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QoL publications

QoL publications
Quantile regression and empirical likelihood for the analysis of longitudinal data with monotone missing responses due to dropout, with applications to quality of life measurements from clinical trials.
 
Lv Y, Qin G, Zhu Z, Tu D. Statist Med 38: 2972-91, 2019.
 
 
The analysis of quality of life (QoL) data can be challenging due to the skewness of responses and the presence of missing data. In this paper, we propose a new weighted quantile regression method for estimating the conditional quantiles of QoL data with responses missing at random. The proposed method makes use of the correlation information within the same subject from an auxiliary mean regression model to enhance the estimation efficiency and takes into account of missing data mechanism. The asymptotic properties of the proposed estimator have been studied and simulations are also conducted to evaluate the performance of the proposed estimator. The proposed method has also been applied to the analysis of the QoL data from a clinical trial on early breast cancer, which motivated this study.
 
A threshold linear mixed model for identification of treatment-sensitive subsets in a clinical trial based on longitudinal outcomes and a continuous covariate.
 
Ge X, Peng Y, Tu D. Stat Methods Med Res 29: 2919-31, 2020.
 
 
Identification of a subset of patients who may be sensitive to a specific treatment is an important problem in clinical trials. In this paper, we consider the case where the treatment effect is measured by longitudinal outcomes, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. A threshold linear mixed model is introduced, and a smoothing maximum likelihood method is proposed to obtain the estimation of the parameters in the model. Broyden-Fletcher-Goldfarb-Shanno algorithm is employed to maximize the proposed smoothing likelihood function. The proposed procedure is evaluated through simulation studies and application to the analysis of data from a randomized clinical trial on patients with advanced colorectal cancer.
 
Intratumoral Transcriptome Heterogeneity Is Associated With Patient Prognosis and Sidedness in Patients With Colorectal Cancer Treated With Anti-EGFR Therapy From the CO.20 Trial.
 
Fontana E, Nyamundanda G, Cunningham D, Tu D, Cheang MCU, Jonker DJ, Siu LL, Sclafani F, Eason K, Ragulan C, Bali MA, Hulkki-Wilson S, Loree JM, Waring PM, Giordano M, Lawrence P, Rodrigues DN, Begum R, Shapiro JD, Price TJ, Cremolini C, Starling N, Pietrantonio F, Trusolino L, O'Callaghan CJ, Sadanandam A. JCO Precis Oncol 4: O, 2020
 
 
Metastatic colorectal cancers (mCRCs) assigned to the transit-amplifying (TA) CRCAssigner subtype are more sensitive to anti–epidermal growth factor receptor (EGFR) therapy. We evaluated the association between the intratumoral presence of TA signature (TA-high/TA-low, dubbed as TA-ness classification) and outcomes in CRCs treated with anti-EGFR therapy.
 
Joint analysis of longitudinal measurements and survival times with a cure fraction based on partly linear mixed and semiparametric cure models
 
Yang L, Song H, Peng Y, Tu D. (ONLINE). Pharmaceutical Statistics n/a: 2020.
 
 
In a joint analysis of longitudinal quality of life (QoL) scores and relapse‐free survival (RFS) times from a clinical trial on early breast cancer conducted by the Canadian Cancer Trials Group, we observed a complicated trajectory of QoL scores and existence of long‐term survivors. Motivated by this observation, we proposed in this paper a flexible joint model for the longitudinal measurements and survival times. A partly linear mixed effect model is used to capture the complicated but smooth trajectory of longitudinal measurements and approximated by B‐splines and a semiparametric mixture cure model with the B‐spline baseline hazard to model survival times with a cure fraction. These two models are linked by shared random effects to explore the dependence between longitudinal measurements and survival times. A semiparametric inference procedure with an EM algorithm is proposed to estimate the parameters in the joint model. The performance of proposed procedures are evaluated by simulation studies and through the application to the analysis of data from the clinical trial which motivated this research.