Evidence map›Paper›PMID 32453839›Full record

ArticleBlood advances2020

Integrating clinical features with genetic factors enhances survival prediction for adults with acute myeloid leukemia.

Douglas R A Silveira, Lynn Quek, Itamar S Santos, Anna Corby, Juan L Coelho-Silva, Diego A Pereira-Martins, Grant Vallance, Benjamin Brown, Luciana Nardinelli, Wellington F Silva and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Blood advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

18 authors.

Douglas R A SilveiraService of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil.
Lynn QuekMedical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
Itamar S SantosInternal Medicine Department, Faculdade de Medicina, University of São Paulo, São Paulo, Brazil.
Anna CorbyMedical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
Juan L Coelho-SilvaDepartment of Medical Images, Hematology and Clinical Oncology, University of São Paulo at Ribeirao Preto Medical School, Ribeirao Preto, Brazil.
Diego A Pereira-MartinsDepartment of Medical Images, Hematology and Clinical Oncology, University of São Paulo at Ribeirao Preto Medical School, Ribeirao Preto, Brazil.
Grant VallanceDepartment of Hematology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.
Benjamin BrownMedical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
Luciana NardinelliService of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil.
Wellington F SilvaLeukemia Unit, Cancer Institute of São Paulo, University of São Paulo Medical School, São Paulo, Brazil; and.
Elvira D R P VellosoService of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil.
Antonio R Lucena-AraujoDepartment of Genetics, Federal University of Pernambuco, Recife, Brazil.
Fabiola TrainaDepartment of Medical Images, Hematology and Clinical Oncology, University of São Paulo at Ribeirao Preto Medical School, Ribeirao Preto, Brazil.
Andy PeniketDepartment of Hematology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.
Paresh VyasMedical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
Eduardo M RegoService of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil.
Israel BenditService of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil.
Vanderson RochaService of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil.

Funding

Medical Research Council G1000729Medical Research Council MC_U137961146Medical Research Council MC_UU_00016/11Medical Research Council MC_UU_12009/11Medical Research Council MR/L008963/1
6 · The paper itself

Abstract

The 2017 European LeukemiaNet 2017 acute myeloid leukemia (AML) risk stratification (ELN2017) is widely used for risk-stratifying patients with AML. However, its applicability in low- and middle-income countries is limited because of a lack of full cytogenetic and molecular information at diagnosis. Here, we propose an alternative for risk stratification (the Adapted Genetic Risk [AGR]), which permits cytogenetic or molecular missing data while retaining prognostic power. We first analyzed 167 intensively treated patients with nonacute promyelocytic leukemia AML enrolled in São Paulo, Brazil (Faculdade de Medicina da Universidade de São Paulo), as our training data set, using ELN2017 as the standard for comparison with our AGR. Next, we combined our AGR with clinical prognostic parameters found in a Cox proportional hazards model to create a novel scoring system (survival AML score, SAMLS) that stratifies patients with newly diagnosed AML. Finally, we have used 2 independent test cohorts, Faculdade de Medicina de Ribeirão Preto (FMRP; Brazil, n = 145) and Oxford University Hospitals (OUH; United Kingdom, n = 157) for validating our findings. AGR was statistically significant for overall survival (OS) in both test cohorts (FMRP, P = .037; OUH, P = .012) and disease-free survival in FMRP (P = .04). The clinical prognostic features in SAMLS were age (>45 years), white blood cell count (<1.5 or >30.0 × 103/μL), and low albumin levels (<3.8 g/dL), which were associated with worse OS in all 3 cohorts. SAMLS showed a significant difference in OS in the training cohort (P < .001) and test cohorts (FMRP, P = .0018; OUH, P < .001). Therefore, SAMLS, which incorporates the novel AGR evaluation with clinical parameters, is an accurate tool for AML risk assessment.

Indexed as

Leukemia, Myeloid, AcuteAdultBrazilHumansMiddle AgedPrognosisProportional Hazards ModelsUnited Kingdom

Identifiers

PMID32453839
PMCPMC7252562

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.