The systemic immune-inflammation index-based model is an effective biomarker on predicting central lymph node metastasis in clinically nodal-negative papillary thyroid carcinoma

The Association of Pretreatment Systemic Immune Inflammatory Response Index (SII) and Neutrophil-to-Lymphocyte Ratio (NLR) with Lymph Node Metastasis in Patients with Papillary Thyroid Carcinoma

Objective

Immunoinflammatory response can participate in the development of cancer. To investigate the relationship between pretreatment systemic immune inflammatory response index (SII), systemic inflammatory response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and lymph node metastasis in patients with papillary thyroid carcinoma (PTC).

Methods

A retrospective analysis was performed on 547 PTC patients treated in Meizhou People's Hospital from January 2018 to December 2021. Clinicopathological data were collected, including gender, age, Hashimoto's thyroiditis, maximum tumor diameter, extra-membrane infiltration, disease stage, BRAF V600E mutation, pretreatment inflammatory index levels, and lymph node metastasis. The optimal cutoff values of SII, SIRI, NLR, PLR and LMR were calculated by receiver operating characteristic (ROC) curve, and the relationship between inflammatory indexes and other clinicopathological features and lymph node metastasis was analyzed.

Results

There were 303 (55.4%) PTC patients with lymph node metastasis. The levels of SII, SIRI, NLR, and PLR in patients with lymph node metastasis were significantly higher than those in patients without lymph node metastasis, while the levels of LMR were significantly lower than those in patients without lymph node metastasis (all p<0.05). When lymph node metastasis was taken as the endpoint, the critical value of SII was 625.375, the SIRI cutoff value was 0.705, the NLR cutoff value was 1.915 (all area under the ROC curve >0.6). The results of regression logistic analysis showed that age <55 years old (OR: 1.626, 95% CI: 1.009-2.623, p=0.046), maximum tumor diameter >1cm (OR: 2.681, 95% CI: 1.819-3.952, p<0.001), BRAF V600E mutation (OR: 2.709, 95% CI: 1.542-4.759, p=0.001), SII positive (≥625.375/<625.375, OR: 2.663, 95% CI: 1.560-4.546, p<0.001), and NLR positive (≥1.915/<1.915, OR: 1.808, 95% CI: 1.118-2.923, p=0.016) were independent risk factors for lymph node metastasis of PTC.

Conclusion

Age <55 years old, maximum tumor diameter >1cm, BRAF V600E mutation, SII positive, and NLR positive were independent risk factors for lymph node metastasis in PTC.

Association between blood inflammatory indicators and prognosis of papillary thyroid carcinoma: a narrative review

Background and Objective

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer, accounting for up to 85-90% of cases, with the best overall prognosis and mostly inert tumors. However, some tumors are aggressive, causing metastasis, recurrence, and other bad outcomes. Preoperative inflammation indices, such as lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII) in peripheral blood, have recently gained attention as nonspecific markers of inflammatory response in thyroid. In this study, we reviewed the interactions between preoperative inflammatory factors and outcomes in patients with PTC.

Methods

This is a narrative review. We searched for English articles published between January 2014 and December 2023 on PubMed and Web of Science to identify how do these blood indicators affect the prognosis of patients with papillary thyroid cancer.

Key Content and Findings

All retrievable indicators that have predictive significance for the prognosis of PTC were included, and the prognosis mainly included tumor-node-metastasis (TNM) staging, survival rate, recurrence, clinical and pathological risk factors such as lymph node metastasis (LNM), etc. From the general evidence, the prognostic predictive value of cell count alone was unknown, and low LMR was usually associated with poor prognosis, high NLR and high platelet-to-lymphocyte ratio (PLR) usually indicated poor prognosis.

Conclusions

These minimally invasive, low-cost, and easily obtainable blood indicators provide convenience for precise prognosis management of PTC patients, but many of the findings are conflicting and need to be validated by prospective studies that are more multi-sample, multi-centre and incorporate factors such as age that affect the immune response.

