Evidence map›Paper›PMID 37642080›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2023

Predicting EGFR Mutation in Lung Adenocarcinoma: Development and Validation of the EGFR Mutation Predictive Score (EMPS) in Bali, Indonesia.

Edwin Nugroho Njoto, Ida Ayu Jasminarti Dwi Kusumawardani, Ida Bagus Ngurah Rai

Abstract read
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Article in Asian Pacific journal of cancer prevention : APJCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Edwin Nugroho NjotoMedical Study Program, Faculty of Medicine and Health, Sepuluh November Institute of Technology, Surabaya, East Java, Indonesia.ORCID 0000-0001-6903-3407
Ida Ayu Jasminarti Dwi KusumawardaniDepartment of Pulmonary Medicine, Faculty of Medicine, Udayana University / Prof IGNG Ngoerah General Hospital, Denpasar, Bali, Indonesia.
Ida Bagus Ngurah RaiDepartment of Pulmonary Medicine, Faculty of Medicine, Udayana University / Prof IGNG Ngoerah General Hospital, Denpasar, Bali, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe examination of epidermal growth factor receptor (EGFR) mutations may not be routinely available to all patients due to the limited availability and the expensive price of the examination, especially in area with limited resources such as in Indonesia. Therefore, we aimed to build a nomogram to predict the EGFR mutation in patients with lung adenocarcinoma by incorporating significant clinical and radiological parameters.

methodsWe conducted an age-matched case-control study using 160 treatment-naïve patients [80 patients with EGFR-mutated (EGFRmut) and 80 with EGFR-wild-type (EGFRwt)] with pathologically confirmed lung adenocarcinomas with tumor specimens available for genetic analysis taken from 2017 through 2021 in Bali, Indonesia. Radiomics features were extracted from contrast CT images. The cut-off of the tumor diameter was defined using Receiver Operating Characteristic Curve. A conditional logistic regression model was constructed to identify significant risk factors, and a nomogram was developed for predicting the risk of EGFR mutation. A cohort was done to validate the nomogram.

resultBeing female, never-smoker, having a smaller tumor diameter (<48.5mm), located in the upper lobe, have bubble-like lucency and air-bronchogram in the chest CT scan were identified as independent risk factors of EGFR mutation at the multivariate logistic regression model. The forming normogram model produced an area under the curve of 0.993 (95 % CI = 0.98-1.00) and 0.91 (95 % CI = 0.84-0.99) in development and validation group, respectively. The calibration curve showed good agreement between predicted and actual probability. At the cut-off point of the normogram score 246 shows a sensitivity of 97.5%, a specificity of 98.8%, a positive predictive value of 99.0%, and a negative predictive value of 96.8%.

conclusionOur study indicated that the EGFR Mutation Normogram could provide a non-invasive way to predict the risk of EGFR mutation in patients with lung adenocarcinoma in clinical practice. This normogram need to be validated in other area in Indonesia.

Indexed as

Adenocarcinoma of LungLung NeoplasmsCase-Control StudiesErbB ReceptorsFemaleHumansIndonesiaMaleMutationRisk FactorsEGFR protein, humanErbB ReceptorsAdenocarcinoma of LungEGFR mutationIndonesiaNomograms

Identifiers

PMID37642080
PMCPMC10685208

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