Programmed death-1 inhibitors as treatment for other subtypes of lymphomas not recommended in the guidelines: Real-world data from a single center in China

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It is unknown how effective are PD-1 inhibitors used for other subtypes not recommended by the guidelines. We conducted a retrospective study in a real-world setting to evaluate efficacy of PD-1 inhibitors for other subtypes not recommended by the guidelines and discuss the potential biomarkers of treatment outcome. We found that the efficacy in some subtypes seems all right, especially in PCNSL. And the kinetics of Neutrophil to Lymphocyte Ratio and Lactate dehydrogenase may indicate clinical outcomes. Thus, PD-1 inhibitor is a promising choice for lymphoma patients. Further screening and monitoring of patients may bring more clinical benefits. PD-1 inhibitor real-world study hyperprogressive disease lymphoma prognosis Figures Figure 1 Figure 2 Figure 3 Introduction Lymphoma includes a variety of malignancies with different histopathological features, molecular characteristics, and clinical course despite arising from a common origin, the lymphatic tissues. Lymphoma is categorized into Hodgkin’s lymphoma (HL) and non-Hodgkin’s lymphoma (NHL) ( 1 , 2 ). Although the curative effect of standard treatment in some subtypes was satisfactory, the overall treatment outcome of other or relapsed patients was unfavorable and dismal ( 3 – 5 ). Therefore, new salvage therapies are needed to improve this situation. Programmed death-1 (PD‐1) inhibitors are effective against classic Hodgkin’s lymphoma (CHL) ( 6 ), primary mediastinal large B-cell lymphoma (PMBCL), and natural killer/T-cell lymphoma (NK/TCL) ( 7 , 8 ), which have been included in the treatment guidelines ( 9 , 10 ). However, PD‐1 inhibitors are not recommended for other subtypes of lymphomas, such as anaplastic large cell lymphoma (ALCL), diffuse large B-cell lymphoma (DLBCL), and peripheral T-cell lymphoma non-specificity (PTCL-nos). Many clinical trials are underway to investigate the efficacy of PD-1 inhibitors in other lymphoma subtypes not recommended in the treatment guidelines. Although the existing clinical trials have employed strict enrollment criteria to reduce bias, they may not entirely mirror the real-world clinical situation. Therefore, we retrospectively analyzed the efficacy of PD‐1 inhibitors in other lymphoma subtypes not recommended in the guidelines in a real-world setting. We aimed to evaluate the rates of response to PD-1 inhibitors and identify the potential biomarkers of treatment outcomes. We also explored the incidence of hyperprogressive disease (HPD) and cytokine release syndrome (CRS) induced by PD-1 inhibitor treatment ( 11 ). To the best of our knowledge, this study is the first to report the HPD and CRS phenomenon in lymphoma patients in a real-world setting. Materials and methods Study population Data of lymphoma patients treated with PD-1 inhibitors between January 2016 and January 2022 at the First Affiliated Hospital of Zhengzhou University were retrospectively collected. The inclusion criteria were as follows: (i) treatment with either PD-1 inhibitors alone or combination therapy; (ii) histologically confirmed diagnosis of lymphoma (except CHL, PMBCL, and NK/TCL); (iii) having undergone at least two cycles of PD-1 inhibitor therapy; and (iv) available computed tomography/magnetic resonance imaging information at three time points: before baseline (when previous therapy was initiated/no therapy was provided), at baseline (before the initiation of PD-1 inhibitor treatment), and at initial evaluation following the initiation of PD-1 inhibitor therapy. The patients were followed up until October 31, 2021 by phone interview, email, or review of medical records. Assessment The data were gathered and analyzed based on the Revised Response Criteria for Malignant Lymphomas (2014 Lugano classification) ( 12 ). The responses were classified as progressive disease (PD), stable disease (SD), partial response (PR), and complete response (CR). Primary study outcome measurements were overall survival (OS) and time-to‐treatment failure (TTF). The CR rate (CRR), objective response rate (ORR), disease control response rate (DCR), and progression-free survival (PFS) were also evaluated. TTF was defined as the time from the first administration of PD-1 inhibitors to treatment failure ( 13 ). OS was defined as the interval from the first administration of PD-1 inhibitors to death or the end of last follow-up. PFS was defined as the interval from the date of the first administration of PD-1 inhibitors to PD or death due from any cause. ORR was defined as the proportion of patients who achieved CR or PR. DCR was defined as the proportion of patients who achieved CR, PR, or SD. To diagnose HPD, the following parameters were considered: ( 1 ) a TTF of 50% after the first cycle of PD-1 inhibitor therapy, ( 3 ) a tumor growth rate of > 100% compared with that at pre-therapy, ( 4 ) appearance of new lesions between baseline and at initial imaging evaluation, and ( 5 ) worsening of clinical condition, evidenced by an Eastern Cooperative Oncology Group performance status (ECOG-PS) score of 2 during the first 2 months of immunotherapy. Patients who fulfilled at least three of these criteria were considered to have experienced HPD ( 14 – 17 ). Statistical analysis The patients’ characteristics were analyzed using a descriptive analysis. A Cox proportional hazard regression model was used to identify the independent factors influencing OS. Logistic regression models were used to identify the predictors of HPD. The cutoff values of lactate dehydrogenase levels at initial evaluation after initiation of PD-1 inhibitor therapy (LDH2) and the specific value of neutrophil-to-lymphocyte ratio before and after administration of PD-1 inhibitors (ΔNLR) were identified using the receiver operating characteristic (ROC) curve. The OS, PFS, and TTF were calculated using the Kaplan–Meier method, and the groups were compared using the log-rank test. All statistical analyses were performed using the R software, version 3.5.3, or GraphPad Prism, version 8.0. A P-value of < 0.05 was considered significant. Results Patients’ characteristics Based on the inclusion and exclusion criteria, 51 patients were selected for the study, including 10 with ALCL, 15 with PTCL-nos, 10 with primary central nervous system lymphoma (PCNSL), and 16 with DLBCL. Most patients (90.2%) tested negative for Epstein-Barr virus (EBV). The patients previously received a median of 1 regimen prior to the initiation of PD-1 inhibitor therapy. Two patients had unconfirmed CR status when PD-1 inhibitor treatment was started, while the remaining patients had active disease. Furthermore, 10 patients received PD-1 inhibitors alone, while the others received combination therapy. Two patients discontinued treatment due to the occurrence of PD-1 inhibitor-related adverse events (AEs), including one with serious pancreatitis and one with secondary interstitial pneumonia. The patients’ characteristics are summarized in Table S1 . Evaluation of efficacy The two patients who had unconfirmed CR status were not included in the evaluation of treatment efficacy. The follow-up evaluation showed that these two patients achieved CR after receiving consolidation therapy with PD-1 inhibitors. As for the rest of the patients, 13 (26.5%) achieved CR, 17 (34.7%) achieved PR, 10 (20.4%) showed SD, and 9 (18.4%) had PD or HPD. The ORR and DCR were 61.2% and 81.9%, respectively (Table I). Survival analysis showed that the median OS, TTF, and PFS were 23.9, 18.8, and 6.3 months, respectively, in all patients (Fig. 1 A–C). In the ALCL subgroup, the median OS, PFS, and TTF were 20.2, 3.8, and 3.6 months, respectively. Three patients achieved CR, and one of them was treated with PD-1 inhibitors alone. Four patients showed progression after PD-1 inhibitor therapy, including two HPD patients. For PTCL-nos patients, the median OS, PFS, and TTF were 23.9, 18.5, and 4.8 months, respectively. Two patients achieved CR. Some patients experienced PD after a