Predictors and Prognostic Stratification of Bronchiolitis Obliterans Syndrome After Pediatric Allogeneic Hematopoietic Stem Cell Transplantation

Predictors and Prognostic Stratification of Bronchiolitis Obliterans Syndrome After Pediatric Allogeneic Hematopoietic Stem Cell Transplantation | 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 Predictors and Prognostic Stratification of Bronchiolitis Obliterans Syndrome After Pediatric Allogeneic Hematopoietic Stem Cell Transplantation Canran WANG, Guoyu DING, Xiaoyue ZHANG, Hongjuan LI, Yan GU, Yan HAN, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7974938/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Bronchiolitis Obliterans Syndrome (BOS) following pediatric allogeneic hematopoietic stem cell transplantation (allo-HSCT) is associated with high morbidity and mortality, largely due to diagnostic delays and static prognostic assessments. This study aimed to validate the value of a strategy based on dynamic pulmonary function monitoring for early warning and prognostic stratification in the management of pediatric BOS. Methods This single-center, retrospective cohort study included 201 children who underwent allo-HSCT between January 2015 and December 2024, comprising 29 patients with BOS and 172 non-BOS controls. Independent risk factors for BOS were identified using multivariate Cox regression analysis. We evaluated the diagnostic performance of an "at-risk stage" warning signal based on the relative decline in Forced Expiratory Volume in 1 second (FEV1). In the longitudinal cohort of BOS patients, the independent predictive value of the FEV1 decline rate within the first 3 months post-diagnosis for progression-free survival (PFS) was investigated. The longitudinal trajectories of pulmonary function and high-resolution computed tomography (HRCT) imaging scores were also compared. Results The cumulative incidence of pediatric BOS at our center was 6.9%. Multivariate analysis identified grade III-IV acute graft-versus-host disease (aGVHD) (HR = 15.12), chronic GVHD (cGVHD) (HR = 6.94), dry cough (HR = 11.77), and an early post-transplant FEV1/FVC decline of ≥ 10% (HR = 8.70) as independent risk factors for BOS development. Using a relative FEV1 decline of ≥ 10% (termed BOS stage 0p) as an early warning signal advanced the diagnostic window by a mean of 176 days and demonstrated a high negative predictive value of 84.95%. For prognosis, a rapid FEV1 decline (≥ 25%) within the first 3 months post-diagnosis was a strong independent predictor for inferior PFS (adjusted HR = 30.68, 95% CI: 3.39-277.79, P = 0.002), independent of the NIH severity grade at diagnosis. Furthermore, a significant "radio-functional discordance" was revealed, where HRCT structural damage scores continued to worsen even as pulmonary function stabilized in some patients (P < 0.001). Conclusion This study confirms that a strategy based on dynamic pulmonary function monitoring effectively addresses key challenges in pediatric BOS management. Monitoring the relative decline in FEV1 serves as a sensitive early warning tool, significantly advancing the diagnostic window. Moreover, assessing the early FEV1 decline rate post-diagnosis provides a powerful dynamic tool for achieving precise prognostic stratification and guiding individualized treatment escalation. The evaluation of BOS treatment response should concurrently address functional improvement and potential underlying structural deterioration. Bronchiolitis Obliterans Syndrome Allogeneic Hematopoietic Stem Cell Transplantation Children Pulmonary Function Test Prognosis Risk Stratification Figures Figure 1 Figure 2 Figure 3 1 Introduction Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for a variety of malignant and non-malignant hematological diseases in children [ 1 , 2 ] . With continuous advancements in transplantation techniques, the long-term survival rates for pediatric patients have significantly improved. Consequently, the management of late post-transplant complications, particularly pulmonary complications, has emerged as a central challenge affecting quality of life and overall prognosis. Among these, Bronchiolitis Obliterans Syndrome (BOS), one of the most severe non-infectious pulmonary complications, is a key manifestation of chronic graft-versus-host disease (cGVHD) in the lungs. Characterized by small airway inflammation and progressive fibrosis, BOS has a reported incidence of 4.5%–8.3% in pediatric allo-HSCT recipients [ 3 ] . Clinically, BOS is characterized by an insidious onset, rapid progression, and high rates of morbidity and mortality, with a 5-year survival rate for affected children as low as 45.0–59.0% [ 4 ] . However, this grim prognosis is largely attributable to two core challenges in the current clinical management of BOS: diagnostic delay and static prognostic assessment. First, significant diagnostic delays lead to missed therapeutic windows [ 5 ] . The early symptoms of BOS, such as dry cough and mild dyspnea on exertion, are non-specific and easily overlooked. The current diagnostic gold standard, the National Institutes of Health (NIH) consensus criteria, relies primarily on fixed absolute thresholds of pulmonary function (e.g., FEV1 < 75% of predicted value) [ 6 ] . This standard essentially confirms significant, established functional impairment, meaning that by the time of diagnosis, most patients have already entered an irreversible stage of airway fibrosis, thereby missing the optimal window for intervention [ 5 ] . Studies have shown that up to 18.8% of patients with biopsy-proven BOS still have an FEV1 above the 75% diagnostic threshold [ 7 ] , exposing the critical insensitivity of the current criteria. To address this, a new expert consensus has proposed using a relative FEV1 decline from an individual's baseline (e.g., ≥ 10%) as a warning signal for an "At-Risk Stage" [ 8 ] . However, the predictive efficacy of this proactive concept and the extent to which it can advance the diagnostic window in real-world pediatric cohorts remain unclear. Second, the static nature of prognostic assessment hinders individualized treatment decision-making. The disease course of BOS patients exhibits significant heterogeneity: some patients may remain stable for long periods, while others deteriorate rapidly and respond poorly to standard therapies. Existing severity grading systems are primarily based on the FEV1 level at the time of diagnosis, representing a one-time, static evaluation that fails to capture the dynamic aggressiveness of the disease. This makes it difficult for clinicians to effectively identify high-risk individuals prone to rapid deterioration, often causing treatment escalation to lag behind disease progression, which is another major contributor to poor outcomes in severe cases. Furthermore, although guidelines recommend regular pulmonary function monitoring (e.g., every 3 months post-transplant) for high-risk groups [ 6 ] , the definition of "high-risk" is not standardized, and there is a lack of effective dynamic tools to assess the disease trajectory and prognosis after a BOS diagnosis. Given these clinical challenges and research gaps, this study aims to provide a set of dynamic monitoring-based assessment tools for the management of pediatric BOS through a retrospective analysis. We first identified the independent risk factors for the development of BOS in our institutional cohort. Subsequently, to address the critical issue of diagnostic delay, we validated the clinical efficacy of relative FEV1 decline as a warning signal for the "at-risk stage." To overcome the challenge of static prognostic assessment, we further investigated whether the rate of FEV1 decline early after diagnosis could serve as an independent prognostic predictor. Finally, we longitudinally tracked the evolving relationship between pulmonary function and HRCT imaging to better understand the "functional-structural" characteristics of disease progression. This study aims to provide evidence-based support for establishing a new management strategy for pediatric BOS, one that encompasses the entire chain of "early warning, dynamic stratification, and precision intervention." 2 Materials and Methods 2.1 Study Design and Patient Cohort This was a single-center, retrospective cohort study conducted at the Department of Pediatric Hematology, the First Affiliated Hospital of Shandong First Medical University. The study protocol was approved by the Institutional Review Board (IRB) of our hospital (Approval No. YXLL-KY-2025(009)). Given the retrospective nature of the data analysis, the IRB waived the requirement for informed consent. We retrospectively reviewed all children aged ≤ 18 years who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) at our center between January 2015 and December 2024. The inclusion criteria were: (1) a confirmed diagnosis of BOS post-transplant and receipt of systematic peri-transplant pulmonary function test (PFT) monitoring; and (2) complete clinical and follow-up data. Exclusion criteria were: (1) pre-existing severe pulmonary diseases that could interfere with the assessment (e.g., cystic fibrosis, severe asthma); (2) prior receipt of experimental cellular therapies for BOS; and (3) inability to perform reproducible PFTs to establish a reliable baseline due to age or cognitive reasons. During the study period, a total of 467 children underwent allo-HSCT. According to the 2014 National Institutes of Health (NIH) consensus criteria [ 5 ] , 32 patients were diagnosed with BOS. Among the cohort meeting the inclusion/exclusion criteria for this study, a final total of 201 children were included in the final analysis, comprising 29 patients with BOS (the BOS group) and 172 patients without BOS (the non-BOS group) as controls. 2.2 BOS-related Definitions and Diagnostic Criteria The final diagnosis and severity grading of BOS strictly adhered to the 2014 NIH cGVHD consensus criteria [ 6 ] . A diagnosis required the simultaneous fulfillment of the following: (1) evidence of airflow limitation, defined as an FEV1/FVC ratio < 0.7 or below the fifth percentile of the predicted value; (2) an irreversible decline in FEV1 to < 75% of the predicted value, with a relative decline from baseline of ≥ 10% within two years; (3) absence of clinical, radiological, and microbiological evidence of active respiratory infection; and (4) presence of supportive imaging features, such as air trapping, bronchial wall thickening, or bronchiectasis on high-resolution computed tomography (HRCT). Operational Revision for Infection Exclusion: Considering that infection and BOS can coexist or mutually trigger each other, this study implemented an operational revision to criterion (3) for clinical practice. This revision aimed to address the limitation of the NIH standard, which does not explicitly handle situations where infection and BOS coexist. If a patient's decline in pulmonary function occurred concurrently with symptoms of infection, standardized anti-infective therapy was administered first. A definitive diagnosis of BOS was established only if the decline in pulmonary function persisted or worsened after the completion of anti-infective treatment, and all other NIH criteria were met. The severity of BOS was graded based on the FEV1 percent predicted at the time of diagnosis [ 9 ] : mild (FEV1 ≥ 60%), moderate (FEV1 40%-59%), and severe (FEV1 10% from baseline or the Forced Expiratory Flow at 25–75% (FEF25-75) had declined by > 25%, but the diagnostic criteria for BOS had not yet been met. Table 1 National Institutes of Health (NIH) Severity Grading of Bronchiolitis Obliterans Syndrome Severity Grade Score FEV1, % predicted Clinical Symptoms Mild 0–1 ≥ 60% Asymptomatic or dyspnea after climbing one flight of stairs Moderate 2 40%-59% Dyspnea after walking on a flat road Severe 3 <40% Dyspnea at rest; oxygen required Definition of "At-Risk Stage" (Early Warning Signal): In this study, the "At-Risk Stage" was defined as the first occurrence of a relative FEV1 decline of ≥ 10% from an individual's stable baseline value during routine PFT monitoring. This concept, similar to "BOS stage 0p" mentioned in the literature, is intended to capture early pulmonary function abnormalities before formal diagnostic criteria are met. Once a patient reached this warning threshold, a comprehensive differential diagnosis process, including HRCT and infection screening, was immediately initiated. Definition of Prognostic Trajectory Stratification: To quantify the dynamic aggressiveness of the disease, patients were stratified into two groups based on the rate of FEV1 decline within the first 3 months of the BOS diagnosis: Rapid Decline (RD) group: Defined as a relative FEV1 decline of ≥ 25% within the first 3 months post-diagnosis. Gradual Decline (GD) group: Defined as a relative FEV1 decline of < 25% during the same period. 2.3 Treatment Protocol All children diagnosed with BOS received standardized therapy centered on immunosuppression. The first-line treatment regimen included corticosteroids (e.g., methylprednisolone) combined with a calcineurin inhibitor (CNI), such as tacrolimus or cyclosporine [ 10 ] . For cases of steroid-refractory disease or disease progression, treatment was escalated to second-line therapies, including mycophenolate mofetil (MMF) or ruxolitinib [ 11 ] . All drug dosages were individually adjusted based on clinical response, patient tolerance, and therapeutic drug monitoring, in accordance with institutional treatment protocols. 2.4 Data Collection and Assessment Standardized data extraction forms were used by researchers to retrospectively collect data from the electronic medical record system. Baseline data included demographic characteristics, primary diseases, and allo-HSCT-related parameters (e.g., conditioning regimen, graft source, grade of acute/chronic GVHD). Longitudinal follow-up data encompassed clinical symptoms, serial PFT results, HRCT imaging assessments, treatment regimens, and survival outcomes. Pulmonary Function Tests (PFTs): All PFTs were performed and quality-controlled according to the American Thoracic Society/European Respiratory Society (ATS/ERS) guidelines [ 9 ] . Key parameters, including Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV1), the FEV1/FVC ratio, and Diffusing Capacity for Carbon Monoxide (DLCO), were recorded as both absolute values and percentages of predicted values. The PFT baseline was defined as the stable pulmonary function level prior to transplantation; if pre-transplant data were missing, the best stable value at 100 days post-transplant (D + 100) was used as the baseline. All children included in the study followed a standardized monitoring protocol: every 3 months for the first year post-transplant, and every 3–6 months thereafter. Imaging Assessment: Chest HRCT scans were evaluated by two independent, senior radiologists who were blinded to the clinical information. HRCT was primarily used to aid in diagnosis (e.g., identifying signs such as air trapping) and to exclude other pulmonary diseases. To quantify structural lung damage, the Bankier semi-quantitative scoring system was employed [ 12 ] . This system assesses three core indicators: bronchiectasis, mosaic perfusion (air trapping), and bronchial wall thickening. Each indicator was scored based on the number of affected lung lobes (1 lobe = 1 point; 2–3 lobes = 2 points; 4–5 lobes = 3 points), with a total score ranging from 0 to 9, where a higher score indicates more severe structural damage. 