Myeloid sarcoma concurrent with de novo <i>KMT2A</i> gene‐rearranged infantile acute lymphoblastic leukemia

Abe, Hideki; Hamada, Satoru; Sakiyama, Hideki; Oshiro, Tokiko; Kato, Miyako; Yagi, Takeshi; Matsuda, Takehiro; Higa, Takeshi; Hyakuna, Nobuyuki; Nakanishi, Koichi

doi:10.1002/pbc.29573

Cited by 2 publications

(1 citation statement)

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“…As previously stated, MS was listed as an AML subtype by the World Health Organization (WHO) and considered as a specific presentation of many other myeloid neoplasms, including MDS, MPN, and CML ( 1 , 12 , 13 ). Recently, two cases were reported in which MS and acute lymphoblastic leukemia occurred simultaneously ( 14 , 15 ). MS’s complex association with other hematologic neoplasms has resulted in a lack of separate epidemiologic data.…”

Section: Discussionmentioning

confidence: 99%

Incidence, clinical characteristics, and prognostic nomograms for patients with myeloid sarcoma: A SEER-based study

Xing

Zhu

et al. 2022

Front. Oncol.

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BackgroundMyeloid sarcoma (MS) is a rare hematological tumor that presents with extramedullary tumor masses comprising myeloid blasts. A controversial issue is whether MS involving normal hematopoietic sites (liver, spleen, and lymph nodes) should be excluded in future studies. We aimed to compare MS characteristics and outcomes involving hematopoietic and non-hematopoietic sites and construct a prognostic nomogram exclusively for the latter.MethodsData from patients diagnosed with MS between 2000 and 2018 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. According to the primary site, patients were classified as having MS involving hematopoietic sites (hMS) or non-hematopoietic sites (eMS). Clinical characteristics and survival outcomes were compared between the two groups using Wilcoxon, chi-square, and log-rank tests. Cox regression analysis was used to identify eMS prognostic factors to establish prognostic nomograms. The models’ efficiency and value were assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).ResultsIn total, 694 patients were enrolled, including 86 with hMS and 608 with eMS. There were no sex, race or marital status distribution differences between the two groups. Patients with eMS had better overall and cancer-specific survival rates than those with hMS. Additionally, prognostic factor effects differed between the two groups. Patients with eMS were randomly divided into the training (number of patiens, n=425) and validation cohorts (n=183). Age, first primary tumor, primary site, and chemotherapy were used to establish nomograms. The C-index values of overall survival (OS) and cancer-specific survival (CSS) nomograms were 0.733 (validation: 0.728) and 0.722 (validation: 0.717), respectively. Moreover, ROC, calibration curves, and DCA confirmed our models’ good discrimination and calibration ability and potential clinical utility value.ConclusionOur study described the differences between patients with eMS and those with hMS. Moreover, we developed novel nomograms based on clinical and therapeutic factors to predict patients with eMS’ 1-, 3- and 5-year survival rates.

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