Clinical and molecular features of progressive papillary thyroid microcarcinoma

In recent decades, the prevalence of thyroid cancer has risen substantially, with papillary thyroid microcarcinoma (PTMC) constituting over 50% of cases. Although most PTMCs exhibit indolent growth and a favorable prognosis, some present an increased risk of recurrence and an unfavorable prognosis due to high-risk characteristics such as lymph node metastasis, extrathyroidal extension, and distant metastasis. The early identification of clinically progressing PTMC remains elusive. In this review, the authors summarize findings from PTMC progression-related literature, highlighting that factors such as larger tumor size, cervical lymph node metastasis, extrathyroidal extension, younger age, higher preoperative serum thyroid-stimulating hormone levels, family history, and obesity positively correlate with PTMC progression. The role of multifocality in promoting PTMC progression; however, remains contentious. Furthermore, recent studies have shed light on the impact of mutations, such as BRAF and TERT mutations, on PTMC progression. Researchers have identified several mRNAs, noncoding RNAs, and proteins associated with various features of PTMC progression. Some studies propose that peripheral and tumor tissue-infiltrating immune cells could serve as biomarkers for the clinical progression of PTMC. Collectively, these clinical and molecular features offer a rationale for the early detection and the development of precision theranostic strategies of clinically progressive PTMC.

Preoperative risk stratification for patients with ≤ 1 cm papillary thyroid carcinomas based on preoperative blood inflammatory markers: construction of a dynamic predictive model

Objective

The aim of this study was to investigate the relationships and predictive value of preoperative peripheral blood inflammatory markers as a means by which to assess risk for patients with ≤ 1 cm papillary thyroid carcinomas (PTCs). In addition, a preoperative risk stratification predictive model was constructed and validated.

Methods

Clinical and pathologic data, as well as preoperative blood specimens, were collected from patients who underwent initial thyroid cancer surgery at the Hangzhou First People's Hospital, from January 2014 to January 2023. Risk assessment was performed based on postoperative pathology according to the 2015 ATA guidelines for recurrence risk stratification. Using univariate analysis and multivariate logistic regression, we identified independent risk factors associated with risk stratification. A predictive model was established and its discriminative and calibration abilities were validated. An independent validation dataset was used to verify the model, and the model was deployed as an online calculator.

Results

A total of 1326 patients were included in the study, with 1047 cases (79.0%) classified as low risk and 279 cases (21.0%) classified as intermediate to high risk. The modeling group consisted of 981 cases, through univariate analysis and multivariate logistic regression analysis, preoperative blood Neutrophil/Lymphocyte Ratio (NLR), gender, tumor diameter, and multifocality were identified as independent risk factors that distinguished between low and intermediate to high risk patients with ≤ 1 cm PTCs. The clinical predictive model exhibited an AUC of 0.785, specificity of 70.6%, and sensitivity of 75.8%. For the independent validation group of 345 patients, the AUC was 0.813, specificity was 83.8%, and sensitivity was 70.4%. The calibration curve and clinical decision curve indicate that the model demonstrates excellent calibration performance.

Conclusion

A dynamic clinical predictive model based on preoperative blood NLR and clinical information for patients with ≤ 1 cm PTCs was established. The model is useful for preoperative risk assessment of patients with ≤ 1 cm PTCs.

Evaluation of the clinical and prognostic importance of infection parameters in thyroid cancers: A cross-sectional study

Thyroid cancers are among the most common endocrine cancers. An inflammation is associated with many stages of cancer. Therefore, in this study, we aimed to evaluate whether it has a prognostic significance inflammation marker. Neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, monocyte/lymphocyte ratio, systemic inflammation response, systemic immune-inflammation index, and neutrophils to lymphocytes and platelets ratio (N/LP) in patients diagnosed with thyroid cancer in the internal medicine outpatient clinic and operated between March 1, 2017 and May 1, 2022 were evaluated retrospectively. Three hundred forty patients were diagnosed with thyroid cancer; 275 (80.9%) of them were women and the mean age was 44.6 ± 13.5 years. Multifocality (P = .02) was significant in patients with invasion. High N/LP ratio (odds ratio: 1.4, 95% confidence interval: 1.0-2.0, p: 0.003) and high invasion (odds ratio: 0.2, 95% confidence interval: 0.1-0.4, P < .01) was found to be significant in patients with tumor size ≥2 cm. There is a relationship between multifocality and invasion, and the risk of invasion increases as the tumor size increases in thyroid cancer. The N/LP ratio was significant as it could be a new marker in showing the relationship between thyroid cancer and its prognosis. Further studies are needed in which the prognosis is followed up, longer-term, more comprehensive, and confounding factors are excluded.

