Effectiveness and mechanism of lymphocytes at different periods in predicting consolidation immunotherapy following adaptive chemoradiotherapy in LA-NSCLC

Effectiveness and mechanism of lymphocytes at different periods in predicting consolidation immunotherapy following adaptive chemoradiotherapy in LA-NSCLC | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effectiveness and mechanism of lymphocytes at different periods in predicting consolidation immunotherapy following adaptive chemoradiotherapy in LA-NSCLC Zhenwei Sun, Jiayi Duan, Zhaohao Zhang, Meng Chen, Dandan Zhou, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6724206/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To explore The role of lymphocytes in prognosis and lymphocyte subsets at different stages of chemoradiotherapy and consolidation immunotherapy in patients with locally advanced non-small cell lung cancer (NSCLC). Methods 139 Patients with Stage IIINSCLC who received adaptive chemoradiotherapy and consolidation immunotherapy were retrospectively enrolled in the final analysis. A paired sample T-test was used to assess the difference among absolute lymphocyte counts (ACLS) and lymphocyte subsets of pre-/post-/during treatmentin different periods. Through the application of univariate and multivariate Cox proportional hazards regression analyses, the determinants influencing the periods of progression-free survival (PFS) and overall survival (OS) were established.The Kaplan-Meier method was used to evaluate the survival prognosis in patients grouped by OS-related independent predictive factors. the PFS and OS. Results There were statistically significant differences among ACLS of before radiotherapy, at the 20th fraction of adaptive radiotherapy, and at one month following radiotherapy, respectively(P < 0.05). According to univariate and multivariate analysis, ACLS at 1 month after radiotherapy, decreased lymphocyte(defined as the difference value of before radiotherapy and the 20th fraction of adaptive radiotherapy), and increased lymphocyte count(defined as the difference value of one month following radiotherapy. and the 20th fraction of adaptive radiotherapy) were identified as Independent predictors of OS ((P 1.015×10 9 at one month following radiotherapy. ACLS with decreased value > 0.71×10 9 , or increase ACLS with increased value > 0.305×10 9 obtained longer OS. There were significant differences in CD4 + and CD8 + counts and CD8/CD4 between before and 1 month after radiotherapy (p < 0.05). KM curve showed the longer OS in patients with the higher level of CD8 + T cell at one month following radiotherapy. (P < 0.05). Conclusion Patients with NSCLC who undergo chemoradiotherapy followed by consolidation immunotherapy exhibit longer OS when they have a higher level of ACLS or CD8 + T cell counts at one month after chemoradiotherapy. Lymphocytes Lung cancer Radiation therapy Consolidation Immunotherapy Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Lung cancer is primarily driven by non-small cell lung cancer (NSCLC), which accounts for 80–85% of all instances[ 1 ], Approximately 20–30% of patients are diagnosed at stage III., of which 60–90% are unresectablestages[ 2 – 4 ]. For patients with unresectable locally advanced non-small cell lung cancer (LA-NSCLC), concurrent chemoradiation therapy (cCRT) has long been the standard approach. Nevertheless, the long-term efficacy of cCRT remains unsatisfactory, with 5-year survival rates typically between 15% and 30%.[ 2 – 5 ].The therapeutic options available to radiation oncologists for treating LA-NSCLC have significantly expanded since the PACIFIC trial reported its practice-changing results in 2017[ 6 ].This randomized, double-blind, placebo-controlled Phase III study enrolled patients with unresectable Stage III NSCLC and investigated the use of durvalumab as a consolidation therapy—a programmed death-ligand 1 (PD-L1) immune checkpoint inhibitor (ICI)—following curative-intent concurrent chemoradiation therapy (cCRT)[ 7 ]. The median follow-up duration was 34.2 months, the most recent survival analyses revealed that consolidation durvalumab achieved that the 5-year overall survival (OS) rate was 42.9%, and the progression-free survival (PFS) rate was 33.1%..[ 8 ]. The PACIFIC trial demonstrated that consolidation durvalumab following CRT (the PACIFIC regimen) provides substantial and durable survival benefits compared to CRT alone, further establishing its role as the new standard of care in this setting.[ 6 , 8 – 12 ]. In a global multicenter, phase Ⅱ, open-label, multi-cohort, non-randomized controlled clinical trial, KEYNOTE⁃799 study, it was shown that pembrolizumab combined with concurrent chemoradiotherapy had good anti-tumor activity and controllable safety in Individuals with newly diagnosed locally advanced stage III NSCLC.too. Although PACIFIC regimen improves the efficacy of NSCLC, there are still some patients with poor efficacy. The use of biomarkers to anticipate the outcomes of immunotherapy has seen a notable rise. Central to this approach are markers such as programmed death-ligand 1 (PD-L1), blood-derived tumor mutation burden (bTMB), microsatellite instability (MSI), mechanisms involved in DNA repair (DDR), and lymphocytes present within tumor tissues (TILs).[ 13 , 14 ]. However, due to the changes in immune microenvironment and biomarkers after radiotherapy, it is necessary to further explore the predictive markers of immune consolidation at different stages. Invasive biopsy after radiotherapy limits the prediction of some markers, and the prediction of blood lymphocytes seems to be more feasible. Thus, identifying more effective approaches to predict immunotherapy efficacy is of paramount importance. This study retrospectively analyzed the effect of blood lymphocytes at different stages in predicting immune consolidation following adaptive chemoradiotherapy in NSCLC. Furthermore, by analyzing the changes of lymphocyte subsets before and after chemoradiotherapy, the mechanism by which the changes of systemic immune microenvironment after radiotherapy can predict the efficacy was preliminarily elucidated. Patients and methods Patients selection Our study involved an examination of the medical histories of NSCLC patients at Taizhou Hospital, Zhejiang Province, China, from December 1, 2018, to July 31, 2024. Inclusion criteria comprised: (1) age range of 18 to 80 years; (2) possession of complete electronic health records, including absolute lymphocyte counts (ALCs); (3) pathologically verified NSCLC; (4) presence of clinically unresectable stage III cancer; (5) an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1 at baseline, alongside a projected survival of six months or more; and (6) administration of at least two cycles of anti-PD-1 inhibitor therapy. In addition, patients who met the following exclusion criteria were excluded: (1) NSCLC with uncertain diagnosis; (2) combined with other malignant tumors; (3) missing clinical data; (4) underlying diseases, such as acute infections, hematological diseases, autoimmune diseases, pregnancy or lactation.The study endpoints were OS and PFS; (5) Genetic alterations in the epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) were identified. The therapeutic impact of anti-PD-1 inhibitors was measured using computed tomography (CT) or magnetic resonance imaging (MRI), in accordance with the Response Evaluation Criteria in Solid Tumors (RECIST v1.1).[ 15 ]. Data collection The Medical record data of the patients were collected. Demographic information (age, gender), smoking history, histological type, lymph node metastasis, clinical stage, treatment method (concurrent chemoradiotherapy or sequential chemoradiotherapy), progression-free survival (PFS), overall survival (OS), and ALCS before radiotherapy, during radiotherapy (20th radiotherapy), and 1 month after radiotherapy (before immunotherapy) were collected. Immunological parameters (counts ofCD4+, CD8+, CD8/CD4) were also collected before and 1 month after radiotherapy. Treatment All patients received radical radiotherapy through conventional fractionated simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT). Initial and mid-treatment radiotherapy planning was based on conventional CT or four-dimensional CT simulation with a slice thickness of ≤ 5 mm. PET/CT was occasionally used before treatment but was not routinely employed for staging and target delineation. To minimize systematic errors caused by inter-fractional geometric displacement, megavoltage orthogonal portal imaging or CBCT was used routinely. Each patient underwent one plan adaptation after The first 20 fractions of radiotherapy were prescribed at 2.14–2.2 Gy per fraction to the planning gross tumor volume (PGTV). The planning treatment volume (PTV) received 54 Gy in 30 fractions, with a total dose of 64–66 Gy. After 20F of radiotherapy, the CT was repositioned and the plan was replanned.Platinum-based doublet chemotherapy was the preferred concurrent regimen, although sequential chemotherapy or radiotherapy alone was considered for patients intolerant to concurrent treatment.[ 16 ]. All patients received chemoradiotherapy or sequential chemoradiotherapy, followed by consolidation immunotherapy with intravenous sintilimab at a dose of 200 mg every 3 weeks.[ 17 ]. Statistical analysis Overall survival was the primary end point of this study. The secondary end point was progression-free survival.Descriptive statistics were applied to detail the features of the patients.. For this analysis, progression-free survival (PFS) was determined as the duration from the first dose of immunotherapy to the time of tumor recurrence, death due to any reason, or censoring at the last follow-up. Overall survival (OS) was measured from the start of immunotherapy until the patient's death or the conclusion of the follow-up period.Paired sample T-tests were used to assess changes in absolute lymphocyte counts at different time points.Cox proportional hazards regression analyses (both univariate and multivariate) were used to examine the relationship between the absolute value of lymphocytes at different periods and PFS and OS. