Prognostic impact of dose to circulating blood cells in non-small cell lung cancer patients after chemoradiotherapy

Introduction

Radiotherapy plays a critical role in the management of locally advanced non-small cell lung cancer (NSCLC), especially in combination with chemotherapy and immunotherapy. However, it may cause unintended systemic effects on the immune system. One key manifestation is radiation-induced lymphopenia (RIL)—a sustained drop in circulating lymphocyte counts following radiation (1-4). RIL is frequently observed in NSCLC patients undergoing chemoradiotherapy (CRT), with grade 3 or higher lymphopenia occurring in over 80% of patients (5). Importantly, RIL is not merely a laboratory finding; it has emerged as a significant prognostic factor associated with poorer outcomes across multiple solid tumors, including NSCLC (6). In the era of consolidation immunotherapy following CRT, RIL holds even greater prognostic importance, with multiple studies consistently demonstrating that RIL diminishes the clinical efficacy of immune checkpoint inhibitors.

Research efforts have increasingly focused on identifying what predisposes patients to RIL after CRT, with attention to both treatment-related and patient-related factors (7). In particular, dosimetric factors play a critical role in lymphocyte depletion. Lymphocytes are extremely radiosensitive; preclinical studies show that even very low radiation doses (≤0.1 Gy) cause measurable lymphocyte depletion without a clear threshold, indicating that exposure of large body volumes to low radiation doses can significantly reduce circulating lymphocytes. There is also growing interest in defining the circulating blood pool as an organ at risk (OAR), in addition to established lymphoid organs such as the spleen, thymus, lymph nodes, and bone marrow (8). In an effort to quantify the impact of radiation on the immune system, various models have been proposed to estimate the radiation dose to circulating blood, including the effective dose to immune cells (EDIC) and the hematological dose (HEDOS) framework (9,10). While EDIC calculates the immune dose based on organ-level exposure, HEDOS integrates blood flow dynamics to provide a stochastic estimate of the actual dose received by circulating lymphocytes, potentially offering a more precise correlation with RIL (11).

Besides dosimetric factors, individual hematologic parameters and immune status influence the risk and severity of RIL. Patients with a lower baseline absolute lymphocyte count (ALC) or compromised immune status are generally more susceptible to experiencing profound lymphopenia during treatment (12). Conversely, a robust immune system—evidenced by higher baseline lymphocyte counts or the presence of tumor-infiltrating lymphocytes—has been associated with better treatment responses and survival (12). These findings align with the broader evidence that an intact host immune system is crucial for controlling cancer, becoming even more important in the immunotherapy era (13). Thus, both the radiation dose-volume metrics and the patient’s hematologic profile contribute to predicting which patients are likely to develop RIL. Identifying these predictors is clinically important, as it may enable risk-adapted strategies (for example, tailoring radiation plans or using supportive measures) to mitigate lymphopenia and improve outcomes.

Despite the growing recognition that RIL adversely affects survival, there remains a significant gap in current clinical guidelines. Present radiotherapy planning guidelines for NSCLC mainly provide dose constraints to protect traditional OARs (such as lungs, heart, spinal cord, and esophagus). Although consensus guidelines for defining immune-related OARs have not yet been established, systematic reviews and ongoing studies are making efforts to identify appropriate dose constraints for sparing immune structures during radiotherapy (7,8). Data accumulation is urgently needed to establish evidence-based recommendations in this area. Our hypothesis was that the circulating blood dose is associated with both RIL and survival of NSCLC patients. By systematically studying hematologic and dosimetric predictors of RIL, including blood dose, and correlating them with patient outcomes, the field can move toward defining safe radiation dose thresholds that preserve immune function. We present this article in accordance with the REMARK reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-547/rc).

Methods

Study population

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Seoul National University Hospital (No. H-2003-145-1111) and individual consent for this retrospective analysis was waived. We retrospectively investigated 241 patients with locally advanced NSCLC who received definitive CRT at Seoul National University Hospital between 2012 and 2018. All patients underwent concurrent radiation and chemotherapy [3-dimensional (3D), n=151; and intensity modulated radiotherapy (IMRT), n=90]. None of the patients had metastatic tumors. All patients received a radiotherapy dose of over 60 Gy. The standard treatment for most patients was either 60 Gy delivered in 30 fractions or 66 Gy in 33 fractions. A subset of patients (n=12) underwent hypofractionated radiation therapy (RT), with per-fraction doses ranging from 2.25 to 4 Gy and total doses between 60 and 80 Gy. The predominant chemotherapy regimens were weekly administrations of carboplatin and paclitaxel (n=153) or cisplatin and docetaxel (n=81). Neoadjuvant chemotherapy was not used, and a small number of patients (n=11) received consolidation immunotherapy following radiotherapy. Table 1 presents detailed information.

