scholarly journals Flexible Bayesian longitudinal models for cost‐effectiveness analyses with informative missing data

2021 ◽  
Author(s):  
Alexina J. Mason ◽  
Manuel Gomes ◽  
James Carpenter ◽  
Richard Grieve
Keyword(s):  
Cost Effectiveness ◽  
Missing Data ◽  
Longitudinal Models ◽  
Informative Missing Data

On assessing model fit for distribution-free longitudinal models under missing data

2013 ◽  
Vol 33 (1) ◽  
pp. 143-157 ◽  
Author(s):  
P. Wu ◽  
X.M. Tu ◽  
J. Kowalski
Keyword(s):  
Missing Data ◽  
Model Fit ◽  
Longitudinal Models ◽  
Distribution Free

scholarly journals Using routinely recorded data in a UK RCT: a comparison to standard prospective data collection methods

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
G. A. Powell ◽  
L. J. Bonnett ◽  
C. T. Smith ◽  
D. A. Hughes ◽  
P. R. Williamson ◽  
...  
Keyword(s):  
Case Report ◽  
Cost Effectiveness ◽  
Missing Data ◽  
Antiepileptic Drugs ◽  
Secondary Care ◽  
Significant Degree ◽  
New Antiepileptic Drugs ◽  
Optimal Mix ◽  
Recorded Data ◽  
Randomised Controlled

Abstract Background Routinely recorded data held in electronic health records can be used to inform the conduct of randomised controlled trials (RCTs). However, limitations with access and accuracy have been identified. Objective: Using epilepsy as an exemplar condition, we assessed the attributes and agreement of routinely recorded data compared to data collected using case report forms in a UK RCT assessing antiepileptic drug treatments for individuals newly diagnosed with epilepsy. Methods The case study RCT is the Standard and New Antiepileptic Drugs II (SANAD II) trial, a pragmatic, UK multicentre RCT assessing the clinical and cost-effectiveness of antiepileptic drugs as treatments for epilepsy. Ninety-eight of 470 eligible participants provided consent for access to routinely recorded secondary care data that were retrieved from NHS Digital Hospital Episode Statistics (N=71) and primary and secondary care data from The Secure Anonymised Information Linkage Databank (N=27). We assessed data items relevant to the identification of individuals eligible for inclusion in SANAD II, baseline and follow-up visits. The attributes of routinely recorded data were assessed including the degree of missing data. The agreement between routinely recorded data and data collected on case report forms in SANAD II was assessed using calculation of Cohen’s kappa for categorical data and construction of Bland-Altman plots for continuous data. Results There was a significant degree of missing data in the routine record for 15 of the 20 variables assessed, including all clinical variables. Agreement was poor for the majority of comparisons, including the assessments of seizure occurrence and adverse events. For example, only 23/62 (37%) participants had a date of first-ever seizure identified in routine datasets. Agreement was satisfactory for the date of prescription of antiepileptic drugs and episodes of healthcare resource use. Conclusions There are currently significant limitations preventing the use of routinely recorded data for participant identification and assessment of clinical outcomes in epilepsy, and potentially other chronic conditions. Further research is urgently required to assess the attributes, agreement, additional benefits, cost-effectiveness and ‘optimal mix’ of routinely recorded data compared to data collected using standard methods such as case report forms at clinic visits for people with epilepsy. Trial registration Standard and New Antiepileptic Drugs II (SANAD II (EudraCT No: 2012-001884-64, registered 05/09/2012; ISRCTN Number: ISRCTN30294119, registered 03/07/2012))

A post-hoc health-related quality of life (HRQoL) analysis of patients with metastatic colorectal cancer (mCRC) in the phase III CONCUR trial.

2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 667-667
Author(s):  
Jane Chang ◽  
Dawn Odom ◽  
Christina Radder ◽  
Christian Kappeler ◽  
Rui-hua Xu ◽  
...  
Keyword(s):  
Missing Data ◽  
Treatment Effect ◽  
Minimal Important Difference ◽  
Progression Free Survival ◽  
Missing At Random ◽  
Phase Iii ◽  
Similar Proportion ◽  
Informative Missing Data ◽  
Post Hoc ◽  
Over Time

