Clinical Characteristics and Prognosis of Patients with Follicular Lymphoma Grade 3A: A real-world study in a single centre

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However, there is no consensus on the management of FL grade 3A (FL3A). Methods We performed a real-world study of newly diagnosed FL patients from January 2013 to December 2022. we collected the clinical data of FL3A patients to analyse the correlation among baseline features, therapy regimens and prognosis. The data were collected from the hospital's electronic medical records system. Results A total of 223 patients with FL3A were enrolled. With a median follow-up of 41 months, the expected 5-year overall survival (OS) was 97.4% and the 5-year progression-free survival (PFS) was 73%. In real-word, most patients with advanced FL3A in low-tumor-load received therapy, majority with RCHOP regimen (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone). Patients with advanced FL3A treated with RCHOP regimen and maintenance therapy had better PFS. There was no significant difference in PFS between the treatment group and watch-and-wait group in patients with low-tumor-load. The univariate analyses indicated that the maximum 18F Fluorodeoxyglucose uptake in PET (SUVmax), Ki-67 index, platelet count were related to prognosis. Multivariate analyses showed that only SUVmax was the independent prognostic factor and SUVmax ≥ 15 related with poor PFS. Conclusion FL3A patients have a long survival, with a 5-year PFS of 73%. In real-world, most patients with advanced FL3A in low-tumor-load received therapy. Multivariate analyses indicated that SUVmax ≥ 15 was an independent poor prognostic factor affecting PFS in patients with advanced FL3A. In addition, Ki-67 index was also maybe related with prognosis. follicular lymphoma advanced FL3A maximum standardized uptake value (SUVmax) Ki-67 progress-free survival (PFS) Figures Figure 1 Figure 2 Figure 3 Introduction Follicular lymphoma (FL) is the most common subtype of indolent non-Hodgkin's lymphoma (NHL), accounting for approximately 22% of NHL cases [ 1 ]. The World Health Organization (WHO) pathological grading system of FL is based on the number of centroblasts per high-power field (HPF) of view, which is considered a clinical predictor of outcome. In the 2017 WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues, classic FL can be divided into three grades: FL grade 1–2 (FL1-2) or low-grade FL, FL grade 3A (FL3A) and FL grade 3B (FL3B). However, in the 2022 WHO classification of haematolymphoid tumours (WHOHAEM5) [ 2 ], pathological grading was abolished, and FL3B was separately classified as follicular large B-cell lymphoma (FLBL), while the International Consensus Classification (ICC) in 2022 [ 3 ] retained the FL grading as described in the 2017 WHO classification. Diagnosis and therapy guidelines, such as the National Comprehensive Cancer Network (NCCN), are available for classic FL /low-grade FL, but there is no consensus on the optimal treatment for FL3A; moreover, treatment regimens need to be individualized. For patients with advanced (stage III-IV) FL, treatment is generally based on tumour load according to the French Groupe d’Etude des Lymphomes Folliculaires (GELF) established criteria [ 4 ]. Several prospective randomized controlled trials have not demonstrated a survival benefit of immediate treatment versus watch-and-wait (W&W) in low-tumour-load, asymptomatic patients [ 5 , 6 , 7 , 8 ]. Chemoimmunotherapy with anti-CD20 monoclonal antibodies (rituximab (R) or obinutuzumab (G)) is the current first-line treatment option for patients with FL. In a multicentre randomized StiL NHL1 phase III study [ 9 ], the results showed that the BR regimen (bendamustine (B) in combination with rituximab) was superior to RCHOP (cyclophosphamide (C), doxorubicin (H), vincristine (O), and prednisone (P) in combination with rituximab) in terms of progression-free survival (PFS). At a median follow-up of 45 months, the median PFS of patients treated with BR and R-CHOP were 69 and 31 months, respectively (P < 0.0001). The GALLIUM trial was a randomized controlled phase III clinical trial comparing the efficacy and safety of rituximab versus obinutuzumab in combination with chemotherapy (bendamustine, CHOP or COP) for the treatment of untreated advanced FL [ 10 ]. A total of 1202 patients were randomized 1:1 to receive combination chemotherapy with either obinutuzumab or rituximab, followed by maintenance therapy with the same antibody for up to 2 years in patients who responded to the treatment. At a median follow-up of 34.5 months, the obinutuzumab group had a longer PFS and lower risk of disease progression and recurrence than did the rituximab group, with predicted 3-year PFS rates of 80% and 73%, respectively. However, there was no difference in the overall remission rate (ORR) or overall survival (OS) between the two groups. The above studies included patients with FL1-2 and FL3A. The International Prognostic Index for Follicular Lymphoma (FLIPI) is the most commonly used in the prognostic evaluation of FL. FLIPI-1 is based on age, Ann Arbor stage and number of lymph node sites involved, hemoglobin level, and serum lactic dehydrogenase (LDH) level. FLIPI-2 is based on age, hemoglobin level, longest diameter of the largest involved lymph node, beta-2 microglobulin level, and bone marrow involvement. FLIPI-2 defines different risk groups within the subgroup of FL patients treated with rituximab-based regimens, with predicted 5-year PFS rates of 98%, 88%, and 77% for low-risk, intermediate-risk, and high-risk patients with FL (P < 0.0001) [ 11 ]. Thus, FLIPI-2 may be useful in assessing the prognosis of patients receiving aggressive rituximab-based regimens. A simpler prognostic model that includes only baseline serum β2-microglobulin and LDH levels is also available [ 12 ]. Although these prognostic models can predict prognosis, no studies have shown that they can be used as a basis for treatment selection. Above studies also included patients with FL1-2 and FL3A. Based on the above research background, we collected the clinical data of FL3A patients to analyse the correlation among baseline features, therapy regimens and prognosis. This study was approved by the Ethics Committee of the First Affiliated Hospital, College of Medicine, Zhejiang University. Patients and methods Patients We performed a real-world study of patients who were newly diagnosed with FL between January 2013 and December 2022 at the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China. Adult patients diagnosed with FL3A according to the 2017 WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues were included. Patients with FL of grades 1–2 and 3A in one specimen were also included. Patients with one or more of the following conditions were excluded from the data analysis: (1) patients with FL of coexisting grade 3A and 3B or diffuse large B-cell lymphoma (DLBCL) anywhere in one specimen; (2) individuals who had visited only once or had not been hospitalized in the haematology department; or (3) patients with no baseline clinical data in the hospital's electronic medical records. Data collection The following data were collected from the hospital's electronic medical records system: entomological characteristics, pathological information, clinical characteristics, blood examinations at diagnosis, treatments, efficacy assessments and survival data. Basic characteristics including but not limited to: age, gender, comorbidity; 18F Fluorodeoxyglucose (FDG) positronemission tomography (PET) scan, computer tomography (CT) scan, color Doppler ultrasound examination; primary site, number of lymph node areas involved, extra-nodal involvement, bone marrow involvement; B-symptoms, tumor-related symptoms; white blood cell count (WBC), hemoglobin level (HB), platelet count (PLT); the levels of glutamic-pyruvic transaminase (ALT), glutamic oxaloacetic transaminase (AST), uric acid (UA), C-reactive protein (CRP), serum lactate dehydrogenase (LDH), β2 microglobulin (β2M), ferritin, Immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), and so on. Patients with FL3A were divided into early (stage I and stage II) FL3A and advanced (stage III and stage IV) FL3A according to the Ann Arbor-Cotswolds staging criteria. Tumor load was evaluated according to the GELF criteria [ 4 ]. The efficacy was evaluated by the revised standards of the 2014 Lugano Conference, which were complete remission (CR), partial remission (PR), overall remission (OR), stable disease (SD), progressive disease (PD). PFS was defined as the time from the date of diagnosis until disease relapse/progression or death. Overall survival (OS) was defined as the time from diagnosis to death from any cause. The last follow-up time for this study was December 31, 2023. Statistical analyses Categorical variables are presented as values and percentages; continuous variables are presented as medians and ranges. For comparisons between groups, t tests and nonparametric tests were used for continuous variables, and chi-square tests were used for categorical variables. Variables with P < 0.1 in the univariate analysis were included in the multivariate analysis. P ≤ 0.05 (2-sided) was considered significant. Statistical analysis was performed with SPSS software (version number: 26.0, SPSS, Inc., Chicago, USA). Results