---
title: "Timing of Neoadjuvant Immunotherapy and Chemotherapy Infusions in Operable NSCLC: Study Aim and Me"
id: "frontiers-in-immunology-17-impact-of-time-of-day-and-timing-interval-of-neoadjuvant-immunotherapy-and"
canonical_url: "https://medichelpline.com/clinical-feed/frontiers-in-immunology-17-impact-of-time-of-day-and-timing-interval-of-neoadjuvant-immunotherapy-and"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "Frontiers in Immunology"
source_url: "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1895311"
published_at: "2026-08-28T00:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Timing of Neoadjuvant Immunotherapy and Chemotherapy Infusions in Operable NSCLC: Study Aim and Me
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/frontiers-in-immunology-17-impact-of-time-of-day-and-timing-interval-of-neoadjuvant-immunotherapy-and
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** Frontiers in Immunology
- **Source URL:** [Original Journal Publication](https://www.frontiersin.org/articles/10.3389/fimmu.2026.1895311)
- **Published At:** 2026-08-28T00:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The source title reports a dual-center, retrospective study of **operable non–small cell lung cancer (NSCLC)** patients examining the impact of **time-of-day** and **timing interval** of **neoadjuvant immunotherapy** and chemotherapy infusions using the **inverse probability of treatment weighting** method. - The study design is described as retrospective and dual-center, implying patient records from two institutions were analyzed, but the source text provided here contains only site navigation and not the article content. - No numeric results, patient characteristics, treatment regimens, outcome measures, statistical results, or conclusions were available in the provided source content. - The title indicates the study used an observational causal-inference approach (inverse probability of treatment weighting) to adjust for confounding between treatment-timing exposures and outcomes; the provided content does not report covariates, balance diagnostics, or model details. - The emphasis on **time-of-day** and **timing interval** suggests the authors investigated circadian or scheduling effects on treatment efficacy or perioperative outcomes; however, the supplied material does not report which outcomes (e.g., pathologic response, survival, toxicity, surgical complications) were assessed. - Because the article text was not included, essential methodological details (eligibility criteria, sample size, infusion timing definitions, immunotherapy agents, chemotherapy regimens, follow-up duration) were not reported in the supplied source. - No statements about ethics approval, funding, conflicts of interest, or author affiliations were available in the content provided. - Users should consult the full article at the journal site for validated data, results, and clinical conclusions; the current summary cannot substitute for the primary report.
## Clinical Analysis & Structured Key Points
Frontiers | Impact of time-of-day and timing interval of neoadjuvant immunotherapy and chemotherapy infusions among patients with operable NSCLC using the inverse probability of treatment weighting method: a dual-center, retrospective study ORIGINAL RESEARCH article Front. Immunol. , 28 August 2026 Sec. Cancer Immunity and Immunotherapy Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1895311 Published in Frontiers in Immunology Cancer Immunity and Immunotherapy 7 impact factor 11.3 citescore Part of a Research Topic Neoadjuvant or perioperative immunotherapy in oncology: A new paradigm shift Submission open 3954 views 5 articles Editor & Reviewers Edited by M G Maria Grazia Vitale Reviewed by D L Duo Li F L Feitong Lei Outline Figures and Tables Figure 1 View in article Figure 2 View in article Figure 3 View in article Table 1 Clinical, radiologic, surgical and pathologic characteristics according to ≥75% (≥75% group) and <75% (<75% group) of patients who received neoadjuvant immunotherapy before 14:00 h. View in article Table 2 Univariable and multivariable Cox proportional hazards models for variables associated with disease-free survival and overall survival in the inverse probability of treatment weighting cohort. View in article ORIGINAL RESEARCH article Front. Immunol. , 28 August 2026 Sec. Cancer Immunity and Immunotherapy Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1895311 Impact of time-of-day and timing interval of neoadjuvant immunotherapy and chemotherapy infusions among patients with operable NSCLC using the inverse probability of treatment weighting method: a dual-center, retrospective study X Y Xiang-yang Yu 1 † W Z Wen-yu Zhai 2 † Z X Zheng-zheng Xia 3 † K M Kai Ma 1 B Z Bai-hua Zhang 1 X Y Xin Yu 1 S L Sheng-cheng Lin 1 X G Xiao-tong Guo 1 * Z Z Ze-rui Zhao 2 * Z Y Zhen-tao Yu 1 * 1. Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer, Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China 2. Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China 3. Department of Pharmacy, National Cancer Center/National Clinical Research Center for Cancer, Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China See more Article metrics View details Abstract Background: Although multiple studies have confirmed that adjusting the time-of-day (ToDA) of immunotherapy and timing interval (TI) of chemoimmunotherapy can improve long-term outcomes in patients with advanced non-small cell lung cancer (NSCLC), whether this model similarly improves survival among patients with operable NSCLC has not been reported. Patients and methods: This dual-center, retrospective study included adult patients who received neoadjuvant chemoimmunotherapy (neoCIT) for clinical stage T1-4N0-3M0 NSCLC between January 2019 and December 2024. The impact of the ToDA of neoadjuvant immunotherapy (neoIO) on the efficacy and safety were analyzed. In addition, the inverse probability of treatment weighting (IPTW)-weighted Cox regression model was used to compare disease-free survival (DFS) and overall survival (OS) between patients who received either ≥75% (≥75% group) or <75% (<75% group) of the neoIO administrations before 14:00 h. Results: A total of 168 consecutive patients with a median follow-up of 30.3 months were included, of whom 123 patients (73.2%) were in the ≥75% group. Neoadjuvant treatment-related adverse events (neoTRAEs) occurred in 47.6% of the patients, including 63 (51.2%) and 17 (37.8%) patients in the ≥75% and <75% groups, respectively ( P = 0.122). Pathologic complete response occurred in 31.7% of the patients in the ≥75% group and in 20.0% of those in the <75% group ( P = 0.177); major pathologic response occurred in 59.3% and 48.9%, respectively ( P = 0.300). According to the results of the IPTW-weighted univariate Cox analysis, patients in the <75% group had worse 3-year rates of DFS (77.1% vs. 77.9%; P = 0.065) and OS (68.3% vs. 89.1%; P = 0.033). These findings remained robust to multivariate Cox regression models (DFS: hazard ratio [HR]ffoo, 2.858; 95% confidence intervals [CIs]: 1.239-6.692; P = 0.014; and OS: HR, 7.625; 95% CIs: 1.112-52.272; P = 0.039). Additionally, a shorter mean TI of patients who received neoCIT infusions (<23.5 vs. ≥23.5 hours) emerged as an independent factor associated with better OS (HR, 0.143; 95% CIs, 0.024-0.875; P = 0.035). Conclusions: Although early infusions of most neoIO drugs did not affect safety or efficacy, it showed a potential trend toward improving long-term survival. The corresponding immune microenvironment and molecular mechanisms need further exploration to guide the design of future prospective clinical studies. 1 Introduction The circadian rhythm affects immune functions by regulating the time-of-day (ToDA)-dependent production and transportation of cytokines/chemokines, as well as immune cell proliferation and tissue/tumor microenvironment infiltration ( 1 – 3 ). Additionally, the expression of programmed death 1 (PD-1), the key targeted protein in the PD-1/PD-ligand 1 (PD-L1) pathway that mediates tumor immune escape, in immune cells exhibits clear diurnal oscillation ( 4 ). A growing body of preclinical and clinical studies have confirmed that leveraging the circadian rhythm of the immune system to adjust the ToDA of immune checkpoint inhibitor (ICI) administration in patients with solid tumors, including melanoma, upper gastrointestinal tumors, and renal, hepatocellular, and bladder carcinomas, could help reduce side effects and improve treatment efficacy ( 1 – 6 ). A recent large, international, multicenter, retrospective cohort study in patients with advanced non-small cell lung cancer (NSCLC) also confirmed that compared with afternoon administration, morning infusion of first-line immunotherapy significantly increased patients’ objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) ( 5 ). Currently, on the basis of the findings of multiple phase 3 randomized controlled trials (RCTs), the standard neoadjuvant therapy paradigm for