Predictors of radiation pneumonitis after postoperative radiotherapy in completely resected pathologic stage III-N2 non-small cell lung cancer: a secondary analysis of a prospective cohort

Introduction

The management of completely resected stage III-N2 non-small cell lung cancer (NSCLC) remains challenging (1). Despite recent advancements in neoadjuvant immunotherapy and adjuvant targeted agents, locoregional recurrence (LRR) remains a significant concern, affecting up to one-third of patients (2,3). The CheckMate 816 trial showed LRR rates of 19% with neoadjuvant nivolumab-chemotherapy and 22% with chemotherapy alone in resected stage IB-IIIA patients (4). While the general application of postoperative radiotherapy (PORT) is debated following the Lung ART and PORT-C trials (5,6), thoracic radiation remains a critical tool for locoregional control, both in the adjuvant setting for high-risk patients and as salvage therapy for recurrence. Consequently, current National Comprehensive Cancer Network (NCCN) guidelines recommend thoracic radiation for patients with high-risk N2 disease, defined as those with extracapsular extension, multi-station involvement, inadequate dissection or sampling of lymph nodes, and/or who refuse or are unable to tolerate adjuvant systemic therapy (7).

Excessive cardiopulmonary toxicity has undermined the survival benefits of thoracic radiation in the postoperative setting (2). In the Lung ART trial, the rates of severe cardiopulmonary toxicity and late grade 3–4 cardiopulmonary toxicity were both significantly higher in the PORT arm than in the control arm (16% vs. 2% cardiopulmonary deaths; 16% vs. 6% late cardiopulmonary toxicities). Notably, symptomatic radiation pneumonitis (RP) occurs in approximately 10% to 20% of patients receiving PORT (8-11). This high incidence raises concerns that standard dosimetric guidelines [typically mean lung dose (MLD) ≤20 Gy and V20 ≤35–40%] may be insufficient in the postoperative setting, as the combination of reduced pulmonary function and the inflammatory response following surgery renders postoperative patients less tolerant to radiation (7,12). This highlights the critical need to minimize the risk of severe RP through stricter dosimetric constraints and improved prediction strategies.

Risk factors for RP in the postoperative setting are poorly defined and differ fundamentally from established predictors for definitive radiotherapy, such as MLD and lung V20. The limited literature presents inconsistent findings. Boonyawan et al. identified lung V10 >30% and V20 >20% as predictive of grade ≥2 (G2+) RP, while Shepherd et al. implicated a different set of factors, including lung V4, heart V16, age, and carboplatin chemotherapy (10,11). However, these findings are derived from predominantly retrospective studies with considerable heterogeneity in patient populations [R1/R2 resections, wedge resections or pneumonectomies, three-dimensional conformal radiation therapy (3D-CRT), inconsistent clinical target volume (CTV) delineation and dose prescriptions]. Clearly, prospective investigations on homogeneous cohorts using standardized protocols are necessary to clarify these risk factors.

Our team previously conducted several studies to propose an institutional CTV delineation protocol and to identify the high-risk population for postoperative pathological stage III-N2 NSCLC (13-16). Building on these findings, we subsequently initiated two prospective clinical trials (NCT02977169 and NCT02974426) to investigate more tailored PORT strategies based on LRR risk stratification. Although both trials terminated prematurely due to slow accrual following the adoption of adjuvant immunotherapy, a subsequent propensity score-matched analysis within the high-risk LRR subgroup revealed significantly improved disease-free survival and overall survival in the PORT cohort (17).

To identify predictive factors and develop a novel model for estimating the risk of G2+ RP, we performed a secondary analysis of the PORT cohort from two prospective randomized trials conducted at our institution. This study focused exclusively on NSCLC patients undergoing lobectomy or sleeve resection with (I) R0 resection; (II) uniform intensity-modulated radiotherapy (IMRT) planning; and (III) standardized CTV delineation. We present this article in accordance with the TRIPOD reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1-1414/rc).