short-term control of the disease. However, none of them developed HPD. For the DLBCL subtype, the median OS, PFS, and TTF were 29.1, 25.9, and 11.8 months, and the CRR and ORR were 26.7% and 60.0%, respectively (Table 1 ). Two patients showed rapid progression of disease after PD-1 inhibitor administration. In the PCNSL group, PD-1 inhibitors were highly effective. The median TTF was 8.9 months, while the median OS and PFS were not reached (Fig. 1 D–F). Overall, 40.0% of the patients were cured, and the ORR was 70.0%. Details of each patient for each subtype are shown in Fig. 2 . Table 1 Clinical Activity in PD-1 Treated Patients NOTE:“1”represents before PD-1 inhibitors therapy, “2”represents at first evaluation after PD-1 inhibitors therapy.HR: Hazard ratio; IPI: IPI score; NLR: Neutrophil to Lymphocyte Ratio; LDH: Lactate dehydrogenase; A/G: ratio of albumin to globulin; ΔNLR: the specific value of NLR before and after PD-1 inhibitors therapy. All patients (n = 49) ALCL (n = 9) PTCL (n = 15) PCNSL (n = 10) DLBCL (n = 15) Best response CR/CRu 13(26.5%) 3 (33.3%) 2(13.3%) 4(40.0%) 4(26.7%) PR 17(34.7%) 1(11.1%) 8(53.3%) 3(30.0%) 5(33.3%) SD 10(20.4%) 3(33.3%) 3(20.0%) 2(20.0%) 2(13.3%) PD 5(10.2%) 0 2(13.3%) 1(10.0%) 2(13.3%) HPD 4(8.2%) 2(22.2%) 0 0 2(13.3%) ORR(CR + PR) 30(61.2%) 4(44.4%) 10(66.7%) 7(70.0%) 9(60.0%) DCR(CR + PR + SD) 40(81.6%) 7(77.8%) 13(86.7%) 9(90.0%) 11(73.3%) OS, median(m) 23.9 20.2 23.9 NR 17.6 PFS, median(m) 18.8 3.8 18.5 NR 26.1 TTF, median(m) 6.3 3.6 4.8 8.9 4.4 Clinical prognostic factors We evaluated the association between the clinical variables and OS using univariate and multivariate analyses (Table 2 ). The specific value of ΔNLR was an independent risk factor for OS, which was driven by an increase in the neutrophil count and a reduction in the lymphocyte count. ROC curve analyses revealed that the optimal cutoff point of ΔNLR for mortality was > 1.78 (Fig. 3 A). The OS in patients with NLR increased by > 1.78 (Fig. 3 B). Table 2 Univariate and multivariable analyses for overall survival(n = 51) Univariate analysis Multivariate analysis HR(95CI%) P value HR(95CI%) P value CR or PR 5.61(1.54–20.4) 0.01 4.84(0.30-77.39) 0.27 EBER 0.65 (0.14–2.94) 0.57 0.58(0.02–21.10) 0.77 Stage 5.57 (1.22–25.41) 0.03 23.41(0.73-749.18) 0.08 IPI 1.57 (0.42–5.89) 0.51 age 1.03(0.23–4.67) 0.97 Bulky disease (> 5 cm) 6.12 (1.72–21.78) 0.01 0.03(0-2.35) 0.11 B symptom 3.92(1.05–14.68) 0.04 5.74 (0.28-119.65) 0.26 ECOG status 3.68 (1.75–7.74) 0.01 11.56 (0.58-232.11) 0.11 Radiotherapy 0.37(0.08–1.72) 0.20 ASCT 0 (0-Inf) 0.99 Lines of previous regimen 1.09(0.70–1.69) 0.70 NLR1 1.07 (0.98–1.16) 0.12 β2-microglobulin1 0.98 (0.85–1.14) 0.84 LDH1 1.00 (0.99–1.01) 0.45 A/G1 1.24 (0.15–10.06) 0.84 NLR2 1.07 (1.01–1.14) 0.02 0.62 (0.32–1.24) 0.18 β2-microglobulin2 1.42 (1.09–1.85) 0.01 1.73(0.92–3.25) 0.09 LDH2 1.01 (1.01–1.02) 0.00 1.01 (0.99–1.03 0.28 A/G2 0.30 (0.06–1.51) 0.14 ΔNLR 1.39(1.14–1.70) 0.01 5.47(1.09–27.45) 0.04 HPD phenomenon Four patients (7.8%) experienced HPD, including two with ALCL and two with DLBCL. All patients met the diagnostic criteria for HPD, and three patients were confirmed to have HPD based on the results of pathological examination. Only one patient with ALCL received PD-1 inhibitor alone, while the others received combination therapy (including chemotherapy and molecular targeted therapy). We investigated the possible links between HPD and clinical variables by conducting univariate and multivariate analyses; the LDH level at the initial evaluation after the administration of PD-1 inhibitors was correlated with HPD (Table S2 ). ROC curve analyses revealed that the optimal cutoff point was 225.5 U/L (Figure S1 ). Three patients received chemotherapy as salvage therapy following the occurrence of HPD induced by immunotherapy, but the treatment was not effective. The median OS time was only 2 months after the hyperprogression of disease caused by PD-1 inhibitor therapy. One patient received chimeric antigen receptor T-cell (CAR-T) therapy after experiencing HPD and achieved CR, with no tumor burden. The radiological images are shown in Fig. 3 D–F. A significant correlation was found between HPD and OS, and the clinical outcome was a worse in patients with HPD (median OS: 5.5 months) compared with that in patients with non-HPD (median OS: 24.0 months) (Fig. 3 C, Table 3 ). Table 3 the treatment information of HPD patients(n = 49) Patient No Subtype Age (yr) Immunotherapy regimens Post HPD Therapy TTF (m) State OS after HPD(m) 1 DLBCL 28 Monotherapy CAR-T therapy 1.3 Surviving 2 DLBCL 66 Combination with Ibrutinib and Thalidomide Expectant treatment 0.8 Dead 2.3 3 ALCL 62 Combination with Chidamide, Lenalidomide and Gemcitabine Hyper CVAD 0.8 Dead 6.3 4 ALCL 47 Combination with Chidamide, Lenalidomide and Gemcitabine GDPT 1.7 Dead 1.0 NOTE: GDPT: gemcitabine + cisplatin + prednisone + thalidomide; Hyper CVAD: fractionated cyclophosphamide + vincristine + doxorubicin + dexamethasone. Discussion In recent years, PD-1 inhibitors have been used for antitumor treatment. It plays an antitumor role by blocking the binding of PD-ligand 1 (PD-L1) and PD-1, thus inhibiting the immunosuppressive signal mediated by PD-1 and activating the body’s own immune response system. Increasing evidence show its efficacy in some lymphoma subtypes, especially in CHL, PMBCL, and NK/TCL. However, its efficacy in other subtypes has not been clearly clarified and needs to be explored. Shi et al. reported the objective response of PD-1 antibody in relapse/refractory PTCL (including PTCL-nos, ALCL, NK/TCL, and other subtypes), which had an ORR of 40.4% and CCR of 14.6% ( 18 ). Alexander et al. showed that the ORRs in refractory/relapse follicular lymphoma and DLBCL were 40% (CR: 10%) and 36% (CR: 9%), respectively ( 19 , 20 ). The overall result was unsatisfactory but intriguing. However, the clinical trials employed strict enrollment criteria to avoid bias, which does not reflect the situation of the actual clinical practice. Our study analyzed the efficacy of PD-1 inhibitors in different lymphoma subtypes not recommended by guidelines in a real-world setting. Four subtypes were examined in our studies: ALCL, PTCL, PCNSL, and DLBCL. None of them were recommended for PD-1 inhibitor therapy based on existing guidelines. The ORR of PCNSL (70.0%, 7/10) was higher than that of PTCL (66.7%, 7/15), DLBCL (60.0%, 9/15), and ALCL (44.4%, 4/9). The CRR of ALCL (33.3%, 3/9) and PCNSL (40.0%, 4/10) was better than that of DLBCL (26.7%, 4/15) or PTCL (13.3%, 2/15). CR was achieved in several patients of all subtypes, and the response was durable. In general, the overall response reported in this study was better than the results of previous clinical trials. Some possible factors may explain this phenomenon. First, most patients were treated with combination therapy, including chemotherapy and molecular targeted drugs. However, most previous clinical trials were performed to evaluate the performance of PD-1 inhibitor monotherapy. Moreover, we attempted to resume the anti-PD-1 immunotherapy when the disease initially progressed to confirm the suspicion of pseudoprogression in the absence of a pathological evidence. After all, the characteristics of patients in our cohort may be different from those of patients in previous clinical trials. For example, a simple regimen was possibly used in the early treatment of most patients ( 19 ). Given the above factors, the effect of PD-1 inhibitor treatment was slow but durable, and potential benefits may exist depending on the disease subtype. Both molecular targeted therapy and proper chemotherapy can enhance the treatment efficacy. Despite the higher response rate acquired in a real-world setting, many patients showed no response or low response to anti-PD-1 therapy, and many others showed disease progression. How can we predict the efficacy of PD-1 inhibitors before or during the early phase of treatment? Previous studies have shown that the expression of PD-1 in tumor-infiltrating lymphocytes, the expression of PD-L1 in the tumor, the tumor mutation load, or the 9p24.1 genetic alteration related to