You are here

Article Text

Article menu

Download PDFPDF

Original research
Imminent death: clinician certainty and accuracy of prognostic predictions
  1. Nicola White1,
  2. Fiona Reid2,
  3. Victoria Vickerstaff3,
  4. Priscilla Harries4,5,
  5. Christopher Tomlinson6 and
  6. Patrick Stone7
  1. 1 Division of Psychiatry, Marie Curie Palliative Care Research Departent, University College London, London, UK
  2. 2 Department of Primary Care & Public Health Sciences, King's College London, London, UK
  3. 3 Division of Psychiatry, University College London, London, UK
  4. 4 Faculty of Health, Social Care and Education, Kingston University & St Georges, University of London, London, UK
  5. 5 Department of Clinical Sciences, Brunel University London, London, UK
  6. 6 Bioinformatics Data Science Group, Centre for Bioinformatics, Imperial College London, London, UK
  7. 7 Marie Curie Palliative Care Research Department, University College London, London, UK
  1. Correspondence to Dr Nicola White, Division of Psychiatry, Marie Curie Palliative Care Research Departent, University College London, London W1T7NF, UK; n.g.white{at}ucl.ac.uk

Abstract

Objectives To determine the accuracy of predictions of dying at different cut-off thresholds and to acknowledge the extent of clinical uncertainty.

Design Secondary analysis of data from a prospective cohort study.

Setting An online prognostic test, accessible by eligible participants across the UK.

Participants Eligible participants were members of the Association of Palliative Medicine. 99/166 completed the test (60%), resulting in 1980 estimates (99 participants × 20 summaries).

Main outcome measures The probability of death occurring within 72 hours (0% certain survival−100% certain death) for 20 patient summaries. The estimates were analysed using five different thresholds: 50/50%, 40/60%, 30/70%, 20/80% and 10/90%, with percentage values between these extremes being regarded as ‘indeterminate’. The positive predictive value (PPV), negative predictive value (NPV) and the number of indeterminate cases were calculated for each cut-off.

Results Using a <50% versus >50% threshold produced a PPV of 62%, an NPV of 74% and 5% indeterminate cases. When the threshold was changed to ≤10% vs ≥90%, the PPV and NPV increased to 75% and 88%, respectively, at the expense of an increase of indeterminate cases up to 62%.

Conclusion When doctors assign a very high (≥90%) or very low (≤10%) probability of imminent death, their prognostic accuracy is improved; however, this increases the number of ‘indeterminate’ cases. This suggests that clinical predictions may continue to have a role for routine prognostication but that other approaches (such as the use of prognostic scores) may be required for those cases where doctors’ estimates are indeterminate.

  • prognosis
  • palliative care
  • clinical decisions
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjspcare-2018-001761

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Footnotes

    • Contributors NW developed the research concept, designed the data collection tools, monitored and collected the data for the study, wrote the statistical analysis plan, cleaned and analysed the data and drafted and revised the paper. She is the guarantor. FR and VV assisted in the study design and the statistical analysis of the data. PH and PS developed the research concept and oversaw the data collection and analysis. CT developed the study website to collect the data and monitored the data collection. All authors reviewed and provided comments on the drafted paper. All authors approve the final version.

    • Funding This research was part funded by a UCL PhD Studentship. Also by Marie Curie I-CAN-CARE Program grant (MCCC-FPO-16-U). Professor Stone is supported by the Marie Curie Chair’s grant (MCCC-509537).

    • Disclaimer The funders had no role in trial design, data collection and analysis, decision to publish, or preparation of the manuscript.

    • Competing interests CT reports personal fees from University College London during the conduct of the study. All other authors have no competing interests.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement All data relevant to the study are included in the article or uploaded as supplementary information.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.