Prognostic significance of inflammatory markers LMR, PLR, MPV, FIB in intermediate-and high-risk papillary thyroid carcinoma

Linking MPV and NLR to TI-RADS: improved predictive accuracy for thyroid malignancy

The incidence of papillary thyroid cancer has fluctuated, partly due to advancements in neck ultrasonography and fine-needle aspiration (FNA). Identifying additional markers to differentiate benign from malignant thyroid nodules could optimize patient management and reduce unnecessary procedures. This retrospective study included 355 patients categorized into those without nodules (group 1) and those with nodules (group 2). FNA results classified nodules as benign (group A) or malignant (group B). The Pearson and Spearman correlations, Student t test, Mann-Whitney U test, and receiver operating characteristic curve analysis calculated and compared inflammatory markers across groups. The study cohort included 126 patients without nodules (group 1), and 229 patients with nodules (group 2) of whom 39 were diagnosed with papillary thyroid cancer. The median age was 56, with 54.4% females and 45.6% males. Receiver operating characteristic analysis revealed significant but poor diagnostic performance for mean platelet volume (MPV) and neutrophil-to-lymphocyte ratio (NLR), with optimal cutoff values of 10.1 and 1.60, respectively (P < .001; area under the curve: 0.30), and P < .001, area under the curve: 0.24, respectively). Patients with MPV ≥ 10.1 fL had a higher prevalence of thyroid cancer (17.1%) compared to those with MPV < 10.1 fL (5.4%). Patients with NLR ≥ 1.6 exhibited a higher prevalence of thyroid cancer (54.7%) compared to those with NLR < 1.6 (4.6%). Higher MPV and NLR values were also significantly associated with higher thyroid imaging reporting and data system classifications (P < .001 and P = .05, respectively). Elevated MPV and NLR are significantly associated with thyroid cancer and higher thyroid imaging reporting and data system classifications. These markers, combined with ultrasonography and FNA, may aid in differentiating benign from malignant thyroid nodules, potentially improving patient management and reducing unnecessary procedures.

Identification of GJC1 as a novel diagnostic marker for papillary thyroid carcinoma using weighted gene co-expression network analysis and machine learning algorithm

BACKGROUND

The incidence of thyroid papillary carcinoma (PTC) is increasing annually, causing both physical and psychological pressure on patients. Therefore, early recognition and specific interventions for PTC are crucial. The objective of this study is to explore novel diagnostic marker and precise intervention targets for PTC.

METHODS

Based on a weighted gene co-expression network analysis (WGCNA), relevant datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were collected. Enrichment analysis was performed on differentially expressed genes (DEGs) using Gene Ontology (GO), Disease Ontology (DO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Subsequently, three machine learning algorithms Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) were used to identify the core genes. Finally, receiver operating characteristic (ROC) curves were used to analyze the clinical diagnostic value of the core genes.

RESULTS

We found, in total, 11,194 DEGs derived the TCGA and GEO datasets, that are primarily enriched in extracellular matrix (ECM) and inflammation related pathways, such as an ECM receptor interaction, cell adhesion molecules (CAMs), Tumor necrosis factor (TNF) signaling, and nucleotide-binding oligomerization domain (NOD) like receptor signaling pathways. Further analysis of the core genes, identified by the protein-protein interaction network, using three machine learning algorithms discovered three intersecting genes GJC1, KLHL4, and NOL4. Of which, GJC1 has good clinical diagnostic ability, which was verified using both the GEO (area under the ROC curve (AUC) = .982) and TCGA databases (AUC = .840).

CONCLUSIONS

GJC1 is highly expressed in PTC. Therefore, it is considered as a potential biomarker and is expected to become a new target for PTC gene therapy. However, it still needs to be supported and verified by more clinical data.

