Evidence map›Paper›PMID 32877435›Full record

SynthesisPloS one2020

Cost effectiveness of immune checkpoint inhibitors for treatment of non-small cell lung cancer: A systematic review.

Haiying Ding, Wenxiu Xin, Yinghui Tong, Jiao Sun, Gaoqi Xu, Ziqi Ye, Yuefeng Rao

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 7% of its field
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

37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Haiying DingDepartment of Pharmacy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Wenxiu XinDepartment of Pharmacy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Yinghui TongDepartment of Pharmacy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Jiao SunDepartment of Pharmacy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Gaoqi XuDepartment of Pharmacy, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Ziqi YeDepartment of Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Yuefeng RaoDepartment of Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.ORCID 0000-0002-3098-2768
Zhejiang Cancer Hospital · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmune checkpoint inhibitors (ICIs) for treatment of non-small cell lung cancer (NSCLC) have been rapidly evolving. ICIs are likely to be more effective but also lead to escalating healthcare costs.

objectivesThe aim of this study was to evaluate the cost effectiveness of immune checkpoint inhibitors (ICIs) for treatment of non-small cell lung cancer (NSCLC).

methodsWe searched the PubMed, Web of Science, and Cochrane Library for studies comparing the cost effectiveness of ICIs for NSCLC. Potential studies identified were independently checked for eligibility by two authors, with disagreement resolved by a third reviewer. Quality of the included studies was evaluated using Consolidated Health Economic Evaluation Reporting Standards checklists.

resultsA total of 22 economic studies were included. Overall reporting of the identified studies largely met CHEERS recommendations. In the first-line setting, for advanced or metastatic NSCLC patients with PD-L1 ≥ 50%, pembrolizumab appeared cost-effective compared with platinum-based chemotherapy in the US and Hong Kong (China), but not in the UK and China. The cost-effectiveness of pembrolizumab versus chemotherapy for first-line treatment of NSCLC in PD-L1 ≥ 1% patients remained obscure. Regardless of PD-L1 expression status, pembrolizumab in combination with chemotherapy could be a cost-effective first-line therapy in the US. On the contrary, addition of atezolizumab to the combination of bevacizumab and chemotherapy was not cost-effective for patients with metastatic non-squamous NSCLC from the US payer perspective. In the second-line setting compared with docetaxel, pembrolizumab was cost-effective; though nivolumab was not cost-effective in the base case, it could be by increased PD-L1 threshold. Results of the cost-effectiveness of atezolizumab second-line treatment remained inconsistent. In addition, the adoption of durvalumab consolidation therapy after chemoradiotherapy could be cost-effective versus no consolidation therapy for patients with stage III NSCLC.

conclusionsImmunotherapy can be a cost-effective option for treatment of NSCLC in several scenarios. A discount of the agents or the use of PD-L1 expression as a biomarker improves the cost-effectiveness of immunotherapy.

Indexed as

Cost-Benefit AnalysisImmunotherapyAntineoplastic Agents, ImmunologicalCarcinoma, Non-Small-Cell LungHumansLung NeoplasmsAntineoplastic Agents, Immunological

Identifiers

PMID32877435
PMCPMC7467260
OpenAlexW3081615089

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.