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Background: Patients with lymphoma and chronic hepatitis B virus infection need to be treated with both chemotherapy and nucleotide analogue (NA) therapy. However, dynamic changes in HBV DNA loads with increasing chemotherapy cycles are lacking. It is unknown whether HBV replication markers, namely, the quantitative hepatitis B core antibody (qAnti-HBc), HBV RNA, and the hepatitis B virus core-related antigen (HBcrAg), are also markers for predicting HBV reactivation (HBVr). Methods: From 29 June 2010 to 6 December 2021, the data of patients with single-site diffuse large B-cell lymphoma and HBV infection (HBsAg+ and HBsAg−/anti-HBc+) were collected from a hospital medical record system, retrospectively. Serum HBV DNA loads (using real-time fluorescent quantitative PCR tests), qAnti-HBc levels (using a newly developed chemiluminescent particle immunoassay), HBV RNA levels (using the simultaneous amplification testing method based on real-time fluorescence detection), and HBcrAg levels (using a Lumipulse G HBcrAg assay) were tested, and factors related to HBVr were analyzed. Results: Under NAs, the HBV DNA loads of 69 HBsAg+ lymphoma patients declined from 3.15 (2.13–4.73) lg IU/mL to 1.00 (1.00–1.75) lg IU/mL, and further declined to 1.00 (1.00–1.04) lg IU/mL at the end of a 24-month follow-up. The qAnti-HBc levels decreased gradually during chemotherapy in HBsAg+ lymphoma patients (F = 7.090, p = 0.009). The HBV RNA and HBcrAg levels remained stable. A multivariate analysis revealed that higher qAnti-HBc levels (1.97 ± 1.20 vs. 1.12 ± 0.84 lg IU/mL, OR = 6.369, [95% CI: 1.523–26.641], p = 0.011) and higher HBV RNA levels (1.00 ± 1.13 vs. 0.37 ± 0.80 lg copies/mL, OR = 3.299, [95% CI: 1.229–8.854], p = 0.018) were related to HBVr in HBsAg−/anti-HBc+ lymphoma patients. Conclusions: HBV DNA loads declined under NAs during chemotherapy in lymphoma patients. In HBsAg−/anti-HBc+ lymphoma patients, a higher level of baseline serum qAnti-HBc and HBV RNA levels can predict the likelihood of HBVr during chemotherapy. [ABSTRACT FROM AUTHOR]

Background: To our knowledge, the different situations of identifying second primary malignant tumors (SPMTs) in lymphoma patients with synchronous solid tumors remain to be comprehensively investigated. Methods: We retrospectively collected information pertaining to lymphoma patients with synchronous solid tumors (diagnosed within 6 months) at Peking University Cancer Hospital & Institute between 2009 and 2019. The non‐parametric Aalen–Johansen estimator was applied to calculate cumulative incidence function in the competing risk model. Furthermore, propensity score‐matched analysis was performed to compare survival differences in lymphoma patients with or without synchronous solid tumors. Results: Thirty‐eight patients were enrolled. There were three situations of identifying SPMTs. First, in 15 patients (39.5%), SPMTs were identified before the initiation of any treatment. Among them, priority was given to anti‐lymphoma treatment in case of only three patients. Second, in 17 patients (44.7%), SPMTs were unexpectedly detected on surgical specimen assessment; of them, 13 received anti‐lymphoma treatment after surgery. Third, in six patients (15.8%), SPMTs were identified after the outset of treatment for the primary tumor; in this population, three of four patients with lymphoma switched toward the treatment plan for SPMTs. The 5‐year overall survival was 58.7%. The cumulative incidence function within 5 years was 26.6% for lymphoma and 14.7% for other solid tumors. The early identification of SPMTs was associated with better outcomes (p = 0.048). After balancing the baseline characteristics, no differences in survival were observed between lymphoma patients with and without synchronous solid tumors (p = 0.664). Conclusions: This is the first study to present the different situations of identifying SPMTs in lymphoma patients with synchronous solid tumors. In only <50% patients, SPMTs were identifiable at baseline. SPMT identification at different situations may make it difficult to choose the optimal therapeutic option, which may consequently impact patient survival. [ABSTRACT FROM AUTHOR]