Diagnostic and prognostic value of serum HBP combined with PCT, CRP, and SAA in early-stage pneumonia

Abstract

Objective

To assess the diagnostic efficacy of serum heparin-binding protein (HBP) as a standalone biomarker and in combination panels for distinguishing early-stage bacterial from viral pneumonia, and to explore its prognostic value in predicting progression to severe pneumonia.

Methods

This retrospective cohort study enrolled 269 participants, including 166 bacterial pneumonia patients (BPG), 42 viral pneumonia patients (VPG), and 61 age-/sex-matched healthy controls (NCG). Serum concentrations of four inflammatory biomarkers—HBP, procalcitonin (PCT), serum amyloid A (SAA), and C-reactive protein (CRP)—were quantitatively analyzed in all participants using immunoturbidimetry assays. Comparative analysis of inflammatory marker levels among the three groups was conducted, and receiver operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic performance of these four inflammatory biomarkers for distinguishing bacterial from viral pneumonia. Patients were stratified into mild and severe pneumonia groups based on CURB-65 score, followed by binary logistic regression and forest plot analysis to identify factors associated with disease severity.

Results

Serum levels of HBP, SAA, and CRP were significantly elevated in both BPG and VPG compared with the NCG (P < 0.01). PCT concentrations showed marked elevation exclusively in bacterial pneumonia (P < 0.01), while remaining comparable to CPG in VPG (P = 0.47). The four inflammatory biomarkers demonstrated favorable diagnostic performance for differentiating both bacterial and viral pneumonia, with enhanced diagnostic accuracy observed in bacterial cases. Notably, HBP exhibited the most prominent discriminative capacity (optimal cutoff: 17.9 ng/mL; AUC: 0.93, 95% CI 0.89–0.97; sensitivity: 81.93%; specificity: 96.72%). The biomarker combination strategy integrating HBP with other three indicators significantly improved diagnostic efficacy. Multivariate binary logistic regression coupled with forest plot analysis identified serum HBP as an independent predictor of severe bacterial pneumonia.

Conclusions

HBP emerges as a dual-functional biomarker demonstrating diagnostic precision for early-stage bacterial pneumonia and prognostic capability for disease progression. Compared to a single biomarker, the combined detection of HBP, PCT, SAA and CRP is more valuable for diagnosing bacterial pneumonia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-026-03078-5.

Introduce

Pneumonia, a clinical syndrome characterized by inflammatory infiltration of distal airways and pulmonary parenchyma, arises from diverse etiologies including infectious pathogens, immunologic reactions, and physical irritants. Notably, bacterial and viral pathogens predominate in clinical practice. Current diagnostic paradigms integrate clinical presentation, radiographic findings, and microbiological studies, yet face critical limitations: nonspecific imaging findings during initial stages and prolonged turnaround time (48–72 h) for conventional sputum cultures, frequently delaying antimicrobial initiation. Serological biomarkers have gained prominence in infectious disease diagnostics due to rapid turnaround and operational convenience. While procalcitonin (PCT), serum amyloid A (SAA), and C-reactive protein (CRP) are routinely employed in pneumonia evaluation, their diagnostic utility is constrained by suboptimal sensitivity and specificity in early disease phases. Mechanistic limitations further compromise clinical application: The production of PCT is genetically regulated by calcitonin I, while its serum concentration fluctuates in response to three key determinants: endotoxin release during bacterial growth, microbial taxonomy, and functional status of host immunity [1]; SAA’s diagnostic potential is curtailed by its transient serum persistence (half-life ≈ 50 min) despite acute-phase responsiveness [2]; CRP, while reflective of inflammatory burden, exhibits poor specificity due to interference from comorbidities and immunological confounders [3].

