ArticleBMJ open respiratory research2018
Survival prediction in mesothelioma using a scalable Lasso regression model: instructions for use and initial performance using clinical predictors.
Article in BMJ open respiratory research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers.
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Who cites it
123 citing papers in PubMed.
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- Development and validation of a nomogram prediction model for cardiovascular comorbidities in COPD patients based on hypertension.Frontiers in medicine · 2026Article
- Leveraging environmental information for enhanced prediction of cardiac readmissions.iScience · 2025Article
- Construction of a predictive model for relapse of primary autoimmune hemolytic anemia: a retrospective cohort study.Annals of medicine · 2025Article
- The role of the infrapatellar fat pad in osteoporotic knee osteoarthritis: bone-fat crosstalk: cross-sectional studies.Journal of orthopaedic surgery and research · 2025Article
- The Causal Relationship and Association between Biomarkers, Dietary Intake, and Diabetic Retinopathy: Insights from Mendelian Randomization and Cross-Sectional Study.Diabetes & metabolism journal · 2025Article
- Predicting the risk of lymph node metastasis in colon cancer: development and validation of an online dynamic nomogram based on multiple preoperative data.BMC gastroenterology · 2025Article
- Predictive Effect of FT3 Within the Euthyroid Range on HDL-C in Patients With Type 2 Diabetes: A Cross-Sectional Analysis of Inpatients in China.Journal of clinical laboratory analysis · 2025Article
- The role of serun lipid, cytokine production in sudden sensorineural hearing loss.Cytotechnology · 2025Article
- Factors contributing to perioperative blood transfusion during total hip arthroplasty in patients continuing preoperative aspirin treatment: a nomogram prediction model.BMC musculoskeletal disorders · 2025Article
- Machine Learning-Based Prediction Model for Predicting the Effect of the Serum γKlotho Level on Susceptibility to Coronary Heart Disease.Vascular health and risk management · 2025Article
- Causal Effects Between Retinal Characteristics and Cardiovascular Diseases: Insights from Genetic Correlation, Mendelian Randomization, and Cross-Sectional Study.Global heart · 2025Article
- Development and validation of a predictive model for acute myelitis secondary to hyperextension-induced spinal cord injury in pediatric patients.Frontiers in neurology · 2025Article
- Development and Validation of a Dynamic Online Nomogram for Predicting Inpatient Fall Risk: A Cohort Study.Journal of multidisciplinary healthcare · 2025Article
- A study on predicting impaired fasting glucose risk in Chinese adults based on individual characteristics.Frontiers in medicine · 2025Article
63 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
introductionAccurate prognostication is difficult in malignant pleural mesothelioma (MPM). We developed a set of robust computational models to quantify the prognostic value of routinely available clinical data, which form the basis of published MPM prognostic models.
methodsData regarding 269 patients with MPM were allocated to balanced training (n=169) and validation sets (n=100). Prognostic signatures (minimal length best performing multivariate trained models) were generated by least absolute shrinkage and selection operator regression for overall survival (OS), OS <6 months and OS <12 months. OS prediction was quantified using Somers D
resultsMedian OS was 270 (IQR 140-450) days. The primary OS model assigned high weights to four predictors: age, performance status, white cell count and serum albumin, and after cross-validation performed significantly better than would be expected by chance (mean D
conclusionsThe prognostic value of the basic clinical information contained in these, and previously published models, is fundamentally of limited value in accurately predicting MPM prognosis. The methods described are suitable for expansion using emerging predictors, including tumour genomics and volumetric staging.
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