Hypofractionated Versus Conventionally Fractionated Radiotherapy After Chemo‑immunotherapy in Locally Advanced or Advanced NSCLC: A Comparative Study of Efficacy and Toxicity

Hypofractionated Versus Conventionally Fractionated Radiotherapy After Chemo‑immunotherapy in Locally Advanced or Advanced NSCLC: A Comparative Study of Efficacy and Toxicity | 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 Hypofractionated Versus Conventionally Fractionated Radiotherapy After Chemo‑immunotherapy in Locally Advanced or Advanced NSCLC: A Comparative Study of Efficacy and Toxicity Siyi Yang, Yuntao Zhou, Hui Zhu, Xueping Huang, Jialei Liu, Miao Yu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9220794/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background : Chemotherapy combined with immunotherapy (CIT) has reshaped the first-line treatment landscape for locally advanced and advanced non-small cell lung cancer (NSCLC). However, the optimal radiotherapy (RT) fractionation regimen for patients who remain inoperable after neoadjuvant therapy has yet to be defined. This study aimed to systematically compare survival outcomes and toxicity between hypofractionated radiotherapy (HFRT) and conventionally fractionated radiotherapy (CFRT) following induction CIT. Methods : In this retrospective analysis, 201 patients with locally advanced/advanced NSCLC receiving RT after CIT were divided into HFRT (45–54 Gy/15–18 fractions, n=69) and CFRT (60 Gy/30 fractions, n=132) groups. Overall survival (OS) was the primary endpoint; secondary endpoints included progression‑free survival (PFS), locoregional PFS (LPFS), and toxicity. Multivariable Cox regression and propensity score matching adjusted for confounders. A novel endpoint—LPFS based on conventional PTV—directly compared “gross‑tumor‑only” versus elective‑nodal irradiation. Results : After a median follow‑up of 26.2 months, adjusted analyses showed no significant differences in OS (HR=1.29, P=0.340), PFS, or LPFS between HFRT and CFRT. Exploratory analyses suggested trends favoring HFRT for PFS with consolidative immunotherapy (HR=0.58) and for OS/PFS in patients with high tumor burden (GTV ≥100 cm³; HR=0.85 and 0.88). HFRT was associated with significantly lower rates of acute radiation pneumonitis, key hematologic toxicities, and grade ≥2 pulmonary fibrosis (17.19% vs. 32.81%, P=0.041). The “PGTV‑only” strategy achieved locoregional control comparable to elective nodal irradiation (HR=1.063, P=0.765). All out‑of‑field nodal recurrences occurred with or after distant metastasis. Conclusion : HFRT provides survival outcomes equivalent to CFRT after CIT, with a more favorable safety profile, supporting a “precision intensification” paradigm of target‑volume de‑escalation combined with hypofractionation. Non‑small cell lung cancer Chemotherapy combined with immunotherapy Hypofractionated radiotherapy Treatment‑related adverse events Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of cases 1 . Immune checkpoint inhibitors (ICIs) have significantly improved survival outcomes in patients with advanced disease 2 , 3 . For unresectable stage III or oligometastatic stage IV NSCLC, radiotherapy (RT) is a cornerstone local treatment 4 , 5 . Recent evidence confirms that adding definitive thoracic RT to first-line chemo-immunotherapy significantly improves survival in locally advanced NSCLC, underscoring its continued relevance in the immunotherapy era 6 . However, the optimal RT fractionation regimen within this multimodal paradigm is undetermined. Although hypofractionated RT (HFRT) is increasingly adopted in practice, robust comparative evidence on its efficacy and safety versus conventionally fractionated RT (CFRT) following chemotherapy combined with immunotherapy (CIT) remains limited and confounded. We compared survival and toxicity between HFRT and CFRT post-CIT using multivariable regression and propensity score matching. 2. Methods 2.1. Study Population and Design This single-center, retrospective cohort study included 201 patients with locally advanced or advanced NSCLC who remained unresectable after neoadjuvant therapy with chemotherapy plus a Programmed cell death protein 1(PD-1)/Programmed death-ligand 1(PD-L1) inhibitor. Between June 2020 and July 2025, all patients subsequently underwent radiotherapy at Tianjin Medical University Cancer Institute & Hospital. Key exclusion criteria were prior thoracic RT, missing baseline imaging, or concurrent active malignancies. Patients were stratified into HFRT (n = 69) or CFRT (n = 132) groups per multidisciplinary decision. 2.2. Treatment Protocols All patients underwent induction therapy with chemotherapy (selected according to pathological type) combined with immune checkpoint inhibitors prior to RT. Patients underwent computed tomography (CT) simulation in the treatment position. The gross tumor volume (GTV) included the primary tumor and any PET-positive or pathologic lymph nodes. The planning gross tumor volume (PGTV) was generated by expanding the GTV by 5–8 mm.For patients receiving CFRT, the planning target volume (PTV) was defined to include the PGTV and high-risk nodal stations. For those receiving HFRT, treatment was delivered only to the PGTV without elective nodal coverage. The prescription doses for the CFRT group were: (1) 60 Gy in 30 fractions to a conventional PTV (expanded from the GTV to include high-risk nodal stations); or (2) a simultaneous integrated boost with 60 Gy in 30 fractions to the PGTV and 54 Gy in 30 fractions to the PTV. For the HFRT group, the prescription dose was 45–54 Gy delivered in 15–18 fractions (3 Gy per fraction) to the PGTV. Both groups were treated once daily, five days per week. The administration of concurrent chemoradiotherapy (CCRT), immunotherapy during RT, and consolidative immunotherapy following RT were documented. 2.3. Data Collection and Study Endpoints Patient demographics, clinicopathological characteristics, treatment details, and toxicity data were collected from the medical record system. The primary endpoint was overall survival (OS), defined as the time from RT initiation to death from any cause. Patients alive at the last follow-up were censored. Secondary endpoints included: (1) progression-free survival (PFS), defined as the time to radiologically confirmed disease progression (according to Response Evaluation Criteria in Solid Tumors [RECIST] 1.1 criteria) or death; (2) locoregional progression-free survival (LPFS), defined as the time to in-field progression or death; and (3) treatment-related toxicity. To compare locoregional control between “gross tumor only” and “elective nodal” irradiation strategies, a novel composite endpoint was defined: locoregional PFS based on the conventional PTV anatomical region (LPFS-conPTV). This endpoint adjudicated events using the standard conventional PTV region (encompassing primary site and involved nodal basin) as a unified reference for all patients. Endpoint events included progression at the primary site, within involved nodes, or new nodal progression within this region, as well as any-cause death. For HFRT patients with progression, failure patterns (in-field, mixed, out-of-field) were categorized, and the timing of out-of-field nodal progression relative to distant metastasis was analyzed. Treatment-related toxicities were assessed according to the Common Terminology Criteria for Adverse Events (CTCAE), version 5.0, with a focus on grade ≥ 2 acute radiation pneumonitis, radiation esophagitis, pulmonary fibrosis, and hematologic toxicities. 2.4. Statistical Analysis Statistical analyses were performed using R software (version 4.3.0). A two-sided P < 0.05 was considered statistically significant. 2.4.1. Comparison of Baseline Characteristics and Treatment Toxicity Continuous variables are expressed as mean ± standard deviation (SD) or median (interquartile range, IQR), depending on the normality of distribution. Comparisons between groups were performed using the independent t‑test or Mann‑Whitney U test, as appropriate. Categorical variables are presented as numbers (percentages) and compared using the Chi-square test or Fisher's exact test. Group comparisons of the incidence of treatment-related adverse events were also performed using the aforementioned tests, conducted separately in the overall cohort and the matched cohort. 2.4.2. Survival Analysis and Prognostic Factor Modeling The Kaplan-Meier method was employed to estimate OS, PFS, LPFS, and the novel endpoint, LPFS-conPTV. Differences between groups were compared using the log-rank test. HRs were calculated with the CFRT group as the reference. 2.4.3. Strategy for Assessing the Effect of Fractionation To control for confounding bias and accurately evaluate the independent effect of RT fractionation on survival outcomes, this study employed two complementary analytical strategies: Nested Cox Model Analysis: A series of nested Cox proportional hazards models were constructed to sequentially adjust for demographic factors (age, sex), treatment covariates (CCRT, immunotherapy during RT, consolidative immunotherapy after RT), and tumor burden (GTV volume).The trajectory of changes in the hazard ratio (HR) corresponding to the fractionation regimen across this sequence of models was observed to assess and disentangle the influence of confounding factors. Propensity Score Matching (PSM) Analysis: PSM with a caliper of 0.2 standard deviation was performed to reduce baseline imbalance. Matching variables included tumor GTV volume, Karnofsky Performance Status (KPS), age, pathological type, clinical stage, sex, smoking history, CCRT, concurrent immunotherapy, and consolidative immunotherapy after RT. Survival differences in the matched cohort were compared using the Kaplan–Meier method and log‑rank test. 2.4.4. Subgroup Analysis and Interaction Testing Exploratory subgroup analyses assessed effect heterogeneity across key covariates. For each covariate, a separate multivariable Cox model was fitted, including the treatment group, the dichotomized covariate, and their multiplicative interaction term. The P-value for interaction was used to formally test for heterogeneity across subgroups. All subgroup analyses were considered exploratory and hypothesis-generating. 3. Results 3.1. Patient Baseline Characteristics The study cohort consisted of 201 patients, with 69 and 132 individuals assigned to the HFRT and CFRT groups, respectively. The overall cohort had a median age of 65 years, 84.1% were male, and 78.6% had a smoking history. Baseline clinico-pathological characteristics were well-balanced between the HFRT and CFRT groups (all P > 0.05; Table 1 ). Table 1 Baseline Characteristics Table Variables Total (n = 201) CFRT (n = 132) HFRT (n = 69) Statistic P Age, M (Q₁, Q₃) 65.00 (58.00, 69.00) 65.00 (57.00, 69.00) 66.00 (60.00, 70.00) Z=-0.48 0.633 KPS, n(%) χ²=0.16 0.689 > 80 151 (75.12) 98 (74.24) 53 (76.81) ≤ 80 50 (24.88) 34 (25.76) 16 (23.19) Pathological Type, n(%) χ²=1.15 0.563 Squamous cell carcinoma 134 (66.67) 89 (67.42) 45 (65.22) Adenocarcinoma 57 (28.36) 38 (28.79) 19 (27.54) Other 10 (4.98) 5 (3.79) 5 (7.25) Sex, n(%) χ²=0.65 0.420 Male 169 (84.08) 109 (82.58) 60 (86.96) Female 32 (15.92) 23 (17.42) 9 (13.04) Smoking, n(%) χ²=0.20 0.654 No 43 (21.39) 27 (20.45) 16 (23.19) Yes 158 (78.61) 105 (79.55) 53 (76.81) T, n(%) χ²=1.80 0.615 1 19 (9.45) 13 (9.85) 6 (8.70) 2 57 (28.36) 39 (29.55) 18 (26.09) 3 58 (28.86) 34 (25.76) 24 (34.78) 4 67 (33.33) 46 (34.85) 21 (30.43) N, n(%) χ²=2.81 0.422 0 11 (5.47) 5 (3.79) 6 (8.70) 1 15 (7.46) 11 (8.33) 4 (5.80) 2 101 (50.25) 65 (49.24) 36 (52.17) 3 74 (36.82) 51 (38.64) 23 (33.33) M, n(%) χ²=1.03 0.311 0 143 (71.14) 97 (73.48) 46 (66.67) 1 58 (28.86) 35 (26.52) 23 (33.33) Clinical Stage, n (%) χ²=3.38 0.496 IIIA 55 (27.36) 40 (30.30) 15 (21.74) IIIB 58 (28.86) 37 (28.03) 21 (30.43) IIIC 30 (14.93) 20 (15.15) 10 (14.49) IVA 47 (23.38) 30 (22.73) 17 (24.64) IVB 11 (5.47) 5 (3.79) 6 (8.70) Note: Data are presented as median (Q₁, Q₃) or n (%). Z: Mann-Whitney U test, χ²: Chi-squared test. CFRT, conventionally fractionated radiotherapy; HFRT, hypofractionated radiotherapy; KPS, Karnofsky Performance Status; M, median; Q₁, first quartile; Q₃, third quartile; T, tumor; N, node; M, metastasis. 3.2. Survival Analysis The median follow-up was 26.2 months. Median OS was not reached in the CFRT group and was 30.0 months (95% confidence interval [CI]: 23.03–not reached) in the HFRT group. Kaplan-Meier analysis showed a non-significant trend toward better OS with CFRT (HR = 1.529, 95% CI: 0.944–2.477, P = 0.082,Fig. 1 ). No significant disparity was observed in PFS (median CFRT 15.53 months vs. HFRT 13.67 months; HR = 1.018, 95% CI: 0.696–1.490, P = 0.926,,Fig. 1 ) or LPFS (median CFRT 18.53 months vs. HFRT 19.03 months; HR = 1.045, 95% CI: 0.702–1.555, P = 0.828,Fig. 1 ). 