UNASSIGNED: Asthma is associated with persistent airway inflammation, and numerous studies have investigated inflammatory markers causing asthma. However, the systemic immune-inflammation index (SII) is a novel inflammatory marker, with scarce research reporting on the correlation between SII and asthma and asthma-related events.
UNASSIGNED: The purpose of this study was to assess the relationship between SII and asthma and asthma-related events (including whether asthma is still present, asthma flare-ups in the past year, and asthma duration) using data from the National Health and Nutrition Examination Survey (NHANES).
UNASSIGNED: The study utilized data from NHANES 2009-2018 with asthma and asthma-related events as dependent variables and SII as an independent variable. Multifactor logistic regression was employed to assess the correlation between the independent and dependent variables. Smoothed curve-fitting and threshold effect analyses were also carried out to determine the presence of non-linear relationships. Subgroup analyses were then performed to identify sensitive populations.
UNASSIGNED: In this study, we analyzed data from 40,664 participants to elucidate the association between SII and asthma and its related events. The study findings indicated a positive correlation between SII and asthma, with a relative risk increase of 0.03% for asthma incidence per one percentage point increase in SII (OR = 1.0003, 95% CI: 1.0002, 1.0004). For individuals still suffering from asthma, higher SII also indicated a positive correlation with ongoing asthma (OR = 1.0004, 95% CI: 1.0001, 1.0006). However, no statistically significant association was observed between SII and asthma exacerbations within the following year (OR = 1.0001, p > 0.05). When considering the duration of asthma, we observed a slight positive correlation with SII (β = 0.0017, 95% CI: 0.0005, 0.0029). Additionally, a significant non-linear relationship between SII and asthma duration emerged at the threshold of 504.3 (β = 0.0031, 95% CI: 0.0014-0.0048, p = 0.0003). Subgroup analysis revealed a stronger correlation between SII and asthma in male patients (OR = 1.0004, 95% CI: 1.0002-1.0006) and individuals aged 60 and above (OR = 1.0005, 95% CI: 1.0003-1.0007). No gender differences were observed for individuals still suffering from asthma. However, the positive correlation between SII and asthma was more pronounced in participants under 20 years old (OR = 1.0004 in Model 3, 95% CI: 1.0002-1.0006). Specific sensitive subgroups for asthma exacerbation recurrence within the past year were not identified. When considering asthma duration, we observed this association to be significant in male individuals (β = 0.0031 in Model 3, 95% CI: 0.0014-0.0049) as well as individuals aged 20 to 39 (β = 0.0023 in Model 3, 95% CI: 0.0005-0.0040).
UNASSIGNED: Our study concludes that SII is positively correlated with the persistence of asthma yet has limited predictive power for asthma recurrence. This highlights SII\'s potential as a tool for assessing asthma risk and formulating targeted management strategies.

BACKGROUND: To evaluate the overall survival (OS) and construct a nomogram to predict the OS of patients with penile squamous cell carcinoma (PSCC).
METHODS: This retrospective study analyzed data of patients with PSCC from the First Affiliated Hospital of Soochow University between 2012 and 2022. R software was used to explore factors influencing OS in PSCC. Kaplan-Meier method and log-rank test were employed for OS estimation. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify these factors. A nomogram was created to identify the independent prognostic factors. The model was evaluated by concordance index, receiver operating characteristic (ROC) curves, and calibration plots.
RESULTS: A total of 159 patients with T1/T2 PSCC were included in the analysis. Patients with T2/N2 stage, older age, larger tumor size, high preoperative systemic immune-inflammation index (SII), and poor preoperative nutrition had a higher incidence of poor OS. Age, T/N stage, tumor size, and SII were identified as independent prognostic indicators. A prognostic nomogram was formulated, and its predictive accuracy for estimating OS in PSCC patients was validated through ROC curves and calibration plots.
CONCLUSIONS: The nomograms, based on age, T/N stage, tumor size, and high preoperative SII, provide a valuable tool for predicting 1-, 2-, and 3-year OS in patients with T1/T2 PSCC without distant metastases.