The role of vascular endothelial growth factor in the development of papillary thyroid carcinoma in patients with lymphocytic thyroiditis

BACKGROUND

Vascular endothelial growth factor (VEGF) plays a pivotal role in the pathogenesis of autoimmune chronic inflammatory conditions and papillary thyroid carcinoma (PTC). We hypothesized that, as VEGF expression is increased both in PTC and in lymphocytic thyroiditis (LT), it may stimulate the development of PTC in patients with LT. To evaluate this, we examined both tumor and adjacent non-tumoral tissues of PTC patients with and without LT.

METHODS

A total of 50 patients with PTC (52.50±7.41 years) and 17 patients with nodular goiter (NG) (50.47±10.38 years) were included in the study. According to the presence of LT, patients with PTC were further divided into two groups. Immunohistochemical analyses of VEGF were conducted in all patients and for PTC patients, both tumor tissue and adjacent non-tumoral tissue were evaluated.

RESULTS

The scores for intensity of staining and percentage of labeled thyrocytes for VEGF were found to be significantly higher in the PTC patients than in the NG patients (P<0.001, P<0.001, respectively). The tumor tissue revealed similar scores for PTC patients with LT and without LT. However, the scores in adjacent non-tumoral tissue were higher in PTC patients with LT than in patients without LT (P=0.004, P=0.01, respectively).

CONCLUSIONS

To the best of our knowledge, our results are the first to demonstrate that the expression of VEGF in adjacent non-tumoral tissue were higher in PTC patients with LT than in those without, which shows a possible role of VEGF expression in the progression of PTC in the presence of LT.

Interpretable machine learning model based on the systemic inflammation response index and ultrasound features can predict central lymph node metastasis in cN0T1-T2 papillary thyroid carcinoma

Background

It is arguable whether individuals with T1-T2 papillary thyroid cancer (PTC) who have a clinically negative (cN0) diagnosis should undergo prophylactic central lymph node dissection (pCLND) on a routine basis. Many inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammatory index (SII), have been reported in PTC. However, the associations between the systemic inflammation response index (SIRI) and the risk of central lymph node metastasis (CLNM) remain unclear.

Methods

Retrospective research involving 1,394 individuals with cN0T1-T2 PTC was carried out, and the included patients were randomly allocated into training (70%) and testing (30%) subgroups. The preoperative inflammatory indices and ultrasound (US) features were used to train the models. To assess the forecasting factors as well as drawing nomograms, the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were utilized. Then eight interpretable models based on machine learning (ML) algorithms were constructed, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost). The performance of the models was evaluated by incorporating the area under the precision-recall curve (auPR) and the area under the receiver operating characteristic curve (auROC), as well as other conventional metrics. The interpretability of the optimum model was illustrated via the shapley additive explanations (SHAP) approach.

Results

Younger age, larger tumor size, capsular invasion, location (lower and isthmus), unclear margin, microcalcifications, color Doppler flow imaging (CDFI) blood flow, and higher SIRI (≥0.77) were independent positive predictors of CLNM, whereas female sex and Hashimoto thyroiditis were independent negative predictors, and nomograms were subsequently constructed. Taking into account both the auROC and auPR, the RF algorithm showed the best performance, and superiority to XGBoost, CatBoost and ANN. In addition, the role of key variables was visualized in the SHAP plot.

Conclusions

An interpretable ML model based on the SIRI and US features can be used to predict CLNM in individuals with cN0T1-T2 PTC.

Predictive value of systemic inflammatory markers for recurrence of papillary thyroid cancer

BACKGROUND

Papillary thyroid cancer (PTC) is the most common type of differentiated thyroid cancer. Early identification of patients at higher risk of recurrence may allow to improve relevant follow-up strategies and plan tailored treatment. Inflammation play an important role in the prognosis of cancer. We aimed to explore the predictive value of systemic inflammatory markers in PTC recurrence.

METHODS

We retrospectively enrolled 200 consecutive patients who were diagnosed with PTC and underwent curative resection at Lianyungang Oriental Hospital between January 2006 and December 2018. Clinicopathological characteristics, preoperative hematologic results were analyzed. The optimal cutoff values were calculated using x-tile software. The multivariate logistic regression and univariable survival analysis were performed by SPSS.

