outputs
Outputs of similar age
#30,344
of 356,044 outputs
Outputs of similar age from Annals of Oncology
#38
of 314 outputs
Altmetric has tracked 34,536,218 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,383 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 356,044 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 314 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.