resectable NSCLC without common driver gene mutations has shifted from chemotherapy alone to the combination of ICIs and chemotherapy ( 7 – 10 ). However, whether optimizing the ToDA of ICI administration during the neoadjuvant phase according to circadian rhythm could similarly enhance short- and long-term outcomes still lacks clinical evidence. Although the National Comprehensive Cancer Network (NCCN) guidelines recommend administering neoadjuvant ICIs and chemotherapy to drive-negative resectable NSCLC patients on the same day, findings from both preclinical and clinical studies suggest that this may not represent the optimal timing interval (TI) strategy ( 6 , 10 , 11 ). Recent ex vivo and metastatic lung cancer mouse model studies have indicated that extending the TI (approximately 48 hours) between a PD-1 inhibitor and chemotherapy may enhance the antitumor immune response and considerably suppress tumor development, and these findings were further validated in a prospective clinical cohort of 170 patients with advanced NSCLC ( 6 ). Furthermore, another integrated study demonstrated that, compared with the concurrent combination, spacing out immunotherapy by 1 to 10 days after chemotherapy significantly improved OS in patients with refractory lung cancer ( 11 ). Therefore, exploring the optimum TI of preoperative ICIs and chemotherapy may be beneficial for improving the response and survival outcomes of patients with resectable NSCLC. Here, leveraging a double-center, real-world cohort, we aimed to explore the effects of ToDA and TI of neoadjuvant chemoimmunotherapy (neoCIT) administrations on the efficacy and survival outcomes of patients with operable NSCLC. This case-control study has been reported in line with the strengthening the report of cohort studies in surgery (STROCSS) 2024 guidelines ( Supplementary Table 1 ) ( 12 ). 2 Patients and methods 2.1 Patient selection Patients who underwent surgery after chemoimmunotherapy for NSCLC between January 2019 and December 2024 were selected from 2 tertiary medical centres in southern China. The main eligibility criteria were as follows: i) based on the 9th edition of the TNM classification of lung cancer, the patient was staged as cT1-4N0-3M0; ii) radical resection was deemed achievable through local multidisciplinary team (MDT) discussion; and iii) age at first diagnosis was ≥18 years. Patients who lacked complete dates and timings of neoCIT infusions; who received additional neoadjuvant radiotherapy; who were diagnosed with other previous or subsequent primary invasive malignancies; who did not have detailed clinical, pathologic, or follow-up information; or who died within 30 days after surgery were excluded. The flowchart in Figure 1 illustrates the patient recruitment process. Figure 1 Study flowchart. 2.2 Neoadjuvant therapy and surgical procedures Neoadjuvant ICIs (i.e., PD-1 or PD-L1 inhibitors) in combination with platinum-based doublet chemotherapy regimens were formulated by the local MDT on the basis of the NCCN and Chinese Society of Clinical Oncology guidelines for lung cancer, or prospective clinical trial protocols approved by the Institutional Review Board ( 8 , 10 , 13 ). Although the number of neoCIT cycles was primarily determined with reference to the aforementioned criteria, patient willingness, therapeutic efficacy, and toxic effects during the neoadjuvant phase were also important considerations. The exact records of dates and starting/ending times (hour:minute) of ICI and chemotherapy infusions were extracted from the nursing records. In the two participating centers, the routine anti-tumor drug infusions were administered daily from 9:00 h to 19:00 h. Therefore, the 14:00 h, as the midpoint, was selected as the dividing time point. The proportion of ICI infusions completed before 14:00 h was defined as the ratio of the total infusions times of neoadjuvant immunotherapy (neoIO) drugs administered before 14:00 h per cycle to the total infusion times of neoIO drugs per cycle. We used quartiles to group all patients. The 75% threshold was selected as the stratification cutoff primarily to align with findings from relevant preclinical and clinical studies ( 1 – 5 , 14 ), maintain consistency with the stratification approaches used in published research ( 5 , 14 ), and facilitate the clinical interpretation of the results. Mean TI was calculated as the sum of the TIs between neoadjuvant ICI and chemotherapy infusion per cycle, divided by the number of neoCIT cycles. The best cut-off