Background: Primary lymphoma of the breast is rare, and primary diffuse large B cell lymphoma (DLBCL) of the breast is very rare. This study aimed to identify the clinicopathological characteristics and treatment associated with prognosis in patients with primary DLBCL of the breast. Material/Methods: A retrospective study included the clinical and treatment data from 46 women with a histological diagnosis of primary DLBCL. Patients were staged using Ann Arbor staging criteria, overall survival (OS), progression-free survival (PFS), and the international prognostic index (IPI) scores were obtained. Laboratory finding included serum lactate dehydrogenase (LDH), and the immunohistochemistry findings were recorded. Results: Patients (n=46), included stage I (n=18), stage II (n=18), stage III (n=3), and stage IV DLBCL (n=9). Treatment included chemotherapy with rituximab (n=16), and radiotherapy (n=12). The median follow-up time was 40.5 months, the 5-year OS rate was 36.2%, and the 5-year PFS rate was 29.1%. Univariate analysis showed that clinical stage, serum LDH, the IPI score, chemotherapy cycles >3, and Bcl-2 and Bcl-6 expression were correlated with the 5-year OS and PFS. Multivariate risk regression analysis showed that the number of chemotherapy cycles (>3) and Bcl-6 expression were independent prognostic factors in primary DLBCL of the breast (P<0.05). Conclusions: A retrospective study of 46 patients with primary DLBCL of the breast showed that >3 cycles of chemotherapy and expression of Bcl-6 resulted in improved OS and PFS. Radiotherapy controlled local tumor recurrence but did not improve the OS and PFS. Rituximab did not improve patient survival.
Background: Primary thyroid diffuse large B cell lymphoma (DLBCL) is a rare type of extranodal lymphoma; optimal treatment methods and the key prognostic factors have not been established. Methods: The clinical data of 58 patients with primary thyroid DLBCL from January 2007 to December 2017 were collected. The Kaplan–Meier method and log-rank tests were used for the survival analysis. Cox regression analysis was performed to evaluate the prognostic factors. Results: The follow-up time was 6–120 months; 5-year overall survival (OS) and progression-free survival (PFS) were 73 and 61%, respectively. Single-factor analysis showed that IPI, Ki-67, treatment modalities, Hans classification, Myc/Bcl-2 protein co-expression, and administration of rituximab had a significant effect on the 5-year OS and PFS ( P < 0.05), while age, sex, Bcl-2 protein expression, Myc protein expression, tumor stage, tumor size, Hashimoto's thyroiditis, and B symptoms were not associated with prognosis ( P > 0.05). Multivariate risk regression analysis revealed that Myc/Bcl-2 protein co-expression, treatment modalities, and rituximab were independent prognostic factors ( P < 0.05). Conclusions: Patients with primary thyroid DLBCL who received combination chemotherapy with radiotherapy had a better prognosis. Surgical treatment alone was not associated with the prognosis and is used only for diagnosis. Rituximab could improve the survival time of patients.
Background: Triple-negative breast cancer (TNBC) is a highly heterogeneous disease and the current prognostic system cannot meet the clinical need. Interactions between immune responsiveness and tumor cells plays a key role in the progression of TNBC and macrophages are vital component of immune cells. A prognostic model based on macrophages may have great accuracy and clinical utility. Methods: For model development, we screened early stage (without metastasis) TNBC patients from The Cancer Genome Atlas (TCGA) database. We extracted messenger RNA (mRNA) expression data and clinical data including age, race, tumor size, lymph node status and tumor stage. The follow up time and vital status were also retrieved for overall survival calculation. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) was used to calculate the immune cell composition of each sample.Weighted gene co-expression network analysis (WGCNA) was used to identify M1-like macrophage-related genes. Combining least absolute shrinkage and selection operator (LASSO) with multivariate Cox regression, the M1-like macrophage polarization-related prognostic index (MRPI) was established. We obtained TNBC patients in Gene Expression Omnibus (GEO) database through PAM50 method and retrieved the mRNA expression data and survival data. The Harrell's concordance index (CI), the area under the receiver operating characteristic (ROC) curves (AUCs) and the calibration curve were used to evaluate the developed model. Results:We obtained 166 early TNBC cases and 113 normal tissue cases for model building, along with 76 samples from GSE58812 cohort for model validation. CIBERSORT analysis suggested obvious infiltration of macrophages, especially M1-like macrophages in early TNBC. Four genes were eventually identified for the construction of MPRI in the training set. The AUCs at 2 years, 3 years, and 5 years in the training cohort were 0.855, 0.881 and 0.893, respectively; and the AUCs at 2 years, 3 years, and 5 years in the validation cohort were 0.887, 0.792 and 0.722, respectively. Calibration curves indicated good predictive ability and high consistency of our model.Conclusions: MRPI is a promising biomarker for predicting the prognosis of early-stage TNBC, which may indicate personalized treatment and follow-up strategies and thus may improve the prognosis.
There is a positive association between air pollution and lung cancer burden. This study aims to identify and examine lung cancer risks and mortality burdens associated with air pollutants, including PM10, NO2 and SO2, in seven eastern metropolises of China. The study population comprised a population from seven eastern metropolises of China. The yearly average values (YAV, μg/m3) of the PM10, NO2 and SO2 levels were extracted from China Statistical Yearbook (CSYB) for each selected city from 2006 to 2014. Data collected in the China Cancer Registry Annual Report (CCRAR) provide lung cancer incidence and mortality information. A two-level normal random intercept regression model was adopted to analyze the association between the lung cancer rates and individual air pollutant concentration within a five-year moving window of past exposure. The yearly average values of PM10, SO2 and NO2 significantly decreased from 2006 to 2014. Consistently, the male age-adjusted incidence rate (MAIR) and male age-adjusted mortality rate (MAMR) decreased significantly from 2006 to 2014.Air pollutants have a lag effect on lung cancer incidence and mortality for 2-3 years. NO2 has the significant association with MAIR (RR=1.57, 95% CI: 1.19-2.05, p=0.002), MAMR (RR=1.70, 95% CI: 1.32-2.18, p=0.0002) and female age-adjusted mortality rate (FAMR) (RR=1.27, 95% CI: 1.08-1.49, p=0.003). Our findings suggested that air pollutants may be related to the occurrence and mortality of lung cancer. NO2 was significantly associated with the risk of lung cancer, followed by SO2. Air pollutants have the strongest lag effect on the incidence and mortality of lung cancer within 2-3 years.
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