Assessment of radiation exposure and hematologic parameters

Data on differential blood count were obtained at baseline and during (weekly) CRT. Severe RIL (SRIL) was defined as an ALC nadir of <200/µL during CRT, consistent with grade 4 lymphopenia according to Common Terminology Criteria for Adverse Events 5.0 (CTCAE) criteria (14). Dose-volume histogram (DVH) parameters for whole body, heart, lung, great vessels, spleen, liver, esophagus and thoracic vertebral bodies were evaluated. DVH parameters for each structure were the percentage volumes receiving 5 Gy (V5), 10 Gy (V10), 20 Gy (V20), 30 Gy (V30), 40 Gy (V40), 50 Gy (V50), and 60 Gy (V60). The absolute volume of the planning target volume (PTV) and total beam on time were analyzed separately as continuous variables. Radiation exposure to circulating blood was estimated using the following two models.

Blood dose volume histogram (bDVH) using HEDOS framework

HEDOS is a time-dependent computational framework that simulates the circulating blood cells in 28 organs and calculates the DVH of blood cells based on an International Commission on Radiological Protection (ICRP) reference blood flow network (9,15). A whole-body blood flow network in HEDOS was created to produce the spatiotemporal distribution of blood particles (BPs) based on the reference cardiac output, blood volume, and flow rates from ICRP Publication 89 (15). At the end of the simulation, the bDVH is created by tracking the dose received by all BPs.

We simulated 10⁴ BPs per patient to describe the situation in which blood cells receive radiation through the RT. The organ DVH of the heart, large arteries, large veins, lung, liver, stomach, esophagus, and spleen were extracted and used to calculate the bDVH in HEDOS. The RT variables of beam-on-time and fraction number were used as input parameters in HEDOS.

Effective dose to circulating immune cells

The development of EDIC aimed to assess the extent of immune cell damage and its influence on the toxicity experienced by cancer patients undergoing RT. EDIC estimated the blood dose using the relationship between the blood-containing organs and blood flow from cardiac output. It was also reflected the irradiation time of blood utilizing blood circulation time and the number of fractions (16). In this study, EDIC was calculated for all patients using mean lung dose (MLD), mean heart dose (MHD), mean liver dose (MlD), integral dose of the body (ITD), and the total number of fractions (n) based on the following equation ([Eq.1]). EDIC during RT was also calculated using the equation ([Eq.1]) and the half of the total fraction number.

EDIC=0.12∗MLD+0.08∗MHD+0.15∗0.85∗MlD∗(n45)1/2+[0.45+0.35∗0.85∗(n0.85)1/2]∗ITD62∗103[1]

Statistical analysis

The primary endpoint of our study was the occurrence of SRIL during CRT. Secondary endpoints included overall survival (OS) and progression-free survival (PFS). Univariate and multivariate logistic regression analyses were conducted to identify hematologic and dosimetric factors significantly associated with SRIL. Hematologic variables—including white blood cell count (WBC), hemoglobin (Hb), platelet (PLT), ALC, and absolute neutrophil count (ANC)—were evaluated for their associations with RIL. Dosimetric variables included DVH parameters for the body, esophagus, great vessels, heart, liver, lungs, spleen, vertebrae, and the HEDOS, as well as EDIC and PTV (Table S1). For survival analysis, patient characteristics were additionally considered along with these hematologic and dosimetric variables (Table S2). Additionally, univariate and multivariate Cox proportional-hazards regression models were used to determine factors influencing OS and PFS. P values from univariate analyses were adjusted for multiple comparisons using the false discovery rate (FDR) method. Among variables significantly associated (FDR <0.05) with each endpoint from univariate analyses, pairs or groups of highly correlated variables (|r| >0.8) were identified (Figure S1). Within each highly correlated group, the variable with the lowest P value from the corresponding univariate analysis was selected as the representative predictor to minimize multicollinearity for the subsequent multivariate logistic regression and Cox proportional-hazards regression analyses. Bidirectional stepwise selection was applied during multivariate analyses to identify optimal sets of predictors. Internal validation of the multivariable logistic regression model was performed using 10-fold cross-validation. The area under the receiver operating characteristic curve (AUC) and 95% confidence interval (CI) were estimated using bootstrap resampling (1,000 iterations). Nonlinear associations between dosimetric parameters and survival outcomes were evaluated using generalized additive models (GAM). Thresholds indicating significant hazard increases were determined by analyzing the first derivatives and their CIs from fitted smooth terms. Patients were subsequently classified into risk groups according to these thresholds, and Kaplan-Meier survival analyses were performed to compare survival outcomes between groups. Statistical analyses were performed using Python 3.9 and R software 4.2.1.