3.3. Efficacy Analysis After Adjustment for Confounding Factors Although univariate analysis suggested a trend toward inferior OS with HFRT (HR = 1.529, P = 0.082), this difference attenuated upon adjustment for confounders. In nested Cox models, the HR for HFRT decreased from 1.53 (P = 0.084) in the unadjusted model to 1.29 (P = 0.340) after sequential inclusion of demographic factors, treatment patterns, and tumor burden (GTV) (Table 2 ). Table 2 Nested Cox Proportional Hazards Models: Effect of HFRT vs. CFRT on OS Model Adjustment Variables HR (95% CI) P-value Model 1 Unadjusted (Radiation fractionation only) 1.53 (0.94–2.48) 0.084 Model 2 Model 1 + Demographic factors (Age, Sex) 1.56 (0.96–2.52) 0.073 Model 3 Model 2 + Treatment patterns (CCRT, Immunotherapy during/after RT) 1.44 (0.86–2.41) 0.168 Model 4 Model 3 + Tumor burden (Total GTV volume) 1.29 (0.76–2.19) 0.340 Footnote: All models use CFRT as the reference group. HR, hazard ratio. PSM further confirmed this finding. In the matched cohort (64 patients per group), no significant difference in OS (HR = 1.070, 95% CI: 0.609–1.879; P = 0.815,Fig. 1 ) or PFS (HR = 0.765, 95% CI: 0.493–1.188; P = 0.231,Fig. 1 ), or LPFS (median: 15.53 vs. 19.03 months; Log-rank P = 0.390,Fig. 1 ) was observed between HFRT and CFRT. Collectively, multivariable and PSM analyses demonstrated comparable survival outcomes for the two fractionation regimens after accounting for baseline and treatment-related factors. 3.4. Locoregional Efficacy and Failure Pattern Characteristics Using the novel endpoint “LPFS based on the anatomical region of the conventional PTV,” we directly compared locoregional control between the HFRT (PGTV-only) and CFRT (elective nodal irradiation) strategies. No significant difference was observed between the groups, with a median LPFS of 18.53 months (95% CI: 14.37–26.10) for CFRT and 17.90 months (95% CI: 11.10–30.27) for HFRT (HR = 1.063, 95% CI: 0.714–1.582; Log-rank P = 0.765,Fig. 2 ). Among the 21 HFRT patients with progression, failure patterns included in-field (12/21, 57.1%,Fig. 3 ), mixed (6/21, 28.6%,Fig. 3 ), and isolated out-of-field progression (3/21, 14.3%,Fig. 3 ). Time-sequencing analysis revealed that all three isolated out-of-field events occurred after distant metastasis (Fig. 3 ). Thus, no instances of isolated nodal progression preceding or independent of systemic metastasis were observed. 3.5. Subgroup Analysis: Exploring Heterogeneity in the Efficacy of Fractionation Regimens 3.5.1 Subgroup Analysis Based on GTV Using a cutoff of 100 cm³, no significant interaction between GTV and fractionation regimen was observed for OS (P-interaction = 0.163) or PFS (P-interaction = 0.162). In the multivariable model adjusted for GTV, the HR for OS was 0.85 (95% CI: 0.36–2.02) in patients with GTV ≥ 100 cm³ and 1.53 (95% CI: 0.70–3.31) in those with GTV < 100 cm³ (Fig. 4 ). For PFS, the corresponding HRs were 0.88 (95% CI: 0.40–1.91) and 0.90 (95% CI: 0.53–1.53), respectively (Fig. 5 ). 3.5.2 Subgroup Analysis Based on CCRT and Consolidative Immunotherapy Status In subgroup analyses, no significant interaction was found between CCRT status and fractionation regimen for OS (P-interaction = 0.765) or PFS (P-interaction = 0.360). For OS, the adjusted HRs were 1.39 (95% CI: 0.79–2.43) and 3.80 (95% CI: 0.36–40.54) for patients not receiving and receiving CCRT, respectively, with the latter estimate being imprecise(Fig. 4 ). For PFS, a statistically significant interaction was observed with consolidative immunotherapy status (P-interaction = 0.017)(Fig. 5 ). Patients receiving consolidative immunotherapy showed a trend toward improved PFS with HFRT (HR = 0.58, 95% CI: 0.29–1.15), while no such trend was seen in those without it (HR = 1.44, 95% CI: 0.82–2.53). No significant interaction was found for OS regarding consolidative immunotherapy (P-interaction = 0.523), with HRs of 2.08 (95% CI: 0.81–5.34) and 1.32 (95% CI: 0.65–2.67) in patients with and without immunotherapy, respectively. 3.5.3 Exploratory Analysis Based on Clinical Stage, Performance Status, and Age The interactions of clinical stage, KPS score, and age with the fractionation regimen did not show statistical significance for either OS or PFS (all P for interaction > 0.05). The hazard ratios for each subgroup after adjustment for the corresponding variable are detailed in in Fig. 4 and Fig. 5 . 3.6 Treatment-Related Toxicity Analysis Within the overall cohort (n = 201), grade ≥ 2 toxicities were significantly less frequent in the HFRT group. This included acute radiation pneumonitis (28.99% vs. 43.94%, P = 0.039), hemoglobin decrease (1.45% vs. 11.36%, P = 0.014), leukopenia (8.70% vs. 30.30%, P < 0.001), and thrombocytopenia (1.45% vs. 10.61%, P = 0.019). No significant difference was observed in acute radiation esophagitis (17.39% vs. 13.64%, P = 0.478), and the lower incidence of pulmonary fibrosis in the HFRT group (17.39% vs. 26.52%, P = 0.147) did not reach statistical significance (Supplementary Table 1). In the PSM-matched cohort (n = 128), the incidence of grade ≥ 2 pulmonary fibrosis became significantly lower in the HFRT group (17.19% vs. 32.81%, P = 0.041). Other toxicities remained numerically lower with HFRT—acute pneumonitis (31.25% vs. 40.62%, P = 0.269), hemoglobin decrease (1.56% vs. 4.69%, P = 0.611), leukopenia (9.4% vs. 15.6%, P = 0.285), and thrombocytopenia (1.56% vs. 6.25%, P = 0.362)—though these differences were not statistically significant. Acute esophagitis incidence did not differ significantly between groups (18.75% vs. 10.94%, P = 0.214) (Table 3 ). Table 3 Comparative Analysis of Treatment-Related Toxicities After Propensity Score Matching: HFRT vs. CFRT Variables Total (n = 128) CFRT (n = 64) HFRT (n = 64) Statistic P Acute Radiation Pneumonitis ≥ Grade 2, n (%) χ²=1.22 0.269 No 82 (64.06) 38 (59.38) 44 (68.75) Yes 46 (35.94) 26 (40.62) 20 (31.25) Pulmonary Fibrosis ≥ Grade 2, n (%) χ²=4.17 0.041 No 96 (75.00) 43 (67.19) 53 (82.81) Yes 32 (25.00) 21 (32.81) 11 (17.19) Acute Radiation Esophagitis ≥ Grade 2, n (%) χ²=1.55 0.214 No 109 (85.16) 57 (89.06) 52 (81.25) Yes 19 (14.84) 7 (10.94) 12 (18.75) Bone Marrow Suppression (Hemoglobin) ≥ Grade 2, n (%) χ²=0.26 0.611 No 124 (96.88) 61 (95.31) 63 (98.44) Yes 4 (3.12) 3 (4.69) 1 (1.56) Bone Marrow Suppression (Leukocytes) ≥ Grade 2, n (%) χ²=1.14 0.285 No 112 (87.50) 54 (84.38) 58 (90.62) Yes 16 (12.50) 10 (15.62) 6 (9.38) Bone Marrow Suppression (Platelets) ≥ Grade 2, n (%) χ²=0.83 0.362 No 123 (96.09) 60 (93.75) 63 (98.44) Yes 5 (3.91) 4 (6.25) 1 (1.56) Note: Data are presented as number of patients (percentage). Group comparisons were performed using the Chi-square test. 4. Discussion Our adjusted analyses show comparable survival outcomes between HFRT and CFRT following CIT. Exploratory analyses revealed favorable trends for HFRT in patients receiving consolidative immunotherapy or with high tumor burden (GTV ≥ 100 cm³). Notably, using an innovative endpoint, this study first demonstrates that a “gross tumor-only” strategy yields locoregional control equivalent to elective nodal irradiation. The initially inferior OS with HFRT was likely due to selection bias, as it was more frequently used in patients with higher tumor burden or less fit for CCRT—an artifact clarified by multivariable and propensity score matching analyses. Our results align with a body of prior work: for instance, a PSM analysis in stage III NSCLC showed no difference in OS between HFRT and CFRT 7 , and their efficacy was also comparable in limited-stage small cell lung cancer 8 . The efficacy of HFRT is also supported in other stages of NSCLC, including stage I 9 and stage IIB 10 . However, the value of this study lies in moving beyond a simple conclusion of "equivalence." Our multivariable analysis confirmed that tumor burden (GTV) is one of the strongest independent prognostic factors affecting survival, aligning with results from multiple studies 11 – 13 . This underscores that high tumor burden constitutes a critical bottleneck to achieving long-term disease control 14 , 15 . After multivariable adjustment, the initial survival disadvantage observed with HFRT disappeared, a finding likely explained by its higher baseline GTV and confirming comparable overall efficacy. Within the GTV ≥ 100 cm³ subgroup, HFRT showed favorable trends in both OS (HR = 0.85) and PFS (HR = 0.88), suggesting a potential clinical benefit. Large tumor burden, associated with hypoxia and proliferative heterogeneity, theoretically requires a higher biologically effective dose (BED) for control. Shorter CFRT courses (typically ≤ 6 weeks) are associated with improved disease control, underscoring the need to limit treatment time to mitigate tumor repopulation 16 .In contrast, radiobiological modeling in NSCLC suggests a low α/β ratio (approximately 4.0 Gy), indicating that increasing BED by elevating fraction size (as in HFRT) is a more efficient strategy than merely increasing total dose 17 . Thus, HFRT offers a dual radiobiological advantage: delivering a higher BED per fraction while avoiding protracted treatment courses that allow for tumor repopulation. This rationale is well established in the literature 18 , and the clinical feasibility of such BED escalation via modern precision techniques has demonstrated acceptable toxicity and promising outcomes 19 . Consequently, our findings provide exploratory support for employing HFRT in patients with larger tumor burdens, though this warrants prospective validation. Univariate analysis linked CCRT to improved OS (HR = 0.53, P = 0.039), consistent with prior studies 20 , 21 ; however, this association lost significance after adjusting for GTV and consolidative immunotherapy (HR = 0.70, P = 0.275). Nested modeling suggested the observed survival trend may reflect higher CCRT use in the CFRT group rather than a fractionation effect. Notably, within the CCRT subgroup, HFRT showed a trend toward better PFS (HR = 0.18). Although this trend warrants cautious interpretation due to its wide confidence interval (0.02–1.45), its direction is consistent with a recent phase III trial reporting significantly improved PFS with HFRT versus CFRT in patients receiving concurrent chemotherapy (HR = 0.58, 95% CI 0.40–0.85, P = 0.003) 22 . Subgroup analysis revealed a significant interaction between consolidative immunotherapy and fractionation for PFS (P-interaction = 0.017), with HFRT showing a trend toward improved PFS in patients receiving immunotherapy (HR = 0.58). This potential synergy was not observed for OS (HR = 2.08), possibly due to limited sample size, subsequent therapies, or insufficient follow-up. This potential synergy finds direct prospective validation in the GASTO-1091 trial, where consolidative nivolumab significantly improved PFS following a treatment backbone that included hypofractionated chemoradiotherapy (hypo-CCRT) 23 . This interaction aligns with a radiobiology framework in which hypofractionation promotes immunogenic cell death and reprograms the tumor microenvironment — key mechanisms for priming systemic anti-tumor immunity 24 . Mechanistically, experimental studies show HFRT promotes early CD8 + T-cell activation and PD-1 upregulation in NSCLC models, facilitating synergy with immune checkpoint inhibitors 25 .This study provides clinical evidence positioning HFRT as the preferred RT option for combination with immunotherapy. Studies indicate severe CCRT toxicity in large tumors; Wiersma et al. reported 7.1% treatment-related mortality, a risk particularly high in patients with comorbidities 26 .Given its favorable safety profile and the observed trend for improved PFS with consolidative immunotherapy, we propose the exploratory hypothesis that HFRT could enable safer CCRT and more effective bridging to immunotherapy in high-risk patients.Beyond clinical efficacy, HFRT offers notable socioeconomic advantages. By reducing the treatment course from the conventional 30 fractions to 15–18 fractions, it lowers direct medical costs and minimizes indirect financial burdens on patients, such as travel expenses and time away from work. Additionally, this condensed schedule optimizes healthcare resources. Thus, HFRT represents a cost-effective, patient-centric approach that enhances treatment convenience. The novel endpoint "locoregional PFS based on the conventional PTV region" showed comparable locoregional control between "PGTV-only" and elective nodal irradiation after