Introduction Lung cancer is the leading cause of oncological deaths worldwide. Various combined inflammatory indexes, such as the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) have shown associations with pretreatment survival prognosis in patients suffering of lung cancer with or without brain metastases. This study aimed to compare the average values of NLR, PLR, LMR, and SII in healthy patients, patients with lung cancer without any other metastases, and patients with lung cancer and brain metastases. Materials and methods In this prospective study, we have divided the patients into three groups: Group 1 included patients diagnosed with lung cancer and one or more brain metastases of lung cancer origin, Group 2 included patients diagnosed with lung cancer without known metastases, and Group 3 was the control group which included healthy subjects. Preoperative complete blood counts were extracted for all included patients and we calculated the values of SII, NLR, PLR, and LMR for each individual patient in each group. The next step was to calculate the average values of SII, NLR, PLR, and LMR for each group of patients and to identify the differences between groups. Results A total number of 228 patients were enrolled in the study. Group 1 included 67 patients with average values of SII = 2020.98, NLR = 7.25, PLR = 199.46, and LMR = 2.97. Group 2 included 88 patients with average values of SII = 1638.01, NLR = 4.58, PLR = 188.42, and LMR = 3.43. Group 3 included 73 subjects with the following average values of the inflammatory indexes: SII = 577.41, NLR = 2.34, PLR = 117.84, and LMR = 3.56. Conclusion We observed statistically significant differences in SII, NLR, and PLR among the three groups of patients, suggesting their potential role as prognostic markers. Furthermore, our analysis revealed significant correlations between inflammatory markers within lung cancer patients, highlighting their involvement in tumor microenvironment modulation. Our findings demonstrate an escalation in SII, NLR, and PLR values as the disease progresses. These parameters of inflammation and immune status are readily and cost-effectively, and repeatedly assessable in routine clinical practice.

UNASSIGNED: Although immunotherapy has revolutionized the treatment landscape of lung cancer and improved the prognosis of this malignancy, many patients with lung cancer still are not able to benefit from it because of many different reasons. The expression of programmed death ligand-1 (PD-L1) in tumor cells has been approved for the prediction of immunotherapy efficacy; however, its clinical application has been limited by the invasiveness of PD-L1 determination and the heterogeneity of tumor cells. As a promising technology, radiomics has made significant progress in the diagnosis and treatment of lung cancer. Thus, we constructed a noninvasive predictive model which based on radiomics to predict the immunotherapy efficacy of lung caner patients.
UNASSIGNED: Data of 82 patients with stage IIIa/IVb NSCLC who received immunotherapy at the First Affiliated Hospital of Soochow University from December 2019 to January 2023 were retrospectively collected. These patients were followed up for durable clinical benefit (DCB), as defined by whether progression-free survival (PFS) reached 12 months. The least absolute shrinkage and selection operator (LASSO) algorithm was used to screen for the radiomic features in the training set, and a radiomics score (Rad-score) was calculated. The clinical baseline data were analyzed, and the peripheral blood inflammation indices were calculated. Univariate and multivariate analyses were performed to identify the applicable indices, which were combined with the Rad-score to create a comprehensive forecasting model (CFM) and nomograms. Internal validation was performed in the validation set.
UNASSIGNED: Up to the last follow-up time, 48 of 82 patients had a PFS of more than 12 months. The area under the receiver operating characteristic (ROC) curve (AUC) of the Rad-score was 0.858 and 0.812, respectively, in the training set and validation set. A systemic immune-inflammation index (SII) score of <500.88 after two cycles of immunotherapy was a protective factor for PFS >12 months [odds ratio (OR) 0.054; P=0.003]. The CFM had an AUC of 0.930 and 0.922, respectively, in the training and validation sets. The calibration curves and decision curve analysis (DCA) demonstrated the reliability and clinical applicability of the model, respectively.
UNASSIGNED: The radiomics model performed well in predicting whether patients with locally advanced or metastatic NSCLC can achieve DCB after receiving immunotherapy. The CFM had good predictive performance and reliability.

UNASSIGNED: Bronchiectasis is a common respiratory disease with neutrophilic inflammation being the predominant pathophysiology. Systemic immune-inflammation index (SII) is a simple and readily available biomarker being studied in various conditions including asthma, chronic obstructive pulmonary disease, and interstitial lung disease, but not in bronchiectasis. We aim to investigate the prognostic role of SII in bronchiectasis with this study.
UNASSIGNED: A retrospective cohort study in Chinese patients with non-cystic fibrosis (CF) bronchiectasis was conducted in Hong Kong, to investigate the association between baseline SII and of hospitalized bronchiectasis exacerbation risk over 4.5 years of follow-up, as well as correlating with disease severity in bronchiectasis. The baseline SII in 2018 was calculated based on stable-state complete blood count.
UNASSIGNED: Among 473 Chinese patients with non-CF bronchiectasis were recruited, 94 of the patients had hospitalized bronchiectasis exacerbation during the follow-up period. Higher SII was associated with increased hospitalized bronchiectasis exacerbation risks with adjusted odds ratio (aOR) of 1.001 [95% confidence interval (CI): 1.000-1.001, P=0.003] for 1 unit (cells/µL) increase in SII count and aOR of 1.403 (95% CI: 1.126-1.748, P=0.003) for 1 standard deviation (SD) increase in SII. SII was found to have significant negative association with baseline forced expiratory volume in the first second (FEV1) (in litre and percentage predicted), forced vital capacity (FVC) in percentage; and significant positive correlation with the extent of bronchiectasis and baseline neutrophil to lymphocyte ratio (NLR).
UNASSIGNED: SII could serve as biomarker to predict the risks of hospitalized exacerbation in bronchiectasis patients, as well as correlating with the disease severity.