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff values for lymphocytes at different time points. Continuous variables are reported in terms of mean ± standard deviation or as median values, and categorical variables are displayed as frequencies along with percentages. The chi-square test was employed to compare categorical variables between the two groups.Categorical variables are presented as frequencies and percentages. The chi-square test was used to compare categorical variables between the two groups.The study employed the K-M survival analysis method to analyze patients' progression-free survival and overall survival.Statistical significance was set at P < 0.05. Data analysis was performed using SPSS 25.0 (Armonk, New York, USA) and GraphPad Prism 8.0 (San Diego, California, USA) software. Results Patients characteristics: A total of 139 NSCLC patients were enrolled according to the inclusion criteria. The median age was 69 years (48–80 years). There were 132 males (95.0%). 108 patients (70.5%) had a history of smoking. Histologically, 117 cases (84.17%) were squamous carcinoma, 13 cases (9.35%) were adenocarcinoma, and Other types, including large cell carcinoma and adenosquamous carcinoma. There were 102 cases (73.38) with ECOG score of 0 (6.47%). According to TNM staging, 48 cases (34.53%) were stage ⅢA, 69 cases (49.64%) were stage ⅢB, and 22 cases (15.83%) were stage ⅢC. Seventy-six patients (54.68%) received sequential chemoradiotherapy and 63 patients (45.32%) received concurrent chemoradiotherapy. Baseline characteristics are shown in Table 1 . Table 1 Baseline characteristics of patients Variables Total (n = 139) Age (year) 69.00 (48, 80) Gender n(%) Female 7 (5.04) Male 132 (94.96) ECOG n(%) 0 102 (73.38) 1 37 (26.62) Smoking n(%) YES 98 (70.5) NO 41 (29.5) T n(%) 1 16 (11.51) 2 31 (22.30) 3 24 (17.27) 4 68 (48.92) N n(%) 1 20 (14.39) 2 78 (56.12) 3 41 (29.50) Stage n(%) ⅢA 48 (34.53) ⅢB 69 (49.64) ⅢC 22 (15.83) Pathologic n(%) Squamous 117 (84.17) Adenocarcinoma 13 (9.35) Other 9 (6.47) Therapy Method n(%) Concurrent Chemoradiotherapy 63 (45.32) Sequential Chemoradiotherapy 76 (54.68) ALCS before RT (Mean ± SD)(10 9 /L) 1.39 ± 0.52 ALCS of 20th fraction during RT (Mean ± SD)(10 9 /L) 0.61 ± 0.80 ALCS of 1month after RT (Mean ± SD)(10 9 /L) 1.10 ± 0.52 Decreased lymphocytes (Mean ± SD)(10 9 /L) 0.78 ± 0.94 Elevated lymphocytes (Mean ± SD)(10 9 /L) 0.49 ± 0.92 ECOG:The Eastern Cooperative Oncology Group Performance Status (ECOG) score. ALCS: absolute lymphocyte counts.RT: radiotherapy. SD: standard deviation Changes of ALCS in different periods . The ALCS were 1.39 ± 0.52×10 9 before radiotherapy, the 20th fraction of radiotherapy were 0.61 ± 0.80×10 9 , and 1 month after radiotherapy were 1.10 ± 0.52×10 9 ,respectively. The ALCS differencesFrom before radiotherapy to 20th fraction radiotherapy were 0.78 ± 0.94×10 9 and increase from 20th fraction radiotherapy to 1 month after radiotherapy were 0.49 ± 0.92×10 9 , respectively. There were significant differences to the ALCS decrease from before radiotherapy to 20th fraction radiotherapy and increase from 20th fraction radiotherapy to one month following radiotherapy (p < 0.05) (Fig. 1). Correlation of ACLS with PFS . Variables such as treatment method, gender, age, smoking status, TNM stage, ECOG score, histological type, ALCS before radiotherapy, ALCS at 20th fraction of radiotherapy, ALCS at 1 month after radiotherapy, ALCS decrease, and ALCS increase were included in univariate analysis. In Suppl Table 1, all were not associated with PFS. And that the ALCS > 1.015×10 9 at 1 month after radiotherapy and decrease ALCS > 0.71×10 9 and increase ALCS > 0.305×10 9 were no difference with PFS (P > 0.05) in Fig. 2. Correlation between ACLS and OS . The results in Table 2 , In our univariate analysis, the ALCS at one month following radiotherapy, the decrease or increase ALCScorrelated with enhanced overall survival (OS). (P < 0.045; P = 0.038; P = 0.006). Multivariate analysis showed that the ALCS at 1 month after radiotherapy, decreased or increased ALCScould serve as independent predictors for significantly improved OS.(OR0.44, 95%CI 0.20–0.97, P < 0.041; OR 0.46 95%ci (0.22–0.97), p = 0.041; OR 95%CI0.33 (0.15–0.72), p = 0.005). Table 2 Univariate and multivariate cox analysis was used to analyze overall survival. Variables Univariate analysis Multivariate analysis P OR (95%CI) P OR (95%CI) Age 0.080 0.97 (0.93 ~ 1.00) Gender Male 1.00 (Reference) Female 0.636 1.45 (0.31 ~ 6.76) ECOG 0 1.00 (Reference) 1 0.265 0.62 (0.27 ~ 1.43) Smoking No 1.00 (Reference) Yes 0.219 1.65 (0.74 ~ 3.69) T 1 1.00 (Reference) 2 0.892 0.92 (0.26 ~ 3.20) 3 0.787 0.83 (0.22 ~ 3.12) 4 0.781 0.85 (0.28 ~ 2.64) N 1 1.00 (Reference) 2 0.434 0.67 (0.24 ~ 1.84) 3 0.942 0.96 (0.32 ~ 2.86) Stage ⅢA 1.00 (Reference) 1.00 (Reference) ⅢB 0.747 1.14 (0.52 ~ 2.47) 0.574 1.26 (0.56 ~ 2.84) ⅢC 0.900 0.93 (0.32 ~ 2.75) 0.930 0.95 (0.30 ~ 2.98) Pathologic Squamous 1.00 (Reference) Adenocarcinoma 0.549 0.58 (0.10 ~ 3.40) Other 0.361 0.58 (0.18 ~ 1.85) Therapy Method Concurrent Chemoradiotherapy 1.00 (Reference) 1.00 (Reference) Sequential Chemoradiotherapy 0.787 1.10 (0.55 ~ 2.23) 0.480 1.31 (0.62 ~ 2.76) ALCS before RT(10 9 /L) 0.255 0.66 (0.33 ~ 1.34) ALCS of 20th fraction during RT(10 9 /L) 0.086 3.01(0.86 ~ 10.54) ALCS of 1month after RT(10 9 /L) 0.045 0.46 (0.21 ~ 0.98) 0.041 0.44(0.20 ~ 0.97) Decreased lymphocytes(10 9 /L) 0.038 0.45 (0.22 ~ 0.96) 0.041 0.46(0.22 ~ 0.97) Elevated lymphocytes(10 9 /L) 0.006 0.34 (0.16 ~ 0.73) 0.005 0.33(0.15 ~ 0.72) ECOG:The Eastern Cooperative Oncology Group Performance Status (ECOG) score. ALCS: absolute lymphocyte counts. RT: radiotherapy. OR: Odds Ratio. CI: confidence interval. The best cut-off values of ALCS at 1 month after radiotherapy(1.015×10 9 ), decrease ALCS (0.71×10 9 ), and increase ALCS (0.305×10 9 ) were obtained by ROC curve using spss software, as shown in Supp Fig. 1. The baseline characteristics of the two groups were compared to confirm the comparability (Suppl Tables 2, 3, and 4).The ALCS > 1.015×10 9 at 1 month after radiotherapy and decrease ALCS > 0.71×10 9 and increase ALCS > 0.305×10 9 achieved better OS (P < 0.05) in Fig. 2. Changes of lymphocyte subsets before and 1 month after radiotherapy A total of 39 patients were tested for lymphocyte subsets before and 1 month after radiotherapy. The absolute counts of CD4 and CD8 and CD8/CD4 were before and one month following radiotherapy, respectively. And, there were significant differences before and 1 month after radiotherapy (p < 0.05) in Fig. 3. Relationship between changes in lymphocyte subsets and OS. Spss software was used to draw ROC curves to obtain the best cut-off values. CD4, CD8, and CD8/CD4 before RT were 605/µL、538/µL、0.79 and 1 month after RT were 140.5/µL、230/µL、1.168, respectively, as shown in Suppl Fig. 2. Kaplan-Meier survival curves are shown in an absolute CD8 lymphocyte count of > 230/µL at 1 month after radiotherapy and CD4 lymphocytes decreased < 6/µLat 1 month after radiotherapy have better OS (Fig. 4). Discussion The emergence of immune checkpoint inhibitors (ICIs) in recent years has dramatically altered the treatment paradigm for NSCLC patients across the globe[ 18 ]. Nevertheless, the response to anti-PD-1 inhibitor therapy has been inconsistent in NSCLC patients[ 19 ]. As a result, determining which patients are most likely to respond favorably to anti-PD-1 inhibitors has surfaced as a major challenge.Yu Wang et al. reported that the median interval from the completion of concurrent chemoradiotherapy (CRT) to the initiation of durvalumab in real-world studies (RWSs) often surpassed 42 days, a notable deviation from the PACIFIC study protocol, which specified a maximum interval of 42 days.[ 20 ]. The main reason is the delay of immune maintenance therapy due to adverse reactions. Moreover, changes in the collective immune microenvironment after chemoradiotherapy require a simple and convenient predictor. Lymphocytes, which constitute approximately 30% of the total white blood cells in healthy individuals, are among the most radiation-sensitive cell subsets and play a crucial role as effector cells in anti-tumor immunity.[ 21 ]. As a reflection of the host's immune status, lymphocyte levels are closely linked to the response to immune checkpoint inhibitors and the overall survival rates in melanoma patients.[ 22 ]. One study have shown that ALCS is associated with the prognosis of a variety of malignant tumors, including NSCLC. Low ALCS is associated with poor prognosis of a variety of cancers, including lung, breast, and colorectal cancer[ 23 ].A clinical study showed that ALCS can predict overall survival in NSCLC patients treated with nivolumab. And, ALCS values at the start of treatment and after three months, as well as changes in ALCS, are all considered dynamic biomarkers that can predict the effect of ICI treatment[ 24 ]. Adaptive radiotherapy (ART) is an image-guided technique for treating tumors. Patients with non-small-cell lung cancer (NSCLC) who have large tumor lesions and high radiosensitivity are particularly well-suited for ART. The radiotherapy period of 30–50 Gy delivered in 15–25 fractions may represent the optimal timing for implementing ART[ 25 ]. Our earlier research indicated that gross tumor volumes (GTVs) diminished by a median of 38.2% after receiving 42–44 Gy of radiotherapy in 20 fractions. By accommodating tumor and anatomical shifts, dosimetric parameters for organs at risk (OARs) were notably reduced. Specifically,The results showed that the average irradiation dose to the lungs decreased by 74.8 cGy, and the average dose to the esophagus was reduced by 183.1 cGy.Moreover, adaptive adjustments were found to decrease the probability of RP2 by 3 percentage points and the risk of RE2 by 5 percentage points.