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. 2018 Dec;27(12):3313-3324.
doi: 10.1007/s11136-018-1979-0. Epub 2018 Aug 30.

Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry

Belle H de Rooij  1   2 , Nicole P M Ezendam  3   4 , Floortje Mols  3   4 , Pauline A J Vissers  4 , Melissa S Y Thong  5 , Carla C P Vlooswijk  4 , Simone Oerlemans  4 , Olga Husson  6 , Nicole J E Horevoorts  3   4 , Lonneke V van de Poll-Franse  3   4   7
Affiliations

Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry

Belle H de Rooij et al. Qual Life Res. 2018 Dec.

Abstract

Purpose: The 'Patient Reported Outcomes Following Initial treatment and Long-term Evaluation of Survivorship' (PROFILES) registry collects patient-reported outcomes (PROs) from short- and long-term cancer survivors in the Netherlands, in a population-based setting. The aim of this analysis is to assess the generalizability of observational PRO research among cancer survivors by comparing socio-demographic and clinical characteristics, and survival of participants and non-participants in cancer survivors invited for questionnaire research through the PROFILES registry.

Methods: Between 2008 and 2015, cancer survivors with different cancer diagnoses (N = 14,011) were invited to participate in PROFILES registry studies, of whom 69% (N = 9684) participated. Socio-demographic and clinical characteristics and survival data, collected through the Netherlands Cancer Registry, were associated with participation versus non-participation in multivariable logistic regression analyses and cox proportional hazard regression models, respectively.

Results: Participants had a significantly better survival compared to non-participants (HR = 1.47, P < .01). Participation was associated with male gender, being 60-70 years old, high socio-economic status, receiving any treatment, receiving radiotherapy, having no comorbidities, and a cancer diagnosis 2-3 years before invitation. Sensitivity analysis demonstrates that the health-related quality of life (HRQoL) might be up to 1.3 points lower (scale 0-100) using hot deck imputation compared to non-imputed participant data.

Conclusions: Cancer survivors not participating in observational PROs research significantly differ from participants, with respect to socio-demographic and clinical characteristics, and survival. Their HRQoL scores may be systematically lower compared to participants. Therefore, even in PRO studies with relatively high participation rates, observed outcomes may represent the healthier patient with better outcomes.

Keywords: Cancer survivors; Non-participation; Non-response bias; Patient-reported outcomes; Quality of life.

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Conflict of interest statement

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Ethical approval was obtained for all study samples separately, from a local certified medical ethics committee. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Figures

Fig. 1
Fig. 1
Graphical view of participation rates (participants versus total non-participants) and interacting independent variables. Note: Central moving means of 5 neighboring ages are shown. For years since diagnosis, year averages are shown
Fig. 2
Fig. 2
Survival curves of participants versus non-participants, unadjusted
See this image and copyright information in PMC

References

    1. Black N. Patient reported outcome measures could help transform healthcare. BMJ. 2013;346:f167. doi: 10.1136/bmj.f167. - DOI - PubMed
    1. Asch DA, Jedrziewski MK, Christakis NA. Response rates to mail surveys published in medical journals. Journal of Clinical Epidemiology. 1997;50(10):1129–1136. doi: 10.1016/S0895-4356(97)00126-1. - DOI - PubMed
    1. Groves RM, Peytcheva E. The impact of nonresponse rates on nonresponse bias a meta-analysis. Public Opinion Quarterly. 2008;72(2):167–189. doi: 10.1093/poq/nfn011. - DOI
    1. Johnson TP, Wislar JS. Response rates and nonresponse errors in surveys. JAMA. 2012;307(17):1805–1806. doi: 10.1001/jama.2012.3532. - DOI - PubMed
    1. Hutchings A, Neuburger J, Frie KG, Black N, van der Meulen J. Factors associated with non-response in routine use of patient reported outcome measures after elective surgery in England. Health and Quality of Life Outcomes. 2012;10(1):1. doi: 10.1186/1477-7525-10-34. - DOI - PMC - PubMed