Methods

Patients and treatment

The PORT patient cohort for our study was drawn from two prospective, randomized clinical trials (NCT02977169 and NCT02974426) launched in November 2016 to evaluate the efficacy and optimal timing of PORT in completely resected stage III-N2 NSCLC patients. Inclusion criteria for participants of NCT02977169 and NCT02974426 included being over 18 years of age with an Eastern Cooperative Oncology Group performance status of 0 or 1, having undergone complete resection (lobectomy or sleeve resection), and being pathologically diagnosed with T1–3N2M0 NSCLC [according to the tumor-node-metastasis (TNM) classification in the Union for International Cancer Control 7th edition (18)]. Complete resection was defined as tumor-free resection margins and systematic nodal assessment with at least three N2 stations sampled or completely dissected, one of which must be the subcarinal station (19). Patients who underwent wedge resections, segmentectomies, or pneumonectomies, received R1 or R2 resections, or had prior neoadjuvant or adjuvant treatment were excluded.

The PORT cohort in this study consisted exclusively of patients meeting the following eligibility criteria: (I) compliance with two registered clinical trials; (II) completion of protocol-adherent PORT delivery; and (III) availability of verifiable dosimetric parameters, serial CT surveillance (≥12 months), and longitudinal clinical documentation.

Radiotherapy was administered through IMRT with a linear accelerator with 6-MV photons on five consecutive days a week. CTV was defined as the bronchial stump along with lymph node regions 2L, 2R, 4L, 4R, 5, 6, 7, 10L, and 11L for left-sided NSCLC patients, while in right-sided cases, it covered the bronchial stump, 2R, 4R, 7, 10R, and 11R (13,14). Simultaneous integrated boost IMRT to high-risk regions [defined as gross tumor volume (GTV)] was also allowed. Planning target volume (PTV) consisted of CTV plus a 5–8 mm margin (PTV-C) and GTV plus a 5–8 mm margin (PTV-G). The prescribed dose was 50.4 Gy delivered at 1.8 Gy per fraction for PTV-C and 60.2 Gy delivered at 2.15 Gy per fraction for PTV-G. All treatment plans were designed to deliver at least 95% of the dose to PTV and 99% of the dose to 95% of PTV. The dose constraints for the surrounding organs were as follows: MLD <13 Gy, V20 <23%, maximum spinal cord dose <45 Gy, and mean heart dose <30 Gy. The timing and plans of chemotherapy were determined by medical oncologists based on individual status. Patients in the study were scheduled to receive 4 cycles of a platinum-based doublet regimen as adjuvant chemotherapy

Clinical and dosimetric factors

Patient demographics and medical history were collected, including age, gender, smoking status, tumor location, surgical approach, histology, stage of disease, timing of chemotherapy, and number of chemotherapy cycles. Patients who had smoked more than 10 pack-years or had quit smoking for less than 15 years were defined as heavy smokers. We also gathered the DICOM planning images, radiotherapy structures, and the prescription dose for each patient. Total lung volume (TLV) was defined as the volume of the remaining lung minus the CTV. Evaluated dose-volume histogram (DVH) parameters included CTV, PTV, MLD, V5–45 (Vx refers to the percentage of lung volume exceeding x Gy, and x ranges from 5–45 in increments of 5 Gy), V13 and the absolute lung volume spared from a 5 Gy dose (VS5).

Endpoint and statistical analysis

The endpoint of this study was G2+ RP defined in the Common Terminology Criteria for Adverse Events, version 5.0. The cumulative incidence of RP was calculated from the beginning of PORT to the occurrence of RP or the last follow-up date. Follow-up visits were conducted at 1, 3, 6, 9 and 12 months respectively after the completion of radiotherapy. Toxicities were evaluated by at least two experienced radiation oncologists and reported as the maximum grade observed during the follow-up.