RESULTS

Multivariable analysis showed that lymph node metastases (odds ratio [OR] = 2.506, 95% confidence interval [CI]: 1.226-5.119, p = 0.012) and higher monocyte-to-lymphocyte ratio (MLR) (OR = 2.100, 95% CI: 1.042-4.233, p = 0.038) were independent prognostic factors for tumor recurrence. The cutoff value 0.22 of MLR significantly predicted recurrence at 53.3% sensitivity and 67.9% specificity. Patients with MLR ≥ 0.22 exhibited significantly poor long-term prognosis (46.8%) compared to the counterpart (76.8%, p = 0.0004).

CONCLUSIONS

Preoperative MLR significantly predicted PTC recurrence after curative resection, which may provide clues for early identification of patients at higher risk of PTC recurrence.

A COMPREHENSIVE EVALUATION OF HEMOGRAM-DERIVED INFLAMMATORY INDICES IN HASHIMOTO THYROIDITIS AND NON-IMMUNOGENIC HYPOTHYROIDISM

Objectives

The objective of this study was to evaluate the Systemic Inflammation Index (SII), Platelet to Lymphocyte Ratio (PLR), and Neutrophil to Lymphocyte Ratio (NLR) in HT and NIH, as well as their diagnostic value to predict the presence of inflammation.

Subjects and Methods

The study included 505 patients, including 190 healthy controls, 166 euthyroid Hashimoto's thyroiditis (HT), 91 hypothyroid HT, and 58 non- immunogenic hypothyroidism (NIH) patients. The records of the patients in each group were reviewed retrospectively.

Results

In terms of SII, there was a significant difference between the control and patient groups (p<0.001). PLR and NLR values were also found to be significantly higher in the patient group (p<0.001 and p=0.007, respectively). When euthyroid HT, hypothyroid HT, and NIH subgroups were compared to the control group, there was a significant difference in SII, PLR (for all p<0.001), but not in NLR (p=0.059). SII, PLR, and NLR were not different between the subgroups (p=0.595, p=0.861, and p=0.777, respectively).

Conclusions

It was found that the PLR, NLR, and SII indices were higher in Hashimoto's thyroiditis and non-immunogenic hypothyroidism. Of these indices, SII was the most powerful marker to predict the presence of inflammation.

Systemic immune-inflammation index: A new marker in differentiation of different thyroid diseases

Inflammation plays an important role in the pathogenesis of many cancer types and is associated with thyroid malignancy. The systemic immune-inflammation index (SII) is a new inflammation marker that can be calculated from routine complete blood count (CBC). This study investigated the association between SII, a marker derived from routine CBC, and different thyroid diseases. The objective was to determine if this simple inflammation marker can distinguish between benign and malignant thyroid diseases. The medical records of all patients who underwent surgical treatment for thyroid disease between January 2018 and January 2022 were systematically evaluated. The routine preoperative CBC parameters' demographic, clinical, and laboratory data were recorded. A total of 241 patients were included in the study, and the patients were grouped as having multinodular goiter (n = 125), lymphocytic thyroiditis (n = 44), and papillary thyroid carcinoma (PTC) (n = 73) according to pathological results. The SII was defined as the ratio of the total count of neutrophils × platelets divided by the lymphocyte count. Subgroup analysis of patients was performed according to the presence of follicular variant or thyroiditis, micro or macro carcinoma, or bilaterality of the tumor. The SII level was significantly higher in the PTC group than in the lymphocytic thyroiditis and multinodular goiter groups (P < .001). When we grouped the patients according to the presence of PTC as benign or malignant, the optimum cutoff point for SII level was found 654.13, with 73.8% sensitivity and 72.3% specificity from ROC analysis. In the subgroup analysis of patients with PTC, the SII level was similar according to the clinicopathological characteristics of the tumor. The differential diagnosis of thyroid diseases is important for patient management. We found that preoperative SII levels were significantly elevated in patients with PTC compared to those with benign thyroid disorders, and this simple marker can be used for the differentiation of benign and malignant thyroid disease.

Development and validation of the nomogram based on ultrasound, thyroid stimulating hormone, and inflammatory marker in papillary thyroid carcinoma: a case-control study

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Risk factors and prediction models of lymph node metastasis in papillary thyroid carcinoma based on clinical and imaging characteristics

BACKGROUND

Papillary thyroid carcinoma (PTC) commonly presents with lymph node metastasis, which may be associated with worsened prognosis. This study aimed to comprehensively evaluate the risk factors of lymph node metastasis in PTC based on preoperative clinical and imaging data and to construct a nomogram model to predict the risk of lymph node metastasis.