[ 16 ]. Additionally, the trajectory of absolute lymphocyte counts (ALCs) during radiotherapy exhibited a general downward trend.And, the ALCS level increased gradually after radiotherapy. In our study, In 20 fractions of adaptive radiotherapy, the ALCS was reduced to 0.61 ± 0.80×10 9 , which was reduced by 0.78 ± 0.94×10 9 . One month after radiotherapy, it increased to 1.10 ± 0.52×10 9 and increased by 0.49 ± 0.92×10 9 。But, in van Rossum PSN, et al studies, At the fourth week, the ALCS decreased to 0.61 ± 0.80×10 9 , a decrease of 0.78 ± 0.94×10 9 .This reduction seems to be slightly lower compared with van Rossum, P.S.N.et al. report[ 26 ], which may be related to the reduction of the range of irradiation by our adaptive radiotherapy and thus the reduction of the degree of lymphocyte reduction. This result needs further study in the future. In our study, univariate analysis and Multivariate analysis showed that theALCS at 1 month after radiotherapy, decreased or increased ALCS were independent prognostic factors for significantly improved OS. ALCS > 1.015×10 9 at 1 month after radiotherapy but not before radiotherapy achieved better OS (P < 0.05). This suggests that RT has a potential effect on the proliferation and activation of lymphocytes[ 27 ].Although radiotherapy has an immuno-stimulatory effect by inducing neoantigens and danger signals for immune activation[ 28 ], It also exerts immunosuppressive effects, such as lymphopenia. However, the extent of this effect hinges on the timing of blood sampling and the timing of lymphodepletion. Some studies have documented that these changes can recover within 2, 3, 6 months, and up to 1 year post-treatment.[ 28 ]. Eckert et al. observed that, during radiotherapy (RT), all immune cell subgroups, excluding Tregs, exhibited elevated proliferation rates, which normalized approximately three months post-treatment.[ 29 ].There are no studies to prove the extent to which lymphocytes can be recovered to continue consolidation immunotherapy. Radiotherapy and immunotherapy also exhibit synergistic effects. Radiotherapy can enhance the efficacy of immunotherapy against tumors by promoting the release of damage-associated molecular patterns (DAMPs) and tumor-associated antigens (TAAs).optimizing the tumor immune microenvironment, and creating a hypoxic environment leading to hypoxia of tumor cells. ICI coincidentally can eliminate radiation resistance caused by radiotherapy. Some studies have shownthat ICI can not only release T cells to attack tumor cells[ 30 – 32 ], but also normalize tumor blood vessels to regulate the tumor microenvironment, thereby increasing radiosensitivity.The mechanism of synergistic effect of radiotherapy and immunotherapy needs further study[ 33 ]. We found that patients with stage III non-small cell lung cancer, in chemoradiotherapy combined with immunotherapy, the ALCS decreased during radiotherapy and was partially recovered 1 month after radiotherapy. And, CD4、CD8、CD8/CD4 lymphocytes also showed a downward trend before and after radiotherapy, and CD4 decreased more significantly. The absolute CD8 lymphocyte count of > 230 /µL at 1 month after radiotherapy and CD4 lymphocytes decreased < 6 / µL at 1 month after radiotherapy have better OS. Inone study, the levels of CD3+,CD4+,CD4+/CD8 + and CD19 + in peripheral blood of lung cancer patients before radiotherapy were significantly lower than those of the control group (P<0.05)[ 34 ]. This is consistent with our conclusion. The effect of radiotherapy on the immune microenvironment is seemingly a double-edged sword. On the one hand, it can activate anti-tumor immune promotion effect, and on the other hand, it kills lymphocytes and produces immunosuppression. However, radiotherapy kills tumor resistant immune cells, recovers the immune microenvironment. And the growth of CD8 + T cells is faster than that of CD4 + T cells, resulting in increased CD8/CD4, which may improve the efficacy of immunotherapy.This result needs to be further confirmed by prospective clinical studies. The primary limitation of this study is its single-center retrospective design and limited sample size, which may introduce potential information bias. Therefore, to further validate our results, a prospective study across multiple centers with a larger cohort is required. Moreover, further study requires analysis of a more diverse array of lymphocyte sub-types, extending beyond just CD8 + or CD4 + cells. Another future focus may be weather a directional intervention on lymphocyte levels can enhance the survival benefits obtained from chemoradiotherapy followed by immunotherapy. Conclusion This study revealed that the ACLS or CD8 + T cell count of 1 month after chemoradiotherapy can act as effective prognostic predictors in patients with NSCLC who undergo chemoradiotherapy followed by consolidation immunotherapy. Declarations Ethics approval and consent to participate This research was conducted in accordance with the Declaration of Helsinki. The ethics of this study was approved by the Ethics Committee of Taizhou Hospital, and an application for waiver of informed consent has been made. (K20250471). Consent for publication All the authors of the manuscript has been informed and agrees to the terms as outlined in the contract. Availability of data and materials Original contributions presented in the study are included in the article/Supplementary materials. For further inquiries during the current study are available from the corresponding author: Haihua Yang, [email protected] . Competing interests The authors declare no competing interests. Funding This work was supported by Medicine and Health Science and Technology Project of Zhejiang Province (2024KY1829) and Taizhou Anti-Cancer Association special research project (TACA2025-C01). Authors' contributions HH Y conceived and conceptualized the study, provided funding. HH Y and SN Z performed data review and analyses, reviewed and edited the manuscript. ZW S managed project execution, performed experimental design and data review and analyses, drafted the manuscript. JY D, ZH Z, M C, DD Z, LQ H, PJ G, J Z performed experimental design and execution. All authors reviewed the manuscript. References Sung H, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49. Aupérin A, et al. Meta-analysis of concomitant versus sequential radiochemotherapy in locally advanced non-small-cell lung cancer. J Clin Oncol. 2010;28(13):2181–90. Yamamoto N, et al. Phase III study comparing second- and third-generation regimens with concurrent thoracic radiotherapy in patients with unresectable stage III non-small-cell lung cancer: West Japan Thoracic Oncology Group WJTOG0105. J Clin Oncol. 2010;28(23):3739–45. Furuse K, et al. Phase III study of concurrent versus sequential thoracic radiotherapy in combination with mitomycin, vindesine, and cisplatin in unresectable stage III non-small-cell lung cancer. J Clin Oncol. 1999;17(9):2692–9. Bradley JD, et al. Long-Term Results of NRG Oncology RTOG 0617: Standard- Versus High-Dose Chemoradiotherapy With or Without Cetuximab for Unresectable Stage III Non-Small-Cell Lung Cancer. J Clin Oncol. 2020;38(7):706–14. Antonia SJ, et al. Durvalumab after Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. N Engl J Med. 2017;377(20):1919–29. Melillo G, et al. Curative-Intent Treatment with Durvalumab in Early-Stage Cancers. Adv Ther. 2021;38(6):2759–78. Spigel DR, et al. Five-Year Survival Outcomes From the PACIFIC Trial: Durvalumab After Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. J Clin Oncol. 2022;40(12):1301–11. Antonia SJ, et al. Overall Survival with Durvalumab after Chemoradiotherapy in Stage III NSCLC. N Engl J Med. 2018;379(24):2342–50. Ettinger DS, et al. NCCN Guidelines Insights: Non-Small Cell Lung Cancer, Version 1.2020. J Natl Compr Canc Netw. 2019;17(12):1464–72. Ettinger DS, et al. NCCN Guidelines® Insights: Non-Small Cell Lung Cancer, Version 2.2023. J Natl Compr Canc Netw. 2023;21(4):340–50. Faivre-Finn C, et al. Four-Year Survival With Durvalumab After Chemoradiotherapy in Stage III NSCLC-an Update From the PACIFIC Trial. J Thorac Oncol. 2021;16(5):860–7. Prelaj A, et al. Predictive biomarkers of response for immune checkpoint inhibitors in non-small-cell lung cancer. Eur J Cancer. 2019;106:144–59. Schuurbiers M et al. Biological and technical factors in the assessment of blood-based tumor mutational burden (bTMB) in patients with NSCLC. J Immunother Cancer, 2022. 10(2). Eisenhauer EA, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45(2):228–47. Meng Y, et al. Adaptive intensity-modulated radiotherapy with simultaneous integrated boost for stage III non-small cell lung cancer: Is a routine adaptation beneficial? Radiother Oncol. 2021;158:118–24. Zhou C, et al. CT-based radiomics nomogram may predict who can benefit from adaptive radiotherapy in patients with local advanced-NSCLC patients. Radiother Oncol. 2023;183:109637. Chen J, et al. Efficacy of immunotherapy in patients with oncogene-driven non-small-cell lung cancer: a systematic review and meta-analysis. Ther Adv Med Oncol. 2024;16:17588359231225036. Zhou S, Yang H. Immunotherapy resistance in non-small-cell lung cancer: From mechanism to clinical strategies. Front Immunol. 2023;14:1129465. Wang Y, et al. Real-World Safety and Efficacy of Consolidation Durvalumab After Chemoradiation Therapy for Stage III Non-small Cell Lung Cancer: A Systematic Review and Meta-analysis. Int J Radiat Oncol Biol Phys. 2022;112(5):1154–64. Wang Q, et al. Changes in T Lymphocyte Subsets in Different Tumors Before and After Radiotherapy: A Meta-analysis. Front Immunol. 2021;12:648652. Conroy MR, et al. Exploring the prognostic impact of absolute lymphocyte count in patients treated with immune-checkpoint inhibitors. BJC Rep. 2024;2(1):31. Liu A, et al. Two nomograms constructed for predicting the efficacy and prognosis of advanced non–small cell lung cancer patients treated with anti–PD–1 inhibitors based on the absolute counts of lymphocyte subsets. Cancer Immunol Immunother. 2024;73(8):152. Karantanos T, et al. The absolute lymphocyte count can predict the overall survival of patients with non-small cell lung cancer on nivolumab: a clinical study. Clin Transl Oncol. 