Evidence map›Paper›PMID 37178373›Full record

ArticleOncology and therapy2023

Diagnostic and Treatment Obstacles in Acute Myeloid Leukemia: Social, Operational, and Financial.

Emine Eylem Genç, İrem Sena Saraç, Hayrunnisa Arslan, Ahmet Emre Eşkazan

Open access · goldAbstract read
In one paragraph

Article in Oncology and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. The global epidemiology of acute myeloid leukaemia.Nature reviews. Clinical oncology · 2026
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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

4 authors at 1 institution in 1 country.

Emine Eylem GençDepartment of Hematology, Tekirdağ Dr. Ismail Fehmi Cumalıoğlu State Hospital, Tekirdağ, Turkey.
İrem Sena SaraçCerrahpaşa Faculty of Medicine, Istanbul University-Cerrahpaşa, Istanbul, Turkey.
Hayrunnisa ArslanCerrahpaşa Faculty of Medicine, Istanbul University-Cerrahpaşa, Istanbul, Turkey.
Ahmet Emre EşkazanDivision of Hematology, Department of Internal Medicine, Cerrahpaşa Faculty of Medicine, Istanbul University-Cerrahpaşa, Fatih, Istanbul, Turkey. emre.eskazan@iuc.edu.tr.ORCID http://orcid.org/0000-0001-9568-0894
Istanbul University-Cerrahpaşa · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) can affect individuals of all ages, but is more common in older adults. It has been estimated that AML accounted for 1% of all newly diagnosed cancers in the USA in 2022. The diagnostic process varies depending on the presenting symptoms and the healthcare facility that patients attend at diagnosis. The treatment process is long and prone to complications, requiring experienced medical professionals and appropriate infrastructure. Treatment of the disease did not change greatly over the years until 2017 when targeted therapies were licensed. The treatment of AML is associated with significant direct economic costs. A number of obstacles originating both from individual patients and the healthcare system may be encountered during the diagnosis and treatment of the disease, which may negatively impact the optimal management of the disease process. In this article, we focus primarily on the social, operational, and financial obstacles including the corona virus disease 2019 (COVID-19) pandemic experienced during the diagnosis and treatment of AML.

Indexed as

Acute myeloid leukemiaAMLBarrierCostCOVID-19Diagnostic delayHealthcare utilizationHealth insurance

Identifiers

PMID37178373
PMCPMC10182356
OpenAlexW4376629894

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.