Baseline characteristics A total of 853 patients with FL were admitted from 1st January 2013 to 31st December 2022, among whom 235 patients with FL3A accounted for 27.55% of all patients with FL. Twelve of the 235 patients with FL3A came to the hospital only once, and no detailed data were available. Finally, 223 patients with FL3A were enrolled in our study (Fig. 1 ). The number of patients enrolled gradually increased as time goes on and 60 (26.9%) patients were diagnosed with FL3A in 2022 (Fig. 2 ). Among the 223 patients, 113 patients were male and 110 were female, with a male-to-female ratio close to 1:1, and the median age was 57 (24–89) years. The median number of lymph nodes involved was 4 (0–7), the median maximum diameter of the lymph nodes was 3cm (0.5-16.6cm), and extra-nodal lesions were most commonly located in the gastrointestinal tract, followed by the thyroid, pancreas, nasopharynx and kidney. The most common comorbidity was hypertension, followed by hepatitis B and autoimmune diseases. A total of 101 patients underwent PET scan before treatment, and the median maximum standardized uptake value (SUVmax) of FDG was 10.5 (3.3–39.6). According to ANN-Arbor staging, 24 patients had early FL3A, and 199 patients had advanced FL3A. Among patients with advanced FL3A, 93 patients (46.7%) had low tumour loads, and 106 patients (53.3%) had high tumour loads, according to the GELF criteria. Compared to patients with early FL3A, patients with advanced FL3A had much greater SUVmax, CRP, serum LDH and β2-microglobulin levels and lower haemoglobin and immunoglobulin G (IgG) levels, as described in Table 1 . Table 1 Baseline clinical characteristics of follicular lymphoma grade 3A Baseline clinical characteristics Early stage Advanced stage P Sex (male:female) 12:12 101:98 0.945 Age, median (range) 53 (43–67) 57 (24–89) 0.373 18F Fluorodeoxyglucose metabolic maximum uptake value in PET scan (SUVmax) 9.578 ± 3.8157 12.747 ± 6.5769 0.047 White blood cell count, WBC (×10 9 /L) 5.7624 ± 1.66725 6.1405 ± 2.84149 0.347 Haemoglobin (g/L) 139.67 ± 22.430 129.73 ± 22.430 0.035 Platelet count, PLT (×10 9 /L) 217.42 ± 52.330 208.13 ± 80.834 0.449 Glutamic-pyruvic transaminase, GPT (U/L) 26.26 ± 19.501 20.04 ± 13.887 0.053 Glutamic oxaloacetic transaminase, GOT (U/L) 23.70 ± 11.918 23.41 ± 1.820 0.912 Uric acid, UA (U/L) 313.39 ± 54.027 329.42 ± 96.269 0.231 C-reactive protein, CRP (U/L) 2.7618 ± 4.03218 16.9886 ± 42.11636 0.000 Serum Lactic dehydrogenase, LDH (U/L) 191.1 ± 49.105 279.59 ± 352.643 0.002 Ferritin (ug/L) 210 ± 204.383 358.35 ± 849.268 0.054 β2-microglobulin (U/L) 1710.86 ± 556.393 2486.24 ± 2463.970 0.001 Immunoglobulin A, IgA (mg/dl) 204.18 ± 90.691 187.55 ± 105.515 0.485 Immunoglobulin M, IgM (mg/dl) 105.3 ± 74.711 101.6 ± 197.442 0.876 Immunoglobulin G, IgG (mg/dl) 1361.88 ± 323.109 1087.68 ± 531.111 0.038 Ki−67 index 52.61 ± 14.761 51.15 ± 15.967 0.660 Therapy regimens and efficacy A total of 192 patients (86.1%) received systemic therapy. The most common treatment regimens were anti-CD20 monoclonal antibodies (rituximab (R) or otuzumab (G)) combined with CHOP (cyclophosphamide (C), doxorubicin/epirubicin/doxorubicin liposomes (H), vincristine (O), prednisone (P)) or a CHOP-like regimen (e.g., COP, CEOP (COP combined with etoposide (E)), CHOPE, etc.) in 61.8% of patients. Other therapy regimens included R/G monotherapy, R2 (rituximab combined with lenalidomide), BR (rituximab combined with bendamustine), and GB (otuzumab combined with bendamustine) regimens, and one patient received chemo-free regimen (rituximab, lenalidomide and ibrutinib). Only 5 patients were not treated with rituximab or otuzumab. Only 24 (25.8%) patients with advanced FL3A with low-tumor-load according to the GELF criteria were treated with watch-and-wait. A total of 175 patients with advanced FL3A received systemic therapy, among witch 62.3% of patients received R/G combined with CHOP/CHOP-like regimens. Of the patients who achieved a PR or CR, 62.9% received maintenance therapy with the same anti-CD20 monoclonal antibody. Among the 175 patients with advanced FL3A disease who received systemic therapy, two patients died early (less than 1 month after diagnosis). Thirteen patients did not complete 4 cycles of therapy at our institution or whose efficacy data were unavailable, and overall survival data were only obtained by telephone follow-up. A total of 160 patients with advanced FL3A were available for efficacy assessment, and efficacy was assessed as SD or PD in only 6 patients, with an OR rate (ORR) of 96.3% during the initial therapy. Survival analysis With a median follow-up time of 41 months, 20 patients with FL3A were lost to follow-up, including 4 patients with available PFS data. Five patients with FL3A were died, including two early deaths. The expected 5-year overall survival (OS) was 97.4%, and the median OS was not reached. A total of 45 patients with FL3A experienced PD, and one patient experienced PD 5 times. The expected 2-year and 5-year PFS rates of patients with FL3A were 87% and 73%, with a median PFS of 117 months. During the follow-up period, only one patient with early FL3A expression experienced PD at 25 months, with a expected 2-year PFS of 100%, and the expected 2-year PFS of advanced FL3A patients was 86%, respectively (P < 0.05) (Fig. 3 A). We performed univariate and multivariate analyses with Cox proportional hazard models to identify baseline features and therapeutic regimens associated with PFS in patients with advanced FL3A, and the univariate analyses results are described in Table 2 . It was shown that SUVmax and platelet count at diagnosis were both associated with PFS, while there was no relationship between hemoglobin level and PFS. Ki-67 index less than 50 or more than 60 (Fig. 3 F), and WBC under 5.0×10 9 /L were both related with poor PFS in patients with advanced FL3A. According to the results of univariate analyses results, we put SUVmax, Ki-67 index, platelet count, WBC, LDH, IgA and IgM together in multivariate analyses with Cox proportional hazard models. Multivariate analyses showed that only the SUVmax was the independent prognostic factor and SUVmax more than 15 related with poor PFS in patients with advanced FL3A. Table 2 The univariate analyses with Cox proportional hazard models of prognostic factors for progress-free survival (PFS) in patients with advanced FL3A Factors HR(%95 CI) P Sex(male vs female) 0.887(0.487–1.616) 0.695 Age 1.017 (0.993–1.042) 0.173 (<60y vs ≥ 60y) 1.083(0.597–1.965) 0.793 18F Fluorodeoxyglucose metabolic maximum uptake value in PET scan (SUVmax) 1.140(1.057–1.231) 0.001 (<13.0 vs ≥13.0) 2.748(0.773–0.9766) 0.118 (<14.0 vs ≥14.0) 3.476(0.977–12.361) 0.054 (<15.0 vs ≥15.0) 4.885(1.356–17.589) 0.015 White blood cell count, WBC 0.982 (0.887–1.086) 0.720 (<5.0×10 9 /L vs ≥ 5.0×10 9 /L) 0.550(0.303–0.997) 0.049 Haemoglobin 0.995 (0.983–1.007) 0.431 (<120g/L vs ≥120g/L) 0.940(0.473–1.866) 0.859 Platelet count, PLT 0.995 (0.991-1.000) 0.037 (<100 ×10 9 /L vs ≥ 100×10 9 /L) 0.408(0.145–1.145) 0.089 Serum Lactic dehydrogenase, LDH 1.000 (1.000-1.001) 0.461 (<210U/L vs ≥210U/L) 2.020(1.099–3.826) 0.024 β2-microglobulin 1.000 (1.000–1.000) 0.796 Ferritin 1.001 (0.998–1.004) 0.627 C-reactive protein, CRP 1.002 (0.995–1.008) 0.561 Immunoglobulin A, IgA 0.997 (0.993–1.001) 0.101 (<178mg/dl vs ≥178mg/dl) 0.488(0.250–0.956) 0.036 Immunoglobulin M, IgM 1.000 (0.997–1.002) 0.961 (<100mg/dl vs ≥100mg/dl) 0.285(0.88–0.928) 0.037 Immunoglobulin G, IgG 0.999 (0.999-1.000) 0.227 (<860mg/dl vs ≥860mg/dl) 0.943(0.481–1.852) 0.866 Ki-67 index 0.998 (0.978–1.019) 0.867 (<50% or ≥ 60% vs ≥ 50% and < 60%) 0.354(0.138–0.907) 0.031 Tumor-load (low-tumor-load vs high-tumor-load) 1.391(0.762–2.542) 0.283 Initial therapy regimes (based with anti-CD20 monoclonal antibody) 0.11 Monotherapy 0.273(0.034–2.184) 0.221 Combined with lenalidomide 0.439(0.160–1.200) 0.109 Combined with bendamustine 0.512(0.163–1.607) 0.251 Combined with CHOP or CHOP-like 0.244(0.111–0.535) 0.000 RCHOP or RCHOP-like vs others 2.381(1.305–4.344) 0.005 Maintainced therapy with anti-CD20 monoclonal antibody (yes vs no) 0.302(0.157–0.581) 0.000 Significant differences were also found between different initial therapy regimens. The PFS of patients in the R-CHOP group (including those in the R/G-CHOP and R/G-CHOP-like regimens) was more favourable than that of patients in the non-R-CHOP group (those in the other regimens), with predicted 5-year PFS rates of 78% and 51.7%, respectively (P < 0.05) (Fig. 3 D and Fig. 3 E). The PFS of patients who received anti-CD20 monoclonal antibody maintenance treatment after remission was more favourable than that of patients who did not receive maintenance treatment (P < 0.05) (Fig. 3 B). There was no statistically significant difference in PFS between the treatment group and watch-and-wait group in patients with advanced FL3A with low-tumor-load according GELF criteria (Fig. 3 C). Discussion FL3A accounted for 27.55% of the FL in our study, which was significantly lower than the proportion of FL1-2, which is consistent with other published research results [ 13 , 14 , 15 ]. Patients with FL have a good prognosis, with longer PFS and OS after chemotherapy and immunotherapy. Previous studies have shown that FL3A shares similarities in histological characteristics with FL1-2, but there are