Baseline patient and treatment characteristics were summarized using descriptive statistics, with categorical variables expressed as total numbers and percentages. The association between DVH parameters was evaluated using the Pearson correlation coefficient. Prior to further analyses, all continuous variables were converted into categorical variables based on the cutoff values selected to maximize the log-rank test statistic for G2+ RP. The cumulative incidence of RP was evaluated using the Kaplan-Meier method (calculated as 1 minus the Kaplan-Meier survival estimate), and differences across groups were assessed using log-rank tests. Feature selection was performed through least absolute shrinkage and selection operator (LASSO) regression (10-fold cross-validation) to identify key prognostic variables. Univariable and multivariable Cox proportional hazards models subsequently evaluated these covariates, which enables the construction of a clinical prediction model via a nomogram. The discriminative ability of the nomogram was evaluated using the concordance index (C-index) and time-dependent C-index curves. Calibration curves were used to assess the model’s goodness-of-fit, and decision curve analysis (DCA) evaluated its clinical utility. Bootstrapping with 500 resamples was performed for internal validation. All analyses were conducted using R software (version 4.3.3), with two-sided tests and a P value <0.05 indicating statistical significance.

Results

Patient clinical characteristics

Between July 2016 and January 2022, 265 eligible participants were enrolled in the original trials at our institution, of whom 197 were scheduled to receive PORT according to the research protocol. After excluding 19 patients (5 patients refused PORT, 6 received PORT at other institutions, 3 lacked available radiotherapy plans, and 5 experienced disease progression after enrollment), the final PORT cohort for analysis in this study comprised 178 patients (Figure 1).

Figure 1 Flowchart showing the selection process of the PORT cohort for our study. LRR, locoregional recurrence; NSCLC, non-small cell lung cancer; pIII, pathologic stage III; PORT, postoperative radiotherapy; RT, radiotherapy.

Patient, tumor and treatment characteristics are summarized in Table 1. The median age was 60.5 years. Most patients underwent lobectomy (98%) and received sequential chemoradiation (79%), with 171 patients (96%) completing at least four cycles of chemotherapy and 176 (99%) completing the full course of PORT. One patient discontinued PORT for personal reasons after completing 22 of the 28 scheduled fractions, and the other due to logistical challenges related to the coronavirus disease 2019 (COVID-19) pandemic.

Of the 178 patients, the median MLD, V5, V20 and CTV were 9.5 Gy, 35.4%, 18.3% and 90 cc, respectively. Twenty-one individuals developed G2+ RP, and 5 patients experienced grade 3 RP; no grade 4 or grade 5 cases were reported. The cumulative incidence of G2+ RP was 3.9%, 10.7%, and 11.8% by 3, 6, and 12 months, respectively. For grade 3 RP, the cumulative incidence was 1.2% by 3 months and increased to 2.9% by 6 months. The median time to G2+ RP diagnosis for the 21 affected patients was 4.5 months, with most cases (19 of 21) occurring within 7 months of initiating radiotherapy.

Identification of optimal predictive factors

In the univariable Cox regression analysis, age was the only significant clinical factor associated with G2+ RP, along with several dosimetric parameters including MLD, VS5, and V10–45 (Table 2). Due to strong correlations among dosimetric metrics (Figure S1), we applied LASSO regression with 10-fold cross-validation to refine variable selection. This process yielded six key factors for further analysis: VS5, age, V13, V35, V40, and tumor laterality (Figure S2).

Subsequently, a stepwise backward multivariable Cox regression based on the Akaike information criterion (AIC) identified three independent predictors of G2+ RP: age ≥67 years, V13 ≥25%, and VS5 <1,230 cc (Table 3, Figure S3).

Construction of the model and risk stratification

A nomogram was constructed to estimate the risk of G2+ RP at 3, 6 and 12 months based on the results of the multivariable Cox regression model, which included VS5, V13, and age (Figure 2A). The length of the lines in the nomogram was proportional to the beta coefficient values in the final multivariable model, reflecting the relative significance of predictors. Notably, the absolute values of the beta coefficients for these three variables were closely matched (0.98, 0.96, and 1.22), indicating that each factor carried a similar weight in the model. We therefore reasoned that a simple accumulation of present risk factors would correlate with an elevated risk of G2+ RP. Stratification of patients into four groups based on their risk factor count (0, 1, 2, or 3) revealed a stepwise increase in the 12-month cumulative incidence of G2+ RP (3.7%, 10.7%, 25.0%, and 60.0%, respectively). We subsequently merged these subsets to establish a simplified risk stratification, categorizing the patient cohort into the low-risk group (0 or 1 risk factor, G2+ RP incidence of 6.6%) and the high-risk group (2 or 3 risk factors, G2+ RP incidence of 29.3%) (P<0.0001, Kaplan-Meier curves shown in Figure 2B).

