Evidence map›Paper›PMID 39030463›Full record

ArticleIrish journal of medical science2024

Blood Cancer Network Ireland (BCNI) and National Cancer Registry Ireland (NCRI) collaboration: challenges and utility of an Enhanced Blood Cancer Outcomes Registry (EBCOR) pilot.

Seán R Millar, Mohamed Bakri Mohamed, Vitaliy Mykytiv, Rose McMorrow, Conan Donnelly, Eamonn O'Leary, Nina Orfali, Philip Murphy, Paul V Browne, John Quinn and 10 more

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Article in Irish journal of medical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Seán R MillarSchool of Public Health, University College Cork, Cork, Ireland. s.millar@ucc.ie.ORCID http://orcid.org/0000-0003-4453-8446
Mohamed Bakri MohamedHaematology Department, Cork University Hospital, Cork, Ireland.
Vitaliy MykytivHaematology Department, Cork University Hospital, Cork, Ireland.
Rose McMorrowNational Cancer Registry Ireland (NCRI), Cork, Ireland.
Conan DonnellyInternational Niemann-Pick Disease Registry, Newcastle, UK.
Eamonn O'LearyNational Cancer Registry Ireland (NCRI), Cork, Ireland.
Nina OrfaliHaematology Department, St James's Hospital, Dublin, Ireland.
Philip MurphyHaematology Department, Beaumont Hospital, Dublin, Ireland.
Paul V BrowneHaematology Department, St James's Hospital, Dublin, Ireland.
John QuinnHaematology Department, Beaumont Hospital, Dublin, Ireland.
Peter O'GormanHaematology Department, The Mater Misericordiae University Hospital, Dublin, Ireland.
Mary F RyanHaematology Department, University Hospital Limerick, Limerick, Ireland.
Ruth CliffordHaematology Department, University Hospital Limerick, Limerick, Ireland.
Ezzat El HassadiHaematology Department, University Hospital Waterford, Waterford, Ireland.
Derville O'SheaHaematology Department, Cork University Hospital, Cork, Ireland.
Oonagh GilliganHaematology Department, Cork University Hospital, Cork, Ireland.
Janusz KrawczykHaematology Department, University Hospital Galway, Galway, Ireland.
Michael E O'DwyerUniversity of Galway, Galway, Ireland.
Eva SzegezdiUniversity of Galway, Galway, Ireland.
Mary R CahillHaematology Department, Cork University Hospital, Cork, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Blood Cancer Network Ireland and National Cancer Registry Ireland worked to create an Enhanced Blood Cancer Outcomes Registry (EBCOR). Enhanced data in acute myeloid leukaemia (AML) included an extensive data dictionary, bespoke software and longitudinal follow-up.

aimsTo demonstrate the utility of the database, we applied the data to examine a clinically relevant question: Charlson comorbidity index (CCI) usefulness in predicting AML patients' survival.

methodsA software designer and consultant haematologists in Cork University Hospital worked together to standardise a data dictionary, train registrars and populate a database. One hundred and forty-one AML patients underwent enhanced data registration. Comorbidities identified by chart review were used to examine the capability of the CCI and age at diagnosis to predict mortality using Kaplan-Meier curves, Cox regression and receiver operating characteristic curves.

resultsIn regression analysis, a dose-response relationship was observed; patients in the highest CCI tertile displayed a greater risk (HR = 4.90; 95% CI 2.79-8.63) of mortality compared to subjects in tertile 2 (HR = 2.74; 95% CI 1.64-4.57) and tertile 1 (reference). This relationship was attenuated in an analysis which adjusted for age at diagnosis. The area under the curve (AUC) for the CCI was 0.76 (95% CI 0.68-0.84) while the AUC for age at diagnosis was 0.84 (95% CI 0.78-0.90).

conclusionsResults suggest that the CCI provides no additional prognostic information beyond that obtained from age alone at AML diagnosis and that an EBCOR can provide a rich database for cancer outcomes research, including predictive models and resource allocation.

Indexed as

RegistriesAdultAgedComorbidityFemaleHumansIrelandLeukemia, Myeloid, AcuteMaleMiddle AgedPilot ProjectsAcute myeloid leukaemiaBlood cancersCancer registryCharlson comorbidity indexPredictionSurvival

Identifiers

PMID39030463
PMCPMC11666745

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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.