The association of the advanced lung cancer inflammation index with postoperative complications in patients undergoing lung resection for bronchiectasis

Introduction

Bronchiectasis is a significant chronic pulmonary condition characterized by permanent and irreversible enlargement of the bronchi, primarily driven by persistent airway inflammation and recurrent infections. This chronic inflammatory state not only exacerbates structural lung damage but also triggers systemic metabolic disorders, often leading to malnutrition and immune dysfunction (1-3). Recent data suggest that the incidence of bronchiectasis varies widely, ranging from 67 to 1,200 cases per 100,000 individuals. Surgical resection is recommended for localized bronchiectasis when conservative treatments fail or when patients experience life-threatening hemoptysis (1,4-6). Despite the majority of patients receiving standardized perioperative care, the rate of complications following lung resection for bronchiectasis has been reported to range from 9.4% to 53% (7-9). Postoperative complications not only lead to prolonged hospital stays and increased treatment costs but also signify a poorer prognosis (10). Although previous studies have identified factors such as a history of tuberculosis, limited expiratory capacity, and incomplete resection as independent risk factors for postoperative complications in patients with bronchiectasis (7,11), these indicators fail to account for the impact of systemic inflammation and nutritional status on surgical outcomes.

Emerging evidence highlights the prognostic significance of inflammatory biomarkers and nutritional indices in thoracic surgery. Preoperative hematological markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) have been identified as risk factors for early recurrence and poor long-term outcomes in lung cancer patients undergoing surgery (12-15). A recent study indicates that high preoperative SII correlates with an increased risk of postoperative pneumonia in non-small cell lung cancer (NSCLC) (16). Additionally, Cai et al. reported that a high PLR serves as an independent predictor of post-pneumonectomy pneumonia (17). Nutritional parameters, including low body mass index (BMI) and high controlling nutritional status (CONUT) scores, have also been recognized as independent risk factors for postoperative complications in bronchiectasis and lung cancer surgery. Moreover, these nutritional deficits are associated with unfavorable long-term oncological outcomes in lung cancer patients (18-22). However, these individual biomarkers alone cannot comprehensively assess the combined inflammatory and nutritional status of patients.

The advanced lung cancer inflammation index (ALI), which integrates BMI, albumin (ALB), and NLR, was initially developed by Jafri et al. to evaluate the prognosis of patients with metastatic NSCLC (23). Subsequent studies have demonstrated that a low pre-treatment ALI is an unfavorable prognostic factor in various cancers, including hepatocellular carcinoma, esophageal squamous cell carcinoma, gastric cancer, and colorectal cancer (24-27). Moreover, ALI has also been shown to predict prognosis in various benign conditions. For instance, based on data from the National Health and Nutrition Examination Survey (NHANES), Tu et al. demonstrated that a high ALI serves as a protective factor against cardiovascular mortality in patients with hypertension (28). Another NHANES-based analysis found that an elevated ALI was significantly associated with reduced mortality in individuals with type 2 diabetes and cardiovascular disease (29). Wang et al. reported that low ALI was an adverse prognostic factor in patients with acute coronary syndrome undergoing percutaneous coronary intervention (30). Additionally, the ALI has been utilized as a predictor of postoperative complications in colon cancer patients (31). Despite its broad range of applications, to our knowledge, no studies have explored the relationship between the ALI and pulmonary postoperative complications, particularly under conditions with high complication rates such as bronchiectasis.

This study reviewed the clinical data of 191 patients with localized bronchiectasis and identified ALI as an independent risk factor for postoperative complications in bronchiectasis patients undergoing lung resection. Based on ALI, a nomogram was developed, providing a valuable predictive tool for assessing the risk of postoperative complications in bronchiectasis patients undergoing surgical treatment. We present this article in accordance with the TRIPOD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2271/rc).