Figure 2 Nomogram-based risk stratification of G2+ RP. (A) A nomogram for estimating 3-month, 6-month and 12-month G2+ RP based on VS5, V13 and age. The total points projected on the bottom scales correspond to the predicted probability for an individual patient. (B) Cumulative incidence curves of G2+ RP in high- and low-risk groups. The shaded areas represent the 95% confidence intervals. The difference between the two groups was assessed using the log-rank test. G2+ RP, grade ≥ 2 radiation pneumonitis; V13, the percentage of lung volume exceeding 13 Gy; VS5, the absolute lung volume spared from a 5 Gy dose.

To explore practical dose-limiting strategies for G2+ RP, we stratified the cohort based on the baseline risk factor count of age and VS5. Given that the G2+ RP incidence rose as the risk factor count increased, we considered a risk-adapted strategy using stricter V13 thresholds to potentially reduce the RP rate. To theoretically limit the G2+ RP incidence to less than 5%, we derived exploratory V13 thresholds for subgroups with 0 and 1 baseline risk factors (<27% and <23%, respectively). The cutoffs were determined by identifying the lowest 5% margin of the V13 distribution among patients who experienced the event within each respective subgroup (Table 4). For the highest-risk subgroup (age ≥67 years and VS5 <1,230 cc), a precise dose threshold could not be established due to the limited sample size (N=8). As the lowest observed V13 in this group was 20.6%, we advise keeping the V13 strictly below this minimum (V13 <20%) for this specific population.

Validation of the model

The bootstrap-corrected C-index values for the different models were presented in Table 5, with time-dependent C-index curves shown in Figure 3A. The nomogram demonstrated the highest C-index of 0.757, exhibiting superior prognostic accuracy for predicting G2+ RP at 3, 6, and 12 months compared to models based solely on either dosimetric or clinical factors.

Figure 3 Evaluation of the nomogram. (A) Time-dependent C-index curves for different predicting factors or models. (B) Calibration curve for predicting 12-month G2+ RP with 500-bootstrap-resampling validation. The dashed line indicates the ideal model while the red line represents the actual performance of the nomogram. (C) Decision curve analysis of different prediction models for 12-month G2+ RP. The “All” line shows the net benefit for a strategy of treating all patients; the “None” line shows the net benefit of treating no patients. G2+ RP, grade ≥2 radiation pneumonitis; V13, the percentage of lung volume exceeding 13 Gy; VS5, the absolute lung volume spared from a 5 Gy dose.

The calibration curve of the nomogram validated by bootstrap resampling was displayed in Figure 3B. A strong agreement was illustrated between the predicted probabilities of 12-month G2+ RP and the actual probabilities. The DCA indicated that the nomogram, based on both clinical and dosimetric parameters, provided the highest net benefits across various threshold probabilities, suggesting its potential to support clinical decision-making in certain patient subsets (Figure 3C). Collectively, these findings confirmed that the model, which included V13, VS5, and age, achieved the best performance in predicting G2+ RP outcomes in the PORT cohort of our study.

Discussion

Based on this secondary analysis of prospectively collected data, our study revealed that the risk of G2+ RP in the postoperative setting is driven by the interplay among clinical factor (age) and dosimetric factors associated with low-dose irradiation to the lung. Age (≥67 years), V13 (≥25%), and VS5 (<1,230 cc) emerged as key predictors. The model incorporating these factors provided accurate risk evaluation, and the count of risk factors effectively identified the high-risk patients with 2 or 3 risk factors.

In our analyzed cohort, the 12-month cumulative incidences were 11.8% for G2+ RP and 2.9% for grade 3 RP, with no grade 4 or 5 events observed. The 1-year observation period was established to cover the typical RP development timeframe (3–12 months after PORT) and correspond to the standard 1-year course of adjuvant immunotherapy (5,20). Our G2+ RP rate is comparable to the 10–19% reported in several studies investigating PORT (8-10), though higher than the 6% incidence from the PORT-C trial (3). This discrepancy may be attributed to the PORT-C cohort’s younger population (76.6% <60 years) and stricter lung dose constraints (V20 <20%, MLD <12 Gy).

