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JAMA Oncol. 2017 Dec 1;3(12):1675-1682. doi: 10.1001/jamaoncol.2017.2714.

Development and Validation of a Novel Acute Myeloid Leukemia-Composite Model to Estimate Risks of Mortality.

Author information

1
Clinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Medicine, Seattle
2
Division of Medical Oncology, Department of Medicine, University of Washington School of Medicine, Seattle
3
Clinical Statistics Program, Clinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle
4
Department of Biostatistics, University of Washington School of Public Health, Seattle
5
Massachusetts General Hospital, Harvard Medical School, Boston
6
Leukemia & Myeloid Disorders Program, Cleveland Clinic, Cleveland, Ohio
7
Department of Medicine, Division of Hematology, Stanford University, Stanford, California
8
Huntsman Cancer Institute, Division of Hematology and Hematologic Malignancies, University of Utah, Salt Lake City
9
Medical Oncology, National Cancer Institute, Cairo University, Cairo, Egypt

Abstract

Importance:

To our knowledge, this multicenter analysis is the first to test and validate (1) the prognostic impact of comorbidities on 1-year mortality after initial therapy of acute myeloid leukemia (AML) and (2) a novel, risk-stratifying composite model incorporating comorbidities, age, and cytogenetic and molecular risks.

Objective:

To accurately estimate risks of mortality by developing and validating a composite model that combines the most significant patient-specific and AML-specific features.

Design, Setting, and Participants:

This is a retrospective cohort study. A series of comorbidities, including those already incorporated into the hematopoietic cell transplantation–comorbidity index (HCT-CI), were evaluated. Patients were randomly divided into a training set (n = 733) and a validation set (n = 367). In the training set, covariates associated with 1-year overall mortality at a significance level of P < .10 constructed a multivariate Cox proportional hazards model in which the impact of each covariate was adjusted for that of all others. Then, the adjusted hazard ratios were used as weights. Performances of models were compared using C statistics for continuous outcomes and area under the curve (AUC) for binary outcomes.

Exposures:

Initial therapy for AML.

Main Outcomes and Measures:

Death within 1 year after initial therapy for AML.

Results:

A total of 1100 patients, ages 20 to 89 years, were treated for AML between January 1, 2008, and December 31, 2012, at 5 academic institutions specialized in treating AML; 605 (55%) were male, and 495 (45%) were female. In the validation set, the original HCT-CI had better C statistic and AUC estimates compared with the AML comorbidity index for prediction of 1-year mortality. Augmenting the original HCT-CI with 3 independently significant comorbidities, hypoalbuminemia, thrombocytopenia, and high lactate dehydrogenase level, yielded a better C statistic of 0.66 and AUC of 0.69 for 1-year mortality. A composite model comprising augmented HCT-CI, age, and cytogenetic/molecular risks had even better predictive estimates of 0.72 and 0.76, respectively.

Conclusions and Relevance:

In this cohort study, comorbidities influenced 1-year survival of patients with AML, and comorbidities are best captured by an augmented HCT-CI. The augmented HCT-CI, age, and cytogenetic/molecular risks could be combined into an AML composite model that could guide treatment decision-making and trial design in AML. Studying physical, cognitive, and social health might further clarify the prognostic role of aging. Targeting comorbidities with interventions alongside specific AML therapy might improve survival.

PMID:
28880971
PMCID:
PMC5824273
DOI:
10.1001/jamaoncol.2017.2714
[Indexed for MEDLINE]
Free PMC Article

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