Identification and validation of the model consisting of DDX49, EGFR, and T-stage as a possible risk factor for lymph node metastasis in patients with lung cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37096455", "kind": "science-record", "revision": 4, "content_hash": "sha256:a360e139e826a53ef7dd42a10dbb9a2b956ead7fa40e010e8a7f2de6806dfc55", "created_at": "2026-11-01T19:01:46Z", "updated_at": "2026-11-01T22:51:46Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of the model consisting of DDX49, EGFR, and T-stage as a possible risk factor for lymph node metastasis in patients with lung cancer.", "doi": "10.1111/1759-7714.14892", "pmid": "37096455", "authors": ["Zhimin Zhang", "Xiaojuan Lian", "Hongxu Yue", "Debing Xiang", "Zhongxi Niu"], "journal": "Thoracic cancer", "year": 2023, "abstract": "INTRODUCTION: The lymph node metastasis stage of lung cancer is an important decisive factor in the need for postoperative adjuvant treatment and the difference between stage IIIa and stage IIIB that is the necessary information to distinguish whether surgery can be performed or not. The specificity of the clinical diagnosis of lung cancer with lymph node metastasis cannot meet the requirements of preoperative evaluation of surgical indications and prediction of surgical removal range in lung cancer.\nMETHODS: This was an early experimental laboratory trial. The model identification data included the RNA sequence data of 10 patients from our clinical data and 188 patients with lung cancer from The Cancer Genome Atlas dataset. The model development and validation data consisted of RNA sequence data for 537 cases from the Gene Expression Omnibus dataset. We explore the predictive value of the model on two independent clinical data.\nRESULTS: A higher specificity of diagnostic model for patients with lung cancer with lymph node metastases consisted of DDX49, EGFR, and tumor stage (T-stage), which were the independent predictive factors. The area under the curve value, specificity, and sensitivity for predicting lymph node metastases were 0.835, 70.4%, and 78.9% at RNA expression level in the training group, and 0.681, 73.2%, and 75.7% at RNA expression level in the validation group as shown as in result part. To verify the predictive performance of the combined model for lymph node metastases, we downloaded the GSE30219 data set (n = 291) and the GSE31210 data set (n = 246) from the Gene Expression Omnibus (GEO) database as the training group and validation group, respectively. In addition, the model had a higher specificity for predicting lymph node metastases in independent tissue samples.\nCONCLUSIONS: Determination of DDX49, EGFR, and T-stage could form a novel prediction model to improve the diagnostic efficacy of lymph node metastasis in clinical application.", "claims": [{"id": "claim-method", "statement": "Independent predictors for lymph node metastasis were analyzed by stepwise logistic regression analysis, with age, gender, histology, T‐ and clinical stage, and nine candidate genes as initial covariates.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37096455", "locator": "sections[9] \"Statistical analysis\" paragraph 2", "quote": "Independent predictors for lymph node metastasis were analyzed by stepwise logistic regression analysis, with age, gender, histology, T‐ and clinical stage, and nine candidate genes as initial covariates."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data and materials will be shared.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37096455", "locator": "sections[22] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "Data and materials will be shared."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The combined DDX49, EGFR, and T-stage model showed an AUC of 0.835 in the training group and 0.681 in the validation group for predicting lymph node metastases.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37096455", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The area under the curve value, specificity, and sensitivity for predicting lymph node metastases were 0.835, 70.4%, and 78.9% at RNA expression level in the training group, and 0.681, 73.2%, and 75.7% at RNA expression level in the validation group as shown as in result part."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The combined DDX49, EGFR, and T-stage model showed an AUC of 0.835 in the training group and 0.681 in the validation group for predicting lymph node metastases.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37096455"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE30219"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE30219"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37096455", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1111/1759-7714.14892", "sha256": 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