Evidence map›Paper›PMID 37101274›Full record

Observational studyBMC palliative care2023

Accuracy of clinical predictions of prognosis at the end-of-life: evidence from routinely collected data in urgent care records.

M Orlovic, J Droney, V Vickerstaff, J Rosling, A Bearne, M Powell, J Riley, P McFarlane, J Koffman, P Stone

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC palliative care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
4.9field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Antithrombotic therapy at the end-of-life-continue or stop?Research and practice in thrombosis and haemostasis · 2026
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 1 country.

M OrlovicRoyal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom.
J DroneyRoyal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom. joanne.droney@rmh.nhs.uk.
V VickerstaffMarie Curie Palliative Care Research Department, Division of Psychiatry, University College London, London, United Kingdom.
J RoslingRoyal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom.
A BearneRoyal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom.
M PowellRoyal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom.
J RileyRoyal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom.
P McFarlaneRoyal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom.
J KoffmanHull York Medical School, Wolfson Palliative Care Research Centre, University of York, York, United Kingdom.
P StoneMarie Curie Palliative Care Research Department, Division of Psychiatry, University College London, London, United Kingdom.
Royal Marsden NHS Foundation Trust · GBImperial College London · GBMarie Curie · GBUniversity College London · GBUniversity of York · GB

Funding

Marie Curie MCCC-FCH-18-UMarie Curie MCCC-FCO-11-UMarie Curie MCCC-FPO-16-U
6 · The paper itself

Abstract

backgroundThe accuracy of prognostication has important implications for patients, families, and health services since it may be linked to clinical decision-making, patient experience and outcomes and resource allocation. Study aim is to evaluate the accuracy of temporal predictions of survival in patients with cancer, dementia, heart, or respiratory disease.

methodsAccuracy of clinical prediction was evaluated using retrospective, observational cohort study of 98,187 individuals with a Coordinate My Care record, the Electronic Palliative Care Coordination System serving London, 2010-2020. The survival times of patients were summarised using median and interquartile ranges. Kaplan Meier survival curves were created to describe and compare survival across prognostic categories and disease trajectories. The extent of agreement between estimated and actual prognosis was quantified using linear weighted Kappa statistic.

resultsOverall, 3% were predicted to live "days"; 13% "weeks"; 28% "months"; and 56% "year/years". The agreement between estimated and actual prognosis using linear weighted Kappa statistic was highest for patients with dementia/frailty (0.75) and cancer (0.73). Clinicians' estimates were able to discriminate (log-rank p < 0.001) between groups of patients with differing survival prospects. Across all disease groups, the accuracy of survival estimates was high for patients who were likely to live for fewer than 14 days (74% accuracy) or for more than one year (83% accuracy), but less accurate at predicting survival of "weeks" or "months" (32% accuracy).

conclusionClinicians are good at identifying individuals who will die imminently and those who will live for much longer. The accuracy of prognostication for these time frames differs across major disease categories, but remains acceptable even in non-cancer patients, including patients with dementia. Advance Care Planning and timely access to palliative care based on individual patient needs may be beneficial for those where there is significant prognostic uncertainty; those who are neither imminently dying nor expected to live for "years".

Indexed as

DementiaNeoplasmsDeathHumansPalliative CarePrognosisRetrospective StudiesRoutinely Collected Health DataAdvance care planningDeathDementiaHeart diseasesLung diseasesNeoplasmsPalliative carePrognosis

Identifiers

PMID37101274
PMCPMC10131555
OpenAlexW4367050733

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.