EBV infection may be useful in identifying patients who may benefit from PD-1 inhibitor treatment ( 28 – 32 ). However, none of these indices are readily available in clinical practice. Thus, searching for easy and readily measured biomarkers capable of predicting the treatment response has become imperative for improving the anti-PD-1 immune checkpoint inhibitor therapy in lymphomas. Using univariate and multivariate analyses, the kinetics of NLR during PD-1 inhibition was an independent prognostic factor in our study and was determined by dividing the peripheral neutrophil count by the peripheral lymphocyte count. The peripheral neutrophil count reflects, to some extent, the tumor-associated neutrophil and myeloid-derived suppressor cell (MDSC) counts. MDSCs may contribute to resistance to anti-PD-1 treatment and tumor progression. A reduction in lymphocyte count represents a blunted antitumor immune response by cytotoxic T lymphocytes. An increase in NLR reflects a complex dialog between the tumor cells and their microenvironment driven by PD-1 inhibitors. Most patients included in our study tested negative for EBV; however, the result was not inferior to that of EBV-positive patients reported in previous studies. Therefore, EBV infection may not be the core mechanism of the susceptibility to anti-PD-1 immunotherapy. Four patients (7.8%) showed an outburst of tumor growth upon PD-1 blockade, determined as HPD and not pseudoprogression. HPD was initially described in previous retrospective studies conducted in lung cancer patients treated with PD-1 inhibitors; some of these patients seemed to undergo growth acceleration after the initiation of PD-1 inhibitor therapy. Immune checkpoint inhibitors activate the immune system by recruiting activated T cells to the tumor sites and triggering inflammatory reactions. For patients with T-cell lymphomas, the risk of experiencing HPD is relatively high owing to the complex microenvironment, especially those with angioimmunoblastic T-cell lymphoma. Surprisingly, two patients who were diagnosed with DLBCL had experienced HPD, which has not been described in previous literature. This may be related to the rapid growth of background T cells in the tumor microenvironment of B-cell lymphoma and the collusion of B cells and T cells. The incidence of HPD in PTCL patients was lower than that reported in a previous study, perhaps because of the use of combination therapy. An elevated LDH level (> 225.5 U/L) after the use of PD-1 inhibitors was associated with the occurrence of HPD and a secondary inferior survival rate. It can be a useful indicator of the tumor growth dynamics to facilitate the early detection of HPD and to minimize the adverse outcomes induced by PD-1 inhibitor treatment. Three patients received chemotherapy following treatment with immune checkpoint inhibitors, thus prolonging the median survival by only 2.3 months. CAR-T therapy is a breakthrough treatment for these patients. One patient with PTCL showed CRS-like symptoms within 24 hours of PD-1 inhibitor administration, including fever (body temperature of > 39℃), hypotension (< 90/60 mmHg), muscle and joint pain, and fatigue (ECOG-PS score of 4). No evidence of infection or any other condition was observed. The blood pressure improved on the first day after symptomatic treatment, but the fever persisted until the third day after PD-1 inhibitor treatment. This study has some limitations. First, this was a single center retrospective study conducted in a limited number of samples. Hence, further studies on large cohorts are needed to confirm our findings. AEs were not described in detail owing to the lack of information, which is a minor concern. In a real-world setting, the effect of PD-1 inhibitors against some lymphoma subtypes not recommended in the guidelines appears to be acceptable, especially in PCNSL. The kinetics of LDH and NLR may be used to predict the clinical outcomes. Abbreviations ALCL anaplastic large cell lymphoma CHL classic Hodgkin’s lymphoma CR complete response CRR complete response rate CRS cytokine release syndrome DCR disease control response rate DLBCL diffuse large B-cell lymphoma EBV Epstein-Barr virus ECOG-PS Eastern Cooperative Oncology Group performance status HL Hodgkin’s lymphoma HPD hyperprogressive disease LD lactate dehydrogenase MDSC myeloid-derived suppressor cell NHL non-Hodgkin’s lymphoma NK/TCL natural killer/T-cell lymphoma ORR objective response rate OS overall survival PCNSL primary central nervous system lymphoma PCNSL primary central nervous system lymphoma PD progressive disease PD-1 programmed death-1 PD-L1 programmed death ligand 1 PFS progression-free survival PMBCL primary mediastinal large B-cell lymphoma PR partial response PTCL-nos peripheral T-cell lymphoma non-specificity ROC receiver operating characteristic SD stable disease TTF time-to‐treatment failure ΔNLR neutrophil-to-lymphocyte ratio before and after PD-1 inhibitor Declarations Acknowledgements Not applicable. Funding This study was supported by the National Natural Science Foundation of China (grant number: 82070210) and the Major Medicine Scientific and Technology Project of Henan Province (grant number: SBG 202001008). Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Author contributions Miao Wang, Siyu Qian, and Mingzhi Zhang designed the study. All investigators and their respective research teams recruited and followed up the patient. Miao Wang, Yue Zhang, Qingjiang Chen and Yue Zhang collected and analyzed the research data. Miao Wang, Xudong Zhang and Siyu Qian wrote and edited the manuscript. All authors were involved at each stage of the manuscript preparation and approved the final version. All authors contributed to the article and approved the submitted version. Ethics approval and consent to participate This study was approved by the Ethics Committee of Scientific Research/Medicine Clinical Trial of The First Affiliated Hospital of Zhengzhou University (approval no. 2022-KY-0869-001; Zhengzhou, China). The informed consent that was obtained from all of the participants. Patient consent for publication Not applicable. Conflict of interest We declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Armitage JO, Gascoyne RD, Lunning MA, Cavalli F. Non-Hodgkin lymphoma. Lancet (London England). 2017;390(10091):298–310. 10.1016/s0140-6736(16)32407-2 . Jaffe ES. Diagnosis and classification of lymphoma: Impact of technical advances. Semin Hematol. 2019;56(1):30–6. 10.1053/j.seminhematol.2018.05.007 . Fowler NH, Dickinson M, Dreyling M, Martinez-Lopez J, Kolstad A, Butler J, et al. 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Ann Hematol. 2019;98(9):2227–30. 10.1007/s00277-019-03758-z . Yao. YZMJYS, Z, Wang. H, Chu J, et al. Anti-Angiogenic Agent Combined with Anti-PD-1 Immunotherapy Showed Activity in Patients With Classical Hodgkin Lymphoma Who Have Failed Immunotherapy: A Retrospective Case Report Study. Front Immunol. 2021;12:727464. 10.3389/fimmu.2021.727464 . Cai J, Liu P, Huang H, Li Y, Ma S, Zhou H, et al. Combination of anti-PD-1 antibody with P-GEMOX as a potentially effective immunochemotherapy for advanced natural killer/T cell lymphoma. Signal Transduct Target therapy. 2020;5(1):289. 10.1038/s41392-020-00331-3 . Doroshow DB, Bhalla S, Beasley MB, Sholl LM, Kerr KM, Gnjatic S, et al. PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat reviews Clin Oncol. 2021;18(6):345–62. 10.1038/s41571-021-00473-5 . Wang F-H, Wei X-L, Feng J, Li Q, Xu N, Hu X-C, et al. Efficacy, Safety, and Correlative Biomarkers of Toripalimab in Previously Treated Recurrent or Metastatic Nasopharyngeal Carcinoma: A Phase II Clinical Trial (POLARIS-02). J Clin oncology: official J Am Soc Clin Oncol. 2021;39(7):704–12. 10.1200/jco.20.02712 . Redman MW, Papadimitrakopoulou VA, Minichiello K, Hirsch FR, Mack PC, Schwartz LH, et al. Biomarker-driven therapies for previously treated squamous non-small-cell lung cancer (Lung-MAP SWOG S1400): a biomarker-driven master protocol. Lancet Oncol. 2020;21(12):1589–601. 10.1016/s1470-2045(20)30475-7 . Marabelle A, Fakih M, Lopez J, Shah M, Shapira-Frommer R, Nakagawa K, et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 2020;21(10):1353–65. 