Baseline Serum Cholinesterase Levels Predict the Outcome of HIV-Related Diffuse Large B-Cell Lymphoma

Baseline Serum Cholinesterase Levels Predict the Outcome of HIV-Related Diffuse Large B-Cell Lymphoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Baseline Serum Cholinesterase Levels Predict the Outcome of HIV-Related Diffuse Large B-Cell Lymphoma Minghan Zhou, Jiaying Qin, Yong Tong, Lingyun Wang, Shasha Ye, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3880969/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Serum cholinesterase (CHE) has been utilized as a surrogate marker in the context of solid cancers. Nevertheless, its potential association with the prognosis of hematologic malignancies remains unclear. Methods Sixty-five patients with new-onset HIV-related diffuse large B-cell lymphoma (DLBCL) were enrolled in this retrospective study. The patients were categorized into a high CHE group (> 5500 U/L) and a low CHE group (≤ 5500 U/L). The demographic details, laboratory test results and clinical outcomes were compared between the high CHE group and the low CHE group. The overall response rate (ORR) at the end of chemotherapy was assessed by logistic regression analysis, and the 1-year overall survival rate (OS) was assessed by a multivariate Cox proportional hazards model. Results Compared with patients with high CHE, HIV-related DLBCL patients with low CHE exhibited lower levels of hemoglobin [g/L; 101.0 (81.0-115.0) vs. 123.5 (108.2–141.0), P < 0.001] and serum albumin [g/L; 31.2 ± 5.6 vs. 40.4 ± 4.5, P < 0.001] but higher levels of lactate dehydrogenase (LDH) [U/L; 404.0 (253.0-849.0) vs. 248.0 (178.3–372.0), P = 0.014] and C-reactive protein (CRP) [mg/L; 36.1 (5.8–66.6) vs. 5.1 (0.8–5.1), P < 0.001]. Moreover, HIV-related DLBCL patients with low CHE demonstrated a higher prevalence of Ann Arbor stage III/IV (92.6% vs. 56.8%, P < 0.001) and International Prognostic Index (IPI) ≥ 3 (85.2% vs. 35.1%, P = 0.002) at the time of diagnosis of DLBCL. The 1-year OS of patients was 84.2% in the high CHE group and 40.7% in the low CHE group (log-rank P < 0.001). At the end of chemotherapy, the ORR was 80.0% in the high CHE group and 31.8% in the low CHE group (P 5500 U/L was independently associated with a higher ORR [adjusted odds ratio (AOR): 4.74 (1.02–22.06), P = 0.047] and lower 1-year mortality [hazard ratio (HR): 0.11 (0.03–0.52), P = 0.005]. Conclusion Based on our robust data, baseline serum CHE levels show great potential as a surrogate marker for risk stratification and for guiding treatment decisions in HIV-related DLBCL patients. cholinesterase human immunodeficiency virus diffuse large B-cell lymphoma prognosis Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Human immunodeficiency virus (HIV) infection increases the risk of diffuse large B-cell lymphoma (DLBCL), which accounts for 35–60% of all reported non-Hodgkin lymphoma (NHL) cases [ 1 – 3 ] . HIV-related DLBCL is characterized by an advanced stage at diagnosis, a higher incidence of extranodal involvement, and an increased frequency of B symptoms compared to the corresponding characteristics in the general population [ 3 , 4 ] . The implementation of combined antiretroviral therapy (cART) and conventional intensive chemotherapy regimens has resulted in improved survival rates for HIV-related DLBCL. Nevertheless, the prognosis for HIV-related DLBCL patients remains poor in resource-limited areas due to challenges in medical conditions, economic costs and misconceptions about the disease [ 4 ] . In sub-Saharan Africa, for example, the 2-year survival rate of patients with HIV-related DLBCL is only 38–55% [ 5 , 6 ] . In clinical practice, it is crucial to identify HIV-related DLBCL patients who are at a high risk of mortality. Consequently, there is an urgent need to find a simple and readily available laboratory indicator that can predict the outcomes of these patients. Serum cholinesterase (CHE), as a reliable indicator of liver synthetic function, is closely linked to conditions such as hepatic impairment, malnutrition, heart failure, and progressive systemic inflammation [ 7 ] . Recent studies have shown that low serum CHE levels are associated with poor prognosis and decreased chemotherapy effectiveness in various solid cancers, such as gastric cancer [ 8 ] , prostate cancer [ 9 ] , pancreatic cancer [ 10 ] , colorectal cancer [ 11 ] , and non-small cell lung cancer [ 12 ] , regardless of hepatic involvement. Research on the correlation between serum CHE levels and hematologic malignancies is currently limited. Previous studies have shown that persistent inflammation and malnutrition are both associated with unfavorable outcomes in patients with HIV-related DLBCL [ 13 – 15 ] . Given that CHE is an important indicator of chronic inflammation and malnutrition, we hypothesize that serum CHE levels may be associated with the progression and prognosis of HIV-related DLBCL. In the present study, a retrospective cohort study was conducted with 65 HIV-related DLBCL patients, with the aim of investigating whether the baseline serum CHE level could serve as a predictor for the outcomes of these patients. MATERIALS AND METHODS Study design and patient selection Between January 2015 and December 2022, a total of 65 chemotherapy-naive HIV-related DLBCL patients at the First Affiliated Hospital, School of Medicine of Zhejiang University, were included in this study. DLBCL was diagnosed based on pathological biopsy in accordance with the 2016 revision of the World Health Organization's classification of lymphoid neoplasms [ 16 ] . The inclusion criteria included the following: 1) new-onset HIV-related DLBCL patients; 2) patients who were over 18 years old; and 3) patients who were about to receive medical care. Additionally, participants were required to be able to provide blood samples for serum CHE level assessment at the time of their DLBCL diagnosis. Conversely, patients were excluded if they had other concurrent active malignancies or if they refused to participate in this study. Chemotherapy and efficacy evaluation Of 65 HIV-related DLBCL patients, 57 (87.7%) individuals opted to undergo chemotherapy, while 8 patients declined chemotherapy. Among those who received chemotherapy, 40 patients were treated with the CHOP ± R regimen, 12 patients received the EOPCH ± R regimen, 2 patients received the R2 regimen, 1 patient received the high-dose MTX regimen, 1 patient received the VICP regimen, and 1 patient received the hyper-CVAD + R regimen [ 17 , 18 ] . Additionally, 36 (63.2%) patients received rituximab, and 21 (36.8%) patients did not. The dosage and protocol of each chemotherapy are listed in Supplementary Table S1 . The assessment of chemotherapeutic response was categorized as complete response (CR), partial response (PR), overall response rate (ORR, encompassing CR and PR), stable disease (SD), or progressive disease (PD), adhering to the Lugano Classification [ 19 ] . Laboratory tests and medical information Routine blood tests, biochemical function tests (including CHE) and C-reactive protein were analyzed by an autobiochemical analyzer (Beckman Coulter, CA, USA) at the time of DLBCL diagnosis. Baseline CHE refers to the serum CHE levels recorded at the time of DLBCL diagnosis. The CD4 count was measured using a flow cytometer (Becton Dickinson, NJ, USA) with fluorescein isothiocyanate-conjugated anti-human CD4 (Becton Dickinson). Patients’ demographic data, including age, sex, body mass index (BMI), underlying conditions, International Prognostic Index (IPI) scores, and chemotherapy regimens, were recorded in the hospital's electronic medical records system (EMRS). The patients were followed up for one year after 6–8 cycles of chemotherapy. Statistical analysis Continuous variables with a normal distribution are presented herein as the mean ± standard deviation, while continuous variables with a nonnormal distribution are presented as the median (interquartile range [IQR]). Categorical variables are presented as counts and percentages. The normal distribution of continuous variables was evaluated using the Shapiro‒Wilk test. Student's t test or the Mann‒Whitney U test was applied to compare two sets of continuous variables. Chi-square or Fisher’s exact tests were used to compare two sets of categorical variables. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal CHE threshold value (5500 U/L). Patients were categorized into the high CHE group (> 5500 U/L) and the low CHE group (≤ 5500 U/L). Canonical correlation analysis was employed to explore the relationship between baseline serum CHE levels and sets of inflammatory and nutritional markers. Univariate and multivariate Cox proportional hazards models were utilized to assess the crude and adjusted associations between CHE levels and overall survival (OS). Univariate and multivariate logistic regression analyses were performed to evaluate the crude and adjusted associations between CHE levels and the overall response rate (ORR). Subsequently, models were adjusted for sex, age, BMI, CNS metastases, GCB subtype, Ann Arbor stage, IPI, Ki-67, CD4 cell counts, chemotherapy, and rituximab usage. Factors with significance (P < 0.300) in univariate analysis were further analyzed in the multivariate Cox proportional hazards model or logistic regression by the forward stepwise (likelihood ratio) method. A sensitivity analysis was conducted to ensure the robustness of the findings by adjusting the CHE cutoff point to less than 4500 U/L and treating CHE as a continuous variable. Patients were categorized into four groups using quartiles of baseline serum CHE levels (Group 1: 1394–4362 U/L, Group 2: 4483–5663 U/L, Group 3: 5981–7227 U/L, Group 4: 7378–12124 U/L) to observe the differences in OS and ORR under different serum CHE gradients. A significance level of P < 0.05 was considered statistically significant. All statistical analyses were conducted using SPSS software version 26.0 (SPSS Institute, Chicago, USA) and GraphPad Prism version 9.0 (GraphPad Software, California, USA). RESULTS Patient characteristics and demographic information Of 65 patients with HIV-related DLBCL, there were 56 (86.2%) male and 9 (13.8%) female patients with an overall mean age of 48.7 ± 14.6 years. Among them, 27 patients were categorized into the low CHE group, while 38 patients were categorized into the high CHE group. Notably, the patients in the low CHE group had a higher average age (54.4 ± 13.1 years) than the high CHE group (average age of 44.7 ± 14.4 years, P = 0.007). The patients with low CHE exhibited lower levels of hemoglobin [g/L: 101.0 (81.0-115.0) vs. 123.5 (108.2–141.0), P < 0.001] and serum albumin (alb) [g/L: 31.2 ± 5.6 vs. 40.4 ± 4.5, P < 0.001] and higher levels of lactate dehydrogenase (LDH) [U/L: 404.0 (253.0-849.0) vs. 248.0 (178.3–372.0), P = 0.014] and C-reactive protein (CRP) [mg/L: 36.1 (5.8–66.6) vs. 5.1 (0.8–5.1), P < 0.001]. No significant disparities were observed between the two groups in terms of body mass index (BMI), sex distribution, white blood cell count (WBC), neutrophil count, lymphocyte count, platelet count (PLT), alanine transaminase (ALT), aspartate transaminase (AST), creatinine (Cr), or blood urea nitrogen (BUN). Furthermore, HIV-related DLBCL patients with low CHE levels exhibited a higher incidence of advanced Ann Arbor stage III/IV disease (92.6% vs. 56.8%, P < 0.001) and a high International Prognostic Index (IPI) ≥ 3 (85.2% vs. 35.1%, P = 0.002) at the time of lymphoma diagnosis. Notably, patients with low CHE experienced higher digestive system involvement (77.8%) than those with high CHE (39.5%) (P = 0.002). Both groups demonstrated similar distributions of the germinal center-derived B-cell (GCB) subtype and high Ki-67 values (Ki-67 ≥ 80%) (all P > 0.05) (Table 1 ). Table 1 General characteristics Characteristics All patient (N = 65) The low group (CHE ≤ 5500U/L, N = 27) The high group (CHE>5500U/L, N = 38) p-value Age 48.7 ± 14.6 54.4 ± 13.1 44.7 ± 14.4 0.007 Male (%) 56/65 (86.2%) 22/27 (81.5%) 34/38 (89.5%) 0.579 BMI (kg/m 2 ) 21.4 ± 2.8 21.6 ± 2.6 21.3 ± 3.0 0.684 Routine blood test WBC (×10 9 /L) 4.7 (3.5–6.3) 4.8 (3.6–7.7) 4.6 (3.4–6.3) 0.483 Neutrophil (×10 9 /L) 2.9 (1.9–4.1) 3.2 (2.3–4.2) 2.6 (1.6–4.1) 0.262 Lymphocyte (×10 9 /L) 0.9 (0.5–1.5) 0.8 (0.3–1.5) 1.0 (0.6–1.6) 0.385 Hemoglobin (g/L) 111.0 (102.0-133.0) 101.0 (81.0-115.0) 123.5 (108.2–141.0) < 0.001 PLT (×10 9 /L) 201.1 ± 110.7 202.9 ± 138.0 199.9 ± 89.4 0.915 Liver function Albumin (g/L) 36.6 ± 6.7 31.2 ± 5.6 40.4 ± 4.5 < 0.001 ALT (U/L) 18.0 (12.5–26.0) 20.0 (12.0–28.0) 17.5 (13.5–24.3) 0.540 AST (U/L) 24.0 (19.0–39.0) 32.0 (19.0–57.0) 22.5 (19.0–28.0) 0.071 CHE (U/L) 5938.7 ± 2140.9 3930.8 ± 1142.6 7365.3 ± 1406.6 < 0.001 Renal function Creatinine (µmol/L) 69.0 (55.5–80.5) 69.0 (52.0–92.0) 68.5 (55.8–76.3) 0.680 BUN (mmol/L) 4.5 (3.4–5.7) 5.0 (3.8–8.5) 4.5 (3.3–5.5) 0.120 CRP (mg/L) 7.8 (23.8–37.5) 36.1 (5.8–66.6) 5.1 (0.8–5.1) < 0.001 Tumor related indicators LDH (U/L) 293.0 (200.0-572.5) 404.0 (253.0-849.0) 248.0 (178.3–372.0) 0.014 GCB (%) 24/47 (51.1%) 8/18 (44.4%) 16/29 (55.2%) 0.474 Ki-67 ≥ 80% 30/47 (63.8) 10/16 (62.5%) 20/31 (64.5%) 0.892 Ann Arbor stage < 0.001 I/II 18/64 (28.1%) 2/27 (7.4%) 16/37 (43.2%) III/IV 46/64 (71.9%) 25/27 (92.6%) 21/37 (56.8%) IPI 0.002 ≤ 2 28/64 (43.8%) 4/27 (14.8%) 24/37 (64.9%) ≥ 3 36/64 (56.3%) 23/27 (85.2%) 13/37 (35.1%) Site of tumor invasion (%) Brains 9/65 (13.8%) 3/27 (11.1%) 6/38 (15.8%) 0.438 Digestive system 36/65 (55.4%) 21/27 (77.8%) 15/38 (39.5%) 0.002 Lung 12/65 (18.5%) 7/27 (25.9%) 5/38 (13.2%) 0.191 Marrow 17/65 (26.2%) 9/27(33.3%) 8/38 (21.1%) 0.267 Note: Abbreviations: CHE, cholinesterase; BMI, body mass index; WBC, white blood cell; PLT, platelet; ALT, alanine transaminase; AST, aspartate transaminase; BUN, blood urea nitrogen; CRP, C-reactive protein; LDH, lactic dehydrogenase; GCB, germinal center B-cell-like; IPI, International Prognostic Index. Canonical correlation analysis Canonical correlation analysis was used to assess the relationship between baseline serum CHE levels and two distinct marker sets: the inflammatory marker set (consisting of WBC, neutrophil count, lymphocyte count and CRP) and the nutritional marker set (including BMI, total serum protein, albumin, and hemoglobin). CHE exhibited a robust correlation with the nutritional marker set (canonical correlation coefficient = 0.769, P < 0.001). Of note, serum albumin accounts for a significant proportion of the nutritional marker set (intergroup structural coefficient = 0.743). CHE also displayed a moderate association with the inflammatory marker set (canonical correlation coefficient = 0.569, P < 0.001). In the inflammatory marker set, the CRP level, neutrophil count and lymphocyte count exhibited a negative correlation with CHE, while the WBC count displayed a positive correlation.( Fig. 1 ) Baseline serum CHE was associated with ORR and 1-year OS in HIV-related DLBCL patients The 1-year OS was compared between patients with high serum CHE and low serum CHE. Of 65 HIV-related DLBCL patients, 22 (33.8%) individuals died during the follow-up period. Our data suggest that the 1-year OS of patients was 84.2% in the high CHE group and 40.7% in the low CHE group (log-rank P < 0.001). For those patients received chemotherapy, the 1-year OS of the high CHE group was still significantly superior to the low CHE group (85.7% vs. 50.0%, log-rank P = 0.004)(Fig. 2 ). In multivariate analysis, models were adjusted for BMI, chemotherapy, CNS metastases, GCB subtype, Ann Arbor stage, IPI and Ki-67. After adjustment, CHE > 5500 U/L [HR: 0.11 (0.03–0.57), P = 0.005] remained an independent prognostic factor for 1-year mortality. In the sensitivity analysis setting CHE as a continuous variable, CHE maintained its robust association with OS/mortality (Table 2 ) ( Supplementary Table 2 ). Table 2 Various CHE estimates and mortality/ORR CHE 1-year mortality ORR HR (95% Cl) p-value OR (95% Cl) p-value > 4500U/L Unadjusted 0.29 (0.13 to 0.69) 0.005 12.80 (3.00 to 54.61) 0.001 Adjusted 0.24 (0.11 to 4.56) 0.207 11.00 (1.75 to 69.08) 0.011 > 5500U/L Unadjusted 0.21 (0.08 to 0.54) 0.001 8.57 (2.53 to 29.06) 0.001 Adjusted 0.11 (0.03 to 0.57) 0.004 4.74 (1.02 to 22.06) 0.047 In(CHE)* Unadjusted 0.24 (0.11 to 0.51) < 0.001 29.18 (3.64 to 234.04) 0.001 Adjusted 0.11 (0.02 to 0.53) 0.005 32.20 (2.09 to 496.15) 0.013 * The continuous Cholinesterase (CHE) variable was transformed into natural logarithm variable. At the end of chemotherapy, the ORR was 80.0% in the high CHE group and 31.8% in the low CHE group (P 5500 U/L and ORR was observed in the univariate logistic regression model [OR: 8.57 (2.53–29.06), P = 0.001]. In the multivariate Cox proportional hazards model, a high CHE level (CHE > 5500 U/L) [AOR: 4.74 (1.02–22.06), P = 0.047] remained an independent prognostic factor for chemotherapeutic effectiveness after adjusting for sex, rituximab usage, CNS metastases, Ann Arbor stage, IPI and Ki-67. Similar results were observed in the sensitivity analysis, adjusting the CHE cutoff point to less than 4500 U/L or setting CHE as a continuous variable (Table 2 ) ( Supplementary Table 2 ). The patients were subsequently divided into four groups based on the quartiles of baseline serum CHE (Group 1: 1394–4362 U/L, Group 2: 4483–5663 U/L, Group 3: 5981–7227 U/L, Group 4: 7378–12124 U/L). We found that the 1-year OS rates from Group 1 to Group 4 were 31.25%, 68.75%, 81.25%, and 82.35%, respectively. The ORRs from Group 1 to Group 4 were 4.29%, 69.23%, 73.33%, and 86.67%, respectively. These data clearly showed a trend in which higher CHE was positively associated with a high ORR and 1-year OS (Fig. 3 ). DISCUSSION In this retrospective study, we aimed to shed light on the potential prognostic significance of serum CHE levels within the context of HIV-related DLBCL. Our investigation revealed the following results: (a) HIV-related DLBCL patients with low serum CHE levels exhibited a higher incidence of anemia, hypoproteinemia and inflammatory indicators. (b) HIV-related DLBCL patients with low CHE levels were more frequently classified as having advanced IPI scores and Ann Arbor stage. (c) High baseline CHE levels were closely correlated with improved ORR and OS. Thus, baseline CHE levels hold promise as a valuable prognostic marker for HIV-related DLBCL patients. "Clinical serum cholinesterase" typically refers to pseudocholinesterase, which is predominantly synthesized in hepatocytes [ 20 ] . Therefore, low levels of serum pseudocholinesterase are often used as an indicator of impaired hepatic synthetic capacity. Patients with malignancy often receive high-dose chemotherapy, experience weight loss and exhibit malnutrition, which can affect liver synthetic function, including CHE production. Serum CHE has been reported to be a prognostic factor in several solid cancers [ 8 , 12 ] . We identified that CHE can serve as a reliable surrogate marker for predicting OS and ORR in HIV-related DLBCL patients. Specifically, patients with CHE ≤ 5500 U/L exhibited significantly poorer OS and ORR, even after adjustment for potential confounding factors. The associations between CHE and patient outcomes can be attributed to several reasons: First, it is worth noting that nutrition has a profound impact on the outcomes of patients with HIV-related DLBCL. A high incidence of anemia and hypoalbuminemia among HIV-related DLBCL patients with low CHE levels was observed in our research. Serum albumin has been widely used as a diagnostic marker for malnutrition in clinical practice. Low serum albumin is associated with inferior outcomes in patients with DLBCL [ 21 , 22 ] . The anemia probably results from DLBCL involvement of bone marrow and dietary causes [ 23 , 24 ] . There is a life-saving requirement for higher nutritional intake for patients with anemia and hypoproteinemia. Of note, canonical correlation analysis confirmed that CHE had a robust correlation with nutrition-related indicators (total protein, albumin, hemoglobin and BMI) in our study. Importantly, a combined assessment of serum cholinesterase and albumin levels can serve as nutrition-related serum markers and be successfully employed to predict prognosis in cancer patients [ 11 , 25 ] . In addition, cancer patients with poorer nutritional status are less likely to complete oncologic treatment according to plan and are at a high risk of developing adverse outcomes. Second, persistent inflammation has been shown to have a detrimental effect on the outcomes of DLBCL patients. Elevated levels of CRP were observed in HIV-related DLBCL patients with lower CHE levels in our study. Inflammation plays a crucial role in various stages of tumor development, including initiation, growth, invasion, and metastasis. The presence of persistent inflammation creates an environment that facilitates tumor progression and contributes to the development of certain types of cancer [ 26 ] . Elevated CRP levels are frequently detected in individuals with cancer, particularly those with advanced or metastatic disease, which are related to poor prognosis [ 26 , 27 ] . This is because tumors can trigger the release of inflammatory cytokines, which in turn stimulate the liver to produce more CRP [ 28 ] . In our research, we found a strong correlation between CRP and CHE, providing an explanation for why CHE levels can serve as a promising prognostic marker for DLBCL. Additionally, cell-based inflammation consisting of neutrophils and lymphocytes is also significantly associated with the progression of cancer and metastasis of malignant cells [ 29 , 30 ] . In our study, the differences in neutrophils and lymphocytes between different ChE groups were not pronounced, possibly due to the impact of HIV itself on the destruction of lymphocytes and neutrophils. Third, our study provided evidence of a significant association between low CHE levels and advanced stages of HIV-related DLBCL. Specifically, 92.6% of patients with CHE levels ≤ 5500 U/L were classified as Ann Arbor stage III/IV, and 85.2% of patients with CHE levels ≤ 5500 U/L had an IPI score > 3. These findings indicate that CHE is an indicator of DLBCL disease progression. The advanced stage of DLBCL deteriorates the prognosis of patients. Compared to other factors for cancer prognosis, CHE has the advantage of being cost-effective and easy to implement, with less interference in clinical settings. In light of our research findings, we strongly recommend that serum CHE levels be used as a valuable prognostic marker for HIV-related DLBCL patients. There are some limitations in our study. First, the sample size was relatively small, and consequently, a large cohort study is needed to further confirm our conclusions. Second, our study was a retrospective study conducted in a single medical center. A prospective study is needed to further elucidate our results. Third, the follow-up period was only one year, which may not have captured the long-term outcomes of patients. In conclusion, our study findings provide strong evidence of a close relationship between serum CHE levels and nutrient status as well as inflammation in HIV-related DLBCL patients. Notably, patients with low serum CHE levels were found to be predominantly in advanced stages of the disease and exhibited poor ORR and 1-year OS. Based on our robust data, serum CHE levels show great potential as a surrogate marker for risk stratification and for guiding treatment decisions in patients with HIV-related DLBCL. Declarations Ethical approval and consent to participate The research protocols were in accordance with the 1975 Declaration of Helsinki and received ethical approval from the Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University (Hangzhou, China) (No. 2021-139). All data were analyzed anonymously. The Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University waived the requirement for written informed consent from the participants. Consent to publish Our study did not contain any identifying information of the participants. Therefore, it is not applicable for our research. Acknowledgements We would like to extend our sincere appreciation to the Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University (Hangzhou, China), for their support and cooperation, including the waiver of informed consent. Their dedication to ethical standards greatly contributed to the success of this retrospective study. Author contributions Lijun Xu designed the study and drafted the manuscript. Jiaying Qin, Yong Tong, Shasha Ye and Lingyun Wang collected the data and performed the study. Minghan Zhou, Jiaying Qin and Yong Tong rechecked the data. Minghan Zhou analyzed and interpreted the data. 