Methods

Study design and population

This was a single-center, retrospective study that included 191 patients with localized bronchiectasis at Beijing Chao-Yang Hospital, Capital Medical University, between January 2013 and November 2023. In this study, localized bronchiectasis was defined as a condition in which the lesions were confined to a single lung lobe. All of the patients achieved complete resection of the lesion via surgical treatment. Complete resection was defined as surgical resection of all involved segments diagnosed preoperatively by high-resolution computed tomography (HRCT). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the ethics board of Beijing Chao-Yang Hospital, Capital Medical University (No. 2022-Ke-530). Given the retrospective nature of the study, the requirement for written informed consent was waived.

Inclusion criteria: (I) localized bronchiectasis; and (II) availability of complete clinical data. Exclusion criteria: (I) presence of preoperative fever; (II) emergency hospital admission; (III) patients with nonsurgical management of bronchiectasis; (IV) history of previous thoracic surgery; and (V) history of hematological disease or malignancies.

Data collection

We reviewed and collected patient data through the electronic medical records system, including patient demographics such as BMI, presence of hemoptysis, comorbidities (hypertension, diabetes and tuberculosis), smoking history, surgical modality [thoracotomy or video-assisted thoracoscopic surgery (VATS)], operation time, drainage tube indwelling time, length of hospital stay after the operation, total length of hospital stay, postoperative complications, and results of routine preoperative blood tests, including leukocyte count, neutrophil count, lymphocyte count and ALB. The biomarkers were calculated as follows: ALI = [BMI (kg/m²)] × [ALB (g/dL)]/(NLR), BMI = [weight (kg)]/[height (m)]², NLR = (neutrophil count)/(lymphocyte count), PLR = (platelet count)/(lymphocyte count), SII = (neutrophil count) × (platelet count)/(lymphocyte count), NLRAR = (NLR)/[ALB (g/L)], LLR = (leukocyte count)/(lymphocyte count).

Definition of complications

In this study, postoperative complications were defined as adverse events occurring during hospitalization after surgery or within 30 days after discharge. The Clavien-Dindo classification was applied to assess the severity of complications (32), and any complication that reached grade II or higher was recorded. Common complications observed in patients included prolonged air leakage, pneumonia, pulmonary atelectasis, empyema, hemorrhage, wound infection, cardiac arrhythmia, and acute respiratory distress syndrome (Table S1). No postoperative mortality was observed in this study. In this study, postoperative complications were assessed by an experienced thoracic surgeon serving as the reviewer.

Statistical analysis

The optimal cutoff value for the ALI was determined through the receiver operating characteristic (ROC) curve and the Youden index, and the ALI was subsequently converted into categorical variables. All continuous variables were first tested for normality. Variables conforming to a normal distribution were expressed as the mean ± standard deviation (SD), and comparisons between the two groups were conducted using the independent samples t-test. Variables not normally distributed were presented as median [interquartile range (IQR)] and were compared using the Mann-Whitney U test. Categorical variables are expressed as numbers (percentages) and were analyzed using either the Pearson χ² test or Fisher’s exact test. Univariate and multivariate logistic regression analyses were employed to identify independent risk factors for postoperative complications. A nomogram was developed to estimate postoperative complications. The predictive performance of the nomogram model was evaluated using the calibration curve. Statistical analyses were performed using SPSS (version 26.0), GraphPad Prism (version 10.2), and R software (version 3.6.2). A two-sided P value less than 0.05 was considered to indicate statistical significance.

Results

Baseline characteristics

A total of 191 patients with a pathological diagnosis of bronchiectasis were included in the study, comprising 80 male patients (41.9%) and 111 female patients (58.1%). The median age was 52 years (IQR, 41–60 years), and the median BMI was 23.0 kg/m² (IQR, 21.0–25.4 kg/m²). Hemoptysis was reported in 110 patients (57.6%), while 40 patients (20.9%) had a history of cigarette smoking. Regarding surgical intervention, VATS was performed in 151 patients (79.1%). Sixteen patients (8.4%) underwent wedge resection/segmentectomy, while 175 patients (91.6%) underwent lobectomy. A total of 44 patients (23.0%) experienced complications, with some patients presenting more than one, resulting in 50 complications in total. Table 1 presents the baseline characteristics of these patients.

