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Cytometry. Part B, Clinical Cytometry May 2021
Topics: Aged, 80 and over; CD4 Antigens; CD56 Antigen; Dendritic Cells; Flow Cytometry; Humans; Leukemia, Myelomonocytic, Chronic; Male; Myeloproliferative Disorders; Skin Neoplasms
PubMed: 32830878
DOI: 10.1002/cyto.b.21932 -
Frontiers in Oncology 2021Numerous examples in oncology have shown that better understanding the pathophysiology of a malignancy may be followed by the development of targeted treatment concepts...
Numerous examples in oncology have shown that better understanding the pathophysiology of a malignancy may be followed by the development of targeted treatment concepts with higher efficacy and lower toxicity as compared to unspecific treatment. The pathophysiology of chronic myelomonocytic leukemia (CMML) is heterogenous and complex but applying different research technologies have yielded a better and more comprehensive understanding of this disease. At the moment treatment for CMML is largely restricted to the unspecific use of cytotoxic drugs and hypomethylating agents (HMA). Numerous potential molecular targets have been recently detected by preclinical research which may ultimately lead to treatment concepts that will provide meaningful benefits for certain subgroups of patients.
PubMed: 34660314
DOI: 10.3389/fonc.2021.751668 -
Hematology (Amsterdam, Netherlands) Dec 2021The present meta-analysis was performed to evaluate the efficacy, toxicities of both hypomethylating agents (decitabine and azaciticine) in the treatment of CMML... (Meta-Analysis)
Meta-Analysis
OBJECTIVES
The present meta-analysis was performed to evaluate the efficacy, toxicities of both hypomethylating agents (decitabine and azaciticine) in the treatment of CMML patients.
METHODS
All available cohort studies of patients with CMML treated with decitabine and azacitidine were identified. The primary endpoints of this meta-analysis were response to hypomethylating agents. Pooled estimates of treatment response and drug-related adverse events were calculated using fixed or random effect models.
RESULTS
Fourteen studies with 600 CMML patients (decitabine: n=196; azacitidine: n=404) were identified and included for meta-analysis. HMAs yielded a pooled ORR estimate of 43% (95% CI: 36%-50%) in patients with CMML. Patients received either azacitidine or decitabine exhibited comparable incidence of ORR (43% vs. 45%, P=0.810), while significantly higher incidence of mCR was observed in patients treated with decitabine (23% vs. 10%, P=0.000). Decitabine treatment was also associated with higher incidence of transfusion independence (42% vs. 20%, P=0.044). Both HMAs led to objective hematologic or non-hematologic AEs (27%-43%), while dosage modification/delay were more frequent in patients treated with azacitidine (81% vs. 67%, P=0.021).
CONCLUSION
This current study may provide preliminary data in evaluating the efficacy and safety of HMAs in patients with CMML. Decitabine and azacitidine are comparable effective and safe in treating CMML. However, it is necessary to point out that any comparison of decitabine and azacitidine with respect to clinical outcomes can only be done in the context of a randomized controlled trial.
Topics: Antimetabolites, Antineoplastic; Azacitidine; Decitabine; Humans; Leukemia, Myelomonocytic, Chronic; Treatment Outcome
PubMed: 33706667
DOI: 10.1080/16078454.2021.1875600 -
Scandinavian Journal of Immunology Jan 2020Tumour-associated macrophages (TAMs) play an important role in the tumour environment and were reported to be associated with poor prognosis in several tumours. However,... (Meta-Analysis)
Meta-Analysis
Tumour-associated macrophages (TAMs) play an important role in the tumour environment and were reported to be associated with poor prognosis in several tumours. However, the prognostic significance of TAMs in Non-Hodgkin's Lymphoma (NHL) remains controversial. Consequently, we aimed to evaluate the relationship between subpopulations of TAMs and clinical outcomes in NHL patients. We did a comprehensive search of the PubMed, elsevier ScienceDirect, and Cochrane databases and extracted hazard ratio (HR) and their corresponding 95% confidence intervals (95% CIs) from eligible studies. Pooling total effect value by the stata statistical software and analysing correlation of TAMs with overall survival (OS) and progression-free survival (PFS). Furthermore, subgroup analysis and sensitivity analysis were also conducted. We deemed eleven studies, including 1211 NHL patients. Our study demonstrated that high-density CD68 TAMs are associated with poor OS (HR: 1.17; 95% CI, 0.81-1.54; P = .000) and poor PFS (HR: 1.15; 95% CI, 0.63-1.67; P = .000) compared with low-density CD68 TAMs in the tumour microenvironment. Similarly, high-density CD163 TAMs can also predict poor OS (HR: 1.52; 95% CI, 1.11-1.92; P = .000) and shorter PFS (HR: 1.52; 95% CI, 0.73-2.30; P = .000). In addition, the high CD163 /CD68 TAMs ratio is significantly correlated with poor OS (HR: 3.59; 95% CI, 0.77-6.40; P = .013). However, in our subgroup analysis, high-density CD68 TAMs in the tumour microenvironment is associated with better OS (HR: 0.75; 95% CI, 0.41-1.09; P = .000) in NHL patients treated with rituximab chemotherapy. Our results suggest that TAMs are a robust predictor of outcomes in NHL.
