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Qual Life Res. 2016 Jul;25(7):1613-23. doi: 10.1007/s11136-015-1206-1. Epub 2016 Jan 28.

The current practice of handling and reporting missing outcome data in eight widely used PROMs in RCT publications: a review of the current literature.

Author information

1
Health Economics Research Centre (HERC), Nuffield Department of Population Health, University of Oxford, Oxford, UK. ines.rombach@ndorms.ox.ac.uk.
2
RCS Surgical Intervention Trials Unit (SITU), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK. ines.rombach@ndorms.ox.ac.uk.
3
National Perinatal Epidemiology Unit (NPEU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
4
Health Economics Research Centre (HERC), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
5
Health Services Research Unit (HSRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
6
Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Abstract

PURPOSE:

Patient-reported outcome measures (PROMs) are designed to assess patients' perceived health states or health-related quality of life. However, PROMs are susceptible to missing data, which can affect the validity of conclusions from randomised controlled trials (RCTs). This review aims to assess current practice in the handling, analysis and reporting of missing PROMs outcome data in RCTs compared to contemporary methodology and guidance.

METHODS:

This structured review of the literature includes RCTs with a minimum of 50 participants per arm. Studies using the EQ-5D-3L, EORTC QLQ-C30, SF-12 and SF-36 were included if published in 2013; those using the less commonly implemented HUI, OHS, OKS and PDQ were included if published between 2009 and 2013.

RESULTS:

The review included 237 records (4-76 per relevant PROM). Complete case analysis and single imputation were commonly used in 33 and 15 % of publications, respectively. Multiple imputation was reported for 9 % of the PROMs reviewed. The majority of publications (93 %) failed to describe the assumed missing data mechanism, while low numbers of papers reported methods to minimise missing data (23 %), performed sensitivity analyses (22 %) or discussed the potential influence of missing data on results (16 %).

CONCLUSIONS:

Considerable discrepancy exists between approved methodology and current practice in handling, analysis and reporting of missing PROMs outcome data in RCTs. Greater awareness is needed for the potential biases introduced by inappropriate handling of missing data, as well as the importance of sensitivity analysis and clear reporting to enable appropriate assessments of treatment effects and conclusions from RCTs.

KEYWORDS:

Missing data; Patient-reported outcomes measures (PROMs); Quality of life (QoL); Randomised controlled trials (RCTs); Sensitivity analysis

PMID:
26821918
PMCID:
PMC4893363
DOI:
10.1007/s11136-015-1206-1
[Indexed for MEDLINE]
Free PMC Article

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