Comparison of the ALI and other hematological biomarkers

We assessed the correlation between the ALI and preoperative inflammatory biomarkers and postoperative complications in bronchiectasis patients (Table 2). Our findings demonstrated significant associations between NLR (P=0.004), PLR (P=0.008), SII (P=0.02), NLRAR (P=0.002), LLR (P=0.01), and ALI (P<0.001) and the occurrence of postoperative complications. Subsequently, using postoperative complications as the outcome variables, we plotted ROC curves for each indicator (Figure 1). By analyzing the area under the curve (AUC) for these indicators, we found that the ALI had a better ability to predict postoperative complications than other indicators. The critical cutoff value for the ALI was established at 43.1 through ROC curve analysis, which identified the maximum Youden index of 0.400, corresponding to a sensitivity of 65.9% and specificity of 74.1%. The AUC reached 0.676 [95% confidence interval (CI): 0.581–0.771] (Table S2). Based on this threshold, patients were categorized into two groups: a low ALI group (ALI ≤43.1, n=67) and a high ALI group (ALI >43.1, n=124).

Figure 1 ROC curves of preoperative inflammatory biomarkers and ALI in patients with bronchiectasis. (A) ALI. (B) NLR. (C) PLR. (D) SII. (E) NLRAR. (F) LLR. ALI, advanced lung cancer inflammation index; AUC, area under the curve; LLR, leukocyte lymphocyte ratio; NLR, neutrophil-to-lymphocyte ratio; NLRAR, NLR-albumin ratio; PLR, platelet-to-lymphocyte ratio; ROC, receiver operating characteristic; SII, systemic immune-inflammation index.

Relationships between the ALI subgroups and clinical variables

The correlations between the ALI and clinical characteristics were shown in Table 3. Significant differences were observed between the two patient groups in terms of BMI, smoking history, hemoptysis, NLR, PLR, SII, NLRAR, and LLR. Additionally, compared to the high ALI group, patients in the low ALI group exhibited a higher proportion of open thoracotomy and had longer durations of chest drainage, as well as extended postoperative and overall hospital stays. Nevertheless, there was no significant difference between the two groups in terms of age, sex, comorbidities, and type of surgery.

Univariate and multivariate logistic regression analysis

According to the univariate logistic analysis, sex, BMI, smoking history, ALI, surgical approach, and operation time were correlated with postoperative complications. After adjustment for confounding factors, multivariate analysis revealed that ALI [odds ratio (OR): 3.006; 95% CI: 1.351–6.686; P=0.007], BMI (OR: 0.868; 95% CI: 0.760–0.992; P=0.04), and operation time (OR: 1.010; 95% CI: 1.002–1.018; P=0.02) were found to be independent prognostic factors for postoperative complications (Table 4). Specifically, an increase of 1 kg/m² in BMI (OR: 0.868) was associated with a 13.2% reduction in the risk of postoperative complications. Patients with lower ALI (OR: 3.006) had approximately three times the risk of developing postoperative complications compared to those with higher ALI. Additionally, for each additional minute of operation time (OR: 1.010), the risk of complications increased by 1.0%.

Nomograms constructed based on independent related factors

Based on the independent factors identified in the multifactor logistic regression analysis, we established a nomogram to predict the risk of postoperative complications in bronchiectasis patients (Figure 2). The predictive performance of the nomogram model was assessed using a calibration curve. As shown in Figure 3, the calibration curve demonstrated that the predicted incidence of postoperative complications in bronchiectasis patients closely matched the actual observed incidence, indicating excellent predictive accuracy. The predictive value of the nomogram for short-term complications in patients with bronchiectasis after lung resection was evaluated using ROC curves (Figure 4). The AUC in the analysis was 0.776.

Figure 2 Nomogram for predicting postoperative complications in patients with bronchiectasis. ALI, advanced lung cancer inflammation index; BMI, body mass index.

Figure 3 Internal verification of nomogram-calibration curve.

Figure 4 ROC curve of the nomogram for prediction of postoperative complications in patients with bronchiectasis. AUC, area under the curve; ROC, receiver operating characteristic.