10.1016/s1470-2045(20)30445-9 . Goldberg SB, Schalper KA, Gettinger SN, Mahajan A, Herbst RS, Chiang AC, et al. Pembrolizumab for management of patients with NSCLC and brain metastases: long-term results and biomarker analysis from a non-randomised, open-label, phase 2 trial. Lancet Oncol. 2020;21(5):655–63. 10.1016/s1470-2045(20)30111-x . Weber R, Fleming V, Hu X, Nagibin V, Groth C, Altevogt P, et al. Myeloid-Derived Suppressor Cells Hinder the Anti-Cancer Activity of Immune Checkpoint Inhibitors. Front Immunol. 2018;9:1310. 10.3389/fimmu.2018.01310 . Greten TF, Sangro B. Targets for immunotherapy of liver cancer. J Hepatol. 2017. 10.1016/j.jhep.2017.09.007 . Ménétrier-Caux C, Ray-Coquard I, Blay J-Y, Caux C. Lymphopenia in Cancer Patients and its Effects on Response to Immunotherapy: an opportunity for combination with Cytokines? J Immunother Cancer. 2019;7(1):85. 10.1186/s40425-019-0549-5 . Adamstein NH, MacFadyen JG, Rose LM, Glynn RJ, Dey AK, Libby P, et al. The neutrophil-lymphocyte ratio and incident atherosclerotic events: analyses from five contemporary randomized trials. Eur Heart J. 2021;42(9):896–903. 10.1093/eurheartj/ehaa1034 . Kim S-J, Hyeon J, Cho I, Ko YH, Kim WS. Comparison of Efficacy of Pembrolizumab between Epstein-Barr Virus–Positive and –Negative Relapsed or Refractory Non-Hodgkin Lymphomas. Cancer Res treatment: official J Korean Cancer Association. 2019;51(2):611–22. 10.4143/crt.2018.191 . Kambayashi Y, Fujimura T, Hidaka T, Aiba S. Biomarkers for Predicting Efficacies of Anti-PD1 Antibodies. Front Med. 2019;6:174. 10.3389/fmed.2019.00174 . Barta SK, Zain J, MacFarlane AW, Smith SM, Ruan J, Fung HC, et al. Phase II Study of the PD-1 Inhibitor Pembrolizumab for the Treatment of Relapsed or Refractory Mature T-cell Lymphoma. Clin lymphoma myeloma Leuk. 2019;19(6):356–64e3. 10.1016/j.clml.2019.03.022 . Ratner L, Waldmann TA, Janakiram M, Brammer JE. Rapid Progression of Adult T-Cell Leukemia-Lymphoma after PD-1 Inhibitor Therapy. N Engl J Med. 2018;378(20):1947–8. 10.1056/NEJMc1803181 . Joshi M, Ansell SM. Activating the Antitumor Immune Response in Non-Hodgkin Lymphoma Using Immune Checkpoint Inhibitors. J Immunol Res. 2020;2020:8820377. 10.1155/2020/8820377 . Ferreira LMR, Muller YD, Bluestone JA, Tang Q. Next-generation regulatory T cell therapy. Nat Rev Drug Discovery. 2019;18(10):749–69. 10.1038/s41573-019-0041-4 . Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure1.tif supplementary.docx 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. We do this by developing innovative software and high quality services for the global research community. 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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-3878647","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271223859,"identity":"c00e9161-a69e-4172-8b7d-f8f67baae530","order_by":0,"name":"Miao Wang","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Miao","middleName":"","lastName":"Wang","suffix":""},{"id":271223861,"identity":"ff59cb2a-d85f-41e9-b2e5-00e40aa740d9","order_by":1,"name":"Siyu Qian","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Siyu","middleName":"","lastName":"Qian","suffix":""},{"id":271223862,"identity":"81ccb81c-c05d-430b-8be2-4fa9fa3c7153","order_by":2,"name":"Yue Zhang","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Zhang","suffix":""},{"id":271223863,"identity":"693c59bb-9dd5-42a7-8a00-c622e3c68c7e","order_by":3,"name":"Qingjiang Chen","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Qingjiang","middleName":"","lastName":"Chen","suffix":""},{"id":271223864,"identity":"24a0ae12-a924-4565-9fbd-13d1943867fb","order_by":4,"name":"Xudong Zhang","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xudong","middleName":"","lastName":"Zhang","suffix":""},{"id":271223865,"identity":"e1916d48-016c-49b9-9732-8aafac98d732","order_by":5,"name":"Mingzhi Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYDACZiBmbJBgYJAA8QxsePj5G0jSUpAmIznjABE2MYLMBWv5cNjGoCEBv2rddt7DL3/usGCQn9387OEXg/M8BgwHGD98zMGtxewwX5qF5BkJBsY5x8yNZQxu85gzNzBLztyGTwuPmYFhmwQDs0SCmbQEUItlwwE2Zl5CWhKBWtgk0r8BtZzjMTiQQFCL8YODQC08Ejlmkh8MDhClxYyxEahFQiKnTJrBIJlHcsbBZvx+OX/G+OPPtjoG+Rnp2yR//LGz5+dvPvjhIx4tQMAGipH6BiDBzAMWAEcTXsD8AcZi/EFI7SgYBaNgFIxIAAAzG0tUnUlRtQAAAABJRU5ErkJggg==","orcid":"","institution":"Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"Mingzhi","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-01-19 11:59:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3878647/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3878647/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50758268,"identity":"d8c8fda8-83f7-4e85-bda2-498fa3b473c5","added_by":"auto","created_at":"2024-02-06 20:13:47","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":180698,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival outcomes of patients: (A) Overall survival curves of all patients, (B) time to treatment failure curves of all patients, (C) progression-free survival curves of all patients, (D) overall survival curves of each patient group, (E) time to treatment failure curves of each patient group, (F) progression-free survival curves of each patient group\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3878647/v1/9604d8aeba5119ab664f825d.jpg"},{"id":50758269,"identity":"72e1b757-0081-4185-92ad-e05d55474423","added_by":"auto","created_at":"2024-02-06 20:13:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":250344,"visible":true,"origin":"","legend":"\u003cp\u003eDuration of treatment for full analysis: (A) ALCL, (B) PTCL-nos, (C) PCNSL, and (D) DLBCL. ALCL: anaplastic large cell lymphoma, PTCL: peripheral T-cell lymphoma non-specificity, PCNSL: primary central nervous system lymphoma, DLBCL: diffuse large B-cell lymphoma, PD-1: PD-1 inhibitor, Chemo: chemotherapy, HDAC: HDAC inhibitor, MTD: molecularly targeted drug, AI: angiogenesis inhibitor, Immuno: immunomodulator\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3878647/v1/472a8b4342ef290fbdaa1144.jpg"},{"id":50758270,"identity":"d3a8d458-98cc-4763-a21c-01458e289890","added_by":"auto","created_at":"2024-02-06 20:13:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":198513,"visible":true,"origin":"","legend":"\u003cp\u003e(A) ROC curve of ΔNLR for predicting the OS. (B) Kaplan–Meier survival plot of the OS according the ΔNLR. (C) Kaplan–Meier survival plot of the OS according to the HPD status. (D–E) Case study of patients with HPD receiving PD-L1 inhibitor treatment. (D) Scans obtained before baseline. (E) Scans obtained at baseline. (F) Scans obtained at initial evaluation after treatment with PD-1 inhibitors. \u0026nbsp;HPD: hyperprogressive disease, OS: overall survival, ROC: receiver operating characteristic, ΔNLR: neutrophil-to-lymphocyte ratio before and after PD-1 inhibitor.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3878647/v1/8cc56355fd432f0d2fa700e6.jpg"},{"id":79579353,"identity":"243567fd-3fcf-4041-9259-fd4f9315ac55","added_by":"auto","created_at":"2025-03-31 11:39:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1354833,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3878647/v1/5287de16-6ef0-4f5c-8a8f-68753cc48928.pdf"},{"id":50758615,"identity":"1d5f7ace-8a22-42b5-9476-933a2e266bf5","added_by":"auto","created_at":"2024-02-06 20:21:50","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":169624,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3878647/v1/d8649e43b0a8f95142da72af.tif"},{"id":50758271,"identity":"fadce325-229e-4743-bff9-d64087c9403e","added_by":"auto","created_at":"2024-02-06 20:13:47","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":15669,"visible":true,"origin":"","legend":"","description":"","filename":"supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-3878647/v1/c19a932bb1cf5b6586aa0c20.