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Background: Disparities in multiple myeloma (MM) prognosis based on sociodemographic factors may exist. We investigated whether education level at diagnosis influenced Chinese MM patient outcomes. Methods: We performed a multicenter retrospective analysis of data from 773 MM patients across 9 centers in China from 2006 to 2019. Sociodemographic and clinical factors at diagnosis and treatment regimens were recorded, and univariate and multivariate analyses were performed. Results: Overall, 69.2% of patients had low education levels. Patients with low education levels differed from those with high education levels in that they were more likely to be older, and a higher proportion lived in rural areas, were unemployed, had lower annual incomes and lacked insurance. Additionally, compared to patients with high education levels, patients with low education levels had a higher proportion of international staging system (ISS) stage III classification and elevated lactate dehydrogenase (LDH) levels and underwent transplantation less often. Patients with high education levels had a median progression-free survival (PFS) of 67.50 (95% confidence interval (CI): 51.66-83.39) months, which was better than that of patients with low education levels (30.60 months, 95% CI: 27.38-33.82, p < 0.001). Similarly, patients with high education levels had a median overall survival (OS) of 122.27 (95% CI: 117.05-127.49) months, which was also better than that of patients with low education levels (58.83 months, 95% CI: 48.87-62.79, p < 0.001). In the multivariable analysis, patients with high education levels had lower relapse rates and higher survival rates than did those with low education level in terms of PFS and OS (hazard ratio (HR) = 0.50 [95% CI: 0.34-0.72], p < 0.001; HR = 0.32 [0.19-0.56], p < 0.001, respectively). Conclusions: Low education levels may independently predict poor survival in MM patients in China.

Purpose: Prediction models for acute myeloid leukemia (AML) are useful, but have considerable inaccuracy and imprecision. No current model includes covariates related to immune cells in the AML microenvironment. Here, an immune risk score was explored to predict the survival of patients with AML.Experimental Design: We evaluated the predictive accuracy of several in silico algorithms for immune composition in AML based on a reference of multi-parameter flow cytometry. CIBERSORTx was chosen to enumerate immune cells from public datasets and develop an immune risk score for survival in a training cohort using least absolute shrinkage and selection operator Cox regression model.Results: Six flow cytometry-validated immune cell features were informative. The model had high predictive accuracy in the training and four external validation cohorts. Subjects in the training cohort with low scores had prolonged survival compared with subjects with high scores, with 5-year survival rates of 46% versus 19% (P < 0.001). Parallel survival rates in validation cohorts-1, -2, -3, and -4 were 46% versus 6% (P < 0.001), 44% versus 18% (P ¼ 0.041), 44% versus 24% (P ¼ 0.004), and 62% versus 32% (P < 0.001). Gene set enrichment analysis indicated significant enrichment of immune relation pathways in the low-score cohort. In multivariable analyses, high-risk score independently predicted shorter survival with HRs of 1.45 (P ¼ 0.005), 2.12 (P ¼ 0.004), 2.02 (P ¼ 0.034), 1.66 (P ¼ 0.019), and 1.59 (P ¼ 0.001) in the training and validation cohorts, respectively.Conclusions: Our immune risk score complements current AML prediction models.

Adults with T-cell lymphoblastic lymphoma (T-LBL) generally benefit from treatment with acute lymphoblastic leukemia (ALL)-like regimens, but approximately 40% will relapse after such treatment. We evaluated the value of CpG methylation in predicting relapse for adults with T-LBL treated with ALL-like regimens.

This real-world, observational study aimed to assess and compare the clinical efficacy and safety of eltrombopag with recombinant human thrombopoietin (rhTPO) in the treatment of chemotherapy induced thrombocytopenia (CIT) in patients with lymphoma. One hundred and fifty-three patients who experienced grade 3 or 4 thrombocytopenia after chemotherapy for lymphoma were enrolled, 51 of which were treated with eltrombopag, 50 with rhTPO, and 52 patients with no drug treatment were served as the control group. The lowest platelet level and mean platelet counts at Day 5, Day 7, and Day 10 were significantly higher in both the eltrombopag group (P=.041,.003,.000,.000) and rhTPO group (P=.005,.005,.000,.000) than the control, but there was no difference between treatment with eltrombopag and rhTPO. Similarly, days required for the recovery of platelet counts to ≥50×109/L and ≥75×109/L were not different between the two treatment groups but significantly higher than the control group (P &lt;.05). Rates of bleeding and platelet transfusion were all significantly reduced in patients treated with eltrombopag (P=.031,.032) or rhTPO (P=.017,.009) when compared to the control. Treatment-related adverse events (AEs) were reported in 7 (13.7%) and 6 (12.0%) patients in the eltrombopag and rhTPO groups, respectively, all being mild and transient in nature. In conclusion, both eltrombopag and rhTPO were effective and safe in the treatment of thrombocytopenia after chemotherapy for lymphoma.