2.5 Study Endpoints and Statistical Analysis The primary endpoint of this study was the incidence of Bronchiolitis Obliterans Syndrome (BOS) following pediatric allogeneic hematopoietic stem cell transplantation (allo-HSCT). Secondary endpoints included the diagnostic performance of the early warning signal, progression-free survival (PFS) and overall survival (OS), the longitudinal evolution of pulmonary function (FEV1%), and the progression of structural damage on imaging (HRCT). All data were statistically analyzed using SPSS software (version 26.0), with a two-sided P-value < 0.05 considered statistically significant. The normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed data were presented as mean ± standard deviation (SD) and compared between groups using the independent samples t-test. Non-normally distributed data were presented as median (interquartile range, IQR) and compared using the Mann-Whitney U test. Categorical variables were expressed as frequency (percentage) and compared using the Chi-square test or Fisher's exact test. A multivariate Logistic regression model was used to analyze independent risk factors for the development of BOS. Survival curves were generated using the Kaplan-Meier method and compared between groups using the Log-rank test. To evaluate the independent prognostic value of the disease progression trajectory, a multivariate Cox proportional hazards regression model was constructed to assess its impact on progression-free survival (PFS) after adjusting for known confounding factors, such as FEV1 level at diagnosis and cGVHD severity. 3 Results 3.1 Independent Risk Factors for BOS Following Pediatric allo-HSCT During the study period, a total of 467 children who underwent allo-HSCT at our center were systematically followed up, among whom 32 were diagnosed with BOS, yielding a cumulative incidence of 6.9%. The median time to BOS diagnosis was 267 days post-transplant (IQR: 176–361 days). After screening, a final cohort of 201 children was included in the cross-sectional analysis for this study, comprising 29 patients with BOS (the BOS group) and 172 controls (the non-BOS group). In the univariate analysis, significant differences were observed in several baseline characteristics between the BOS and non-BOS groups (Table 2 ). Compared to the non-BOS group, a significantly higher proportion of patients in the BOS group had a malignant primary disease (51.7% vs. 29.7%, P = 0.031), received a myeloablative conditioning regimen (72.4% vs. 37.8%, P < 0.001), used a combination of peripheral blood and bone marrow as the graft source (75.9% vs. 50.0%, P = 0.012), developed grade III-IV aGVHD (51.7% vs. 7.0%, P < 0.001), and developed cGVHD (79.3% vs. 20.9%, P < 0.001). There were no statistically significant differences between the two groups in terms of age, sex, or baseline pulmonary function (FVC, FEV1, FEV1/FVC, and DLCO). Table 2 Comparison of Demographic and Clinical Baseline Characteristics Between the BOS and Non-BOS Groups Characteristic BOS Group (n = 29) Non-BOS Group (n = 172) P-value Age at transplant, median (IQR) 9.51 (8.73–10.30) 9.45 (9.18–9.72) 0.921 Sex, n (%) 0.530 Male 17 (58.6) 90 (52.3) Female 12 (41.4) 82 (47.7) Primary disease, n (%) 0.031 Non-malignant 14 (48.3) 121 (70.3) Malignant 15 (51.7) 51 (29.7) Conditioning regimen, n (%) < 0.001 Myeloablative 21 (72.4) 65 (37.8) Non-myeloablative 8 (27.6) 107 (62.2) ABO compatibility, n (%) 0.329 Identical 19 (65.5) 96 (55.8) Non-identical 10 (34.5) 76 (44.2) HLA match, n (%) 0.066 Matched 2 (6.9) 37 (21.5) Mismatched 27 (93.1) 135 (78.5) Graft source, n (%) 0.012 Peripheral blood stem cells 2 (6.9) 57 (33.1) PBSC + Bone marrow 22 (75.9) 86 (50.0) Cord blood 5 (17.2) 29 (16.9) Pre-transplant CT, n (%) 0.256 Abnormal 23 (79.3) 150 (87.2) Normal 6 (20.7) 22 (12.8) aGVHD, n (%) < 0.001 None 1 (3.5) 80 (46.5) Grade I-II 13 (44.8) 80 (46.5) Grade III-IV 15 (51.7) 12 (7.0) cGVHD, n (%) < 0.001 Yes 23 (79.3) 36 (20.9) No 6 (20.7) 136 (79.1) Pulmonary Function at Baseline FVC, % predicted 96.61 ± 2.05 97.20 ± 0.97 0.815 FEV1, % predicted 99.15 ± 2.78 101.43 ± 1.04 0.413 FEV1/FVC ratio, % 102.34 (100.56, 104.13) 104.92 (104.11, 105.73) 0.230 DLCO, % predicted 79.87 (76.94, 82.79) 74.69 (73.62, 75.76) 0.052 Note: Continuous variables are presented as mean ± standard deviation for normally distributed data or median (interquartile range, IQR) for non-normally distributed data. Categorical variables are presented as frequency (percentage). aGVHD, acute graft-versus-host disease; cGVHD, chronic graft-versus-host disease; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; DLCO, diffusing capacity for carbon monoxide. In the 201 children included in the cross-sectional analysis (29 in the BOS group, 172 in the non-BOS group), a multivariate Cox proportional hazards regression analysis ultimately identified four independent predictors for the development of BOS following pediatric allo-HSCT(Table 3 ): a history of grade III-IV aGVHD (HR = 15.12, 95% CI:1.25-182.66, P = 0.033), the development of cGVHD (HR = 6.94, 95%CI: 1.77–27.15, P = 0.005), the presence of dry cough within 6 months post-transplant (HR = 11.77, 95%CI:2.92–47.48, P = 0.001), and a decline in FEV1/FVC of ≥ 10% within 6 months post-transplant (HR = 8.70, 95% CI:1.22–62.22, P = 0.031). Table 3 Multivariate Cox Regression Analysis for Predicting BOS After Pediatric allo-HSCT Candidate predictors Multivariable analysis Characteristic HR (95% CI) P-value Primary disease (Malignant vs. Non-malignant) 0.67 (0.09–4.99) 0.693 Conditioning regimen (Myeloablative vs. Non-myeloablative) 2.10 (0.28–15.72) 0.472 Graft source PBSC (Ref.) 0.390 PBSC + Bone marrow 3.02 (0.50-18.32) 0.230 Cord blood 1.45 (0.12–17.01) 0.770 aGVHD grade None (Ref.) 0.073 Grade I-II 4.89 (0.46–51.90) 0.188 Grade III-IV 15.12 (1.25-182.66) 0.033 Presence of cGVHD (Yes vs. No) 6.94 (1.77–27.15) 0.005 FEV1 decline group Increase/No decline (Ref.) 0.914 Decline < 10% 1.46 (0.16–13.51) 0.737 Decline ≥ 10% 1.10 (0.12–10.17) 0.936 FEV1/FVC decline group Increase/No decline (Ref.) 0.084 Decline < 10% 2.15 (0.37–12.37) 0.392 Decline ≥ 10% 8.70 (1.22–62.22) 0.031 DLCO decline group Increase/No decline (Ref.) 0.800 Decline < 10% 0.52 (0.08–3.54) 0.505 Decline ≥ 10% 0.73 (0.13–3.94) 0.712 Presence of dry cough 11.77 (2.92–47.48) 0.001 Presence of hypoxemia 0.27 (0.04–1.89) 0.186 Presence of retractions 1.68 (0.07-38.00) 0.744 Presence of pulmonary wheezing 0.42 (0.02–7.69) 0.560 Recurrent respiratory infections 4.82 (0.40-58.03) 0.215 3.2 Identification and Diagnostic Performance Evaluation of Early Warning Signals for BOS 3.2.1 Predictive Value of Clinical Symptoms As shown in Table 4 , the incidence of dry cough, hypoxemia, retractions, pulmonary wheezing, and recurrent respiratory infections within 6 months post-transplant was significantly higher in the BOS group than in the non-BOS group (all P < 0.01). To further evaluate the value of each clinical symptom for the early identification of BOS, we calculated their diagnostic performance metrics, as presented in Table 5 . Dry cough was the most sensitive clinical symptom for BOS (sensitivity, 79.31%), indicating that the vast majority of patients with BOS exhibited this symptom. However, its specificity (21.51%) and positive predictive value (PPV, 38.33%) were low, meaning that dry cough is also very common among non-BOS patients, and relying solely on this symptom for a BOS diagnosis would lead to a high number of false positives. The negative predictive value (NPV) of dry cough was high at 95.74%, suggesting that children without this symptom are highly unlikely to have BOS, which makes it an effective tool for exclusion. The specificities for other signs and histories, such as hypoxemia, retractions, pulmonary wheezing, and recurrent grade II-III infections, were extremely low (ranging from 2.33% to 10.47%), and their sensitivities were also poor (ranging from 20.00% to 31.03%), demonstrating their limited value in early differential diagnosis. Table 4 Comparison of the Incidence of Early Post-Transplant Clinical Symptoms Between the BOS and Non-BOS Groups Characteristic BOS Group (n = 29) Non-BOS Group (n = 172) P-value Dry cough < 0.001 Yes 23 (79.31) 37 (21.51) No 6 (20.69) 135 (78.49) Hypoxemia 0.006 Yes 9 (31.03) 18 (10.47) No 20 (68.97) 154 (89.53) Retractions < 0.001 Yes 6 (20.69) 4 (2.33) No 23 (79.31) 168 (97.67) Pulmonary wheezing 0.005 Yes 6 (20.69) 7 (4.07) No 23 (79.31) 165 (95.93) Recurrent respiratory infections < 0.001 Grade 0-I 22 (75.86) 168 (97.67) Grade II-III 7 (24.14) 4 (2.33) Table 5 Diagnostic Performance of Different Clinical Symptoms for BOS Clinical Symptom Sensitivity Specificity Positive Predictive Value Negative Predictive Value Dry cough 79.31% 21.51% 38.33% 95.74% Hypoxemia 31.03% 10.47% 33.30% 88.51% Retractions 20.69% 2.33% 60.00% 87.96% 3.2.2 Predictive Value of Pulmonary Function Decline Compared to patients in the non-BOS group, children in the BOS group exhibited a significant and continuous decline in pulmonary function within the first 6 months post-transplant. The median FVC% predicted decreased from a pre-transplant value of 96.61% to 79.05% (P < 0.001), the FEV1% predicted decreased from 99.15% to 69.44% (P < 0.001), the FEV1/FVC% predicted decreased from 102.34% to 87.01% (P < 0.001), and the DLCO% predicted decreased from 79.87% to 66.33% (P = 0.003). As shown in Table 6 , the proportion of patients with a ≥ 10% decline from baseline in FEV1, FEV1/FVC, and DLCO predicted values within 6 months post-transplant was significantly higher in the BOS group than in the non-BOS group (P 10% or FEF25-75 decline > 25%) as an early warning indicator. Among the 29 patients in the BOS group, 15 (51.7%) had been identified as being in BOS stage 0p before meeting the NIH diagnostic criteria. These patients reached the BOS stage 0p warning threshold a median of 176 (range: 35–537) days before their formal BOS diagnosis, providing a potential window for early intervention. However, the diagnostic performance analysis (Table 7 ) revealed that while BOS stage 0p had a high NPV (84.95%), its sensitivity for identifying BOS was moderate (51.72%), and its specificity (54.07%) and PPV (13.89%) were low. This indicates that although BOS stage 0p can effectively rule out low-risk patients, its high false-positive rate limits its value as a standalone screening tool. It is more suitable as a "high-risk signal" that triggers a comprehensive evaluation. Table 6 Comparison of Subgroups Based on Changes in Pulmonary Function Parameters from Baseline within 6 Months Post-Transplant Change from Baseline BOS Group (n = 29) Non-BOS Group (n = 172) P-value FVC change subgroups (%) 0.326 0 5 (17.24) 40 (23.26) 1 7 (24.14) 58 (33.72) 2 17 (58.62) 74 (43.02) FEV1 change subgroups (%) 0.017 0 2 (6.90) 44 (25.58) 1 6 (20.69) 49 (28.49) 2 21 (72.41) 79 (45.93) FEV1/FVC change subgroups (%) < 0.001 0 6 (20.69) 90 (52.32) 1 9 (31.03) 63 (36.63) 2 14 (48.28) 19 (11.05) DLCO change subgroups (%) 0.047 0 7 (24.14) 67 (38.95) 1 6 (20.69) 51 (29.65) 2 16 (55.17) 54 (31.40) Note: 0 = Increase or no decline; 1 = Decline 10%) 48.28% 51.74% 13.59% 84.69% FEF25-75 0p (FEF25-75 decline > 25%) 34.48% 27.91% 17.24% 86.71% FEV1 or FEF25-75 0p (BOS 0p) 51.72% 54.07% 13.89% 84.95% 3.2.3 Early Indicative Role of HRCT Imaging Abnormalities Among the 31 BOS patients with complete imaging data, the primary findings on chest high-resolution computed tomography (HRCT) were airway abnormalities. The most common signs included mosaic perfusion (25/31, 80.6%), bronchial wall thickening (24/31, 77.4%), and bronchiectasis (16/31, 51.6%). Some patients developed reversible complications such as mucous plugging, subcutaneous/mediastinal emphysema, and bullae, which resolved after treatment. HRCT also demonstrated potential for early warning: in 11 of the 31 patients (35.5%), typical HRCT abnormalities preceded the pulmonary function findings indicative of BOS. An analysis of these 11 patients revealed that at the time of their first abnormal imaging finding, 7 had concurrent PFT data. Among these, 5 showed a decline in pulmonary function that had not yet reached the diagnostic threshold, while 2 had no significant pulmonary function abnormalities. This suggests that HRCT can provide earlier evidence of structural lesions in some children, but its diagnostic application needs to be combined with frequent pulmonary function monitoring to achieve precise early identification of BOS. 3.3 Disease Evolution and Prognostic Stratification After BOS Diagnosis 3.3.1 Pulmonary Function Trajectories Based on NIH Grading Reveal Heterogeneity in Disease Progression Among the 31 BOS patients included in the longitudinal analysis, patients were stratified according to the NIH criteria into mild (n = 11), moderate (n = 13), and severe (n = 7) groups. As shown in Fig. 1 , the post-treatment pulmonary function trajectories of each group exhibited significant heterogeneity. The FEV1% predicted values in the mild and moderate groups largely stabilized after treatment, with some patients in the mild group even recovering to > 80% of the predicted value. In contrast, the median FEV1% predicted in the severe group continuously declined within the first 6 months post-diagnosis, and the inter-individual variability progressively widened (with the difference between the 75th and 25th percentiles expanding to 32%), suggesting a more aggressive disease progression and a poor response to treatment in this subgroup. 