Heparin-binding protein (HBP), a homoserine protease released by activated neutrophils (also termed azurocidin or cationic antimicrobial protein 37 [CAP37]), serves dual functions in antimicrobial defense. It enhances leukocyte chemotaxis to infection sites while augmenting the phagocytic capacity of mononuclear macrophages. The biomarker’s diagnostic potential stems from its acute-phase responsiveness, particularly in infection detection. He et al. [4] demonstrated HBP’s clinical utility in sepsis management, showing significant correlations with hepatic impairment and exhibiting strong prognostic value for adverse outcomes. Parallel investigations revealed serum HBP levels as quantitative indicators of acute pancreatitis severity, with dynamic monitoring proving particularly valuable during initial disease stages [5]. Prognostically, 24-hour HBP clearance rates showed predictive superiority over static measurements, with enhanced performance when integrated with CRP/PCT ratios [6]. A study showed HBP modulates vascular endothelial permeability, facilitating plasma exudation and tissue edema formation through endothelial barrier disruption [7]. This phenomenon potentially linked to HBP-mediated endothelial dysfunction and systemic vasculitis .

Despite these advancements, critical knowledge gaps persist regarding HBP’s diagnostic efficacy in pneumonia, particularly during early disease progression. This study systematically evaluates HBP’s standalone and combinatorial diagnostic performance with conventional biomarkers (PCT, CRP, SAA), while assessing its prognostic utility in pneumonia management. Our findings aim to advance the clinical implementation of serological biomarkers for optimized pneumonia care.

Materials and methods

Study population

This retrospective cohort study analyzed 269 consecutively enrolled participants at Fujian Provincial Hospital (June 2024 - April 2025), comprising 208 antibiotic-naïve pneumonia patients (stratified into bacterial [BPG, n = 166] and viral pneumonia [VPG, n = 42] groups) and 61 age/sex-matched healthy controls (NCG). Diagnostic criteria included: BPG: Respiratory virus testing by nasopharyngeal swab PCR yielded a negative result, radiographic consolidation and positive bacterial culture (sputum/bronchoalveolar lavage fluid); VPG: Pathogenic bacterial cultures were negative, compatible imaging findings and nasopharyngeal swab PCR positivity for respiratory viruses. Exclusion criteria encompassed: 1) Pre-admission antimicrobial use; 2) Active malignancies/autoimmune disorders; 3) Polymicrobial infections; 4) Organ dysfunction (SOFA score > 6); 5) Patients with evidence of both bacterial and viral pneumonia infections. This study protocol received ethical approval from Fujian Provincial Hospital’s Institutional Review Board. All pneumonia patients were diagnosed with community-acquired pneumonia, and written informed consent was obtained from all participants.

Data collection

Demographic and clinical parameters were systematically recorded, including: Basic characteristics: sex, age (years), Systolic/diastolic blood pressure; Hematological indices: white blood cell count (WBC), neutrophil percentage (NE%), blood urea nitrogen (BUN).

Sample collection and laboratory analysis

Fasting venous blood (2 mL) was collected in EDTA tubes from the outpatients and newly admitted patients before clinical treatment, then centrifuged (3,000 × g, 10 min) within 30 min post-collection. Plasma aliquots underwent immediate analysis or cryopreservation (-20 °C) for batch testing. HBP, PCT, CRP, and SAA levels were measured in parallel using a Beckman Coulter AU5800 system (Jiubio Biotechnology reagents, Beijing Strong Biotechnologies, Inc, Beijing, China) following manufacturer protocols.

Research method

Intergroup comparisons of HBP/PCT/CRP/SAA levels (BPG vs. VPG vs. NCG) and ROC analysis for individual/combined biomarker performance. The CURB-65 score system for community-acquired pneumonia (CAP) was applied to stratify enrolled bacterial and viral pneumonia patients into severity cohorts (Supplementary Table 1). This validated tool incorporates five dichotomous criteria: (1) age ≥ 65 years; (2) Confusion (disorientation or impaired consciousness); (3) Blood urea nitrogen (BUN) > 7 mmol/L (19 mg/dL); (4) rate ≥ 30 breaths/min; (5) systolic blood pressure < 90 mmHg or diastolic pressure ≤ 60 mmHg. Each criterion was scored 0 (absent) or 1 (present), yielding a maximum total of 5 points. Participants were subsequently categorized into low-risk (0–2 points) and high-risk (3–5 points) cohorts for comparative analysis of serum inflammatory biomarker profiles. Binary logistic regression with forest plot visualization was implemented to quantify associations between clinical parameters (gender, age, WBC, NE%, BUN) and the four inflammatory markers with pneumonia severity outcomes.