differences in actual survival, and there is no consensus on the recurrence and prognosis of FL3A and FL1-2 patients. A study conducted by Naik et al. [ 16 ], based on surveillance, epidemiology, and end results (SEER) data, compared the impact of histological grade on treatment outcomes and prognosis. A total of 39925 patients with FL were enrolled. This study revealed that FL3 (FL3A and FL3B) is more invasive and has a worse prognosis than FL1-2, but FL3B patients were not excluded from this study; therefore, the results cannot be fully attributed to FL3A. A multicentre study in China showed that FL3A patients had significantly shorter PFS than FL1-2 patients, but there was no significant difference in OS between them [ 17 ]. This may be related to differences in clinical and pathological features at the time of diagnosis. Montello et al. [ 18 ] conducted a long-term comparative follow-up study on 132 FL3A patients who received R-CHOP and BR treatment. The median follow-up time was 14.8 years in the R-CHOP group and 15.2 years in the BR group. There was no significant difference in OS between the two groups, and the median OS was not reached. The median PFS of the BR group was significantly longer than that of the RCHOP group (15 years vs. 11.7 years, respectively). Our study revealed that the median follow-up time was 41 months, the median OS was not reached, and the median PFS was 117 months, with an expected 2-year PFS of 87% and a 5-year PFS of 73%. Early FL3A patients had better PFS than advanced FL3A patients. We investigated the impacts of initial therapeutic regimens on PFS in patients with advanced FL3A. According to the GELF criteria and guidelines, advanced FL patients with low-tumour-load can be treated with watch-and-wait method. Our analysis revealed the same results. However, in our study, the most of patients with low-tumour-load received systematic treatment, and only 25.8% of patients received watch-and-wait strategy. This research result needs to be further confirmed by expanding the sample size and conducting randomized controlled studies. The initial treatment for advanced FL3A is anti-CD20 monoclonal antibody-based chemoimmunotherapy. Patients who achieved PR or CR then received maintenance treatment with the same anti-CD20 antibodies. In our study, 61.9% of patients with advanced FL3A mutations received R-CHOP or R-CHOP-like regimens, while 38.1% of patients received other treatment regimens (such as BR, R2, etc.). The 5-year PFS of patients in the RCHOP group was significantly longer than that of patients in the non-RCHOP group (78% vs. 51.7%, P < 0.05). This was inconsistent with previous reports due to much fewer patients received BR regime compared with R-CHOP regime. Patients who received maintenance therapy with anti-CD20 monoclonal antibodies had better PFS than patients who did not receive maintenance therapy. We also conducted exploratory research on the correlation between clinical and pathological features and the prognosis of patients with advanced FL3A. We found that the SUVmax level was independent prognostic factor for PFS, and the critical points obtained are different from those reported in previous studies. Univariate analyses with Cox proportional hazard models reveled that Ki67 index and platelet count were both related with PFS, however, multivariate analyses were not indicated positive results. PET scan is one of the most commonly used methods for evaluating the condition of indolent lymphoma. Previous reports have shown that FDG uptake can predict the possibility of histological transformation to DLBCL. In a retrospective study [ 19 ], an SUVmax > 10 or > 13 was associated with high specificity in detecting histological transformation. Dupuis et al. [ 20 ] conducted a prospective study on the treatment of advanced high-burden FL tumours with a 6-cycle R-CHOP regimen. Mid-induction PET scan evaluation was performed after 4 cycles, and end of induction (EOI) PET scan evaluation was performed after 6 cycles. The 2-year PFS of the mid-induction PET-negative group was significantly greater than that of the PET-positive group (86% vs. 61%, P = 0.0046), but there was no significant difference in OS. The 2-year PFS and OS of the EOI PET-negative group were significantly greater than those of the PET-positive group (2-year PFS: 87% vs. 51%, P < 0.001; 2-year OS: 100% vs. 88%, P = 0.013). However, there is no research showing the relationship between the baseline PET scan FDG metabolism SUVmax and prognosis. In our study, 101 patients underwent baseline PET scan, with a median SUVmax of 10.5 (3.3–39.6). In the analysis of prognostic factors, we found that the PFS of advanced FL3A patients with an SUVmax ≥ 15 was much poorer than that of patients with an SUVmax < 15 (5-year PFS, 59.9% vs. 74.6%, P = 0.015). Based on previous reports, we speculate that patients with an SUVmax ≥ 15 have a tendency towards histological transformation, and their prognosis is relatively poor. Based on previous relevant studies, we believe that it is necessary to conduct further prospective studies to determine the impact of PET scans on prognosis at baseline and after induction therapy to play a role in induction therapy and subsequent treatments. At the same time, we suggest conducting another pathological biopsy on patients with a high SUVmax to determine whether there is a possibility of histological transformation. Pathology is the gold standard for the diagnosis of lymphoma, and immunohistochemical staining plays an important role in the differential diagnosis of lymphoma. Ki-67, also known as the proliferation index, represents the proliferation index of tumour cells and is a protein present in the nucleus. It is generally used to determine the malignancy, prognosis, and sensitivity of tumours to chemotherapy drugs. Clinically, we have found that the majority of invasive lymphomas, such as DLBCL, have Ki-67 index values ranging from 70%-80%, while the Ki-67 index in Burkitt lymphoma is greater than 90%, and that in indolent lymphoma is generally less than 50%. Therefore, multiple studies have suggested that Ki-67 ≥ 30% is one of the factors contributing to poor prognosis in FL patients [ 21 , 22 ]. Our study revealed that a Ki-67 index ≥ 30% cannot predict PFS in advanced FL3A patients, which is different from the findings of previous reports. This may be because previous reports of FL included all pathological levels of FL. We found through the segmentation of Ki-67 and other methods that the expected 5-year PFS of advanced FL3A patients with 50% ≤ Ki-67 < 60% was significantly better than that of patients with Ki-67 < 50% or Ki-67 ≥ 60% (87.9% vs. 67.4%, P = 0.024), while multivariate analyses were not confirmed the result. The above results may require pathological review and pathological imaging for further validation. Conclusion In conclusion, we conducted a real-word study of FL3A at a single centre. We revealed that FL3A accounted for less than one-third of all FL and the number of patients diagnosed with FL3A was increased year by year. At diagnosis, most patients with FL3A were in advanced stage, and compared to patients with early FL3A, patients with advanced FL3A had much greater SUVmax, CRP, serum LDH and β2-microglobulin levels and lower haemoglobin and IgG levels. In real-word, most patients with advanced FL3A in low-tumor-load received therapy, majority with RCHOP regime. Our results indicated that SUVmax ≥ 15 was an independent poor prognostic factor affecting PFS in patients with advanced FL3A. In addition, Ki-67 index was also maybe related with prognosis, which need more research. Abbreviations FL Follicular lymphoma NHL non-Hodgkin's lymphoma FL3A Follicular lymphoma grade 3A OS Overall survival PFS Progression-free survival WHO World Health Organization GELF the French Groupe d’Etude des Lymphomes Folliculaires ORR Overall remission rate LDH Lactic dehydrogenase PET Positronemission tomography FDG 18F Fluorodeoxyglucose SUVmax Maximum standardized uptake value RCHOP Rituximab combined with cyclophosphamide, doxorubicin, vincristine, and prednisone Declarations Ethics approval and consent to participate This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the First Affiliated Hospital, College of Medicine, Zhejiang University. The requirement for informed consent was waived because of the anonymous nature of the data. Consent for publication Not applicable Availability of data and materials The data sets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contributions XY, GX, JJ, WY and HT contributed to the study conception and design. Material preparation and data collection were performed by YZ, YL, FX, CY, DZ, WX, JH, YL, LM, MY, WM and HM. Statistical analyses were performed by XL, JW, XZ and XZ. All authors contributed to interpretation of data. The first draft of the manuscript was written by XY, GX, JJ, WY and HT. all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank the patients and their families. References Al-Hamadani M, Habermann TM, Cerhan JR, Macon WR, Maurer MJ, Go RS. Non-Hodgkin lymphoma subtype distribution, geodemographic patterns, and survival in the US: A longitudinal analysis of the National Cancer Data Base from 1998 to 2011. Am J Hematol. 2015;90(9):790–5. https://doi.org/10.1002/ajh.24086 . Alaggio R, Amador C, Anagnostopoulos I, Attygalle AD, de Oliveira Araujo IB, Berti E et al. