Epidemiology, Risk Factors, and Routine Blood Biomarkers of Aspergillosis in Cancer Patients in Jiangxi, China

Introduction

Invasive aspergillosis is a serious and potentially fatal fungal infection among oncology patients.¹ Cancer patients are at high risk of invasive fungal infection due to immunosuppression caused by malignancy itself, along with oncolytic treatments, corticosteroid use, neutropenia, prolonged hospital stay, underlying pulmonary disorders, organ dysfunctions, and invasive medical procedures.² Among solid tumors, lung cancer patients are particularly vulnerable to invasive fungal infection and colonization.³ In lung cancer patients, invasive pulmonary aspergillosis (IPA) occurred from 0.2% to 11.7%, with the mortality rate around 30 to 50%.^4–6 Furthermore, bronchial colonization with Aspergillus species is reported in 10–83% of cases and is associated with a poor survival rate.⁵ Colonization refers to the presence of species without clinical, radiological, and microbiological evidence of active diseases, whereas invasive infection involves tissue invasion with compatible clinical and radiologic feature.⁷

Host and treatment-related risk factors of aspergillosis have been described in various studies; however, their contribution in cancer cohorts and geographical regions may vary.³ Microbiological culture techniques and polymerase chain reaction (PCR) are the routinely used methods for identifying Aspergillus species in biological specimens.⁸ Besides these, biomarkers including serum and bronchoalveolar lavage fluid (BALF) galactomannan (GM) assays, as well as radiological findings, are essential for the early diagnosis and management of aspergillosis.⁹ The guidelines from the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium (EORTC/MSG-ERC), along with the Aspergillosis in Intensive Care Units (AspICU) guidelines, provide a structured approach to diagnosing aspergillosis.^7,10 Recent studies have emphasized the rising incidence of aspergillosis in immunocompromised patients and the need for early diagnostic markers and improved risk stratification in oncological settings.¹¹

Studies from China have revealed substantial geographical variation in the distribution and prevalence of Aspergillus species. The available literature indicates that most of the aspergillosis data are from North and East China. The central region, including Jiangxi province, reported a relatively limited number of cases. Moreover, most published data are mainly from critically ill patients and mixed cohorts, and studies specific to cancer patients are limited.¹² As a result, little is known about the clinical features and epidemiology of aspergillosis among cancer patients in this area. Furthermore, differentiating Aspergillus colonization from actual infection continues to be a clinical challenge, especially in settings where sophisticated fungal diagnostics are not always easily accessible. Therefore, this retrospective study analyzed the epidemiology of aspergillosis in cancer patients in Jiangxi, China. To the best of our knowledge, this is one of the first thorough studies in Jiangxi Province that focuses particularly on aspergillosis in cancer patients. We performed a risk factor analysis comparing infection versus colonization and lung cancer versus other solid cancers. Furthermore, routine blood biomarkers were analyzed in colonization and infection groups. This study intends to provide clinically relevant evidence that may support early risk assessment and enhance infection management in oncology patients, especially in regional or resource-constrained healthcare settings.

Methods

Study Design and Setting

The current retrospective study was conducted at Jiangxi Cancer Hospital, a provincial tertiary A cancer care center located in Nanchang, Jiangxi, China. All patients aged 18 years or older, diagnosed with cancer and with at least one positive culture or PCR result for Aspergillus from any clinical specimen between January 1, 2021, and November 1, 2025, were included. Patients were identified through the hospital microbiology database. The demographic, clinical, and laboratory data for the identified cases were collected from electronic hospital records (EHRs) and organized in an Excel sheet. We recognize the possibility of selection bias and limitations in generalizability due to the retrospective nature and single-center study. The study was approved by the hospital’s Ethics Review Committee (approval letter number 2024ky078).

