Novel inflammatory biomarkers and disease severity in hospitalized children with Mycoplasma pneumoniae pneumonia: a retrospective study

Introduction

Mycoplasma pneumoniae (M. pneumoniae) can cause both upper and lower respiratory tract infections, accounting for up to 40% of community-acquired pneumonia cases in children >5 years old (1,2). M. pneumoniae exhibits a cyclical epidemic, typically occurring every 3–7 years and lasting for 2 years (3). Since 2023, the epidemiology of M. pneumoniae pneumonia (MPP) has shifted notably, with a resurgence of cases globally following the relaxation of non-pharmaceutical interventions, imposing substantial socioeconomic and public health burdens (4-6). While MPP is usually mild, a subset of cases progresses to severe or refractory pneumonia, developing various extrapulmonary complications affecting multiple systems including renal, neurological, and hematological systems, which can even become life-threatening (7,8). Early identification of severe MPP is critical, as the optimal treatment window is within 5–10 days of fever onset. However, atypical early symptoms and lack of clear clinical imaging indicators often delay diagnosis (9). Therefore, identifying clinical or laboratory indicators associated with disease severity may help clinicians improve risk stratification and guide clinical decision-making in pediatric patients with MPP.

Accumulating evidence suggests that the pathogenesis of severe MPP is closely related to dysregulated host immune responses rather than direct cytotoxic effects of the pathogen itself (10-12). M. pneumoniae infection dysregulates innate and adaptive immunity, resulting in exaggerated pulmonary and systemic inflammation (12). Subsequently, the resulting cytokine and chemokine release amplifies inflammation via a cascade effect. This disrupts the balance of peripheral blood neutrophils (NEUs), lymphocytes (LYMs), and platelets (PLTs), ultimately leading to multi-system damage involving both pulmonary and extrapulmonary organs (13). Previous studies have reported that the severity of pulmonary lesions in MPP is inversely correlated with LYM counts and monocyte (MON) proportions (14,15). Severe cases are also more likely to develop both pulmonary and extrapulmonary complications, suggesting that immune-mediated injury plays an important role in disease progression (16).

In this context, systemic inflammatory markers derived from routine blood tests have attracted increasing attention. Several inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), integrate information from different immune cell populations and may reflect the balance between inflammatory activation and immune regulation. Previous studies have investigated these indices as potential biomarkers in various inflammatory conditions, including cancer, sepsis, coronavirus disease 2019 (COVID-19) (17,18). Therefore, the present study aimed to evaluate several novel inflammatory indices derived from routine blood parameters, including NLR, monocyte-to-lymphocyte ratio (MLR), PLR, SII, and systemic inflammation response index (SIRI), in hospitalized children with MPP. By comparing clinical and laboratory characteristics between severe and non-severe cases, we sought to explore the association between these inflammatory markers and disease severity, and to assess their potential value in assisting clinical risk stratification. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0323/rc).

Methods

Study design and setting

We conducted a retrospective study in the Department of Pediatrics at The First Affiliated Hospital of Naval Medical University, a tertiary hospital located in Shanghai, China. Since May 2023, cases of M. pneumoniae infection increased and demonstrated an epidemic trend in China. Thus, all children aged <18 years who fulfilled the diagnostic criteria for MPP from July 2023 to June 2024 were included in this study. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Review Committee of The First Affiliated Hospital of Naval Medical University (No. CHEC2024-321). Due to the retrospective nature of the study and the use of anonymized clinical data, the requirement for informed consent was waived by the Ethics Review Committee.

Data collection

We collected demographic characteristics including age, gender, body mass index (BMI) and hospital stay which were sourced from the medical electronic database in this hospital. Venous whole blood samples of all study participants were collected within the first 24 hours after being admitted to the hospital. White blood cell (WBC) count, NEU count, LYM count, MON count, PLT count, lactate dehydrogenase (LDH), alanine aminotransferase (ALT), aspartate aminotransferase (AST), were recorded. Novel inflammatory markers were calculated as follows: NLR = NEU count/LYM count, PLR = PLT count/LYM count, and MLR = MON count/LYM count, SII = (PLT count × NEU count)/LYM count, and SIRI = (NEU count × MON count)/LYM count.