Statistical methods

Statistical analyses were performed using SPSS 24.0. Continuous variables were assessed for normality using the Shapiro-Wilk test. Variables with normal distribution were expressed as mean ± standard deviation and compared using independent t-tests (for two groups) or one-way ANOVA with post hoc Bonferroni correction (for multiple group comparisons). Non-normally distributed variables were presented as median (interquartile range) and analyzed using Mann-Whitney U tests (two groups) or Kruskal-Wallis tests (multiple groups). Categorical variables were described as frequency (percentage) and compared using χ² tests or Fisher’s exact test when expected cell counts were < 5. For diagnostic evaluation, receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance of HBP both alone and in combination with PCT, CRP, and SAA for bacterial pneumonia. Binary logistic regression and forest plots were used to analyze factors associated with severe pneumonia prediction. A P-value < 0.05 was considered statistically significant.

Results

Baseline clinical characteristics

Demographic characteristics including age and sex ratio were comparable across the three groups (P > 0.05). Significant intergroup variations emerged in biochemical markers, with BUN, WBC, NE% demonstrating statistically distinct profiles among the three cohorts (P < 0.05; Table 1).

Table 1.

Baseline characteristics of the study population [(X ± SD), (n%)]

Variable	BPG(N = 166)	VPG(N = 42)	NCG(N = 61)	X2	P value
Age(year)	48.7 ± 36.4	51.2 ± 28.8	45.6 ± 18.1	2.0	0.361
Gender(%)				1.37	0.54
Male	116 (69.9%)	26 (61.9%)	39 (63.9%)
Female	50 (30.1%)	16 (38.1%)	22 (36.1%)
BUN(mmol/L)	8.4 ± 6.6	9.0 ± 11.0	4.6 ± 1.5	15.4	< 0.001
WBC (x 10 9 /L)	10.2 ± 5.3	8.1 ± 3.7	6.7 ± 2.8	27.7	< 0.001
NE%	69.8 ± 20.1	57.3 ± 23.5	56.3 ± 10.6	31.3	< 0.001
HBP(ng/ml)	73.8 ± 74.2	29.0 ± 21.0	9.3 ± 4.6	109.3	< 0.001
PCT(ng/ml)	3.7 ± 11.7	1.3 ± 4.5	0.11 ± 0.05	79.1	< 0.001
SAA(mg/l)	134.8 ± 155.0	146.0 ± 169.0	3.9 ± 2.7	66.9	< 0.001
CRP(mg/dl)	4.9 ± 7.6	3.9 ± 5.1	0.12 ± 0.08	71.3	< 0.001

Comparative analysis of serum HBP and other inflammatory markers

Departures from normality in serum concentrations of HBP, PCT, SAA, and CRP necessitated nonparametric analyses for group comparisons. Mann-Whitney U tests revealed that both BPG (P < 0.001) and VPG (P < 0.001) demonstrated markedly elevated HBP levels compared to NCG. Parallel increases were observed for SAA and CRP in infection groups versus controls (P < 0.001). Notably, while PCT levels differentiated BPG from NCG (P < 0.001), no statistically discernible difference emerged between VPG and NCG (P = 0.47 ) (Fig. 1, Table 1).

Fig. 1.

Serum levels of four inflammatory markers in the three study groups. Figures A/B/C/D show the comparisons of serum levels of HBP, PCT, SAA and CRP in the bacterial pneumonia group, the viral pneumonia group and the normal control group, respectively. Note: BPG, Bacterial Pneumonia Group; VPG, Viral Pneumonia Group; NCG, normal control group. ns: There was no statistically significant comparison between the two groups

Diagnostic performance of HBP and inflammatory markers for bacterial/viral pneumonia