Data Collection and Risk Factors Analysis

All data collected from the electronic hospital records were cleaned, and only the first positive culture was selected when multiple cultures were positive. Routine blood biomarker data were collected on the date of the first positive Aspergillus culture. Cases were divided into three groups: likely colonization, possible infection, and probable infection, according to the EORTC/MSGERC and AspICU guidelines.^7,10 Aspergillus isolation from respiratory specimens without indications of invasive disease was referred to as colonization. Possible infection was defined by compatible clinical or imaging findings without definitive mycological evidence. Probable infection was defined by the presence of host factors, clinical and radiological features, and mycological evidence such as a positive culture or galactomannan positivity in serum or BALF.

For categorical variables, the total counts and percentages were calculated; for continuous variables, the median and interquartile range (IQR) were determined. Initially, two groups were created: one consisting of likely colonization, and the second including possible and probable infections. Univariate and multivariate regression analyses were conducted to identify risk factors associated with infections. As more than half of the cases in our cohort were lung cancer, two infection groups among solid cancers were created: one for lung cancer and the second for all other solid cancers. Univariate and multivariate logistic regression analyses were performed to identify risk factors. Any case with missing variables was excluded from the multivariate analysis. All variables with p-values <0.1 in the univariate analysis were included in the multivariate models. A p-value of less than 0.05 was considered statistically significant.

Biomarker Analysis

Biomarkers were selected based on prior clinical evidence suggesting their relevance to systemic inflammatory responses in invasive aspergillosis.^13,14 The analysis was performed across the three Aspergillus-based categories for all cancer types. Hierarchical clustering analysis with z-score normalization was performed to identify patterns in biomarker expression across cancer-infection type combinations. This normalization enabled direct comparison of biomarkers measured on different scales. A heatmap was constructed to display z-scores for each biomarker across each cancer-infection type combination. Hierarchical clustering using Euclidean distance and complete linkage was applied to group similar biomarkers and cancer-infection types. Point-biserial correlation analysis was employed to examine the relationship between each biomarker and each cancer-infection type. Principal component analysis (PCA) was then performed to assess global biomarker variation across infection and assess their potential utility in differentiating colonization from infection, rather than to infer causality. Biomarker values were centered and scaled before PCA. PCA was conducted using the FactoMineR package (version 2.8) in R (v. 4.4.1), and the first two principal components were visualized in a score plot. Variable loadings and contributions to PC1 and PC2 were examined to identify biomarkers that most strongly influenced component separation. All analyses were performed using R (v. 4.4.1) and GraphPad Prism (v. 9).

Results

During the study period, a total of 354 cases were reported. Among these, 50 (14.1%) were classified as likely colonization, 154 (43.5%) as possible infection, and 150 (42.4%) as probable infection (Figure 1A). The majority of patients had lung cancer (n = 161, 45.48%), followed by gastrointestinal cancer (n = 68, 19.21%) and hematological malignancies (n = 35, 9.89%). Only 16 cases (4.52%) were from head and neck cancers. The prevalence of Aspergillus infection across cancer groups is shown in Figure 1B.

Figure 1 Distribution of Aspergillus cases in our cohort. (A) Overall distribution of cases. (B) Distribution of cases across different cancer types.

The median age of all cases was 66 years (IQR, 58–71), with 260 (73.45%) male and 94 (26.55%) female patients. Most specimens were sputum (n = 329, 92.94%), followed by BALF (n = 13, 3.67%), throat swabs (n = 6, 1.69%), secretions (n = 5, 1.41%), and catheters (n = 1, 0.28%), highlighting the challenge of distinguishing true infection from colonization. Regarding species, 313 (88.42%) were Aspergillus fumigatus, 36 (10.17%) were Aspergillus flavus, and 5 (1.41%) were Aspergillus niger.

Factors Associated with Infection versus Colonization in the Entire Cohort

Univariate and multivariate regression analyses were performed to identify risk factors for infection in our cohort, as shown in Table 1. Demographic characteristics were not significantly associated with infection. Among the cancer types, lung cancer was less frequently associated with infection; however, this was not significant in the multivariate analysis. Regarding comorbidities, chronic obstructive pulmonary disease (COPD) was less associated with infection, whereas hematopoietic stem cell transplantation appeared to increase the risk of infection; however, neither association remained significant in the multivariate analysis. Treatment exposures within 30 days were strongly associated with infection. Steroid use (OR 18.16, 95% CI 7.47–48.37, p < 0.001), chemotherapy (OR 5.41, 95% CI 1.87–18.34, p = 0.003), and elevated glucose levels (OR 1.68, 95% CI 1.08–2.63, p = 0.02) remained independently associated with infection.