667 Background: CONCUR (NCT01584830) showed that regorafenib (REG) significantly improves overall survival (OS) and progression-free survival (PFS) vs. placebo (PBO) in Asian patients with mCRC who progressed after standard therapy (J Li, et al. WCGI 2014). Post hoc exploratory analyses were conducted to assess the effect of treatment on HRQoL. Methods: Patients were randomly assigned 2:1 to treatment with either REG (n=136) or PBO (n=68). The HRQoL analyses included all 204 patients and were selected a priori based on clinical relevance; the global health status/QoL (QL) and the physical functioning (PF) scales of the EORTC QLQ-C30 questionnaire were used. A linear mixed-effects model (LMM) was used to examine the treatment effect on HRQoL and trends over time, assuming that data were missing at random. A pattern-mixture model (PMM) was applied to assess the treatment effect while accounting for potentially informative missing data. Time-to-deterioration (TTD) of HRQoL and responder analyses were conducted to determine the treatment effect based on timing and proportion of patients reaching a minimal important difference (MID) change in QL/PF (≥10 points). Results: The QL and PF changes over time were numerically similar between REG and PBO based on the LMM. The PMM grouped patients based on timing of last HRQoL assessment (<3 or ≥3 cycles) and had results similar to the LMM, demonstrating little impact of informative missing data. For the TTD analysis, when an event was defined as the earliest MID decrease in QL/PF, disease progression, or death, REG showed significantly different TTD curves from PBO (QL: median 8.0 vs. 7.0 weeks, hazard ratio (HR)=0.54; PF: median 7.9 vs. 7.0 weeks, HR=0.59, respectively; all p<0.01). Median TTD was comparable between treatments after removing progression/death from the definition. The responder analyses showed that a similar proportion of patients achieved an improvement in MID in REG vs. PBO (QL: 27.2% vs. 29.4%; PF: 14.0% vs.16.2%, respectively). Conclusions: The findings of this exploratory analysis demonstrate that HRQoL is similar for the REG and PBO groups, indicating that REG prolongs OS and PFS vs. PBO while maintaining a comparable HRQoL. Clinical trial information: NCT01584830.

scholarly journals Correction to: Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis: A Tutorial

2019 ◽  
Vol 37 (7) ◽  
pp. 971-971
Author(s):  
Baptiste Leurent ◽  
Manuel Gomes ◽  
Rita Faria ◽  
Stephen Morris ◽  
Richard Grieve ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Missing Data ◽  
Cost Effectiveness Analysis ◽  
Effectiveness Analysis

The Statistical Approach in Trial-based Economic Evaluations Matters: Get your Statistics Together!

2021 ◽  
Author(s):  
Elizabeth Mutubuki ◽  
Mohamed El Alili ◽  
Judith Bosmans ◽  
Teddy Oosterhuis ◽  
Frank Snoek ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Missing Data ◽  
Statistical Approach ◽  
Cost Effective ◽  
Economic Evaluations ◽  
Full Cost ◽  
Statistical Approaches ◽  
Software Code ◽  
The Impact ◽  
Effectiveness Data

Abstract Background: Baseline imbalances, skewed costs, the correlation between costs and effects, and missing data are statistical challenges that are often not adequately accounted for in the analysis of cost-effectiveness data. This study aims to illustrate the impact of accounting for these statistical challenges in trial-based economic evaluations. Methods: Data from two trial-based economic evaluations, the REALISE and HypoAware studies, were used. In total, 14 full cost-effectiveness analyses were performed per study, in which the four statistical challenges in trial-based economic evaluations were taken into account step-by-step. Statistical approaches were compared in terms of the resulting cost and effect differences, ICERs, and probabilities of cost-effectiveness. Results: In the REALISE study and HypoAware study, the ICER ranged from 636,744€/QALY and 90,989€/QALY when ignoring all statistical challenges to -7,502€/QALY and 46,592€/QALY when accounting for all statistical challenges, respectively. The probabilities of the intervention being cost-effective at 0€/ QALY gained were 0.67 and 0.59 when ignoring all statistical challenges, and 0.54 and 0.27 when all of the statistical challenges were taken into account for the REALISE study and HypoAware study, respectively.Conclusions: Not accounting for baseline imbalances, skewed costs, correlated costs and effects, and missing data in trial-based economic evaluations may notably impact results. Therefore, when conducting trial-based economic evaluations, it is important to align the statistical approach with the identified statistical challenges in cost-effectiveness data. To facilitate researchers in handling statistical challenges in trial-based economic evaluations, software code is provided.

Sign in / Sign up

Export Citation Format

Share Document