ROC analyses were conducted with BPG/VPG versus NCG. Biomarkers showed strong discriminative capacity across etiologies. For bacterial pneumonia: HBP achieved the highest diagnostic accuracy (AUC = 0.93, 95%CI 0.89–0.96), followed sequentially by PCT (0.87; 0.83–0.92), SAA (0.86; 0.82–0.91), and CRP (0.85; 0.80–0.90). Optimal thresholds with diagnostic metrics: HBP: 17.9 ng/mL (81.9% sensitivity/96.7% specificity); PCT: 0.18 ng/mL (78.3%/ 95.8%); SAA: 10.4 mg/L (75.9%/98.3%); CRP: 0.35 mg/dL (75.3%/98.4%) ( Fig. 2A). The combined four-marker panel attained maximal efficacy (AUC = 0.96, 0.93–0.99; 91.0% sensitivity, 98.4% specificity), though all combinatorial approaches demonstrated equivalent performance (P > 0.05; Table 2). For viral pneumonia: Biomarker performance hierarchy emerged as: HBP (0.87; 0.79–0.95) > PCT (0.86; 0.78–0.94) > CRP (0.82; 0.72–0.92) > SAA (0.81; 0.71–0.93). Threshold optimization revealed: HBP: 17.7 ng/mL (69.1%/95.1%); PCT: 0.17 ng/mL (78.6%/91.8%); SAA: 15.4 mg/L (76.2%/100%); CRP: 0.49 mg/dL (64.3%/100%) (Fig. 2B). The HBP + PCT + CRP triad showed peak discriminative power (AUC 0.94, 95%CI: 0.87–1.00; 90.5% sensitivity, 95.1% specificity), with no statistically significant differences among combination models (Table 3).

Fig. 2.

ROC curves for the diagnosis of early pneumonia infection by the individual detection of four inflammatory markers. Figures A/B respectively show the ROC curves of serum HBP, PCT, SAA and CRP for the diagnosis of bacterial pneumonia and viral pneumonia. AUC, area under the ROC curve.

Table 2.

Diagnostic performance of combined detection of HBP, PCT, SAA and CRP for bacterial pneumonia

Combined biomarkers	Sensibility(%)	Specificity(%)	AUC(95%CI)
HBP + PCT	89.8	95.1	0.95(0.93–0.98)
HBP + SAA	95.1	88.6	0.94(0.91–0.97)
HBP + CRP	87.4	98.4	0.95(0.93–0.98)
HBP + PCT + SAA	90.4	98.4	0.95(0.93–0.98)
HBP + PCT + CRP	89.2	98.4	0.95(0.93–0.98)
HBP + SAA + CRP	90.4	98.4	0.95(0.93–0.98)
HBP + PCT + SAA + CRP	91.0	98.4	0.96(0.93–0.99)

Table 3.

Diagnostic performance of combined detection of HBP, PCT, SAA and CRP for viral pneumonia

Combined biomarkers	Sensibility(%)	Specificity(%)	AUC(95%CI)
HBP + PCT	85.7	95.1	0.92(0.84–0.99)
HBP + SAA	83.3	96.7	0.91(0.83–0.98)
HBP + CRP	85.7	95.1	0.93(0.86–0.99)
HBP + PCT + SAA	83.3	98.4	0.92(0.85–0.99)
HBP + PCT + CRP	90.5	95.1	0.94(0.87-1.00)
HBP + SAA + CRP	85.7	95.1	0.93(0.86–0.99)
HBP + PCT + SAA + CRP	90.5	95.1	0.93(0.87-1.00)

CURB-65 score stratified prognostic modeling

Binary logistic regression analyses stratified by CURB-65 score severity demonstrated distinct biomarker-risk associations. Bacterial Pneumonia Progression Model: High-risk patients (n = 71) exhibited markedly elevated HBP levels [99.5 (79.3-171.3) ng/mL] versus low-risk counterparts (n = 95) [23.7 (14.8–33.0) ng/mL] (P = 0.006). Consistent escalation patterns emerged for PCT, SAA, and CRP (P < 0.001). Univariate analysis identified age, WBC, NE%, HBP, PCT, and CRP as progression correlates (P < 0.05) (Fig. 3A, Table 4). Multivariate analysis confirmed HBP as an independent prognostic factor for High-risk patients (OR = 1.052, P < 0.001; Fig. 3B, Table 4). Viral Pneumonia Trajectory Analysis:

Fig. 3.

