Evidence map›Paper›PMID 40948851›Full record

ArticleTranslational lung cancer research2025

International cost-effectiveness analysis of durvalumab consolidation treatment after chemoradiotherapy for patients with limited-stage small-cell lung cancer.

Kun Liu, Youwen Zhu, Hong Zhu

Abstract read
In one paragraph

Article in Translational lung cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kun LiuDepartment of Oncology, Xiangya Hospital, Central South University, Changsha, China.
Youwen ZhuDepartment of Oncology, Xiangya Hospital, Central South University, Changsha, China.
Hong ZhuDepartment of Oncology, Xiangya Hospital, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The recently conducted ADRIATIC trial demonstrated that adding durvalumab led to significant improvements in the survival of non-advanced limited-stage small cell lung cancer (LS-SCLC) following concurrent chemoradiotherapy (CCRT). While efficacious, immunotherapeutic drugs are associated with high costs. Therefore, the purpose of this study is to conduct pharmacoeconomic analyses of the cost-effectiveness of durvalumab consolidation treatment after CCRT for LS-SCLC from the perspective of payers in specific countries. Methods: The costs and efficacy of consolidation durvalumab versus placebo treatment following CCRT for LS-SCLC patients were analyzed using a three-state Markov model. The lifetime direct medical costs, incremental cost-effectiveness ratios (ICERs), incremental cost-utility ratios (ICURs), and incremental net-health benefit (INHB) associated with these treatment strategies were evaluated from the perspective of payers in China and the USA (the primary source countries for patients in the ADRIATIC trial) at respective willingness-to-pay (WTP) thresholds of $37,023 and $150,000 per quality-adjusted life-year (QALY). Sensitivity and subgroup analyses were used to assess model stability. Results: Durvalumab consolidation was associated with 2.24 and 2.80 incremental QALYs relative to placebo for patients in China and the USA, but it was also associated with significant increases in lifetime medical costs ($48,511 Conclusions: Durvalumab consolidation following CCRT represents a cost-effective option for the treatment of LS-SCLC patients in China and the USA.

Indexed as

chemoradiotherapyconsolidation treatmentcost-effectivenessdurvalumabLimited-stage small cell lung cancer (LS-SCLC)

Identifiers

PMID40948851
PMCPMC12432599

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.