Table 1 Univariate and Multivariate Regression Analysis of Demographic, Clinical, Treatment, and Laboratory Factors Associated with Infection versus Colonization

Factors Associated with Aspergillosis in Lung Cancer versus Other Solid Cancers

In our cohort, the majority of cases were from lung cancer patients. Therefore, the infection group was divided into two categories: one comprising all lung cancer patients with possible and probable infections, and the other comprising patients with other solid cancers who had possible and probable infections. Univariate and multivariate regression analyses were performed, as shown in Table 2. Smoking (OR 4.11, 95% CI 2.00–8.81, p < 0.001) and COPD (OR 3.83, 95% CI 1.43–11.51, p = 0.02) were independently associated with lung cancer infection. Hematopoietic stem cell transplantation was less frequent in lung cancer and showed an inverse association after adjustment (OR 0.48, 95% CI 0.23–0.99, p = 0.05). Among treatment categories, steroid use showed a trend in the univariate analysis and became independently associated with lung cancer after adjustment (OR 3.06, 95% CI 1.18–8.73, p = 0.03). Regarding laboratory results, higher nadir neutrophil counts (multivariate OR, 1.19; 95% CI, 1.08–1.33; p < 0.001) and higher hemoglobin levels (OR, 1.02; 95% CI, 1.01–1.03; p = 0.01) were notably associated with the lung cancer group. In contrast, higher total bilirubin and glucose levels were independently associated with other solid cancers (bilirubin OR 0.95, 95% CI 0.92–0.98, p = 0.01; glucose OR 0.86, 95% CI 0.79–0.94, p = 0.01). The 30-day mortality rate was higher for other solid cancers (10.76%) compared to lung cancer (3.05%); however, this difference was not statistically significant after adjustment.

Table 2 Univariate and Multivariate Regression Analysis of Demographic, Clinical, Treatment, and Laboratory Factors Associated with Aspergillosis in Lung Cancer versus Other Solid Cancers

Biomarker Analysis

Biomarker patterns across cancer–infection groups were examined using hierarchical clustering of z-score–normalized values (Figure 2). This analysis revealed that cancer–infection combinations clustered more strongly according to infection category than by underlying cancer type. Most probable infection cases clustered together, with higher z-scores for inflammatory and liver-related markers than colonization cases. Neutrophils, white blood cells (WBCs), and the neutrophil-to-lymphocyte ratio (NLR) were consistently elevated in probable infection cases across several cancer types. This was especially seen in gastrointestinal, head and neck, and other solid cancers, indicating a stronger systemic inflammatory response in these patients. In colonization cases, these markers showed low z-scores, indicating lower inflammatory activity. Lymphocyte counts were higher in hematological cancer-probable infection cases, but this varied across malignancies.

Figure 2 Z-score heatmap showing biomarker profiles across cancer types and Aspergillus infection categories. Abbreviations: PLR, Platelet-to-Lymphocyte Ratio; NLR, Neutrophil-to-Lymphocyte Ratio; WBC, White Blood Cell count; ALT, Alanine Aminotransferase; AST, Aspartate Aminotransferase; Gi cancer, Gastrointestinal cancer.

Liver enzymes, as well as renal and metabolic markers, exhibited a similar stepwise pattern across infection categories. Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were frequently higher in probable infection cases, particularly in hepatobiliary, gastrointestinal, and lung cancer patients, suggesting more pronounced systemic inflammatory or metabolic stress in these groups. Creatinine and glucose levels also tended to be higher in probable infection groups, particularly in patients with gastrointestinal, hepatobiliary, and other solid cancers, whereas colonization cases generally exhibited lower z-scores. Platelet levels in some probable infection cases were higher than in colonization, although this pattern was less consistent than that observed for neutrophils, NLR, and WBC. Albumin and hemoglobin patterns were less consistent, showing slightly higher z-scores for colonization and possible infection than for probable infection; however, no clear overall trend was observed.