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms. Leukemia. 2022;36(7):1720-48. https://doi.org/10.1038/s41375-022-01620-2 . Campo E, Jaffe ES, Cook JR, Quintanilla-Martinez L, Swerdlow SH, Anderson KC, et al. 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A comparative analysis of prognostic factor models for follicular lymphoma based on a phase III trial of CHOP-rituximab versus CHOP + 131iodine–tositumomab. Clin Cancer Res. 2013;19(23):6624–32. https://doi.org/10.1158/1078-0432.CCR-13-1120 . Shustik J, Quinn M, Connors JM, Gascoyne RD, Skinnider B, Sehn LH. Follicular non-Hodgkin lymphoma grades 3A and 3B have a similar outcome and appear incurable with anthracycline-based therapy. Ann Oncol. 2011;22(5):1164–9. https://doi.org/10.1093/annonc/mdq574 . Wahlin BE, Yri OE, Kimby E, Holte H, Delabie J, Smeland EB, et al. Clinical significance of the WHO grades of follicular lymphoma in a population based cohort of 505 patients with long follow-up times. Br J Haematol. 2012;156(2):225–33. https://doi.org/10.1111/j.1365-2141.2011.08942.x . Pouyiourou M, Meyer A, Stroux A, Viardot A, La Rosée P, Maschmeyer G, et al. First-line treatment with R-CHOP or rituximab-bendamustine in patients with follicular lymphoma grade 3A-results of a retrospective analysis. Ann Hematol. 2020;99(12):2821–9. https://doi.org/10.1007/s00277-020-04171-7 . Naik A, Gooley T, Loeb K, Soma L, Smith SD, Gopal A, et al. The impact of histological grade on outcomes in follicular lymphoma: An analysis of patients in the SEER database in the context of evolving disease classification and treatment. Br J Haematol. 2022;199(5):696–706. https://doi.org/10.1111/bjh.18404 . Zha J, Chen Q, Ye J, Yu H, Yi S, Zheng Z, et al. Differences in clinical characteristics and outcomes between patients with grade 3a and grades 1–2 follicular lymphoma: a real-world multicenter study. Biomark Res. 2023;11(1):16. https://doi.org/10.1186/s40364-023-00462-z . Mondello P, Steiner N, Willenbacher W, Cerchione C, Nappi D, Mauro E, et al. Bendamustine plus rituximab versus R-CHOP as first-line treatment for patients with follicular lymphoma grade 3A: evidence from a multicenter, retrospective study. Oncologist. 2018;23(4):454–60. https://doi.org/10.1634/theoncologist.2017-0037 . Noy A, Schöder H, Gönen M, Weissler M, Ertelt K, Cohler C, et al. The majority of transformed lymphomas have high standardized uptake values (SUVs) on positronemission tomography (PET) scanning similar to diffuse large B-celllymphoma (DLBCL). Ann Oncol. 2009;20(3):508–12. https://doi.org/10.1093/annonc/mdn657 . Dupuis J, Berriolo-Riedinger A, Julian A, Brice P, Tychyj-Pinel C, Tilly H, et al. Impact of [18F]Fluorodeoxyglucose Positron Emission Tomography Response Evaluation in Patients With High-Tumor Burden Follicular Lymphoma Treated With Immunochemotherapy: A Prospective Study From the Groupe d'Etudes des Lymphomes de l'Adulte and GOELAMS. J Clin Oncol. 2012;30(35):4317–22. https://doi.org/10.1200/JCO.2012.43.0934 . Wang SA, Wang L, Hochberg EP, Muzikansky A, Harris NL, Hasserjian RP. Low histologic grade follicular lymphoma with high proliferation index: morphologic and clinical features. Am J Surg Pathol. 2005;29(11):1490–6. https://doi.org/10.1097/01.pas.0000172191.87176.3b . Koster A, Tromp HA, Raemaekers JM, Borm GF, Hebeda K, Mackenzie MA, et al. The prognostic significance of the intra-follicular tumor cell proliferative rate in follicular lymphoma. Haematologica. 2007;92(2):184–90. https://doi.org/10.3324/haematol.10384 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-4466497","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":307543392,"identity":"89c443dc-ac5d-4fde-b72c-bce0d5a9851b","order_by":0,"name":"Xingnong Ye","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xingnong","middleName":"","lastName":"Ye","suffix":""},{"id":307543393,"identity":"54969927-49cc-4d80-a8c9-b3d9371f7cc8","order_by":1,"name":"Gaixiang Xu","email":"","orcid":"","institution":"Zhejiang University School of 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11:21:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4466497/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4466497/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58169526,"identity":"2a91c7a2-49f0-4f91-9416-7d1fc33e075b","added_by":"auto","created_at":"2024-06-12 03:31:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47517,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of patient enrolled\u003c/p\u003e","description":"","filename":"OnlineFig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4466497/v1/3872da969cb26d4fe5091dfd.png"},{"id":58169528,"identity":"aa651c92-369d-45ea-a37e-4a9e246fbbe1","added_by":"auto","created_at":"2024-06-12 03:31:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41356,"visible":true,"origin":"","legend":"\u003cp\u003eNumbers of patients with newly diagnosed with follicular lymphoma grade 3A every year\u003c/p\u003e","description":"","filename":"OnlineFig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4466497/v1/26608ea041fc3b7a2db8b264.png"},{"id":58170899,"identity":"e6566736-fa11-4565-b8a4-d750e7f68a0d","added_by":"auto","created_at":"2024-06-12 03:39:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87110,"visible":true,"origin":"","legend":"\u003cp\u003eProgression-free survival (PFS) of patients with folicullar lymhoma grade 3A (FL3A). \u003cstrong\u003eA\u003c/strong\u003e The PFS compared between early FL3A and advanced FL3A. \u003cstrong\u003eB\u003c/strong\u003e The PFS of patients with advanced FL3A who received anti-CD20 monoclonal antibody maintenance treatment after remission or not. \u003cstrong\u003eC \u003c/strong\u003eThe PFS between the treatment group and watch-and-wait group in patients with advanced FL3A withlow-tumor-load according GELF criteria. \u003cstrong\u003eD \u003c/strong\u003eThe PFS of patients with advanced FL3A in different initial therapy regimes. \u003cstrong\u003eE\u003c/strong\u003e The PFS of patients with advanced FL3A compared between the R-CHOP group (including those in the R/G-CHOP and R/G-CHOP-like regimens) and non-R-CHOP group (those in the other regimens).\u003cstrong\u003e F \u003c/strong\u003eThe PFS of patients with advanced FL3A in different Ki-67 index.\u003c/p\u003e","description":"","filename":"OnlineFig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-4466497/v1/66df7b7810c71f26a40755d1.png"},{"id":68681865,"identity":"99d511d3-1289-4187-858a-960baead4564","added_by":"auto","created_at":"2024-11-11 03:47:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":908840,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4466497/v1/4e96820b-da81-4d7d-adfa-99cc921de7fc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Characteristics and Prognosis of Patients with Follicular Lymphoma Grade 3A: A real-world study in a single centre","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFollicular lymphoma (FL) is the most common subtype of indolent non-Hodgkin's lymphoma (NHL), accounting for approximately 22% of NHL cases [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The World Health Organization (WHO) pathological grading system of FL is based on the number of centroblasts per high-power field (HPF) of view, which is considered a clinical predictor of outcome. In the 2017 WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues, classic FL can be divided into three grades: FL grade 1\u0026ndash;2 (FL1-2) or low-grade FL, FL grade 3A (FL3A) and FL grade 3B (FL3B). However, in the 2022 WHO classification of haematolymphoid tumours (WHOHAEM5) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], pathological grading was abolished, and FL3B was separately classified as follicular large B-cell lymphoma (FLBL), while the International Consensus Classification (ICC) in 2022 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] retained the FL grading as described in the 2017 WHO classification. Diagnosis and therapy guidelines, such as the National Comprehensive Cancer Network (NCCN), are available for classic FL /low-grade FL, but there is no consensus on the optimal treatment for FL3A; moreover, treatment regimens need to be individualized.\u003c/p\u003e \u003cp\u003eFor patients with advanced (stage III-IV) FL, treatment is generally based on tumour load according to the French Groupe d\u0026rsquo;Etude des Lymphomes Folliculaires (GELF) established criteria [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Several prospective randomized controlled trials have not demonstrated a survival benefit of immediate treatment versus watch-and-wait (W\u0026amp;W) in low-tumour-load, asymptomatic patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Chemoimmunotherapy with anti-CD20 monoclonal antibodies (rituximab (R) or obinutuzumab (G)) is the current first-line treatment option for patients with FL. In a multicentre randomized StiL NHL1 phase III study [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the results showed that the BR regimen (bendamustine (B) in combination with rituximab) was superior to RCHOP (cyclophosphamide (C), doxorubicin (H), vincristine (O), and prednisone (P) in combination with rituximab) in terms of progression-free survival (PFS). At a median follow-up of 45 months, the median PFS of patients treated with BR and R-CHOP were 69 and 31 months, respectively (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The GALLIUM trial was a randomized controlled phase III clinical trial comparing the efficacy and safety of rituximab versus obinutuzumab in combination with chemotherapy (bendamustine, CHOP or COP) for the treatment of untreated advanced FL [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A total of 1202 patients were randomized 1:1 to receive combination chemotherapy with either obinutuzumab or rituximab, followed by maintenance therapy with the same antibody for up to 2 years in patients who responded to the treatment. At a median follow-up of 34.5 months, the obinutuzumab group had a longer PFS and lower risk of disease progression and recurrence than did the rituximab group, with predicted 3-year PFS rates of 80% and 73%, respectively. However, there was no difference in the overall remission rate (ORR) or overall survival (OS) between the two groups. The above studies included patients with FL1-2 and FL3A.