3.3.2 Rate of FEV1 Decline is a Strong Independent Predictor of Survival Based on the rate of FEV1 decline within the first 3 months post-diagnosis, the 31 patients were stratified into a Rapid Decline group (RD, n = 4, 12.9%) and a Gradual Decline group (GD, n = 27, 87.1%). Kaplan-Meier survival analysis (Fig. 2 ) revealed a significant difference in progression-free survival (PFS) between the two groups. The median PFS for the RD group was only 9.0 months, whereas the median PFS for the GD group has not yet been reached (Log-rank test, P < 0.001). To validate the independent prognostic value of the disease progression trajectory, we constructed a multivariate Cox regression model. As shown in Table 8 , after adjusting for key confounding factors, namely the FEV1 level at diagnosis and the severity of aGVHD, a rapid progression trajectory (RD vs. GD) remained the strongest independent predictor of early-onset poor progression-free survival (adjusted HR = 30.68, 95% CI: 3.39-277.79, P = 0.002). Table 8 Multivariate Cox Regression Analysis of Factors Affecting Progression-Free Survival (PFS) in BOS Patients Risk Factor Adjusted HR (95% CI) P-value Rapid Progression Trajectory (RD vs. GD) 30.68 (3.39-277.79) 0.002 FEV1% predicted at BOS diagnosis 0.97 (0.92–1.02) 0.220 History of Grade III-IV aGVHD 2.55 (0.27–24.32) 0.416 3.4 "Radio-functional Discordance" in Disease Progression Longitudinal follow-up revealed a critical phenomenon of "radio-functional discordance" in the progression of BOS. As illustrated in Fig. 3 , although the FEV1 in many patients tended to stabilize after treatment, the mean Bankier semi-quantitative score, which reflects structural damage, showed a progressive increase. The score rose continuously and significantly from a mean of 2 points before treatment to 6 points after 2 years (P < 0.001). This indicates that even in patients whose ventilatory function appears stable, the underlying, irreversible small airway fibrosis and structural remodeling continue to advance. 3.5 Auxiliary Diagnostic Value of Flexible Bronchoscopy Among the 18 BOS patients who underwent flexible bronchoscopy, only 6 exhibited findings of bronchial branch occlusion. Of these, 3 primarily showed proximal bronchial dilation with partial sub-branch occlusion observed distally. One patient presented with an additional bronchial opening. The positive rate of this examination was not high in our cohort. Its main clinical value lay in excluding active infections or other pulmonary complications rather than in directly diagnosing BOS. 4 Discussion The management of Bronchiolitis Obliterans Syndrome (BOS) following pediatric allogeneic hematopoietic stem cell transplantation (allo-HSCT) is hampered by two major challenges: first, the lack of sensitive warning signals before the disease reaches an irreversible stage, and second, the inability to accurately identify high-risk individuals with a poor prognosis early after diagnosis. Through a systematic analysis of a pediatric cohort, this study proposes solutions based on dynamic monitoring to address these two challenges. We demonstrate for the first time in children that the early rate of FEV1 decline post-diagnosis is the strongest prognostic predictor, independent of baseline severity. Concurrently, we validated that a relative decline in pulmonary function from an individual's baseline can serve as an effective early "at-risk" warning signal. Furthermore, the "radio-functional discordance" phenomenon revealed in this study provides a new perspective for understanding the pathological progression of BOS and evaluating treatment response. Collectively, these findings establish a new, comprehensive management framework for pediatric BOS, extending from early identification to dynamic risk stratification. 4.1 BOS Epidemiology and High-Risk Factors The cumulative incidence of BOS at our center was 6.9%, which is consistent with the reported incidence of 4.5%-8.3% in international pediatric cohorts [ 3 ] . The results of our multivariate analysis confirm that a strong immune response is the primary driver of BOS pathogenesis: grade III-IV aGVHD dramatically increased the risk of BOS by 15.12-fold, while cGVHD increased the risk by 6.94-fold. Meanwhile, the presence of a dry cough within 6 months post-transplant increased the risk of BOS by 11.77-fold. Although this clinical symptom has a low positive predictive value, its high sensitivity and extremely high negative predictive value (95.74%) make it an ideal first-line, non-invasive exclusion tool that can be detected at any time without special equipment, helping to avoid unnecessary investigations in low-risk children. Dynamic monitoring of pulmonary function demonstrated core predictive value in our study. We found that a relative decline of ≥ 10% in the FEV1/FVC ratio from baseline within 6 months post-transplant was a strong independent predictor of BOS development (HR = 8.70). This finding has significant clinical implications: compared to the fixed absolute thresholds recommended in current guidelines (e.g., FEV1/FVC < 0.7), a relative decline based on an individual's own baseline is clearly more sensitive. Particularly in children with good pulmonary function reserve, absolute value abnormalities often appear much later, whereas capturing early relative changes can significantly advance the warning window, creating an opportunity for early intervention. 4.2 Value and Limitations of the Early Warning Strategy Our in-depth investigation into the clinical significance of obstructive physiological abnormalities that do not yet meet the diagnostic criteria for BOS (BOS stage 0p) [ 13 ] found that this state has a high negative predictive value (84.95%), confirming its effectiveness in ruling out the disease. However, its positive predictive value (PPV = 13.89%) and specificity (54.07%) were low, and only 51.7% of BOS patients were identified in the BOS 0p stage before their formal diagnosis. This result reflects the inadequacy of a single pulmonary function indicator as a standalone screening tool. The high false-positive rate could lead to anxiety among patients' families and potential over-intervention. Therefore, this study supports viewing the BOS 0p state as a "high-risk signal" that should trigger a comprehensive evaluation, including the immediate initiation of a full differential diagnosis (including HRCT and infection screening) and integrated assessment with other high-risk clinical factors. Future research should focus on developing a multifactorial predictive model that integrates clinical risk factors (e.g., severe aGVHD), symptoms (e.g., dry cough), pulmonary function trajectories, and novel biomarkers to improve the positive predictive value of early warnings. 4.3 The "Radio-functional Discordance" Phenomenon and its Pathological Significance Imaging plays a unique role in the early identification of BOS, but its evolution is not always synchronous with changes in pulmonary function [ 14 ] . This study found that in 11 patients (35.5%), typical HRCT abnormalities preceded pulmonary function indicators of BOS, suggesting that HRCT has an advantage in providing early warning of structural lesions. However, we observed a significant "radio-functional discordance": despite patients receiving systematic treatment, and with FEV1 stabilizing or even improving in the mild-to-moderate groups, the Bankier semi-quantitative score continued to show a progressive upward trend. This suggests that the irreversible structural damage of the small airways (fibrosis, bronchiectasis) was still worsening. The mechanisms for this discordance may include: (1) immunosuppressive therapy primarily targets the reversible inflammatory components of the airways but can hardly reverse established fibrotic obliteration; and (2) HRCT is highly sensitive to subtle structural deterioration, whereas the stability of global lung function (FEV1) may mask disease progression in certain regions. This finding strongly suggests that the evaluation of treatment response and disease progression in BOS should never rely solely on pulmonary function indicators. Clinicians must recognize that stable lung function may conceal underlying, ongoing structural damage. Therefore, a dual-dimensional monitoring strategy that combines HRCT imaging assessment (to measure structure) with pulmonary function monitoring (to measure function) is crucial for a comprehensive understanding of the disease state and for judging the true effectiveness of treatment. 4.4 The Critical Value of Disease Progression Trajectory and Prognostic Stratification The disease course and treatment response in BOS exhibit significant individual heterogeneity. This study is the first to introduce the concept of a disease progression trajectory in a pediatric cohort, stratifying patients into a Rapid Decline (RD) group and a Gradual Decline (GD) group. Multivariate Cox regression analysis confirmed that a rapid decline trajectory (relative FEV1 decline ≥ 25% within 3 months of diagnosis) is a strong prognostic predictor, independent of the severity at diagnosis (NIH grading) and systemic cGVHD status. Longitudinal data showed that while pulmonary function in most mild-to-moderate patients stabilized with individualized treatment, patients in the RD group and those with severe BOS continued to deteriorate rapidly in the early phase (within 6 months). This heterogeneity is consistent with findings from other studies [ 15 , 16 ] , suggesting that current treatment protocols (often based on intensified GVHD therapy and pulmonary symptom management) are not effective for severe BOS patients with a rapid progression trajectory. Therefore, it is crucial to move beyond the static NIH grading at diagnosis and adopt a prognostic stratification based on the rate of early dynamic changes. This approach can precisely identify the subgroup with the poorest response to standard therapy and the worst prognosis (the RD group), providing clinicians with a critical evidence base for promptly escalating treatment (e.g., targeted anti-fibrotic drugs, novel immunosuppressants, mesenchymal stem cell (MSC) therapy, or early pulmonary rehabilitation). The clinical practice recommendations proposed in this study (Table 8 ) are based on this evidence, aiming to shift the management of pediatric BOS from a "one-size-fits-all" model to individualized, risk-stratified therapy. Table 8 Key Recommendations for Clinical Practice Domain Recommendation Clinical Significance Screening Frequency Maintain PFT monitoring every 3 months during the first year post-transplant. Ensures timely capture of early declines in pulmonary function. Early Warning A relative FEV1 decline of ≥ 10% should immediately trigger a comprehensive BOS evaluation (including HRCT and infection screening). Advances the diagnostic window, creating an opportunity for early intervention. Prognostic Stratification After BOS diagnosis, stratify patients into a high-risk rapid progression group based on a threshold of ≥ 25% relative FEV1 decline within 3 months. Precisely identifies the subgroup with highly aggressive disease. Treatment Intensification Patients in the Rapid Decline (RD) group should be considered to have high-risk/refractory BOS, and escalation of immunosuppressive therapy or enrollment in clinical trials must be actively considered. Achieves individualized, risk-stratified therapy to improve outcomes for high-risk patients. 4.5 Conclusion and Future Perspectives In summary, the core contribution of this study is to provide critical, dynamic change-based evidence for decision-making in the management of pediatric post-HSCT BOS, thereby addressing the shortcomings of traditional static assessment metrics. Specifically, we have established two assessment tools that can be directly applied in clinical practice: first, by monitoring the relative decline in early post-transplant pulmonary function (especially FEV1/FVC), we propose a more sensitive early warning strategy to identify "at-risk" children; second, we confirmed that the early rate of FEV1 decline post-diagnosis is a strong prognostic predictor independent of disease severity at diagnosis, providing a new method for achieving precise prognostic stratification and risk-guided treatment escalation. Furthermore, the "radio-functional discordance" phenomenon revealed in this study offers an important supplement to existing efficacy evaluation systems, emphasizing the necessity of parallel monitoring of structural damage and functional impairment. This study also has some limitations. First, as a single-center, retrospective study, it may be subject to selection bias, and the sample size, particularly in the longitudinal subgroup analyses, was limited. The generalizability of its findings requires validation in prospective, multicenter cohorts. Second, we were unable to routinely use more sensitive methods for detecting early small airway disease, such as the multiple breath washout (MBW) technique. Looking ahead, future research should include: 1) validating the risk factors and early predictive thresholds (e.g., FEV1/FVC decline ≥ 10%) proposed in this study in prospective, multicenter cohorts; 2) exploring a comprehensive predictive tool that integrates clinical risk scores, dynamic rates of pulmonary function change, and novel biomarkers; 3) conducting innovative clinical trials for severe or progressive pediatric BOS; and 4) further investigating the immunopathological mechanisms of pediatric BOS to identify specific therapeutic targets. Through the early and accurate identification of high-risk children and the implementation of individualized interventions, it is hoped that the prognosis of this severe pulmonary complication can be improved. Declarations Funding This work was sponsored by Research Project of Shandong Qilu Stem Cell Engineering Co., Ltd. (Grant No. QLSC01202023008). Conflicts of interest/Competing interests No financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article. Ethics approval/declarations This study was approved by the Institutional Review Board (IRB) of the First Affiliated Hospital of Shandong First Medical University (Approval No. YXLL-KY-2025(009)). Author Contribution declaration CW and GD contributed equally to this work and share first authorship. HW (Hongmei Wang), HL, and YG conceived and designed the study. HW, HL, YG, HF, HY, ZY, LX, ZX, and LZ were responsible for the acquisition of clinical data. CW, GD, and HW performed the statistical analysis, interpreted the data, and generated the figures and tables. CW and GD drafted the initial manuscript. HW (Hongmei Wang) provided critical revision of the manuscript for important intellectual content. All authors participated in reviewing and revising the manuscript, approved the final version to be published, and agree to be accountable for all aspects of the work. As the corresponding author, HW (Hongmei Wang) is the guarantor of this work and takes full responsibility for the integrity of the work as a whole, from inception to the published article. Consent to participate All participants were informed and consented. Data Availability Statement The data that support the findings of this study are available from the corresponding author, Hongmei WANG, upon reasonable request. References Oikonomopoulou C, Paisiou A, Ioannidou ED, et al. Allogeneic hematopoietic stem cell transplantation in infants is associated with significant morbidity and mortality. Pediatr Transplant. 2022;26(4):e14239. doi:10.1111/petr.14239. Bezler NS, Ilowite M, London WB, Pei-Chi K, Joffe S, Mack JW. Health Literacy and Clinical Outcomes Following Hematopoietic Stem-Cell Transplantation. JCO Oncol Pract. 2022;18(6):e857-e868. doi:10.1200/OP.21.00049. Walther S, Rettinger E, Maurer HM, et al. Long-term pulmonary function testing in pediatric bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation. Pediatr Pulmonol. 