Results

Hematologic changes and incidence of hematologic toxicities during CRT

During CRT, myelosuppression occurred across all evaluated hematologic parameters (Figure 1). ALC demonstrated the most pronounced decrease, with an average reduction of 81.7%, compared to ANC (49.1%), PLT count (39.0%), and Hb level (14.4%). Evaluating hematologic nadirs, grade 3 lymphopenia (ALC ≤500 cells/µL) occurred in 207 patients (85.8%), and grade 4 lymphopenia (ALC ≤200 cells/µL) was observed in 68 patients (28.2%). In contrast, grade 3 neutropenia occurred in 26 patients (10.8%), grade 3 anemia in 13 patients (5.4%), and grade 3 thrombocytopenia in 6 patients (2.5%), which were relatively less common.

Figure 1 Changes in hematologic parameters pre- and during CRT. Violin plots illustrate the distributions of ALC, Hb, PLT, and ANC before (baseline, blue) and during CRT (nadir values, orange). Dashed black lines within the violins represent the median and quartiles of these data. Clinically significant hematologic toxicity grades are indicated by horizontal dashed lines according to Common Terminology Criteria for Adverse Events, version 5.0: grade 3 lymphopenia (ALC <500 cells/µL), grade 4 lymphopenia (ALC <200 cells/µL), grade 2 anemia (Hb <10.0 g/dL), grade 3 anemia (Hb <8.0 g/dL), grade 2 thrombocytopenia (PLT <75×10³/µL), grade 3 thrombocytopenia (PLT <50×10³/µL), grade 3 neutropenia (ANC <1,000 cells/µL), and grade 4 neutropenia (ANC <500 cells/µL). Significant reductions were observed across all parameters during CRT compared to baseline levels. ALC, absolute lymphocyte count; ANC, absolute neutrophil count; CRT, concurrent chemoradiotherapy; Hb, hemoglobin; PLT, platelet count.

Factors predicting SRIL

Given the well-established association between SRIL and poor clinical outcomes, univariate logistic regression analysis was performed to identify predictive factors for SRIL. Baseline hematologic variables, dosimetric parameters, and clinical factors, including age, sex, radiotherapy modality, chemotherapy regimen, weight, and height, were evaluated. After correction for multiple comparisons (FDR <0.05), baseline ALC and Hb levels emerged as significant hematologic predictors. Significant dosimetric factors included irradiated volumes to circulating blood, body, esophagus, great vessels, heart, lung, and thoracic vertebral bodies. Lower-dose irradiated volumes (V5–V20) generally predicted SRIL effectively, while higher-dose volumes (V30–V50) were significant predictors for vertebral bodies and esophagus (Table S1). The EDIC demonstrated marginal significance in predicting SRIL (OR =1.236, P=0.09), but this association was not maintained after FDR correction (FDR =0.12). Notably, chemotherapy regimen was not significantly associated with SRIL in either univariate or multivariate analyses (Figure S2). To address multicollinearity in the multivariable analysis, highly correlated dosimetric variables (r ≥0.8) were filtered. Following bidirectional stepwise selection, multivariable logistic regression analysis identified hematological and dosimetric factors significantly associated with SRIL: minimum blood dose (HEDOS D100), volume of lung receiving ≥10 Gy (lung V10), baseline ALC, and baseline Hb levels (Figure 2A). Higher HEDOS D100 (OR: 1.259, 95% CI: 1.017–1.567, P=0.04) and higher lung V10 (OR: 1.034, 95% CI: 1.006–1.066, P=0.02) were associated with increased SRIL risk, whereas higher baseline Hb levels (OR: 0.823, 95% CI: 0.683–0.987, P=0.04) correlated with reduced SRIL risk. Baseline ALC demonstrated borderline significance with an OR close to 1 (OR: 0.999, 95% CI: 0.999–1.000, P=0.02). The predictive performance of this multivariable logistic model was evaluated using 10-fold cross-validation, yielding an AUC of 0.721 (95% CI: 0.652–0.790) (Figure 2B). Additionally, the relationships between each significant predictor and the risk of SRIL were visualized using effect plots (Figure 2C). These plots demonstrate an increasing probability of SRIL with higher HEDOS D100 and Lung V10, indicating dose-dependent relationships. Conversely, higher baseline ALC and Hb levels showed inverse relationships, predicting lower SRIL probabilities. Figure 3 showed that HEDOS D100 (R=−0.23, P<0.001) and Lung V10 (R=−0.23, P<0.001) were correlated with ALC during CRT. Baseline ALC (R=0.35, P<0.001) and Hb level (R=0.19, P=0.004) also emerged as influential factors associated with ALC during CRT.