2019;21(2):206–12. Zhou S, et al. The critical components for effective adaptive radiotherapy in patients with unresectable non-small-cell lung cancer: who, when and how. Future Oncol. 2022;18(31):3551–62. van Rossum PSN, et al. Severe radiation-induced lymphopenia during concurrent chemoradiotherapy for stage III non-small cell lung cancer: external validation of two prediction models. Front Oncol. 2023;13:1278723. Burnette B, Weichselbaum RR. Radiation as an immune modulator. Semin Radiat Oncol. 2013;23(4):273–80. Eckert F, et al. Impact of curative radiotherapy on the immune status of patients with localized prostate cancer. Oncoimmunology. 2018;7(11):e1496881. Ray-Coquard I, et al. Lymphopenia as a prognostic factor for overall survival in advanced carcinomas, sarcomas, and lymphomas. Cancer Res. 2009;69(13):5383–91. Casares N, et al. Caspase-dependent immunogenicity of doxorubicin-induced tumor cell death. J Exp Med. 2005;202(12):1691–701. Tian L, et al. Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming. Nature. 2017;544(7649):250–4. Zheng X, et al. Increased vessel perfusion predicts the efficacy of immune checkpoint blockade. J Clin Invest. 2018;128(5):2104–15. Li S, et al. Radiation drives tertiary lymphoid structures to reshape TME for synergized antitumour immunity. Expert Rev Mol Med. 2024;26:e30. Zhou C, et al. Expression and Clinical Significance of Lymphocyte Subpopulations and Peripheral Inflammatory Markers in Glioma. J Inflamm Res. 2024;17:9423–51. Additional Declarations No competing interests reported. Supplementary Files SupplTables.docx SuppFigure1.tif SuppFIigure2.tif 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6724206","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476295948,"identity":"00498157-39d3-47ba-bd32-55dee5b164ab","order_by":0,"name":"Zhenwei Sun","email":"","orcid":"","institution":"Shaoxing University, shaoxing","correspondingAuthor":false,"prefix":"","firstName":"Zhenwei","middleName":"","lastName":"Sun","suffix":""},{"id":476295949,"identity":"295670b6-d072-4ddd-831b-b23b05087b66","order_by":1,"name":"Jiayi Duan","email":"","orcid":"","institution":"Shaoxing University, shaoxing","correspondingAuthor":false,"prefix":"","firstName":"Jiayi","middleName":"","lastName":"Duan","suffix":""},{"id":476295951,"identity":"eccc0456-7387-454f-beac-366bfbf4eede","order_by":2,"name":"Zhaohao Zhang","email":"","orcid":"","institution":"Hangzhou Medical College","correspondingAuthor":false,"prefix":"","firstName":"Zhaohao","middleName":"","lastName":"Zhang","suffix":""},{"id":476295953,"identity":"38efe7b6-1d50-49d2-a72d-9cda186d7eee","order_by":3,"name":"Meng Chen","email":"","orcid":"","institution":"Enze Hospital, Taizhou","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Chen","suffix":""},{"id":476295955,"identity":"34b469e7-93ac-428a-aebc-58e8b9e80035","order_by":4,"name":"Dandan Zhou","email":"","orcid":"","institution":"Enze Hospital, Taizhou","correspondingAuthor":false,"prefix":"","firstName":"Dandan","middleName":"","lastName":"Zhou","suffix":""},{"id":476295957,"identity":"eda9f99d-d855-404e-8e23-5525aaf32668","order_by":5,"name":"Liqiao Hou","email":"","orcid":"","institution":"Zhejiang Taizhou Hospital, Linhai","correspondingAuthor":false,"prefix":"","firstName":"Liqiao","middleName":"","lastName":"Hou","suffix":""},{"id":476295960,"identity":"0ff7aaa0-a742-4471-b53e-79dc61e18bbb","order_by":6,"name":"Pingjun Gu","email":"","orcid":"","institution":"Zhejiang Taizhou Hospital, Linhai","correspondingAuthor":false,"prefix":"","firstName":"Pingjun","middleName":"","lastName":"Gu","suffix":""},{"id":476295962,"identity":"3c8a3b81-e534-422a-ad3c-967fd783530f","order_by":7,"name":"Jian Zhu","email":"","orcid":"","institution":"Zhejiang Taizhou Hospital, Linhai","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Zhu","suffix":""},{"id":476295963,"identity":"0f1634c5-ddc6-4740-bfb7-1114b701f344","order_by":8,"name":"Suna Zhou","email":"","orcid":"","institution":"Enze Hospital, Taizhou","correspondingAuthor":false,"prefix":"","firstName":"Suna","middleName":"","lastName":"Zhou","suffix":""},{"id":476295964,"identity":"950f5abc-8e22-4821-96c8-67a583bee130","order_by":9,"name":"Haihua Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYDACCR7Ghx8MbHj4JSBcGWK0MBtLFKTJSM5gYGwAcYnRwibB8+GwjcENsBYGwloMbvcek5AwSOMxvt18/NGNGgseBvbDRzfg1XLnXLJFAdAvZneOJTbnHAM6jCct7QZeLTdyDG+AbDEDMppzgI4EOtWMkBYDCR6DwzzGM0Ba/hGnxQisxUACqCW3jQgtkjdyjI1BDpO4kZY4O7cPGICE/MIH9MLDD39s7PlnJB/4nPOtTo6f/fAxvFoUDqCLsOFTDgLyDYRUjIJRMApGwSgAAGfMRvWBKedsAAAAAElFTkSuQmCC","orcid":"","institution":"Zhejiang Taizhou Hospital, Linhai","correspondingAuthor":true,"prefix":"","firstName":"Haihua","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-05-22 10:53:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6724206/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6724206/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85754762,"identity":"1d63db90-bbe8-4245-8fbd-59b3324ca197","added_by":"auto","created_at":"2025-07-01 10:39:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1659620,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/c7b5bdfe249126876c09c318.png"},{"id":85753398,"identity":"5c05ad4c-ef23-42b2-b03b-3fb373377213","added_by":"auto","created_at":"2025-07-01 10:31:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1395186,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/96eaeec41842ca58dd39309b.png"},{"id":85753400,"identity":"d030a46d-b312-4eee-8051-65699446ede0","added_by":"auto","created_at":"2025-07-01 10:31:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":637769,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/92f552d74a23cf2f19d7e50d.png"},{"id":85753404,"identity":"8094f21c-8d69-47cd-a693-fe4fedbe0c59","added_by":"auto","created_at":"2025-07-01 10:31:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1613157,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/2fb41942d019617edbaa4f76.png"},{"id":87485041,"identity":"1c0ceaf9-884a-4ccd-b321-a4674b345a0a","added_by":"auto","created_at":"2025-07-24 10:46:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6353298,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/7528fa05-587c-4801-a304-1d0be6eb6e6c.pdf"},{"id":85753397,"identity":"209db433-7561-4f4f-a4ed-973ffc4dccaa","added_by":"auto","created_at":"2025-07-01 10:31:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":43084,"visible":true,"origin":"","legend":"","description":"","filename":"SupplTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/a7b5cbfc0a6e65aef1ddc532.docx"},{"id":85753422,"identity":"b862bf42-5255-41cf-8759-7e349411cc49","added_by":"auto","created_at":"2025-07-01 10:31:51","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":8533496,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/e05c030b7bff0069d2a00303.tif"},{"id":85753425,"identity":"919513c1-5574-43ac-9289-41ac3bc7223e","added_by":"auto","created_at":"2025-07-01 10:31:52","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":17311172,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFIigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-6724206/v1/1d26e2f302ad9b169bb2dd9f.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effectiveness and mechanism of lymphocytes at different periods in predicting consolidation immunotherapy following adaptive chemoradiotherapy in LA-NSCLC","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer is primarily driven by non-small cell lung cancer (NSCLC), which accounts for 80\u0026ndash;85% of all instances[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], Approximately 20\u0026ndash;30% of patients are diagnosed at stage III., of which 60\u0026ndash;90% are unresectablestages[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. For patients with unresectable locally advanced non-small cell lung cancer (LA-NSCLC), concurrent chemoradiation therapy (cCRT) has long been the standard approach. Nevertheless, the long-term efficacy of cCRT remains unsatisfactory, with 5-year survival rates typically between 15% and 30%.[\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].The therapeutic options available to radiation oncologists for treating LA-NSCLC have significantly expanded since the PACIFIC trial reported its practice-changing results in 2017[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].This randomized, double-blind, placebo-controlled Phase III study enrolled patients with unresectable Stage III NSCLC and investigated the use of durvalumab as a consolidation therapy\u0026mdash;a programmed death-ligand 1 (PD-L1) immune checkpoint inhibitor (ICI)\u0026mdash;following curative-intent concurrent chemoradiation therapy (cCRT)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The median follow-up duration was 34.2 months, the most recent survival analyses revealed that consolidation durvalumab achieved that the 5-year overall survival (OS) rate was 42.9%, and the progression-free survival (PFS) rate was 33.1%..[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The PACIFIC trial demonstrated that consolidation durvalumab following CRT (the PACIFIC regimen) provides substantial and durable survival benefits compared to CRT alone, further establishing its role as the new standard of care in this setting.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In a global multicenter, phase Ⅱ, open-label, multi-cohort, non-randomized controlled clinical trial, KEYNOTE⁃799 study, it was shown that pembrolizumab combined with concurrent chemoradiotherapy had good anti-tumor activity and controllable safety in Individuals with newly diagnosed locally advanced stage III NSCLC.too.\u003c/p\u003e \u003cp\u003eAlthough PACIFIC regimen improves the efficacy of NSCLC, there are still some patients with poor efficacy. The use of biomarkers to anticipate the outcomes of immunotherapy has seen a notable rise. Central to this approach are markers such as programmed death-ligand 1 (PD-L1), blood-derived tumor mutation burden (bTMB), microsatellite instability (MSI), mechanisms involved in DNA repair (DDR), and lymphocytes present within tumor tissues (TILs).