We presented a hypothetical case to illustrate the application of a nomogram in assessing surgical risk. The patient was a 55-year-old male with localized bronchiectasis scheduled for elective lung segmentectomy. Preoperative evaluation indicated BMI of 22 kg/m² (28 points on the nomogram), ALI of 38 (23 points), and an estimated operation time of 200 minutes (38 points). The total score of 89 points corresponded to a 60% risk of postoperative complications according to the nomogram (Figure 2). Given the elevated risk of postoperative complications, several preoperative strategies were recommended to mitigate this risk, including nutritional supplementation to enhance the patient’s nutritional status, the use of prophylactic antibiotics and anti-inflammatory treatments to reduce inflammation, and preoperative three-dimensional surgical planning to optimize operative time. These interventions aimed to effectively reduce the likelihood of postoperative complications in this high-risk patient population.

Discussion

In this study, we were the first to establish a significant association between preoperative ALI and postoperative complications in patients with localized bronchiectasis undergoing surgical treatment. Our results indicate that a low preoperative ALI serves as an independent risk factor for postoperative complications. As ALI integrates BMI, ALB levels, and NLR, it provides a more comprehensive reflection of both nutritional status and systemic inflammation. A lower ALI signifies a state of malnutrition and heightened inflammation. Consequently, patients with low ALI may benefit from targeted preoperative interventions, such as nutritional supplementation and inflammation management, to optimize surgical outcomes and mitigate the risk of complications.

Bronchiectasis is a prevalent chronic respiratory disease globally, and inflammation plays a pivotal role in its onset and progression. The infiltration of innate immune cells, primarily neutrophils, into lung tissue is a key factor initiating cascades that lead to the pathological changes observed in bronchiectasis (33). Moreover, inflammation can contribute to malnutrition, as evidenced by decreases in the serum ALB concentration and BMI (34,35). There is growing evidence that peripheral blood biomarkers of inflammation and nutrition can help predict bronchiectasis progression and prognosis. A high NLR is indicative of worsening conditions in these patients (36). A study from a nationwide population in South Korea highlighted that being underweight (BMI <18.5 kg/m²) is a risk factor for bronchiectasis in young individuals (37). Research by Qi and colleagues demonstrated that patients with a low BMI experience more severe bronchiectasis, increasing their risk of hospitalization and mortality (38). Additionally, low serum ALB levels are significantly associated with the bronchiectasis severity index (BSI) and FACED score (3,39). However, these biomarkers alone do not provide a comprehensive assessment of the inflammation and nutritional status of patients. The ALI, based on BMI, the serum ALB concentration, and the NLR, can simultaneously reflect the nutritional and inflammatory status of patients (23). The correlation between a lower ALI and poorer prognosis has been established in various cancers and inflammatory diseases. Nonetheless, research on the clinical significance of the ALI in bronchiectasis patients remains limited. Our study indicates that a low preoperative ALI is an independent risk factor for postoperative complications in bronchiectasis patients undergoing single-lung resection.

In our research, we observed that a greater preoperative NLR was associated with an increased incidence of postoperative complications following lung resection, which is consistent with the findings of previous studies (40,41). Furthermore, we identified high preoperative SII, PLR, NLRAR, and LLR as adverse predictors of postoperative complications in patients with bronchiectasis. ROC curve analysis revealed that the AUC of ALI (0.676) was higher than that of other indices, including NLR (0.644), PLR (0.631), SII (0.618), NLRAR (0.654), and LLR (0.650). While NLR, PLR, SII, NLRAR, and LLR primarily reflect systemic inflammation, they fail to account for the interplay between malnutrition and immune dysregulation in patients with bronchiectasis. In contrast, ALI incorporates both nutritional indicators and an inflammatory marker, thereby enhancing its predictive accuracy. BMI serves as a measure of body composition. A lower BMI often indicates inadequate nutrition, which correlates with early lung inflammation and increased activity of free neutrophil elastase, thereby linking poor nutritional status with exacerbated lung disease (42). Previous finding indicates that a low BMI predicts poor prognosis in bronchiectasis (38). Our recent findings further confirm its role as an independent risk factor for postoperative complications after bronchial dilation surgery (19). ALB levels, another marker of nutritional status, also play a significant role. Patients with hypoalbuminemia typically exhibit more severe forms of bronchiectasis (3,39). This may be due to hypoalbuminemia leading to impaired immune responses in the host (43). NLR reflects the severity of innate immune responses, mainly triggered by bacterial infections. In bronchiectasis, lymphocyte levels are reduced, potentially leading to an uncontrolled immune response (33,36,44,45). Thus, ALI serves as a comprehensive index, integrating anthropometric, nutritional, and inflammatory factors essential for evaluating bronchiectasis patients.