CIT (Log-rank P = 0.765, HR = 1.063), supporting target‑volume de‑escalation to improve the therapeutic ratio. Prior evidence from the chemotherapy era demonstrated that involved-field radiotherapy (IFRT) did not increase nodal failure risk compared to elective nodal irradiation (ENI), while reducing toxicity and maintaining efficacy—justifying dose escalation through target‑volume reduction 27 , 28 . Leveraging CIT's high pathological response rates 29 , this study focuses target‑volume de‑escalation on residual disease irradiation. Failure pattern analysis showed all out-of-field nodal recurrences coincided with or followed distant metastasis, suggesting they reflect systemic progression. This supports combining focused target‑volume de‑escalation with HFRT’s biologic potentiation in a “precision intensification” paradigm: maximally attacking refractory lesions while sparing systemically controlled areas and normal tissue to optimize the therapeutic ratio. Based on the findings, treatment decisions for NSCLC patients receiving post-CIT radiotherapy should evolve from a simple HFRT vs. CFRT comparison to a multidimensional, risk‑adaptive framework. This framework integrates tumor aggressiveness (e.g., GTV 30 , 31 and pathological subtype 32 ), treatment intensity (e.g., CCRT 20 , 21 ), and host‑specific risks (e.g., treatment‑related toxicity 33 ). Within this model, HFRT emerges as a valuable strategic option due to its efficacy equivalence, favorable acute toxicity profile, and observed potential for synergistic benefit, offering a feasible pathway for patients who need to balance efficacy with safety (e.g., those with large tumor burden or CCRT intolerance). Limitations and Future Perspectives The retrospective, single-center design limits this study, as residual confounding and selection bias may persist despite statistical adjustments. The sample size also limits the power of subgroup analyses. Furthermore, the biological mechanisms underlying potential benefits of HFRT, such as immune-microenvironment interactions, remain unexplored. Consequently, the generalizability of our findings may be limited to similar patient populations treated at specialized cancer centers. Future multicenter prospective studies are warranted to validate these findings. Further research should also integrate novel biomarkers—such as radiomics and circulating tumor DNA—into risk prediction models to guide clinical decisions, thereby advancing radiotherapy for locally advanced NSCLC toward more precise and individualized modalities. 5. Conclusion This study demonstrates that HFRT provides equivalent OS, PFS, and locoregional control compared to CFRT in patients with locally advanced or advanced NSCLC treated with CIT, while offering a superior safety profile with significantly lower risks of acute hematologic toxicity and radiation pneumonitis. Exploratory analyses revealed numerical trends favoring HFRT in specific subgroups, such as patients receiving consolidative immunotherapy or those with high tumor burden (GTV ≥ 100 cm³). Through an innovative endpoint, this study provides the first clinical evidence in the CIT setting that a precise “gross tumor-only” target strategy yields locoregional control comparable to traditional elective nodal irradiation. These findings support HFRT combined with focused target volumes as a viable “toxicity-reducing and efficacy-enhancing”approach. Future work should focus on developing risk-adaptive frameworks to guide individualized RT in this evolving treatment paradigm. Abbreviations NSCLC Non-small cell lung cancer ICIs Immune checkpoint inhibitors RT Radiotherapy HFRT Hypofractionated radiotherapy CFRT Conventionally fractionated radiotherapy CIT Chemotherapy combined with immunotherapy PD-1 Programmed cell death protein 1 PD-L1 Programmed death-ligand 1 GTV Gross tumor volume PGTV Planning gross tumor volume PTV Planning target volume CCRT Concurrent chemoradiotherapy OS Overall survival PFS Progression-free survival LPFS Locoregional progression-free survival RECIST Response Evaluation Criteria in Solid Tumors CTCAE Common Terminology Criteria for Adverse Events LPFS-conPTV Locoregional progression-free survival based on the anatomical region of the conventional PTV PSM Propensity score matching KPS Karnofsky Performance Status HR Hazard ratio CI Confidence interval BED Biologically effective dose Declarations Ethics approval and consent to participate Ethics approval was waived The Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (No.bc20260586). Informed consent was waived by the ethics committee/Institutional Review Board of Tianjin Medical University Cancer Institute and Hospital. All methods were performed in accordance with the relevant guidelines and regulations. Consent for publication Not applicable. Availability of data and materials The data are available from the corresponding author upon request. Competing interests The authors declare no competing interests Funding This study is funded by National Natural Science Foundation of China (82460580), Natural Science Foundation of Xinjiang Uygur Autonomous Region of China (2023D01A55), Tianjin Key Medical Discipline Construction Project (TJYXZDXK-3-004B). Author contributions Conceptualization: Siyi Yang, Yuntao Zhou, Chao Qu and Ningbo Liu; Methodology: Yuntao Zhou, Chengwen Yang, Chao Qu and Ningbo Liu; Formal analysis: Siyi Yang and Yuntao Zhou; Investigation: Siyi Yang, Hui Zhu, Xueping Huang, Jialei Liu and Miao Yu; Data Curation: Siyi Yang, Xueping Huang, Jialei Liu and Miao Yu; Visualization: Siyi Yang and Yuntao Zhou; Writing – Original Draft: Siyi Yang; Writing – Review & Editing: Chengwen Yang, Chao Qu and Ningbo Liu; Resources: Lujun Zhao and Yongchun Song; Supervision: Lujun Zhao, Chengwen Yang and Ningbo Liu; Project Administration: Hui Zhu and Yongchun Song; Funding Acquisition: Ningbo Liu Acknowledgements None. References Padinharayil H, Varghese J, John MC, et al. Non-small cell lung carcinoma (NSCLC): Implications on molecular pathology and advances in early diagnostics and therapeutics. Genes Dis. 2023;10(3):960–89. Assi HI, Kamphorst AO, Moukalled NM, Ramalingam SS. Immune checkpoint inhibitors in advanced non-small cell lung cancer. Cancer. 2018;124(2):248–61. Yao J, Li S, Bai L, et al. Efficacy and safety of immune checkpoint inhibitors in elderly patients with advanced non-small cell lung cancer: A systematic review and meta-analysis. EClinicalMedicine. 2025;81:103081. Remon J, Levy A, Gille R et al. Unresectable stage III non-small-cell lung cancer: State of the art and challenges. Nat Rev Clin Oncol 2025. Delcuratolo MD, Crespi V, Saba G, et al. The evolving landscape of stage III unresectable non-small cell lung cancer between lights and shadows. Cancer Treat Rev. 2025;135:102918. Zhu X, Liu J, Cai R, et al. Comparative outcomes of treatment with versus without definitive thoracic radiotherapy in locally advanced inoperable non-small cell lung cancer during the immunotherapy era: A Chinese real-world study. Transl Lung Cancer Res. 2025;14(10):4398–411. Iocolano M, Wild AT, Hannum M, et al. Hypofractionated vs. conventional radiation therapy for stage III non-small cell lung cancer treated without chemotherapy. Acta Oncol. 2020;59(2):164–70. Zayed S, Chen H, Ali E, et al. Is there a role for hypofractionated thoracic radiation therapy in limited-stage small cell lung cancer? A propensity score matched analysis. Int J Radiat Oncol Biol Phys. 2020;108(3):575–86. Saeed NA, Jin L, Amini A, et al. Utilization and survival impact of hypofractionated radiotherapy in stage I non-small cell lung cancer. Am J Clin Oncol. 2023;46(2):66. Jacobs CD, Gao J, Wang X, et al. Definitive radiotherapy for inoperable stage IIB non-small-cell lung cancer: Patterns of care and comparative effectiveness. Clin Lung Cancer. 2020;21(3):238–46. Yu Y, Guan H, Xing L-G, Xiang Y-B. Role of gross tumor volume in the prognosis of non-small cell lung cancer treated with 3D conformal radiotherapy: A meta-analysis. Clin Ther. 2015;37(10):2256–66. Stinchcombe TE, Morris DE, Moore DT, et al. Post-chemotherapy gross tumor volume is predictive of survival in patients with stage III non-small cell lung cancer treated with combined modality therapy. Lung Cancer. 2006;52(1):67–74. Chang H-J, Ko H-L, Lee C-Y, et al. Hypofractionated radiotherapy for primary or secondary oligometastatic lung cancer using tomotherapy. Radiat Oncol. 2012;7:222. Tang C, Liao Z, Gomez D, et al. Lymphopenia association with gross tumor volume and lung V5 and its effects on non-small cell lung cancer patient outcomes. Int J Radiat Oncol Biol Phys. 2014;89(5):1084–91. De Petris L, Lax I, Sirzén F, Friesland S. Role of gross tumor volume on outcome and of dose parameters on toxicity of patients undergoing chemoradiotherapy for locally advanced non-small cell lung cancer. Med Oncol. 2005;22(4):375–81. Partridge M, Ramos M, Sardaro A, Brada M. Dose escalation for non-small cell lung cancer: Analysis and modelling of published literature. Radiother Oncol. 2011;99(1):6–11. Nix MG, Rowbottom CG, Vivekanandan S, Hawkins MA, Fenwick JD. Chemoradiotherapy of locally-advanced non-small cell lung cancer: Analysis of radiation dose-response, chemotherapy and survival-limiting toxicity effects indicates a low α/β ratio. Radiother Oncol. 2020;143:58–65. Kepka L, Socha J. Dose and fractionation schedules in radiotherapy for non-small cell lung cancer. Transl Lung Cancer Res. 2021;10(4):1969–82. Donato V, Arcangeli S, Monaco A, et al. Moderately escalated hypofractionated (chemo) radiotherapy delivered with helical intensity-modulated technique in stage III unresectable non-small cell lung cancer. Front Oncol. 2013;3:286. Rowell NP, O’rourke NP. Concurrent chemoradiotherapy in non-small cell lung cancer. Cochrane Database Syst Rev 2004;(4):CD002140. Vokes EE, Crawford J, Bogart J, Socinski MA, Clamon G, Green MR. Concurrent chemoradiotherapy for unresectable stage III non-small cell lung cancer. Clin Cancer Res. 2005;11(13 Pt 2):s5045–50. Zhang Q, Fan S, Xu X, et al. Efficacy and toxicity of moderately hypofractionated radiation therapy with helical TomoTherapy versus conventional radiation therapy in patients with unresectable stage III non-small cell lung cancer receiving concurrent chemotherapy: A multicenter, randomized phase 3 trial. Int J Radiat Oncol Biol Phys. 2024;120(2):422–31. Liu H, Qiu B, Zhao Y et al. A phase II randomized trial evaluating consolidative nivolumab in locally advanced non-small cell lung cancer post neoadjuvant chemotherapy plus nivolumab and concurrent chemoradiotherapy (GASTO-1091). JCO. 2024;42(16_suppl):8008–8008. Mortezaee K, Najafi M. Immune system in cancer radiotherapy: Resistance mechanisms and therapy perspectives. Crit Rev Oncol Hematol. 2021;157:103180. Zhao X, Li J, Zheng L, et al. Immune response on optimal timing and fractionation dose for hypofractionated radiotherapy in non-small-cell lung cancer. Front Mol Biosci. 2022;9:786864. Wiersma TG, Dahele M, Verbakel WFAR, et al. Concurrent chemoradiotherapy for large-volume locally-advanced non-small cell lung cancer. Lung Cancer. 2013;80(1):62–7. Fernandes AT, Shen J, Finlay J, et al. Elective nodal irradiation (ENI) vs. involved field radiotherapy (IFRT) for locally advanced non-small cell lung cancer (NSCLC): A comparative analysis of toxicities and clinical outcomes. Radiother Oncol. 2010;95(2):178–84. Rosenzweig KE, Sura S, Jackson A, Yorke E. Involved-field radiation therapy for inoperable non small-cell lung cancer. J Clin Oncol. 2007;25(35):5557–61. Yang X, He Y, Guo T, et al. The efficacy analysis of neoadjuvant chemoimmunotherapy followed by surgery in stage III locally advanced non-small cell lung cancer: A systematic review and meta-analysis. BMC Cancer. 2025;25(1):1443. Chen X, Zhang W, Luo L, et al. Effect of primary tumor volume on survival of concurrent chemoradiotherapy in stage IV non-small cell lung cancer. Cancer Med. 2024;13(17):e70221. Lee HI, Choi EK, Kim SS, Shin YS, Park JW, Song SY. Predictive value of primary tumor volume change during concurrent chemoradiotherapy in patients with unresectable stage III non-small cell lung cancer. Radiother Oncol. 2024;198:110383. Skrzypski M, Dziadziuszko R, Jassem E, et al. Main histologic types of non-small-cell lung cancer differ in expression of prognosis-related genes. Clin Lung Cancer. 2013;14(6):666–e6732. Kale MS, Mhango G, Gomez JE, et al. Treatment toxicity in elderly patients with advanced non-small cell lung cancer. Am J Clin Oncol. 2017;40(5):470–6. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 09 May, 2026 Reviewers agreed at journal 08 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers invited by journal 02 Apr, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 25 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9220794","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":616581112,"identity":"fe8ed7f2-b097-4d1e-8747-46151dd3e23e","order_by":0,"name":"Siyi Yang","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Siyi","middleName":"","lastName":"Yang","suffix":""},{"id":616581118,"identity":"97b7348a-8031-49e2-99c0-d3aeaa354d66","order_by":1,"name":"Yuntao Zhou","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuntao","middleName":"","lastName":"Zhou","suffix":""},{"id":616581121,"identity":"81f1cffa-7fc6-4962-b968-f65344e9498c","order_by":2,"name":"Hui Zhu","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Zhu","suffix":""},{"id":616581124,"identity":"37fa4b11-b205-4090-884f-d79b9fa7e214","order_by":3,"name":"Xueping Huang","email":"","orcid":"","institution":"Lingcheng District People's Hospital of Dezhou City","correspondingAuthor":false,"prefix":"","firstName":"Xueping","middleName":"","lastName":"Huang","suffix":""},{"id":616581133,"identity":"c152a67f-5857-474a-8587-83bee3ba75ee","order_by":4,"name":"Jialei Liu","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jialei","middleName":"","lastName":"Liu","suffix":""},{"id":616581136,"identity":"22aa2e78-f344-45c7-a4ca-cf3632741c8a","order_by":5,"name":"Miao Yu","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Miao","middleName":"","lastName":"Yu","suffix":""},{"id":616581138,"identity":"3de2abd1-e8ec-48e7-a5fd-e3010a100b7e","order_by":6,"name":"Lujun Zhao","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lujun","middleName":"","lastName":"Zhao","suffix":""},{"id":616581140,"identity":"82ed6dea-d723-4454-bbd9-8beeee3c2eaa","order_by":7,"name":"Yongchun Song","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yongchun","middleName":"","lastName":"Song","suffix":""},{"id":616581141,"identity":"a0a5e570-8f19-4628-90c8-ef39c3c2f1ef","order_by":8,"name":"Chengwen Yang","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chengwen","middleName":"","lastName":"Yang","suffix":""},{"id":616581143,"identity":"df7596fa-ae50-495c-9bf1-f454037d5457","order_by":9,"name":"Chao Qu","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Qu","suffix":""},{"id":616581144,"identity":"76a4910a-426e-4ffb-93ea-90d6f50fcb85","order_by":10,"name":"Ningbo Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBACPmYgkQBC7A0MBhA2AcAG18JzmFgtUDqBQSIZyiCohZ3H7MHDHbV5/JLvDxTdbLPLY2A/fHQDfofxmBsknjleLDk7mcE4ty25mIEnLe0GAS1mEoltxxI33AZrOZDYIMFjRqSWm4dJ01KTuOEGM9Fa2MqAWg4US/YkGxjnnEtObCPkF37+w9skf7bV5fGzH3xmnFNml9jPfvgYXi1QcBhsowGYJEI5CNSBCOYHRKoeBaNgFIyCEQYAj7RFMCO8oUIAAAAASUVORK5CYII=","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":true,"prefix":"","firstName":"Ningbo","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-03-25 09:09:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9220794/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9220794/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106724705,"identity":"7226c9a4-4c37-4bd5-8c0a-82f309206799","added_by":"auto","created_at":"2026-04-12 18:29:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":324872,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves comparing HFRT and CFRT. (A) Overall survival (Overall cohort), (B) Progression‑free survival (Overall cohort), (C) Locoregional progression‑free survival (Overall cohort), (D) Overall survival (Matched cohort), (E) Progression‑free survival (Matched cohort), (F) Locoregional progression‑free survival (Matched cohort).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9220794/v1/4f133d28b1d0cba6f8f3d825.png"},{"id":106533965,"identity":"f87247e9-5b11-4ed0-91b3-8e94c4c50be9","added_by":"auto","created_at":"2026-04-09 15:01:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75649,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves comparing HFRT and CFRT for locoregional progression‑free survival based on the anatomical region of the conventional PTV (Overall cohort).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9220794/v1/6ba5e945d970a975d9d05e98.png"},{"id":106724947,"identity":"9f67d958-ea26-40c5-9d49-32f91998c200","added_by":"auto","created_at":"2026-04-12 18:30:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19923,"visible":true,"origin":"","legend":"\u003cp\u003eFailure patterns in HFRT-treated patients with progression (n=21). (A) Distribution of recurrence sites. (B) Timing of distant metastasis vs. out-of-field nodal progression (all metastases occurred concurrently with or preceded nodal progression).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9220794/v1/2657ebcd4bde04de6030b010.png"},{"id":106724700,"identity":"4213c598-32ac-4fc7-a28d-4efd1bf276ef","added_by":"auto","created_at":"2026-04-12 18:29:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":51564,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for subgroup analysis of overall survival comparing HFRT to CFRT. Hazard ratios (95% CI) are shown for key subgroups; the dashed line indicates no difference (HR=1). P for interaction tests heterogeneity of treatment effect across subgroups.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9220794/v1/297a72588ca070e118c0f615.png"},{"id":106533967,"identity":"eae0e264-504e-4189-956a-96fda56fd08e","added_by":"auto","created_at":"2026-04-09 15:01:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":50060,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for subgroup analysis of progression-free survival comparing HFRT to CFRT. Hazard ratios (95% CI) are shown for key subgroups; the dashed line indicates no difference (HR=1). P for interaction tests heterogeneity of treatment effect across subgroups.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9220794/v1/5359db4a57be76bce1e1f8b1.png"},{"id":107704749,"identity":"6b6d089f-b394-4ecc-ba36-9749afdcea05","added_by":"auto","created_at":"2026-04-24 08:56:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1094474,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9220794/v1/368a5901-bf4d-413b-b330-4417ef7e0d43.pdf"},{"id":106533963,"identity":"71e45ff6-ec59-4cae-9d2e-23ea8cf43327","added_by":"auto","created_at":"2026-04-09 15:01:04","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":71788,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-9220794/v1/a1914d88706c8b067fc9803c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hypofractionated Versus Conventionally Fractionated Radiotherapy After Chemo‑immunotherapy in Locally Advanced or Advanced NSCLC: A Comparative Study of Efficacy and Toxicity","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of cases\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Immune checkpoint inhibitors (ICIs) have significantly improved survival outcomes in patients with advanced disease\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. For unresectable stage III or oligometastatic stage IV NSCLC, radiotherapy (RT) is a cornerstone local treatment\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Recent evidence confirms that adding definitive thoracic RT to first-line chemo-immunotherapy significantly improves survival in locally advanced NSCLC, underscoring its continued relevance in the immunotherapy era\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. However, the optimal RT fractionation regimen within this multimodal paradigm is undetermined. Although hypofractionated RT (HFRT) is increasingly adopted in practice, robust comparative evidence on its efficacy and safety versus conventionally fractionated RT (CFRT) following chemotherapy combined with immunotherapy (CIT) remains limited and confounded. We compared survival and toxicity between HFRT and CFRT post-CIT using multivariable regression and propensity score matching.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Population and Design\u003c/h2\u003e \u003cp\u003e This single-center, retrospective cohort study included 201 patients with locally advanced or advanced NSCLC who remained unresectable after neoadjuvant therapy with chemotherapy plus a Programmed cell death protein 1(PD-1)/Programmed death-ligand 1(PD-L1) inhibitor. Between June 2020 and July 2025, all patients subsequently underwent radiotherapy at Tianjin Medical University Cancer Institute \u0026amp; Hospital. Key exclusion criteria were prior thoracic RT, missing baseline imaging, or concurrent active malignancies. Patients were stratified into HFRT (n\u0026thinsp;=\u0026thinsp;69) or CFRT (n\u0026thinsp;=\u0026thinsp;132) groups per multidisciplinary decision.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Treatment Protocols\u003c/h2\u003e \u003cp\u003eAll patients underwent induction therapy with chemotherapy (selected according to pathological type) combined with immune checkpoint inhibitors prior to RT. Patients underwent computed tomography (CT) simulation in the treatment position. The gross tumor volume (GTV) included the primary tumor and any PET-positive or pathologic lymph nodes. The planning gross tumor volume (PGTV) was generated by expanding the GTV by 5\u0026ndash;8 mm.For patients receiving CFRT, the planning target volume (PTV) was defined to include the PGTV and high-risk nodal stations. For those receiving HFRT, treatment was delivered only to the PGTV without elective nodal coverage.\u003c/p\u003e \u003cp\u003eThe prescription doses for the CFRT group were: (1) 60 Gy in 30 fractions to a conventional PTV (expanded from the GTV to include high-risk nodal stations); or (2) a simultaneous integrated boost with 60 Gy in 30 fractions to the PGTV and 54 Gy in 30 fractions to the PTV. For the HFRT group, the prescription dose was 45\u0026ndash;54 Gy delivered in 15\u0026ndash;18 fractions (3 Gy per fraction) to the PGTV. Both groups were treated once daily, five days per week. The administration of concurrent chemoradiotherapy (CCRT), immunotherapy during RT, and consolidative immunotherapy following RT were documented.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data Collection and Study Endpoints\u003c/h2\u003e \u003cp\u003ePatient demographics, clinicopathological characteristics, treatment details, and toxicity data were collected from the medical record system. The primary endpoint was overall survival (OS), defined as the time from RT initiation to death from any cause. Patients alive at the last follow-up were censored. Secondary endpoints included: (1) progression-free survival (PFS), defined as the time to radiologically confirmed disease progression (according to Response Evaluation Criteria in Solid Tumors [RECIST] 1.1 criteria) or death; (2) locoregional progression-free survival (LPFS), defined as the time to in-field progression or death; and (3) treatment-related toxicity.\u003c/p\u003e \u003cp\u003eTo compare locoregional control between \u0026ldquo;gross tumor only\u0026rdquo; and \u0026ldquo;elective nodal\u0026rdquo; irradiation strategies, a novel composite endpoint was defined: locoregional PFS based on the conventional PTV anatomical region (LPFS-conPTV). This endpoint adjudicated events using the standard conventional PTV region (encompassing primary site and involved nodal basin) as a unified reference for all patients. Endpoint events included progression at the primary site, within involved nodes, or new nodal progression within this region, as well as any-cause death. For HFRT patients with progression, failure patterns (in-field, mixed, out-of-field) were categorized, and the timing of out-of-field nodal progression relative to distant metastasis was analyzed.\u003c/p\u003e \u003cp\u003eTreatment-related toxicities were assessed according to the Common Terminology Criteria for Adverse Events (CTCAE), version 5.0, with a focus on grade\u0026thinsp;\u0026ge;\u0026thinsp;2 acute radiation pneumonitis, radiation esophagitis, pulmonary fibrosis, and hematologic toxicities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using R software (version 4.3.0). A two-sided P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1. Comparison of Baseline Characteristics and Treatment Toxicity\u003c/h2\u003e \u003cp\u003eContinuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median (interquartile range, IQR), depending on the normality of distribution. Comparisons between groups were performed using the independent t‑test or Mann‑Whitney U test, as appropriate. Categorical variables are presented as numbers (percentages) and compared using the Chi-square test or Fisher's exact test. Group comparisons of the incidence of treatment-related adverse events were also performed using the aforementioned tests, conducted separately in the overall cohort and the matched cohort.