[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, due to the changes in immune microenvironment and biomarkers after radiotherapy, it is necessary to further explore the predictive markers of immune consolidation at different stages. Invasive biopsy after radiotherapy limits the prediction of some markers, and the prediction of blood lymphocytes seems to be more feasible. Thus, identifying more effective approaches to predict immunotherapy efficacy is of paramount importance.\u003c/p\u003e \u003cp\u003eThis study retrospectively analyzed the effect of blood lymphocytes at different stages in predicting immune consolidation following adaptive chemoradiotherapy in NSCLC. Furthermore, by analyzing the changes of lymphocyte subsets before and after chemoradiotherapy, the mechanism by which the changes of systemic immune microenvironment after radiotherapy can predict the efficacy was preliminarily elucidated.\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients selection\u003c/h2\u003e \u003cp\u003eOur study involved an examination of the medical histories of NSCLC patients at Taizhou Hospital, Zhejiang Province, China, from December 1, 2018, to July 31, 2024. Inclusion criteria comprised: (1) age range of 18 to 80 years; (2) possession of complete electronic health records, including absolute lymphocyte counts (ALCs); (3) pathologically verified NSCLC; (4) presence of clinically unresectable stage III cancer; (5) an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1 at baseline, alongside a projected survival of six months or more; and (6) administration of at least two cycles of anti-PD-1 inhibitor therapy. In addition, patients who met the following exclusion criteria were excluded: (1) NSCLC with uncertain diagnosis; (2) combined with other malignant tumors; (3) missing clinical data; (4) underlying diseases, such as acute infections, hematological diseases, autoimmune diseases, pregnancy or lactation.The study endpoints were OS and PFS; (5) Genetic alterations in the epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) were identified. The therapeutic impact of anti-PD-1 inhibitors was measured using computed tomography (CT) or magnetic resonance imaging (MRI), in accordance with the Response Evaluation Criteria in Solid Tumors (RECIST v1.1).[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe Medical record data of the patients were collected. Demographic information (age, gender), smoking history, histological type, lymph node metastasis, clinical stage, treatment method (concurrent chemoradiotherapy or sequential chemoradiotherapy), progression-free survival (PFS), overall survival (OS), and ALCS before radiotherapy, during radiotherapy (20th radiotherapy), and 1 month after radiotherapy (before immunotherapy) were collected. Immunological parameters (counts ofCD4+, CD8+, CD8/CD4) were also collected before and 1 month after radiotherapy.\u003c/p\u003e\n\u003ch3\u003eTreatment\u003c/h3\u003e\n\u003cp\u003eAll patients received radical radiotherapy through conventional fractionated simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT). Initial and mid-treatment radiotherapy planning was based on conventional CT or four-dimensional CT simulation with a slice thickness of \u0026le;\u0026thinsp;5 mm. PET/CT was occasionally used before treatment but was not routinely employed for staging and target delineation. To minimize systematic errors caused by inter-fractional geometric displacement, megavoltage orthogonal portal imaging or CBCT was used routinely. Each patient underwent one plan adaptation after The first 20 fractions of radiotherapy were prescribed at 2.14\u0026ndash;2.2 Gy per fraction to the planning gross tumor volume (PGTV). The planning treatment volume (PTV) received 54 Gy in 30 fractions, with a total dose of 64\u0026ndash;66 Gy. After 20F of radiotherapy, the CT was repositioned and the plan was replanned.Platinum-based doublet chemotherapy was the preferred concurrent regimen, although sequential chemotherapy or radiotherapy alone was considered for patients intolerant to concurrent treatment.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. All patients received chemoradiotherapy or sequential chemoradiotherapy, followed by consolidation immunotherapy with intravenous sintilimab at a dose of 200 mg every 3 weeks.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eOverall survival was the primary end point of this study. The secondary end point was progression-free survival.Descriptive statistics were applied to detail the features of the patients.. For this analysis, progression-free survival (PFS) was determined as the duration from the first dose of immunotherapy to the time of tumor recurrence, death due to any reason, or censoring at the last follow-up. Overall survival (OS) was measured from the start of immunotherapy until the patient's death or the conclusion of the follow-up period.Paired sample T-tests were used to assess changes in absolute lymphocyte counts at different time points.Cox proportional hazards regression analyses (both univariate and multivariate) were used to examine the relationship between the absolute value of lymphocytes at different periods and PFS and OS. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff values for lymphocytes at different time points. Continuous variables are reported in terms of mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or as median values, and categorical variables are displayed as frequencies along with percentages. The chi-square test was employed to compare categorical variables between the two groups.Categorical variables are presented as frequencies and percentages. The chi-square test was used to compare categorical variables between the two groups.The study employed the K-M survival analysis method to analyze patients' progression-free survival and overall survival.Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data analysis was performed using SPSS 25.0 (Armonk, New York, USA) and GraphPad Prism 8.0 (San Diego, California, USA) software.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatients characteristics:\u003c/h2\u003e \u003cp\u003eA total of 139 NSCLC patients were enrolled according to the inclusion criteria. The median age was 69 years (48\u0026ndash;80 years). There were 132 males (95.0%). 108 patients (70.5%) had a history of smoking. Histologically, 117 cases (84.17%) were squamous carcinoma, 13 cases (9.35%) were adenocarcinoma, and Other types, including large cell carcinoma and adenosquamous carcinoma. There were 102 cases (73.38) with ECOG score of 0 (6.47%). According to TNM staging, 48 cases (34.53%) were stage ⅢA, 69 cases (49.64%) were stage ⅢB, and 22 cases (15.83%) were stage ⅢC. Seventy-six patients (54.68%) received sequential chemoradiotherapy and 63 patients (45.32%) received concurrent chemoradiotherapy. Baseline characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;139)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.00 (48, 80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132 (94.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eECOG\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (73.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (26.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (70.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (29.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eT\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (11.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (22.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (17.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (48.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (14.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (56.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (29.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eⅢA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (34.53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eⅢB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (49.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eⅢC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (15.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePathologic\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSquamous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (84.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdenocarcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (9.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTherapy Method\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConcurrent Chemoradiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (45.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSequential Chemoradiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (54.68)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALCS before RT (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALCS of 20th fraction during RT (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALCS of 1month after RT (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDecreased lymphocytes (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eElevated lymphocytes (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eECOG:The Eastern Cooperative Oncology Group Performance Status (ECOG) score. ALCS: absolute lymphocyte counts.RT: radiotherapy. SD: standard deviation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eChanges of ALCS in different periods\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe ALCS were 1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u0026times;10\u003csup\u003e9\u003c/sup\u003ebefore radiotherapy, the 20th fraction of radiotherapy were 0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u0026times;10\u003csup\u003e9\u003c/sup\u003e, and 1 month after radiotherapy were 1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u0026times;10\u003csup\u003e9\u003c/sup\u003e,respectively. The ALCS differencesFrom before radiotherapy to 20th fraction radiotherapy were 0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u0026times;10\u003csup\u003e9\u003c/sup\u003e and increase from 20th fraction radiotherapy to 1 month after radiotherapy were 0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u0026times;10\u003csup\u003e9\u003c/sup\u003e, respectively. There were significant differences to the ALCS decrease from before radiotherapy to 20th fraction radiotherapy and increase from 20th fraction radiotherapy to one month following radiotherapy (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCorrelation of ACLS with PFS\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eVariables such as treatment method, gender, age, smoking status, TNM stage, ECOG score, histological type, ALCS before radiotherapy, ALCS at 20th fraction of radiotherapy, ALCS at 1 month after radiotherapy, ALCS decrease, and ALCS increase were included in univariate analysis. In Suppl Table\u0026nbsp;1, all were not associated with PFS. And that the ALCS\u0026thinsp;\u0026gt;\u0026thinsp;1.015\u0026times;10\u003csup\u003e9\u003c/sup\u003e at 1 month after radiotherapy and decrease ALCS\u0026thinsp;\u0026gt;\u0026thinsp;0.71\u0026times;10\u003csup\u003e9\u003c/sup\u003e and increase ALCS\u0026thinsp;\u0026gt;\u0026thinsp;0.305\u0026times;10\u003csup\u003e9\u003c/sup\u003ewere no difference with PFS (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in Fig.