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.

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.

UNASSIGNED: Colorectal cancer (CRC) ranks highly in malignant tumor incidence and mortality rates, severely affecting human health. The predictive value of the systemic immune-inflammation index (SII) in CRC prognosis is gaining attention, but there is limited research on the combined preoperative and postoperative SII. This study aims to explore the prognostic value of combined SII on disease-free survival (DFS) in patients undergoing radical surgery for rectal cancer.
UNASSIGNED: We enrolled 292 patients with rectal cancer who underwent radical resection at the Affiliated Hospital of Xuzhou Medical University from May 2018 to September 2020, along with regular follow-ups to document the DFS. Patients\' complete blood cell counts were assessed before surgery and between 21-56 days postoperatively. Calculating preoperative and postoperative SII, patients were categorized into four groups based on the optimal cutoff values: (I) low-low group (preoperative SII <449.325 and postoperative SII <568.13); (II) high-low group (preoperative SII ≥449.325 and postoperative SII <568.13); (III) low-high group (preoperative SII <449.325 and postoperative SII ≥568.13); and (IV) high-high group (preoperative SII ≥449.325 and postoperative SII ≥568.13). The receiver operating characteristic (ROC) curve analysis evaluated the prediction efficacy of preoperative, postoperative, and combined SII. Kaplan-Meier analysis generated DFS curves, and Cox regression analysis determined prognostic factors.
UNASSIGNED: With a median follow-up of 41 months, 65.4% (191/292) patients reached DFS. The clinical pathological features between the four groups are balanced and comparable (P>0.05). The area under the ROC curve for preoperative, postoperative, and combined SII was 0.668 [95% confidence interval (CI): 0.6-0.737], 0.696 (95%CI: 0.63-0.763), and 0.741 (95% CI: 0.681-0.802), respectively. After adjusting for confounding factors such as adjuvant therapy, differentiation, vascular invasion, neural invasion, tumor-node-metastasis (TNM) stage, carcinoembryonic antigen (CEA), and carbohydrate antigen 19-9 (CA19-9), significant differences were observed between the high-low group [hazard ratio (HR) =2.403; 95% CI: 1.255-4.602; P=0.008], low-high group (HR =5.058; 95% CI: 2.389-10.71; P<0.001), and high-high group (HR =6.214; 95% CI: 3.474-11.115; P<0.001) compared to the low-low group, with higher risks of adverse outcomes.
UNASSIGNED: Combined SII has better predictive efficacy than monitoring preoperative or postoperative SII alone in rectal cancer patients undergoing radical surgery.

UNASSIGNED: This study aimed to determine whether SII on different days of admission is associated with severity and 180-day functional outcomes after basal ganglia ICH.
UNASSIGNED: In this retrospective study, data on baseline CT imaging characteristics, mRS, hematoma volume, and laboratory variables were included. The SII and NLR, LMR, and PLR were calculated from laboratory data collected on admission day, day 1, and days 5-7. Both univariate and multivariable logistic regression analyses were used to assess the association between the SII and the outcome. The receiver operating characteristic (ROC) analysis and area under the curve (AUC) were also used to evaluate the ability of the SII to predict outcomes.
UNASSIGNED: A total of 245 patients were enrolled in the study. On different days, the NLR, PLR, and SII were significantly lower in patients with favorable outcomes than in those with poor outcomes, and the volume of hemorrhage was positively correlated with the SII. These parameters were associated with outcomes in the univariate logistic regression. In the adjusted analyses, the SII and PLR were independent predictors of basal ganglia ICH outcomes. ROC analysis revealed that the SII showed a stronger ability to predict the 6-month outcomes of patients after basal ganglia ICH than the PLR on different days (AUC = 0.642, 0.804, 0.827 vs. 0.592, 0.725, 0.757; all P < 0.001).
UNASSIGNED: The SII independently and strongly predicts the outcome of basal ganglia ICH. A high SII was associated with poor 6-month outcomes in patients with basal ganglia ICH.

UNASSIGNED: The Spinnaker study evaluated survival outcomes and prognostic factors in patients with advanced non-small-cell lung cancer receiving first-line chemoimmunotherapy in the real world. This sub-analysis assessed the immunotherapy-related adverse effects (irAEs) seen in this cohort, their impact on overall survival (OS) and progression-free survival (PFS), and related clinical factors.
UNASSIGNED: The Spinnaker study was a retrospective multicentre observational cohort study of patients treated with first-line pembrolizumab plus platinum-based chemotherapy in six United Kingdom and one Swiss oncology centres. Data were collected on patient characteristics, survival outcomes, frequency and severity of irAEs, and peripheral immune-inflammatory blood markers, including the neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII).
UNASSIGNED: A total of 308 patients were included; 132 (43%) experienced any grade irAE, 100 (32%) Grade 1-2, and 49 (16%) Grade 3-4 irAEs. The median OS in patients with any grade irAES was significantly longer (17.5 months [95% CI, 13.4-21.6 months]) than those without (10.1 months [95% CI, 8.3-12.0 months]) (p<0.001), either if Grade 1-2 (p=0.003) or Grade 3-4 irAEs (p=0.042). The median PFS in patients with any grade irAEs was significantly longer (10.1 months [95% CI, 9.0-11.2 months]) than those without (6.1 months [95% CI, 5.2-7.1 months]) (p<0.001), either if Grade 1-2 (p=0.011) or Grade 3-4 irAEs (p=0.036). A higher rate of irAEs of any grade and specifically Grade 1-2 irAEs correlated with NLR <4 (p=0.013 and p=0.018), SII <1,440 (p=0.029 ad p=0.039), response to treatment (p=0.001 and p=0.034), a higher rate of treatment discontinuation (p<0.00001 and p=0.041), and the NHS-Lung prognostic classes (p=0.002 and p=0.008).
UNASSIGNED: These results confirm survival outcome benefits in patients with irAEs and suggest a higher likelihood of Grade 1-2 irAEs in patients with lower NLR or SII values or according to the NHS-Lung score.

