Bias in survival estimates created by a requirement for consent to enter a clinical breast cancer registry

Elwood, J. Mark; Marshall, Roger; Tin, Sandar Tin; Barrios, Mark; Harvey, Vernon

doi:10.1016/j.canep.2018.12.005

Cited by 15 publications

(45 citation statements)

References 20 publications

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“…Participants supported a central system for patients to control the uses of their data, and likewise a single NHS mechanism to sign up for active research participation. There is a trade-off between the scientific desirability of everyone contributing de-identified data, including to avoid bias,76 77 and the desirability of individual control over data use 78. As we suggest below, a reasonable balance might be a central system to opt out from identifiable clinical use, identifiable (§251) research use, or de-identified research use of one’s data, and to opt in for participatory research.…”

Section: Discussionmentioning

confidence: 99%

Public opinion on sharing data from health services for clinical and research purposes without explicit consent: an anonymous online survey in the UK

et al. 2022

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ObjectivesUK National Health Service/Health and Social Care (NHS/HSC) data are variably shared between healthcare organisations for direct care, and increasingly de-identified for research. Few large-scale studies have examined public opinion on sharing, including of mental health (MH) versus physical health (PH) data. We measured data sharing preferences.Design/setting/interventions/outcomesPre-registered anonymous online survey, measuring expressed preferences, recruiting February to September 2020. Participants were randomised to one of three framing statements regarding MH versus PH data.ParticipantsOpen to all UK residents. Participants numbered 29 275; 40% had experienced an MH condition.ResultsMost (76%) supported identifiable data sharing for direct clinical care without explicit consent, but 20% opposed this. Preference for clinical/identifiable sharing decreased with geographical distance and was slightly less for MH than PH data, with small framing effects. Preference for research/de-identified data sharing without explicit consent showed the same small PH/MH and framing effects, plus greater preference for sharing structured data than de-identified free text. There was net support for research sharing to the NHS, academic institutions, and national research charities, net ambivalence about sharing to profit-making companies researching treatments, and net opposition to sharing to other companies (similar to sharing publicly). De-identified linkage to non-health data was generally supported, except to data held by private companies. We report demographic influences on preference. A majority (89%) supported a single NHS mechanism to choose uses of their data. Support for data sharing increased during COVID-19.ConclusionsSupport for healthcare data sharing for direct care without explicit consent is broad but not universal. There is net support for the sharing of de-identified data for research to the NHS, academia, and the charitable sector, but not the commercial sector. A single national NHS-hosted system for patients to control the use of their NHS data for clinical purposes and for research would have broad support.Trial registration numberISRCTN37444142.

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Section: Discussionmentioning

confidence: 99%

Public opinion on sharing data from health services for clinical and research purposes without explicit consent: an anonymous online survey in the UK

et al. 2022

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“…it may lead to non-maximal prevention of harm. There are examples of consent requirements producing biased results [ 88 , 89 ]. There are also examples of consent requirements not biasing results [ 90 , 91 ].…”

Section: Discussionmentioning

confidence: 99%

In Defence of informed consent for health record research - why arguments from ‘easy rescue’, ‘no harm’ and ‘consent bias’ fail

Ploug

2020

BMC Med Ethics

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Background Health data holds great potential for improved treatments. Big data research and machine learning models have been shown to hold great promise for improved diagnostics and treatment planning. The potential is tied, however, to the availability of personal health data. In recent years, it has been argued that data from health records should be available for health research, and that individuals have a duty to make the data available for such research. A central point of debate is whether such secondary use of health data requires informed consent. Main body In response to recent writings this paper argues that a requirement of informed consent for health record research must be upheld. It does so by exploring different contrasting notions of the duty of easy rescue and arguing that none of them entail a perfect duty to participate in health record research. In part because the costs of participation cannot be limited to 1) the threat of privacy breaches, but includes 2) the risk of reduced trust and 3) suboptimal treatment, 4) stigmatization and 5) medicalisation, 6) further stratification of solidarity and 7) increased inequality in access to treatment and medicine. And finally, it defends the requirement of informed consent by arguing that the mere possibility of consent bias provides a rather weak reason for making research participation mandatory, and that there are strong, independent reasons for making. Conclusion Arguments from the duty of easy rescue in combination with claims about little risk of harm and potential consent bias fail to establish not only a perfect duty to participate in health record research, but also that participation in such research should be mandatory. On the contrary, an analysis of these arguments indicates that the duty to participate in research is most adequately construed as an imperfect duty, and reveals a number of strong reasons for insisting that participation in health records research is based on informed consent.

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“…In 13 studies, participants provided active consent to health data reuse [28][29][30][31][32][33][34][35][36][37][38][39][40]. In all of these studies, non-responders were classi ed as non-consenters.…”

Section: Uk [38]mentioning

confidence: 99%

Opt-in and opt-out consent procedures for the reuse of routinely recorded health data in scientific research and their consequences for consent rate and consent bias– A systematic review

Man

Jorna

Torensma

et al. 2022

Preprint

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Background Scientific researchers who wish to reuse health data pertaining to individuals can obtain consent through an opt-in procedure or opt-out procedure. The choice of procedure may have consequences for the consent rate and representativeness of the study sample, and the quality of the research, but these consequences are not well known. Therefore, this review aims to provide insight into the consequences for the consent rate and consent bias of the study sample of opt-in procedures versus opt-out procedures for the reuse of routinely recorded health data for scientific research purposes. Method A systematic review was performed, based on searches in PubMed, Embase, Cinahl, PsycInfo, Web of Science Core Collection, and the Cochrane Library. Two reviewers independently included studies based on predefined eligibility criteria and assessed whether the statistical methods used in the reviewed literature were appropriate for describing the differences between consenters and non-consenters. Statistical pooling and a narrative synthesis were conducted to report results. Results Fifteen studies were included. Of these, 13 implemented an opt-in procedure, one implemented an opt-out procedure, and one implemented both. The average weighted consent rates were 84.0% among the studies that used opt-in and 96.8% in the single study that used opt-out. In the single study that described both procedures, the consent rate was 21.0% in the opt-in group and 95.6% in the opt-out group. Opt-in procedures resulted in more consent bias compared to opt-out procedures. In studies with opt-in, consenting individuals were more likely to be men, had a higher level of education, a higher income, and a higher socioeconomic status. Conclusion Consent rates are generally lower when using an opt-in procedure compared to using an opt-out procedure. Furthermore, in studies with opt-in, participants are less representative of the study population. However, both the study populations and the way in which opt-in or opt-out was organized, varied widely between the studies, which makes it difficult to draw general conclusions regarding the desired balance between patient control over data and learning from patient data. Such further use may be hampered by administrative burdens and the risk of bias.

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Bias in survival estimates created by a requirement for consent to enter a clinical breast cancer registry

Cited by 15 publications

References 20 publications

Public opinion on sharing data from health services for clinical and research purposes without explicit consent: an anonymous online survey in the UK

Public opinion on sharing data from health services for clinical and research purposes without explicit consent: an anonymous online survey in the UK

In Defence of informed consent for health record research - why arguments from ‘easy rescue’, ‘no harm’ and ‘consent bias’ fail

Opt-in and opt-out consent procedures for the reuse of routinely recorded health data in scientific research and their consequences for consent rate and consent bias– A systematic review

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