BACKGROUND: We aimed to determine whether systemic immune-inflammation index (SII) combined with prealbumin can provide better predictive power for postoperative pneumonia in patients undergoing lung resection surgery.
METHODS: We identified eligible patients undergoing lung resection surgery at the Affiliated Hospital of Nantong University from March 2021 to March 2022. Demographic characteristics, clinical data, and laboratory information were collected and reviewed from the electronic medical records of the patients. To test the effect of the combined detection of SII and prealbumin, we made an equation using logistic regression analysis. The receiver operating characteristic curve (ROC) was plotted to evaluate the predictive powers, sensitivity, and specificity of prealbumin, SII, and SII combined with prealbumin. Decision curve analysis (DCA) was used to determine the clinical validity and net benefit of different methods of detection.
RESULTS: Totally 386 eligible patients were included with a median age of 62.0 years (IQR: 55.0, 68.0), and 57 (14.8%) patients presented with postoperative pneumonia within 7 days after surgery. The multivariate regression analysis showed that preoperative SII as continuous variable was associated with an increased risk of postoperative pneumonia (OR: 1.38, 95% CI: 1.19-2.83, P = 0.011), whereas the prealbumin as continuous variable remained as an independent protective predictor of postoperative pneumonia in the adjusted analysis (OR: 0.80, 95% CI: 0.37-0.89, P = 0.023). Compared to SII or prealbumin, the combined detection of preoperative SII and prealbumin showed a higher predictive power with area under curve of 0.79 (95% CI: 0.71-0.86, P < 0.05 for all). Additionally, DCA indicated that the combined detection was superior over preoperative SII or prealbumin alone in clinical validity and net benefit.
CONCLUSIONS: Both preoperative SII and prealbumin are independent influencing factors for postoperative pneumonia after lung resection surgery. The combined detection of preoperative SII and prealbumin can significantly improve prediction capability to identify potential postoperative pneumonia-susceptible patients, facilitating early interventions to improve postoperative quality of life for surgical lung resection patients.

The disease severity of psoriasis is mainly assessed subjectively via  psoriasis area and severity index (PASI) and body surface area (BSA), while an optimal measure of cutaneous response, may overlook systemic inflammation in psoriasis patients. The neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), monocyte to high density lipoprotein ratio (MHR), and systemic immune-inflammation index (SII) exhibit notable associations with the inflammation severity in multiple diseases. The aim of this retrospective study was to explore the associations between inflammatory parameters and the skin lesions\' severity of psoriasis. After analysis, we found that patients with psoriasis had higher NLR, MLR, PLR, MHR, and SII levels compared to the control group. At baseline, the parameters of NLR (r = 0.124, P = 0.003), MLR (r = 0.153, P < 0.001), MHR (r = 0.217, P < 0.001) and SII (r = 0.141, P = 0.001) had a positive correlation with PASI in psoriasis patients. At the same time, we analyzed the patients who received different systemic therapy. We observed a significant decrease in NLR, PLR, MLR, and SII in psoriasis patients after treatment. Notably, TNF-α inhibitors and IL-17A inhibitors subgroups showed a more significant reduction than IL-23/IL-12/23 inhibitors and MTX medication. Additionally, we found the change of NLR (r = 0.194, P < 0.001), PLR (r = 0.104, P = 0.014), MLR (r = 0.191, P < 0.001), MHR (r = 0.106, P = 0.012), and SII (r = 0.228, P < 0.001) had a positive correlation with the change of PASI in psoriasis patients. In conclusion, this study suggests that NLR, MLR, and SII may serve as useful biomarkers for assessing systemic inflammation extent and disease severity in psoriasis patients.

The aim of this study was to establish whether multiple blood parameters might predict an early treatment response to intravitreal bevacizumab injections in patients with diabetic macular edema (DME). Seventy-eight patients with non-proliferative diabetic retinopathy (NPDR) and DME were included. The treatment response was evaluated with central macular thickness decrease and best corrected visual acuity increase one month after the last bevacizumab injection. Parameters of interest were the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), vitamin D, and apolipoprotein B to A-I ratio (ApoB/ApoA-I). The NLR (2.03 ± 0.70 vs. 2.80 ± 1.08; p < 0.001), MLR (0.23 ± 0.06 vs. 0.28 ± 0.10; p = 0.011), PLR (107.4 ± 37.3 vs. 135.8 ± 58.0; p = 0.013), and SII (445.3 ± 166.3 vs. 675.3 ± 334.0; p < 0.001) were significantly different between responder and non-responder groups. Receiver operator characteristics analysis showed the NLR (AUC 0.778; 95% CI 0.669-0.864), PLR (AUC 0.628; 95% CI 0.511-0.735), MLR (AUC 0.653; 95% CI 0.536-0.757), and SII (AUC 0.709; 95% CI 0.595-0.806) could be predictors of response to bevacizumab in patients with DME and NPDR. Patients with severe NPDR had a significantly higher ApoB/ApoA-I ratio (0.70 (0.57-0.87) vs. 0.61 (0.49-0.72), p = 0.049) and lower vitamin D (52.45 (43.10-70.60) ng/mL vs. 40.05 (25.95-55.30) ng/mL, p = 0.025). Alterations in the NLR, PLR, MLR, and SII seem to provide prognostic information regarding the response to bevacizumab in patients with DME, whilst vitamin D deficiency and the ApoB/ApoA-I ratio could contribute to better staging.

