Evidence map›Paper›PMID 37713583›Full record

ArticleAnnals of medicine2023

LAPS score for individualized treatment of advanced EGFR-mutated non-small cell lung cancer receiving EGFR-TKIs with or without bevacizumab.

Yahua Wu, Bin Du, Chengliu Lv, Xiaohui Ji, Jinhuo Lai

Open access · goldAbstract read
In one paragraph

Article in Annals of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 5 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

5 authors at 3 institutions in 1 country.

Yahua WuDepartment of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, P.R. China.
Bin DuDepartment of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, P.R. China.
Chengliu LvDepartment of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, P.R. China.
Xiaohui JiDepartment of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, P.R. China.
Jinhuo LaiDepartment of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, P.R. China.
Fujian Medical University · CNChongqing Cancer Hospital · CNUnion Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo establish a risk stratification score to facilitate individualized treatment for patients with advanced epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC).

methodsWe enrolled 160 advanced EGFR-mutated NSCLC who received first-generation EGFR-tyrosine kinase inhibitor (EGFR-TKI) with or without bevacizumab. Kaplan-Meier curves were used for survival analysis. Univariate and multivariate analyses were used to identify independent prognostic factors associated with progression-free survival (PFS) and overall survival (OS).

resultsThere were 107 patients in EGFR-TKI monotherapy (T group) and 53 patients in EGFR-TKI with bevacizumab (A + T group). The median PFS in the A + T group was significantly longer than that in the T group (

conclusionsNovel LAPS score may help to facilitate individualized treatment of advanced EGFR-mutated NSCLC receiving EGFR-TKI with or without bevacizumab.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsTyrosine Kinase InhibitorsAlbuminsBevacizumabErbB ReceptorsHumansAlbuminsBevacizumabEGFR protein, humanErbB ReceptorsTyrosine Kinase InhibitorsEGFR mutationIndividualized treatmentLAPS scoreNon-small cell lung cancerRisk stratification

Identifiers

PMID37713583
PMCPMC10506427
OpenAlexW4386765381

What OpenQuestion holds

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LicenceCC BY-NC
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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.