Topics: Animals; Antigens, CD; Antigens, Differentiation, Myelomonocytic; Biomarkers; Cell Count; Humans; Immunophenotyping; Lymphoma, Non-Hodgkin; Macrophages; Prognosis; Publication Bias; Receptors, Cell Surface; Tumor Microenvironment
PubMed: 31419843
DOI: 10.1111/sji.12814 -
Journal of the American Academy of... Jun 2024
Review
PubMed: 38906261
DOI: 10.1016/j.jaad.2024.05.086 -
Journal of Musculoskeletal & Neuronal... Mar 2021Osteosarcoma (OS) is the most common type of primary malignant bone tumor, The effect of tumor microenvironment components on OS oncogenesis remains unknown. (Meta-Analysis)
Meta-Analysis
OBJECTIVES
Osteosarcoma (OS) is the most common type of primary malignant bone tumor, The effect of tumor microenvironment components on OS oncogenesis remains unknown.
METHODS
To investigate the function of immune cells in osteosarcoma, we provided a text-based GMT (Gene Matrix Transposed) file in which each line defines one of lm22 with their markers. We used STRING to draw DEG's PPI network and selected hub genes and modules. Then, survival analysis was conducted to hub genes. We identified 10,390 common genes, and identified 218 DEGs based on the combined t-value and Z scores.
RESULTS
The KEGG and GSEA enrichment analysis showed that macrophages are significantly activated in osteosarcoma. PPI network analysis revealed that hub gene CD163 molecule. We found that the expression of CD163 was negatively associated with the OS of osteosarcoma patients. These results suggest that macrophages are a risk factor in patients with osteosarcoma.
CONCLUSIONS
This study has systematically validated results of the studies carried out previously and filled up the gap in the field of OS on large-scaled meta-analysis. In addition, for the hub gene (CD163) and the macrophage cell capable of being used as a novel biomarker in promoting early diagnosis and development of therapeutic approaches.
Topics: Antigens, CD; Antigens, Differentiation, Myelomonocytic; Bone Neoplasms; Databases, Genetic; Gene Regulatory Networks; Humans; Immunity, Cellular; Macrophages; Osteosarcoma; Prognosis; Protein Array Analysis; Receptors, Cell Surface; Tumor Microenvironment
PubMed: 33657763
DOI: No ID Found -
Value in Health : the Journal of the... Jul 2020We performed a systematic review of health state utility values (HSUVs) obtained using the EQ-5D questionnaire for patients with hematologic malignancies.
OBJECTIVES
We performed a systematic review of health state utility values (HSUVs) obtained using the EQ-5D questionnaire for patients with hematologic malignancies.
METHODS
The following databases were searched up to September 2018: MEDLINE, EMBASE, The Cochrane Library, and the EQ-5D publications database on the EuroQol website. Additional references were extracted from reviewed articles. Only studies presenting EQ-Index results were incorporated. In view of the heterogeneity across the included publications, we limited ourselves to a narrative synthesis of original HSUVs found.
RESULTS
Fifty-nine studies (described in 63 articles) met the inclusion criteria. Data from 21 635 respondents provided 796 HSUV estimates for hematologic malignancy patients. EQ-Index scores ranged from -0.025 to 0.980. The most represented area was multiple myeloma (4 studies, 11 112 patients, and 249 HSUVs). In clinical areas such as chronic myeloid leukemia, acute myeloid leukemia, chronic lymphocytic leukemia, non-Hodgkin lymphoma, and mantle cell lymphoma, we described over 50 health utilities in each. In contrast, we identified only 13 HSUVs (based on 4 studies and the data of 166 patients) for Hodgkin lymphoma. Areas without EQ-5D-based health utilities comprised: polycythemia vera, primary myelofibrosis, essential thrombocythemia, mastocytosis, myeloid sarcoma, chronic myelomonocytic, eosinophilic leukemia, and neutrophilic leukemia.
CONCLUSIONS
There is a wide range of HSUVs available for hematologic cancer patients with different indications. The review provides a catalog of utility values for use in cost-effectiveness models for hematologic malignancies.
Topics: Cost-Benefit Analysis; Health Status; Hematologic Neoplasms; Humans; Models, Economic; Quality of Life; Surveys and Questionnaires
PubMed: 32762998
DOI: 10.1016/j.jval.2020.04.1825