Furthermore, point-biserial correlation analyses were performed to provide a more granular assessment of the association between individual biomarkers and each cancer–infection type (Figure 3). Across cancer types, probable infection was modestly positively correlated with higher neutrophil counts, white blood cell counts, NLR, ALT, AST, creatinine, glucose, and platelets, while showing negative or near-zero correlations with albumin and hemoglobin, consistent with the clustering results.

Figure 3 Correlation heatmap between routine laboratory biomarkers and cancer–infection categories. Abbreviations: PLR, Platelet-to-Lymphocyte Ratio; NLR, Neutrophil-to-Lymphocyte Ratio; ALT, Alanine Aminotransferase; AST, Aspartate Aminotransferase.

To further characterize biomarker variation across infection categories, a PCA was performed (Figure 4). The PCA score plot indicates that, due to higher neutrophil counts, the probable infections shifted toward the positive Dim1 axis. The possible infection group slightly shifted toward Dim1, while the colonization group was mainly clustered at the center. The Dim2 had a minimal effect on group separation, while 25% of the variance in Dim1 was mainly due to inflammatory biomarkers (Figure 4A). According to variable-loading analysis, WBC (35%), neutrophils (21.6%), and NLR (21.6%) contributed to PC1. Conversely, PC2 was most affected by platelets (25.4%), lymphocytes (16.7%), and their ratio (41.1%) (Figure 4B).

Figure 4 Principal Component Analysis (PCA) of biomarkers by infection type. (A) PCA score plot showing clustering of likely colonization, possible infection, and probable infection. (B) Variable contribution bar plot showing loadings for PC1 and PC2.

Discussion

In the present study, a total of 354 Aspergillus-positive cultures were investigated, with a high proportion of possible infections (43.5%), followed by probable infections (42.4%) and colonization (14%). A high proportion of cases (45.48%) occurred in lung cancer patients, which aligns with the previous studies stating that Aspergillus infection or colonization is common in individuals with pulmonary malignancies.⁴ In lung cancer patients, invasive aspergillosis and colonization are reported up to 11.7% and 83%, respectively.^4,5 This high incidence of aspergillosis might be due to the advanced underlying complications, and excessive use of corticosteroids and chemotherapies.⁶ In our study, only 9.9% of patients had hematological cancers. Patients with hematological cancers have the highest risk of invasive fungal diseases. A relatively lower rate in our setting might be due to a lower local incidence or referral rate of hematological cancer, rather than the true epidemiology.¹⁵

Among the biological specimens, 92.94% were sputum, because most patients had lung cancer, and sputum collection is a patient-friendly and less invasive approach in such cases.¹⁶ Regarding the Aspergillus species types, 88.42% were A. fumigatus, 10.17% were A. flavus, and 1.41% were A. niger. The predominance of A. fumigatus in our cancer population is comparable to its overall distribution in China, which is reported at 75.14% of all Aspergillus cases.¹² Among non-fumigatus Aspergillus species, our distribution ratio aligns with the overall distribution in China; however, A. niger occurred at a lower proportion in the current study than in the overall distribution in China.¹² These findings highlight the role of A. fumigatus and emphasize the importance of prioritizing empirical therapy and susceptibility testing.¹⁷

Steroid use and chemotherapy were independently associated with infection, consistent with their known immunosuppressive effects that increase susceptibility to fungal infections.^18–21 Higher glucose levels (OR 1.68) and lower hemoglobin (OR 0.98) were associated with infection, reflecting impaired immunity and possible chemotherapy-related bone marrow suppression.^6,22–24