Figure 2 Logistic regression analysis for predicting SRIL and model performance. (A) Forest plot displaying ORs and 95% CIs for factors associated with lymphopenia risk identified through multivariate logistic regression. Variables HEDOS D100 (per Gy increase), Lung V10 (per 1% increase), baseline ALC (per cells/µL increase), and baseline Hb (per g/dL increase). P values indicate the statistical significance of each predictor. (B) ROC curve demonstrating the predictive performance of the logistic regression model, evaluated via 10-fold cross-validation. The shaded area indicates the 95% CI. The AUC was 0.721 (95% CI: 0.652–0.790), reflecting moderate discriminatory capability. (C) Effect plots illustrating the predicted probability of SRIL according to dosimetric and hematologic variables. ALC, absolute lymphocyte count; AUC, area under the curve; CI, confidence interval; Hb, hemoglobin; HEDOS D100, minimum dose covering 100% of circulating blood; OR, odds ratio; ROC, receiver operating characteristic; SRIL, severe radiation-induced lymphopenia; V10, volume receiving ≥10 Gy.

Figure 3 Correlation between HEDOS D100 (Gy), Lung V10 (%), baseline ALC (cells/ μL), baseline Hb (g/dL), and ALC during chemoradiotherapy (CRT ALC, cells/ μL). Dashed lines represent fitted linear regression lines; shaded areas indicate 95% CI. ALC, absolute lymphocyte count; CI, confidence interval; CRT, chemoradiotherapy; Hb, hemoglobin; HEDOS D100, minimum dose covering 100% of circulating blood; V10, volume receiving ≥10 Gy.

Dosimetric predictors of survival outcomes

The median OS was 35.0 months (95% CI: 29.0–41.0), and the median PFS was 10.0 months (95% CI: 8.0–12.0). Univariate analyses revealed significant associations between survival outcomes (OS and PFS) and both clinical and dosimetric variables (Table S2). For OS, patient sex, PTV volume, smoking history, baseline Hb levels, and irradiated volumes of the body (V5–V60) and spleen (V5–V50) showed significant associations (FDR <0.05). In terms of PFS, significant factors included irradiated volumes of the body (V5–V60) and PTV volume (FDR <0.05).

Previous analyses identified HEDOS D100 and Lung V10 as key dosimetric predictors of SRIL; however, initial evaluations did not demonstrate significant associations of these factors, as continuous variables, with survival outcomes. To further explore potential threshold effects, we applied GAM, which identified critical thresholds where hazard rates significantly increased: 8.29 Gy for HEDOS D100 and 49% for Lung V10 (Figure 4A). Kaplan-Meier survival analysis stratified by these thresholds demonstrated significantly worse OS (P<0.001) and PFS (P=0.003) among patients receiving HEDOS D100 above 8.29 Gy. Likewise, lung V10 values above 49% were significantly associated with reduced OS (P=0.04), though no significant difference was observed for PFS (Figure 4B). Multivariate Cox regression analyses confirmed HEDOS D100 ≥8.29 Gy as a robust independent predictor of both worse OS (HR 2.073, 95% CI: 1.252–3.432, P=0.005) (Table 2) and worse PFS (HR 2.046, 95% CI: 1.191–3.514, P=0.01) (Table 3). Additional significant predictors of worse OS included higher splenic irradiated volume (Spleen V30; HR 1.028, 95% CI: 1.003–1.055, P=0.03), male sex (HR 2.825, 95% CI: 1.655–4.822, P<0.001), larger PTV volume (HR 1.001, 95% CI: 1.001–1.002, P<0.001), and lower baseline Hb levels (HR 0.799, 95% CI:0.716–0.892, P<0.001). For PFS, additional prognostic factors included older age (HR 0.981, 95% CI: 0.965–0.998, P=0.03) and larger PTV volume (HR 1.001, 95% CI: 1.001–1.002, P<0.001). These results collectively highlight that, beyond circulating blood dose, splenic dose, patient demographics, and baseline hematologic parameters—especially Hb levels—play critical roles in influencing survival outcomes following CRT.