UNASSIGNED: The prognosis of patients who can achieve a complete response after neoadjuvant chemotherapy could be significantly improved. Thus, accurately predicting the efficacy of neoadjuvant chemotherapy is of great clinical significance. Currently, previous indicators such as neutrophil to lymphocyte ratio was poor in predicting the efficacy and prognosis of neoadjuvant chemotherapy in human epidermal growth factor receptor 2 (HER2) positive breast cancer patients.
UNASSIGNED: The data of 172 HER2 positive breast cancer patients admitted to the Nuclear 215 Hospital of Shaanxi Province from January 2015 to January 2017 were retrospectively collected. After neoadjuvant chemotherapy, the patients were divided into the complete response group (n=70) and the non-complete response group (n=102). The clinical characteristics and systemic immune-inflammation index (SII) levels of the two groups were compared. The patients were followed-up for 5 years post-surgery to observe whether recurrence or metastasis occurred after the operation by clinic visit combined with telephone calls.
UNASSIGNED: The SII of the complete response group was significantly lower than that of the non-complete response group (587.43±175.97 vs. 821.82±231.58; P=0.000). The SII was valuable in predicting which HER2 positive breast cancer patients would fail to achieve a pathological complete response, and the area under the curve (AUC) was 0.773 [95% confidence interval (CI): 0.705-0.804; P=0.000]. A SII >755.10 was an adverse factor for HER2 positive breast cancer patients achieving a pathological complete response after neoadjuvant chemotherapy [P=0.000; relative risk (RR): 0.172 (95% CI: 0.082-0.358)]. The SII level was valuable in predicting recurrence within 5 years of surgery, and had an AUC of 0.828 (95% CI: 0.757-0.900; P=0.000). A SII >755.10 was a risk factor for recurrence within 5 years of surgery [P=0.001; RR: 4.945 (95% CI: 1.949-12.544)]. The SII level was valuable in predicting metastasis within 5 years of surgery, and had an AUC of 0.837 (95% CI: 0.756-0.917; P=0.000). A SII >755.10 was a risk factor for metastasis within 5 years of surgery [P=0.014, RR: 4.553 (95% CI: 1.362-15.220)].
UNASSIGNED: The SII was associated with the prognosis and efficacy of neoadjuvant chemotherapy in HER2 positive breast cancer patients.

UNASSIGNED: The increase in the number of thyroid cancer cases in recent years has increased not only the medical burden but also the potential for overtreatment. Therefore, it is crucial to distinguish papillary thyroid cancer from benign thyroid nodules before surgery when treating thyroid nodules.
UNASSIGNED: The patients were divided into two groups: 117 patients made up the validation cohort and 414 patients made up the primary cohort. As a result of the primary cohort, a preoperative prediction model was developed, which was then validated externally in the validation cohort. Preoperative thyrotropin (thyroid stimulating hormone, TSH), systemic immune-inflammation index (SII), lymphocyte-to-monocyte ratio (LMR), and ultrasonographic features were recorded in both groups.
UNASSIGNED: As predictors for the model, the preoperative blood levels of TSH, SII, LMR, echogenicity, margin, calcification, composition, taller-than-wide, and age were chosen. This was the regression equation: Y = -0.070 × (age) + 1.511 × (echogenicity) + 1.664 × (margin) + 1.003 × (calcification) + 0.939 × (composition) + 2.964 × (tall than wide) + 0.305 × (TSH) + 0.558 × (SII) - 1.271 × (LMR) + 0.327. Papillary thyroid carcinoma (PTC) was predicted positively with values of Y ≥0.808. The prediction model\'s accuracy, sensitivity, and specificity were 88.2%, 85.1%, and 94.9%, respectively. The area under the receiver operating characteristic (ROC) curve was 0.961. The model\'s external validation produced satisfactory results with accuracy, sensitivity, and specificity of 85.5%, 90.9%, and 75.5%, respectively.
UNASSIGNED: Using the preoperative TSH, SII, LMR, and ultrasonographic characteristics, a straightforward and accurate preoperative prediction model for PTC has been developed and validated. The preoperative assessment of PTC in clinical application is enhanced by this approach.

