Diagnostic value of modified systemic inflammation score for prediction of malignancy in patients with indeterminate thyroid nodules

Exploring the environmental contamination toxicity and potential carcinogenic pathways of perfluorinated and polyfluoroalkyl substances (PFAS): An integrated network toxicology and molecular docking strategy

The objective of this study was to investigate the potential carcinogenic toxicity and mechanisms of PFAS in thyroid, renal, and testicular cancers base on network toxicology and molecular docking techniques. Structural modeling was performed to predict relevant toxicity information, and compounds and cancer-related targets were screened in multiple databases. The interaction of PFAS with three cancers and their key protein targets were explored by combining protein network analysis, enrichment analysis and molecular docking techniques. PFOA, PFOS, and PFHXS exhibited significant carcinogenic and cytotoxic effects. These compounds may induce cancer by mediating active oxygen metabolism and the transduction of phosphatidylinositol 3-kinase/protein kinase B signaling pathway through genes such as ALB, mTOR, MDM2, and ERBB2. Furthermore, the underlying toxic mechanisms may be linked to the pathways in cancer, chemical carcinogenesis through reactive oxygen species/receptor activation, and the FoxO signaling pathway. The results contribute to a comprehensive understanding of the effects of these environmental pollutants on genes, proteins, and metabolic pathways in living organisms. It revealed their toxicity mechanisms in inducing thyroid, renal, and testicular cancers, and provided a solid theoretical foundation for designing new environmental control strategies and drug screening initiatives. Additionally, the integrated application of network toxicology and molecular docking technology can enhance our understanding of the toxicity and mechanisms of unknown environmental pollutants, which is beneficial for protecting the environment and human health.

Risk stratification of papillary thyroid cancers using multidimensional machine learning

BACKGROUND

Papillary thyroid cancer (PTC) is one of the most common endocrine malignancies with different risk levels. However, preoperative risk assessment of PTC is still a challenge in the worldwide. Here, the authors first report a Preoperative Risk Assessment Classifier for PTC (PRAC-PTC) by multidimensional features including clinical indicators, immune indices, genetic feature, and proteomics.

MATERIALS AND METHODS

The 558 patients collected from June 2013 to November 2020 were allocated to three groups: the discovery set [274 patients, 274 formalin-fixed paraffin-embedded (FFPE)], the retrospective test set (166 patients, 166 FFPE), and the prospective test set (118 patients, 118 fine-needle aspiration). Proteomic profiling was conducted by FFPE and fine-needle aspiration tissues from the patients. Preoperative clinical information and blood immunological indices were collected. The BRAFV600E mutation were detected by the amplification refractory mutation system.

RESULTS

The authors developed a machine learning model of 17 variables based on the multidimensional features of 274 PTC patients from a retrospective cohort. The PRAC-PTC achieved areas under the curve (AUC) of 0.925 in the discovery set and was validated externally by blinded analyses in a retrospective cohort of 166 PTC patients (0.787 AUC) and a prospective cohort of 118 PTC patients (0.799 AUC) from two independent clinical centres. Meanwhile, the preoperative predictive risk effectiveness of clinicians was improved with the assistance of PRAC-PTC, and the accuracies reached at 84.4% (95% CI: 82.9-84.4) and 83.5% (95% CI: 82.2-84.2) in the retrospective and prospective test sets, respectively.

CONCLUSION

This study demonstrated that the PRAC-PTC that integrating clinical data, gene mutation information, immune indices, high-throughput proteomics and machine learning technology in multicentre retrospective and prospective clinical cohorts can effectively stratify the preoperative risk of PTC and may decrease unnecessary surgery or overtreatment.

Inflammatory markers may predict post-operative complications and recurrence in Crohn's disease patients undergoing gastrointestinal surgery

BACKGROUND

Most Crohn's Disease (CD) patients will require surgical intervention over their lifetime, with considerably high rates of post-operative complications. Risk stratification with reliable prognostic tools may facilitate clinical decision making in these patients. Blood cell interaction based inflammatory markers have proven useful in predicting patient outcomes in oncological and benign diseases. The aim of this study was to investigate their prognostic value in CD patients undergoing surgery.

METHODS

A retrospective single institution study of CD patients who underwent surgery between the years 2008 and 2019 was conducted. Data were collected from medical records and analysed for association of Platelet-to-Lymphocyte Ratio (PLR), Neutrophil-to-Lymphocyte Ratio (NLR), Lymphocyte-to-Monocyte Ratio (LMR) and the modified Systemic Inflammatory Score (mSIS) with post-operative outcomes.

RESULTS

A total of 81 patients were included in the analysis. Half were females; mean age was 36 ± 15.54 years. Fifty seven percent (n = 46) were operated in expedited settings, with 23.5% developing post-operative complications. In elective patients, higher pre-operative NLR (P = 0.029) and PLR (P = 0.034) were associated with major post-operative complications, higher NLR (P = 0.029) and PLR (P = 0.034) were associated with re-operation and higher PLR correlated with Clavien-Dindo score (P = 0.032). In patients operated in expedited operations, higher pre-operative NLR (P = 0.021) and lower pre-operative LMR (P = 0.018) were associated with thromboembolic events and higher mSIS was associated with major post-operative complications (P = 0.032).