Univariate and multivariate binary logistic regression forest plots for predicting severe bacterial pneumonia. Figures A and B are respectively the forest plots of single-factor and multi-factor binary logistic regression

Table 4.

Univariate and multivariate logistic regression analysis of CRB scores in patients with bacterial pneumonia

Factors	Univariate analysis				Multivariate analysis
	P	HR	95% CI (Lower/Upper)		P	HR	95% CI (Lower/Upper)
Male vs. Female	0.895	0.956	0.489	1.870
Age	< 0.001	1.015	1.006	1.024	0.221	1.012	0.993	1.030
WBC	0.043	1.065	1.002	1.131	0.098	1.093	0.984	1.214
NE (%)	0.003	1.026	1.009	1.044	0.069	0.963	0.926	1.003
BUN	0.053	1.049	0.999	1.101
HBP	< 0.001	1.052	1.036	1.068	< 0.01	1.052	1.035	1.070
PCT	0.027	1.075	1.008	1.146	0.194	1.053	0.974	1.137
SAA	0.078	1.002	1.000	1.004
CRP	0.019	1.061	1.010	1.115	0.986	0.999	0.918	1.088

No significant HBP differential was observed between high-risk (n = 13) [31.2 (13.3–58.1) ng/mL] and low-risk groups (n = 29) [21.4 (14.4–33.7)ng/mL]. Notably, while PCT and SAA showed comparable levels, CRP demonstrated risk-stratified elevation [18.7 (12.4–29.1) mg/dL] vs. [12.3 (8.5–16.9) mg/dL] ( P = 0.045). Only age and NE% showed univariate associations (Table 5, Fig. 4A). No parameters retained statistical significance in multivariate analysis (P > 0.05) (Table 5, Fig. 4B).

Table 5.

Univariate and multivariate logistic regression analysis of CRB scores in patients with viral pneumonia

Factors	Univariate analysis				Multivariate analysis
	P	HR	95% CI (Lower/Upper)		P	HR	95% CI (Lower/Upper)
Male vs. Female	0.055	0.195	0.037	1.038
Age	0.019	1.040	1.007	1.075	0.075	1.033	0.997	1.070
WBC	0.210	1.121	0.938	1.341
NE (%)	0.034	1.035	1.002	1.068	0.069	0.963	0.926	1.003
BUN	0.323	1.031	0.970	1.096
HBP	0.137	1.025	0.992	1.058
PCT	0.494	0.800	0.422	1.517
SAA	0.277	1.002	0.998	1.006
CRP	0.238	1.079	0.950	1.224

Fig. 4.

Univariate and multivariate binary logistic regression forest plots for predicting severe viral pneumonia. A and B are respectively the forest plots of single-factor and multi-factor binary logistic regression

Discussion

Pneumonia remains a global health priority, particularly affecting immunocompromised populations through delayed diagnosis and therapeutic challenges [8]. Therefore, early and accurate diagnosis followed by targeted treatment is crucial. The clinical dilemma stems from overlapping presentations across bacterial/viral etiologies and current diagnostic limitations [9–11]. This often compels clinicians to empirically administer both antibiotics and antivirals before a definitive diagnosis is made, ensuring prompt treatment but also contributing to the emergence of drug-resistant strains [8]. Our investigation identifies heparin-binding protein (HBP) as a pivotal biomarker addressing these critical gaps.