\u003c/p\u003e \u003cp\u003eThe International Prognostic Index for Follicular Lymphoma (FLIPI) is the most commonly used in the prognostic evaluation of FL. FLIPI-1 is based on age, Ann Arbor stage and number of lymph node sites involved, hemoglobin level, and serum lactic dehydrogenase (LDH) level. FLIPI-2 is based on age, hemoglobin level, longest diameter of the largest involved lymph node, beta-2 microglobulin level, and bone marrow involvement. FLIPI-2 defines different risk groups within the subgroup of FL patients treated with rituximab-based regimens, with predicted 5-year PFS rates of 98%, 88%, and 77% for low-risk, intermediate-risk, and high-risk patients with FL (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thus, FLIPI-2 may be useful in assessing the prognosis of patients receiving aggressive rituximab-based regimens. A simpler prognostic model that includes only baseline serum β2-microglobulin and LDH levels is also available [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although these prognostic models can predict prognosis, no studies have shown that they can be used as a basis for treatment selection. Above studies also included patients with FL1-2 and FL3A.\u003c/p\u003e \u003cp\u003eBased on the above research background, we collected the clinical data of FL3A patients to analyse the correlation among baseline features, therapy regimens and prognosis. This study was approved by the Ethics Committee of the First Affiliated Hospital, College of Medicine, Zhejiang University.\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eWe performed a real-world study of patients who were newly diagnosed with FL between January 2013 and December 2022 at the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China. Adult patients diagnosed with FL3A according to the 2017 WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues were included. Patients with FL of grades 1\u0026ndash;2 and 3A in one specimen were also included. Patients with one or more of the following conditions were excluded from the data analysis: (1) patients with FL of coexisting grade 3A and 3B or diffuse large B-cell lymphoma (DLBCL) anywhere in one specimen; (2) individuals who had visited only once or had not been hospitalized in the haematology department; or (3) patients with no baseline clinical data in the hospital's electronic medical records.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eThe following data were collected from the hospital's electronic medical records system: entomological characteristics, pathological information, clinical characteristics, blood examinations at diagnosis, treatments, efficacy assessments and survival data. Basic characteristics including but not limited to: age, gender, comorbidity; \u003csup\u003e18F\u003c/sup\u003eFluorodeoxyglucose (FDG) positronemission tomography (PET) scan, computer tomography (CT) scan, color Doppler ultrasound examination; primary site, number of lymph node areas involved, extra-nodal involvement, bone marrow involvement; B-symptoms, tumor-related symptoms; white blood cell count (WBC), hemoglobin level (HB), platelet count (PLT); the levels of glutamic-pyruvic transaminase (ALT), glutamic oxaloacetic transaminase (AST), uric acid (UA), C-reactive protein (CRP), serum lactate dehydrogenase (LDH), β2 microglobulin (β2M), ferritin, Immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), and so on.\u003c/p\u003e \u003cp\u003ePatients with FL3A were divided into early (stage I and stage II) FL3A and advanced (stage III and stage IV) FL3A according to the Ann Arbor-Cotswolds staging criteria. Tumor load was evaluated according to the GELF criteria [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The efficacy was evaluated by the revised standards of the 2014 Lugano Conference, which were complete remission (CR), partial remission (PR), overall remission (OR), stable disease (SD), progressive disease (PD).\u003c/p\u003e \u003cp\u003ePFS was defined as the time from the date of diagnosis until disease relapse/progression or death. Overall survival (OS) was defined as the time from diagnosis to death from any cause. The last follow-up time for this study was December 31, 2023.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eCategorical variables are presented as values and percentages; continuous variables are presented as medians and ranges. For comparisons between groups, t tests and nonparametric tests were used for continuous variables, and chi-square tests were used for categorical variables. Variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in the univariate analysis were included in the multivariate analysis. P\u0026thinsp;\u0026le;\u0026thinsp;0.05 (2-sided) was considered significant. Statistical analysis was performed with SPSS software (version number: 26.0, SPSS, Inc., Chicago, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 853 patients with FL were admitted from 1st January 2013 to 31st December 2022, among whom 235 patients with FL3A accounted for 27.55% of all patients with FL. Twelve of the 235 patients with FL3A came to the hospital only once, and no detailed data were available. Finally, 223 patients with FL3A were enrolled in our study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The number of patients enrolled gradually increased as time goes on and 60 (26.9%) patients were diagnosed with FL3A in 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the 223 patients, 113 patients were male and 110 were female, with a male-to-female ratio close to 1:1, and the median age was 57 (24\u0026ndash;89) years. The median number of lymph nodes involved was 4 (0\u0026ndash;7), the median maximum diameter of the lymph nodes was 3cm (0.5-16.6cm), and extra-nodal lesions were most commonly located in the gastrointestinal tract, followed by the thyroid, pancreas, nasopharynx and kidney. The most common comorbidity was hypertension, followed by hepatitis B and autoimmune diseases. A total of 101 patients underwent PET scan before treatment, and the median maximum standardized uptake value (SUVmax) of FDG was 10.5 (3.3\u0026ndash;39.6).\u003c/p\u003e \u003cp\u003eAccording to ANN-Arbor staging, 24 patients had early FL3A, and 199 patients had advanced FL3A. Among patients with advanced FL3A, 93 patients (46.7%) had low tumour loads, and 106 patients (53.3%) had high tumour loads, according to the GELF criteria. Compared to patients with early FL3A, patients with advanced FL3A had much greater SUVmax, CRP, serum LDH and β2-microglobulin levels and lower haemoglobin and immunoglobulin G (IgG) levels, as described in 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\u003eBaseline clinical characteristics of follicular lymphoma grade 3A\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline clinical characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdvanced stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male:female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12:12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101:98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (43\u0026ndash;67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (24\u0026ndash;89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003csup\u003e18F\u003c/sup\u003eFluorodeoxyglucose metabolic maximum uptake value in PET scan (SUVmax)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.578\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.747\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eWhite blood cell count, WBC (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7624\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.1405\u0026thinsp;\u0026plusmn;\u0026thinsp;2.84149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139.67\u0026thinsp;\u0026plusmn;\u0026thinsp;22.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129.73\u0026thinsp;\u0026plusmn;\u0026thinsp;22.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count, PLT (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e217.42\u0026thinsp;\u0026plusmn;\u0026thinsp;52.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208.13\u0026thinsp;\u0026plusmn;\u0026thinsp;80.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlutamic-pyruvic transaminase, GPT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.26\u0026thinsp;\u0026plusmn;\u0026thinsp;19.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.04\u0026thinsp;\u0026plusmn;\u0026thinsp;13.