Age was an influential predictive clinical factor in our analysis, consistent with previous literature. Multiple studies identify older age as a primary independent risk factor for grade ≥3 RP (21-23). Nevertheless, there is no consensus on a definitive age threshold, with proposed cutoffs ranging from 65 to 70 years. The increased susceptibility in older patients may result from poorer baseline lung function and compromised tissue repair capacity.

The identification of VS5 as a predictor superior to relative volume metrics (V5) is a central finding of this study. VS5 was initially introduced as an alternative low-dose exposure indicator to V5, and further proved to correlate with RP among NSCLC patients (22,24,25). Notably, V5 was not significantly associated with G2+ RP in our PORT cohort, which may result from the unique anatomical context of the postoperative lung. Unlike intact lungs, where relative percentages (V5) serve as adequate surrogates for functional reserve, the surgically reduced TLV in our cohort renders absolute volume metrics (VS5) physiologically more relevant. Our data suggest that ensuring a critical threshold of absolute functional lung volume is indispensable for safety, whereas merely limiting the percentage of irradiated lung may be misleading when the denominator (TLV) is decreased.

Besides VS5, V13 was also incorporated into our predictive model. Previous studies observed a pronounced decline in lung function when local doses exceeded 13 Gy (26), and V13 also served as an effective predictor of RP in several studies (27,28). The necessity of including both VS5 and V13 was demonstrated by our data (Table 4), where V13 remained relatively comparable across subgroups while G2+ RP rates varied significantly. Overall, the integration of an absolute volumetric parameter (VS5) with a relative intermediate-dose parameter (V13) and age provided a comprehensive prediction of RP risk.

Our findings contribute directly to the long-standing debate on whether irradiating “a lot to a little” or “a little to a lot” is more determinant in promoting pulmonary toxicity. While some studies emphasize high-dose regions as critical (29,30), other research highlights the importance of low-dose metrics. In the PORT setting, Boonyawan et al. identified V10 >30% and V20 >20% as predictors, while Shepherd et al. recommended limiting V5 (9,10). Consistent with these findings, our results revealed that low-dose irradiation to large lung volumes is a key driver of RP among PORT-treated patients. A plausible explanation lies in the lower prescription doses characteristic of the postoperative setting (typically 50 Gy) compared to definitive radiotherapy. With the reduced intensity of high-dose regions, the relative contribution of widespread low-dose irradiation to pulmonary inflammation becomes the predominant driver of toxicity. Since modern IMRT often creates such low-dose regions, our findings advocate prioritizing the absolute volume of spared lung (VS5) over conventional dose-volume constraints (V5, V20).

Our study is innovative in proposing both a predictive model for RP risk and risk-adapted dose limits to lower RP incidence. We introduced a simple risk factor count for 12-month G2+ RP occurrence, categorizing patients into low-risk (0 or 1 factor) and high-risk (2 or 3 factors) groups. To provide an exploratory reference for dose constraints, we derived risk-adapted V13 thresholds based on the baseline risk factor count, with the theoretical aim of limiting the G2+ RP incidence to <5%:

• 0 risk factor (age <67 years, VS5 ≥1,230 cc): V13 <27%;
• 1 risk factor (age ≥67 years, VS5 ≥1,230 cc or age <67 years, VS5 <1,230 cc): V13 <23%;
• 2 risk factors (age ≥67 years, VS5 <1,230 cc): For this highest-risk group, while an insufficient sample size precluded establishing a definitive dose limit, we cautiously recommend V13 <20%. Given their exceedingly high (50%) incidence of G2+ RP, the decision to administer subsequent immunotherapy or other systemic therapies warrants careful evaluation.

Likewise, Shepherd et al. also proposed stratified dose limits for PORT patients, suggesting lung V5 limited to 36% rather than 65% in patients over 65 years to reduce the risk of G2+ RP (10). Our framework advances this concept by integrating anatomical volume (VS5) with age and dose. By clarifying the interplay among these factors, we offer a practical tool to personalize treatment planning and minimize excessive low-dose lung irradiation, particularly for elderly patients or those with compromised residual lung volume.