2020;55(7):1725-1735. doi:10.1002/ppul.24801. Myrdal OH, Aaløkken TM, Diep PP, et al. Late-Onset, Noninfectious Pulmonary Complications following Allogeneic Hematopoietic Stem Cell Transplantation: A Nationwide Cohort Study of Long-Term Survivors. Respiration. 2022;101(6):544-552. doi:10.1159/000520824. Palmer J, Williams K, Inamoto Y, Chai X, Martin PJ, Tomas LS, Cutler C, Weisdorf D, Kurland BF, Carpenter PA, Pidala J, Pavletic SZ, Wood W, Jacobsohn D, Arai S, Arora M, Jagasia M,Vogelsang GB, Lee SJ. Pulmonary symptoms measured by the national institutes of health lung score predict overall survival, nonrelapse mortality, and patient-reported outcomes in chronic graft-versus-host disease. Biol Blood Marrow Transplant 2014;20:337-44.doi:10.1016/j.bbmt.2013.11.025. Carpenter PA , Kitko CL , Elad S , et al. National Institutes of Health Consensus Development Project on Criteria for Clinical Trials in Chronic Graft-versus-Host Disease: V. The 2014 Ancillary Therapy and Supportive Care Working Group Report. Biol Blood Marrow Transplant .2015;21:1167–1187. Duncan CN, Buonanno MR, Barry EV, Myers K, Peritz D, Lehmann L. Bronchiolitis obliterans following pediatric allogeneic hematopoietic stem cell transplantation. Bone Marrow Transplant. 2008;41(11):971-975. doi:10.1038/bmt.2008.19. Shanthikumar S, Gower WA, Cooke KR, et al. Diagnosis of Post-Hematopoietic Stem Cell Transplantation Bronchiolitis Obliterans Syndrome in Children: Time for a Rethink?. Transplant Cell Ther. 2024;30(8):760-769. doi:10.1016/j.jtct.2024.05.012. Filipovich AH, Weisdorf D, Pavletic S, et al. National Institutes of Health consensus development project on criteria for clinical trials in chronic graft-versus-host disease: I. Diagnosis and staging working group report. Biol Blood Marrow Transplant. 2005;11(12):945-956. doi:10.1016/j.bbmt.2005.09.004. Penack O, Marchetti M, Ruutu T, et al. Prophylaxis and management of graft versus host disease after stem-cell transplantation for haematological malignancies: updated consensus recommendations of the European Society for Blood and Marrow Transplantation. Lancet Haematol. 2020;7(2):e157-e167. Streiler C, Shaikh F, Davis C，et al. Ruxolitinib is an effective steroid sparing agent in bronchiolitis obliterans due to chronic graft-versus-host-disease. Bone Marrow Transplant. 2020;55(6):1194-1196. Bankier AA, MacMahon H, Colby T, et al. Fleischner Society: Glossary of Terms for Thoracic Imaging. Radiology. 2024;310(2):e232558. doi:10.1148/radiol.232558. Abedin S, Yanik GA, Braun T, et al. Predictive value of bronchiolitis obliterans syndrome stage 0p in chronic graft-versus-host disease of the lung. Biol Blood Marrow Transplant. 2015;21(6): 1127-1131. Gunn ML, Godwin JD, Kanne JP, Flowers ME, Chien JW. High-resolution CT findings of bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation. J Thorac Imaging. 2008;23(4):244-250. doi:10.1097/RTI.0b013e3181809df0. Bos S, Murray J, Marchetti M, et al. ERS/EBMT clinical practice guidelines on treatment of pulmonary chronic graft-versus-host disease in adults. Eur Respir J. 2024;63(3):2301727. Published 2024 Mar 28. doi:10.1183/13993003.01727-2023. Huang QS, Han TX, Chen Q, et al. Clinical risk factors and prognostic model for patients with bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation. Bone Marrow Transplant. 2024;59(2):239-246. doi:10.1038/s41409-023-02151-9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Jan, 2026 Reviews received at journal 18 Dec, 2025 Reviews received at journal 01 Dec, 2025 Reviewers agreed at journal 26 Nov, 2025 Reviewers agreed at journal 14 Nov, 2025 Reviewers invited by journal 05 Nov, 2025 Editor assigned by journal 05 Nov, 2025 Submission checks completed at journal 05 Nov, 2025 First submitted to journal 28 Oct, 2025 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. 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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-7974938","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":545661968,"identity":"445d1310-d475-4033-8714-7adda56a706a","order_by":0,"name":"Canran WANG","email":"","orcid":"","institution":"Shandong First Medical University \u0026 Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Canran","middleName":"","lastName":"WANG","suffix":""},{"id":545661969,"identity":"e25252df-a6a7-4e5d-a922-81c98d9cf1a5","order_by":1,"name":"Guoyu DING","email":"","orcid":"","institution":"The First Affiliated 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10:20:07","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":56820,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7974938/v1/73f23e2cc181a92b624208e7.png"},{"id":96073529,"identity":"973ef31b-97d0-4476-be6c-4556401b4b7a","added_by":"auto","created_at":"2025-11-17 10:20:07","extension":"xml","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":166026,"visible":true,"origin":"","legend":"","description":"","filename":"5a8ad7d596e04ade82024a7d581a93ff1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7974938/v1/1b43b45a658a957ca5f37fc2.xml"},{"id":96248403,"identity":"b01af9ca-5019-4317-b95e-46a13945e6e6","added_by":"auto","created_at":"2025-11-19 07:28:25","extension":"html","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":174319,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7974938/v1/43a0a225272c23980d85c268.html"},{"id":96073514,"identity":"23f58562-6b8f-4ddc-b9a3-a42d72290388","added_by":"auto","created_at":"2025-11-17 10:20:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":48645,"visible":true,"origin":"","legend":"\u003cp\u003eLongitudinal evolution of FEV1% predicted within 24 months post-diagnosis in BOS patients with different severity levels\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: The figure displays the median (solid line) and interquartile range (shaded area) of FEV1% predicted over time for the mild, moderate, and severe BOS groups.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7974938/v1/4902422520aa80359abf3237.png"},{"id":96073510,"identity":"efe5a026-ea20-49f7-88b7-0dc97796b35e","added_by":"auto","created_at":"2025-11-17 10:20:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79253,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier progression-free survival curves for BOS patients stratified by disease progression trajectory\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: The Rapid Decline (RD) group was defined as a relative FEV1 decline of ≥25% within 3 months post-diagnosis; the Gradual Decline (GD) group was defined as a relative FEV1 decline of \u0026lt;25% during the same period.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7974938/v1/3165f8ded18fe18070802cd1.png"},{"id":96073512,"identity":"e3b6d42b-b9eb-4864-a6dc-b0d28baf777f","added_by":"auto","created_at":"2025-11-17 10:20:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33000,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the longitudinal evolution of pulmonary function (FEV1% predicted) and HRCT structural damage (Bankier score) during treatment in BOS patients\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: The figure illustrates the trends of the mean FEV1% predicted (blue line) and the mean Bankier score (red line) over time, revealing a discordance between their evolutionary trajectories.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7974938/v1/96a22bc9ea1ced26ea74c4b6.png"},{"id":96256169,"identity":"028005ad-6040-45af-b2d3-88cb74a9b95b","added_by":"auto","created_at":"2025-11-19 07:49:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1615192,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7974938/v1/5514b5ea-298d-4adb-9949-1ae24f413c3b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictors and Prognostic Stratification of Bronchiolitis Obliterans Syndrome After Pediatric Allogeneic Hematopoietic Stem Cell Transplantation","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAllogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for a variety of malignant and non-malignant hematological diseases in children\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. With continuous advancements in transplantation techniques, the long-term survival rates for pediatric patients have significantly improved. Consequently, the management of late post-transplant complications, particularly pulmonary complications, has emerged as a central challenge affecting quality of life and overall prognosis. Among these, Bronchiolitis Obliterans Syndrome (BOS), one of the most severe non-infectious pulmonary complications, is a key manifestation of chronic graft-versus-host disease (cGVHD) in the lungs. Characterized by small airway inflammation and progressive fibrosis, BOS has a reported incidence of 4.5%\u0026ndash;8.3% in pediatric allo-HSCT recipients\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Clinically, BOS is characterized by an insidious onset, rapid progression, and high rates of morbidity and mortality, with a 5-year survival rate for affected children as low as 45.0\u0026ndash;59.0%\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. However, this grim prognosis is largely attributable to two core challenges in the current clinical management of BOS: diagnostic delay and static prognostic assessment.\u003c/p\u003e\u003cp\u003eFirst, significant diagnostic delays lead to missed therapeutic windows\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. The early symptoms of BOS, such as dry cough and mild dyspnea on exertion, are non-specific and easily overlooked. The current diagnostic gold standard, the National Institutes of Health (NIH) consensus criteria, relies primarily on fixed absolute thresholds of pulmonary function (e.g., FEV1\u0026thinsp;\u0026lt;\u0026thinsp;75% of predicted value)\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. This standard essentially confirms significant, established functional impairment, meaning that by the time of diagnosis, most patients have already entered an irreversible stage of airway fibrosis, thereby missing the optimal window for intervention\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Studies have shown that up to 18.8% of patients with biopsy-proven BOS still have an FEV1 above the 75% diagnostic threshold\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, exposing the critical insensitivity of the current criteria. To address this, a new expert consensus has proposed using a relative FEV1 decline from an individual's baseline (e.g., \u0026ge;\u0026thinsp;10%) as a warning signal for an \"At-Risk Stage\"\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. However, the predictive efficacy of this proactive concept and the extent to which it can advance the diagnostic window in real-world pediatric cohorts remain unclear.\u003c/p\u003e\u003cp\u003eSecond, the static nature of prognostic assessment hinders individualized treatment decision-making. The disease course of BOS patients exhibits significant heterogeneity: some patients may remain stable for long periods, while others deteriorate rapidly and respond poorly to standard therapies. Existing severity grading systems are primarily based on the FEV1 level at the time of diagnosis, representing a one-time, static evaluation that fails to capture the dynamic aggressiveness of the disease. This makes it difficult for clinicians to effectively identify high-risk individuals prone to rapid deterioration, often causing treatment escalation to lag behind disease progression, which is another major contributor to poor outcomes in severe cases. Furthermore, although guidelines recommend regular pulmonary function monitoring (e.g., every 3 months post-transplant) for high-risk groups\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, the definition of \"high-risk\" is not standardized, and there is a lack of effective dynamic tools to assess the disease trajectory and prognosis after a BOS diagnosis.\u003c/p\u003e\u003cp\u003eGiven these clinical challenges and research gaps, this study aims to provide a set of dynamic monitoring-based assessment tools for the management of pediatric BOS through a retrospective analysis. We first identified the independent risk factors for the development of BOS in our institutional cohort. Subsequently, to address the critical issue of diagnostic delay, we validated the clinical efficacy of relative FEV1 decline as a warning signal for the \"at-risk stage.\" To overcome the challenge of static prognostic assessment, we further investigated whether the rate of FEV1 decline early after diagnosis could serve as an independent prognostic predictor. Finally, we longitudinally tracked the evolving relationship between pulmonary function and HRCT imaging to better understand the \"functional-structural\" characteristics of disease progression. This study aims to provide evidence-based support for establishing a new management strategy for pediatric BOS, one that encompasses the entire chain of \"early warning, dynamic stratification, and precision intervention.\"\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design and Patient Cohort\u003c/h2\u003e\u003cp\u003eThis was a single-center, retrospective cohort study conducted at the Department of Pediatric Hematology, the First Affiliated Hospital of Shandong First Medical University. The study protocol was approved by the Institutional Review Board (IRB) of our hospital (Approval No. YXLL-KY-2025(009)). Given the retrospective nature of the data analysis, the IRB waived the requirement for informed consent.\u003c/p\u003e\u003cp\u003e We retrospectively reviewed all children aged\u0026thinsp;\u0026le;\u0026thinsp;18 years who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) at our center between January 2015 and December 2024. The inclusion criteria were: (1) a confirmed diagnosis of BOS post-transplant and receipt of systematic peri-transplant pulmonary function test (PFT) monitoring; and (2) complete clinical and follow-up data. Exclusion criteria were: (1) pre-existing severe pulmonary diseases that could interfere with the assessment (e.g., cystic fibrosis, severe asthma); (2) prior receipt of experimental cellular therapies for BOS; and (3) inability to perform reproducible PFTs to establish a reliable baseline due to age or cognitive reasons.\u003c/p\u003e\u003cp\u003eDuring the study period, a total of 467 children underwent allo-HSCT. According to the 2014 National Institutes of Health (NIH) consensus criteria\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, 32 patients were diagnosed with BOS. Among the cohort meeting the inclusion/exclusion criteria for this study, a final total of 201 children were included in the final analysis, comprising 29 patients with BOS (the BOS group) and 172 patients without BOS (the non-BOS group) as controls.