Given the high number of lung cancer patients in our cohort, we analyzed the risk factors for aspergillosis in lung cancer compared to other solid cancers. Smoking and COPD were identified as independent risk factors for aspergillosis in lung cancer patients (OR 4.1 and 3.83, respectively). Studies have shown that these variables follow well-established epidemiological patterns and are associated with lung infections and pulmonary malignancies.^3,4,25 Steroid use was independently associated with aspergillosis in lung cancer patients (OR 3.06). This may be attributed to its use in managing tumor-related respiratory tract obstruction, chemotherapy-related complications, or post-radiation pneumonitis.^4,26 Hematopoietic stem cell transplantation was independently associated with the other solid cancer group in the multivariate model. This is expected, as transplantation is less common in patients with lung cancer.²⁷

Higher nadir neutrophil and hemoglobin levels were independently associated with aspergillosis in lung cancer patients, suggesting occurrence in non-neutropenic individuals due to local immunosuppression, COPD, or airway obstruction.^4,28 Similarly, higher hemoglobin levels in lung cancer patients may reflect less chemotherapy-related marrow suppression than in other solid tumors receiving more intensive treatment.^29,30 Higher glucose and bilirubin levels were independently associated with aspergillosis in non-lung solid cancers, particularly hepatobiliary and gastrointestinal malignancies, where metabolic disturbances impair immunity and increase susceptibility to invasive fungal infections.^23,31

Hierarchical clustering revealed that cases were grouped by infection status rather than cancer type, suggesting that systemic aspergillosis indicators are consistent across malignancies.^32,33 The probable infection group showed elevated inflammatory markers (neutrophils, WBCs, NLR) and metabolic markers (glucose and creatinine). These patterns are typical of invasive fungal infections, characterized by systemic inflammation and associated with a high mortality rate.^34–36 AST and ALT changes in probable aspergillosis infection indicate liver involvement alongside systemic inflammation. This suggests that the fungus may affect both liver function and blood parameters.^34,37 Albumin and hemoglobin showed weak, inconsistent links to infection, influenced by cancer, chemotherapy, and cachexia, limiting their reliability as aspergillosis markers.^38,39

Correlation analysis confirmed the clusters, showing higher neutrophils, WBCs, NLR, glucose, and platelets in probable infections. This suggests that fungal invasion triggers innate immunity, often leading to reactive platelet increases during inflammation.^35,40,41 PCA showed probable infections aligned with inflammation, colonization stayed near the origin, and possible infections shifted slightly. This indicates invasive aspergillosis triggers strong inflammation, which may serve as a diagnostic biomarker.³⁵

This study has several limitations. The study is retrospective; therefore, several variables were unavailable for analysis. For example, the data from antifungal susceptibility testing were not accessible, which is required to determine the resistance pattern of the isolates, especially to azole-resistant isolates. Information regarding prior antifungal therapy and its correlation with fungal infection was not provided. Furthermore, the isolates were unavailable for molecular confirmation and subsequent analysis. Despite these limitations, this is the first large study describing Aspergillus epidemiology, risk factors, and biomarker patterns in cancer patients in Jiangxi, China. These findings provide region-specific insights that could help with early risk assessment and guide clinical decisions in similar resource-limited settings. These findings might help health care officials in the region and similar settings in managing aspergillosis. However, future molecular-based prospective studies are needed to analyze the genetic determinants of identification and antifungal resistance mechanisms.

Conclusion

This is one of the first comprehensive epidemiological analyses of aspergillosis among cancer patients in Jiangxi, China. In the present study, a high number of cases were possible infections, followed by probable infections and colonization. Among the cancer types, a high proportion of cases were from lung cancer, followed by gastrointestinal and blood cancer. Among the species types, A. fumigatus was reported most frequently at 88.42%. Risk factor analysis indicates that patients using steroids and chemotherapy had a greater risk of aspergillosis. For lung cancer patients, smoking underlying COPD and steroid usage were found to be independent risk factors of aspergillosis. The analysis of blood biomarkers revealed that elevated neutrophil and WBC counts, along with the NLR ratio, were associated with Aspergillus infection. These biomarkers may help differentiate infection from colonization in routine clinical practice. However, these findings should be interpreted with caution due to the study limitations, which are a single-center, retrospective design and lack of AST data and molecular confirmations. Future prospective, multi-center, molecular-based studies for identification and antifungal resistance mechanisms are required to manage and prevent aspergillosis.