Abstract
Background/Aim: Infection is a common cause of morbidity and mortality in patients treated for diffuse large B-cell lymphoma (DLBCL). However, there is limited information on the impact and risk factors for infection among patients receiving rituximab, cyclophosphamide, vincristine, doxorubicin, and prednisolone (R-CHOP). Patients and Methods: A retrospective study evaluating patients with DLBCL receiving R-CHOP and R-COP between 2004 and 2021 was conducted at a medical center. Hospital patients’ records for the five-item modified frailty index (mFI-5), sarcopenia, blood-based inflammatory markers, and clinical outcomes were statistically analyzed. Results: Patients with frailty, sarcopenia, and high neutrophil-to-lymphocyte ratio (NLR) were associated with a higher risk of infections. The revised International Prognostic Index poor-risk group, high NLR, infections, and treatment modality were risk factors for shorter progression-free and overall survival. Conclusion: Pre-treatment high NLR was a predictor of infection and survival outcome in DLBCL patients.
Diffuse large B cell lymphoma (DLBCL) is the most common type of lymphoma (1). Chemoimmunotherapy (CIT) with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP), the standard of care for DLBCL, is effective in 60%-70% of patients (2, 3).
Bone marrow suppression induced febrile neutropenia (FN), and infections were crucial in the pathogenesis of lymphoma treatment-related mortality (4). During treatment with the R-CHOP regimen in DLBCL, up to 24% (5) and 63% (6) of patients present with FN and infection, respectively. Advanced disease, older age, poor performance status, comorbidities, poor nutritional status, and the absence of granulocyte colony-stimulating factor (G-CSF) prophylaxis were independent risk factors for FN in patients treated with the R-CHOP regimen (7-9).
Infection is a typical cause of morbidity and mortality in patients treated for lymphoma. However, there is limited information on infection risk factors and their impact on patients treated for DLBCL. Extensive research has previously revealed that sarcopenia, frailty status, and blood-based biomarkers including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, and systemic immune-inflammation index (SII) are significant prognostic markers of DLBCL (10-12). Up to now, there has been no comprehensive analysis of the associated infection and survival outcome in patients with DLBCL.
Thus, the current study aimed to retrospectively analyze the predictive effect of frailty, sarcopenia, and blood-based inflammatory markers on infections and survival outcomes in patients with DLBCL treated with the R-CHOP or R-COP regimen.
Patients and Methods
Patient selection criteria. This retrospective study was approved by the Research Ethics Committee of the Hualien Tzu Chi General Hospital (no.: IRB109-193-B). In this study, we included patients who (i) were confirmed as CD20-positive DLBCL between September 2004 and September 2021 at the Hualien Tzu Chi General Hospital; (ii) had no active infections and whose infections were resolved before initiating therapy; (iii) received the R-CHOP or R-COP regimen. Patients were excluded if they had (i) primary central nervous system B-cell lymphoma or intravascular large B-cell lymphoma; (ii) human immunodeficiency virus or Epstein-Barr virus infection; (iii) a previous history of cancer and concurrent uncontrolled medical conditions. All patients underwent a thorough work-up, including medical history, physical, and laboratory examination, bone marrow aspiration, computed tomography (CT) scanning, and 18F-FDG positron emission tomography (PET)/CT. The requirement for written informed consent was waived due to the retrospective nature of the study and the anonymity that was ensured during data collection.
Patient characteristics and data collection. From the electronic chart review, each patient’s age, sex, Ann Arbor stage, extranodal involvement, Eastern Cooperative Oncology Group, and lactate dehydrogenase level were recorded for the calculation of the R-IPI score (13), Bulky disease (which presents as a nodal mass whose greatest dimension exceeds 7.5 cm) (14), comorbidity, five-item modified frailty index (mFI-5) (15), body mass index (BMI), serum albumin, skeletal muscle index (SMI), R-CHOP, or R-COP regimen with or without involved-field radiotherapy. In routine blood tests, white blood cell counts, hemoglobin levels, platelet counts, and differential white blood cell counts were obtained within one week of DLBCL treatment. The NLR was calculated as the ratio of the number of neutrophils to the number of lymphocytes. The SII was calculated as the NLR × the platelet count.