Development of a nomogram incorporating BRAF-V600E to predict central lymph node metastasis in papillary thyroid carcinoma

ObjectiveThis study aims to identify risk factors associated with central lymph node metastasis (CLNM) in individuals with papillary thyroid carcinoma (PTC) and to develop a predictive nomogram model, thereby offering clinicians a valuable tool for guiding surgical treatment decisions in PTC management.MethodsClinical and ultrasound data were collected from 348 patients with PTC who underwent surgical treatment at our hospital between July 2022 and November 2023. The cohort was randomly divided into a training group (n = 243) and a validation group (n = 105 cases). Independent risk factors for CLNM were identified using multivariate logistic regression analysis, which was subsequently used to construct a predictive nomogram. The performance of the model was internally validated, and its predictive accuracy was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves.ResultsAmong the 348 patients, CLNM was observed in 115 (47.33%) patients in the training group and 48 (45.71%) patients in the validation group. Univariate and multivariate logistic regression analyses revealed that male sex, age under 55 years, nodular anteroposterior diameter of ≥1 cm, BRAF-V600E gene mutation, and tumor capsule invasion were independent risk factors for CLNM in PTC (P < 0.05). The constructed nomogram demonstrated strong predictive capability, with areas under the ROC curve (AUC) of 0.84 (95% CI, 0.78-0.89) for the training group and 0.85 (95% CI, 0.78-0.93) for the validation group.ConclusionThe nomogram constructed based on ultrasound and BRAF-V600E gene mutation status is a reliable predictive tool for CLNM in patients with PTC, potentially aiding clinicians in the formulation of personalized surgical treatment strategies.

Analysis of risk factors for papillary thyroid carcinoma and the association with thyroid function indicators

Objective

This study aims to analyze the relationship between papillary thyroid carcinoma (PTC) and various factors.

Methods

The study involved two groups-PTC patients and non-PTC controls. We utilized binary logistic regression and Least Absolute Shrinkage and Selection Operator (Lasso) regression for variable selection and risk factor analysis. Correlation analysis was performed using Spearman's rank correlation. The diagnostic value of thyroid stimulating hormone (TSH) levels for PTC was assessed using Receiver Operating Characteristic (ROC) curves.

Results

PTC patients exhibited higher body mass index (BMI) (23.71 vs. 22.66, p<0.05) and TSH levels (3.38 vs. 1.59, p<0.05). Urinary iodine concentration (UIC) was an independent predictor of PTC (OR=1.005, p<0.05). The optimal TSH threshold for PTC diagnosis was 2.4 mIU/L [The Area Under the Curve (AUC)=67.3%, specificity=71.4%, sensitivity=70.1%]. TSH levels positively correlated with BMI (r=0.593, p<0.05) and UIC (r=0.737, p<0.05).

Conclusions

UIC may be an independent predictor of PTC, and TSH levels have some diagnostic value for identifying PTC.

Predictive value of hematologic parameters and clinicopathological features of poorly differentiated thyroid carcinoma and anaplastic thyroid carcinoma

PURPOSE

Poorly differentiated thyroid carcinoma (PDTC) and anaplastic thyroid carcinoma (ATC) are rare, aggressive thyroid cancers with poor prognosis. At present, there are a limited number of research reports on PDTC and ATC. The study aimed to analysis the predictive value of hematologic parameters and clinicopathological features of PDTC and ATC.

METHODS

This study retrospectively analyzed 67 patients at Tianjin Medical University Cancer Hospital from 2007 to 2019. We analyzed the clinicopathological features and survival outcomes of PDTC and ATC.

RESULTS

This study showed that positive D-dimer, a high NLR, and a high PLR were more common in death patients. At the end of follow-up, 22 (32.8%) patients were alive at the time of study and 45 (67.2%) patients died from thyroid carcinoma. Disease-related death rates were 93.8% in ATC and 42.9% in the PDTC group. The median overall survival (OS) was 2.5 (0.3-84) months for patients with ATC, and 56 (3-113) months of PDTC patients. Univariate analysis showed that age at diagnosis and surgery were associations with OS in ATC patients, what's more, age at diagnosis, a high NLR, a high PLR, and positive D-dimer were associations with OS in PDTC patients. Multivariate analysis revealed that age at diagnosis was an independent association with OS in ATC patients.

CONCLUSIONS

The hematologic parameters and clinicopathological features may provide predictive value of prognosis for patients with PTDC and ATC.