values of mean TI were determined by maximum Youden index, which were generated by respective receiver operating characteristics (ROC) curves, to evaluate the predictive values in overall survival (OS, calculated from the initiation of the first cycle of neoCIT until the date of death from any cause). The Common Terminology Criteria for Adverse Events (CTCAE, version 5.0) was utilized for recording and grading AEs during the neoCIT period. Surgical resection was generally scheduled at 28 to 42 days after completion of the last cycles of neoCIT. The surgical approach, either thoracotomy or minimally invasive surgery, was deliberated and agreed upon by the panel of thoracic surgery specialists at each center. The extent of resection included the primary tumor, along with the ipsilateral hilar and mediastinal lymph nodes. However, for patients with concomitant baseline N3 lymph node metastasis from our two investigator-initiated trials (ChiCTR2000040673 and ChiCTR2400081493), additional dissection was also needed. Surgical complications were defined and graded via the Clavien-Dindo classification. 2.3 Baseline and efficacy evaluations, follow-up, and outcomes Magnetic resonance imaging (MRI) or computed tomography (CT) of the brain, contrast-enhanced CT of the neck, thorax and abdomen, and radionuclide whole-body bone scanning were carried out as routine baseline staging examinations. For N2 or N3 lymph nodes suspected of metastasis, invasive staging procedures (such as endobronchial ultrasound-guided transbronchial needle aspiration, endoscopic ultrasound-guided biopsy, video-assisted thoracoscopic surgery biopsy, mediastinoscopy, or ultrasound-guided fine-needle aspiration) and/or a positron emission tomography CT (PET/CT) scan (a maximum standardized uptake value ≥3 on PET and a short-axis diameter ≥10 mm on CT) were needed. Chest CT with contrast was performed within 7 days prior to surgery, and at least two experienced radiologists evaluated the radiographic response status according to the Response Evaluation Criteria in Solid Tumours (RECIST, version 1.1). Pathologic assessment of the surgical specimens was performed by local seasoned pathologists as per the immune-related pathologic response criteria (irPRC). Pathologic complete response (pCR) was defined as the absence of any residual tumor cells observed in both the tumor bed and all the resected lymph nodes, whereas major pathologic response (MPR) was defined as a response in which only the proportion of residual tumor cells in the tumor bed did not exceed 10%. Routine follow-up surveillance included chest CT and ultrasound examinations of the scalene and supraclavicular lymph nodes every 3 months for 2 years and then every 6 months for 3–5 years, followed by yearly follow-up. Consistent with the prospective RCTs and retrospective studies ( 9 , 15 , 16 ), disease-free survival (DFS) was defined as the time interval from the date of surgery to either lung cancer recurrence or death from any cause. 2.4 Statistical analysis Continuous variables are presented as the mean (± standard deviation, SD) or median (interquartile range, IQR), and their differences were analyzed using Student’s t test or the Mann-Whitney U test, respectively. Differences between categorical variables, which are presented as numbers and percentages, were compared using the chi-square test or Fisher’s exact test. Our study employed a doubly robust estimation method that incorporates both inverse probability of treatment weighting (IPTW) and Cox regression adjustment to improve the robustness of survival analysis results. The IPTW method used the standardized mean difference (SMD) to balance baseline variables between the two groups of patients who received either ≥75% or <75% neoIO drugs before 14:00 h, where an SMD value less than 0.10 denoted good equilibrium ( Table 1 ; Supplementary Figure 1 ). In the IPTW-weighted cohort, univariate Cox proportional hazards model was used to calculate the hazard ratios (HRs) and 95% confidence interval (CI), with accompanying survival curves generated using the Kaplan-Meier method. Variables with a P value <0.10 in the above univariate analysis were then included in the multivariate proportional hazards model to identify variables significantly associated with prognosis, defined as a two-sided P value <0.05. In addition, Firth’s penalized Cox regression model was employed to validate the trend of covariates in predicting survival. All the statistical analyses were conducted using R version 4.3.1 