Definition of frailty and sarcopenia. CT images from 18F-FDG PET/CT scans were used to assess the axial slice closest to the inferior aspect of the third lumbar vertebra body (L3) by applying a threshold within −29 to +150 Hounsfield units. The L3 skeletal muscle index (SMI, cm2/m2) was calculated as the skeletal muscle area normalized by the square of the height. All images were analyzed using the open-source software program called OsiriX (Pixmeo, Geneva, Switzerland) (16). Sarcopenia was defined using X-Tile software (Yale University, New Haven, CT, USA) (17), which sets each number within the range of measurement of the SMI as the cutoff point. The number with the maximum chi-square score and minimum p-value is selected as the optimal cutoff point, which uses log-rank tests for survival comparison between the two groups. The thresholds for L3 SMI were 46 cm2/m2 for men and 34 cm2/m2 for women in our study population. Frailty was quantified using the mFI-5, a modified form of the 11-item frailty index based on the Canadian Study of Health and Aging Frailty Index that is used to quantify a series of “accumulating deficits” (18). The mFI-5 screening tool, which combines functional status and comorbidity, is scored from 0 to 5. Based on a previous study (19), patients were classified as no frailty, pre-frailty, and frailty (0, 1, ≥2) based on their scores.
Patient follow-up evaluation. Data on neutropenia events were collected from the worst severity within each CIT and graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events, v.5.0 (20). Definitions of infections as positive bacterial or fungal culture from the bloodstream, urine, or sputum were deemed by the clinical team to require intervention. Symptomatic toxicity had no collection because it might have been overlooked in the review of the medical records. Progression-free survival (PFS) was defined as the time from treatment to the date of the first relapse, progression, or death due to any cause. Overall survival (OS) was defined as the time from treatment until death due to any cause.
Statistical analysis. The data were coded and analyzed using SPSS version 28 (IBM, Armonk, NY, USA). The optimal cutoff values for NLR and SII were determined using receiver operating characteristic (ROC) curve analyses based on Youden’s index (21). The correlation between clinical risk variables and CIT-related neutropenia events and infections was assessed using logistic regression analysis. The Kaplan–Meier method was used to estimate the OS and PFS differences using the log-rank test. A Cox regression analysis was performed for significant findings regarding mortality. Time-dependent ROC curve analyses of systemic inflammation indexes were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan), a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria). A p-value of <0.05 was considered statistically significant.
Results
Patient characteristics. The flowchart presented in Figure 1 outlines this study. A total of 123 patients were assessed for eligibility for inclusion in this study. Patient characteristics are provided in Table I. More than half of the patients were male (57.7%). The median age was 62 years (interquartile range 50.5-73.0), and 52.8% were older than 60. Most patients had very good (8.9%) and good risk (48.8%), no frailty status (48%), while bulky disease was rare (9.8%). Most patients had normal nutritional status. Sarcopenia was identified in 36 patients (29.3%); 16.7% had sarcopenic obesity. As treatment regimens, 72.4% of patients received R-CHOP, whereas 22% received radiotherapy.
Flow chart. R-CHOP: Rituximab + cyclophosphamide + doxorubicin + vincristine + prednisone; R-COP: rituximab + cyclophosphamide + vincristine + pednisone; PET: positron emission tomography; CT: computed tomography.
Patient characteristics.
Characteristics factors associated with CIT-related severity adverse events. The incidence of neutropenia and infections is seen in Table II. A decrease in neutrophil count occurred more often (56.9%), followed by infections (30.9%), FN (20.3%), and anemia (13.8%), and decreased platelet count (13%). Univariate and multivariate Cox regression analyses are summarized in Table III and Table IV. Statistically significant variables in the univariate analysis were included in the multivariate analysis. The cutoff values of high NLR for infections was over 7.2. Since there was no significant ROC curve to determine the optimal cutoff value of SII, we used the continuous variable. In multivariate analysis, treatment with R-CHOP was associated with severe neutropenia. The mFI-5, sarcopenia, and higher NLR were associated with infections.
Incidence of severe adverse events during chemoimmunotherapy.
Univariate analysis of factors predicting the severe side effects of chemoimmunotherapy.
Multivariate analysis of factors predicting the severe side effects of chemoimmunotherapy.
Survival analysis. The results of univariate and multivariate Cox regression analyses for the clinical risk variables on PFS and OS are presented in Table V. In the univariate analysis, R-IPI, sarcopenia, high NLR, treatment with R-COP, and infections were associated with PFS. The univariate Cox regression analysis for OS showed that BMI, albumin, SII, and FN failed to predict OS. Statistically significant variables in the univariate analysis were included in the multivariate analysis. The cutoff values of high NLR for PFS and OS were over 5.8 and 4.9, respectively. R-IPI, high NLR, treatment of R-COP, and infections maintained their prognostic significance for PFS and OS.
Univariate and multivariate cox regression analyses for predictors of survival outcomes.
