scholarly journals Mapping the FACT-B Instrument to EQ-5D-3L in Patients with Breast Cancer Using Adjusted Limited Dependent Variable Mixture Models versus Response Mapping

2018 ◽  
Vol 21 (12) ◽  
pp. 1399-1405 ◽  
Author(s):  
Laura A. Gray ◽  
Allan J. Wailoo ◽  
Monica Hernandez Alava
Keyword(s):  
Breast Cancer ◽  
Mixture Models ◽  
Limited Dependent Variable ◽  
Response Mapping

scholarly journals Mapping to Quality of Life and Capability Measures in Cataract Surgery Patients: From Cat-PROM5 to EQ-5D-3L, EQ-5D-5L, and ICECAP-O Using Mixture Modelling

2020 ◽  
Vol 5 (1) ◽  
pp. 238146832091544
Author(s):  
Padraig Dixon ◽  
William Hollingworth ◽  
John Sparrow
Keyword(s):  
Quality Of Life ◽  
Cataract Surgery ◽  
Mixture Models ◽  
Linear Models ◽  
Outcome Measure ◽  
Performance Criteria ◽  
Limited Dependent Variable ◽  
Patient Reported ◽  
Support Cost

Objectives. Cataract is a prevalent and potentially blinding eye condition. Cataract surgery, the only proven treatment for this condition, is a very frequently undertaken procedure. The objective of this analysis was to develop a mapping algorithm that could be used to predict quality of life and capability scores from the Cat-PROM5, a newly developed, validated patient-reported outcome measure for patients undergoing cataract surgery. Methods. We estimated linear models and adjusted limited dependent variable mixture models. Data were taken from the Predict-CAT cohort of up to 1181 patients undergoing cataract surgery at two sites in England. The Cat-PROM5 was mapped to two quality of life measures (EQ-5D-3L and EQ-5D-5L) and one capability measure (ICECAP-O). All patients reported ICECAP-O and one or other of the EQ-5D measures both before and after cataract surgery. Model performance was assessed using likelihood statistics, graphical inspections of model fit, and error measurements. Results. Adjusted limited dependent variable mixture models dominated linear models on all performance criteria. Mixture models offered very good fit. Three component models that allowed component membership to be a function of covariates (age, sex, and diabetic status depending on specification and outcome measure) and which conditioned on covariates offered the best performance in almost all cases. An exception was the EQ-5D-5L post-surgery for which a two-component model was selected. Conclusions. Mapping from Cat-PROM5 to quality of life and capability measures using adjusted limited dependent variable mixture models is feasible, and the estimates can be used to support cost-effectiveness analysis in relation to cataract care. Mixture models performed strongly for both quality of life outcomes and capability outcomes.

scholarly journals Gaussian Mixture Models for Probabilistic Classification of Breast Cancer

2019 ◽  
Vol 79 (13) ◽  
pp. 3492-3502 ◽  
Author(s):  
Indira Prabakaran ◽  
Zhengdong Wu ◽  
Changgun Lee ◽  
Brian Tong ◽  
Samantha Steeman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mixture Models ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Probabilistic Classification

First-line treatment with lapatinib plus paclitaxel versus paclitaxel alone for patients with HER2+ metastatic breast cancer (MBC): Quality-of-life (QOL) analysis using repeated measures and pattern mixture models

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 1049-1049 ◽  
Author(s):  
B. Sherrill ◽  
Y. Wu ◽  
M. Amonkar ◽  
M. Arbushites ◽  
A. DiLeo
Keyword(s):  
Breast Cancer ◽  
Mixture Models ◽  
Repeated Measures ◽  
Group Analysis ◽  
Metastatic Breast ◽  
Stage Iv ◽  
Phase Iii ◽  
Controlled Study ◽  
First Line ◽  
Double Blind