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Serum Albumin Levels Strongly Predict Survival Outcome of Elderly Patients with Diffuse Large B-Cell Lymphoma Treated with Rituximab-Combined Chemotherapy . Int J Hematol Oncol Stem Cell Res 2022; 16(1):1-8. Kumar SB, Arnipalli SR, Mehta P, Carrau S, Ziouzenkova O. Iron Deficiency Anemia: Efficacy and Limitations of Nutritional and Comprehensive Mitigation Strategies . Nutrients 2022; 14(14). Yasmeen T, Ali J, Khan K, Siddiqui N. Frequency and causes of anemia in Lymphoma patients . Pak J Med Sci 2019; 35(1):61-65. Takano Y, Haruki K, Kai W, Tsukihara S, Kobayashi Y, Ito D, et al. The influence of serum cholinesterase levels and sarcopenia on postoperative infectious complications in colorectal cancer surgery . Surg Today 2023; 53(7):816-823. Allin KH, Nordestgaard BG. Elevated C-reactive protein in the diagnosis, prognosis, and cause of cancer . Crit Rev Clin Lab Sci 2011; 48(4):155-170. Koukourakis MI, Kambouromiti G, Pitsiava D, Tsousou P, Tsiarkatsi M, Kartalis G. Serum C-reactive protein (CRP) levels in cancer patients are linked with tumor burden and are reduced by anti-hypertensive medication . Inflammation 2009; 32(3):169-175. Hart PC, Rajab IM, Alebraheem M, Potempa LA. C-Reactive Protein and Cancer-Diagnostic and Therapeutic Insights . Front Immunol 2020; 11:595835. Lee SM, Russell A, Hellawell G. Predictive value of pretreatment inflammation-based prognostic scores (neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio) for invasive bladder carcinoma . Korean J Urol 2015; 56(11):749-755. Kitayama J, Yasuda K, Kawai K, Sunami E, Nagawa H. Circulating lymphocyte number has a positive association with tumor response in neoadjuvant chemoradiotherapy for advanced rectal cancer . Radiat Oncol 2010; 5:47. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3880969","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273125354,"identity":"76800b30-8697-4de3-b1ac-59acd3fed4dd","order_by":0,"name":"Minghan Zhou","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Minghan","middleName":"","lastName":"Zhou","suffix":""},{"id":273125355,"identity":"498ac893-6e7e-4d06-b6e8-13483d8e90ec","order_by":1,"name":"Jiaying Qin","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Jiaying","middleName":"","lastName":"Qin","suffix":""},{"id":273125356,"identity":"a2cc761a-7d7d-45ab-9924-1cc61cd52c3f","order_by":2,"name":"Yong Tong","email":"","orcid":"","institution":"Huzhou central hospital of Zhejiang Univestiy","correspondingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Tong","suffix":""},{"id":273125357,"identity":"c4c5062f-a0bf-409c-9c11-602189c824fb","order_by":3,"name":"Lingyun Wang","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Lingyun","middleName":"","lastName":"Wang","suffix":""},{"id":273125358,"identity":"aba8893b-3c77-4cc3-a847-798121df6c2e","order_by":4,"name":"Shasha Ye","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Shasha","middleName":"","lastName":"Ye","suffix":""},{"id":273125359,"identity":"3cd2b545-6077-4312-9a2f-67aa11f2a1e4","order_by":5,"name":"Lijun Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIie3RMWvCQBTA8RcCcXl4Hd+BtJvzmwRpwa+iBHTJ4FRwS5d0SXa/hlvHCwe6BOcMDpaCk0OLi9lMFN2S6yh4/+E4Hvfj4A7AZrvL3FARAIqXn3QLWE2GJuKcSUeGY5//Tar1jVXQpcvEQDgffah+tEFWmTc7djSIVsBQfNUTOR+FSkY7lGmyzAk1yHjPTpLVE0FnorGt2+OcS8J5wK4T1RPvSmCJvemwJAMTud3ylGEPVHULGYiMv8tHXmuUc8+XIU6Qst00TRoIr3x9oHc9EOSmf0X8+iw+/cW2aCBVLl13Tnz5TNUMyoO/t+3RdNZms9kesRP5IVK97wOTmgAAAABJRU5ErkJggg==","orcid":"","institution":"First Affiliated Hospital Zhejiang University","correspondingAuthor":true,"prefix":"","firstName":"Lijun","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-01-20 07:44:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3880969/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3880969/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51331451,"identity":"f5119bcb-de3a-4f04-804b-f8f851cc8380","added_by":"auto","created_at":"2024-02-19 17:53:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56699,"visible":true,"origin":"","legend":"\u003cp\u003eCHE exhibited a good correlation with the nutritional markers set and the inflammatory markers set. CHE exhibited a robust correlation with the nutritional markers set (canonical correlation coefficient = 0.769, P \u0026lt; 0.001) and a moderate association with the inflammatory markers set (canonical correlation coefficient = 0.569, P \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3880969/v1/24fcd36fdc8fbe300f9be00a.png"},{"id":51331453,"identity":"49448e57-9ec0-4e1e-b1f0-a299412c5039","added_by":"auto","created_at":"2024-02-19 17:53:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55454,"visible":true,"origin":"","legend":"\u003cp\u003eSerum CHE and 1-year OS. \u003cstrong\u003eA.\u003c/strong\u003e The one-year OS was 84.2% in the high CHE group and 40.7% in the low CHE group in all patients (log-rank P \u0026lt; 0.001). \u003cstrong\u003eB.\u003c/strong\u003e The 1-year OS was 85.7% in the high CHE group and 50.0% in the low CHE group in those received chemotherapy (log-rank P = 0.004).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3880969/v1/ac514a0cdb1ff541036fbee6.png"},{"id":51331452,"identity":"5f90d810-7bc4-4468-a01e-0e881fad99d8","added_by":"auto","created_at":"2024-02-19 17:53:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":80302,"visible":true,"origin":"","legend":"\u003cp\u003eSerum CHE and OS/ORR. \u003cstrong\u003eA. \u003c/strong\u003eThe 1-year OS from Group 1 to Group 4 were 31.25%, 68.75%, 81.25%, 82.35%, respectively.\u003cstrong\u003e B. \u003c/strong\u003eThe ORR from Group 1 to Group 4 were 4.29%, 69.23%, 73.33%, 86.67%, respectively.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3880969/v1/192b5e45f496b24eda10f604.png"},{"id":52422665,"identity":"a546a489-a562-4434-9af5-3151b2af30e9","added_by":"auto","created_at":"2024-03-11 13:00:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1299258,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3880969/v1/51de5ee0-8e88-45b7-bddd-911ee52c80c0.pdf"},{"id":51331454,"identity":"bbaf7546-2722-4ce5-b84b-98721b307303","added_by":"auto","created_at":"2024-02-19 17:53:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18244,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3880969/v1/59bb21cbab393e53623712e8.docx"},{"id":51331455,"identity":"bb2438b2-1a48-4fa3-a159-03404e6c13de","added_by":"auto","created_at":"2024-02-19 17:53:25","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":32807,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementTbale2.docx","url":"https://assets-eu.researchsquare.com/files/rs-3880969/v1/d49aafa6cb6584393f7b70e3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Baseline Serum Cholinesterase Levels Predict the Outcome of HIV-Related Diffuse Large B-Cell Lymphoma","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHuman immunodeficiency virus (HIV) infection increases the risk of diffuse large B-cell lymphoma (DLBCL), which accounts for 35\u0026ndash;60% of all reported non-Hodgkin lymphoma (NHL) cases\u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. HIV-related DLBCL is characterized by an advanced stage at diagnosis, a higher incidence of extranodal involvement, and an increased frequency of B symptoms compared to the corresponding characteristics in the general population \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The implementation of combined antiretroviral therapy (cART) and conventional intensive chemotherapy regimens has resulted in improved survival rates for HIV-related DLBCL. Nevertheless, the prognosis for HIV-related DLBCL patients remains poor in resource-limited areas due to challenges in medical conditions, economic costs and misconceptions about the disease \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In sub-Saharan Africa, for example, the 2-year survival rate of patients with HIV-related DLBCL is only 38\u0026ndash;55%\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In clinical practice, it is crucial to identify HIV-related DLBCL patients who are at a high risk of mortality. Consequently, there is an urgent need to find a simple and readily available laboratory indicator that can predict the outcomes of these patients.\u003c/p\u003e \u003cp\u003eSerum cholinesterase (CHE), as a reliable indicator of liver synthetic function, is closely linked to conditions such as hepatic impairment, malnutrition, heart failure, and progressive systemic inflammation \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Recent studies have shown that low serum CHE levels are associated with poor prognosis and decreased chemotherapy effectiveness in various solid cancers, such as gastric cancer\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, prostate cancer\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, pancreatic cancer\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, colorectal cancer\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e, and non-small cell lung cancer\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e, regardless of hepatic involvement.