software. Table 1 Variables Original cohort Inverse probability of treatment weighting cohort ≥75% group (N = 123) <75% group (N = 45) SMD P value ≥75% group (N = 166.6) <75% group (N = 172.4) SMD P value Age (years old), median (IQR) 64.0 (59.0-70.0) 64.0 (56.5-69.0) 0.051 0.893 64.0 (59.0-69.0) 63.3 (58.5-68.0) 0.018 0.923 Female sex, n (%) 15 (12.2%) 8 (17.8%) 0.157 0.497 21.4 (14.3%) 24.6 (14.3%) 0.041 0.834 Current/former smoker, n (%) 78 (63.4%) 32 (71.1%) 0.165 0.456 109.5 (65.8%) 106.7 (61.9%) 0.081 0.720 Histology, n (%) Squamous cell carcinoma 72 (58.5%) 25 (55.6%) 0.330 0.257 97.2 (58.4%) 105.6 (61.3%) 0.060 0.989 Adenocarcinoma 41 (33.3%) 16 (35.6%) 56.1 (33.7%) 54.2 (31.5%) LELC 8 (6.5%) 1 (2.2%) 9.2 (5.5%) 8.5 (4.9%) Others 2 (1.6%) 3 (6.7%) 4.0 (2.4%) 4.0 (2.3%) PD-L1 expression, n (%) Unknown 59 (48.0%) 21 (46.7%) 0.245 0.390 77.0 (46.2%) 68.2 (39.5%) 0.136 0.833 <1% 38 (30.9%) 18 (40.0%) 57.3 (34.4%) 66.6 (38.6%) ≥1% 26 (21.2%) 6 (13.3%) 32.3 (19.4%) 37.7 (21.8%) Baseline tumor size, cm, mean (SD) 5.5 (1.9) 5.1 (2.2) 0.184 0.276 5.35 (1.86) 5.22 (1.84) 0.071 0.694 Clinical TNM staging, n (%) cI 2 (1.6%) 1 (2.2%) 0.045 0.965 2.8 (1.7%) 2.3 (1.3%) 0.159 0.706 cII 17 (13.8%) 6 (13.3%) 21.7 (13.0%) 32.4 (18.8%) cIII 104 (84.6%) 38 (84.4%) 142.1 (85.3%) 137.7 (79.9%) Neoadjuvant PD-1 inhibitor, n (%) 120 (97.6%) 44 (97.8%) 0.014 0.935 162.7 (97.7%) 169.7 (98.4%) 0.052 0.747 Neoadjuvant cycles, n (%) 1-2 69 (56.1%) 27 (60.0%) 0.079 0.782 93.6 (56.2%) 87.4 (50.7%) 0.111 0.620 ≥3 54 (43.9%) 18 (40.0%) 73.0 (43.8%) 85.1 (49.3%) Mean timing interval, n (%) <23.5 hours 10 (8.1%) 3 (6.7%) 0.056 0.753 12.2 (7.3%) 6.8 (4.0%) 0.146 0.347 ≥23.5 hours 113 (91.9%) 42 (93.3%) 154.4 (92.7%) 165.6 (96.0%) Objective response, n (%) 83 (67.5%) 27 (60.0%) 0.156 0.472 111.7 (67.1%) 111.4 (64.6%) 0.053 0.810 Pathologic TNM staging, n (%) p0 39 (31.7%) 9 (20.0%) 0.350 0.258 47.9 (28.8%) 56.7 (32.9%) 0.098 0.966 pI 40 (32.5%) 16 (35.6%) 56.4 (33.9%) 56.0 (32.5%) pII 19 (15.4%) 12 (26.7%) 29.9 (17.9%) 26.8 (15.5%) pIII 25 (20.3%) 8 (17.8%) 32.3 (19.4%) 33.0 (19.1%) Major pathologic response, n (%) 73 (59.3%) 22 (48.9%) 0.211 0.300 94.2 (56.6%) 105.3 (61.1%) 0.091 0.664 Extent of resection, n (%) Sublobar resection 3 (2.4%) 0 (0%) 0.417 0.115 3.0 (1.8%) 0 (0%) 0.205 0.567 Lobectomy 105 (85.4%) 34 (75.6%) 139.3 (83.6%) 150.3 (87.2%) Bilobectomy 8 (6.5%) 8 (17.8%) 14.7 (8.8%) 14.7 (8.5%) Pneumonectomy 7 (5.7%) 3 (6.7%) 9.6 (5.8%) 7.5 (4.3%) Adjuvant therapy, n (%) 100 (81.3%) 36 (80.0%) 0.033 0.849 134.2 (80.6%) 142.2 (82.5%) 0.049 0.812 Clinical, radiologic, surgical and pathologic characteristics according to ≥75% (≥75% group) and <75% (<75% group) of patients who received neoadjuvant immunotherapy before 14:00 h. SMD, standardized mean difference; IQR, interquartile range; LELC, lymphoepithelioma-like carcinoma; PD-L1, programmed death ligand 1; SD, standard deviation; PD-1, programmed death 1. 3 Results 3.1 Patient characteristics In this study, the 276 consecutive patients who underwent surgery after neoCIT were selected from a total of 337 consecutive patients who received initial neoCIT. Among them, 61 patients (18.1%) did not undergo subsequent surgery, primarily due to patient refusal of the recommended surgery (N = 29, 8.6%), followed by potential R1/R2 resection (N = 11, 3.3%), comorbidities rendering patients intolerant to surgery (N = 10, 3.0%), neoadjuvant treatment-related adverse events (neoTRAEs) (N = 9, 2.7%), and achieving radiographic complete response (N = 2, 0.6%). A total of 168 out of 276 consecutive patients (60.9%) met the selection criteria and were included in the final analysis ( Figure 1 ). The included patients received neoCIT mainly for clinical stage III (84.5%) NSCLC, including 97 (57.7%) with squamous cell carcinoma (SCC), 56 (33.9%) with adenocarcinoma, and 9 (5.4%) with lymphoepithelioma-like carcinoma. The majority were male (86.3%), with a median age of 64.0 (IQR, 58.0-69.0) years, and had a history of smoking (65.5%). More than half (52.4%) of the patients underwent PD-L1 testing via immunohistochemistry, of whom 32 had a PD-L1 tumor proportion score (TPS) of ≥1%. 164 patients (97.6%) received neoadjuvant PD-1 inhibitor therapy. Patients who received ≥75% of the neoIO administrations before 14:00 h were more likely to be male and nonsmokers, to have SCC, to test positive (≥1%) for PD-L1 expression, to have a smaller baseline tumor size, to have a lower pathologic stage, to undergo
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