Figure 4 Non-linear effects of dosimetric parameters on survival outcomes and Kaplan-Meier survival analysis stratified by identified thresholds. (A) GAMs demonstrating the non-linear relationships between dosimetric parameters—HEDOS D100 (Gy) and Lung V10 (%)—and survival outcomes: OS and PFS. The solid black lines represent fitted smooth functions, and the shaded regions indicate 95% CIs. The rug plots at the bottom of each panel indicate individual patient data points. (B) Kaplan-Meier survival curves illustrating OS and PFS stratified by thresholds derived from GAM analysis (HEDOS D100: 8.29 Gy, Lung V10: 49%). Statistical significance between groups was assessed using log-rank tests, with P values indicated within each plot. Shaded regions represent 95% CIs. CI, confidence interval; GAM, generalized additive model; HEDOS D100, minimum dose covering 100% of circulating blood; OS, overall survival; PFS, progression-free survival; V10, volume receiving ≥10 Gy.

Discussion

In this study, we identified the HEDOS D100 and baseline Hb levels as critical predictors of SRIL and survival outcomes in patients with NSCLC undergoing CRT. Higher HEDOS D100 was strongly associated with increased risk of SRIL and poorer clinical outcomes, demonstrating a clear threshold effect on survival, with significantly worse prognosis when the dose exceeded 8.29 Gy. This finding underscores the importance of identifying and adhering to critical circulating blood dose thresholds to preserve immune function and enhance patient prognosis.

Our results reinforce the existence of an immune dose-response relationship, highlighting HEDOS D100 as a dominant factor in predicting SRIL. Higher values of HEDOS D100, indicative of universal radiation exposure to circulating lymphocytes, elevated the risk of profound lymphocyte depletion. Lung V10 also emerged as an important predictor of SRIL, correlating closely with low-dose irradiated volumes (V5–V10) of thoracic structures, including the lung, heart, great vessels, and thoracic vertebral bodies, as well as with the EDIC (Figure S1). These observations align with existing evidence emphasizing the importance of minimizing extensive low-dose irradiation of thoracic tissues to reduce lymphopenia (5,7,8,17-19). Notably, HEDOS demonstrated superior predictive ability compared to low-dose thoracic irradiation metrics and EDIC, suggesting that stochastic modeling approaches like HEDOS could provide more accurate assessments of immune dose than traditional deterministic methods.

Furthermore, our analyses identified multiple independent predictors of OS and PFS. HEDOS D100 emerged as a robust independent predictor, directly linking higher circulating blood doses with poorer outcomes, presumably through excessive immune system compromise and reduced antitumor immunity. Additionally, higher spleen irradiation negatively influenced survival, emphasizing the spleen’s role as a radiosensitive, immune-rich organ frequently irradiated inadvertently during thoracic CRT (20). This highlights the importance of incorporating splenic dose constraints into radiotherapy planning. Baseline Hb levels were also independently associated with both SRIL and worse survival outcomes. Traditionally recognized as an indicator of tumor hypoxia, our findings further suggest anemia may reflect compromised bone marrow reserve and systemic immune dysfunction, contributing to poor clinical outcomes.

To reduce circulating blood dose in NSCLC patients undergoing CRT, treatment plans should aim to minimize radiation exposure to organs involved in blood circulation. As shown in Figure S1, HEDOS D100 exhibited a relatively strong correlation (R>0.49) with dosimetric parameters of organs such as the heart, thoracic vertebrae, and great vessels. Among these, Heart V20 showed the highest correlation (R=0.57). Therefore, reducing radiation dose to blood flow-related organs may be a reasonable strategy in radiotherapy planning to spare the circulating blood dose.