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2. Survival Analysis and Prognostic Factor Modeling\u003c/h2\u003e \u003cp\u003eThe Kaplan-Meier method was employed to estimate OS, PFS, LPFS, and the novel endpoint, LPFS-conPTV. Differences between groups were compared using the log-rank test. HRs were calculated with the CFRT group as the reference.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3. Strategy for Assessing the Effect of Fractionation\u003c/h2\u003e \u003cp\u003eTo control for confounding bias and accurately evaluate the independent effect of RT fractionation on survival outcomes, this study employed two complementary analytical strategies:\u003c/p\u003e \u003cp\u003eNested Cox Model Analysis: A series of nested Cox proportional hazards models were constructed to sequentially adjust for demographic factors (age, sex), treatment covariates (CCRT, immunotherapy during RT, consolidative immunotherapy after RT), and tumor burden (GTV volume).The trajectory of changes in the hazard ratio (HR) corresponding to the fractionation regimen across this sequence of models was observed to assess and disentangle the influence of confounding factors.\u003c/p\u003e \u003cp\u003ePropensity Score Matching (PSM) Analysis: PSM with a caliper of 0.2 standard deviation was performed to reduce baseline imbalance. Matching variables included tumor GTV volume, Karnofsky Performance Status (KPS), age, pathological type, clinical stage, sex, smoking history, CCRT, concurrent immunotherapy, and consolidative immunotherapy after RT. Survival differences in the matched cohort were compared using the Kaplan\u0026ndash;Meier method and log‑rank test.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.4. Subgroup Analysis and Interaction Testing\u003c/h2\u003e \u003cp\u003eExploratory subgroup analyses assessed effect heterogeneity across key covariates. For each covariate, a separate multivariable Cox model was fitted, including the treatment group, the dichotomized covariate, and their multiplicative interaction term. The P-value for interaction was used to formally test for heterogeneity across subgroups. All subgroup analyses were considered exploratory and hypothesis-generating.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Patient Baseline Characteristics\u003c/h2\u003e \u003cp\u003eThe study cohort consisted of 201 patients, with 69 and 132 individuals assigned to the HFRT and CFRT groups, respectively. The overall cohort had a median age of 65 years, 84.1% were male, and 78.6% had a smoking history. Baseline clinico-pathological characteristics were well-balanced between the HFRT and CFRT groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; 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 Table\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;201)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCFRT (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHFRT (n\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.00 (58.00, 69.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.00 (57.00, 69.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.00 (60.00, 70.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKPS, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e151 (75.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98 (74.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (76.81)\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\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50 (24.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (25.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (23.19)\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\"\u003e \u003cp\u003ePathological Type, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.563\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSquamous cell carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e134 (66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89 (67.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45 (65.22)\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\"\u003e \u003cp\u003eAdenocarcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57 (28.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38 (28.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19 (27.54)\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\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (4.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (7.25)\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\"\u003e \u003cp\u003eSex, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169 (84.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109 (82.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60 (86.96)\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\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32 (15.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (17.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (13.04)\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\"\u003e \u003cp\u003eSmoking, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (21.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27 (20.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (23.19)\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e158 (78.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105 (79.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (76.81)\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\"\u003e \u003cp\u003eT, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (9.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (9.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (8.70)\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\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57 (28.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39 (29.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18 (26.09)\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\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (28.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (25.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24 (34.78)\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\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67 (33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46 (34.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21 (30.43)\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\"\u003e \u003cp\u003eN, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (5.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (8.70)\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\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (7.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (8.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (5.80)\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\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101 (50.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65 (49.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (52.17)\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\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74 (36.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51 (38.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23 (33.33)\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\"\u003e \u003cp\u003eM, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e143 (71.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97 (73.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (66.67)\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\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (28.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (26.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23 (33.33)\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\"\u003e \u003cp\u003eClinical Stage, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIIIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55 (27.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40 (30.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (21.74)\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\"\u003e \u003cp\u003eIIIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (28.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37 (28.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21 (30.43)\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\"\u003e \u003cp\u003eIIIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (14.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (15.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (14.49)\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\"\u003e \u003cp\u003eIVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47 (23.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (22.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (24.64)\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\"\u003e \u003cp\u003eIVB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (5.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (8.70)\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 \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote:\u0026nbsp;Data are presented as median (Q₁, Q₃) or n (%). Z: Mann-Whitney U test, χ\u0026sup2;: Chi-squared test. CFRT, conventionally fractionated radiotherapy; HFRT, hypofractionated radiotherapy; KPS, Karnofsky Performance Status; M, median; Q₁, first quartile; Q₃, third quartile; T, tumor; N, node; M, metastasis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Survival Analysis\u003c/h2\u003e \u003cp\u003eThe median follow-up was 26.2 months. Median OS was not reached in the CFRT group and was 30.0 months (95% confidence interval [CI]: 23.03\u0026ndash;not reached) in the HFRT group. Kaplan-Meier analysis showed a non-significant trend toward better OS with CFRT (HR\u0026thinsp;=\u0026thinsp;1.529, 95% CI: 0.944\u0026ndash;2.477, P\u0026thinsp;=\u0026thinsp;0.082,Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No significant disparity was observed in PFS (median CFRT 15.53 months vs. HFRT 13.67 months; HR\u0026thinsp;=\u0026thinsp;1.018, 95% CI: 0.696\u0026ndash;1.490, P\u0026thinsp;=\u0026thinsp;0.926,,Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) or LPFS (median CFRT 18.53 months vs. HFRT 19.03 months; HR\u0026thinsp;=\u0026thinsp;1.045, 95% CI: 0.702\u0026ndash;1.555, P\u0026thinsp;=\u0026thinsp;0.828,Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Efficacy Analysis After Adjustment for Confounding Factors\u003c/h2\u003e \u003cp\u003eAlthough univariate analysis suggested a trend toward inferior OS with HFRT (HR\u0026thinsp;=\u0026thinsp;1.529, P\u0026thinsp;=\u0026thinsp;0.082), this difference attenuated upon adjustment for confounders. In nested Cox models, the HR for HFRT decreased from 1.53 (P\u0026thinsp;=\u0026thinsp;0.084) in the unadjusted model to 1.29 (P\u0026thinsp;=\u0026thinsp;0.340) after sequential inclusion of demographic factors, treatment patterns, and tumor burden (GTV) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eNested Cox Proportional Hazards Models: Effect of HFRT vs. CFRT on OS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjustment Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted (Radiation fractionation only)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.53 (0.94\u0026ndash;2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u0026thinsp;+\u0026thinsp;Demographic factors (Age, Sex)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.56 (0.96\u0026ndash;2.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 2\u0026thinsp;+\u0026thinsp;Treatment patterns (CCRT, Immunotherapy during/after RT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.44 (0.86\u0026ndash;2.