Discussion
The present study investigated the efficacy of the combination of R-IPI, frailty, sarcopenia status, systemic inflammation, and treatment regimen in predicting neutropenia events, infections, and survival outcomes in 123 patients with newly diagnosed DLBCL. We demonstrated that a high NLR, frailty, and sarcopenia status were associated with a higher risk of infections. More importantly, the high NLR and infections were risk factors for shorter PFS and OS, except in the R-IPI poor-risk group and received the R-COP regimen. In addition, age>65 years, comorbidities, frailty, sarcopenia, the chemotherapy regimen, and no prophylaxis with G-CSF were risk factors for FN (7-9, 22-24). In this study, we did not find any relation between FN and risk factors. Only the R-CHOP regimen was associated with severe neutropenia. FN in our study may have been influenced by baseline characteristics such as relatively younger age, fewer patients presenting frailty, sarcopenia status, and appropriate nutritional status. Moreover, according to the guidelines (4) on the use of the G-CSF for FN prophylaxis in our center, this was consistent with the findings of previous studies that demonstrated decreased neutropenia and FN with colony-stimulating factors (25, 26).
In this study, we found that a high NLR was one of the independent predictors of infection. During the last decade, more and more attention has been focused on the relationship between a high NLR (≥7) and infections in various diseases (27-29). Several current studies have revealed that the inflammatory nature of a tumor microenvironment is an important component of tumor initiation, growth, and progression (30, 31). Furthermore, the NLR reflected the balance between the inflammation pathway activity and anti-immune function. A meta-analysis including 11 studies with a total of 2,515 DLBCL patients discovered that a higher NLR (≥3) was associated with poor survival outcomes (32). The NLR, which can be acquired only by routine work-up, can help personalize the treatment intensity and aftercare plan to improve the likelihood of early detection and decrease the additional cost involved.
Infection, a common cause of morbidity and mortality in DLBCL patients treated with R-CHOP, is associated with shorter survival outcomes. Other reported rates of infection range from 10% to 63% (6, 33). In the current study, 30.9% of patients experienced at least one infection. Subsequently, death occurred more frequently among infected patients within three months in 21.0% (n=8) than within 4-6 months (5%, n=2). The patients were more likely to die during their first two cycles of CIT than during subsequent cycles, which is consistent with the findings of previous studies in which lymphoma patients died from all causes (6, 25, 34). This study identified patients at high risk of infection and emphasized the elevated mortality risk period during CIT treatment. The early detection of high-risk patients and supportive measures, including hand hygiene, respiratory hygiene/cough etiquette, vaccine administration, and the limitation of hazardous environmental exposures are planned to enhance infection prevention (35).
Patients with newly diagnosed DLBCL who are at the highest risk of infection are those who have higher NLRs, frailty, and sarcopenia statuses. The presence of a R-IPI poor risk score and a higher NLR, the R-COP regimen, and infections were predictors of shorter PFS and OS. Upon reviewing the literature, conflicting results were found, and the predictive value of sarcopenia in patients with poor survival was not confirmed for hematological malignancies (11, 36-40). This difference could be directly associated with the heterogeneity of samples studied, such as lymphoma variants, type of treatment, stage, SMI thresholds, and imaging tools. Further prospective studies investigating the diagnostic criteria in patients with DLBCL for sarcopenia are needed.
The study also has certain limitations. Initially, as a retrospective study conducted at a single medical center, its sample size was small. Thus, the findings of this study require further validation in a larger cohort. Additionally, extensive cohort studies need to be conducted to specify the cutoff threshold of continuous biomarkers, such as the cutoff value of the NLR and sarcopenia. Future multicenter studies involving patients with infections are required to fully elucidate the role of the NLR in improving clinical outcomes of patients with DLBCL undergoing treatment. Furthermore, no genetic analysis using techniques such as fluorescence in situ hybridization and immunostaining has been conducted, and these evaluations are not routinely performed in clinical practice retrospectively.
In conclusion, the present study demonstrated that frailty, sarcopenia, and higher NLR are significant predictors of infections in DLBCL patients receiving the R-CHOP or R-COP regimen. Infection and higher NLRs were also associated with reduced survival rates, except for the R-IPI poor risk score and the R-COP regimen.
Acknowledgements
This study was funded by grant number TCRD110-03 from the Buddhist Tzu Chi Medical Foundation. The funder had no role in the study design, data collection, statistical analysis, manuscript preparation, or the decision to publish.
Footnotes
Authors’ Contributions
Research design: Huang CH; Clinical data: Wang TF and Chu SC; Image analysis: Lue KH, Wang TF, and Chu SC; Statistical analysis: Shin MF and Huang CH; Manuscript writing: Shin MF and Huang CH; Reviewing and revising: Huang CH.
Conflicts of Interest
The Authors have no conflicts of interest to declare in relation to this study.
- Received January 24, 2023.
- Revision received February 10, 2023.
- Accepted February 13, 2023.
- Copyright © 2023 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