A key strength of our study lies in the reliability of the data and a highly homogeneous cohort. The prospective data collection process ensured an adequate sample size and complete follow-up. In contrast to previous literature that included heterogeneous populations (patients receiving wedge resections, pneumonectomies, non-R0 resections, proton therapy or 3D-CRT), our study focused predominantly on patients receiving IMRT-based PORT after lobectomy. This well-defined cohort enabled a comprehensive analysis of dosimetric and clinical factors, which highlighted the significance of remaining lung volume exposed to low-dose irradiation (VS5) in predicting G2+ RP among patients with compromised lung function after surgery. Building on this foundation, our primary contribution is the development of the first predictive model and risk stratification framework specifically tailored for this patient population, which demonstrated superior discriminative performance over existing models.

One of the limitations of this study is the lack of external validation. Model performance might also be enhanced by incorporating heart dose metrics (mean heart dose, V16), baseline subclinical interstitial lung changes, and relevant biomarkers (31,32). In addition, the complex statistical modeling strategy was not prespecified in the original trial protocol, rendering the present work a post-hoc analysis. Importantly, the multivariable model was constructed with only 21 events of G2+ RP, which increases the risk of overfitting and reduces statistical power for subgroup analyses. Consequently, the risk-adapted V13 thresholds (Table 4) and the proposed target of limiting the G2+ RP rate to <5% should be viewed as exploratory and hypothesis-generating rather than as definitive clinical criteria. Finally, as our trial was initiated prior to the standard adoption of adjuvant immunotherapy or targeted therapy, our analysis does not account for the synergistic pulmonary toxicity of immune checkpoint inhibitors and targeted agents (33-35). Further studies are necessary to validate these predictors.

Conclusions

In this secondary analysis of completely resected NSCLC patients receiving PORT, lung toxicity was generally manageable. We identified age (≥67 years), V13 (≥25%), and VS5 (<1,230 cc) as key risk factors associated with G2+ RP. An internally validated nomogram incorporating these factors was developed to estimate G2+ RP probability. Additionally, patients stratified as high-risk (2 or 3 risk factors) demonstrated a significantly higher incidence of G2+ RP, warranting closer monitoring. To reduce G2+ RP incidence, we further proposed V13 dose constraints tailored to patient subgroups based on age and VS5. Together, these findings highlight the importance of minimizing low-dose lung irradiation in the postoperative setting. However, given the relatively limited number of events, the results should be interpreted as cautious references that require validation in larger, prospective cohorts.

Acknowledgments

Portions of this study were presented as a poster abstract at the ASTRO’s 67th Annual Meeting in 2025.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1-1414/rc