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 3\u0026thinsp;+\u0026thinsp;Tumor burden (Total GTV volume)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.29 (0.76\u0026ndash;2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eFootnote: All models use CFRT as the reference group. HR, hazard ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePSM further confirmed this finding. In the matched cohort (64 patients per group), no significant difference in OS (HR\u0026thinsp;=\u0026thinsp;1.070, 95% CI: 0.609\u0026ndash;1.879; P\u0026thinsp;=\u0026thinsp;0.815,Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) or PFS (HR\u0026thinsp;=\u0026thinsp;0.765, 95% CI: 0.493\u0026ndash;1.188; P\u0026thinsp;=\u0026thinsp;0.231,Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), or LPFS (median: 15.53 vs. 19.03 months; Log-rank P\u0026thinsp;=\u0026thinsp;0.390,Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was observed between HFRT and CFRT. Collectively, multivariable and PSM analyses demonstrated comparable survival outcomes for the two fractionation regimens after accounting for baseline and treatment-related factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Locoregional Efficacy and Failure Pattern Characteristics\u003c/h2\u003e \u003cp\u003eUsing the novel endpoint \u0026ldquo;LPFS based on the anatomical region of the conventional PTV,\u0026rdquo; we directly compared locoregional control between the HFRT (PGTV-only) and CFRT (elective nodal irradiation) strategies. No significant difference was observed between the groups, with a median LPFS of 18.53 months (95% CI: 14.37\u0026ndash;26.10) for CFRT and 17.90 months (95% CI: 11.10\u0026ndash;30.27) for HFRT (HR\u0026thinsp;=\u0026thinsp;1.063, 95% CI: 0.714\u0026ndash;1.582; Log-rank P\u0026thinsp;=\u0026thinsp;0.765,Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the 21 HFRT patients with progression, failure patterns included in-field (12/21, 57.1%,Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), mixed (6/21, 28.6%,Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and isolated out-of-field progression (3/21, 14.3%,Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Time-sequencing analysis revealed that all three isolated out-of-field events occurred after distant metastasis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Thus, no instances of isolated nodal progression preceding or independent of systemic metastasis were observed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Subgroup Analysis: Exploring Heterogeneity in the Efficacy of Fractionation Regimens\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.5.1 Subgroup Analysis Based on GTV\u003c/h2\u003e \u003cp\u003eUsing a cutoff of 100 cm\u0026sup3;, no significant interaction between GTV and fractionation regimen was observed for OS (P-interaction\u0026thinsp;=\u0026thinsp;0.163) or PFS (P-interaction\u0026thinsp;=\u0026thinsp;0.162). In the multivariable model adjusted for GTV, the HR for OS was 0.85 (95% CI: 0.36\u0026ndash;2.02) in patients with GTV\u0026thinsp;\u0026ge;\u0026thinsp;100 cm\u0026sup3; and 1.53 (95% CI: 0.70\u0026ndash;3.31) in those with GTV\u0026thinsp;\u0026lt;\u0026thinsp;100 cm\u0026sup3; (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For PFS, the corresponding HRs were 0.88 (95% CI: 0.40\u0026ndash;1.91) and 0.90 (95% CI: 0.53\u0026ndash;1.53), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.5.2 Subgroup Analysis Based on CCRT and Consolidative Immunotherapy Status\u003c/h2\u003e \u003cp\u003eIn subgroup analyses, no significant interaction was found between CCRT status and fractionation regimen for OS (P-interaction\u0026thinsp;=\u0026thinsp;0.765) or PFS (P-interaction\u0026thinsp;=\u0026thinsp;0.360). For OS, the adjusted HRs were 1.39 (95% CI: 0.79\u0026ndash;2.43) and 3.80 (95% CI: 0.36\u0026ndash;40.54) for patients not receiving and receiving CCRT, respectively, with the latter estimate being imprecise(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For PFS, a statistically significant interaction was observed with consolidative immunotherapy status (P-interaction\u0026thinsp;=\u0026thinsp;0.017)(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Patients receiving consolidative immunotherapy showed a trend toward improved PFS with HFRT (HR\u0026thinsp;=\u0026thinsp;0.58, 95% CI: 0.29\u0026ndash;1.15), while no such trend was seen in those without it (HR\u0026thinsp;=\u0026thinsp;1.44, 95% CI: 0.82\u0026ndash;2.53). No significant interaction was found for OS regarding consolidative immunotherapy (P-interaction\u0026thinsp;=\u0026thinsp;0.523), with HRs of 2.08 (95% CI: 0.81\u0026ndash;5.34) and 1.32 (95% CI: 0.65\u0026ndash;2.67) in patients with and without immunotherapy, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.5.3 Exploratory Analysis Based on Clinical Stage, Performance Status, and Age\u003c/h2\u003e \u003cp\u003eThe interactions of clinical stage, KPS score, and age with the fractionation regimen did not show statistical significance for either OS or PFS (all P for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The hazard ratios for each subgroup after adjustment for the corresponding variable are detailed in in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Treatment-Related Toxicity Analysis\u003c/h2\u003e \u003cp\u003eWithin the overall cohort (n\u0026thinsp;=\u0026thinsp;201), grade\u0026thinsp;\u0026ge;\u0026thinsp;2 toxicities were significantly less frequent in the HFRT group. This included acute radiation pneumonitis (28.99% vs. 43.94%, P\u0026thinsp;=\u0026thinsp;0.039), hemoglobin decrease (1.45% vs. 11.36%, P\u0026thinsp;=\u0026thinsp;0.014), leukopenia (8.70% vs. 30.30%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and thrombocytopenia (1.45% vs. 10.61%, P\u0026thinsp;=\u0026thinsp;0.019). No significant difference was observed in acute radiation esophagitis (17.39% vs. 13.64%, P\u0026thinsp;=\u0026thinsp;0.478), and the lower incidence of pulmonary fibrosis in the HFRT group (17.39% vs. 26.52%, P\u0026thinsp;=\u0026thinsp;0.147) did not reach statistical significance (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eIn the PSM-matched cohort (n\u0026thinsp;=\u0026thinsp;128), the incidence of grade\u0026thinsp;\u0026ge;\u0026thinsp;2 pulmonary fibrosis became significantly lower in the HFRT group (17.19% vs. 32.81%, P\u0026thinsp;=\u0026thinsp;0.041). Other toxicities remained numerically lower with HFRT\u0026mdash;acute pneumonitis (31.25% vs. 40.62%, P\u0026thinsp;=\u0026thinsp;0.269), hemoglobin decrease (1.56% vs. 4.69%, P\u0026thinsp;=\u0026thinsp;0.611), leukopenia (9.4% vs. 15.6%, P\u0026thinsp;=\u0026thinsp;0.285), and thrombocytopenia (1.56% vs. 6.25%, P\u0026thinsp;=\u0026thinsp;0.362)\u0026mdash;though these differences were not statistically significant. Acute esophagitis incidence did not differ significantly between groups (18.75% vs. 10.94%, P\u0026thinsp;=\u0026thinsp;0.214) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Analysis of Treatment-Related Toxicities After Propensity Score Matching: HFRT vs. CFRT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;128)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCFRT (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHFRT (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Radiation Pneumonitis\u0026thinsp;\u0026ge;\u0026thinsp;Grade 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82 (64.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38 (59.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44 (68.75)\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46 (35.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (40.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (31.25)\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\"\u003e \u003cp\u003ePulmonary Fibrosis\u0026thinsp;\u0026ge;\u0026thinsp;Grade 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.041\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96 (75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (67.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (82.81)\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (32.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (17.19)\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\"\u003e \u003cp\u003eAcute Radiation Esophagitis\u0026thinsp;\u0026ge;\u0026thinsp;Grade 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e109 (85.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (89.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52 (81.25)\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (14.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (10.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (18.75)\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\"\u003e \u003cp\u003eBone Marrow Suppression (Hemoglobin) \u0026ge; Grade 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124 (96.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61 (95.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63 (98.44)\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (3.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (4.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (1.56)\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\"\u003e \u003cp\u003eBone Marrow Suppression (Leukocytes) \u0026ge; Grade 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112 (87.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (84.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58 (90.62)\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (15.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (9.38)\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\"\u003e \u003cp\u003eBone Marrow Suppression (Platelets) \u0026ge; Grade 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123 (96.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60 (93.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63 (98.44)\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\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (3.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (1.56)\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 \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Data are presented as number of patients (percentage). Group comparisons were performed using the Chi-square test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur adjusted analyses show comparable survival outcomes between HFRT and CFRT following CIT. Exploratory analyses revealed favorable trends for HFRT in patients receiving consolidative immunotherapy or with high tumor burden (GTV\u0026thinsp;\u0026ge;\u0026thinsp;100 cm\u0026sup3;). Notably, using an innovative endpoint, this study first demonstrates that a \u0026ldquo;gross tumor-only\u0026rdquo; strategy yields locoregional control equivalent to elective nodal irradiation. The initially inferior OS with HFRT was likely due to selection bias, as it was more frequently used in patients with higher tumor burden or less fit for CCRT\u0026mdash;an artifact clarified by multivariable and propensity score matching analyses. Our results align with a body of prior work: for instance, a PSM analysis in stage III NSCLC showed no difference in OS between HFRT and CFRT \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, and their efficacy was also comparable in limited-stage small cell lung cancer \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The efficacy of HFRT is also supported in other stages of NSCLC, including stage I \u003csup\u003e9\u003c/sup\u003eand stage IIB\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, the value of this study lies in moving beyond a simple conclusion of \"equivalence.\" Our multivariable analysis confirmed that tumor burden (GTV) is one of the strongest independent prognostic factors affecting survival, aligning with results from multiple studies\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. This underscores that high tumor burden constitutes a critical bottleneck to achieving long-term disease control \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. After multivariable adjustment, the initial survival disadvantage observed with HFRT disappeared, a finding likely explained by its higher baseline GTV and confirming comparable overall efficacy. Within the GTV\u0026thinsp;\u0026ge;\u0026thinsp;100 cm\u0026sup3; subgroup, HFRT showed favorable trends in both OS (HR\u0026thinsp;=\u0026thinsp;0.85) and PFS (HR\u0026thinsp;=\u0026thinsp;0.88), suggesting a potential clinical benefit. Large tumor burden, associated with hypoxia and proliferative heterogeneity, theoretically requires a higher biologically effective dose (BED) for control. Shorter CFRT courses (typically\u0026thinsp;\u0026le;\u0026thinsp;6 weeks) are associated with improved disease control, underscoring the need to limit treatment time to mitigate tumor repopulation\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.In contrast, radiobiological modeling in NSCLC suggests a low α/β ratio (approximately 4.0 Gy), indicating that increasing BED by elevating fraction size (as in HFRT) is a more efficient strategy than merely increasing total dose\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Thus, HFRT offers a dual radiobiological advantage: delivering a higher BED per fraction while avoiding protracted treatment courses that allow for tumor repopulation. This rationale is well established in the literature \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, and the clinical feasibility of such BED escalation via modern precision techniques has demonstrated acceptable toxicity and promising outcomes\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Consequently, our findings provide exploratory support for employing HFRT in patients with larger tumor burdens, though this warrants prospective validation.