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCorrelation between ACLS and OS\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe results in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, In our univariate analysis, the ALCS at one month following radiotherapy, the decrease or increase ALCScorrelated with enhanced overall survival (OS). (P\u0026thinsp;\u0026lt;\u0026thinsp;0.045; P\u0026thinsp;=\u0026thinsp;0.038; P\u0026thinsp;=\u0026thinsp;0.006). Multivariate analysis showed that the ALCS at 1 month after radiotherapy, decreased or increased ALCScould serve as independent predictors for significantly improved OS.(OR0.44, 95%CI 0.20\u0026ndash;0.97, P\u0026thinsp;\u0026lt;\u0026thinsp;0.041; OR 0.46 95%ci (0.22\u0026ndash;0.97), p\u0026thinsp;=\u0026thinsp;0.041; OR 95%CI0.33 (0.15\u0026ndash;0.72), p\u0026thinsp;=\u0026thinsp;0.005).\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 multivariate cox analysis was used to analyze overall survival.\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=\"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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.93\u0026thinsp;~\u0026thinsp;1.00)\u003c/p\u003e \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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.45 (0.31\u0026thinsp;~\u0026thinsp;6.76)\u003c/p\u003e \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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eECOG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62 (0.27\u0026thinsp;~\u0026thinsp;1.43)\u003c/p\u003e \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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.65 (0.74\u0026thinsp;~\u0026thinsp;3.69)\u003c/p\u003e \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\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.26\u0026thinsp;~\u0026thinsp;3.20)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 (0.22\u0026thinsp;~\u0026thinsp;3.12)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85 (0.28\u0026thinsp;~\u0026thinsp;2.64)\u003c/p\u003e \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\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.24\u0026thinsp;~\u0026thinsp;1.84)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96 (0.32\u0026thinsp;~\u0026thinsp;2.86)\u003c/p\u003e \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\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eⅢA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eⅢB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.52\u0026thinsp;~\u0026thinsp;2.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.26 (0.56\u0026thinsp;~\u0026thinsp;2.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eⅢC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93 (0.32\u0026thinsp;~\u0026thinsp;2.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95 (0.30\u0026thinsp;~\u0026thinsp;2.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePathologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSquamous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003eAdenocarcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58 (0.10\u0026thinsp;~\u0026thinsp;3.40)\u003c/p\u003e \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=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58 (0.18\u0026thinsp;~\u0026thinsp;1.85)\u003c/p\u003e \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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTherapy Method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConcurrent Chemoradiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSequential Chemoradiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 (0.55\u0026thinsp;~\u0026thinsp;2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.31 (0.62\u0026thinsp;~\u0026thinsp;2.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALCS before RT(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66 (0.33\u0026thinsp;~\u0026thinsp;1.34)\u003c/p\u003e \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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALCS of 20th fraction during RT(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.01(0.86\u0026thinsp;~\u0026thinsp;10.54)\u003c/p\u003e \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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eALCS of 1month after RT(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46 (0.21\u0026thinsp;~\u0026thinsp;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44(0.20\u0026thinsp;~\u0026thinsp;0.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDecreased lymphocytes(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45 (0.22\u0026thinsp;~\u0026thinsp;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46(0.22\u0026thinsp;~\u0026thinsp;0.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eElevated lymphocytes(10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34 (0.16\u0026thinsp;~\u0026thinsp;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33(0.15\u0026thinsp;~\u0026thinsp;0.72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eECOG:The Eastern Cooperative Oncology Group Performance Status (ECOG) score. ALCS: absolute lymphocyte counts. RT: radiotherapy. OR: Odds Ratio. CI: confidence interval.\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\u003eThe best cut-off values of ALCS at 1 month after radiotherapy(1.015\u0026times;10\u003csup\u003e9\u003c/sup\u003e), decrease ALCS (0.71\u0026times;10\u003csup\u003e9\u003c/sup\u003e), and increase ALCS (0.305\u0026times;10\u003csup\u003e9\u003c/sup\u003e) were obtained by ROC curve using spss software, as shown in Supp Fig.\u0026nbsp;1. The baseline characteristics of the two groups were compared to confirm the comparability (Suppl Tables\u0026nbsp;2, 3, and 4).The ALCS\u0026thinsp;\u0026gt;\u0026thinsp;1.015\u0026times;10\u003csup\u003e9\u003c/sup\u003e at 1 month after radiotherapy and decrease ALCS\u0026thinsp;\u0026gt;\u0026thinsp;0.71\u0026times;10\u003csup\u003e9\u003c/sup\u003e and increase ALCS\u0026thinsp;\u0026gt;\u0026thinsp;0.305\u0026times;10\u003csup\u003e9\u003c/sup\u003e achieved better OS (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in Fig.\u0026nbsp;2.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChanges of lymphocyte subsets before and 1 month after radiotherapy\u003c/h3\u003e\n\u003cp\u003eA total of 39 patients were tested for lymphocyte subsets before and 1 month after radiotherapy. The absolute counts of CD4 and CD8 and CD8/CD4 were before and one month following radiotherapy, respectively. And, there were significant differences before and 1 month after radiotherapy (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in Fig.\u0026nbsp;3.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRelationship between changes in lymphocyte subsets and OS.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSpss software was used to draw ROC curves to obtain the best cut-off values. CD4, CD8, and CD8/CD4 before RT were 605/\u0026micro;L、538/\u0026micro;L、0.79 and 1 month after RT were 140.5/\u0026micro;L、230/\u0026micro;L、1.168, respectively, as shown in Suppl Fig.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eKaplan-Meier survival curves are shown in an absolute CD8 lymphocyte count of \u0026gt;\u0026thinsp;230/\u0026micro;L at 1 month after radiotherapy and CD4 lymphocytes decreased\u0026thinsp;\u0026lt;\u0026thinsp;6/\u0026micro;Lat 1 month after radiotherapy have better OS (Fig.\u0026nbsp;4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe emergence of immune checkpoint inhibitors (ICIs) in recent years has dramatically altered the treatment paradigm for NSCLC patients across the globe[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Nevertheless, the response to anti-PD-1 inhibitor therapy has been inconsistent in NSCLC patients[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. As a result, determining which patients are most likely to respond favorably to anti-PD-1 inhibitors has surfaced as a major challenge.Yu Wang et al. reported that the median interval from the completion of concurrent chemoradiotherapy (CRT) to the initiation of durvalumab in real-world studies (RWSs) often surpassed 42 days, a notable deviation from the PACIFIC study protocol, which specified a maximum interval of 42 days.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The main reason is the delay of immune maintenance therapy due to adverse reactions. Moreover, changes in the collective immune microenvironment after chemoradiotherapy require a simple and convenient predictor. Lymphocytes, which constitute approximately 30% of the total white blood cells in healthy individuals, are among the most radiation-sensitive cell subsets and play a crucial role as effector cells in anti-tumor immunity.