OBJECTIVE: Diet quality is a critical modifiable factor related to health, including the risk of cardiometabolic complications. Rather than assessing the intake of individual food items, it is more meaningful to examine overall dietary patterns. This study investigated the adherence to common dietary indices and their association with serum/metabolic parameters of disease risk.
METHODS: Dietary intakes of the general adult population (n = 1404, 25-79 years) were assessed by a validated food-frequency questionnaire (174 items). The French ANSES-Ciqual food composition database was used to compute nutrient intakes. Seven indicators were calculated to investigate participants\' diet quality: the Alternative Healthy Eating Index (AHEI), Dietary Approaches to Stop Hypertension Score (DASH-S), Mediterranean Diet Score (MDS), Diet Quality Index-International (DQI-I), Dietary Inflammatory Index (DII), Dietary Antioxidant Index (DAI), and Naturally Nutrient-Rich Score (NNRS). Various serum/metabolic parameters were used in the validity and association analyses, including markers of inflammation, blood glucose, and blood lipid status.
RESULTS: Following linear regression models adjusted for confounders, the DASH-S was significantly associated with most metabolic parameters (14, e.g., inversely with blood pressure, triglycerides, urinary sodium, uric acid, and positively with serum vitamin D), followed by the DQI-I (13, e.g., total cholesterol, apo-A/B, uric acid, and blood pressure) and the AHEI (11, e.g., apo-A, uric acid, serum vitamin D, diastolic blood pressure and vascular age).
CONCLUSIONS: Food-group-based indices, including DASH-S, DQI-I, and AHEI, were good predictors for serum/metabolic parameters, while nutrient-based indices, such as the DAI or NNRS, were less related to biological markers and, thus, less suitable to reflect diet quality in a general population.

BACKGROUND: Gastric cancer with only peritoneal lavage cytology (GC-CY1) is a special type of gastric cancer, which is defined as stage IV. The pre-treatment systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) are representative blood indexes of systemic inflammatory response and nutritional status. However, the clinical significance of combined detection of these two indexes is still unclear. This study aims to evaluate the clinical value of the new score system by combining SII and PNI (SII-PNI score) as a predictor of efficacy and prognosis after neoadjuvant intraperitoneal and systemic (NIPS) paclitaxel combined with Apatinib conversion therapy for GC-CY1 patients.
METHODS: We registered a prospective clinical study involving 36 GC-CY1 patients from April 2018 to August 2019 (NCT03718624). All patients underwent re-laparoscopic exploration after treatment. According to free cancer cells (FCCs) status, these patients were divided into FCCs group and non-FCCs group. The SII-PNI score ranged from 0 to 2 as follows: score of 2, high SII (≥512.1) and low PNI (≤52.9); score of 1, either high SII or low PNI; score of 0, no high SII nor low PNI.
RESULTS: All patients underwent re-laparoscopic exploration after 3 cycles of NIPS paclitaxel and Apatinib conversion therapy. Among them, 28 cases (77.78%) were in non-FCCs group, and 8 cases (22.22%) were in FCCs group. The SII-PNI score of non-FCCs patients was significantly lower than that of FCCs patients (p=0.041). The prognosis of patients with high SII-PNI score was significantly worse than that of patients with low SII-PNI score (p<0.001). Multivariate analysis showed that SII-PNI score was an independent prognostic factor for predicting overall survival and progression-free survival (p=0.001, 0.002).
CONCLUSIONS: Pretreatment SII-PNI score is an important predictor for the efficacy of GC-CY1 patients after NIPS paclitaxel combined with Apatinib conversion therapy, which can help to identify high-risk groups and predict prognosis.

BACKGROUND: Systemic immune-inflammation index (SII) is significantly associated with poor survival in variety of cancers. However, SII has not yet been investigated in patients with newly diagnosed metastatic nasopharyngeal carcinoma (mNPC). Thus, our aim is to explore the role of SII in metastatic Nasopharyngeal Carcinoma.
METHODS: Two hundred and forty-three patients with newly diagnosed mNPC were retrospectively enrolled. The Kaplan-Meier analysis and Cox regression analysis was performed to evaluate the prognostic value of SII in overall survival (OS) and progression-free survival (PFS). Heterogeneity of factors was balanced by using propensity score-matched (PSM) analysis (1:1 for high SII versus low SII).
RESULTS: Kaplan-Meier analysis showed that patients with high SII were associated with poor median OS (18.0 vs. 36.0 m, P<0.001) and PFS (10.0 vs. 22.0 m, P<0.001) in mNPC. The Cox regression analysis suggested that high SII was a prognostic factor for OS (HR 1.75, 95% CI: 1.22-2.52, P=0.001) and PFS (HR 1.69, 95% CI: 1.22-2.35, P=0.002). PSM analysis still confirmed that SII was an independent marker for OS (HR 1.86, 95% CI: 1.22-2.83, P=0.004) and PFS (HR 1.84, 95% CI: 1.23-2.77, P=0.003).
CONCLUSIONS: SII is an independent prognostic biomarker for poor OS and PFS in patients with newly diagnosed mNPC and might be a promising tool for guiding treatment strategy decisions.