METHODS

A total of 989 patients with PTC were enrolled and randomly divided into training and validation cohorts in an 8:2 ratio. Independent risk factors for lymph node metastasis in PTC were analyzed using univariate and stepwise multivariate logistic regression. An importance analysis of independent risk factors affecting lymph node metastasis was performed according to the random forest method. Subsequently, a nomogram to predict lymph node metastasis was constructed, and the predictive effect of the nomogram was evaluated using receiver operating characteristic analysis and calibration curves.

RESULTS

Univariate regression analysis revealed that age, sex, body weight, systolic blood pressure, free triiodothyronine, nodule location, nodule number, Thyroid Imaging Reporting and Data System (TI-RADS) grade on color Doppler ultrasound, enlarged lymph node present on imaging, and nodule diameter could affect lymph node metastasis in PTC. Stepwise multivariate regression analysis showed that sex, age, enlarged lymph node present on imaging, nodule diameter, and color Doppler TI-RADS grade were independent risk factors for lymph node metastasis in PTC. Combining these five independent risk factors, a nomogram prediction model was constructed. The area under the curve (AUC) of the nomogram in the training and validation cohorts was 0.742 and 0.765, respectively, with a well-fitted calibration curve.

CONCLUSION

Our study showed that independent risk factors for lymph node metastasis in PTC were sex, age, enlarged lymph node present on imaging, nodule diameter, and color Doppler TI-RADS grade. The nomogram constructed based on these independent risk factors can better predict the risk of lymph node metastasis.

Preoperative strain ultrasound elastography can predict occult central cervical lymph node metastasis in papillary thyroid cancer: a single-center retrospective study

Objective

To determine whether preoperative ultrasound elastography can predict occult central cervical lymph node metastasis (CCLNM) in patients with papillary thyroid cancer.

Methods

This retrospective study included 541 papillary thyroid cancer patients with clinically negative lymph nodes prior to surgery between July 2019 and December 2021. Based on whether CCLNM was present on postoperative pathology, patients were categorized as CCLNM (+) or CCLNM (-). Preoperative clinical data, conventional ultrasound features, and ultrasound elastography indices were compared between the groups. Univariate and multivariate logistic regression analysis were performed to identify the independent predictors of occult CCLNM.

Results

A total of 36.60% (198/541) patients had confirmed CCLNM, while 63.40% (343/541) did not. Tumor location, bilaterality, multifocality, echogenicity, margin, shape, vascularity, capsule contact, extrathyroidal extension, aspect ratio, and shear wave elasticity parameters were comparable between the groups (all P > 0.05). Univariate analysis showed statistically significant differences between the two groups in age, sex, tumor size, calcification, capsule invasion, and strain rates ratio in strain ultrasound elastography (all P < 0.05). In multivariate logistic regression analysis, the independent predictors of occult CCLNM were age (OR = 0.975, 95% CI = 0.959-0.991, P = 0.002), sex (OR = 1.886, 95% CI = 1.220-2.915, P = 0.004), tumor size (OR = 1.054, 95% CI = 1.014-1.097, P = 0.008), and strain rates ratio (OR = 1.178, 95% CI = 1.065-1.304, P = 0.002).

Conclusion

Preoperative strain ultrasound elastography can predict presence of occult CCLNM in papillary thyroid cancer patients and help clinicians select the appropriate treatment strategy.

Systemic immune‐inflammation landscape in brain metastasis needing neurosurgical resection: Analysis of 230 consecutive cases in a single center

Background

Systemic immune‐inflammation states across the heterogeneous population of brain metastases are very important in the context of brain‐immune bidirectional communication, especially among the patients needing neurosurgical resection. Four blood cell ratios based on complete blood count (CBC) test serving as prognostic biomarkers have been highlighted by previous studies, including systemic immune‐inflammation index (SII), neutrophil‐to‐lymphocyte ratio (NLR), platelet‐to‐lymphocyte ratio (PLR), and lymphocyte‐to‐monocyte ratio (LMR). However, the presurgical systemic immune‐inflammation landscape in brain metastasis needing neurosurgical resection is limited.

