ArticleCancer medicine2022
A novel LASSO-derived prognostic model predicting survival for non-small cell lung cancer patients with M1a diseases.
Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Prognostic factors and survival prediction for patients with metastatic lung adenocarcinoma: A population-based study.Medicine · 2022Trial
- Development and multicenter validation of a predictive model for malignant pleural effusion recurrence.iScience · 2026Article
- Machine learning-based LASSO-Cox model for dementia prediction: The role of midlife cardiometabolic, inflammatory, and genetic risk factors in a US cohort.Annals of epidemiology · 2026Article
- SIRPA, BTN3A1, and TDO2 in osteosarcoma: a prognostic triad with therapeutic implications from integrated genomic and pharmacogenomic data.Journal of orthopaedic surgery and research · 2025Article
- LASSO-derived prognostic model predicts cancer-specific survival in advanced pancreatic ductal adenocarcinoma over 50 years of age: a retrospective study of SEER database research.Frontiers in oncology · 2023Article
- A novel LASSO-derived prognostic model predicting survival for non-small cell lung cancer patients with M1a diseases.Cancer medicine · 2022Article
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe current American Joint Committee on Cancer (AJCC) M1a staging of non-small cell lung cancer (NSCLC) encompasses a wide disease spectrum, showing diverse prognosis.
methodsPatients who diagnosed in an earlier period formed the training cohort, and those who diagnosed thereafter formed the validation cohort. Kaplan-Meier analysis was performed for the training cohort by dividing the M1a stage into three subgroups: (I) malignant pleural effusion (MPE) or malignant pericardial effusion (MPCE); (II) separate tumor nodules in contralateral lung (STCL); and (III) pleural tumor nodules on the ipsilateral lung (PTIL). Gender, age, histologic, N stage, grade, surgery for primary site, lymphadenectomy, M1a groups, and chemotherapy were selected as independent prognostic factors using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. And a nomogram was constructed using Cox hazard regression analysis. Accuracy and clinical practicability were separately tested by Harrell's concordance index, the receiver operating characteristic (ROC) curve, calibration plots, residual plot, the integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA).
resultsThe concordance index (0.661 for the training cohort and 0.688 for the validation cohort) and the area under the ROC curve (training cohort: 0.709 for 1-year and 0.727 for 2-year OS prediction; validation cohort: 0.737 for 1-year and 0.734 for 2-year OS prediction) indicated satisfactory discriminative ability of the nomogram. Calibration curve and DCA presented great prognostic accuracy, and clinical applicability. Its prognostic accuracy preceded the AJCC staging with evaluated NRI (1-year: 0.327; 2-year: 0.302) and IDI (1-year: 0.138; 2-year: 0.130).
conclusionOur study established a nomogram for the prediction of 1- and 2-year OS in patients with NSCLC diagnosed with stage M1a, facilitating healthcare workers to accurately evaluate the individual survival of M1a NSCLC patients. The accuracy and clinical applicability of this nomogram were validated.
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