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 BOS-related Definitions and Diagnostic Criteria\u003c/h2\u003e\u003cp\u003eThe final diagnosis and severity grading of BOS strictly adhered to the 2014 NIH cGVHD consensus criteria\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. A diagnosis required the simultaneous fulfillment of the following: (1) evidence of airflow limitation, defined as an FEV1/FVC ratio\u0026thinsp;\u0026lt;\u0026thinsp;0.7 or below the fifth percentile of the predicted value; (2) an irreversible decline in FEV1 to \u0026lt;\u0026thinsp;75% of the predicted value, with a relative decline from baseline of \u0026ge;\u0026thinsp;10% within two years; (3) absence of clinical, radiological, and microbiological evidence of active respiratory infection; and (4) presence of supportive imaging features, such as air trapping, bronchial wall thickening, or bronchiectasis on high-resolution computed tomography (HRCT).\u003c/p\u003e\u003cp\u003eOperational Revision for Infection Exclusion: Considering that infection and BOS can coexist or mutually trigger each other, this study implemented an operational revision to criterion (3) for clinical practice. This revision aimed to address the limitation of the NIH standard, which does not explicitly handle situations where infection and BOS coexist. If a patient's decline in pulmonary function occurred concurrently with symptoms of infection, standardized anti-infective therapy was administered first. A definitive diagnosis of BOS was established only if the decline in pulmonary function persisted or worsened after the completion of anti-infective treatment, and all other NIH criteria were met.\u003c/p\u003e\u003cp\u003eThe severity of BOS was graded based on the FEV1 percent predicted at the time of diagnosis\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e: mild (FEV1\u0026thinsp;\u0026ge;\u0026thinsp;60%), moderate (FEV1 40%-59%), and severe (FEV1\u0026thinsp;\u0026lt;\u0026thinsp;40%) (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition, this study evaluated BOS stage 0p, which was defined as a state where the FEV1 had declined by \u0026gt;\u0026thinsp;10% from baseline or the Forced Expiratory Flow at 25\u0026ndash;75% (FEF25-75) had declined by \u0026gt;\u0026thinsp;25%, but the diagnostic criteria for BOS had not yet been met.\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\u003eNational Institutes of Health (NIH) Severity Grading of Bronchiolitis Obliterans Syndrome\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeverity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade Score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFEV1, % predicted\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eClinical Symptoms\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;60%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAsymptomatic or dyspnea after climbing one flight of stairs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40%-59%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDyspnea after walking on a flat road\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDyspnea at rest; oxygen required\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eDefinition of \"At-Risk Stage\" (Early Warning Signal): In this study, the \"At-Risk Stage\" was defined as the first occurrence of a relative FEV1 decline of \u0026ge;\u0026thinsp;10% from an individual's stable baseline value during routine PFT monitoring. This concept, similar to \"BOS stage 0p\" mentioned in the literature, is intended to capture early pulmonary function abnormalities before formal diagnostic criteria are met. Once a patient reached this warning threshold, a comprehensive differential diagnosis process, including HRCT and infection screening, was immediately initiated.\u003c/p\u003e\u003cp\u003eDefinition of Prognostic Trajectory Stratification: To quantify the dynamic aggressiveness of the disease, patients were stratified into two groups based on the rate of FEV1 decline within the first 3 months of the BOS diagnosis: Rapid Decline (RD) group: Defined as a relative FEV1 decline of \u0026ge;\u0026thinsp;25% within the first 3 months post-diagnosis. Gradual Decline (GD) group: Defined as a relative FEV1 decline of \u0026lt;\u0026thinsp;25% during the same period.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Treatment Protocol\u003c/h2\u003e\u003cp\u003eAll children diagnosed with BOS received standardized therapy centered on immunosuppression. The first-line treatment regimen included corticosteroids (e.g., methylprednisolone) combined with a calcineurin inhibitor (CNI), such as tacrolimus or cyclosporine\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. For cases of steroid-refractory disease or disease progression, treatment was escalated to second-line therapies, including mycophenolate mofetil (MMF) or ruxolitinib\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. All drug dosages were individually adjusted based on clinical response, patient tolerance, and therapeutic drug monitoring, in accordance with institutional treatment protocols.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Data Collection and Assessment\u003c/h2\u003e\u003cp\u003eStandardized data extraction forms were used by researchers to retrospectively collect data from the electronic medical record system. Baseline data included demographic characteristics, primary diseases, and allo-HSCT-related parameters (e.g., conditioning regimen, graft source, grade of acute/chronic GVHD). Longitudinal follow-up data encompassed clinical symptoms, serial PFT results, HRCT imaging assessments, treatment regimens, and survival outcomes.\u003c/p\u003e\u003cp\u003ePulmonary Function Tests (PFTs): All PFTs were performed and quality-controlled according to the American Thoracic Society/European Respiratory Society (ATS/ERS) guidelines\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Key parameters, including Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV1), the FEV1/FVC ratio, and Diffusing Capacity for Carbon Monoxide (DLCO), were recorded as both absolute values and percentages of predicted values. The PFT baseline was defined as the stable pulmonary function level prior to transplantation; if pre-transplant data were missing, the best stable value at 100 days post-transplant (D\u0026thinsp;+\u0026thinsp;100) was used as the baseline. All children included in the study followed a standardized monitoring protocol: every 3 months for the first year post-transplant, and every 3\u0026ndash;6 months thereafter.\u003c/p\u003e\u003cp\u003eImaging Assessment: Chest HRCT scans were evaluated by two independent, senior radiologists who were blinded to the clinical information. HRCT was primarily used to aid in diagnosis (e.g., identifying signs such as air trapping) and to exclude other pulmonary diseases. To quantify structural lung damage, the Bankier semi-quantitative scoring system was employed\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. This system assesses three core indicators: bronchiectasis, mosaic perfusion (air trapping), and bronchial wall thickening. Each indicator was scored based on the number of affected lung lobes (1 lobe\u0026thinsp;=\u0026thinsp;1 point; 2\u0026ndash;3 lobes\u0026thinsp;=\u0026thinsp;2 points; 4\u0026ndash;5 lobes\u0026thinsp;=\u0026thinsp;3 points), with a total score ranging from 0 to 9, where a higher score indicates more severe structural damage.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Study Endpoints and Statistical Analysis\u003c/h2\u003e\u003cp\u003eThe primary endpoint of this study was the incidence of Bronchiolitis Obliterans Syndrome (BOS) following pediatric allogeneic hematopoietic stem cell transplantation (allo-HSCT). Secondary endpoints included the diagnostic performance of the early warning signal, progression-free survival (PFS) and overall survival (OS), the longitudinal evolution of pulmonary function (FEV1%), and the progression of structural damage on imaging (HRCT).\u003c/p\u003e\u003cp\u003eAll data were statistically analyzed using SPSS software (version 26.0), with a two-sided P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant. The normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and compared between groups using the independent samples t-test. Non-normally distributed data were presented as median (interquartile range, IQR) and compared using the Mann-Whitney U test. Categorical variables were expressed as frequency (percentage) and compared using the Chi-square test or Fisher's exact test. A multivariate Logistic regression model was used to analyze independent risk factors for the development of BOS. Survival curves were generated using the Kaplan-Meier method and compared between groups using the Log-rank test. To evaluate the independent prognostic value of the disease progression trajectory, a multivariate Cox proportional hazards regression model was constructed to assess its impact on progression-free survival (PFS) after adjusting for known confounding factors, such as FEV1 level at diagnosis and cGVHD severity.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Independent Risk Factors for BOS Following Pediatric allo-HSCT\u003c/h2\u003e\n \u003cp\u003eDuring the study period, a total of 467 children who underwent allo-HSCT at our center were systematically followed up, among whom 32 were diagnosed with BOS, yielding a cumulative incidence of 6.9%. The median time to BOS diagnosis was 267 days post-transplant (IQR: 176\u0026ndash;361 days). After screening, a final cohort of 201 children was included in the cross-sectional analysis for this study, comprising 29 patients with BOS (the BOS group) and 172 controls (the non-BOS group).\u003c/p\u003e\n \u003cp\u003eIn the univariate analysis, significant differences were observed in several baseline characteristics between the BOS and non-BOS groups (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Compared to the non-BOS group, a significantly higher proportion of patients in the BOS group had a malignant primary disease (51.7% vs. 29.7%, P\u0026thinsp;=\u0026thinsp;0.031), received a myeloablative conditioning regimen (72.4% vs. 37.8%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), used a combination of peripheral blood and bone marrow as the graft source (75.9% vs. 50.0%, P\u0026thinsp;=\u0026thinsp;0.012), developed grade III-IV aGVHD (51.7% vs. 7.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and developed cGVHD (79.3% vs. 20.9%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There were no statistically significant differences between the two groups in terms of age, sex, or baseline pulmonary function (FVC, FEV1, FEV1/FVC, and DLCO).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of Demographic and Clinical Baseline Characteristics Between the BOS and Non-BOS Groups\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBOS Group (n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-BOS Group (n\u0026thinsp;=\u0026thinsp;172)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge at transplant, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.51 (8.73\u0026ndash;10.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.45 (9.18\u0026ndash;9.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17 (58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90 (52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (41.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82 (47.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary disease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-malignant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e121 (70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMalignant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConditioning regimen, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMyeloablative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21 (72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65 (37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-myeloablative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e107 (62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eABO compatibility, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIdentical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96 (55.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-identical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76 (44.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHLA match, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMatched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMismatched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27 (93.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135 (78.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGraft source, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePeripheral blood stem cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePBSC\u0026thinsp;+\u0026thinsp;Bone marrow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (75.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCord blood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29 (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-transplant CT, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbnormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23 (79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e150 (87.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eaGVHD, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80 (46.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade I-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80 (46.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade III-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecGVHD, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23 (79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e136 (79.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary Function at Baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFVC, % predicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1, % predicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e101.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1/FVC ratio, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102.34 (100.56, 104.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104.92 (104.11, 105.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDLCO, % predicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79.87 (76.94, 82.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e74.69 (73.62, 75.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003cem\u003eNote: Continuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for normally distributed data or median (interquartile range, IQR) for non-normally distributed data. Categorical variables are presented as frequency (percentage). aGVHD, acute graft-versus-host disease; cGVHD, chronic graft-versus-host disease; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; DLCO, diffusing capacity for carbon monoxide.