Methods

Patients with brain metastases admitted to the Department of Neurosurgery at the National Cancer Center, Cancer Hospital of Chinese Academy of Medical Sciences between January 2016 and December 2019 were included. Based on peripheral blood cell counts in CBC test before neurosurgical resection, four systemic immune‐inflammation biomarkers (SII, NLR, PLR, and LMR) were calculated. We characterized the changes of SII, NLR, PLR, and LMR in patients with brain metastasis before neurosurgical resection and the associations of these types of immune‐inflammation states with patient demographics. In parallel, the corresponding data from the relative healthy populations without systemic diseases were enrolled as the control in the present study.

Results

Brain metastases induced systemic immune‐inflammation perturbation, which was characterized by a significant increase in SII (p < .01) and NLR levels (p < .01) and a significant decrease in the LMR level (p < .01) in comparison with the healthy control group. Moreover, patients with male gender, less Karnofsky Performance Status (KPS) scores (<70), specific pathological subtypes, extracranial transfer, and history of both systemic and radiation therapy may have significant differences in one or more of these biomarkers, which indicated poorer systemic immune‐inflammation states.

Conclusions

This study provides evidence that brain metastasis is associated with perturbations in presurgical systemic immune‐inflammation states. We should pay attention to the systemic immune‐inflammation perturbations following brain metastasis in clinic, especially in the subpopulations with high risks.

Blood immune indexes can predict lateral lymph node metastasis of thyroid papillary carcinoma

OBJECTIVE

To explore the clinical significance of blood immune indexes in predicting lateral lymph node metastasis (LLNM) of thyroid papillary carcinoma (PTC).

METHODS

The pathological data and preoperative blood samples of 713 patients that underwent thyroid surgery at affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine from January 2013 to June 2021 were collected as the model group. The pathological data and preoperative blood samples of 177 patients that underwent thyroid surgery in the same hospital from July 2021 to October 2021 were collected as the external validation group. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors of LLNM in PTC patients. A predictive model for assessing LLNM in PTC patients was established and externally validated using the external data.

RESULTS

According to univariate and multivariate logistic regression analyses, tumor diameter (P < 0.001, odds ratios (OR): 1.205, 95% confidence interval (CI): 1.162-1.249) and the preoperative systemic immune-inflammation index (SII) (P = 0.032, OR: 1.001, 95% CI: 1.000-1.002) were independent risk factors for distinguishing LLNM in PTC patients. When the Youden index was the highest, the area under the curve (AUC) was 0.860 (P < 0.001, 95% CI: 0.821-0.898). The externally validated AUC was 0.827 (P < 0.001, 95% CI: 0.724-0.929), the specificity was 86.4%, and the sensitivity was 69.6%. The calibration curve and the decision curve indicated that the model had good diagnostic value.

CONCLUSION

Blood immune indexes can reflect the occurrence of LLNM and the biological behavior of PTC. The predictive model established in combination with SII and tumor diameter can effectively predict the occurrence of LLNM in PTC patients.

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte Ratios, and Systemic Immune-Inflammation Index as Potential Biomarkers of Chronic Inflammation in Patients with Newly Diagnosed Acromegaly: A Single-Centre Study

Acromegaly is a rare disease caused by overproduction of growth hormone (GH) by a pituitary adenoma, and consequently increased insulin-like growth factor 1 (IGF-1) concentration. The GH/IGF-1 axis and immune cells interactions are hypothesized to be involved in subclinical inflammation. This retrospective study aimed to investigate the differences in neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR) ratios, and systemic immune-inflammation index (SII) in GH-secreting adenomas compared with non-functioning pituitary adenomas (NFPAs) concerning clinical and radiological findings. After evaluation of 665 patients with pituitary tumors, 62 individuals with newly diagnosed acromegaly and 134 with NFPAs were enrolled in the analysis. The control group consisted of 120 healthy individuals. Fifty-eight patients with acromegaly were re-evaluated after medical or surgical therapies. NLR, PLR, SII values, and neutrophil count were significantly higher (p ≤ 0.001), whereas lymphocyte count was lower in acromegaly than in NFPAs (p = 0.001). No significant differences between NFPAs and controls were observed in analyzed ratios. Higher preoperative NLR, PLR, SII values were found in patients who failed to achieve a cure with surgery (p < 0.05). Although NLR, PLR, and SII values were significantly higher in acromegaly, these indices cannot be used to discriminate GH-secreting pituitary tumors from NFPAs. Treatment of acromegaly decreased the value of NLR and SII, but it requires further studies to consolidate the real clinical role of these inflammation-related ratios.