\u003c/p\u003e \u003cp\u003eResearch on the correlation between serum CHE levels and hematologic malignancies is currently limited. Previous studies have shown that persistent inflammation and malnutrition are both associated with unfavorable outcomes in patients with HIV-related DLBCL\u003csup\u003e[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Given that CHE is an important indicator of chronic inflammation and malnutrition, we hypothesize that serum CHE levels may be associated with the progression and prognosis of HIV-related DLBCL.\u003c/p\u003e \u003cp\u003eIn the present study, a retrospective cohort study was conducted with 65 HIV-related DLBCL patients, with the aim of investigating whether the baseline serum CHE level could serve as a predictor for the outcomes of these patients.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and patient selection\u003c/h2\u003e \u003cp\u003eBetween January 2015 and December 2022, a total of 65 chemotherapy-naive HIV-related DLBCL patients at the First Affiliated Hospital, School of Medicine of Zhejiang University, were included in this study. DLBCL was diagnosed based on pathological biopsy in accordance with the 2016 revision of the World Health Organization's classification of lymphoid neoplasms\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. The inclusion criteria included the following: 1) new-onset HIV-related DLBCL patients; 2) patients who were over 18 years old; and 3) patients who were about to receive medical care. Additionally, participants were required to be able to provide blood samples for serum CHE level assessment at the time of their DLBCL diagnosis. Conversely, patients were excluded if they had other concurrent active malignancies or if they refused to participate in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eChemotherapy and efficacy evaluation\u003c/h2\u003e \u003cp\u003eOf 65 HIV-related DLBCL patients, 57 (87.7%) individuals opted to undergo chemotherapy, while 8 patients declined chemotherapy. Among those who received chemotherapy, 40 patients were treated with the CHOP\u0026thinsp;\u0026plusmn;\u0026thinsp;R regimen, 12 patients received the EOPCH\u0026thinsp;\u0026plusmn;\u0026thinsp;R regimen, 2 patients received the R2 regimen, 1 patient received the high-dose MTX regimen, 1 patient received the VICP regimen, and 1 patient received the hyper-CVAD\u0026thinsp;+\u0026thinsp;R regimen \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Additionally, 36 (63.2%) patients received rituximab, and 21 (36.8%) patients did not. The dosage and protocol of each chemotherapy are listed in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe assessment of chemotherapeutic response was categorized as complete response (CR), partial response (PR), overall response rate (ORR, encompassing CR and PR), stable disease (SD), or progressive disease (PD), adhering to the Lugano Classification\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory tests and medical information\u003c/h2\u003e \u003cp\u003eRoutine blood tests, biochemical function tests (including CHE) and C-reactive protein were analyzed by an autobiochemical analyzer (Beckman Coulter, CA, USA) at the time of DLBCL diagnosis. Baseline CHE refers to the serum CHE levels recorded at the time of DLBCL diagnosis. The CD4 count was measured using a flow cytometer (Becton Dickinson, NJ, USA) with fluorescein isothiocyanate-conjugated anti-human CD4 (Becton Dickinson). Patients\u0026rsquo; demographic data, including age, sex, body mass index (BMI), underlying conditions, International Prognostic Index (IPI) scores, and chemotherapy regimens, were recorded in the hospital's electronic medical records system (EMRS). The patients were followed up for one year after 6\u0026ndash;8 cycles of chemotherapy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables with a normal distribution are presented herein as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while continuous variables with a nonnormal distribution are presented as the median (interquartile range [IQR]). Categorical variables are presented as counts and percentages. The normal distribution of continuous variables was evaluated using the Shapiro‒Wilk test. Student's \u003cem\u003et\u003c/em\u003e test or the Mann‒Whitney U test was applied to compare two sets of continuous variables. Chi-square or Fisher\u0026rsquo;s exact tests were used to compare two sets of categorical variables. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal CHE threshold value (5500 U/L). Patients were categorized into the high CHE group (\u0026gt;\u0026thinsp;5500 U/L) and the low CHE group (\u0026le;\u0026thinsp;5500 U/L). Canonical correlation analysis was employed to explore the relationship between baseline serum CHE levels and sets of inflammatory and nutritional markers. Univariate and multivariate Cox proportional hazards models were utilized to assess the crude and adjusted associations between CHE levels and overall survival (OS). Univariate and multivariate logistic regression analyses were performed to evaluate the crude and adjusted associations between CHE levels and the overall response rate (ORR). Subsequently, models were adjusted for sex, age, BMI, CNS metastases, GCB subtype, Ann Arbor stage, IPI, Ki-67, CD4 cell counts, chemotherapy, and rituximab usage. Factors with significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.300) in univariate analysis were further analyzed in the multivariate Cox proportional hazards model or logistic regression by the forward stepwise (likelihood ratio) method. A sensitivity analysis was conducted to ensure the robustness of the findings by adjusting the CHE cutoff point to less than 4500 U/L and treating CHE as a continuous variable. Patients were categorized into four groups using quartiles of baseline serum CHE levels (Group 1: 1394\u0026ndash;4362 U/L, Group 2: 4483\u0026ndash;5663 U/L, Group 3: 5981\u0026ndash;7227 U/L, Group 4: 7378\u0026ndash;12124 U/L) to observe the differences in OS and ORR under different serum CHE gradients. A significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were conducted using SPSS software version 26.0 (SPSS Institute, Chicago, USA) and GraphPad Prism version 9.0 (GraphPad Software, California, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics and demographic information\u003c/h2\u003e \u003cp\u003eOf 65 patients with HIV-related DLBCL, there were 56 (86.2%) male and 9 (13.8%) female patients with an overall mean age of 48.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6 years. Among them, 27 patients were categorized into the low CHE group, while 38 patients were categorized into the high CHE group. Notably, the patients in the low CHE group had a higher average age (54.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1 years) than the high CHE group (average age of 44.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4 years, P\u0026thinsp;=\u0026thinsp;0.007). The patients with low CHE exhibited lower levels of hemoglobin [g/L: 101.0 (81.0-115.0) vs. 123.5 (108.2\u0026ndash;141.0), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001] and serum albumin (alb) [g/L: 31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6 vs. 40.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001] and higher levels of lactate dehydrogenase (LDH) [U/L: 404.0 (253.0-849.0) vs. 248.0 (178.3\u0026ndash;372.0), P\u0026thinsp;=\u0026thinsp;0.014] and C-reactive protein (CRP) [mg/L: 36.1 (5.8\u0026ndash;66.6) vs. 5.1 (0.8\u0026ndash;5.1), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001]. No significant disparities were observed between the two groups in terms of body mass index (BMI), sex distribution, white blood cell count (WBC), neutrophil count, lymphocyte count, platelet count (PLT), alanine transaminase (ALT), aspartate transaminase (AST), creatinine (Cr), or blood urea nitrogen (BUN).