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlutamic oxaloacetic transaminase, GOT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.70\u0026thinsp;\u0026plusmn;\u0026thinsp;11.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric acid, UA (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e313.39\u0026thinsp;\u0026plusmn;\u0026thinsp;54.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e329.42\u0026thinsp;\u0026plusmn;\u0026thinsp;96.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein, CRP (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7618\u0026thinsp;\u0026plusmn;\u0026thinsp;4.03218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.9886\u0026thinsp;\u0026plusmn;\u0026thinsp;42.11636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Lactic dehydrogenase, LDH (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e191.1\u0026thinsp;\u0026plusmn;\u0026thinsp;49.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e279.59\u0026thinsp;\u0026plusmn;\u0026thinsp;352.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eFerritin (ug/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e210\u0026thinsp;\u0026plusmn;\u0026thinsp;204.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e358.35\u0026thinsp;\u0026plusmn;\u0026thinsp;849.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ2-microglobulin (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1710.86\u0026thinsp;\u0026plusmn;\u0026thinsp;556.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2486.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2463.970\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin A, IgA (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e204.18\u0026thinsp;\u0026plusmn;\u0026thinsp;90.691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187.55\u0026thinsp;\u0026plusmn;\u0026thinsp;105.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin M, IgM (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105.3\u0026thinsp;\u0026plusmn;\u0026thinsp;74.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.6\u0026thinsp;\u0026plusmn;\u0026thinsp;197.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin G, IgG (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1361.88\u0026thinsp;\u0026plusmn;\u0026thinsp;323.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1087.68\u0026thinsp;\u0026plusmn;\u0026thinsp;531.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi\u0026minus;67 index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.61\u0026thinsp;\u0026plusmn;\u0026thinsp;14.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.15\u0026thinsp;\u0026plusmn;\u0026thinsp;15.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTherapy regimens and efficacy\u003c/h2\u003e \u003cp\u003eA total of 192 patients (86.1%) received systemic therapy. The most common treatment regimens were anti-CD20 monoclonal antibodies (rituximab (R) or otuzumab (G)) combined with CHOP (cyclophosphamide (C), doxorubicin/epirubicin/doxorubicin liposomes (H), vincristine (O), prednisone (P)) or a CHOP-like regimen (e.g., COP, CEOP (COP combined with etoposide (E)), CHOPE, etc.) in 61.8% of patients. Other therapy regimens included R/G monotherapy, R2 (rituximab combined with lenalidomide), BR (rituximab combined with bendamustine), and GB (otuzumab combined with bendamustine) regimens, and one patient received chemo-free regimen (rituximab, lenalidomide and ibrutinib). Only 5 patients were not treated with rituximab or otuzumab.\u003c/p\u003e \u003cp\u003eOnly 24 (25.8%) patients with advanced FL3A with low-tumor-load according to the GELF criteria were treated with watch-and-wait. A total of 175 patients with advanced FL3A received systemic therapy, among witch 62.3% of patients received R/G combined with CHOP/CHOP-like regimens. Of the patients who achieved a PR or CR, 62.9% received maintenance therapy with the same anti-CD20 monoclonal antibody.\u003c/p\u003e \u003cp\u003eAmong the 175 patients with advanced FL3A disease who received systemic therapy, two patients died early (less than 1 month after diagnosis). Thirteen patients did not complete 4 cycles of therapy at our institution or whose efficacy data were unavailable, and overall survival data were only obtained by telephone follow-up. A total of 160 patients with advanced FL3A were available for efficacy assessment, and efficacy was assessed as SD or PD in only 6 patients, with an OR rate (ORR) of 96.3% during the initial therapy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSurvival analysis\u003c/h2\u003e \u003cp\u003eWith a median follow-up time of 41 months, 20 patients with FL3A were lost to follow-up, including 4 patients with available PFS data. Five patients with FL3A were died, including two early deaths. The expected 5-year overall survival (OS) was 97.4%, and the median OS was not reached. A total of 45 patients with FL3A experienced PD, and one patient experienced PD 5 times. The expected 2-year and 5-year PFS rates of patients with FL3A were 87% and 73%, with a median PFS of 117 months. During the follow-up period, only one patient with early FL3A expression experienced PD at 25 months, with a expected 2-year PFS of 100%, and the expected 2-year PFS of advanced FL3A patients was 86%, respectively (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe performed univariate and multivariate analyses with Cox proportional hazard models to identify baseline features and therapeutic regimens associated with PFS in patients with advanced FL3A, and the univariate analyses results are described in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. It was shown that SUVmax and platelet count at diagnosis were both associated with PFS, while there was no relationship between hemoglobin level and PFS. Ki-67 index less than 50 or more than 60 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF), and WBC under 5.0\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L were both related with poor PFS in patients with advanced FL3A. According to the results of univariate analyses results, we put SUVmax, Ki-67 index, platelet count, WBC, LDH, IgA and IgM together in multivariate analyses with Cox proportional hazard models. Multivariate analyses showed that only the SUVmax was the independent prognostic factor and SUVmax more than 15 related with poor PFS in patients with advanced FL3A.\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\u003eThe univariate analyses with Cox proportional hazard models of prognostic factors for progress-free survival (PFS) in patients with advanced FL3A\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR(%95 CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex(male vs female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.887(0.487\u0026ndash;1.616)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.017 (0.993\u0026ndash;1.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;60y vs\u0026thinsp;\u0026ge;\u0026thinsp;60y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.083(0.597\u0026ndash;1.965)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003csup\u003e18F\u003c/sup\u003eFluorodeoxyglucose metabolic maximum uptake value in PET scan (SUVmax)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.140(1.057\u0026ndash;1.231)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\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 \u003cp\u003e(\u0026lt;13.0 vs \u0026ge;13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.748(0.773\u0026ndash;0.9766)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;14.0 vs \u0026ge;14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.476(0.977\u0026ndash;12.361)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;15.0 vs \u0026ge;15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4.885(1.356\u0026ndash;17.589)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell count, WBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.982 (0.887\u0026ndash;1.086)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;5.0\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L vs\u0026thinsp;\u0026ge;\u0026thinsp;5.0\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.550(0.303\u0026ndash;0.997)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.049\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.995 (0.983\u0026ndash;1.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;120g/L vs \u0026ge;120g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.940(0.473\u0026ndash;1.866)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count, PLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.995 (0.991-1.000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;100 \u0026times;10\u003csup\u003e9\u003c/sup\u003e/L vs\u0026thinsp;\u0026ge;\u0026thinsp;100\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.408(0.145\u0026ndash;1.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Lactic dehydrogenase, LDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000 (1.000-1.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;210U/L vs \u0026ge;210U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.020(1.099\u0026ndash;3.826)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ2-microglobulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000 (1.000\u0026ndash;1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFerritin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.001 (0.998\u0026ndash;1.