Study population

A total of 886 patients with a diagnosis of MPP aged <18 years were admitted to the hospital between July 2023 and June 2024. The study flowchart is presented in Figure 1. Among the 886 cases included in the study, 403 were male and 483 were female, indicating a relatively balanced gender distribution across the cohort. The median age of the 886 children with MPP was 7 (4.7, 9.1) years old. The particle agglutination (PA) method was used for laboratory determination of serum M. pneumoniae-specific IgM antibodies. A single serum antibody titer >1:160 or a fourfold or greater increase in M. pneumoniae antibody titers of two paired sera, and/or positive detection of M. pneumoniae-DNA or M. pneumoniae-RNA by nucleic acid amplification test from the nasopharyngeal aspirate were used as the standard for recent M. pneumoniae infection. In addition, patients accompanied by chest radiography-proven pneumonia, with acute respiratory symptoms (cough, tachypnea, difficulty breathing, etc.), were diagnosed as MPP. According to the National Guideline for the Diagnosis and Treatment of MPP in Children (2023 edition) (19), severe MPP was defined as meeting any of the following criteria: (I) persistent high fever (>39 ℃) for 5 days or fever for 7 days; (II) one or more symptoms of gasping, shortness of breath, dyspnea, chest pain, hemoptysis; (III) external pulmonary complications occurred, such as meningoencephalitis, ascending (i.e., Guillain-Barré) paralysis, myopericarditis, erythema multiforme, autoimmune hemolytic anemia, hemophagocytic syndrome, or disseminated intravascular coagulation, but not meeting the criteria for critical illness; (IV) peripheral oxygen saturation (SpO₂) ≤93% on room air in the resting state; (V) imaging showing moderate to large pleural effusion, large area of pulmonary consolidation, plastic bronchitis, pulmonary embolism, necrotizing pneumonia; (VI) clinical symptoms worsening gradually, and imaging showing that the lesion range progressed to more than 50% within 24 to 48 hours. Exclusion criteria: (I) patients with bacteria, virus or other pathogens; (II) recently received immunosuppressive therapy; (III) history of severe cardiovascular disease, malignant tumor, or immune system disease; (IV) patients with incomplete clinical data.

Figure 1 Patient selection flow chart. MPP, Mycoplasma pneumoniae pneumonia; PCR, polymerase chain reaction.

Statistical analysis

Statistical analyses were performed with SPSS (V.26.0, IBM, Armonk, New York). Categorical variables were presented as numbers and frequencies. Normally distributed variables were presented as means ± standard deviation (SD), while non-normally distributed variables are reported as median [interquartile range (IQR)]. Pearson’s chi-squared test was used to compare categorical variables between groups. Continuous variables with a normal distribution were compared using t-tests, whereas non-normally distributed variables were compared using non-parametric tests, including Mann-Whitney U test and Kruskal-Wallis test. Binary logistic regression was employed to identify risk factors associated with severe MPP in children. Variables with P<0.05 in univariate analyses were entered into a multivariate logistic regression model. Model fit was assessed using the Hosmer-Lemeshow test (P>0.05 indicating adequate fit). Receiver operating characteristic (ROC) curves were used to evaluate the discriminatory performance of these biomarkers in distinguishing severe from non-severe MPP. Area under the curve (AUC) values between 0.5 and 0.7 were considered to indicate limited discriminatory ability, whereas values ≥0.7 were considered acceptable for discrimination. All tests were two-sided, with statistical significance set at P<0.05.

Results

Clinical characteristics

From July 2023 to June 2024, 886 children with MPP were enrolled in this study. Among them, 196 were classified as severe MPP cases. There was no significant difference in sex distribution between the severe and non-severe groups. The median age in the severe group was higher than in the non-severe group [7.5 (5.5, 9.5) vs. 6.8 (4.5, 9.0) years, P=0.001]. The severe group exhibited a longer durations of fever and length of hospital stay than non-severe group (6.33±2.47 vs. 4.6±2.47 days, P<0.001; 5.6±1.99 vs. 4.93±2.32 days, P<0.001, respectively).