\u003c/p\u003e \u003cp\u003eFurthermore, HIV-related DLBCL patients with low CHE levels exhibited a higher incidence of advanced Ann Arbor stage III/IV disease (92.6% vs. 56.8%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a high International Prognostic Index (IPI)\u0026thinsp;\u0026ge;\u0026thinsp;3 (85.2% vs. 35.1%, P\u0026thinsp;=\u0026thinsp;0.002) at the time of lymphoma diagnosis. Notably, patients with low CHE experienced higher digestive system involvement (77.8%) than those with high CHE (39.5%) (P\u0026thinsp;=\u0026thinsp;0.002). Both groups demonstrated similar distributions of the germinal center-derived B-cell (GCB) subtype and high Ki-67 values (Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;80%) (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patient (N\u0026thinsp;=\u0026thinsp;65)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe low group (CHE\u0026thinsp;\u0026le;\u0026thinsp;5500U/L, N\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe high group (CHE\u0026gt;5500U/L, N\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56/65 (86.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22/27 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34/38 (89.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRoutine blood test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.7 (3.5\u0026ndash;6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.8 (3.6\u0026ndash;7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6 (3.4\u0026ndash;6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.483\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9 (1.9\u0026ndash;4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2 (2.3\u0026ndash;4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.6 (1.6\u0026ndash;4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.5\u0026ndash;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.3\u0026ndash;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.6\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111.0 (102.0-133.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.0 (81.0-115.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123.5 (108.2\u0026ndash;141.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201.1\u0026thinsp;\u0026plusmn;\u0026thinsp;110.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202.9\u0026thinsp;\u0026plusmn;\u0026thinsp;138.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e199.9\u0026thinsp;\u0026plusmn;\u0026thinsp;89.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiver function\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.0 (12.5\u0026ndash;26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0 (12.0\u0026ndash;28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.5 (13.5\u0026ndash;24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.540\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.0 (19.0\u0026ndash;39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.0 (19.0\u0026ndash;57.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.5 (19.0\u0026ndash;28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCHE (U/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5938.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2140.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3930.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1142.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7365.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1406.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRenal function\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.0 (55.5\u0026ndash;80.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.0 (52.0\u0026ndash;92.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.5 (55.8\u0026ndash;76.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5 (3.4\u0026ndash;5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0 (3.8\u0026ndash;8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5 (3.3\u0026ndash;5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCRP (mg/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.8 (23.8\u0026ndash;37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.1 (5.8\u0026ndash;66.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1 (0.8\u0026ndash;5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor related indicators\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e293.0 (200.0-572.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e404.0 (253.0-849.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248.0 (178.3\u0026ndash;372.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCB (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24/47 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/18 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16/29 (55.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi-67\u0026thinsp;\u0026ge;\u0026thinsp;80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30/47 (63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10/16 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20/31 (64.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnn Arbor stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI/II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18/64 (28.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2/27 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16/37 (43.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII/IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46/64 (71.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25/27 (92.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21/37 (56.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIPI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28/64 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4/27 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24/37 (64.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36/64 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23/27 (85.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13/37 (35.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSite of tumor invasion (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9/65 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3/27 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6/38 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigestive system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36/65 (55.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21/27 (77.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15/38 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12/65 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7/27 (25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5/38 (13.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarrow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17/65 (26.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/27(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8/38 (21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Abbreviations: CHE, cholinesterase; BMI, body mass index; WBC, white blood cell; PLT, platelet; ALT, alanine transaminase; AST, aspartate transaminase; BUN, blood urea nitrogen; CRP, C-reactive protein; LDH, lactic dehydrogenase; GCB, germinal center B-cell-like; IPI, International Prognostic Index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCanonical correlation analysis\u003c/h2\u003e \u003cp\u003eCanonical correlation analysis was used to assess the relationship between baseline serum CHE levels and two distinct marker sets: the inflammatory marker set (consisting of WBC, neutrophil count, lymphocyte count and CRP) and the nutritional marker set (including BMI, total serum protein, albumin, and hemoglobin). CHE exhibited a robust correlation with the nutritional marker set (canonical correlation coefficient\u0026thinsp;=\u0026thinsp;0.769, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Of note, serum albumin accounts for a significant proportion of the nutritional marker set (intergroup structural coefficient\u0026thinsp;=\u0026thinsp;0.743). CHE also displayed a moderate association with the inflammatory marker set (canonical correlation coefficient\u0026thinsp;=\u0026thinsp;0.569, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the inflammatory marker set, the CRP level, neutrophil count and lymphocyte count exhibited a negative correlation with CHE, while the WBC count displayed a positive correlation.( Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBaseline serum CHE was associated with ORR and 1-year OS in HIV-related DLBCL patients\u003c/h2\u003e \u003cp\u003eThe 1-year OS was compared between patients with high serum CHE and low serum CHE. Of 65 HIV-related DLBCL patients, 22 (33.8%) individuals died during the follow-up period. Our data suggest that the 1-year OS of patients was 84.2% in the high CHE group and 40.7% in the low CHE group (log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For those patients received chemotherapy, the 1-year OS of the high CHE group was still significantly superior to the low CHE group (85.7% vs. 50.0%, log-rank P\u0026thinsp;=\u0026thinsp;0.004)(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In multivariate analysis, models were adjusted for BMI, chemotherapy, CNS metastases, GCB subtype, Ann Arbor stage, IPI and Ki-67. After adjustment, CHE\u0026thinsp;\u0026gt;\u0026thinsp;5500 U/L [HR: 0.11 (0.03\u0026ndash;0.57), P\u0026thinsp;=\u0026thinsp;0.005] remained an independent prognostic factor for 1-year mortality. In the sensitivity analysis setting CHE as a continuous variable, CHE maintained its robust association with OS/mortality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (\u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVarious CHE estimates and mortality/ORR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eCHE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1-year mortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eORR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95% Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;4500U/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29 (0.13 to 0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.80 (3.00 to 54.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24 (0.11 to 4.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.00 (1.75 to 69.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;5500U/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21 (0.08 to 0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.57 (2.53 to 29.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11 (0.03 to 0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.74 (1.02 to 22.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn(CHE)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24 (0.11 to 0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.18 (3.64 to 234.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11 (0.02 to 0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.20 (2.09 to 496.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e*\u003c/b\u003e The continuous Cholinesterase (CHE) variable was transformed into natural logarithm variable.\u003c/p\u003e \u003cp\u003eAt the end of chemotherapy, the ORR was 80.0% in the high CHE group and 31.8% in the low CHE group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A positive correlation between CHE\u0026thinsp;\u0026gt;\u0026thinsp;5500 U/L and ORR was observed in the univariate logistic regression model [OR: 8.57 (2.53\u0026ndash;29.06), P\u0026thinsp;=\u0026thinsp;0.001]. In the multivariate Cox proportional hazards model, a high CHE level (CHE\u0026thinsp;\u0026gt;\u0026thinsp;5500 U/L) [AOR: 4.74 (1.02\u0026ndash;22.06), P\u0026thinsp;=\u0026thinsp;0.047] remained an independent prognostic factor for chemotherapeutic effectiveness after adjusting for sex, rituximab usage, CNS metastases, Ann Arbor stage, IPI and Ki-67. Similar results were observed in the sensitivity analysis, adjusting the CHE cutoff point to less than 4500 U/L or setting CHE as a continuous variable (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (\u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eThe patients were subsequently divided into four groups based on the quartiles of baseline serum CHE (Group 1: 1394\u0026ndash;4362 U/L, Group 2: 4483\u0026ndash;5663 U/L, Group 3: 5981\u0026ndash;7227 U/L, Group 4: 7378\u0026ndash;12124 U/L). We found that the 1-year OS rates from Group 1 to Group 4 were 31.25%, 68.75%, 81.25%, and 82.35%, respectively. The ORRs from Group 1 to Group 4 were 4.29%, 69.23%, 73.33%, and 86.67%, respectively. These data clearly showed a trend in which higher CHE was positively associated with a high ORR and 1-year OS (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this retrospective study, we aimed to shed light on the potential prognostic significance of serum CHE levels within the context of HIV-related DLBCL. Our investigation revealed the following results: (a) HIV-related DLBCL patients with low serum CHE levels exhibited a higher incidence of anemia, hypoproteinemia and inflammatory indicators. (b) HIV-related DLBCL patients with low CHE levels were more frequently classified as having advanced IPI scores and Ann Arbor stage. (c) High baseline CHE levels were closely correlated with improved ORR and OS. Thus, baseline CHE levels hold promise as a valuable prognostic marker for HIV-related DLBCL patients.\u003c/p\u003e \u003cp\u003e\"Clinical serum cholinesterase\" typically refers to pseudocholinesterase, which is predominantly synthesized in hepatocytes\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Therefore, low levels of serum pseudocholinesterase are often used as an indicator of impaired hepatic synthetic capacity. Patients with malignancy often receive high-dose chemotherapy, experience weight loss and exhibit malnutrition, which can affect liver synthetic function, including CHE production. Serum CHE has been reported to be a prognostic factor in several solid cancers \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe identified that CHE can serve as a reliable surrogate marker for predicting OS and ORR in HIV-related DLBCL patients. Specifically, patients with CHE\u0026thinsp;\u0026le;\u0026thinsp;5500 U/L exhibited significantly poorer OS and ORR, even after adjustment for potential confounding factors. The associations between CHE and patient outcomes can be attributed to several reasons:\u003c/p\u003e \u003cp\u003eFirst, it is worth noting that nutrition has a profound impact on the outcomes of patients with HIV-related DLBCL. A high incidence of anemia and hypoalbuminemia among HIV-related DLBCL patients with low CHE levels was observed in our research. Serum albumin has been widely used as a diagnostic marker for malnutrition in clinical practice. Low serum albumin is associated with inferior outcomes in patients with DLBCL \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The anemia probably results from DLBCL involvement of bone marrow and dietary causes \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. There is a life-saving requirement for higher nutritional intake for patients with anemia and hypoproteinemia. Of note, canonical correlation analysis confirmed that CHE had a robust correlation with nutrition-related indicators (total protein, albumin, hemoglobin and BMI) in our study. Importantly, a combined assessment of serum cholinesterase and albumin levels can serve as nutrition-related serum markers and be successfully employed to predict prognosis in cancer patients \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. In addition, cancer patients with poorer nutritional status are less likely to complete oncologic treatment according to plan and are at a high risk of developing adverse outcomes.\u003c/p\u003e \u003cp\u003eSecond, persistent inflammation has been shown to have a detrimental effect on the outcomes of DLBCL patients. Elevated levels of CRP were observed in HIV-related DLBCL patients with lower CHE levels in our study. Inflammation plays a crucial role in various stages of tumor development, including initiation, growth, invasion, and metastasis. The presence of persistent inflammation creates an environment that facilitates tumor progression and contributes to the development of certain types of cancer \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Elevated CRP levels are frequently detected in individuals with cancer, particularly those with advanced or metastatic disease, which are related to poor prognosis \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. This is because tumors can trigger the release of inflammatory cytokines, which in turn stimulate the liver to produce more CRP \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. In our research, we found a strong correlation between CRP and CHE, providing an explanation for why CHE levels can serve as a promising prognostic marker for DLBCL. Additionally, cell-based inflammation consisting of neutrophils and lymphocytes is also significantly associated with the progression of cancer and metastasis of malignant cells\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. In our study, the differences in neutrophils and lymphocytes between different ChE groups were not pronounced, possibly due to the impact of HIV itself on the destruction of lymphocytes and neutrophils.