Evidence map›Paper›PMID 28880971›Full record

ArticleJAMA oncology2017

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

Mohamed L Sorror, Barry E Storer, Amir T Fathi, Aaron T Gerds, Bruno C Medeiros, Paul Shami, Andrew M Brunner, Mikkael A Sekeres, Sudipto Mukherjee, Esteban Peña and 8 more

Abstract readMulticenter Study
In one paragraph

Article in JAMA oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 2 pooled it
–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

93 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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33 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Mohamed L SorrorClinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Medicine, Seattle
Barry E StorerClinical Statistics Program, Clinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle
Amir T FathiMassachusetts General Hospital, Harvard Medical School, Boston
Aaron T GerdsLeukemia & Myeloid Disorders Program, Cleveland Clinic, Cleveland, Ohio
Bruno C MedeirosDepartment of Medicine, Division of Hematology, Stanford University, Stanford, California
Paul ShamiHuntsman Cancer Institute, Division of Hematology and Hematologic Malignancies, University of Utah, Salt Lake City
Andrew M BrunnerMassachusetts General Hospital, Harvard Medical School, Boston
Mikkael A SekeresMassachusetts General Hospital, Harvard Medical School, Boston
Sudipto MukherjeeLeukemia & Myeloid Disorders Program, Cleveland Clinic, Cleveland, Ohio
Esteban PeñaHuntsman Cancer Institute, Division of Hematology and Hematologic Malignancies, University of Utah, Salt Lake City
Mahmoud ElsawyClinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Medicine, Seattle
Shylo WardynClinical Statistics Program, Clinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle
Jennifer WhittenClinical Statistics Program, Clinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle
Rachelle MooreClinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Medicine, Seattle
Pamela S BeckerClinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Medicine, Seattle
Jeannine S McCuneClinical Statistics Program, Clinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle
Frederick R AppelbaumClinical Research Division, Fred Hutchinson Cancer Research Center, University of Washington School of Medicine, Seattle
Elihu H EsteyDivision of Medical Oncology, Department of Medicine, University of Washington School of Medicine, Seattle

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Patient-Specific ModelingAdultAgedAged, 80 and overCohort StudiesComorbidityFemaleHematopoietic Stem Cell TransplantationHumansLeukemia, Myeloid, AcuteMaleMiddle AgedModels, TheoreticalPrognosisRandom AllocationRetrospective Studies

Identifiers

PMID28880971
PMCPMC5824273

What OpenQuestion holds

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Registered trials

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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.