UNASSIGNED: The clinical challenge of differentiating suspected tuberculosis with positive T-SPOT.TB results persist. This study aims to investigate the utility of the Systemic Immune-Inflammation Index (SII), Fibrinogen, and T-SPOT.TB in distinguishing between active pulmonary tuberculosis (PTB) and non-tuberculous lung diseases.
UNASSIGNED: A retrospective analysis included 1,327 cases of active PTB with positive T-SPOT.TB results and 703 cases of non-tuberculous lung diseases from May 2016 to December 2020 at Meizhou People\'s Hospital. These were designated as the case group and the control group, respectively. The detection indicators of T-SPOT.TB: Early Secreted Antigenic Target 6 (ESAT-6), Culture Filtrate Protein 10 (CFP-10), as well as SII and Fibrinogen levels-were compared and analyzed for association and joint diagnostic value between the two groups.
UNASSIGNED: The case group showed higher values of ESAT-6, CFP-10, SII, and Fibrinogen compared to the control group (all p < 0.001). In the case group, SII and Fibrinogen did not correlate with ESAT-6 and CFP-10 (∣rs∣ all < 0.3) but were positively correlated with C-reactive protein (CRP; rs all > 0.3). SII and Fibrinogen values in smear-positive pulmonary tuberculosis were higher than in smear-negative cases (all p < 0.05). The optimal diagnostic thresholds for ESAT-6, CFP-10, SII, and Fibrinogen in differentiating between active PTB and non-tuberculous lung diseases were 21.50 SFCs/106 PBMC, 22.50 SFCs/106 PBMC, 2128.32, and 5.02 g/L, respectively. Regression logistic analysis showed that ESAT-6 < 21.5 (OR: 1.637, 95% CI: 1.311-2.043, p < 0.001), CFP-10 < 22.5 (OR: 3.918, 95% CI: 3.138-4.892, p = 0.025), SII < 2128.32 (OR: 0.763, 95% CI: 0.603-0.967, p < 0.001), and FIB < 5.02 (OR: 2.287, 95% CI: 1.865-2.806, p < 0.001) were independent risk factors for active PTB. The specificity for ESAT-6 + CFP-10, ESAT-6 + CFP-10 + SII, ESAT-6 + CFP-10 + FIB, and ESAT-6 + CFP-10 + SII + FIB was 82.5%, 83.2%, 95.8%, and 80.1%, respectively, while sensitivity was 52.6%, 53.0%, 55.8%, and 44.7%, and positive predictive values were 85.0%, 85.6%, 84.1%, and 89.6%, respectively.
UNASSIGNED: SII and Fibrinogen are positively correlated with the degree of tuberculosis inflammation and the bacterial load of Mycobacterium tuberculosis. The combined detection of SII, Fibrinogen, and T-SPOT.TB is significant in distinguishing between active PTB with positive T-SPOT.TB results and non-tuberculous lung diseases.

UNASSIGNED: Less research has linked the Systemic Immune Inflammatory Index (SII) with post-stroke depression (PSD). This study aims to look at any potential connections between SII and PSD.
UNASSIGNED: The National Health and Nutrition Examination Survey (NHANES), conducted in a population that embodied complete SII and stroke data from 2005 to 2020, was used to perform the current cross-sectional survey. A fitted smoothed curve was used to depict the nonlinear link between SII and PSD, and multiple linear regression analysis demonstrated a positive correlation between SII and PSD.
UNASSIGNED: Multiple linear regression analysis showed that SII and PSD were markedly related [1.11(1.05, 1.17)]. Interaction tests showed that the association between SII and PSD was not statistically different between strata, and age, sex, BMI, income poverty ratio, education level, smoking status, diabetes mellitus, coronary heart disease, and heart failure did not have a significant effect on this positive association (p > 0.05 for interaction). In addition, a nonlinear association between SII and PSD was found using a two-stage linear regression model.
UNASSIGNED: The results of our research support the existence of a significant positive correlation between SII levels and PSD. Further prospective trials are required to comprehend SII, which is for the PSD thoroughly.