CONCLUSIONS

Blood cell interaction based inflammatory markers confer an association with post-operative complications in CD patients undergoing surgery. These indices may facilitate patient selection and optimization when considering the risks and benefits of surgical interventions.

Predictive value of modified systemic inflammation score for postoperative unplanned ICU admission in patients with NSCLC

Background

The purpose of this study was to investigate the predictive value of the modified systemic inflammation score (mSIS) in postoperative unplanned admission to the intensive care unit (ICU) in patients with non-small-cell lung cancer (NSCLC).

Methods

The clinical data of 1,321 patients with NSCLC treated with thoracic surgery in our hospital from August 2019 to June 2021 were analyzed retrospectively. The preoperative mSIS, which takes into account the serum albumin (ALB) level and lymphocyte-to-monocyte ratio (LMR), was recorded as 0, 1 or 2 and then was used to identify high-risk patients with unplanned admission to the ICU. The independent risk factors for unplanned admission to the ICU in patients with NSCLC after surgery were identified by multivariate logistic regression analysis.

Results

A total of 1,321 patients, including 549 (41.6%) males and 772 (58.4%) females, were included. The median age was 57 years (range 16–95 years). The incidence of unplanned admission to the ICU in patients with mSIS = 2 was significantly higher than that in those with mSIS = 0 and mSIS = 1. The multivariate analysis showed that an mSIS of 2 (OR = 3.728; P = 0.004; 95% CI, 1.520–9.143), an alcohol consumption history (OR = 2.791, P = 0.011; 95% CI, 1.262–6.171), intraoperative infusion volume (OR = 1.001, P = 0.021; 95% CI, 1.000–1.001) and preoperative underlying diseases (OR = 3. 57, P = 0.004; 95% CI, 1.497–8.552) were independent risk factors for unplanned admission to the ICU after lung cancer surgery. In addition, the multivariate logistic regression model showed that the C-statistic value was 0.799 (95% CI: 0.726∼0.872, P < 0.001).

Conclusions

The mSIS scoring system can be used as a simplified and effective predictive tool for unplanned ICU admission in patients with NSCLC.

Prognostic Evaluation of Metastasis-Related Lymphocyte/Monocyte Ratio in Stage Ⅰ-Ⅲ Breast Cancer Receiving Chemotherapy

Purpose

This study aims to clarify the prognostic significance of metastasis-related indicators in peripheral blood in stage I-III breast cancer (BC).

Methods

The clinicopathological data of 938 breast cancer patients and 509 benign breast disease patients were retrospectively analyzed, and fasting blood samples were collected before treatment. Univariate and multivariate regression analyses were used to evaluate factors related to metastasis risk and prognosis. The Kaplan-Meier method was used to generate survival curves, and the log-rank test was used to measure differences in survival between groups.

Results

Use the cut-off value (3.433) of LMR, the logistic regression analysis revealed that high carbohydrate antigen 153 (CA153), carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), killer T cell level, and low lymphocyte to monocyte ratio (LMR) level were significantly associated with BC distant metastasis. In contrast, LMR>=3.433 (HR: 0.409, 95%CI: 0.193–0.867, P = 0.020), Th/Tc ratio >=1.946 (HR: 0.378, 95% CI: 0.158–0.904, P =0.029) is regarded as a protective factor in the multivariate cox analyses. LMR is an independent prognostic factor for DFS in HER2-negative BC patients.

Conclusion

Peripheral blood parameters play an important role in predicting distant metastasis and prognosis of BC patients. As a potential marker, LMR can predict the metastasis and prognosis of patients with stage I-III BC.

Can preoperative modified systemic inflammation score (mSIS) be used to predict malignancy in persistent nondiagnostic thyroid nodules?

Background/aim

Despite the use of ultrasound guidance, a significant part of thyroid biopsies are nondiagnostic (ND). We aimed to investigate the utility of the preoperative modified systemic inflammation score (mSIS) to predict malignancies in patients with persistent ND thyroid nodules (TNs).

Materials and methods

Records of 924 patients underwent thyroidectomy between September 2016 and May 2019 were retrospectively reviewed. The calculation of mSIS was as follows: mSIS 0 [patients with albumin (ALB) ≥ 4.0 g/dL and lymphocyte to monocyte ratio (LMR) ≥ 3.4], mSIS 1 [ALB < 4.0 g/dL or LMR < 3.4], and mSIS 2 [ALB < 4.0 g/dL and LMR < 3.4].

Results

One hundred and thirty-six patients were included in the study. Of the patients with a median age of 49 (21–81) years, 26 (19.1%) were male, and 110 (80.9%) were female. Besides low lymphocyte count (P = 0.03), and ALB levels (P < 0.01), higher BMI (P = 0.02) were also associated with malignancy. In patients classified as mSIS 2, 1 and 0; malignancy rates were 100%, 25.8%, and 16.1%, respectively. The association between preoperative mSIS and thyroid malignancies was statistically significant (P < 0.01).

Conclusion

We recommend that when patients with persistent ND TNs are assigned to mSIS 2 or 1, surgery should not be delayed due to the risk of malignancy.