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Programmed death-1 inhibitors as treatment for other subtypes of lymphomas not recommended in the guidelines: Real-world data from a single center in China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLymphoma includes a variety of malignancies with different histopathological features, molecular characteristics, and clinical course despite arising from a common origin, the lymphatic tissues. Lymphoma is categorized into Hodgkin\u0026rsquo;s lymphoma (HL) and non-Hodgkin\u0026rsquo;s lymphoma (NHL) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Although the curative effect of standard treatment in some subtypes was satisfactory, the overall treatment outcome of other or relapsed patients was unfavorable and dismal (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Therefore, new salvage therapies are needed to improve this situation.\u003c/p\u003e \u003cp\u003eProgrammed death-1 (PD‐1) inhibitors are effective against classic Hodgkin\u0026rsquo;s lymphoma (CHL) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), primary mediastinal large B-cell lymphoma (PMBCL), and natural killer/T-cell lymphoma (NK/TCL) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), which have been included in the treatment guidelines (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, PD‐1 inhibitors are not recommended for other subtypes of lymphomas, such as anaplastic large cell lymphoma (ALCL), diffuse large B-cell lymphoma (DLBCL), and peripheral T-cell lymphoma non-specificity (PTCL-nos). Many clinical trials are underway to investigate the efficacy of PD-1 inhibitors in other lymphoma subtypes not recommended in the treatment guidelines. Although the existing clinical trials have employed strict enrollment criteria to reduce bias, they may not entirely mirror the real-world clinical situation. Therefore, we retrospectively analyzed the efficacy of PD‐1 inhibitors in other lymphoma subtypes not recommended in the guidelines in a real-world setting. We aimed to evaluate the rates of response to PD-1 inhibitors and identify the potential biomarkers of treatment outcomes. We also explored the incidence of hyperprogressive disease (HPD) and cytokine release syndrome (CRS) induced by PD-1 inhibitor treatment (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). To the best of our knowledge, this study is the first to report the HPD and CRS phenomenon in lymphoma patients in a real-world setting.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eData of lymphoma patients treated with PD-1 inhibitors between January 2016 and January 2022 at the First Affiliated Hospital of Zhengzhou University were retrospectively collected. The inclusion criteria were as follows: (i) treatment with either PD-1 inhibitors alone or combination therapy; (ii) histologically confirmed diagnosis of lymphoma (except CHL, PMBCL, and NK/TCL); (iii) having undergone at least two cycles of PD-1 inhibitor therapy; and (iv) available computed tomography/magnetic resonance imaging information at three time points: before baseline (when previous therapy was initiated/no therapy was provided), at baseline (before the initiation of PD-1 inhibitor treatment), and at initial evaluation following the initiation of PD-1 inhibitor therapy. The patients were followed up until October 31, 2021 by phone interview, email, or review of medical records.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAssessment\u003c/h2\u003e \u003cp\u003eThe data were gathered and analyzed based on the Revised Response Criteria for Malignant Lymphomas (2014 Lugano classification) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The responses were classified as progressive disease (PD), stable disease (SD), partial response (PR), and complete response (CR). Primary study outcome measurements were overall survival (OS) and time-to‐treatment failure (TTF). The CR rate (CRR), objective response rate (ORR), disease control response rate (DCR), and progression-free survival (PFS) were also evaluated. TTF was defined as the time from the first administration of PD-1 inhibitors to treatment failure (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). OS was defined as the interval from the first administration of PD-1 inhibitors to death or the end of last follow-up. PFS was defined as the interval from the date of the first administration of PD-1 inhibitors to PD or death due from any cause. ORR was defined as the proportion of patients who achieved CR or PR. DCR was defined as the proportion of patients who achieved CR, PR, or SD.\u003c/p\u003e \u003cp\u003eTo diagnose HPD, the following parameters were considered: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) a TTF of \u0026lt;\u0026thinsp;2 months, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) an increase in the sum of the target lesion major diameter by \u0026gt;\u0026thinsp;50% after the first cycle of PD-1 inhibitor therapy, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) a tumor growth rate of \u0026gt;\u0026thinsp;100% compared with that at pre-therapy, (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) appearance of new lesions between baseline and at initial imaging evaluation, and (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) worsening of clinical condition, evidenced by an Eastern Cooperative Oncology Group performance status (ECOG-PS) score of 2 during the first 2 months of immunotherapy. Patients who fulfilled at least three of these criteria were considered to have experienced HPD (\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe patients\u0026rsquo; characteristics were analyzed using a descriptive analysis. A Cox proportional hazard regression model was used to identify the independent factors influencing OS. Logistic regression models were used to identify the predictors of HPD. The cutoff values of lactate dehydrogenase levels at initial evaluation after initiation of PD-1 inhibitor therapy (LDH2) and the specific value of neutrophil-to-lymphocyte ratio before and after administration of PD-1 inhibitors (ΔNLR) were identified using the receiver operating characteristic (ROC) curve. The OS, PFS, and TTF were calculated using the Kaplan\u0026ndash;Meier method, and the groups were compared using the log-rank test. All statistical analyses were performed using the R software, version 3.5.3, or GraphPad Prism, version 8.0. A P-value of \u0026lt;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u0026rsquo; characteristics\u003c/h2\u003e \u003cp\u003eBased on the inclusion and exclusion criteria, 51 patients were selected for the study, including 10 with ALCL, 15 with PTCL-nos, 10 with primary central nervous system lymphoma (PCNSL), and 16 with DLBCL. Most patients (90.2%) tested negative for Epstein-Barr virus (EBV). The patients previously received a median of 1 regimen prior to the initiation of PD-1 inhibitor therapy. Two patients had unconfirmed CR status when PD-1 inhibitor treatment was started, while the remaining patients had active disease. Furthermore, 10 patients received PD-1 inhibitors alone, while the others received combination therapy. Two patients discontinued treatment due to the occurrence of PD-1 inhibitor-related adverse events (AEs), including one with serious pancreatitis and one with secondary interstitial pneumonia. The patients\u0026rsquo; characteristics are summarized in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of efficacy\u003c/h2\u003e \u003cp\u003eThe two patients who had unconfirmed CR status were not included in the evaluation of treatment efficacy. The follow-up evaluation showed that these two patients achieved CR after receiving consolidation therapy with PD-1 inhibitors. As for the rest of the patients, 13 (26.5%) achieved CR, 17 (34.7%) achieved PR, 10 (20.4%) showed SD, and 9 (18.4%) had PD or HPD. The ORR and DCR were 61.2% and 81.9%, respectively (Table I). Survival analysis showed that the median OS, TTF, and PFS were 23.9, 18.8, and 6.3 months, respectively, in all patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u0026ndash;C). In the ALCL subgroup, the median OS, PFS, and TTF were 20.2, 3.8, and 3.6 months, respectively. Three patients achieved CR, and one of them was treated with PD-1 inhibitors alone. Four patients showed progression after PD-1 inhibitor therapy, including two HPD patients. For PTCL-nos patients, the median OS, PFS, and TTF were 