As a neutrophil-derived acute-phase reactant, HBP is released during neutrophil aggregation and exhibits chemotactic properties along with inflammatory regulatory functions [12, 13]. Our cohort analysis (BPG = 166, VPG = 42, NCG = 61) revealed striking intergroup variations: BPG exhibited 5.4-fold higher median HBP levels than NCG (44.1 vs. 8.2 ng/mL), with VPG demonstrating intermediate elevation (25.2 ng/mL). These findings align with Halldorsdottir’s mechanistic model where HBP activates monocyte-mediated inflammatory cascades [14], though our ROC analyses extend clinical relevance - showing superior bacterial discrimination (AUC = 0.93 vs. viral AUC = 0.87). Notably, our optimized HBP cutoffs (BPG:17.9ng/mL, 81.9%/96.7%; VPG:17.7ng/mL, 69.1%/95.1%) outperformed prior neonatal reports [15], potentially reflecting improved assay standardization. While traditional markers (PCT/CRP/SAA) maintained diagnostic competence, HBP’s neutrophil-specific origin likely explains its bacterial predilection. The observed viral-associated HBP elevation (2.9-fold vs. controls) may stem from secondary neutrophilic inflammation, as evidenced by concomitant WBC/NE% increases. Consistent with precision medicine imperatives, our multi-analyte analysis demonstrated incremental diagnostic gains. However, viral pneumonia diagnostics proved more refractory, with optimal triad combinations (HBP + PCT + CRP) suggesting fundamental pathophysiological distinctions requiring alternative biomarker strategies. CURB-65 score-stratified modeling revealed HBP’s unique prognostic capacity. In bacterial progression, HBP emerged as the sole independent severity predictor (OR = 1.052, P < 0.001), potentially through sustained endothelial activation and cytokine amplification [16, 17]. Viral trajectories showed divergent mechanisms, with no inflammatory markers retaining prognostic significance - highlighting etiological specificity in host-response pathways.

The plasma levels of the four inflammatory markers in this study were all measured using the Beckman Coulter automatic biochemical analyzer detection system, with a sensitivity of ng/ml and detection time less than half an hour for serum HBP detection, ensuring accurate detection. Additionally, all testing reagents were provided by Beijing Strong Biotechnologies, Inc., at a low cost. Large-scale combined testing can be conducted for individuals with fever or suspected pneumonia, improving the early detection rate of pneumonia and accurately assess the severity of the condition in pneumonia patients.

Study Limitations: Firstly, the study is a single-center retrospective study with a very limited number of subjects included (especially viral pneumonia), lacking independent external validation; secondly, subjects with incomplete or erroneous medical records will affect the accuracy of statistical analysis; thirdly, there is selection bias for patients with mixed infections or those who have been treated with antibiotics or antiviral drugs before admission but not recorded in the medical records; fourthly, the CURB-65 score-stratified -stratified modeling is susceptible to the influence of patient age, comorbidities, etc., while the assessment of consciousness disorders, respiratory rate, and blood pressure is susceptible to the influence of doctors’ assessment methods. Finally, the study only included bacterial and viral pneumonia cases, without considering the correlation between HBP and infections such as fungi and Mycoplasma pneumoniae.

In summary, this evidence positions serum HBP as a dual-purpose biomarker for bacterial pneumonia management - enabling early diagnosis (AUC > 0.9) and predicting disease progression (OR = 1.052). When integrated with conventional markers, HBP enhances diagnostic precision while offering therapeutic monitoring potential. In the future, we will conduct multi-regional and multi-center prospective studies, carrying out comprehensive and rigorous external validation to assess the diagnostic and prognostic performance of serum HBP for infectious pneumonia in a more systematic and accurate manner. Simultaneously, a diverse range and a larger number of cases will be included, scientifically acquire patient follow-up data, and precisely stratify the severity of pneumonia to further verify the prognostic evaluation performance of the four inflammatory markers in different types of infectious pneumonia.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Conceptualization: Pengju Cao, Songgao Zhang, Jiangang Huang, Wanru Dai; Writing—original draft preparation: Pengju Cao and Songgao Zhang; Writing—review and editing: Jiangang Huang and Wanru Dai; Visualization: Pengju Cao, Songgao Zhang, Jiangang Huang, Wanru Dai.; Supervision: Wanru Dai; Project administration: Wanru Dai; Funding acquisition: Wanru Dai. All authors have read and agreed to the published version of the manuscript.

Funding

This research fund by Ministry of Education Industry-Academia Collaboration Initiative, (NO:231107010102120).

Data availability

All the data are contained in this article.

Declarations

Institutional Review Board Statement and Informed Consent Statement

This study adhered to the tenets of the Declaration of Helsinki and was approved by the Fujian Provincial Hospital Affiliated to Fuzhou University ((Fuzhou, China; No.K2025-09-004). Informed consent was not required due to the nature of the study.

Consent for publication

All authors have approved the publication.

Informed consent

was obtained from the subject involved in this study.

Competing interests

The authors declare no competing interests.