Evidence map›Paper›PMID 32985127›Full record

ArticleBJS open2020

Australasian ACPGBI risk prediction model for 30-day mortality after colorectal cancer surgery.

S Wilkins, K Oliva, E Chowdhury, B Ruggiero, A Bennett, E J Andrews, O Dent, P Chapuis, C Platell, C M Reid and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BJS open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. 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

11 authors.

S WilkinsCabrini Monash University Department of Surgery, Malvern, Victoria.ORCID https://orcid.org/0000-0001-7712-4114
K OlivaCabrini Monash University Department of Surgery, Malvern, Victoria.
E ChowdhuryDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria.
B RuggieroCabrini Monash University Department of Surgery, Malvern, Victoria.
A BennettDepartment of Anaesthesia, Cabrini Hospital, Malvern, Victoria.
E J AndrewsDepartment of Surgery, Cork University Hospital, Cork, Ireland.
O DentDepartment of Colorectal Surgery, Concord Hospital, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0003-3033-5744
P ChapuisDepartment of Colorectal Surgery, Concord Hospital, Sydney, New South Wales, Australia.
C PlatellColorectal Surgical Unit, St John of God Subiaco Hospital, University of Western Australia, Perth, Western Australia.
C M ReidDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria.
P J McMurrickCabrini Monash University Department of Surgery, Malvern, Victoria.

Funding

Let's Beat Bowel Cancer
6 · The paper itself

Abstract

backgroundPostoperative mortality after colorectal cancer surgery varies across hospitals and countries. The aim of this study was to test the Association of Coloproctologists of Great Britain and Ireland (ACPGBI) models as predictors of 30-day mortality in an Australian cohort.

methodsData from patients who underwent surgery in six hospitals between 1996 and 2015 (CRC data set) were reviewed to test ACPGBI models, and patients from 79 hospitals in the Bi-National Colorectal Cancer Audit between 2007 and 2016 (BCCA data set) were analysed to validate model performance. Recalibrated models based on ACPGBI risk models were developed, tested and validated on a data set of Australasian patients.

resultsOf 18 752 patients observed during the study, 6727 (CRC data set) and 3814 (BCCA data set) were analysed. The 30-day mortality rate was 1·1 and 3·5 per cent in the CRC and BCCA data sets respectively. Both the original and revised ACPGBI models overestimated 30-day mortality for the CRC data set (observed to expected (O/E) ratio 0·17 and 0·21 respectively). Their ability to correctly predict mortality risk was poor (P < 0·001, Hosmer-Lemeshow test); however, the area under the curve for both models was 0·88 (95 per cent c.i. 0·85 to 0·92) showing good discriminatory power to classify 30-day mortality. The recalibrated original model performed well for calibration and discrimination, whereas the recalibrated revised model performed well for discrimination but not for calibration. Risk prediction was good for both recalibrated models. On external validation using the BCCA data set, the recalibrated models underestimated mortality risk (O/E ratio 3·06 and 2·98 respectively), whereas both original and revised ACPGBI models overestimated the risk (O/E ratio 0·48 and 0·69). All models showed similar good discrimination.

conclusionThe original and revised ACPGBI models overpredicted risk of 30-day mortality. The new Australasian calibrated ACPGBI model needs to be tested further in clinical practice.

Identifiers

PMID32985127
PMCPMC7709373

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.