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eIn the 201 children included in the cross-sectional analysis (29 in the BOS group, 172 in the non-BOS group), a multivariate Cox proportional hazards regression analysis ultimately identified four independent predictors for the development of BOS following pediatric allo-HSCT(Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e): a history of grade III-IV aGVHD (HR\u0026thinsp;=\u0026thinsp;15.12, 95% CI:1.25-182.66, P\u0026thinsp;=\u0026thinsp;0.033), the development of cGVHD (HR\u0026thinsp;=\u0026thinsp;6.94, 95%CI: 1.77\u0026ndash;27.15, P\u0026thinsp;=\u0026thinsp;0.005), the presence of dry cough within 6 months post-transplant (HR\u0026thinsp;=\u0026thinsp;11.77, 95%CI:2.92\u0026ndash;47.48, P\u0026thinsp;=\u0026thinsp;0.001), and a decline in FEV1/FVC of \u0026ge;\u0026thinsp;10% within 6 months post-transplant (HR\u0026thinsp;=\u0026thinsp;8.70, 95% CI:1.22\u0026ndash;62.22, P\u0026thinsp;=\u0026thinsp;0.031).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate Cox Regression Analysis for Predicting BOS After Pediatric allo-HSCT\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCandidate predictors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMultivariable analysis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary disease (Malignant vs. Non-malignant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67 (0.09\u0026ndash;4.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConditioning regimen (Myeloablative vs. Non-myeloablative)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.10 (0.28\u0026ndash;15.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.472\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGraft source\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePBSC (Ref.)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePBSC\u0026thinsp;+\u0026thinsp;Bone marrow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.02 (0.50-18.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCord blood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.45 (0.12\u0026ndash;17.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eaGVHD grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNone (Ref.)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade I-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.89 (0.46\u0026ndash;51.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade III-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.12 (1.25-182.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresence of cGVHD (Yes vs. No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.94 (1.77\u0026ndash;27.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1 decline group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIncrease/No decline (Ref.)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.914\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecline\u0026thinsp;\u0026lt;\u0026thinsp;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.46 (0.16\u0026ndash;13.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.737\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecline\u0026thinsp;\u0026ge;\u0026thinsp;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10 (0.12\u0026ndash;10.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.936\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1/FVC decline group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIncrease/No decline (Ref.)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecline\u0026thinsp;\u0026lt;\u0026thinsp;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.15 (0.37\u0026ndash;12.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecline\u0026thinsp;\u0026ge;\u0026thinsp;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.70 (1.22\u0026ndash;62.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDLCO decline group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIncrease/No decline (Ref.)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecline\u0026thinsp;\u0026lt;\u0026thinsp;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52 (0.08\u0026ndash;3.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecline\u0026thinsp;\u0026ge;\u0026thinsp;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73 (0.13\u0026ndash;3.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresence of dry cough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.77 (2.92\u0026ndash;47.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresence of hypoxemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27 (0.04\u0026ndash;1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresence of retractions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.68 (0.07-38.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresence of pulmonary wheezing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.42 (0.02\u0026ndash;7.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecurrent respiratory infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.82 (0.40-58.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Identification and Diagnostic Performance Evaluation of Early Warning Signals for BOS\u003c/h2\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.1 Predictive Value of Clinical Symptoms\u003c/h2\u003e\n \u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, the incidence of dry cough, hypoxemia, retractions, pulmonary wheezing, and recurrent respiratory infections within 6 months post-transplant was significantly higher in the BOS group than in the non-BOS group (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). To further evaluate the value of each clinical symptom for the early identification of BOS, we calculated their diagnostic performance metrics, as presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. Dry cough was the most sensitive clinical symptom for BOS (sensitivity, 79.31%), indicating that the vast majority of patients with BOS exhibited this symptom. However, its specificity (21.51%) and positive predictive value (PPV, 38.33%) were low, meaning that dry cough is also very common among non-BOS patients, and relying solely on this symptom for a BOS diagnosis would lead to a high number of false positives. The negative predictive value (NPV) of dry cough was high at 95.74%, suggesting that children without this symptom are highly unlikely to have BOS, which makes it an effective tool for exclusion. The specificities for other signs and histories, such as hypoxemia, retractions, pulmonary wheezing, and recurrent grade II-III infections, were extremely low (ranging from 2.33% to 10.47%), and their sensitivities were also poor (ranging from 20.00% to 31.03%), demonstrating their limited value in early differential diagnosis.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of the Incidence of Early Post-Transplant Clinical Symptoms Between the BOS and Non-BOS Groups\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBOS Group (n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-BOS Group (n\u0026thinsp;=\u0026thinsp;172)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDry cough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23 (79.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37 (21.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135 (78.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypoxemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (31.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18 (10.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20 (68.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154 (89.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRetractions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4 (2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23 (79.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e168 (97.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary wheezing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (4.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23 (79.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e165 (95.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecurrent respiratory infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 0-I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (75.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e168 (97.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade II-III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (24.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4 (2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDiagnostic Performance of Different Clinical Symptoms for BOS\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClinical Symptom\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive Predictive Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative Predictive Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDry cough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79.31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.51%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e95.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypoxemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.03%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.51%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRetractions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.69%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87.96%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.2 Predictive Value of Pulmonary Function Decline\u003c/h2\u003e\n \u003cp\u003eCompared to patients in the non-BOS group, children in the BOS group exhibited a significant and continuous decline in pulmonary function within the first 6 months post-transplant. The median FVC% predicted decreased from a pre-transplant value of 96.61% to 79.05% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the FEV1% predicted decreased from 99.15% to 69.44% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the FEV1/FVC% predicted decreased from 102.34% to 87.01% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the DLCO% predicted decreased from 79.87% to 66.33% (P\u0026thinsp;=\u0026thinsp;0.003). As shown in Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, the proportion of patients with a\u0026thinsp;\u0026ge;\u0026thinsp;10% decline from baseline in FEV1, FEV1/FVC, and DLCO predicted values within 6 months post-transplant was significantly higher in the BOS group than in the non-BOS group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003cp\u003eTo translate this dynamic change into an actionable early warning tool, this study focused on evaluating the efficacy of the BOS stage 0p (defined as FEV1 decline\u0026thinsp;\u0026gt;\u0026thinsp;10% or FEF25-75 decline\u0026thinsp;\u0026gt;\u0026thinsp;25%) as an early warning indicator. Among the 29 patients in the BOS group, 15 (51.7%) had been identified as being in BOS stage 0p before meeting the NIH diagnostic criteria. These patients reached the BOS stage 0p warning threshold a median of 176 (range: 35\u0026ndash;537) days before their formal BOS diagnosis, providing a potential window for early intervention.\u003c/p\u003e\n \u003cp\u003eHowever, the diagnostic performance analysis (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e) revealed that while BOS stage 0p had a high NPV (84.95%), its sensitivity for identifying BOS was moderate (51.72%), and its specificity (54.07%) and PPV (13.89%) were low. This indicates that although BOS stage 0p can effectively rule out low-risk patients, its high false-positive rate limits its value as a standalone screening tool. It is more suitable as a \u0026quot;high-risk signal\u0026quot; that triggers a comprehensive evaluation.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of Subgroups Based on Changes in Pulmonary Function Parameters from Baseline within 6 Months Post-Transplant\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChange from Baseline\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBOS Group (n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-BOS Group (n\u0026thinsp;=\u0026thinsp;172)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFVC change subgroups (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.326\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (17.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 (23.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (24.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58 (33.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17 (58.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e74 (43.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1 change subgroups (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (6.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44 (25.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49 (28.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21 (72.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79 (45.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1/FVC change subgroups (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90 (52.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (31.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63 (36.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14 (48.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (11.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDLCO change subgroups (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (24.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67 (38.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (20.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51 (29.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16 (55.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54 (31.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003cem\u003eNote: 0\u0026thinsp;=\u0026thinsp;Increase or no decline; 1\u0026thinsp;=\u0026thinsp;Decline\u0026thinsp;\u0026lt;\u0026thinsp;10%; 2\u0026thinsp;=\u0026thinsp;Decline\u0026thinsp;\u0026ge;\u0026thinsp;10%.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePredictive Performance of BOS Stage 0p and Related Pulmonary Function Indicators for BOS\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCriterion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePPV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNPV\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1 0p (FEV1 decline\u0026thinsp;\u0026gt;\u0026thinsp;10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.28%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.69%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEF25-75 0p (FEF25-75 decline\u0026thinsp;\u0026gt;\u0026thinsp;25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86.71%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1 or FEF25-75 0p (BOS 0p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.72%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.07%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.95%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.3 Early Indicative Role of HRCT Imaging Abnormalities\u003c/h2\u003e\n \u003cp\u003eAmong the 31 BOS patients with complete imaging data, the primary findings on chest high-resolution computed tomography (HRCT) were airway abnormalities. The most common signs included mosaic perfusion (25/31, 80.6%), bronchial wall thickening (24/31, 77.4%), and bronchiectasis (16/31, 51.6%). Some patients developed reversible complications such as mucous plugging, subcutaneous/mediastinal emphysema, and bullae, which resolved after treatment.