Survival prediction in mesothelioma using a scalable Lasso regression model: instructions for use and initial performance using clinical predictors

BMJ Open Respiratory Research
Andrew C KiddKevin G Blyth

Abstract

Accurate 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. Data 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 DXYstatistic, which varies from 0 to 1, with increasing concordance between observed and predicted outcomes. 6-month survival and 12-month survival were described by area under the curve (AUC) scores. Median 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 DXY0.332 (±0.019)). However, validation set DXYwas only 0.221 (0.0935-0.346), equating to a 22% improvement in survival prediction than would be expected by ch...Continue Reading

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Citations

Oct 9, 2019·Current Opinion in Supportive and Palliative Care·Andrew C KiddKevin G Blyth
Jun 5, 2020·Acta Neurologica Scandinavica·Pingping NingYanming Xu
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Jan 29, 2021·Frontiers in Oncology·Xin-Bin PanXiao-Dong Zhu
Mar 6, 2021·International Journal of Chronic Obstructive Pulmonary Disease·Yide WangFeng-Sen Li
Mar 11, 2021·BioMed Research International·Shu-Ping ZhouChun-Yang Zhao
Jun 4, 2021·Diabetes, Metabolic Syndrome and Obesity : Targets and Therapy·Huanhuan ZhaoZhangsuo Liu
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Aug 13, 2021·The Journal of International Medical Research·Yukun WuBin Huang

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glmnet
MPM

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