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.

Analysis of risk factors for lymph node metastasis in 241 patients with thyroid carcinoma and establishment of a prediction model

This study aimed to identify risk factors for cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) and develop a clinical prediction model. Retrospectively, data were collected from 348 PTC patients treated at the Second Affiliated Hospital of Nanchang University between January 2019 and December 2022, with 241 patients included in the final analyses. Patients with lateral cervical LNM were categorized into a metastasis group, and those without were in a non-metastasis group. The patients were divided into a training set (n=169) and a validation set (n=72) in a 7:3 ratio. Logistic and least absolute shrinkage and selection operator (LASSO) regression models were used to identify key factors associated with lateral cervical LNM and prognosis, enabling the construction of a predictive model. The model's validity was assessed via the Hosmer-Lemeshow Test, calibration curves, ROC curves, and decision curve analysis. The metastasis group exhibited higher proportions of males, multiple lesions, bilateral involvement, tumor diameter ≥1 cm, and elevated levels of PLR, LMR, and NLR (P<0.05). Logistic regression analysis revealed that gender, multiple lesions, affected side, and tumor diameter were associated with lateral cervical LNM (P<0.05). The predictive Nomogram model, which included factors like affected side, tumor diameter, capsular invasion, central LNM, PLR, and NLR, demonstrated strong predictive accuracy and clinical utility. Thus, this study provides a practical clinical tool through an accurate Nomogram model to assess lateral cervical LNM risk in PTC patients using logistic and LASSO regression analyses.

Prognostic Roles of Inflammatory Biomarkers in Radioiodine-Refractory Thyroid Cancer Treated with Lenvatinib

BACKGRUOUND

Inflammatory biomarkers, such as the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR), serve as valuable prognostic indicators in various cancers. This multicenter, retrospective cohort study assessed the treatment outcomes of lenvatinib in 71 patients with radioactive iodine (RAI)-refractory thyroid cancer, considering the baseline inflammatory biomarkers.

METHODS

This study retrospectively included patients from five tertiary hospitals in Korea whose complete blood counts were available before lenvatinib treatment. Progression-free survival (PFS) and overall survival (OS) were evaluated based on the median value of inflammatory biomarkers.

RESULTS

No significant differences in baseline characteristics were observed among patients grouped according to the inflammatory biomarkers, except for older patients with a higher-than-median NLR (≥2) compared to their counterparts with a lower NLR (P= 0.01). Patients with a higher-than-median NLR had significantly shorter PFS (P=0.02) and OS (P=0.017) than those with a lower NLR. In multivariate analysis, a higher-than-median NLR was significantly associated with poor OS (hazard ratio, 3.0; 95% confidence interval, 1.24 to 7.29; P=0.015). However, neither the LMR nor the PLR was associated with PFS. A higher-than-median LMR (≥3.9) was significantly associated with prolonged OS compared to a lower LMR (P=0.036). In contrast, a higher-than-median PLR (≥142.1) was associated with shorter OS compared to a lower PLR (P=0.039).

CONCLUSION

Baseline inflammatory biomarkers can serve as predictive indicators of PFS and OS in patients with RAI-refractory thyroid cancer treated with lenvatinib.

Nomogram model based on preoperative clinical characteristics of unilateral papillary thyroid carcinoma to predict contralateral medium-volume central lymph node metastasis

Objectives

To explore the preoperative high-risk clinical factors for contralateral medium-volume central lymph node metastasis (conMVCLNM) in unilateral papillary thyroid carcinoma (uPTC) and the indications for dissection of contralateral central lymph nodes (conCLN).

Methods

Clinical and pathological data of 204 uPTC patients who underwent thyroid surgery at the Hangzhou First People's Hospital from September 2010 to October 2022 were collected. Univariate and multivariate logistic regression analyses were conducted to determine the independent risk factors for contralateral central lymph node metastasis (conCLNM) and conMVCLNM in uPTC patients based on the preoperative clinical data. Predictive models for conCLNM and conMVCLNM were constructed using logistic regression analyses and validated using receiver operating characteristic (ROC) curves, concordance index (C-index), calibration curves, and decision curve analysis (DCA).

