ArticleHematology, transfusion and cell therapy
Role of physical function in predicting short-term treatment outcome in Egyptian acute myeloid leukemia patients: a single center experience.
Article in Hematology, transfusion and cell therapy. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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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.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- A systematic review of physical function tests as predictors of key clinical outcomes for adults with blood cancers.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023Pooled it
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
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Abstract
backgroundAcute myeloid leukemia (AML) is a potentially fatal hematological disease. Along with disease-related factors, patient-related factors, in particular age, are a strong predictor of outcome that influence treatment decisions. Many acute myeloid leukemia risk stratification models have been developed to predict the outcome of intensive chemotherapy. However, these models did not include physical function assessments.
methodsThis study investigated the impact of several factors, namely the performance status, physical function and age on the short-term outcomes of intensive chemotherapy in a cohort of 50 Egyptian patients with
resultsComplete remission after intensive chemotherapy in these myeloid leukemia patients at Day 28 was 56% and the mortality rate was 12% and 34% at Day 28 and Day 60, respectively. The pretreatment Eastern Cooperative Oncology Group score was significantly correlated with outcomes on Day 28 and Day 60 (
conclusionPerformance status and physical function assessments were strong predictors of outcome of intensive chemotherapy in acute myeloid leukemia and we recommend the incorporation of these variables in risk stratification models for the personalization of therapy before treating acute myeloid leukemia patients with intensive chemotherapy.
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