Imputing missing patient-level data and propensity score matching in cost-effectiveness analysis in Crohn's disease

ABSTRACT

Objectives

The effect of imputing missing data followed by propensity score analysis on the incremental cost-effectiveness ratio (ICER) in a cost-effectiveness analysis is unknown. The objective was to compare alternative approaches in grouping data following imputation and prior to calculating propensity scores for use in economic evaluation.

Methods

Patient-level data from an observational study of 573 children with Crohn’s disease were used in a microsimulation model to determine the incremental cost of early anti-tumor necrosis factor-α treatment compared to standard care per remission week gained. Multiple imputation of a missing covariate followed by propensity score matching to create comparator groups was approached in two ways. The Within approach calculated propensity scores on each imputed dataset separately, while the Across method averaged propensity scores to create one matched population resulting in multiple sets of health state transition probabilities.

Results

The incremental cost per remission week gained ranged from CAD$2,236 to CAD$12,464 (mean CAD$4,266) with Within datasets and was CAD$4,679 per remission week gained with the Across dataset.

Conclusion

Imputation of missing patient-level data and propensity score analysis increases methodological uncertainty in cost-effectiveness analysis. The present study indicated that the Across approach may be less cumbersome, and slightly reduce bias and variance.

KEYWORDS:

• Economic evaluation
• missing data
• imputation
• propensity score analysis
• cost-effectiveness analysis methods

Key issues

• Imputation of missing patient-level data and propensity score analysis can introduce additional methodological uncertainty when informing inputs in a cost-effectiveness analysis and should be reported.

• Different methods of grouping imputed datasets such as an Across approach or a Within approach prior to propensity score matching were explored within the context of an economic evaluation. Both approaches are feasible but result in slightly different incremental cost-effectiveness ratios (ICERs) thus requiring further characterization.

• Validated methods that account for uncertainty and bias in observational data will enable the conduct of more economic evaluations in the absence of randomized controlled trials such as for emerging treatments in children, thereby increasing the evidence available to funding decision-makers.

Acknowledgments

We acknowledge with thanks data provided for this study from the RISK-PROKIIDS study. The RISK Study and Dataset were solely and fully funded by the Crohn’s and Colitis Foundation of America under the umbrella of the PRO-KIIDS pediatric research network.

Declaration of interest

Thomas Walters has received grants, and personal fees from Janssen Canada, Abbvie Canada and Merck Canada; personal fees from Ferring Canada and non-financial support from Janssen, Canada and Abbvie, Canada, outside the submitted work. Anne Griffiths has received grants and personal fees from Abbvie, and personal fees from Celgene, Janssen, Lilly, Roche, Shire, and Nestle, outside the submitted work. Shinya Ito reports grants from Crohn’s and Colitis Foundations of America, grants from UCB Gmbh, outside the submitted work. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewers Disclosure

Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.

Additional information

Funding

This work was supported by the Canadian Institutes of Health Research (CIHR) operating grant (#137137) to W. Ungar and the Ontario Ministry of Health and Long-term Care Drug Innovation Fund Grant No. 2010-001. Wendy J. Ungar is supported by a Canada Research Chair in Economic Evaluation and Technology Assessment in Child Health. Additional financial support for this work was provided to N. Bashir in the form of a Hospital for Sick Children Restracomp Doctoral Scholarship, a University of Toronto Institute of Health Policy, Management and Evaluation (IHPME) Graduate Fellowship, the Eugene Vayda Award, the Dr Robert Duff Barron Graduate Scholarship in Public Health Policy Award, a Doctoral Completion Award, an IHPME Travel Award, the Canadian Federation of University Women Dr Alice B. Wilson Award, and a CIHR Travel Award.