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein, CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.002 (0.995\u0026ndash;1.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin A, IgA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.997 (0.993\u0026ndash;1.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;178mg/dl vs \u0026ge;178mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.488(0.250\u0026ndash;0.956)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.036\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin M, IgM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000 (0.997\u0026ndash;1.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;100mg/dl vs \u0026ge;100mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.285(0.88\u0026ndash;0.928)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin G, IgG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.999 (0.999-1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;860mg/dl vs \u0026ge;860mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.943(0.481\u0026ndash;1.852)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi-67 index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.998 (0.978\u0026ndash;1.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u0026lt;50% or \u0026ge;\u0026thinsp;60% vs\u0026thinsp;\u0026ge;\u0026thinsp;50% and \u0026lt;\u0026thinsp;60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.354(0.138\u0026ndash;0.907)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor-load\u003c/p\u003e \u003cp\u003e(low-tumor-load vs high-tumor-load)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.391(0.762\u0026ndash;2.542)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial therapy regimes\u003c/p\u003e \u003cp\u003e(based with anti-CD20 monoclonal antibody)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.273(0.034\u0026ndash;2.184)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined with lenalidomide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.439(0.160\u0026ndash;1.200)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined with bendamustine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.512(0.163\u0026ndash;1.607)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined with CHOP or CHOP-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.244(0.111\u0026ndash;0.535)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCHOP or RCHOP-like vs others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.381(1.305\u0026ndash;4.344)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaintainced therapy with anti-CD20 monoclonal antibody (yes vs no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.302(0.157\u0026ndash;0.581)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.000\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\u003eSignificant differences were also found between different initial therapy regimens. The PFS of patients in the R-CHOP group (including those in the R/G-CHOP and R/G-CHOP-like regimens) was more favourable than that of patients in the non-R-CHOP group (those in the other regimens), with predicted 5-year PFS rates of 78% and 51.7%, respectively (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). The PFS of patients who received anti-CD20 monoclonal antibody maintenance treatment after remission was more favourable than that of patients who did not receive maintenance treatment (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). There was no statistically significant difference in PFS between the treatment group and watch-and-wait group in patients with advanced FL3A with low-tumor-load according GELF criteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eFL3A accounted for 27.55% of the FL in our study, which was significantly lower than the proportion of FL1-2, which is consistent with other published research results [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Patients with FL have a good prognosis, with longer PFS and OS after chemotherapy and immunotherapy. Previous studies have shown that FL3A shares similarities in histological characteristics with FL1-2, but there are differences in actual survival, and there is no consensus on the recurrence and prognosis of FL3A and FL1-2 patients. A study conducted by Naik et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], based on surveillance, epidemiology, and end results (SEER) data, compared the impact of histological grade on treatment outcomes and prognosis. A total of 39925 patients with FL were enrolled. This study revealed that FL3 (FL3A and FL3B) is more invasive and has a worse prognosis than FL1-2, but FL3B patients were not excluded from this study; therefore, the results cannot be fully attributed to FL3A. A multicentre study in China showed that FL3A patients had significantly shorter PFS than FL1-2 patients, but there was no significant difference in OS between them [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This may be related to differences in clinical and pathological features at the time of diagnosis. Montello et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] conducted a long-term comparative follow-up study on 132 FL3A patients who received R-CHOP and BR treatment. The median follow-up time was 14.8 years in the R-CHOP group and 15.2 years in the BR group. There was no significant difference in OS between the two groups, and the median OS was not reached. The median PFS of the BR group was significantly longer than that of the RCHOP group (15 years vs. 11.7 years, respectively). Our study revealed that the median follow-up time was 41 months, the median OS was not reached, and the median PFS was 117 months, with an expected 2-year PFS of 87% and a 5-year PFS of 73%.\u003c/p\u003e \u003cp\u003eEarly FL3A patients had better PFS than advanced FL3A patients. We investigated the impacts of initial therapeutic regimens on PFS in patients with advanced FL3A. According to the GELF criteria and guidelines, advanced FL patients with low-tumour-load can be treated with watch-and-wait method. Our analysis revealed the same results. However, in our study, the most of patients with low-tumour-load received systematic treatment, and only 25.8% of patients received watch-and-wait strategy. This research result needs to be further confirmed by expanding the sample size and conducting randomized controlled studies. The initial treatment for advanced FL3A is anti-CD20 monoclonal antibody-based chemoimmunotherapy. Patients who achieved PR or CR then received maintenance treatment with the same anti-CD20 antibodies. In our study, 61.9% of patients with advanced FL3A mutations received R-CHOP or R-CHOP-like regimens, while 38.1% of patients received other treatment regimens (such as BR, R2, etc.). The 5-year PFS of patients in the RCHOP group was significantly longer than that of patients in the non-RCHOP group (78% vs. 51.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This was inconsistent with previous reports due to much fewer patients received BR regime compared with R-CHOP regime. Patients who received maintenance therapy with anti-CD20 monoclonal antibodies had better PFS than patients who did not receive maintenance therapy.\u003c/p\u003e \u003cp\u003eWe also conducted exploratory research on the correlation between clinical and pathological features and the prognosis of patients with advanced FL3A. We found that the SUVmax level was independent prognostic factor for PFS, and the critical points obtained are different from those reported in previous studies. Univariate analyses with Cox proportional hazard models reveled that Ki67 index and platelet count were both related with PFS, however, multivariate analyses were not indicated positive results.\u003c/p\u003e \u003cp\u003ePET scan is one of the most commonly used methods for evaluating the condition of indolent lymphoma. Previous reports have shown that FDG uptake can predict the possibility of histological transformation to DLBCL. In a retrospective study [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], an SUVmax\u0026thinsp;\u0026gt;\u0026thinsp;10 or \u0026gt;\u0026thinsp;13 was associated with high specificity in detecting histological transformation. Dupuis et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] conducted a prospective study on the treatment of advanced high-burden FL tumours with a 6-cycle R-CHOP regimen. Mid-induction PET scan evaluation was performed after 4 cycles, and end of induction (EOI) PET scan evaluation was performed after 6 cycles. The 2-year PFS of the mid-induction PET-negative group was significantly greater than that of the PET-positive group (86% vs. 61%, P\u0026thinsp;=\u0026thinsp;0.0046), but there was no significant difference in OS. The 2-year PFS and OS of the EOI PET-negative group were significantly greater than those of the PET-positive group (2-year PFS: 87% vs. 51%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 2-year OS: 100% vs. 88%, P\u0026thinsp;=\u0026thinsp;0.013). However, there is no research showing the relationship between the baseline PET scan FDG metabolism SUVmax and prognosis. In our study, 101 patients underwent baseline PET scan, with a median SUVmax of 10.5 (3.3\u0026ndash;39.6). In the analysis of prognostic factors, we found that the PFS of advanced FL3A patients with an SUVmax\u0026thinsp;\u0026ge;\u0026thinsp;15 was much poorer than that of patients with an SUVmax\u0026thinsp;\u0026lt;\u0026thinsp;15 (5-year PFS, 59.9% vs. 74.6%, P\u0026thinsp;=\u0026thinsp;0.015). Based on previous reports, we speculate that patients with an SUVmax\u0026thinsp;\u0026ge;\u0026thinsp;15 have a tendency towards histological transformation, and their prognosis is relatively poor. Based on previous relevant studies, we believe that it is necessary to conduct further prospective studies to determine the impact of PET scans on prognosis at baseline and after induction therapy to play a role in induction therapy and subsequent treatments. At the same time, we suggest conducting another pathological biopsy on patients with a high SUVmax to determine whether there is a possibility of histological transformation.