\u003c/p\u003e \u003cp\u003eThird, our study provided evidence of a significant association between low CHE levels and advanced stages of HIV-related DLBCL. Specifically, 92.6% of patients with CHE levels\u0026thinsp;\u0026le;\u0026thinsp;5500 U/L were classified as Ann Arbor stage III/IV, and 85.2% of patients with CHE levels\u0026thinsp;\u0026le;\u0026thinsp;5500 U/L had an IPI score\u0026thinsp;\u0026gt;\u0026thinsp;3. These findings indicate that CHE is an indicator of DLBCL disease progression. The advanced stage of DLBCL deteriorates the prognosis of patients.\u003c/p\u003e \u003cp\u003eCompared to other factors for cancer prognosis, CHE has the advantage of being cost-effective and easy to implement, with less interference in clinical settings. In light of our research findings, we strongly recommend that serum CHE levels be used as a valuable prognostic marker for HIV-related DLBCL patients.\u003c/p\u003e \u003cp\u003eThere are some limitations in our study. First, the sample size was relatively small, and consequently, a large cohort study is needed to further confirm our conclusions. Second, our study was a retrospective study conducted in a single medical center. A prospective study is needed to further elucidate our results. Third, the follow-up period was only one year, which may not have captured the long-term outcomes of patients.\u003c/p\u003e \u003cp\u003eIn conclusion, our study findings provide strong evidence of a close relationship between serum CHE levels and nutrient status as well as inflammation in HIV-related DLBCL patients. Notably, patients with low serum CHE levels were found to be predominantly in advanced stages of the disease and exhibited poor ORR and 1-year OS. Based on our robust data, serum CHE levels show great potential as a surrogate marker for risk stratification and for guiding treatment decisions in patients with HIV-related DLBCL.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research protocols were in accordance with the 1975 Declaration of Helsinki and received ethical approval from the Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University (Hangzhou, China) (No. 2021-139). All data were analyzed anonymously. The \u0026nbsp;Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University waived the requirement for written informed consent from the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study did not contain any identifying information of the participants. Therefore, it is not applicable for our research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our sincere appreciation to the Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University (Hangzhou, China), for their support and cooperation, including the waiver of informed consent. Their dedication to ethical standards greatly contributed to the success of this retrospective study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLijun Xu designed the study and drafted the manuscript. Jiaying Qin, Yong Tong, Shasha Ye and Lingyun Wang collected the data and performed the study. Minghan Zhou, Jiaying Qin and Yong Tong rechecked the data. Minghan Zhou analyzed and interpreted the data. Minghan Zhou, Jiaying Qin and Yong Tong performed the follow-ups. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eDiumenjo MC, Abriata G, Forman D, Sierra MS. \u003cstrong\u003eThe burden of non-Hodgkin lymphoma in Central and South America\u003c/strong\u003e. \u003cem\u003eCancer Epidemiol\u0026nbsp;\u003c/em\u003e2016; 44 Suppl 1:S168-S177.\u003c/li\u003e\n \u003cli\u003eEkberg S, K ES, Glimelius I, Nilsson-Ehle H, Goldkuhl C, Lewerin C, et al. \u003cstrong\u003eTrends in the prevalence, incidence and survival of non-Hodgkin lymphoma subtypes during the 21st century - a Swedish lymphoma register study\u003c/strong\u003e. \u003cem\u003eBr J Haematol\u0026nbsp;\u003c/em\u003e2020; 189(6):1083-1092.\u003c/li\u003e\n \u003cli\u003eHuguet M, Navarro JT, Molt\u0026oacute; J, Ribera JM, Tapia G. \u003cstrong\u003eDiffuse Large B-Cell Lymphoma in the HIV Setting\u003c/strong\u003e. \u003cem\u003eCancers (Basel)\u0026nbsp;\u003c/em\u003e2023; 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5:47.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cholinesterase, human immunodeficiency virus, diffuse large B-cell lymphoma, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-3880969/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3880969/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSerum cholinesterase (CHE) has been utilized as a surrogate marker in the context of solid cancers. Nevertheless, its potential association with the prognosis of hematologic malignancies remains unclear.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eSixty-five patients with new-onset HIV-related diffuse large B-cell lymphoma (DLBCL) were enrolled in this retrospective study. The patients were categorized into a high CHE group (\u0026gt;\u0026thinsp;5500 U/L) and a low CHE group (\u0026le;\u0026thinsp;5500 U/L). The demographic details, laboratory test results and clinical outcomes were compared between the high CHE group and the low CHE group. The overall response rate (ORR) at the end of chemotherapy was assessed by logistic regression analysis, and the 1-year overall survival rate (OS) was assessed by a multivariate Cox proportional hazards model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared with patients with high CHE, HIV-related DLBCL patients with low CHE exhibited lower levels of hemoglobin [g/L; 101.0 (81.0-115.0) vs. 123.5 (108.2\u0026ndash;141.0), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001] and serum albumin [g/L; 31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6 vs. 40.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001] but higher levels of lactate dehydrogenase (LDH) [U/L; 404.0 (253.0-849.0) vs. 248.0 (178.3\u0026ndash;372.0), P\u0026thinsp;=\u0026thinsp;0.014] and C-reactive protein (CRP) [mg/L; 36.1 (5.8\u0026ndash;66.6) vs. 5.1 (0.8\u0026ndash;5.1), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001]. Moreover, HIV-related DLBCL patients with low CHE demonstrated a higher prevalence of Ann Arbor stage III/IV (92.6% vs. 56.8%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and International Prognostic Index (IPI)\u0026thinsp;\u0026ge;\u0026thinsp;3 (85.2% vs. 35.1%, P\u0026thinsp;=\u0026thinsp;0.002) at the time of diagnosis of DLBCL. The 1-year OS of patients was 84.2% in the high CHE group and 40.7% in the low CHE group (log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). At the end of chemotherapy, the ORR was 80.0% in the high CHE group and 31.8% in the low CHE group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In multivariate analysis, CHE\u0026thinsp;\u0026gt;\u0026thinsp;5500 U/L was independently associated with a higher ORR [adjusted odds ratio (AOR): 4.74 (1.02\u0026ndash;22.06), P\u0026thinsp;=\u0026thinsp;0.047] and lower 1-year mortality [hazard ratio (HR): 0.11 (0.03\u0026ndash;0.52), P\u0026thinsp;=\u0026thinsp;0.005].\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBased on our robust data, baseline serum CHE levels show great potential as a surrogate marker for risk stratification and for guiding treatment decisions in HIV-related DLBCL patients.\u003c/p\u003e","manuscriptTitle":"Baseline Serum Cholinesterase Levels Predict the Outcome of HIV-Related Diffuse Large B-Cell Lymphoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-19 17:53:20","doi":"10.21203/rs.3.rs-3880969/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f9693f60-96ca-4ebc-8585-b3acb44f895f","owner":[],"postedDate":"February 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-11T12:57:58+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-19 17:53:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3880969","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3880969","identity":"rs-3880969","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}