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1-1414/prf

Funding: This work was supported by the Major Research Plan of the National Natural Science Foundation of China (No. 92059206, to X.F.) and the National Natural Science Foundation of China (No. 82103010, to W.F. and No. 82304065, to Y.Y.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1-1414/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Li Y, Juergens RA, Finley C, et al. Current and Future Treatment Options in the Management of Stage III NSCLC. J Thorac Oncol 2023;18:1478-91. [Crossref] [PubMed]
2. Wu YL, Tsuboi M, He J, et al. Osimertinib in Resected EGFR-Mutated Non-Small-Cell Lung Cancer. N Engl J Med 2020;383:1711-23. [Crossref] [PubMed]
3. Felip E, Altorki N, Zhou C, et al. Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB-IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, open-label, phase 3 trial. Lancet 2021;398:1344-57. Erratum in: Lancet 2021;398:1686.
4. Forde PM, Spicer J, Girard N, et al. 84O Neoadjuvant nivolumab (N)+ platinum-doublet chemotherapy (C) for resectable NSCLC: 3-y update from CheckMate 816. J Thorac Oncol 2023;18:S89-90.
5. Le Pechoux C, Pourel N, Barlesi F, et al. Postoperative radiotherapy versus no postoperative radiotherapy in patients with completely resected non-small-cell lung cancer and proven mediastinal N2 involvement (Lung ART): an open-label, randomised, phase 3 trial. Lancet Oncol 2022;23:104-14. [Crossref] [PubMed]
6. Hui Z, Men Y, Hu C, et al. Effect of Postoperative Radiotherapy for Patients With pIIIA-N2 Non-Small Cell Lung Cancer After Complete Resection and Adjuvant Chemotherapy: The Phase 3 PORT-C Randomized Clinical Trial. JAMA Oncol 2021;7:1178-85. [Crossref] [PubMed]
7. National Comprehensive Cancer Network (2026). Non-small cell lung cancer NCCN guidelines Version 3. Available online: https://www.nccn.org/professionals/physician_gls/pdf/nscl.pdf (accessed February 12, 2026).
8. Zhao L, Ji W, Ou G, et al. Risk factors for radiation-induced lung toxicity in patients with non-small cell lung cancer who received postoperative radiation therapy. Lung Cancer 2012;77:326-30. [Crossref] [PubMed]
9. Boonyawan K, Gomez DR, Komaki R, et al. Clinical and Dosimetric Factors Predicting Grade ≥2 Radiation Pneumonitis After Postoperative Radiotherapy for Patients With Non-Small Cell Lung Carcinoma. Int J Radiat Oncol Biol Phys 2018;101:919-26. [Crossref] [PubMed]
10. Shepherd AF, Iocolano M, Leeman J, et al. Clinical and Dosimetric Predictors of Radiation Pneumonitis in Patients With Non-Small Cell Lung Cancer Undergoing Postoperative Radiation Therapy. Pract Radiat Oncol 2021;11:e52-62. [Crossref] [PubMed]
11. Tang X, Li Y, Tian X, et al. Predicting severe acute radiation pneumonitis in patients with non-small cell lung cancer receiving postoperative radiotherapy: Development and internal validation of a nomogram based on the clinical and dose-volume histogram parameters. Radiother Oncol 2019;132:197-203. [Crossref] [PubMed]
12. Dang J, Li G, Zang S, et al. Comparison of risk and predictors for early radiation pneumonitis in patients with locally advanced non-small cell lung cancer treated with radiotherapy with or without surgery. Lung Cancer 2014;86:329-33. [Crossref] [PubMed]
13. Feng W, Fu XL, Cai XW, et al. Patterns of local-regional failure in completely resected stage IIIA(N2) non-small cell lung cancer cases: implications for postoperative radiation therapy clinical target volume design. Int J Radiat Oncol Biol Phys 2014;88:1100-7. [Crossref] [PubMed]
14. Feng W, Zhang Q, Yu W, et al. Feasibility and safety of the clinical target volume design for postoperative radiation therapy in completely resected stage IIIA (N2) non-small cell lung cancer: a prospective validation study. Int J Radiat Oncol Biol Phys 2016;96:E445.
15. Zhang CC, Yu W, Zhang Q, et al. A decision support framework for postoperative radiotherapy in patients with pathological N2 non-small cell lung cancer. Radiother Oncol 2022;173:313-8. [Crossref] [PubMed]
16. Zhang CC, Hou RP, Xia WY, et al. Prognostic index for estimating the survival benefit of postoperative radiotherapy in pathologic N2 non-small cell lung cancer: A real-world validation study. Lung Cancer 2021;156:100-8. [Crossref] [PubMed]
