Evidence map›Paper›PMID 37166346›Full record

ArticleOncology2023

The Glasgow Prognostic Score Predicts Survival in Patients with Advanced Non-Small Cell Lung Cancer Harboring Sensitive Epidermal Growth Factor Receptor Mutations Who Are Treated with Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitors.

Yuki Akazawa, Satoshi Igawa, Kaori Yamada, Hiroki Yamamoto, Yuri Yagami, Nobuki Kaizuka, Hiroya Manaka, Masashi Kasajima, Yoshiro Nakahara, Takashi Sato and 5 more

Open access · hybridAbstract read
In one paragraph

Article in Oncology, 2023. 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
1.0field-weighted citation impact, top 22% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

15 authors at 1 institution in 1 country.

Yuki AkazawaDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Satoshi IgawaDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Kaori YamadaDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Hiroki YamamotoDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Yuri YagamiDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Nobuki KaizukaDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Hiroya ManakaDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Masashi KasajimaDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Yoshiro NakaharaDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Takashi SatoDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Hisashi MitsufujiKitasato University School of Nursing, Sagamihara, Japan.
Masanori YokobaSchool of Allied Health Sciences, Kitasato University, Sagamihara, Japan.
Masaru KubotaSchool of Allied Health Sciences, Kitasato University, Sagamihara, Japan.
Jiichiro SasakiResearch and Development Center for New Medical Frontiers, Kitasato University School of Medicine, Sagamihara, Japan.
Katsuhiko NaokiDepartment of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
Kitasato University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEpidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) with sensitive EGFR mutations. The Glasgow prognostic score (GPS) is an inflammation-assessing score based on C-reactive protein and albumin concentrations. Information regarding the association between the GPS and EGFR-TKI treatment effectiveness is limited; hence, we investigated whether the GPS can predict the response of NSCLC to EGFR-TKIs.

methodsWe evaluated 340 patients with NSCLC harboring sensitive EGFR mutations who received EGFR-TKI monotherapy between March 2009 and July 2021. The Kaplan-Meier method and Cox proportional hazards models were used to assess progression-free survival (PFS) and overall survival (OS).

resultsAfter a median follow-up of 26.6 months, patients with a GPS of 0, 1, and 2 had PFS of 15.7, 10.0, and 6.3 months, respectively, and OS of 40.1, 25.8, and 14.4 months, respectively; patients with a GPS of 0 had significantly better PFS and OS than those with a GPS of 1 (p = 0.03, p = 0.001, respectively) or 2 (p < 0.001, p < 0.001, respectively). Multivariate analysis identified poor performance status, stage 4 at diagnosis, type of EGFR-TKI (gefitinib/erlotinib vs. afatinib), and GPS = 2 as predictors of a short PFS. Meanwhile, poor performance status, gefitinib/erlotinib administration, and GPS = 2 were predictors of a short OS.

conclusionThe GPS predicted the survival of NSCLC patients harboring sensitive EGFR mutations who were undergoing EGFR-TKI treatment. The GPS might be ideal for routine use in clinical practice, given that it is an easily calculated parameter.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsErbB ReceptorsErlotinib HydrochlorideGefitinibHumansMutationPrognosisProtein Kinase InhibitorsRetrospective StudiesTyrosine Kinase InhibitorsErbB ReceptorsErlotinib HydrochlorideGefitinibProtein Kinase InhibitorsTyrosine Kinase InhibitorsEpidermal growth factor receptorGlasgow prognostic scoreNon-small cell lung cancerTyrosine kinase inhibitors

Identifiers

PMID37166346
PMCPMC10614514
OpenAlexW4366976856

What Socratic holds

Textmetadata
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 Socratic graph.