1049 Background: A phase III randomized, multicenter, double-blind, placebo-controlled study compared first-line therapy with lapatinib and paclitaxel (L+P) versus paclitaxel alone (P) for MBC. In a sub-group analysis of HER2+ patients, time to tumor progression for L+P was significantly improved, with an emerging trend for survival benefit. This analysis models the QOL data in the subset of the randomized ITT population that overexpressed HER2 (FISH+ or IHC3+). Methods: QOL was assessed using the Functional Assessment of Cancer Therapy-Breast (FACT-B) questionnaire. Outcome measures included FACT-B total score, trial outcome index (TOI) score and breast cancer subscale (BCS). Higher scores represent better QOL. Patients completed the FACT-B at the screening visit, week 9, every 12 weeks thereafter, and at discontinuation of therapy. The assessment at discontinuation was applied to the next scheduled visit for analyses. Changes from baseline were analyzed using repeated measures models with baseline score as a covariate. Pattern mixture modeling was implemented as a sensitivity analysis. Results: Of 579 randomized patients, 86 were HER-2+ and 85 completed at least one item from the FACT-B (n = 48 L+P; n = 37 P). The baseline characteristics of this subset were well-matched with regard to age, ECOG status, and prior anthracycline use. More patients in the L+P group than in the P group had visceral disease (69% vs 51%) and more were at stage IV (88% vs 78%).Over the first year, the L+P arm demonstrated stable FACT-B scores over time, whereas average scores for patients on paclitaxel monotherapy decreased (change from baseline: L+P p = 0.99; P p = 0.01). Statistically significant differences were observed between treatment arms on the FACT-B (p = 0.05), TOI (p = 0.03), and BCS (p = 0.01). Pattern mixture models suggested more QOL differentiation between treatments among patients who progressed or withdrew within 6 months of study start. Conclusions: Among patients with HER2+ MBC, treatment with L+P resulted in more stable QOL than with P monotherapy. These findings represent clinically important differences between treatment groups. [Table: see text]

scholarly journals Mapping the kidney disease quality of life 36-item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L in patients undergoing dialysis

2019 ◽  
Vol 20 (8) ◽  
pp. 1195-1206 ◽  
Author(s):  
Fan Yang ◽  
Carlos K. H. Wong ◽  
Nan Luo ◽  
James Piercy ◽  
Rebecca Moon ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Mixture Models ◽  
Short Form ◽  
Predictive Performance ◽  
Cross Sectional Study ◽  
Beta Regression ◽  
Sectional Study ◽  
Cross Sectional ◽  
Response Mapping

Abstract Objectives To develop algorithms mapping the Kidney Disease Quality of Life 36-Item Short Form Survey (KDQOL-36) onto the 3-level EQ-5D questionnaire (EQ-5D-3L) and the 5-level EQ-5D questionnaire (EQ-5D-5L) for patients with end-stage renal disease requiring dialysis. Methods We used data from a cross-sectional study in Europe (France, n = 299; Germany, n = 413; Italy, n = 278; Spain, n = 225) to map onto EQ-5D-3L and data from a cross-sectional study in Singapore (n = 163) to map onto EQ-5D-5L. Direct mapping using linear regression, mixture beta regression and adjusted limited dependent variable mixture models (ALDVMMs) and response mapping using seemingly unrelated ordered probit models were performed. The KDQOL-36 subscale scores, i.e., physical component summary (PCS), mental component summary (MCS), three disease-specific subscales or their average, i.e., kidney disease component summary (KDCS), and age and sex were included as the explanatory variables. Predictive performance was assessed by mean absolute error (MAE) and root mean square error (RMSE) using 10-fold cross-validation. Results Mixture models outperformed linear regression and response mapping. When mapping to EQ-5D-3L, the ALDVMM model was the best-performing one for France, Germany and Spain while beta regression was best for Italy. When mapping to EQ-5D-5L, the ALDVMM model also demonstrated the best predictive performance. Generally, models using KDQOL-36 subscale scores showed better fit than using the KDCS. Conclusions This study adds to the growing literature suggesting the better performance of the mixture models in modelling EQ-5D and produces algorithms to map the KDQOL-36 onto EQ-5D-3L (for France, Germany, Italy, and Spain) and EQ-5D-5L (for Singapore).

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