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Record W4210334637 · doi:10.1371/journal.pone.0263240

Less intensive antileukemic therapies (monotherapy and/or combination) for older adults with acute myeloid leukemia who are not candidates for intensive antileukemic therapy: A systematic review and meta-analysis

2022· review· en· W4210334637 on OpenAlexaff
Luis Enrique Colunga‐Lozano, Fernando Kenji Nampo, Arnav Agarwal, Pinkal Desai, Mark R. Litzow, Mikkael A. Sekeres, Gordon Guyatt, Romina Brignardello‐Petersen

Bibliographic record

VenuePLoS ONE · 2022
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity of TorontoMcMaster UniversityImpact
FundersAmerican Society of Hematology
KeywordsMedicineInternal medicineRandomized controlled trialAzacitidineCytarabineNeutropeniaFebrile neutropeniaHazard ratioDecitabineMeta-analysisCombination therapyRelative riskOncologyMyeloid leukemiaConfidence intervalChemotherapy

Abstract

fetched live from OpenAlex

INTRODUCTION: Elderly patients with acute myeloid leukemia not eligible for intensive antileukemic therapy are treated with less intensive therapies, uncertainty remains regarding their relative merits. OBJECTIVES: To compare the effectiveness and safety of less intensive antileukemic therapies for older adults with newly diagnosed AML not candidates for intensive therapies. METHODS: We included randomized controlled trials (RCTs) and non-randomized studies (NRS) comparing less intensive therapies in adults over 55 years with newly diagnosed AML. We searched MEDLINE and EMBASE from inception to August 2021. We assessed risk of bias of RCTs with a modified Cochrane Risk of Bias tool, and NRS with the Non-Randomized Studies of Interventions tool (ROBINS-I). We calculated pooled hazard ratios (HRs), risk ratios (RRs), mean differences (MD) and their 95% confidence intervals (CIs) using a random-effects pairwise meta-analyses and assessed the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. RESULTS: We included 27 studies (17 RCTs, 10 NRS; n = 5,698), which reported 9 comparisons. Patients were treated with azacitidine, decitabine, and low-dose cytarabine (LDAC), as monotherapies or in combination with other agents. Moderate certainty of evidence suggests no convincing difference in overall survival of patients who receive azacitidine monotherapy compared to LDAC monotherapy (HR 0.69; 95% CI, 0.31-1.53), fewer febrile neutropenia events occurred between azacitidine monotherapy to azacitidine combination (RR 0.45; 95% CI, 0.31-0.65), and, fewer neutropenia events occurred between LDAC monotherapy to decitabine monotherapy (RR 0.62; 95% CI 0.44-0.86). All other comparisons and outcomes had low or very low certainty of evidence. CONCLUSION: There is no convincing superiority in OS when comparing less intensive therapies. Azacitidine monotherapy is likely to have fewer adverse events than azacitidine combination (febrile neutropenia), and LDAC monotherapy is likely to have fewer adverse events than decitabine monotherapy (neutropenia).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.036
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0200.031
Bibliometrics0.0060.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.125
GPT teacher head0.335
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations4
Published2022
Admission routes1
Has abstractyes

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