Laboratory findings

Regarding the inflammatory ratios, patients with severe MPP had significantly higher levels of NEU, NLR, PLR, SII than those in the non-severe groups (4.65±2.24 vs. 4.18±2.21×10⁹/L, P=0.01; 2.24±1.28 vs. 1.8±1.05, P<0.001; 154.31±74.41 vs. 130.47±55.44, P<0.001; 725.29±509.81 vs. 541.31±344.44, P=0.001; 291.23±66.06 vs. 279.58±69.87, P=0.02, respectively) in Table 1. In contrast, compared with the non-severe MPP group, the LYM, SIRI were at a lower level in the severe group compared with the severe MPP groups (2.24±1.27 vs. 2.66±1.25×10⁹/L, P=0.002; 1.4±1.09 vs. 1.52±5.34, P<0.01, respectively), in Table 1. Meanwhile, the levels of MLR were not statistically different between the two groups.

Logistic regression analysis of severe MPP

Multivariable logistic regression analysis was performed to explore factors associated with the severity of MPP. In the univariate logistic regression analysis, fever duration, length of hospital stays, and SII were significantly associated with severe MPP (all P<0.05). Variables with statistical significance were subsequently entered into a multivariable logistic regression model. The results showed that fever duration (P<0.001), SII (P<0.001), and length of hospital stay (P=0.002) remained significantly associated with severe MPP, as shown in Table 2. However, it should be noted that length of hospital stay is more appropriately considered a clinical consequence reflecting disease severity rather than a true predictive factor.

ROC curve analysis of SII and clinical variables for identifying severe MPP

ROC curve analysis was performed to evaluate the ability of inflammatory indices and clinical variables to discriminate severe from non-severe MPP. The AUC for SII alone was 0.599 [95% confidence interval (CI): 0.554–0.645] (Table 3 and Figure 2), indicating a limited discriminatory ability. When SII was combined with fever duration, the AUC increased to 0.705 (95% CI: 0.663–0.747) (Table 3 and Figure 3), suggesting a modest improvement in discriminatory performance. At the optimal cutoff value determined by the Youden index, the combined model demonstrated a sensitivity of 70.4%, specificity of 68.5%, positive predictive value of 38.8%, negative predictive value of 89.1%, and an overall accuracy of 68.9%. These findings indicate that the integration of laboratory inflammatory markers and clinical characteristics may provide additional information for identifying children with severe disease.

Figure 2 ROC curve analysis of SII, fever duration, hospital day for the prediction of severe MPP. MPP, Mycoplasma pneumoniae pneumonia; ROC, receiver operating characteristic; SII, systemic immune inflammation index.

Figure 3 ROC curve analysis of SII + fever duration for the prediction of severe MPP. MPP, Mycoplasma pneumoniae pneumonia; ROC, receiver operating characteristic; SII, systemic immune inflammation index.

Discussion

Main findings

In this retrospective study involving 866 hospitalized children with MPP, we investigated the clinical characteristics and inflammatory indices associated with severe MPP in children. We found that children with severe MPP showed significantly higher levels of NLR, PLR, and SII (all P<0.001), compared with the non-severe group. In addition, children with severe MPP were generally older and experienced a longer duration of fever (Table 1). Multivariate logistic regression analysis showed that SII and fever duration were independently associated with severe disease (Table 2). Furthermore, in ROC analysis, SII demonstrated limited discriminatory ability (Figure 2). The combination of SII and fever duration showed the highest AUC among the evaluated indices and showed modest improvement in distinguishing severe from non-severe cases (Figure 3). These findings suggest that systemic inflammatory responses may play an important role in the progression and severity of MPP in children. However, it should also be noted that fever duration may introduce incorporation bias, as prolonged fever is included among the diagnostic criteria for severe MPP according to current pediatric guidelines (19). Therefore, its association with disease severity should be interpreted cautiously.

Systemic inflammatory indices and immune dysregulation in severe MPP

MPP is generally a mild and self-limiting illness, however, a subset of pediatric patients develops severe or refractory pneumonia. The pathogenesis of severe MPP is increasingly considered to be associated with dysregulated host immune responses rather than direct pathogen-induced cytotoxicity alone. Excessive inflammatory activation and immune-mediated injury may contribute to pulmonary damage and disease progression (10-13). M. pneumoniae infection can induce exaggerated cytokine and chemokine responses, resulting in systemic inflammatory activation and immune dysregulation (12,13). Therefore, inflammatory indices derived from routine blood counts may partly reflect the balance between systemic inflammation and immune regulation in children with severe MPP.