\u003c/p\u003e\n \u003cp\u003eHRCT also demonstrated potential for early warning: in 11 of the 31 patients (35.5%), typical HRCT abnormalities preceded the pulmonary function findings indicative of BOS. An analysis of these 11 patients revealed that at the time of their first abnormal imaging finding, 7 had concurrent PFT data. Among these, 5 showed a decline in pulmonary function that had not yet reached the diagnostic threshold, while 2 had no significant pulmonary function abnormalities. This suggests that HRCT can provide earlier evidence of structural lesions in some children, but its diagnostic application needs to be combined with frequent pulmonary function monitoring to achieve precise early identification of BOS.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Disease Evolution and Prognostic Stratification After BOS Diagnosis\u003c/h2\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003cp\u003e3.3.1 Pulmonary Function Trajectories Based on NIH Grading Reveal Heterogeneity in Disease Progression\u003c/p\u003e\n \u003cp\u003eAmong the 31 BOS patients included in the longitudinal analysis, patients were stratified according to the NIH criteria into mild (n\u0026thinsp;=\u0026thinsp;11), moderate (n\u0026thinsp;=\u0026thinsp;13), and severe (n\u0026thinsp;=\u0026thinsp;7) groups. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, the post-treatment pulmonary function trajectories of each group exhibited significant heterogeneity. The FEV1% predicted values in the mild and moderate groups largely stabilized after treatment, with some patients in the mild group even recovering to \u0026gt;\u0026thinsp;80% of the predicted value. In contrast, the median FEV1% predicted in the severe group continuously declined within the first 6 months post-diagnosis, and the inter-individual variability progressively widened (with the difference between the 75th and 25th percentiles expanding to 32%), suggesting a more aggressive disease progression and a poor response to treatment in this subgroup.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.2 Rate of FEV1 Decline is a Strong Independent Predictor of Survival\u003c/h2\u003e\n \u003cp\u003eBased on the rate of FEV1 decline within the first 3 months post-diagnosis, the 31 patients were stratified into a Rapid Decline group (RD, n\u0026thinsp;=\u0026thinsp;4, 12.9%) and a Gradual Decline group (GD, n\u0026thinsp;=\u0026thinsp;27, 87.1%). Kaplan-Meier survival analysis (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) revealed a significant difference in progression-free survival (PFS) between the two groups. The median PFS for the RD group was only 9.0 months, whereas the median PFS for the GD group has not yet been reached (Log-rank test, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003cp\u003eTo validate the independent prognostic value of the disease progression trajectory, we constructed a multivariate Cox regression model. As shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, after adjusting for key confounding factors, namely the FEV1 level at diagnosis and the severity of aGVHD, a rapid progression trajectory (RD vs. GD) remained the strongest independent predictor of early-onset poor progression-free survival (adjusted HR\u0026thinsp;=\u0026thinsp;30.68, 95% CI: 3.39-277.79, P\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate Cox Regression Analysis of Factors Affecting Progression-Free Survival (PFS) in BOS Patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRisk Factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted HR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRapid Progression Trajectory (RD vs. GD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.68 (3.39-277.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1% predicted at BOS diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97 (0.92\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHistory of Grade III-IV aGVHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.55 (0.27\u0026ndash;24.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 \u0026quot;Radio-functional Discordance\u0026quot; in Disease Progression\u003c/h2\u003e\n \u003cp\u003eLongitudinal follow-up revealed a critical phenomenon of \u0026quot;radio-functional discordance\u0026quot; in the progression of BOS. As illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, although the FEV1 in many patients tended to stabilize after treatment, the mean Bankier semi-quantitative score, which reflects structural damage, showed a progressive increase. The score rose continuously and significantly from a mean of 2 points before treatment to 6 points after 2 years (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This indicates that even in patients whose ventilatory function appears stable, the underlying, irreversible small airway fibrosis and structural remodeling continue to advance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Auxiliary Diagnostic Value of Flexible Bronchoscopy\u003c/h2\u003e\n \u003cp\u003eAmong the 18 BOS patients who underwent flexible bronchoscopy, only 6 exhibited findings of bronchial branch occlusion. Of these, 3 primarily showed proximal bronchial dilation with partial sub-branch occlusion observed distally. One patient presented with an additional bronchial opening. The positive rate of this examination was not high in our cohort. Its main clinical value lay in excluding active infections or other pulmonary complications rather than in directly diagnosing BOS.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe management of Bronchiolitis Obliterans Syndrome (BOS) following pediatric allogeneic hematopoietic stem cell transplantation (allo-HSCT) is hampered by two major challenges: first, the lack of sensitive warning signals before the disease reaches an irreversible stage, and second, the inability to accurately identify high-risk individuals with a poor prognosis early after diagnosis. Through a systematic analysis of a pediatric cohort, this study proposes solutions based on dynamic monitoring to address these two challenges. We demonstrate for the first time in children that the early rate of FEV1 decline post-diagnosis is the strongest prognostic predictor, independent of baseline severity. Concurrently, we validated that a relative decline in pulmonary function from an individual's baseline can serve as an effective early \"at-risk\" warning signal. Furthermore, the \"radio-functional discordance\" phenomenon revealed in this study provides a new perspective for understanding the pathological progression of BOS and evaluating treatment response. Collectively, these findings establish a new, comprehensive management framework for pediatric BOS, extending from early identification to dynamic risk stratification.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.1 BOS Epidemiology and High-Risk Factors\u003c/h2\u003e\u003cp\u003eThe cumulative incidence of BOS at our center was 6.9%, which is consistent with the reported incidence of 4.5%-8.3% in international pediatric cohorts\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. The results of our multivariate analysis confirm that a strong immune response is the primary driver of BOS pathogenesis: grade III-IV aGVHD dramatically increased the risk of BOS by 15.12-fold, while cGVHD increased the risk by 6.94-fold. Meanwhile, the presence of a dry cough within 6 months post-transplant increased the risk of BOS by 11.77-fold. Although this clinical symptom has a low positive predictive value, its high sensitivity and extremely high negative predictive value (95.74%) make it an ideal first-line, non-invasive exclusion tool that can be detected at any time without special equipment, helping to avoid unnecessary investigations in low-risk children.\u003c/p\u003e\u003cp\u003eDynamic monitoring of pulmonary function demonstrated core predictive value in our study. We found that a relative decline of \u0026ge;\u0026thinsp;10% in the FEV1/FVC ratio from baseline within 6 months post-transplant was a strong independent predictor of BOS development (HR\u0026thinsp;=\u0026thinsp;8.70). This finding has significant clinical implications: compared to the fixed absolute thresholds recommended in current guidelines (e.g., FEV1/FVC\u0026thinsp;\u0026lt;\u0026thinsp;0.7), a relative decline based on an individual's own baseline is clearly more sensitive. Particularly in children with good pulmonary function reserve, absolute value abnormalities often appear much later, whereas capturing early relative changes can significantly advance the warning window, creating an opportunity for early intervention.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Value and Limitations of the Early Warning Strategy\u003c/h2\u003e\u003cp\u003eOur in-depth investigation into the clinical significance of obstructive physiological abnormalities that do not yet meet the diagnostic criteria for BOS (BOS stage 0p) \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003efound that this state has a high negative predictive value (84.95%), confirming its effectiveness in ruling out the disease. However, its positive predictive value (PPV\u0026thinsp;=\u0026thinsp;13.89%) and specificity (54.07%) were low, and only 51.7% of BOS patients were identified in the BOS 0p stage before their formal diagnosis.\u003c/p\u003e\u003cp\u003eThis result reflects the inadequacy of a single pulmonary function indicator as a standalone screening tool. The high false-positive rate could lead to anxiety among patients' families and potential over-intervention. Therefore, this study supports viewing the BOS 0p state as a \"high-risk signal\" that should trigger a comprehensive evaluation, including the immediate initiation of a full differential diagnosis (including HRCT and infection screening) and integrated assessment with other high-risk clinical factors. Future research should focus on developing a multifactorial predictive model that integrates clinical risk factors (e.g., severe aGVHD), symptoms (e.g., dry cough), pulmonary function trajectories, and novel biomarkers to improve the positive predictive value of early warnings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e4.3 The \"Radio-functional Discordance\" Phenomenon and its Pathological Significance\u003c/h2\u003e\u003cp\u003eImaging plays a unique role in the early identification of BOS, but its evolution is not always synchronous with changes in pulmonary function\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. This study found that in 11 patients (35.5%), typical HRCT abnormalities preceded pulmonary function indicators of BOS, suggesting that HRCT has an advantage in providing early warning of structural lesions. However, we observed a significant \"radio-functional discordance\": despite patients receiving systematic treatment, and with FEV1 stabilizing or even improving in the mild-to-moderate groups, the Bankier semi-quantitative score continued to show a progressive upward trend. This suggests that the irreversible structural damage of the small airways (fibrosis, bronchiectasis) was still worsening. The mechanisms for this discordance may include: (1) immunosuppressive therapy primarily targets the reversible inflammatory components of the airways but can hardly reverse established fibrotic obliteration; and (2) HRCT is highly sensitive to subtle structural deterioration, whereas the stability of global lung function (FEV1) may mask disease progression in certain regions.\u003c/p\u003e\u003cp\u003eThis finding strongly suggests that the evaluation of treatment response and disease progression in BOS should never rely solely on pulmonary function indicators. Clinicians must recognize that stable lung function may conceal underlying, ongoing structural damage. Therefore, a dual-dimensional monitoring strategy that combines HRCT imaging assessment (to measure structure) with pulmonary function monitoring (to measure function) is crucial for a comprehensive understanding of the disease state and for judging the true effectiveness of treatment.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e4.4 The Critical Value of Disease Progression Trajectory and Prognostic Stratification\u003c/h2\u003e\u003cp\u003eThe disease course and treatment response in BOS exhibit significant individual heterogeneity. This study is the first to introduce the concept of a disease progression trajectory in a pediatric cohort, stratifying patients into a Rapid Decline (RD) group and a Gradual Decline (GD) group. Multivariate Cox regression analysis confirmed that a rapid decline trajectory (relative FEV1 decline\u0026thinsp;\u0026ge;\u0026thinsp;25% within 3 months of diagnosis) is a strong prognostic predictor, independent of the severity at diagnosis (NIH grading) and systemic cGVHD status.\u003c/p\u003e\u003cp\u003eLongitudinal data showed that while pulmonary function in most mild-to-moderate patients stabilized with individualized treatment, patients in the RD group and those with severe BOS continued to deteriorate rapidly in the early phase (within 6 months). This heterogeneity is consistent with findings from other studies\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, suggesting that current treatment protocols (often based on intensified GVHD therapy and pulmonary symptom management) are not effective for severe BOS patients with a rapid progression trajectory. Therefore, it is crucial to move beyond the static NIH grading at diagnosis and adopt a prognostic stratification based on the rate of early dynamic changes. This approach can precisely identify the subgroup with the poorest response to standard therapy and the worst prognosis (the RD group), providing clinicians with a critical evidence base for promptly escalating treatment (e.g., targeted anti-fibrotic drugs, novel immunosuppressants, mesenchymal stem cell (MSC) therapy, or early pulmonary rehabilitation). The clinical practice recommendations proposed in this study (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e8\u003c/span\u003e) are based on this evidence, aiming to shift the management of pediatric BOS from a \"one-size-fits-all\" model to individualized, risk-stratified therapy.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKey Recommendations for Clinical Practice\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRecommendation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClinical Significance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScreening Frequency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMaintain PFT monitoring every 3 months during the first year post-transplant.