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. 2024 Sep;33(9):2387-2400.
doi: 10.1007/s11136-024-03707-y. Epub 2024 Jun 16.

Relationship between reasons for intermittent missing patient-reported outcomes data and missing data mechanisms

Lene Kongsgaard Nielsen  1   2 , Rebecca Mercieca-Bebber  3 , Sören Möller  4   5 , Louise Redder  6   5 , Mary Jarden  7   8 , Christen Lykkegaard Andersen  7   9 , Henrik Frederiksen  6   5 , Asta Svirskaite  10 , Trine Silkjær  11 , Morten Saaby Steffensen  12 , Per Trøllund Pedersen  13 , Maja Hinge  14 , Mikael Frederiksen  15 , Bo Amdi Jensen  16 , Carsten Helleberg  7 , Anne Kærsgaard Mylin  7 , Niels Abildgaard  6   5 , Madeleine T King  6   17
Affiliations

Relationship between reasons for intermittent missing patient-reported outcomes data and missing data mechanisms

Lene Kongsgaard Nielsen et al. Qual Life Res. 2024 Sep.

Abstract

Purpose: Non-response (NR) to patient-reported outcome (PRO) questionnaires may cause bias if not handled appropriately. Collecting reasons for NR is recommended, but how reasons for NR are related to missing data mechanisms remains unexplored. We aimed to explore this relationship for intermittent NRs.

Methods: Patients with multiple myeloma completed validated PRO questionnaires at enrolment and 12 follow-up time-points. NR was defined as non-completion of a follow-up assessment within seven days, which triggered contact with the patient, recording the reason for missingness and an invitation to complete the questionnaire (denoted "salvage response"). Mean differences between salvage and previous on-time scores were estimated for groups defined by reasons for NR using linear regression with clustered standard errors. Statistically significant mean differences larger than minimal important difference thresholds were interpreted as "missing not at random" (MNAR) mechanism (i.e. assumed to be related to declining health), and the remainder interpreted as aligned with "missing completely at random" (MCAR) mechanism (i.e. assumed unrelated to changes in health).

Results: Most (7228/7534 (96%)) follow-up questionnaires were completed; 11% (802/7534) were salvage responses. Mean salvage scores were compared to previous on-time scores by reason: those due to hospital admission, mental or physical reasons were worse in 10/22 PRO domains; those due to technical difficulties/procedural errors were no different in 21/22 PRO domains; and those due to overlooked/forgotten or other/unspecified reasons were no different in any domains.

Conclusion: Intermittent NRs due to hospital admission, mental or physical reasons were aligned with MNAR mechanism for nearly half of PRO domains, while intermittent NRs due to technical difficulties/procedural errors or other/unspecified reasons generally were aligned with MCAR mechanism.

Keywords: Missing data; Missing data mechanism; Multiple myeloma; Patient-reported outcomes; Quality of life.

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Conflict of interest statement

All authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1
For 10 out of 22 domains of non-responses group 1, the mean salvage responses were statistical significant and clinically different compared to the mean previous on-time score before salvage responses. The dots are the mean score differences, the vertical bars represents 95% confidence intervals (CI) and the horizontal dotted lines represent the upper and lower minimal important difference for the individual domain. QoL quality of life
See this image and copyright information in PMC

References

    1. Ahmed, S., Berzon, R. A., Revicki, D. A., Lenderking, W. R., Moinpour, C. M., Basch, E., Reeve, B. B., & Wu, A. W. (2012). The use of patient-reported outcomes (PRO) within comparative effectiveness research: Implications for clinical practice and health care policy. Medical Care,50(12), 1060–1070. 10.1097/MLR.0b013e318268aaff 10.1097/MLR.0b013e318268aaff - DOI - PubMed
    1. Fayers, P. M., & Machin, D. (2016). Quality of life: The assessment, analysis, and reporting of patient-reported outcomes (3rd ed.). Wiley.
    1. Bell, M. L., & Fairclough, D. L. (2014). Practical and statistical issues in missing data for longitudinal patient-reported outcomes. Statistical Methods in Medical Research,23(5), 440–459. 10.1177/0962280213476378 10.1177/0962280213476378 - DOI - PubMed
    1. Fairclough, D. L. (2010). Design and analysis of quality of life studies in clinical trials. Chapman & Hall/CRC interdisciplinary statistics series (2nd ed.). Chapman & Hall/CRC.
    1. Fielding, S., Fayers, P. M., & Ramsay, C. R. (2009). Investigating the missing data mechanism in quality of life outcomes: A comparison of approaches. Health and Quality of Life Outcomes,7, 57. 10.1186/1477-7525-7-57 10.1186/1477-7525-7-57 - DOI - PMC - PubMed

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