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. As a reflection of the host's immune status, lymphocyte levels are closely linked to the response to immune checkpoint inhibitors and the overall survival rates in melanoma patients.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. One study have shown that ALCS is associated with the prognosis of a variety of malignant tumors, including NSCLC. Low ALCS is associated with poor prognosis of a variety of cancers, including lung, breast, and colorectal cancer[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].A clinical study showed that ALCS can predict overall survival in NSCLC patients treated with nivolumab. And, ALCS values at the start of treatment and after three months, as well as changes in ALCS, are all considered dynamic biomarkers that can predict the effect of ICI treatment[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdaptive radiotherapy (ART) is an image-guided technique for treating tumors. Patients with non-small-cell lung cancer (NSCLC) who have large tumor lesions and high radiosensitivity are particularly well-suited for ART. The radiotherapy period of 30\u0026ndash;50 Gy delivered in 15\u0026ndash;25 fractions may represent the optimal timing for implementing ART[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Our earlier research indicated that gross tumor volumes (GTVs) diminished by a median of 38.2% after receiving 42\u0026ndash;44 Gy of radiotherapy in 20 fractions. By accommodating tumor and anatomical shifts, dosimetric parameters for organs at risk (OARs) were notably reduced. Specifically,The results showed that the average irradiation dose to the lungs decreased by 74.8 cGy, and the average dose to the esophagus was reduced by 183.1 cGy.Moreover, adaptive adjustments were found to decrease the probability of RP2 by 3 percentage points and the risk of RE2 by 5 percentage points.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, the trajectory of absolute lymphocyte counts (ALCs) during radiotherapy exhibited a general downward trend.And, the ALCS level increased gradually after radiotherapy. In our study, In 20 fractions of adaptive radiotherapy, the ALCS was reduced to 0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u0026times;10\u003csup\u003e9\u003c/sup\u003e, which was reduced by 0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u0026times;10\u003csup\u003e9\u003c/sup\u003e. One month after radiotherapy, it increased to 1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u0026times;10\u003csup\u003e9\u003c/sup\u003e and increased by 0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u0026times;10\u003csup\u003e9\u003c/sup\u003e。But, in van Rossum PSN, et al studies, At the fourth week, the ALCS decreased to 0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u0026times;10\u003csup\u003e9\u003c/sup\u003e, a decrease of 0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u0026times;10\u003csup\u003e9\u003c/sup\u003e.This reduction seems to be slightly lower compared with van Rossum, P.S.N.et al. report[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which may be related to the reduction of the range of irradiation by our adaptive radiotherapy and thus the reduction of the degree of lymphocyte reduction. This result needs further study in the future.\u003c/p\u003e \u003cp\u003eIn our study, univariate analysis and Multivariate analysis showed that theALCS at 1 month after radiotherapy, decreased or increased ALCS were independent prognostic factors for significantly improved OS. ALCS\u0026thinsp;\u0026gt;\u0026thinsp;1.015\u0026times;10\u003csup\u003e9\u003c/sup\u003e at 1 month after radiotherapy but not before radiotherapy achieved better OS (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This suggests that RT has a potential effect on the proliferation and activation of lymphocytes[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].Although radiotherapy has an immuno-stimulatory effect by inducing neoantigens and danger signals for immune activation[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], It also exerts immunosuppressive effects, such as lymphopenia. However, the extent of this effect hinges on the timing of blood sampling and the timing of lymphodepletion. Some studies have documented that these changes can recover within 2, 3, 6 months, and up to 1 year post-treatment.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Eckert et al. observed that, during radiotherapy (RT), all immune cell subgroups, excluding Tregs, exhibited elevated proliferation rates, which normalized approximately three months post-treatment.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].There are no studies to prove the extent to which lymphocytes can be recovered to continue consolidation immunotherapy. Radiotherapy and immunotherapy also exhibit synergistic effects. Radiotherapy can enhance the efficacy of immunotherapy against tumors by promoting the release of damage-associated molecular patterns (DAMPs) and tumor-associated antigens (TAAs).optimizing the tumor immune microenvironment, and creating a hypoxic environment leading to hypoxia of tumor cells. ICI coincidentally can eliminate radiation resistance caused by radiotherapy. Some studies have shownthat ICI can not only release T cells to attack tumor cells[\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], but also normalize tumor blood vessels to regulate the tumor microenvironment, thereby increasing radiosensitivity.The mechanism of synergistic effect of radiotherapy and immunotherapy needs further study[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe found that patients with stage III non-small cell lung cancer, in chemoradiotherapy combined with immunotherapy, the ALCS decreased during radiotherapy and was partially recovered 1 month after radiotherapy. And, CD4、CD8、CD8/CD4 lymphocytes also showed a downward trend before and after radiotherapy, and CD4 decreased more significantly. The absolute CD8 lymphocyte count of \u0026gt;\u0026thinsp;230 \u003cb\u003e/\u0026micro;L\u003c/b\u003eat 1 month after radiotherapy and CD4 lymphocytes decreased\u0026thinsp;\u0026lt;\u0026thinsp;6 \u003cb\u003e/\u003c/b\u003e\u0026micro;L at 1 month after radiotherapy have better OS. Inone study, the levels of CD3+,CD4+,CD4+/CD8\u0026thinsp;+\u0026thinsp;and CD19\u0026thinsp;+\u0026thinsp;in peripheral blood of lung cancer patients before radiotherapy were significantly lower than those of the control group (P\u0026lt;0.05)[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This is consistent with our conclusion. The effect of radiotherapy on the immune microenvironment is seemingly a double-edged sword. On the one hand, it can activate anti-tumor immune promotion effect, and on the other hand, it kills lymphocytes and produces immunosuppression. However, radiotherapy kills tumor resistant immune cells, recovers the immune microenvironment. And the growth of CD8\u0026thinsp;+\u0026thinsp;T cells is faster than that of CD4\u0026thinsp;+\u0026thinsp;T cells, resulting in increased CD8/CD4, which may improve the efficacy of immunotherapy.This result needs to be further confirmed by prospective clinical studies.\u003c/p\u003e \u003cp\u003eThe primary limitation of this study is its single-center retrospective design and limited sample size, which may introduce potential information bias. Therefore, to further validate our results, a prospective study across multiple centers with a larger cohort is required. Moreover, further study requires analysis of a more diverse array of lymphocyte sub-types, extending beyond just CD8\u0026thinsp;+\u0026thinsp;or CD4\u0026thinsp;+\u0026thinsp;cells. Another future focus may be weather a directional intervention on lymphocyte levels can enhance the survival benefits obtained from chemoradiotherapy followed by immunotherapy.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that the ACLS or CD8\u0026thinsp;+\u0026thinsp;T cell count of 1 month after chemoradiotherapy can act as effective prognostic predictors in patients with NSCLC who undergo chemoradiotherapy followed by consolidation immunotherapy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted in accordance with the Declaration of Helsinki. The ethics of this study was approved by the Ethics Committee of Taizhou Hospital, and an application for waiver of informed consent has been made. (K20250471).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors of the manuscript has been informed and agrees to the terms as outlined in the contract.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOriginal contributions presented in the study are included in the article/Supplementary materials. For further inquiries during the current study are available from the corresponding author: Haihua Yang, [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Medicine and Health Science and Technology Project of Zhejiang Province (2024KY1829) and Taizhou Anti-Cancer Association special research project (TACA2025-C01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHH Y conceived and conceptualized the study, provided funding. HH Y and SN Z performed data review and analyses, reviewed and edited the manuscript. ZW S \u0026nbsp;managed project execution, performed experimental design and data review and analyses, drafted the manuscript. JY D, ZH Z, M C, DD Z, LQ H, PJ G, J Z \u0026nbsp;performed experimental design and execution. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAup\u0026eacute;rin A, et al. Meta-analysis of concomitant versus sequential radiochemotherapy in locally advanced non-small-cell lung cancer. J Clin Oncol. 2010;28(13):2181\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamamoto N, et al. Phase III study comparing second- and third-generation regimens with concurrent thoracic radiotherapy in patients with unresectable stage III non-small-cell lung cancer: West Japan Thoracic Oncology Group WJTOG0105. J Clin Oncol. 2010;28(23):3739\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuruse K, et al. Phase III study of concurrent versus sequential thoracic radiotherapy in combination with mitomycin, vindesine, and cisplatin in unresectable stage III non-small-cell lung cancer. J Clin Oncol. 