The DOI matches its Crossref record; 177 of the 177 references it cites were found in a registry or an index.
Acute myeloid leukemia: 2023 update on diagnosis, risk‐stratification, and management
Open accessAbstract
Disease overview: Acute myeloid leukemia (AML) is a frequently fatal bone marrow stem cell cancer characterized by unbridled proliferation of malignant marrow stem cells with associated infection, anemia, and bleeding. An improved understanding of pathophysiology, improvements in measurement technology and at least 10 recently approved therapies have led to revamping the diagnostic, prognostic, and therapeutic landscape of AML. Diagnosis: One updated and one new classification system were published in 2022, both emphasizing the integration of molecular analysis into daily practice. Differences between the International Consensus Classification and major revisions from the previous 2016 WHO system provide both challenges and opportunities for care and clinical research. Risk assessment and monitoring: The European Leukemia Net 2022 risk classification integrates knowledge from novel molecular findings and recent trial results, as well as emphasizing dynamic risk based on serial measurable residual disease assessment. However, how to leverage our burgeoning ability to measure a small number of potentially malignant myeloid cells into therapeutic decision making is controversial. Risk adapted therapy: The diagnostic and therapeutic complexity plus the availability of newly approved agents requires a nuanced therapeutic algorithm which should integrate patient goals of care, comorbidities, and disease characteristics including the specific mutational profile of the patient's AML. The framework we suggest only represents the beginning of the discussion.
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Arber, D. A., Orazi, A., Hasserjian, R., Thiele, J., Borowitz, M. J., Le Beau, M. M., Bloomfield, C. D., Cazzola, M., & Vardiman, J. W. (2016) · Blood · doi:10.1182/blood-2016-03-643544 · Cited by 10,119 · cited 1×
“in the bone marrow or peripheral blood, any evidence of extramedullary myeloblasts (myeloid sarcoma), or presence of AML defining genetic abnormalities PML::RARA, RUNX1::RUNX1T1, and CBFB:: MYH11 irrespective of blast percentage.(42) Of note, Acute promyelocytic leukemia (APL), usually associated with a PML::RARA tran…”
BackgroundDöhner, H., Estey, E., Grimwade, D., Amadori, S., Appelbaum, F. R., Büchner, T., Dombret, H., Ebert, B. L., Fenaux, P., Larson, R. A., et al. (2017) · Blood · doi:10.1182/blood-2016-08-733196 · Cited by 5,775
Genomic classification and prognosis in acute myeloid leukemia
Papaemmanuil, E., Gerstung, M., Bullinger, L., Gaidzik, V. I., Paschka, P., Roberts, N. D., Potter, N. E., Heuser, M., Thol, F., Bolli, N., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1516192 · Cited by 4,350
Khoury, J. D., Solary, E., Abla, O., Akkari, Y., Alaggio, R., Apperley, J. F., Bejar, R., Berti, E., Busque, L., Chan, J. K. C., et al. (2022) · Leukemia · doi:10.1038/s41375-022-01613-1 · Cited by 4,274
Döhner, H., Weisdorf, D. J., & Bloomfield, C. D. (2015) · New England Journal of Medicine · doi:10.1056/nejmra1406184 · Cited by 3,306
Döhner, H., Wei, A. H., Appelbaum, F. R., Craddock, C., DiNardo, C. D., Dombret, H., Ebert, B. L., Fenaux, P., Godley, L. A., Hasserjian, R. P., et al. (2022) · Blood · doi:10.1182/blood.2022016867 · Cited by 3,279
Arber, D. A., Orazi, A., Hasserjian, R. P., Borowitz, M. J., Calvo, K. R., Kvasnicka, H.-M., Wang, S. A., Bagg, A., Barbui, T., Branford, S., et al. (2022) · Blood · doi:10.1182/blood.2022015850 · Cited by 2,945
Self-citationAzacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia
DiNardo, C. D., Jonas, B. A., Pullarkat, V., Thirman, M. J., Garcia, J. S., Wei, A. H., Konopleva, M., Döhner, H., Letai, A., Fenaux, P., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2012971 · Cited by 2,900
Figueroa, M. E., Abdel-Wahab, O., Lu, C., Ward, P. S., Patel, J., Shih, A., Li, Y., Bhagwat, N., Vasanthakumar, A., Fernandez, H. F., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.11.015 · Cited by 2,766
Midostaurin plus Chemotherapy for Acute Myeloid Leukemia with a FLT3 Mutation
Stone, R. M., Mandrekar, S. J., Sanford, B. L., Laumann, K., Geyer, S., Bloomfield, C. D., Thiede, C., Prior, T. W., Döhner, K., Marcucci, G., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1614359 · Cited by 2,250
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Cited by
Glycosylation: mechanisms, biological functions and clinical implications
He, M., Zhou, X., & Wang, X. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01886-1 · Cited by 499
Hossen, M. A., Jahan, U. M. S., Hossain, M. A., Asif, K. H., Rahman, A., Ahmed, S., Uddin, M. M., Amin, M. F., Barik, M. A., Islam, M. J., et al. (2025) · PLOS One · doi:10.1371/journal.pone.0320550 · Cited by 8
Metadata
- Authors
- Shimony, S., Stahl, M., & Stone, R. M.
- Venue
- American Journal of Hematology
- Publisher
- Wiley
- Published
- 2023-01-13
- Volume
- 98
- Issue
- 3
- Pages
- 502-526
- ISSN
- 0361-8609 (ISSN-L)
- 1096-8652
- OpenAlex
- W4313454313
- Cited by
- 448
- References
- 177
- FWCI
- 81.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- CoChat. (2026). Citation check: Acute myeloid leukemia: 2023 update on diagnosis, risk‐stratification, and management. https://app.cochat.ai/papers/10.1002/ajh.26822
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- Shimony, S., Stahl, M., & Stone, R. M. (2023). Acute myeloid leukemia: 2023 update on diagnosis, risk‐stratification, and management. American Journal of Hematology. https://doi.org/10.1002/ajh.26822
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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