\u003c/p\u003e \u003cp\u003eUnivariate analysis linked CCRT to improved OS (HR\u0026thinsp;=\u0026thinsp;0.53, P\u0026thinsp;=\u0026thinsp;0.039), consistent with prior studies\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e; however, this association lost significance after adjusting for GTV and consolidative immunotherapy (HR\u0026thinsp;=\u0026thinsp;0.70, P\u0026thinsp;=\u0026thinsp;0.275). Nested modeling suggested the observed survival trend may reflect higher CCRT use in the CFRT group rather than a fractionation effect. Notably, within the CCRT subgroup, HFRT showed a trend toward better PFS (HR\u0026thinsp;=\u0026thinsp;0.18). Although this trend warrants cautious interpretation due to its wide confidence interval (0.02\u0026ndash;1.45), its direction is consistent with a recent phase III trial reporting significantly improved PFS with HFRT versus CFRT in patients receiving concurrent chemotherapy (HR\u0026thinsp;=\u0026thinsp;0.58, 95% CI 0.40\u0026ndash;0.85, P\u0026thinsp;=\u0026thinsp;0.003) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Subgroup analysis revealed a significant interaction between consolidative immunotherapy and fractionation for PFS (P-interaction\u0026thinsp;=\u0026thinsp;0.017), with HFRT showing a trend toward improved PFS in patients receiving immunotherapy (HR\u0026thinsp;=\u0026thinsp;0.58). This potential synergy was not observed for OS (HR\u0026thinsp;=\u0026thinsp;2.08), possibly due to limited sample size, subsequent therapies, or insufficient follow-up. This potential synergy finds direct prospective validation in the GASTO-1091 trial, where consolidative nivolumab significantly improved PFS following a treatment backbone that included hypofractionated chemoradiotherapy (hypo-CCRT) \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. This interaction aligns with a radiobiology framework in which hypofractionation promotes immunogenic cell death and reprograms the tumor microenvironment \u0026mdash; key mechanisms for priming systemic anti-tumor immunity\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Mechanistically, experimental studies show HFRT promotes early CD8\u0026thinsp;+\u0026thinsp;T-cell activation and PD-1 upregulation in NSCLC models, facilitating synergy with immune checkpoint inhibitors\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.This study provides clinical evidence positioning HFRT as the preferred RT option for combination with immunotherapy. Studies indicate severe CCRT toxicity in large tumors; Wiersma et al. reported 7.1% treatment-related mortality, a risk particularly high in patients with comorbidities\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.Given its favorable safety profile and the observed trend for improved PFS with consolidative immunotherapy, we propose the exploratory hypothesis that HFRT could enable safer CCRT and more effective bridging to immunotherapy in high-risk patients.Beyond clinical efficacy, HFRT offers notable socioeconomic advantages. By reducing the treatment course from the conventional 30 fractions to 15\u0026ndash;18 fractions, it lowers direct medical costs and minimizes indirect financial burdens on patients, such as travel expenses and time away from work. Additionally, this condensed schedule optimizes healthcare resources. Thus, HFRT represents a cost-effective, patient-centric approach that enhances treatment convenience.\u003c/p\u003e \u003cp\u003eThe novel endpoint \"locoregional PFS based on the conventional PTV region\" showed comparable locoregional control between \"PGTV-only\" and elective nodal irradiation after CIT (Log-rank P\u0026thinsp;=\u0026thinsp;0.765, HR\u0026thinsp;=\u0026thinsp;1.063), supporting target‑volume de‑escalation to improve the therapeutic ratio. Prior evidence from the chemotherapy era demonstrated that involved-field radiotherapy (IFRT) did not increase nodal failure risk compared to elective nodal irradiation (ENI), while reducing toxicity and maintaining efficacy\u0026mdash;justifying dose escalation through target‑volume reduction\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Leveraging CIT's high pathological response rates\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, this study focuses target‑volume de‑escalation on residual disease irradiation. Failure pattern analysis showed all out-of-field nodal recurrences coincided with or followed distant metastasis, suggesting they reflect systemic progression. This supports combining focused target‑volume de‑escalation with HFRT\u0026rsquo;s biologic potentiation in a \u0026ldquo;precision intensification\u0026rdquo; paradigm: maximally attacking refractory lesions while sparing systemically controlled areas and normal tissue to optimize the therapeutic ratio.\u003c/p\u003e \u003cp\u003eBased on the findings, treatment decisions for NSCLC patients receiving post-CIT radiotherapy should evolve from a simple HFRT vs. CFRT comparison to a multidimensional, risk‑adaptive framework. This framework integrates tumor aggressiveness (e.g., GTV\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and pathological subtype\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e), treatment intensity (e.g., CCRT \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e), and host‑specific risks (e.g., treatment‑related toxicity \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e). Within this model, HFRT emerges as a valuable strategic option due to its efficacy equivalence, favorable acute toxicity profile, and observed potential for synergistic benefit, offering a feasible pathway for patients who need to balance efficacy with safety (e.g., those with large tumor burden or CCRT intolerance).\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations and Future Perspectives\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe retrospective, single-center design limits this study, as residual confounding and selection bias may persist despite statistical adjustments. The sample size also limits the power of subgroup analyses. Furthermore, the biological mechanisms underlying potential benefits of HFRT, such as immune-microenvironment interactions, remain unexplored. Consequently, the generalizability of our findings may be limited to similar patient populations treated at specialized cancer centers. Future multicenter prospective studies are warranted to validate these findings. Further research should also integrate novel biomarkers\u0026mdash;such as radiomics and circulating tumor DNA\u0026mdash;into risk prediction models to guide clinical decisions, thereby advancing radiotherapy for locally advanced NSCLC toward more precise and individualized modalities.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates that HFRT provides equivalent OS, PFS, and locoregional control compared to CFRT in patients with locally advanced or advanced NSCLC treated with CIT, while offering a superior safety profile with significantly lower risks of acute hematologic toxicity and radiation pneumonitis. Exploratory analyses revealed numerical trends favoring HFRT in specific subgroups, such as patients receiving consolidative immunotherapy or those with high tumor burden (GTV\u0026thinsp;\u0026ge;\u0026thinsp;100 cm\u0026sup3;). Through an innovative endpoint, this study provides the first clinical evidence in the CIT setting that a precise \u0026ldquo;gross tumor-only\u0026rdquo; target strategy yields locoregional control comparable to traditional elective nodal irradiation. These findings support HFRT combined with focused target volumes as a viable \u0026ldquo;toxicity-reducing and efficacy-enhancing\u0026rdquo;approach. Future work should focus on developing risk-adaptive frameworks to guide individualized RT in this evolving treatment paradigm.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSCLC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-small cell lung cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmune checkpoint inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRadiotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHFRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHypofractionated radiotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCFRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConventionally fractionated radiotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCIT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChemotherapy combined with immunotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgrammed cell death protein 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD-L1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgrammed death-ligand 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGTV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGross tumor volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePGTV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlanning gross tumor volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePTV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlanning target volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConcurrent chemoradiotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgression-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLPFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLocoregional progression-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRECIST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eResponse Evaluation Criteria in Solid Tumors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTCAE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommon Terminology Criteria for Adverse Events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLPFS-conPTV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLocoregional progression-free survival based on the anatomical region of the conventional PTV\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePropensity score matching\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKPS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKarnofsky Performance Status\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBED\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBiologically effective dose\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval was waived The Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (No.bc20260586). Informed consent was waived by the ethics committee/Institutional Review Board of Tianjin Medical University Cancer Institute and Hospital. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data are available from the corresponding author upon request.\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 study is funded by National Natural Science Foundation of China (82460580), Natural Science Foundation of Xinjiang Uygur Autonomous Region of China (2023D01A55), \u0026nbsp;Tianjin Key Medical Discipline Construction Project (TJYXZDXK-3-004B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Siyi Yang, Yuntao Zhou, Chao Qu and Ningbo Liu; Methodology: Yuntao Zhou, Chengwen Yang, Chao Qu and Ningbo Liu; Formal analysis: Siyi Yang and Yuntao Zhou; Investigation: Siyi Yang, Hui Zhu, Xueping Huang, Jialei Liu and Miao Yu; Data Curation: Siyi Yang, Xueping Huang, Jialei Liu and Miao Yu; Visualization: Siyi Yang and Yuntao Zhou; Writing – Original Draft: Siyi Yang; Writing – Review \u0026amp; Editing: Chengwen Yang, Chao Qu and Ningbo Liu; Resources: Lujun Zhao and Yongchun Song; Supervision: Lujun Zhao, Chengwen Yang and Ningbo Liu; Project Administration: Hui Zhu and Yongchun Song; Funding Acquisition: Ningbo Liu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePadinharayil H, Varghese J, John MC, et al. Non-small cell lung carcinoma (NSCLC): Implications on molecular pathology and advances in early diagnostics and therapeutics. Genes Dis. 2023;10(3):960\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAssi HI, Kamphorst AO, Moukalled NM, Ramalingam SS. Immune checkpoint inhibitors in advanced non-small cell lung cancer. Cancer. 2018;124(2):248\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYao J, Li S, Bai L, et al. Efficacy and safety of immune checkpoint inhibitors in elderly patients with advanced non-small cell lung cancer: A systematic review and meta-analysis. EClinicalMedicine. 2025;81:103081.