We identified prolonged duration of surgery as another independent risk factor for postoperative complications, consistent with findings from previous research (46,47). The specific mechanisms by which extended surgical time contributes to complications remain unclear; however, several potential explanations exist. For example, surgeries with prolong time increase the exposure of the wound to microbes, thereby increasing the risk of wound contamination. Additionally, prolonged operations can cause tissue retraction, leading to tissue ischemia and necrosis. Furthermore, extended durations of surgery often reflect the complexity of the procedures, which can increase surgeon fatigue and potentially result in a greater incidence of postoperative complications (47,48).

This study developed a predictive model for postoperative complications in patients with bronchiectasis based on ALI, BMI, and operation time. The model demonstrated good predictive performance and discriminative ability, as validated by calibration and ROC curves. Currently, research on predicting postoperative complications in bronchiectasis remains limited. Previous studies have identified forced expiratory volume in 1 second <60% of the predicted value, a history of tuberculosis, and incomplete resection as independent risk factors for postoperative complications (7,11). However, these studies primarily focused on pulmonary function and surgical factors while failing to account for systemic inflammatory and nutritional status. Our previous model, which incorporated the CONUT score, BMI, and operation time, considered preoperative nutritional status but did not address systemic inflammation (19). In contrast, this study is the first to integrate ALI into a predictive model for postoperative complications, bridging the gap in assessing inflammatory status. Moreover, we specifically targeted patients with localized bronchiectasis confined to a single lobe, thereby enhancing the specificity of the model. In clinical practice, this model can aid in preoperative risk assessment for patients undergoing elective surgery for bronchiectasis. For those with low BMI and ALI, preoperative nutritional interventions, such as a high-protein diet, have been shown to improve perioperative recovery (49,50). Additionally, for patients with excessive systemic inflammation, targeted anti-inflammatory therapies, including antibiotics, may be considered to improve inflammatory status (51,52). Furthermore, preoperative three-dimensional reconstruction can facilitate surgical planning, particularly for segmentectomy, potentially reducing operative time and minimizing the risk of postoperative complications.

There are several potential limitations of our study. First, as a single-center study with a relatively small sample size, the generalizability of our findings may be limited. A multicenter, prospective study is necessary to validate our results in a broader population. Second, the retrospective nature of the study may introduce selection bias, which could affect the interpretation of our findings. Future prospective studies with well-defined inclusion criteria and standardized interventions aimed at improving patients’ nutritional and inflammatory status may enhance the applicability of our nomogram. Third, our study lacks external validation, which further limits the clinical utility of our findings. Future studies with independent external cohorts are needed to confirm the robustness and reproducibility of our nomogram. Additionally, we only assessed short-term postoperative complications, and long-term outcomes, such as the recurrence of bronchiectasis or pulmonary functional recovery, were not evaluated. A longer follow-up period is warranted to determine the prognostic value of ALI in predicting long-term complications and overall patient outcomes.

Conclusions

This study highlights ALI as an independent and effective predictor of postoperative complications in patients undergoing bronchiectasis surgery. The nomogram developed by incorporating ALI, BMI, and operation time provides a novel and practical tool for clinicians to assess individual patient risk and optimize perioperative management strategies. Future multicenter, prospective studies are required to further validate these findings and refine the nomogram for broader clinical application.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2271/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2271/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2271/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2271/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the ethics board of Beijing Chao-Yang Hospital, Capital Medical University (No. 2022-Ke-530). Given the retrospective nature of the study, the requirement for written informed consent was waived.

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

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