1999;17(9):2692\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBradley JD, et al. Long-Term Results of NRG Oncology RTOG 0617: Standard- Versus High-Dose Chemoradiotherapy With or Without Cetuximab for Unresectable Stage III Non-Small-Cell Lung Cancer. J Clin Oncol. 2020;38(7):706\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntonia SJ, et al. Durvalumab after Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. N Engl J Med. 2017;377(20):1919\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelillo G, et al. Curative-Intent Treatment with Durvalumab in Early-Stage Cancers. Adv Ther. 2021;38(6):2759\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpigel DR, et al. Five-Year Survival Outcomes From the PACIFIC Trial: Durvalumab After Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. J Clin Oncol. 2022;40(12):1301\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntonia SJ, et al. Overall Survival with Durvalumab after Chemoradiotherapy in Stage III NSCLC. N Engl J Med. 2018;379(24):2342\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEttinger DS, et al. NCCN Guidelines Insights: Non-Small Cell Lung Cancer, Version 1.2020. J Natl Compr Canc Netw. 2019;17(12):1464\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEttinger DS, et al. NCCN Guidelines\u0026reg; Insights: Non-Small Cell Lung Cancer, Version 2.2023. J Natl Compr Canc Netw. 2023;21(4):340\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFaivre-Finn C, et al. Four-Year Survival With Durvalumab After Chemoradiotherapy in Stage III NSCLC-an Update From the PACIFIC Trial. J Thorac Oncol. 2021;16(5):860\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrelaj A, et al. Predictive biomarkers of response for immune checkpoint inhibitors in non-small-cell lung cancer. Eur J Cancer. 2019;106:144\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchuurbiers M et al. Biological and technical factors in the assessment of blood-based tumor mutational burden (bTMB) in patients with NSCLC. J Immunother Cancer, 2022. 10(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEisenhauer EA, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45(2):228\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeng Y, et al. Adaptive intensity-modulated radiotherapy with simultaneous integrated boost for stage III non-small cell lung cancer: Is a routine adaptation beneficial? Radiother Oncol. 2021;158:118\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou C, et al. CT-based radiomics nomogram may predict who can benefit from adaptive radiotherapy in patients with local advanced-NSCLC patients. Radiother Oncol. 2023;183:109637.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen J, et al. Efficacy of immunotherapy in patients with oncogene-driven non-small-cell lung cancer: a systematic review and meta-analysis. Ther Adv Med Oncol. 2024;16:17588359231225036.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou S, Yang H. Immunotherapy resistance in non-small-cell lung cancer: From mechanism to clinical strategies. Front Immunol. 2023;14:1129465.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, et al. Real-World Safety and Efficacy of Consolidation Durvalumab After Chemoradiation Therapy for Stage III Non-small Cell Lung Cancer: A Systematic Review and Meta-analysis. Int J Radiat Oncol Biol Phys. 2022;112(5):1154\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Q, et al. Changes in T Lymphocyte Subsets in Different Tumors Before and After Radiotherapy: A Meta-analysis. Front Immunol. 2021;12:648652.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConroy MR, et al. Exploring the prognostic impact of absolute lymphocyte count in patients treated with immune-checkpoint inhibitors. BJC Rep. 2024;2(1):31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu A, et al. Two nomograms constructed for predicting the efficacy and prognosis of advanced non\u0026ndash;small cell lung cancer patients treated with anti\u0026ndash;PD\u0026ndash;1 inhibitors based on the absolute counts of lymphocyte subsets. Cancer Immunol Immunother. 2024;73(8):152.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarantanos T, et al. The absolute lymphocyte count can predict the overall survival of patients with non-small cell lung cancer on nivolumab: a clinical study. Clin Transl Oncol. 2019;21(2):206\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou S, et al. The critical components for effective adaptive radiotherapy in patients with unresectable non-small-cell lung cancer: who, when and how. Future Oncol. 2022;18(31):3551\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Rossum PSN, et al. Severe radiation-induced lymphopenia during concurrent chemoradiotherapy for stage III non-small cell lung cancer: external validation of two prediction models. Front Oncol. 2023;13:1278723.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurnette B, Weichselbaum RR. Radiation as an immune modulator. Semin Radiat Oncol. 2013;23(4):273\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEckert F, et al. Impact of curative radiotherapy on the immune status of patients with localized prostate cancer. Oncoimmunology. 2018;7(11):e1496881.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRay-Coquard I, et al. Lymphopenia as a prognostic factor for overall survival in advanced carcinomas, sarcomas, and lymphomas. Cancer Res. 2009;69(13):5383\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasares N, et al. Caspase-dependent immunogenicity of doxorubicin-induced tumor cell death. J Exp Med. 2005;202(12):1691\u0026ndash;701.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian L, et al. Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming. Nature. 2017;544(7649):250\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng X, et al. Increased vessel perfusion predicts the efficacy of immune checkpoint blockade. J Clin Invest. 2018;128(5):2104\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi S, et al. Radiation drives tertiary lymphoid structures to reshape TME for synergized antitumour immunity. Expert Rev Mol Med. 2024;26:e30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou C, et al. Expression and Clinical Significance of Lymphocyte Subpopulations and Peripheral Inflammatory Markers in Glioma. J Inflamm Res. 2024;17:9423\u0026ndash;51.\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":"Lymphocytes, Lung cancer, Radiation therapy, Consolidation Immunotherapy","lastPublishedDoi":"10.21203/rs.3.rs-6724206/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6724206/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo explore The role of lymphocytes in prognosis and lymphocyte subsets at different stages of chemoradiotherapy and consolidation immunotherapy in patients with locally advanced non-small cell lung cancer (NSCLC).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e139 Patients with Stage IIINSCLC who received adaptive chemoradiotherapy and consolidation immunotherapy were retrospectively enrolled in the final analysis. A paired sample T-test was used to assess the difference among absolute lymphocyte counts (ACLS) and lymphocyte subsets of pre-/post-/during treatmentin different periods. Through the application of univariate and multivariate Cox proportional hazards regression analyses, the determinants influencing the periods of progression-free survival (PFS) and overall survival (OS) were established.The Kaplan-Meier method was used to evaluate the survival prognosis in patients grouped by OS-related independent predictive factors. the PFS and OS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere were statistically significant differences among ACLS of before radiotherapy, at the 20th fraction of adaptive radiotherapy, and at one month following radiotherapy, respectively(P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). According to univariate and multivariate analysis, ACLS at 1 month after radiotherapy, decreased lymphocyte(defined as the difference value of before radiotherapy and the 20th fraction of adaptive radiotherapy), and increased lymphocyte count(defined as the difference value of one month following radiotherapy. and the 20th fraction of adaptive radiotherapy) were identified as Independent predictors of OS ((P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). KM curve showed that patients with ACLS\u0026thinsp;\u0026gt;\u0026thinsp;1.015\u0026times;10\u003csup\u003e9\u003c/sup\u003e at one month following radiotherapy. ACLS with decreased value\u0026thinsp;\u0026gt;\u0026thinsp;0.71\u0026times;10\u003csup\u003e9\u003c/sup\u003e, or increase ACLS with increased value\u0026thinsp;\u0026gt;\u0026thinsp;0.305\u0026times;10\u003csup\u003e9\u003c/sup\u003e obtained longer OS. There were significant differences in CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;counts and CD8/CD4 between before and 1 month after radiotherapy (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). KM curve showed the longer OS in patients with the higher level of CD8\u0026thinsp;+\u0026thinsp;T cell at one month following radiotherapy. (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePatients with NSCLC who undergo chemoradiotherapy followed by consolidation immunotherapy exhibit longer OS when they have a higher level of ACLS or CD8\u0026thinsp;+\u0026thinsp;T cell counts at one month after chemoradiotherapy.\u003c/p\u003e","manuscriptTitle":"Effectiveness and mechanism of lymphocytes at different periods in predicting consolidation immunotherapy following adaptive chemoradiotherapy in LA-NSCLC","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 10:31:46","doi":"10.21203/rs.3.rs-6724206/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":"f6fc217f-8b94-4291-944b-ee2f35d4e027","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-24T10:38:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-01 10:31:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6724206","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6724206","identity":"rs-6724206","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}