23.9, 18.5, and 4.8 months, respectively. Two patients achieved CR. Some patients experienced PD after a short-term control of the disease. However, none of them developed HPD. For the DLBCL subtype, the median OS, PFS, and TTF were 29.1, 25.9, and 11.8 months, and the CRR and ORR were 26.7% and 60.0%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Two patients showed rapid progression of disease after PD-1 inhibitor administration. In the PCNSL group, PD-1 inhibitors were highly effective. The median TTF was 8.9 months, while the median OS and PFS were not reached (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD\u0026ndash;F). Overall, 40.0% of the patients were cured, and the ORR was 70.0%. Details of each patient for each subtype are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\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\u003eClinical Activity in PD-1 Treated Patients NOTE:\u0026ldquo;1\u0026rdquo;represents before PD-1 inhibitors therapy, \u0026ldquo;2\u0026rdquo;represents at first evaluation after PD-1 inhibitors therapy.HR: Hazard ratio; IPI: IPI score; NLR: Neutrophil to Lymphocyte Ratio; LDH: Lactate dehydrogenase; A/G: ratio of albumin to globulin; ΔNLR: the specific value of NLR before and after PD-1 inhibitors therapy.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eALCL\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePTCL\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePCNSL\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDLBCL\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBest response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR/CRu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13(26.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4(26.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17(34.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10(20.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5(10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4(8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eORR(CR\u0026thinsp;+\u0026thinsp;PR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30(61.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(70.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9(60.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDCR(CR\u0026thinsp;+\u0026thinsp;PR\u0026thinsp;+\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40(81.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(77.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(86.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9(90.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11(73.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOS, median(m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePFS, median(m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTTF, median(m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eClinical prognostic factors\u003c/h2\u003e \u003cp\u003eWe evaluated the association between the clinical variables and OS using univariate and multivariate analyses (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The specific value of ΔNLR was an independent risk factor for OS, which was driven by an increase in the neutrophil count and a reduction in the lymphocyte count. ROC curve analyses revealed that the optimal cutoff point of ΔNLR for mortality was \u0026gt;\u0026thinsp;1.78 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The OS in patients with NLR increased by \u0026gt;\u0026thinsp;1.78 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\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\u003eUnivariate and multivariable analyses for overall survival(n\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR(95CI%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR(95CI%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR or PR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.61(1.54\u0026ndash;20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.84(0.30-77.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEBER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.65 (0.14\u0026ndash;2.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58(0.02\u0026ndash;21.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.57 (1.22\u0026ndash;25.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.41(0.73-749.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIPI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.57 (0.42\u0026ndash;5.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03(0.23\u0026ndash;4.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulky disease (\u0026gt;\u0026thinsp;5 cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.12 (1.72\u0026ndash;21.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03(0-2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB symptom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.92(1.05\u0026ndash;14.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.74 (0.28-119.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECOG status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.68 (1.75\u0026ndash;7.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.56 (0.58-232.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.37(0.08\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0-Inf)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLines of previous regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09(0.70\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.07 (0.98\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ2-microglobulin1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98 (0.85\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.99\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA/G1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.24 (0.15\u0026ndash;10.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.07 (1.01\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62 (0.32\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ2-microglobulin2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.42 (1.09\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.73(0.92\u0026ndash;3.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 (1.01\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.99\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA/G2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30 (0.06\u0026ndash;1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39(1.14\u0026ndash;1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.47(1.09\u0026ndash;27.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eHPD phenomenon\u003c/h2\u003e \u003cp\u003eFour patients (7.8%) experienced HPD, including two with ALCL and two with DLBCL. All patients met the diagnostic criteria for HPD, and three patients were confirmed to have HPD based on the results of pathological examination. Only one patient with ALCL received PD-1 inhibitor alone, while the others received combination therapy (including chemotherapy and molecular targeted therapy). We investigated the possible links between HPD and clinical variables by conducting univariate and multivariate analyses; the LDH level at the initial evaluation after the administration of PD-1 inhibitors was correlated with HPD (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). ROC curve analyses revealed that the optimal cutoff point was 225.5 U/L (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Three patients received chemotherapy as salvage therapy following the occurrence of HPD induced by immunotherapy, but the treatment was not effective. The median OS time was only 2 months after the hyperprogression of disease caused by PD-1 inhibitor therapy. One patient received chimeric antigen receptor T-cell (CAR-T) therapy after experiencing HPD and achieved CR, with no tumor burden. The radiological images are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u0026ndash;F. A significant correlation was found between HPD and OS, and the clinical outcome was a worse in patients with HPD (median OS: 5.5 months) compared with that in patients with non-HPD (median OS: 24.0 months) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ethe