17. Zhang SX, Zhang CC, Hou RP, et al. Is postoperative radiotherapy effective in patients with completely resected pathologic stage IIIA(N2) non-small cell lung cancer? High-risk populations should consider it. Clin Transl Radiat Oncol 2025;50:100889.
18. Detterbeck FC, Boffa DJ, Tanoue LT. The new lung cancer staging system. Chest 2009;136:260-71. [Crossref] [PubMed]
19. Rami-Porta R, Wittekind C, Goldstraw P, et al. Complete resection in lung cancer surgery: proposed definition. Lung Cancer 2005;49:25-33. [Crossref] [PubMed]
20. O’Brien M, Paz-Ares L, Marreaud S, et al. Pembrolizumab versus placebo as adjuvant therapy for completely resected stage IB-IIIA non-small-cell lung cancer (PEARLS/KEYNOTE-091): an interim analysis of a randomised, triple-blind, phase 3 trial. Lancet Oncol 2022;23:1274-86.
21. Vogelius IR, Bentzen SM. A literature-based meta-analysis of clinical risk factors for development of radiation induced pneumonitis. Acta Oncol 2012;51:975-83. [Crossref] [PubMed]
22. Tsujino K, Hashimoto T, Shimada T, et al. Combined analysis of V20, VS5, pulmonary fibrosis score on baseline computed tomography, and patient age improves prediction of severe radiation pneumonitis after concurrent chemoradiotherapy for locally advanced non-small-cell lung cancer. J Thorac Oncol 2014;9:983-90. [Crossref] [PubMed]
23. McFarlane MR, Hochstedler KA, Laucis AM, et al. Predictors of Pneumonitis After Conventionally Fractionated Radiotherapy for Locally Advanced Lung Cancer. Int J Radiat Oncol Biol Phys 2021;111:1176-85. [Crossref] [PubMed]
24. Sato M, Odagiri K, Tabuchi Y, et al. Patterns and Incidence of Pneumonitis and Initial Treatment Outcomes with Durvalumab Consolidation Therapy after Radical Chemoradiotherapy for Stage III Non-Small Cell Lung Cancer. Cancers (Basel) 2024;16:1162. [Crossref] [PubMed]
25. Chen J, Hong J, Zou X, et al. Association between absolute volumes of lung spared from low-dose irradiation and radiation-induced lung injury after intensity-modulated radiotherapy in lung cancer: a retrospective analysis. J Radiat Res 2015;56:883-8. [Crossref] [PubMed]
26. Gopal R, Tucker SL, Komaki R, et al. The relationship between local dose and loss of function for irradiated lung. Int J Radiat Oncol Biol Phys 2003;56:106-13. [Crossref] [PubMed]
27. Uno T, Isobe K, Kawakami H, et al. Dose-volume factors predicting radiation pneumonitis in patients receiving salvage radiotherapy for postlobectomy locoregional recurrent non-small-cell lung cancer. Int J Clin Oncol 2006;11:55-9. [Crossref] [PubMed]
28. Schallenkamp JM, Miller RC, Brinkmann DH, et al. Incidence of radiation pneumonitis after thoracic irradiation: Dose-volume correlates. Int J Radiat Oncol Biol Phys 2007;67:410-6. [Crossref] [PubMed]
29. Alharbi M, Janssen S, Golpon H, et al. Temporal and spatial dose distribution of radiation pneumonitis after concurrent radiochemotherapy in stage III non-small cell cancer patients. Radiat Oncol 2017;12:165. [Crossref] [PubMed]
30. Briere TM, Krafft S, Liao Z, et al. Lung Size and the Risk of Radiation Pneumonitis. Int J Radiat Oncol Biol Phys 2016;94:377-84. [Crossref] [PubMed]
31. Kuipers ME, van Doorn-Wink KCJ, Hiemstra PS, et al. Predicting Radiation-Induced Lung Injury in Patients With Lung Cancer: Challenges and Opportunities. Int J Radiat Oncol Biol Phys 2024;118:639-49. [Crossref] [PubMed]
32. Zhu Y, Yan Y, Fu J, et al. Reducing radiation pneumonitis in lung cancer patients: from Chinese expert consensus to practice. Transl Lung Cancer Res 2025;14:2747-59. [Crossref] [PubMed]
33. Bi J, Meng R, Yang D, et al. Dosimetric predictors of radiation pneumonitis in patients with prior immunotherapy exposure: A multi-institutional analysis. Radiother Oncol 2024;190:110040. [Crossref] [PubMed]
34. Nie T, Chen Z, Cai J, et al. Integration of dosimetric parameters, clinical factors, and radiomics to predict symptomatic radiation pneumonitis in lung cancer patients undergoing combined immunotherapy and radiotherapy. Radiother Oncol 2024;190:110047. [Crossref] [PubMed]
35. Xu Y, Qie W, Zhong X, et al. Incidence and risk factors of pneumonitis in ALK-rearranged non-small cell lung cancer patients treated with alectinib and thoracic radiotherapy. Transl Lung Cancer Res 2025;14:2723-35. [Crossref] [PubMed]