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRemon J, Levy A, Gille R et al. Unresectable stage III non-small-cell lung cancer: State of the art and challenges. Nat Rev Clin Oncol 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDelcuratolo MD, Crespi V, Saba G, et al. The evolving landscape of stage III unresectable non-small cell lung cancer between lights and shadows. Cancer Treat Rev. 2025;135:102918.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu X, Liu J, Cai R, et al. Comparative outcomes of treatment with versus without definitive thoracic radiotherapy in locally advanced inoperable non-small cell lung cancer during the immunotherapy era: A Chinese real-world study. Transl Lung Cancer Res. 2025;14(10):4398\u0026ndash;411.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIocolano M, Wild AT, Hannum M, et al. Hypofractionated vs. conventional radiation therapy for stage III non-small cell lung cancer treated without chemotherapy. Acta Oncol. 2020;59(2):164\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZayed S, Chen H, Ali E, et al. Is there a role for hypofractionated thoracic radiation therapy in limited-stage small cell lung cancer? A propensity score matched analysis. Int J Radiat Oncol Biol Phys. 2020;108(3):575\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaeed NA, Jin L, Amini A, et al. Utilization and survival impact of hypofractionated radiotherapy in stage I non-small cell lung cancer. Am J Clin Oncol. 2023;46(2):66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJacobs CD, Gao J, Wang X, et al. Definitive radiotherapy for inoperable stage IIB non-small-cell lung cancer: Patterns of care and comparative effectiveness. Clin Lung Cancer. 2020;21(3):238\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu Y, Guan H, Xing L-G, Xiang Y-B. Role of gross tumor volume in the prognosis of non-small cell lung cancer treated with 3D conformal radiotherapy: A meta-analysis. Clin Ther. 2015;37(10):2256\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStinchcombe TE, Morris DE, Moore DT, et al. Post-chemotherapy gross tumor volume is predictive of survival in patients with stage III non-small cell lung cancer treated with combined modality therapy. Lung Cancer. 2006;52(1):67\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang H-J, Ko H-L, Lee C-Y, et al. Hypofractionated radiotherapy for primary or secondary oligometastatic lung cancer using tomotherapy. Radiat Oncol. 2012;7:222.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang C, Liao Z, Gomez D, et al. Lymphopenia association with gross tumor volume and lung V5 and its effects on non-small cell lung cancer patient outcomes. Int J Radiat Oncol Biol Phys. 2014;89(5):1084\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Petris L, Lax I, Sirz\u0026eacute;n F, Friesland S. Role of gross tumor volume on outcome and of dose parameters on toxicity of patients undergoing chemoradiotherapy for locally advanced non-small cell lung cancer. Med Oncol. 2005;22(4):375\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePartridge M, Ramos M, Sardaro A, Brada M. Dose escalation for non-small cell lung cancer: Analysis and modelling of published literature. Radiother Oncol. 2011;99(1):6\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNix MG, Rowbottom CG, Vivekanandan S, Hawkins MA, Fenwick JD. Chemoradiotherapy of locally-advanced non-small cell lung cancer: Analysis of radiation dose-response, chemotherapy and survival-limiting toxicity effects indicates a low α/β ratio. Radiother Oncol. 2020;143:58\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKepka L, Socha J. Dose and fractionation schedules in radiotherapy for non-small cell lung cancer. Transl Lung Cancer Res. 2021;10(4):1969\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonato V, Arcangeli S, Monaco A, et al. Moderately escalated hypofractionated (chemo) radiotherapy delivered with helical intensity-modulated technique in stage III unresectable non-small cell lung cancer. Front Oncol. 2013;3:286.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRowell NP, O\u0026rsquo;rourke NP. Concurrent chemoradiotherapy in non-small cell lung cancer. Cochrane Database Syst Rev 2004;(4):CD002140.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVokes EE, Crawford J, Bogart J, Socinski MA, Clamon G, Green MR. Concurrent chemoradiotherapy for unresectable stage III non-small cell lung cancer. Clin Cancer Res. 2005;11(13 Pt 2):s5045\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Q, Fan S, Xu X, et al. Efficacy and toxicity of moderately hypofractionated radiation therapy with helical TomoTherapy versus conventional radiation therapy in patients with unresectable stage III non-small cell lung cancer receiving concurrent chemotherapy: A multicenter, randomized phase 3 trial. Int J Radiat Oncol Biol Phys. 2024;120(2):422\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu H, Qiu B, Zhao Y et al. A phase II randomized trial evaluating consolidative nivolumab in locally advanced non-small cell lung cancer post neoadjuvant chemotherapy plus nivolumab and concurrent chemoradiotherapy (GASTO-1091). JCO. 2024;42(16_suppl):8008\u0026ndash;8008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMortezaee K, Najafi M. Immune system in cancer radiotherapy: Resistance mechanisms and therapy perspectives. Crit Rev Oncol Hematol. 2021;157:103180.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao X, Li J, Zheng L, et al. Immune response on optimal timing and fractionation dose for hypofractionated radiotherapy in non-small-cell lung cancer. Front Mol Biosci. 2022;9:786864.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWiersma TG, Dahele M, Verbakel WFAR, et al. Concurrent chemoradiotherapy for large-volume locally-advanced non-small cell lung cancer. Lung Cancer. 2013;80(1):62\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFernandes AT, Shen J, Finlay J, et al. Elective nodal irradiation (ENI) vs. involved field radiotherapy (IFRT) for locally advanced non-small cell lung cancer (NSCLC): A comparative analysis of toxicities and clinical outcomes. Radiother Oncol. 2010;95(2):178\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosenzweig KE, Sura S, Jackson A, Yorke E. Involved-field radiation therapy for inoperable non small-cell lung cancer. J Clin Oncol. 2007;25(35):5557\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang X, He Y, Guo T, et al. The efficacy analysis of neoadjuvant chemoimmunotherapy followed by surgery in stage III locally advanced non-small cell lung cancer: A systematic review and meta-analysis. BMC Cancer. 2025;25(1):1443.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X, Zhang W, Luo L, et al. Effect of primary tumor volume on survival of concurrent chemoradiotherapy in stage IV non-small cell lung cancer. Cancer Med. 2024;13(17):e70221.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee HI, Choi EK, Kim SS, Shin YS, Park JW, Song SY. Predictive value of primary tumor volume change during concurrent chemoradiotherapy in patients with unresectable stage III non-small cell lung cancer. Radiother Oncol. 2024;198:110383.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkrzypski M, Dziadziuszko R, Jassem E, et al. Main histologic types of non-small-cell lung cancer differ in expression of prognosis-related genes. Clin Lung Cancer. 2013;14(6):666\u0026ndash;e6732.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKale MS, Mhango G, Gomez JE, et al. Treatment toxicity in elderly patients with advanced non-small cell lung cancer. Am J Clin Oncol. 2017;40(5):470\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"radiation-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"raon","sideBox":"Learn more about [Radiation Oncology](http://ro-journal.biomedcentral.com/)","snPcode":"13014","submissionUrl":"https://submission.nature.com/new-submission/13014/3","title":"Radiation Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Non‑small cell lung cancer, Chemotherapy combined with immunotherapy, Hypofractionated radiotherapy, Treatment‑related adverse events","lastPublishedDoi":"10.21203/rs.3.rs-9220794/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9220794/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Chemotherapy combined with immunotherapy (CIT) has reshaped the first-line treatment landscape for locally advanced and advanced non-small cell lung cancer (NSCLC).\u003c/p\u003e\n\u003cp\u003eHowever, the optimal radiotherapy (RT) fractionation regimen for patients who remain inoperable after neoadjuvant therapy has yet to be defined. This study aimed to systematically compare survival outcomes and toxicity between hypofractionated radiotherapy (HFRT) and conventionally fractionated radiotherapy (CFRT) following induction CIT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: In this retrospective analysis, 201 patients with locally advanced/advanced NSCLC receiving RT after CIT were divided into HFRT (45–54 Gy/15–18 fractions, n=69) and CFRT (60 Gy/30 fractions, n=132) groups. Overall survival (OS) was the primary endpoint; secondary endpoints included progression‑free survival (PFS), locoregional PFS (LPFS), and toxicity. Multivariable Cox regression and propensity score matching adjusted for confounders. A novel endpoint—LPFS based on conventional PTV—directly compared “gross‑tumor‑only” versus elective‑nodal irradiation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: After a median follow‑up of 26.2 months, adjusted analyses showed no significant differences in OS (HR=1.29, P=0.340), PFS, or LPFS between HFRT and CFRT. Exploratory analyses suggested trends favoring HFRT for PFS with consolidative immunotherapy (HR=0.58) and for OS/PFS in patients with high tumor burden (GTV ≥100 cm³; HR=0.85 and 0.88). HFRT was associated with significantly lower rates of acute radiation pneumonitis, key hematologic toxicities, and grade ≥2 pulmonary fibrosis (17.19% vs. 32.81%, P=0.041). The “PGTV‑only” strategy achieved locoregional control comparable to elective nodal irradiation (HR=1.063, P=0.765). All out‑of‑field nodal recurrences occurred with or after distant metastasis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: HFRT provides survival outcomes equivalent to CFRT after CIT, with a more favorable safety profile, supporting a “precision intensification” paradigm of target‑volume de‑escalation combined with hypofractionation.\u003c/p\u003e","manuscriptTitle":"Hypofractionated Versus Conventionally Fractionated Radiotherapy After Chemo‑immunotherapy in Locally Advanced or Advanced NSCLC: A Comparative Study of Efficacy and Toxicity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 15:01:00","doi":"10.21203/rs.3.rs-9220794/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"136331573000780413353496107049331427069","date":"2026-05-09T08:44:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286761545521887254078932897399526817791","date":"2026-05-08T06:57:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323419349224133959041622800018088065364","date":"2026-05-06T07:15:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60020429833820016771085013274216106372","date":"2026-05-04T16:18:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T11:52:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T15:16:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-26T15:16:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Radiation Oncology","date":"2026-03-25T08:55:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"radiation-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"raon","sideBox":"Learn more about [Radiation Oncology](http://ro-journal.biomedcentral.com/)","snPcode":"13014","submissionUrl":"https://submission.nature.com/new-submission/13014/3","title":"Radiation Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ce4370d5-901b-4408-99d5-9576727676d5","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"136331573000780413353496107049331427069","date":"2026-05-09T08:44:11+00:00","index":22,"fulltext":""},{"type":"reviewerAgreed","content":"286761545521887254078932897399526817791","date":"2026-05-08T06:57:12+00:00","index":21,"fulltext":""},{"type":"reviewerAgreed","content":"323419349224133959041622800018088065364","date":"2026-05-06T07:15:06+00:00","index":20,"fulltext":""},{"type":"reviewerAgreed","content":"60020429833820016771085013274216106372","date":"2026-05-04T16:18:57+00:00","index":19,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T15:01:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 15:01:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9220794","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9220794","identity":"rs-9220794","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}