treatment information of HPD patients(n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubtype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003e(yr)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImmunotherapy regimens\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost HPD Therapy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTTF\u003c/p\u003e \u003cp\u003e(m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eState\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOS after HPD(m)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDLBCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCAR-T therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSurviving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDLBCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCombination with Ibrutinib and Thalidomide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExpectant treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCombination with Chidamide, Lenalidomide and Gemcitabine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHyper CVAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCombination with Chidamide, Lenalidomide and Gemcitabine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGDPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNOTE: GDPT: gemcitabine\u0026thinsp;+\u0026thinsp;cisplatin\u0026thinsp;+\u0026thinsp;prednisone\u0026thinsp;+\u0026thinsp;thalidomide; Hyper CVAD: fractionated cyclophosphamide\u0026thinsp;+\u0026thinsp;vincristine\u0026thinsp;+\u0026thinsp;doxorubicin\u0026thinsp;+\u0026thinsp;dexamethasone.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn recent years, PD-1 inhibitors have been used for antitumor treatment. It plays an antitumor role by blocking the binding of PD-ligand 1 (PD-L1) and PD-1, thus inhibiting the immunosuppressive signal mediated by PD-1 and activating the body\u0026rsquo;s own immune response system. Increasing evidence show its efficacy in some lymphoma subtypes, especially in CHL, PMBCL, and NK/TCL. However, its efficacy in other subtypes has not been clearly clarified and needs to be explored. Shi et al. reported the objective response of PD-1 antibody in relapse/refractory PTCL (including PTCL-nos, ALCL, NK/TCL, and other subtypes), which had an ORR of 40.4% and CCR of 14.6% (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Alexander et al. showed that the ORRs in refractory/relapse follicular lymphoma and DLBCL were 40% (CR: 10%) and 36% (CR: 9%), respectively (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The overall result was unsatisfactory but intriguing. However, the clinical trials employed strict enrollment criteria to avoid bias, which does not reflect the situation of the actual clinical practice. Our study analyzed the efficacy of PD-1 inhibitors in different lymphoma subtypes not recommended by guidelines in a real-world setting.\u003c/p\u003e \u003cp\u003eFour subtypes were examined in our studies: ALCL, PTCL, PCNSL, and DLBCL. None of them were recommended for PD-1 inhibitor therapy based on existing guidelines. The ORR of PCNSL (70.0%, 7/10) was higher than that of PTCL (66.7%, 7/15), DLBCL (60.0%, 9/15), and ALCL (44.4%, 4/9). The CRR of ALCL (33.3%, 3/9) and PCNSL (40.0%, 4/10) was better than that of DLBCL (26.7%, 4/15) or PTCL (13.3%, 2/15). CR was achieved in several patients of all subtypes, and the response was durable. In general, the overall response reported in this study was better than the results of previous clinical trials. Some possible factors may explain this phenomenon. First, most patients were treated with combination therapy, including chemotherapy and molecular targeted drugs. However, most previous clinical trials were performed to evaluate the performance of PD-1 inhibitor monotherapy. Moreover, we attempted to resume the anti-PD-1 immunotherapy when the disease initially progressed to confirm the suspicion of pseudoprogression in the absence of a pathological evidence. After all, the characteristics of patients in our cohort may be different from those of patients in previous clinical trials. For example, a simple regimen was possibly used in the early treatment of most patients (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Given the above factors, the effect of PD-1 inhibitor treatment was slow but durable, and potential benefits may exist depending on the disease subtype. Both molecular targeted therapy and proper chemotherapy can enhance the treatment efficacy.\u003c/p\u003e \u003cp\u003eDespite the higher response rate acquired in a real-world setting, many patients showed no response or low response to anti-PD-1 therapy, and many others showed disease progression. How can we predict the efficacy of PD-1 inhibitors before or during the early phase of treatment? Previous studies have shown that the expression of PD-1 in tumor-infiltrating lymphocytes, the expression of PD-L1 in the tumor, the tumor mutation load, or the 9p24.1 genetic alteration related to EBV infection may be useful in identifying patients who may benefit from PD-1 inhibitor treatment (\u003cspan additionalcitationids=\"CR29 CR30 CR31\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, none of these indices are readily available in clinical practice. Thus, searching for easy and readily measured biomarkers capable of predicting the treatment response has become imperative for improving the anti-PD-1 immune checkpoint inhibitor therapy in lymphomas. Using univariate and multivariate analyses, the kinetics of NLR during PD-1 inhibition was an independent prognostic factor in our study and was determined by dividing the peripheral neutrophil count by the peripheral lymphocyte count. The peripheral neutrophil count reflects, to some extent, the tumor-associated neutrophil and myeloid-derived suppressor cell (MDSC) counts. MDSCs may contribute to resistance to anti-PD-1 treatment and tumor progression. A reduction in lymphocyte count represents a blunted antitumor immune response by cytotoxic T lymphocytes. An increase in NLR reflects a complex dialog between the tumor cells and their microenvironment driven by PD-1 inhibitors. Most patients included in our study tested negative for EBV; however, the result was not inferior to that of EBV-positive patients reported in previous studies. Therefore, EBV infection may not be the core mechanism of the susceptibility to anti-PD-1 immunotherapy.\u003c/p\u003e \u003cp\u003eFour patients (7.8%) showed an outburst of tumor growth upon PD-1 blockade, determined as HPD and not pseudoprogression. HPD was initially described in previous retrospective studies conducted in lung cancer patients treated with PD-1 inhibitors; some of these patients seemed to undergo growth acceleration after the initiation of PD-1 inhibitor therapy. Immune checkpoint inhibitors activate the immune system by recruiting activated T cells to the tumor sites and triggering inflammatory reactions. For patients with T-cell lymphomas, the risk of experiencing HPD is relatively high owing to the complex microenvironment, especially those with angioimmunoblastic T-cell lymphoma. Surprisingly, two patients who were diagnosed with DLBCL had experienced HPD, which has not been described in previous literature. This may be related to the rapid growth of background T cells in the tumor microenvironment of B-cell lymphoma and the collusion of B cells and T cells. The incidence of HPD in PTCL patients was lower than that reported in a previous study, perhaps because of the use of combination therapy. An elevated LDH level (\u0026gt;\u0026thinsp;225.5 U/L) after the use of PD-1 inhibitors was associated with the occurrence of HPD and a secondary inferior survival rate. It can be a useful indicator of the tumor growth dynamics to facilitate the early detection of HPD and to minimize the adverse outcomes induced by PD-1 inhibitor treatment. Three patients received chemotherapy following treatment with immune checkpoint inhibitors, thus prolonging the median survival by only 2.3 months. CAR-T therapy is a breakthrough treatment for these patients. One patient with PTCL showed CRS-like symptoms within 24 hours of PD-1 inhibitor administration, including fever (body temperature of \u0026gt;\u0026thinsp;39℃), hypotension (\u0026lt;\u0026thinsp;90/60 mmHg), muscle and joint pain, and fatigue (ECOG-PS score of 4). No evidence of infection or any other condition was observed. The blood pressure improved on the first day after symptomatic treatment, but the fever persisted until the third day after PD-1 inhibitor treatment.