Systemic inflammatory indices derived from routine blood tests have been increasingly used as markers reflecting the balance between inflammation and immune regulation. These indices are typically calculated of peripheral blood cell counts, including NEUs, LYMs, and PLTs, each of which plays a distinct role in the inflammatory process. NEUs and LYMs serve as primary cellular mediators in the initial hyperdynamic phase of infection and act as a role in modulating adaptive immunity. A characteristic pattern of elevated NEUs and lymphocytopenia is associated with a diverse array of conditions. Various pathological conditions, including stroke, infection, burns, and major surgery, may induce systemic inflammatory response syndrome (20). The inverse relationship between NEU and LYM counts reflects a multifactorial physiological response, regulated through a complex interplay of immunological, neuroendocrine, and humoral mechanisms (21,22). Thrombocytosis is associated with an intensified inflammatory response, resulting from alterations in systemic microcirculation, enhanced vascular permeability, PLT activation, and extensive PLT aggregation (23).

Therefore, composite inflammatory indices such as the NLR, PLR, and SII, which integrate information from multiple blood cell types, may better reflect the systemic inflammatory status. These characteristics may explain why such indices have been increasingly investigated as potential markers of severity in various infectious and inflammatory conditions, and may provide additional information for assessing inflammation status, disease progression, and risk stratification. For example, previous studies have reported that NLR is associated with the severity of community-acquired pneumonia (24) and can serve as a predictor of poor prognosis in patients with MPP (25), and the SII shows value in predicting necrotizing pneumonia (26). In addition, one study showed that an increased PLT count presented as an independent risk factor for predicting the severity of MPP (27). Moreover, PLTs participate in inflammatory responses. Under stimulation by M. pneumoniae, activated PLTs and released chemokines may contribute to immune-mediated injury (28). The SII and SIRI have demonstrated predictive utility in M. pneumoniae infection (29).

Combining inflammatory indices with clinical features for severity assessment in MPP

Although NEU, NLR, and PLR levels were significantly higher in the severe MPP group than in the non-severe group, whereas LY and SIRI levels were lower, multivariate analysis showed that none of these indices remained independently associated with MPP. We found that SII was independently associated with severe MPP. SII integrates NEU, LYM, and PLT counts, which may reflect the balance of the patient’s inflammatory, immune, and thrombotic pathways (17). Elevated SII levels indicate heightened inflammatory activity or compromised immune function (30). Severe MPP is often characterized by an exaggerated inflammatory response and immune dysregulation, which may lead to increased NEU and PLT counts as well as relative lymphopenia, resulting in elevated SII levels. In addition to inflammatory indices, several clinical characteristics were also significantly associated with disease severity in our cohort. In our study, patients in the severe group were older and had a longer duration of fever than those in the non-severe group. Fever duration was also independently associated with severe disease, which may reflect prolonged inflammatory activity and more severe disease progression. Previous study on refractory MPP has shown that persistent fever and radiological progression after antibiotic therapy are commonly associated with ongoing inflammatory activity and more severe pulmonary involvement (31). A recent study also reported that patients with severe MPP complicated by pleural effusion or necrotizing pneumonia had a longer duration of fever (32). Both univariate and multivariate analyses consistently demonstrated that fever duration was significantly associated with severe MPP. In addition, the median age in the severe group was 7.5 (5.5, 9.5) years, suggesting an increased susceptibility to severe disease among older children. This finding is consistent with previous study showing that children older than 5 years are more susceptible to M. pneumoniae infection and tend to develop more severe clinical manifestations (33). The severity of pneumonia may also reflect the intensity of the host’s immune reaction, and older children, who have more mature immune systems, may be more prone to developing severe pulmonary lesions following infection.

