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Record W4206528978 · doi:10.3390/cancers14030478

Early Palliative Care in Acute Myeloid Leukemia

2022· review· en· W4206528978 on OpenAlexaff
Leonardo Potenza, Eleonora Borelli, Sarah Bigi, Davide Giusti, Giuseppe Longo, Oreofe O. Odejide, Carlo Adolfo Porro, Camilla Zimmermann, Fabio Efficace, Éduardo Bruera, Mario Luppi, Elena Bandieri

Bibliographic record

VenueCancers · 2022
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineMyeloid leukemiaPalliative careCoping (psychology)Intensive care medicineQuality of life (healthcare)Randomized controlled trialDiseaseOncologyInternal medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Several novel targeted therapies seem to improve the outcome of acute myeloid leukemia (AML) patients. Nonetheless, the 5-year survival rate remains below 40%, and the trajectory of the disease remains physically and emotionally challenging, with little time to make relevant decisions. For patients with advanced solid tumors, the integration of early palliative care (EPC) with standard oncologic care a few weeks after diagnosis has demonstrated several benefits. However, this model is underutilized in patients with hematologic malignancies. METHODS: In this article, we analyze the palliative care (PC) needs of AML patients, examine the operational aspects of an integrated model, and review the evidence in favor of EPC integration in the AML course. RESULTS: AML patients have a high burden of physical and psychological symptoms and high use of avoidant coping strategies. Emerging studies, including a phase III randomized controlled trial, have reported that EPC is feasible for inpatients and outpatients, improves quality of life (QoL), promotes adaptive coping, reduces psychological symptoms, and enhances the quality of end-of-life care. CONCLUSIONS: EPC should become the new standard of care for AML patients. However, this raises issues about the urgent development of adequate programs of education to increase timely access to PC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.377
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations27
Published2022
Admission routes1
Has abstractyes

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