HEDOS is a stochastic blood dose metric, which results in dose variability depending on the number of BPs. In this study, we simulated 10⁴ BPs to calculate the circulating blood dose of the patients. We observed that as the number of BPs increased, the mean HEDOS derived from the stochastic bDVH exhibited reduced variability across 10 simulations [number of BPs: 10⁴, mean HEDOS D100 (95% CI): 5.34 (5.25–5.43) Gy] (Figure S3).

In addition to nadir ALC during treatment, previous studies have highlighted the prognostic importance of delayed lymphopenia (5) and the ALC recovery index (defined as ALC at 6 months divided by baseline ALC) (21). These findings suggest that not only the depth of lymphocyte suppression but also the capacity for immune reconstitution may influence long-term outcomes. While radiation to circulating blood results in transient lymphocyte pool depletion, sustained lymphopenia may reflect underlying hematopoietic dysfunction. In this context, radiation dose to bone marrow reservoirs, particularly in the thoracic vertebrae and pelvis, may play a critical role in determining recovery potential. Thus, beyond minimizing blood dose, preserving bone marrow integrity through dose-sparing strategies may represent an additional avenue to mitigate immunosuppression. Further studies are warranted to evaluate the interaction between marrow radiation dose, hematopoietic reserve, and lymphocyte recovery dynamics in patients receiving thoracic CRT.

Despite these important findings, this study has limitations. It was retrospective and single-institutional, potentially introducing selection bias and limiting generalizability. The modest sample size restricts robust subgroup analyses, particularly regarding the role of consolidation immunotherapy. Given that consolidation immunotherapy is now a standard component of care in locally advanced NSCLC, the small number of immunotherapy-treated patients in our cohort (n=11) may limit the robustness of OS interpretation. Future studies including larger cohorts of patients receiving immunotherapy are warranted to validate our findings and ensure their generalizability in contemporary clinical settings. Additionally, the HEDOS model simplifies complex blood flow dynamics and does not fully capture inter-patient variability or dose heterogeneity within the circulating blood pool. Nevertheless, our study provides significant clinical insights, highlighting the need for prospective validation of HEDOS-based metrics and exploration of lymphocyte-sparing radiotherapy techniques. Potential strategies include reducing low-dose irradiation volumes and adopting advanced radiotherapy methods such as proton beam therapy (PBT). Notably, recent prospective evidence from a randomized phase II trial in esophageal cancer demonstrated that PBT significantly reduced the incidence of grade 4 lymphopenia compared to IMRT, particularly among patients with intermediate baseline lymphocyte counts and large treatment volumes, underscoring the potential immune-sparing benefit of PBT in the CRT setting (22). Future studies should also evaluate adjunctive interventions aimed at protecting immune function, particularly in patients with higher predicted blood doses or baseline anemia.

Conclusions

Minimizing radiation exposure to immune-related organs, including circulating blood and spleen, alongside addressing baseline hematologic health, particularly Hb, is essential for optimizing outcomes in NSCLC patients undergoing CRT. These insights advocate multidisciplinary approaches—spanning optimized radiation delivery, careful patient selection, and supportive interventions—to enhance patient prognosis in the modern era of combined modality treatments and immunotherapy.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-547/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-547/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-547/prf

Funding: This work was supported by grants from the National Research Foundation of Korea (NRF, Grant Nos. NRF-2021R1A2C1095168, and RS-2023-00218623 to J.H.L.) funded by the Ministry of Science and ICT. This work was supported by grant from the National Research Foundation of Korea (NRF, No. 2021R1C1C1005930 to W.S.) funded by the Korea government (MSIT).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-547/coif). J.H.L. reports that this work was supported by grants from the National Research Foundation of Korea (NRF, Grant Nos. NRF-2021R1A2C1095168, and RS-2023-00218623 to J.H.L.) funded by the Ministry of Science and ICT. W.S. reports that this work was supported by grants from the National Research Foundation of Korea (NRF, No. 2021R1C1C1005930) funded by the Korea government (MSIT). The other 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. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Seoul National University Hospital (No. H-2003-145-1111) and individual consent for this retrospective analysis was waived.

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/.

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