Given that fever duration was independently associated with severe disease in our multivariate analysis, we further explored whether combining this clinical parameter with SII could improve discriminatory performance. Although SII alone demonstrated only limited discriminatory ability in ROC analysis, the combination of SII and fever duration showed a modest improvement in distinguishing severe from non-severe disease (Figure 3). Therefore, integrating laboratory inflammatory markers with clinical information may provide additional support for identifying children who require closer monitoring or more intensive management. In particular, the relatively high negative predictive value observed in the combined model may suggest a potential role in identifying children at lower risk for severe disease, although further validation is required. This finding also highlights an important limitation of relying on a single inflammatory biomarker to characterize a complex disease process. Disease severity in MPP is influenced by multiple factors, including host immune responses, pathogen characteristics, age-related immune variability, and treatment timing. Therefore, inflammatory indices such as SII may be more useful when interpreted alongside clinical parameters rather than as standalone predictors. Moreover, future prospective multicenter studies and investigations of dynamic inflammatory changes during disease progression are warranted to further validate the clinical relevance of these biomarkers. In addition, although NLR, NEU, PLR, and SIRI showed significant differences between the severe and non-severe groups in univariate analysis, they were not independently associated with severe disease in multivariate analysis. One possible explanation is that several inflammatory indices are derived from overlapping hematological parameters and therefore exhibit substantial intercorrelations, as demonstrated in the correlation analysis (Table S1). These findings suggest that the inflammatory indices evaluated in this study may reflect partially overlapping aspects of systemic inflammatory responses. In addition, differences in study populations, disease severity definitions, and timing of laboratory measurements across studies may also contribute to inconsistent findings. Therefore, further prospective studies are required before definitive conclusions regarding the clinical application of these indices can be drawn.

Limitations

There are some limitations in this study. Firstly, this was a single-center retrospective study including only hospitalized children with MPP. Therefore, future multicenter studies with larger sample sizes are needed to validate these findings. In addition, the classification of severe MPP was based on the 2023 Chinese national guideline criteria. Different severity definitions used in other studies or regions may affect the generalizability and comparability of the findings. Furthermore, the imbalance between severe and non-severe cases in this cohort may have increased statistical power and contributed to statistically significant differences with relatively modest effect sizes. Therefore, the clinical relevance of these findings should be interpreted cautiously. Secondly, inflammatory markers were evaluated at a single time point. Future studies could investigate the dynamic changes of inflammatory indices during the disease course, which may provide additional insights into the pathophysiology and progression of severe MPP. Thirdly, children with respiratory co-infections were excluded from this study. Although this approach helped reduce confounding factors affecting inflammatory markers, it may limit the applicability of the findings in routine clinical practice where co-infections are relatively common. Finally, the role of these inflammatory biomarkers in monitoring the therapeutic efficacy of M. pneumoniae infection could also be explored in the future.

Conclusions

This retrospective study explored the association between several inflammatory indices and disease severity in children with MPP. The results showed that SII and prolonged fever duration were independently associated with severe disease, while a longer hospital stay likely reflected the greater clinical burden of severe infection. ROC analysis suggested that SII alone had limited discriminatory ability, whereas the combination of SII and fever duration showed modest performance in distinguishing severe from non-severe cases. Given that SII can be easily calculated from routine blood tests, it may serve as a simple and accessible indicator reflecting systemic inflammatory responses in pediatric MPP. When considered together with clinical characteristics such as fever duration, it may provide additional information for identifying children who may require closer monitoring. However, these findings should be interpreted cautiously due to the retrospective design of the study and the limited-to-modest discriminatory performance observed. Future prospective multicenter studies and investigations of dynamic inflammatory changes during disease progression are warranted to further validate the clinical relevance of these biomarkers.

Acknowledgments

The authors would like to thank Haihui Tong for assistance with English language editing and manuscript revision.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0323/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0323/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0323/prf

Funding: This work was supported in part by Shanghai Municipal Hospital Pediatric Internal Medicine Alliance (Nos. SHDC22024307-A and SHDC22024307-B).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0323/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 Review Committee of The First Affiliated Hospital of Naval Medical University (No. CHEC2024-321). Due to the retrospective nature of the study and the use of anonymized clinical data, the requirement for informed consent was waived by the Ethics Review Committee.

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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