Abstract
Abstract
Background
The 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.
Aims
To 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.
Methods
A 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.
Results
In 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).
Conclusions
Results 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.
Publisher
Springer Science and Business Media LLC
Reference28 articles.
1. National Cancer Registry Ireland (2021) Cancer in Ireland 1994–2019: annual report of the national cancer registry. Available: https://www.ncri.ie/publications/statistical-reports/cancer-ireland-1994-2019-annual-report-national-cancer-registry. Accessed 7 Sept 2023
2. Visser O, Trama A, Maynadié M et al (2012) Incidence, survival and prevalence of myeloid malignancies in Europe. Eur J Cancer 48:3257–3266
3. Menzin J, Lang K, Earle CC et al (2002) The outcomes and costs of acute myeloid leukemia among the elderly. Arch Intern Med 162:1597–1603
4. Zeidan AM, Mahmoud D, Kucmin-Bemelmans IT and others (2016) Economic burden associated with acute myeloid leukemia treatment. Expert Rev Hematol 9:79–89
5. Döhner H, Wei AH, Appelbaum FR et al (2022) Diagnosis and management of acute myeloid leukemia in adults: 2022 recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood 140(12):1345–1377