Evidence map›Paper›PMID 38965530›Full record

SynthesisJournal of cardiothoracic surgery2024

Durvalumab supplementation for non-small-cell lung cancer: a meta-analysis study.

Chengchen Wang, Hongyi Fu, Feng Wang

Abstract readMeta-Analysis
In one paragraph

Synthesis in Journal of cardiothoracic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Chengchen Wang *Department of Oncology Radiotherapy Center, Chongqing University Cancer Hospital, Chongqing, 400030, China. wcc19930503@163.com.
Hongyi Fu *Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400042, China.
Feng WangDepartment of Oncology Radiotherapy Center, Chongqing University Cancer Hospital, Chongqing, 400030, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDurvalumab supplementation may have some potential in improving the efficacy in patients with non-small-cell lung cancer (NSCLC), and this meta-analysis aims to explore the impact of durvalumab supplementation on efficacy for NSCLC.

methodsPubMed, EMbase, Web of science, EBSCO, and Cochrane library databases were systematically searched, and we included randomized controlled trials (RCTs) assessing the effect of durvalumab supplementation on efficacy in patients with NSCLC. Overall survival and progression-free survival were included for this meta-analysis.

resultsFour RCTs were finally included in the meta-analysis. Overall, compared with control group for NSCLC, durvalumab supplementation showed significantly improved survival rate (odd ratio [OR] = 1.64; 95% confidence interval [CI] = 1.31 to 2.06; P < 0.0001), overall survival ( hazard ratio [HR] = 0.73; 95% CI = 0.61 to 0.87; P = 0.0003), progression-free survival rate (OR = 2.31; 95% CI = 1.78 to 3.01; P < 0.00001) and progression-free survival (HR = 0.71; 95% CI = 0.54 to 0.95; P = 0.02), and had the capability to reduce the incidence of grade ≥ 3 adverse events (OR = 0.26; 95% CI = 0.16 to 0.42; P < 0.00001).

conclusionsDurvalumab supplementation is effective to improve the efficacy for NSCLC.

Indexed as

Antibodies, MonoclonalCarcinoma, Non-Small-Cell LungLung NeoplasmsAntineoplastic Agents, ImmunologicalHumansRandomized Controlled Trials as TopicAntibodies, MonoclonalAntineoplastic Agents, ImmunologicaldurvalumabDurvalumabNSCLCOverall survivalProgression-free survival

Identifiers

PMID38965530
PMCPMC11223428

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.