ArticleCancers2022
Screening a Targeted Panel of Genes by Next-Generation Sequencing Improves Risk Stratification in Real World Patients with Acute Myeloid Leukemia.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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.
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Who cites it
4 citing papers in PubMed.
- Integrating Genomic and Clinical Data in AML: Real-World Application of the Sanger Multistage Model.Genes · 2026Article
- Apoptosis-targeting BH3 mimetics: transforming treatment for patients with acute myeloid leukaemia.Nature reviews. Clinical oncology · 2025Review
- Acute myeloid leukemia in the next-generation sequencing era : Real-world data from an Austrian tertiary cancer care center.Wiener klinische Wochenschrift · 2025Article
- T-cell acute lymphoblastic leukaemia: subtype prevalence, clinical outcome, and emerging targeted treatments.Leukemia · 2025Review
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
Although mutation profiling of defined genes is recommended for classification of acute myeloid leukemia (AML) patients, screening of targeted gene panels using next-generation sequencing (NGS) is not always routinely used as standard of care. The objective of this study was to prospectively assess whether extended molecular monitoring using NGS adds clinical value for risk assessment in real-world AML patients. We analyzed a cohort of 268 newly diagnosed AML patients. We compared the prognostic stratification of our study population according to the European LeukemiaNet recommendations, before and after the incorporation of the extended mutational profile information obtained by NGS. Without access to NGS data, 63 patients (23%) failed to be stratified into risk groups. After NGS data, only 27 patients (10%) failed risk stratification. Another 33 patients were re-classified as adverse-risk patients once the NGS data was incorporated. In total, access to NGS data refined risk assessment for 62 patients (23%). We further compared clinical outcomes with prognostic stratification, and observed unexpected outcomes associated with
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