Results

Univariate and multivariate logistic regression analyses showed that gender (P < 0.001), age (P < 0.001), tumor diameter (P < 0.001), and multifocality (P = 0.008) were independent risk factors for conCLNM in uPTC patients. Gender(P= 0.026), age (P = 0.010), platelet-to-lymphocyte ratio (PLR) (P =0.003), and tumor diameter (P = 0.036) were independent risk factors for conMVCLNM in uPTC patients. A predictive model was established to assess the risk of conCLNM and conMVCLNM, with ROC curve areas of 0.836 and 0.845, respectively. The C-index, the calibration curve, and DCA demonstrated that the model had good diagnostic value.

Conclusion

Gender, age, tumor diameter, and multifocality are high-risk factors for conCLNM in uPTC patients. Gender, age, tumor diameter, and PLR are high-risk factors for conMVCLNM in uPTC patients, and preventive conCLN dissection should be performed.

Predicting coexisting thyroid cancer with primary hyperparathyroidism in an endemic region of multinodular goiter: evaluating the effectiveness of preoperative inflammatory markers

Purpose

The aim is to examine the efficacy of inflammatory indicators to predict thyroid cancer in patients with primary hyperparathyroidism (PHPT) in an endemic region of nodular goiter.

Methods

The prospective database was reviewed to identify patients operated on with the diagnosis of PHPT and thyroid disease between April 2015 and June 2021. Permanent pathologic reports were used as the gold standard for diagnosis. Detailed imaging data with peripheral blood inflammation indices were analyzed to assess their predictive values for concomitant PHPT with thyroid cancer. Postoperative complications and the duration of hospitalization were also reviewed.

Results

Thyroid malignancy accompanying PHPT was found in 13 patients (26.0%) out of 50 who had concurrent surgery. The analysis regarding inflammatory indexes revealed nothing significant between thyroid cancer and preoperative blood biochemistry (P > 0.05). In the concurrent surgery group, recurrent laryngeal nerve injury was observed in 1 patient (2.0%) and the mean hospital stay was longer.

Conclusion

In endemic regions of nodular thyroid disease, thyroid cancer might accompany PHPT. The value of inflammatory indexes to predict thyroid malignancy in PHPT is controversial and should not be employed in the surgical decision-making process.

Relation of Mean Platelet Volume (MPV) with Cancer: A Systematic Review with a Focus on Disease Outcome on Twelve Types of Cancer

Inflammatory proteins activate platelets, which have been observed to be directly related to cancer progression and development. The aim of this systematic review is to investigate the possible association between Mean Platelet Volume (MPV) and cancer (diagnostic capacity of MPV, relation to survival, the severity of the disease, and metastasis). A literature review was performed in the online database PubMed and Google Scholar for the period of 2010–2022. In total, 83 studies including 21,034 participants with 12 different types of cancer (i.e., gastric cancer, colon cancer, esophageal squamous cell carcinoma, renal cancer, breast cancer, ovarian cancer, endometrial cancer, thyroid cancer, lung cancer, bladder cancer, gallbladder cancer, and multiple myeloma) were identified. The role of MPV has been extensively investigated in several types of cancer, such as gastric, colon, breast, and lung cancer, while few data exist for other types, such as renal, gallbladder cancer, and multiple myeloma. Most studies in gastric, breast, endometrium, thyroid, and lung cancer documented an elevated MPV in cancer patients. Data were less clear-cut for esophageal, ovarian, and colon cancer, while reduced MPV was observed in renal cell carcinoma and gallbladder cancer. Several studies on colon cancer (4 out of 6) and fewer on lung cancer (4 out of 10) indicated an unfavorable role of increased MPV regarding mortality. As far as other cancer types are concerned, fewer studies were conducted. MPV can be used as a potential biomarker in cancer diagnosis and could be a useful tool for the optimization of treatment strategies. Possible underlying mechanisms between cancer and MPV are discussed. However, further studies are needed to elucidate the exact role of MPV in cancer progression and metastasis.