\u003c/p\u003e \u003cp\u003ePathology is the gold standard for the diagnosis of lymphoma, and immunohistochemical staining plays an important role in the differential diagnosis of lymphoma. Ki-67, also known as the proliferation index, represents the proliferation index of tumour cells and is a protein present in the nucleus. It is generally used to determine the malignancy, prognosis, and sensitivity of tumours to chemotherapy drugs. Clinically, we have found that the majority of invasive lymphomas, such as DLBCL, have Ki-67 index values ranging from 70%-80%, while the Ki-67 index in Burkitt lymphoma is greater than 90%, and that in indolent lymphoma is generally less than 50%. Therefore, multiple studies have suggested that Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;30% is one of the factors contributing to poor prognosis in FL patients [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Our study revealed that a Ki-67 index\u0026thinsp;\u0026ge;\u0026thinsp;30% cannot predict PFS in advanced FL3A patients, which is different from the findings of previous reports. This may be because previous reports of FL included all pathological levels of FL. We found through the segmentation of Ki-67 and other methods that the expected 5-year PFS of advanced FL3A patients with 50% \u0026le; Ki-67\u0026thinsp;\u0026lt;\u0026thinsp;60% was significantly better than that of patients with Ki-67\u0026thinsp;\u0026lt;\u0026thinsp;50% or Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;60% (87.9% vs. 67.4%, P\u0026thinsp;=\u0026thinsp;0.024), while multivariate analyses were not confirmed the result. The above results may require pathological review and pathological imaging for further validation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, we conducted a real-word study of FL3A at a single centre. We revealed that FL3A accounted for less than one-third of all FL and the number of patients diagnosed with FL3A was increased year by year. At diagnosis, most patients with FL3A were in advanced stage, and compared to patients with early FL3A, patients with advanced FL3A had much greater SUVmax, CRP, serum LDH and β2-microglobulin levels and lower haemoglobin and IgG levels. In real-word, most patients with advanced FL3A in low-tumor-load received therapy, majority with RCHOP regime. Our results indicated that SUVmax\u0026thinsp;\u0026ge;\u0026thinsp;15 was an independent poor prognostic factor affecting PFS in patients with advanced FL3A. In addition, Ki-67 index was also maybe related with prognosis, which need more research.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFL\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFollicular lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNHL\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-Hodgkin's lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFL3A\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFollicular lymphoma grade 3A\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePFS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgression-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWHO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGELF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe French Groupe d\u0026rsquo;Etude des Lymphomes Folliculaires\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eORR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall remission rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLDH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLactic dehydrogenase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePET\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePositronemission tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFDG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003csup\u003e18F\u003c/sup\u003eFluorodeoxyglucose\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSUVmax\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximum standardized uptake value\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRCHOP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRituximab combined with cyclophosphamide, doxorubicin, vincristine, and prednisone\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the First Affiliated Hospital, College of Medicine, Zhejiang University. The requirement for informed consent was waived because of the anonymous nature of the data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data sets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXY, GX, JJ, WY and HT contributed to the study conception and design. Material preparation and data collection were performed by YZ, YL, FX, CY, DZ, WX, JH, YL, LM, MY, WM and HM. Statistical analyses were performed by XL, JW, XZ and XZ. All authors contributed to interpretation of data. The first draft of the manuscript was written by XY, GX, JJ, WY and HT. all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the patients and their families.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAl-Hamadani M, Habermann TM, Cerhan JR, Macon WR, Maurer MJ, Go RS. Non-Hodgkin lymphoma subtype distribution, geodemographic patterns, and survival in the US: A longitudinal analysis of the National Cancer Data Base from 1998 to 2011. 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Haematologica. 2007;92(2):184\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3324/haematol.10384\u003c/span\u003e\u003cspan address=\"10.3324/haematol.10384\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \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":"follicular lymphoma, advanced FL3A, maximum standardized uptake value (SUVmax) Ki-67, progress-free survival (PFS)","lastPublishedDoi":"10.21203/rs.3.rs-4466497/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4466497/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003ePurpose\u003c/b\u003e Follicular lymphoma (FL) is common subtype of indolent non-Hodgkin's lymphoma (NHL). However, there is no consensus on the management of FL grade 3A (FL3A).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e We performed a real-world study of newly diagnosed FL patients from January 2013 to December 2022. we collected the clinical data of FL3A patients to analyse the correlation among baseline features, therapy regimens and prognosis. The data were collected from the hospital's electronic medical records system.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e A total of 223 patients with FL3A were enrolled. With a median follow-up of 41 months, the expected 5-year overall survival (OS) was 97.4% and the 5-year progression-free survival (PFS) was 73%. In real-word, most patients with advanced FL3A in low-tumor-load received therapy, majority with RCHOP regimen (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone). Patients with advanced FL3A treated with RCHOP regimen and maintenance therapy had better PFS. There was no significant difference in PFS between the treatment group and watch-and-wait group in patients with low-tumor-load. The univariate analyses indicated that the maximum \u003csup\u003e18F\u003c/sup\u003eFluorodeoxyglucose uptake in PET (SUVmax), Ki-67 index, platelet count were related to prognosis. Multivariate analyses showed that only SUVmax was the independent prognostic factor and SUVmax\u0026thinsp;\u0026ge;\u0026thinsp;15 related with poor PFS.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e FL3A patients have a long survival, with a 5-year PFS of 73%. In real-world, most patients with advanced FL3A in low-tumor-load received therapy. Multivariate analyses indicated that SUVmax\u0026thinsp;\u0026ge;\u0026thinsp;15 was an independent poor prognostic factor affecting PFS in patients with advanced FL3A. In addition, Ki-67 index was also maybe related with prognosis.\u003c/p\u003e","manuscriptTitle":"Clinical Characteristics and Prognosis of Patients with Follicular Lymphoma Grade 3A: A real-world study in a single centre","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-12 03:31:30","doi":"10.21203/rs.3.rs-4466497/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":"4da7fbcc-c518-4d47-88f7-d6865acf5abb","owner":[],"postedDate":"June 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-11T03:39:15+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-12 03:31:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4466497","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4466497","identity":"rs-4466497","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}