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnsures timely capture of early declines in pulmonary function.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEarly Warning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA relative FEV1 decline of \u0026ge;\u0026thinsp;10% should immediately trigger a comprehensive BOS evaluation (including HRCT and infection screening).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdvances the diagnostic window, creating an opportunity for early intervention.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrognostic Stratification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAfter BOS diagnosis, stratify patients into a high-risk rapid progression group based on a threshold of \u0026ge;\u0026thinsp;25% relative FEV1 decline within 3 months.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrecisely identifies the subgroup with highly aggressive disease.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment Intensification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePatients in the Rapid Decline (RD) group should be considered to have high-risk/refractory BOS, and escalation of immunosuppressive therapy or enrollment in clinical trials must be actively considered.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAchieves individualized, risk-stratified therapy to improve outcomes for high-risk patients.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e4.5 Conclusion and Future Perspectives\u003c/h2\u003e\u003cp\u003eIn summary, the core contribution of this study is to provide critical, dynamic change-based evidence for decision-making in the management of pediatric post-HSCT BOS, thereby addressing the shortcomings of traditional static assessment metrics. Specifically, we have established two assessment tools that can be directly applied in clinical practice: first, by monitoring the relative decline in early post-transplant pulmonary function (especially FEV1/FVC), we propose a more sensitive early warning strategy to identify \"at-risk\" children; second, we confirmed that the early rate of FEV1 decline post-diagnosis is a strong prognostic predictor independent of disease severity at diagnosis, providing a new method for achieving precise prognostic stratification and risk-guided treatment escalation. Furthermore, the \"radio-functional discordance\" phenomenon revealed in this study offers an important supplement to existing efficacy evaluation systems, emphasizing the necessity of parallel monitoring of structural damage and functional impairment.\u003c/p\u003e\u003cp\u003eThis study also has some limitations. First, as a single-center, retrospective study, it may be subject to selection bias, and the sample size, particularly in the longitudinal subgroup analyses, was limited. The generalizability of its findings requires validation in prospective, multicenter cohorts. Second, we were unable to routinely use more sensitive methods for detecting early small airway disease, such as the multiple breath washout (MBW) technique.\u003c/p\u003e\u003cp\u003eLooking ahead, future research should include: 1) validating the risk factors and early predictive thresholds (e.g., FEV1/FVC decline\u0026thinsp;\u0026ge;\u0026thinsp;10%) proposed in this study in prospective, multicenter cohorts; 2) exploring a comprehensive predictive tool that integrates clinical risk scores, dynamic rates of pulmonary function change, and novel biomarkers; 3) conducting innovative clinical trials for severe or progressive pediatric BOS; and 4) further investigating the immunopathological mechanisms of pediatric BOS to identify specific therapeutic targets. Through the early and accurate identification of high-risk children and the implementation of individualized interventions, it is hoped that the prognosis of this severe pulmonary complication can be improved.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was sponsored by Research Project of Shandong Qilu Stem Cell Engineering Co., Ltd. (Grant No. QLSC01202023008).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval/declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board (IRB) of the First Affiliated Hospital of Shandong First Medical University (Approval No. YXLL-KY-2025(009)).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCW and GD contributed equally to this work and share first authorship.\u003c/p\u003e\n\u003cp\u003eHW (Hongmei Wang), HL, and YG conceived and designed the study. HW, HL, YG, HF, HY, ZY, LX, ZX, and LZ were responsible for the acquisition of clinical data. CW, GD, and HW performed the statistical analysis, interpreted the data, and generated the figures and tables. CW and GD drafted the initial manuscript. HW (Hongmei Wang) provided critical revision of the manuscript for important intellectual content. All authors participated in reviewing and revising the manuscript, approved the final version to be published, and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003eAs the corresponding author, HW (Hongmei Wang) is the guarantor of this work and takes full responsibility for the integrity of the work as a whole, from inception to the published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; All participants were informed and consented.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, Hongmei WANG, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eOikonomopoulou C, Paisiou A, Ioannidou ED, et al. Allogeneic hematopoietic stem cell transplantation in infants is associated with significant morbidity and mortality. Pediatr Transplant. 2022;26(4):e14239. doi:10.1111/petr.14239.\u003c/li\u003e\n \u003cli\u003eBezler NS, Ilowite M, London WB, Pei-Chi K, Joffe S, Mack JW. Health Literacy and Clinical Outcomes Following Hematopoietic Stem-Cell Transplantation. JCO Oncol Pract. 2022;18(6):e857-e868. doi:10.1200/OP.21.00049.\u003c/li\u003e\n \u003cli\u003eWalther S, Rettinger E, Maurer HM, et al. Long-term pulmonary function testing in pediatric bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation. Pediatr Pulmonol. 2020;55(7):1725-1735. doi:10.1002/ppul.24801.\u003c/li\u003e\n \u003cli\u003eMyrdal OH, Aal\u0026oslash;kken TM, Diep PP, et al. Late-Onset, Noninfectious Pulmonary Complications following Allogeneic Hematopoietic Stem Cell Transplantation: A Nationwide Cohort Study of Long-Term Survivors. Respiration. 2022;101(6):544-552. doi:10.1159/000520824.\u003c/li\u003e\n \u003cli\u003ePalmer J, Williams K, Inamoto Y, Chai X, Martin PJ, Tomas LS, Cutler C, Weisdorf D, Kurland BF, Carpenter PA, Pidala J, Pavletic SZ, Wood W, Jacobsohn D, Arai S, Arora M, Jagasia M,Vogelsang GB, Lee SJ. Pulmonary symptoms measured by the national institutes of health lung score predict overall survival, nonrelapse mortality, and patient-reported outcomes in chronic graft-versus-host disease. Biol Blood Marrow Transplant 2014;20:337-44.doi:10.1016/j.bbmt.2013.11.025.\u003c/li\u003e\n \u003cli\u003eCarpenter PA , Kitko CL , Elad S , et al. National Institutes of Health Consensus Development Project on Criteria for Clinical Trials in Chronic Graft-versus-Host Disease: V. The 2014 Ancillary Therapy and Supportive Care Working Group Report. Biol Blood Marrow Transplant .2015;21:1167\u0026ndash;1187.\u003c/li\u003e\n \u003cli\u003eDuncan CN, Buonanno MR, Barry EV, Myers K, Peritz D, Lehmann L. Bronchiolitis obliterans following pediatric allogeneic hematopoietic stem cell transplantation. Bone Marrow Transplant. 2008;41(11):971-975. doi:10.1038/bmt.2008.19.\u003c/li\u003e\n \u003cli\u003eShanthikumar S, Gower WA, Cooke KR, et al. Diagnosis of Post-Hematopoietic Stem Cell Transplantation Bronchiolitis Obliterans Syndrome in Children: Time for a Rethink?. Transplant Cell Ther. 2024;30(8):760-769. doi:10.1016/j.jtct.2024.05.012.\u003c/li\u003e\n \u003cli\u003eFilipovich AH, Weisdorf D, Pavletic S, et al. National Institutes of Health consensus development project on criteria for clinical trials in chronic graft-versus-host disease: I. Diagnosis and staging working group report. Biol Blood Marrow Transplant. 2005;11(12):945-956. doi:10.1016/j.bbmt.2005.09.004.\u003c/li\u003e\n \u003cli\u003ePenack O, Marchetti M, Ruutu T, et al. Prophylaxis and management of graft versus host disease after stem-cell transplantation for haematological malignancies: updated consensus recommendations of the European Society for Blood and Marrow Transplantation.\u0026nbsp;Lancet Haematol. 2020;7(2):e157-e167.\u003c/li\u003e\n \u003cli\u003eStreiler C, Shaikh F, Davis C，et al. Ruxolitinib is an effective steroid sparing agent in bronchiolitis obliterans due to chronic graft-versus-host-disease.\u0026nbsp;Bone Marrow Transplant. 2020;55(6):1194-1196.\u003c/li\u003e\n \u003cli\u003eBankier AA, MacMahon H, Colby T, et al. Fleischner Society: Glossary of Terms for Thoracic Imaging. Radiology. 2024;310(2):e232558. doi:10.1148/radiol.232558.\u003c/li\u003e\n \u003cli\u003eAbedin S, Yanik GA, Braun T, et al. Predictive value of bronchiolitis obliterans syndrome stage 0p in chronic graft-versus-host disease of the lung. Biol Blood Marrow Transplant. 2015;21(6): 1127-1131.\u003c/li\u003e\n \u003cli\u003eGunn ML, Godwin JD, Kanne JP, Flowers ME, Chien JW. High-resolution CT findings of bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation. J Thorac Imaging. 2008;23(4):244-250. doi:10.1097/RTI.0b013e3181809df0.\u003c/li\u003e\n \u003cli\u003eBos S, Murray J, Marchetti M, et al. ERS/EBMT clinical practice guidelines on treatment of pulmonary chronic graft-versus-host disease in adults. Eur Respir J. 2024;63(3):2301727. Published 2024 Mar 28. doi:10.1183/13993003.01727-2023.\u003c/li\u003e\n \u003cli\u003eHuang QS, Han TX, Chen Q, et al. Clinical risk factors and prognostic model for patients with bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation. Bone Marrow Transplant. 2024;59(2):239-246. doi:10.1038/s41409-023-02151-9.\u003c/li\u003e\n\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":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Bronchiolitis Obliterans Syndrome, Allogeneic Hematopoietic Stem Cell Transplantation, Children, Pulmonary Function Test, Prognosis, Risk Stratification","lastPublishedDoi":"10.21203/rs.3.rs-7974938/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7974938/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eBronchiolitis Obliterans Syndrome (BOS) following pediatric allogeneic hematopoietic stem cell transplantation (allo-HSCT) is associated with high morbidity and mortality, largely due to diagnostic delays and static prognostic assessments. This study aimed to validate the value of a strategy based on dynamic pulmonary function monitoring for early warning and prognostic stratification in the management of pediatric BOS.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis single-center, retrospective cohort study included 201 children who underwent allo-HSCT between January 2015 and December 2024, comprising 29 patients with BOS and 172 non-BOS controls. Independent risk factors for BOS were identified using multivariate Cox regression analysis. We evaluated the diagnostic performance of an \"at-risk stage\" warning signal based on the relative decline in Forced Expiratory Volume in 1 second (FEV1). In the longitudinal cohort of BOS patients, the independent predictive value of the FEV1 decline rate within the first 3 months post-diagnosis for progression-free survival (PFS) was investigated. The longitudinal trajectories of pulmonary function and high-resolution computed tomography (HRCT) imaging scores were also compared.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe cumulative incidence of pediatric BOS at our center was 6.9%. Multivariate analysis identified grade III-IV acute graft-versus-host disease (aGVHD) (HR\u0026thinsp;=\u0026thinsp;15.12), chronic GVHD (cGVHD) (HR\u0026thinsp;=\u0026thinsp;6.94), dry cough (HR\u0026thinsp;=\u0026thinsp;11.77), and an early post-transplant FEV1/FVC decline of \u0026ge;\u0026thinsp;10% (HR\u0026thinsp;=\u0026thinsp;8.70) as independent risk factors for BOS development. Using a relative FEV1 decline of \u0026ge;\u0026thinsp;10% (termed BOS stage 0p) as an early warning signal advanced the diagnostic window by a mean of 176 days and demonstrated a high negative predictive value of 84.95%. For prognosis, a rapid FEV1 decline (\u0026ge;\u0026thinsp;25%) within the first 3 months post-diagnosis was a strong independent predictor for inferior PFS (adjusted HR\u0026thinsp;=\u0026thinsp;30.68, 95% CI: 3.39-277.79, P\u0026thinsp;=\u0026thinsp;0.002), independent of the NIH severity grade at diagnosis. Furthermore, a significant \"radio-functional discordance\" was revealed, where HRCT structural damage scores continued to worsen even as pulmonary function stabilized in some patients (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study confirms that a strategy based on dynamic pulmonary function monitoring effectively addresses key challenges in pediatric BOS management. Monitoring the relative decline in FEV1 serves as a sensitive early warning tool, significantly advancing the diagnostic window. Moreover, assessing the early FEV1 decline rate post-diagnosis provides a powerful dynamic tool for achieving precise prognostic stratification and guiding individualized treatment escalation. The evaluation of BOS treatment response should concurrently address functional improvement and potential underlying structural deterioration.\u003c/p\u003e","manuscriptTitle":"Predictors and Prognostic Stratification of Bronchiolitis Obliterans Syndrome After Pediatric Allogeneic Hematopoietic Stem Cell Transplantation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-17 10:20:02","doi":"10.21203/rs.3.rs-7974938/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-23T16:11:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-19T03:02:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-01T13:42:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282105740617792907915247745897936220463","date":"2025-11-26T22:49:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"190595640100047319715472759440770401281","date":"2025-11-14T14:53:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-06T01:20:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-05T12:18:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-05T12:15:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Annals of Hematology","date":"2025-10-29T03:04:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7b4e22a0-6f40-4ba5-b477-4b21df66f90e","owner":[],"postedDate":"November 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-17T18:38:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-17 10:20:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7974938","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7974938","identity":"rs-7974938","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}