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, this was a single center retrospective study conducted in a limited number of samples. Hence, further studies on large cohorts are needed to confirm our findings. AEs were not described in detail owing to the lack of information, which is a minor concern.\u003c/p\u003e \u003cp\u003e In a real-world setting, the effect of PD-1 inhibitors against some lymphoma subtypes not recommended in the guidelines appears to be acceptable, especially in PCNSL. The kinetics of LDH and NLR may be used to predict the clinical outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALCL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanaplastic large cell lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eclassic Hodgkin\u0026rsquo;s lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomplete response\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomplete response rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecytokine release syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edisease control response rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDLBCL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ediffuse large B-cell lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEBV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEpstein-Barr virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECOG-PS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEastern Cooperative Oncology Group performance status\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHodgkin\u0026rsquo;s lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehyperprogressive disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elactate dehydrogenase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMDSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emyeloid-derived suppressor cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNHL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-Hodgkin\u0026rsquo;s lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNK/TCL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enatural killer/T-cell lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eORR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eobjective response rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\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\"\u003ePCNSL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprimary central nervous system lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCNSL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprimary central nervous system lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprogressive disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprogrammed death-1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD-L1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprogrammed death ligand 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFS\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\"\u003ePMBCL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprimary mediastinal large B-cell lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epartial response\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePTCL-nos\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eperipheral T-cell lymphoma non-specificity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estable disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTTF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etime-to‐treatment failure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eΔNLR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneutrophil-to-lymphocyte ratio before and after PD-1 inhibitor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (grant number: 82070210) and the Major Medicine Scientific and Technology Project of Henan Province (grant number: SBG 202001008).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMiao Wang, Siyu Qian, and Mingzhi Zhang designed the study. All investigators and their respective research teams recruited and followed up the patient.\u0026nbsp;Miao Wang, Yue Zhang, Qingjiang Chen and\u0026nbsp;Yue Zhang collected and analyzed the research data.\u0026nbsp;Miao Wang,\u0026nbsp;Xudong Zhang and Siyu Qian wrote and edited the manuscript. All authors were involved at each stage of the manuscript preparation and approved the final version. All authors contributed to the article and approved the submitted version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Scientific Research/Medicine Clinical Trial of The First Affiliated Hospital of Zhengzhou University (approval no. 2022-KY-0869-001; Zhengzhou, China). The informed consent that was obtained from all of the participants.\u003c/p\u003e\n\u003cp\u003ePatient consent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArmitage JO, Gascoyne RD, Lunning MA, Cavalli F. Non-Hodgkin lymphoma. Lancet (London England). 2017;390(10091):298\u0026ndash;310. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s0140-6736(16)32407-2\u003c/span\u003e\u003cspan address=\"10.1016/s0140-6736(16)32407-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJaffe ES. Diagnosis and classification of lymphoma: Impact of technical advances. Semin Hematol. 2019;56(1):30\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1053/j.seminhematol.2018.05.007\u003c/span\u003e\u003cspan address=\"10.1053/j.seminhematol.2018.05.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFowler NH, Dickinson M, Dreyling M, Martinez-Lopez J, Kolstad A, Butler J, et al. 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Nat Rev Drug Discovery. 2019;18(10):749\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41573-019-0041-4\u003c/span\u003e\u003cspan address=\"10.1038/s41573-019-0041-4\" 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":"PD-1 inhibitor, real-world study, hyperprogressive disease, lymphoma, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-3878647/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3878647/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e In recent years, PD-1 inhibitors have shined in some subtypes of lymphoma, including Classic Hodgkin\u0026rsquo;s lymphoma, Primary Mediastinal Large B-cell Lymphoma, and Natural Killer/T-cell Lymphoma, recommended by clinical practice guidelines. It is unknown how effective are PD-1 inhibitors used for other subtypes not recommended by the guidelines. We conducted a retrospective study in a real-world setting to evaluate efficacy of PD-1 inhibitors for other subtypes not recommended by the guidelines and discuss the potential biomarkers of treatment outcome. We found that the efficacy in some subtypes seems all right, especially in PCNSL. And the kinetics of Neutrophil to Lymphocyte Ratio and Lactate dehydrogenase may indicate clinical outcomes. Thus, PD-1 inhibitor is a promising choice for lymphoma patients. Further screening and monitoring of patients may bring more clinical benefits.\u003c/p\u003e","manuscriptTitle":"Programmed death-1 inhibitors as treatment for other subtypes of lymphomas not recommended in the guidelines: Real-world data from a single center in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-06 20:13:42","doi":"10.21203/rs.3.rs-3878647/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":"6e48fb6e-03d6-4b39-8706-924e54a23805","owner":[],"postedDate":"February 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-31T11:38:49+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-06 20:13:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3878647","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3878647","identity":"rs-3878647","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}