Patient-based pre-classified real-time quality control (PCRTQC).

BACKGROUND: Patient-based real-time quality control (PBRTQC) has gained increasing attention in clinical laboratory management. Although its valuable characteristics complement traditional quality control measures, its performance and practical application have faced scrutiny. In this study, patient-based pre-classified real-time quality control (PCRTQC), an extended approach was devised to enhance real-time quality control protocols. METHODS: PCRTQC distinguishes itself by incorporating an additional patient pre-classification step utilising the OPTICS algorithm, thus addressing interference from diverse patient types. The complete set of patient test results obtained from a clinical chemistry analyser at The First Hospital of China Medical University in 2021 was utilised. Constant error (CE) and proportional error (PE) were introduced as analytical errors. Four analytes were selected to evaluate the PCRTQC, measuring probability for false rejection (Pfr) and the average number of patient samples until error detection (ANPed). Relevant error detection charts were generated. RESULTS: The PCRTQC outperformed regression-adjusted real-time quality control (RARTQC) based on the ANPed by approximately 50% for both the CE and PE, compared to the RARTQC, particularly for the total allowable error threshold. CONCLUSION: The pre-classification step effectively reduced inter-individual variation and improved data preprocessing, filtering, and modelling. The PCRTQC is a robust framework for real-time quality control research.

Development and validation of explainable machine-learning models for carotid atherosclerosis early screening.

BACKGROUND: Carotid atherosclerosis (CAS), an important factor in the development of stroke, is a major public health concern. The aim of this study was to establish and validate machine learning (ML) models for early screening of CAS using routine health check-up indicators in northeast China. METHODS: A total of 69,601 health check-up records from the health examination center of the First Hospital of China Medical University (Shenyang, China) were collected between 2018 and 2019. For the 2019 records, 80% were assigned to the training set and 20% to the testing set. The 2018 records were used as the external validation dataset. Ten ML algorithms, including decision tree (DT), K-nearest neighbors (KNN), logistic regression (LR), naive Bayes (NB), random forest (RF), multiplayer perceptron (MLP), extreme gradient boosting machine (XGB), gradient boosting decision tree (GBDT), linear support vector machine (SVM-linear), and non-linear support vector machine (SVM-nonlinear), were used to construct CAS screening models. The area under the receiver operating characteristic curve (auROC) and precision-recall curve (auPR) were used as measures of model performance. The SHapley Additive exPlanations (SHAP) method was used to demonstrate the interpretability of the optimal model. RESULTS: A total of 6315 records of patients undergoing carotid ultrasonography were collected; of these, 1632, 407, and 1141 patients were diagnosed with CAS in the training, internal validation, and external validation datasets, respectively. The GBDT model achieved the highest performance metrics with auROC of 0.860 (95% CI 0.839-0.880) in the internal validation dataset and 0.851 (95% CI 0.837-0.863) in the external validation dataset. Individuals with diabetes or those over 65 years of age showed low negative predictive value. In the interpretability analysis, age was the most important factor influencing the performance of the GBDT model, followed by sex and non-high-density lipoprotein cholesterol. CONCLUSIONS: The ML models developed could provide good performance for CAS identification using routine health check-up indicators and could hopefully be applied in scenarios without ethnic and geographic heterogeneity for CAS prevention.

Corrected Serum Ionized Calcium as a Risk Factor Related to Adult Dyslipidemia.

Background: Dyslipidemia is a significant threat to global public health due to its pivotal role as a cardiovascular disease (CVD) risk factor. Calcium is a critical nutritional element required for electrical signal transduction and muscle and heart function, and calcium supplementation is widespread in the general population. However, associations between serum calcium and serum lipid profiles remain conflicting. Considering ionized calcium [Ca(2+)] is the best measure of active serum calcium and the lack of Ca(2+) analyzers, we aimed to examine the independent and joint associations between serum ionized calcium corrected by albumin ([Ca2+]corr) and the known modifiable risk factors and dyslipidemia. Methods: We collected physical examination records, including demographic, anthropometric, laboratory tests, and clinical characteristics from individuals who had health checkups in 2019 at the health examination center of the First Affiliated Hospital of China Medical University. Subjects were categorized into Q1-Q4 groups using [Ca2+]corr quartiles, and odds ratios (ORs) with 95% confidence intervals (CIs) for dyslipidemia and associated components were calculated using logistic regression. We also performed non-linear and threshold effect analyses of [Ca2+]corr and triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (Non-HDL-C) levels. Findings: Of 5,416 individuals aged 18-92 years, multivariable-adjusted models showed that ORs for dyslipidemia increased gradually with elevated [Ca2+]corr levels. Logistic regression analyses demonstrated that [Ca2+]corr levels were associated with the increased odds of dyslipidemia (per 1 mmol/L increase: OR = 3.53, 95% CI: 1.56-8.00, P < 0.001). When compared with individuals in the Q1 group, those in groups Q3 and Q4 had significantly higher dyslipidemia odds (OR Q3 vs. Q1 = 1.20, 95% CI: 1.01-1.42; OR Q4 vs. Q1 = 1.31, 95% CI: 1.10-1.56, all P < 0.05). Furthermore, a linear, positive relationship between [Ca2+]corr levels and dyslipidemia odds was observed (P for non-linear trend = 0.506), and the optimal cut-off point of [Ca2+]corr for dyslipidemia management was 2.26 mmol/L. A modifiable effect of albumin on the relationship between [Ca2+]corr and dyslipidemia odds was also found (P for interaction = 0.014). High [Ca2+]corr levels were positively associated with elevated TC, LDL-C, and Non-HDL-C but inversely associated with decreased HDL-C odds. Moreover, Locally weighted regression (Loess) analyses showed a non-linear, positive relationship between [Ca2+]corr and TG, TC, HDL-C, LDL-C, and Non-HDL-C levels. Interpretation: Corrected serum ionized calcium was positively associated with increased odds of dyslipidemia and elevated TC, LDL-C, and Non-HDL-C, but inversely associated with the odds of decreased HDL-C.

Remnant Lipoprotein Cholesterol as a Factor Related to Adult Fatty Liver Disease.

CONTEXT: Dyslipidemia is related to fatty liver disease (FLD), whose relationship with remnant lipoprotein cholesterol (RLP-C), a component of blood lipids, remains unclear. OBJECTIVE: To clarify the correlation between RLP-C and the occurrence and severity of FLD and establish an FLD discriminant model based on health check indicators. METHODS: Retrospective study of participants who underwent health check-up in the First Affiliated Hospital of China Medical University (Shenyang, China) between January and December 2019. We categorized participants according to liver ultrasound results and analyzed the correlation between RLP-C and occurrence of FLD (n = 38 885) through logistic regression, restricted cubic spline, and receiver operating characteristic curve. We categorized the severity of FLD according to the control attenuation parameter and analyzed the correlation between RLP-C and FLD severity through multiple logistic regression; only males were included (n = 564). RESULTS: The adjusted OR (aOR) per SD between RLP-C and FLD was 2.33 (95% CI 2.21-2.46, P < .001), indicating a dose-response relationship (P < .0001). The optimal cut-off value of RLP-C was 0.45 mmol/L and the area under the curve (AUC) was 0.79. The AUC of the 8-variable model was 0.89 in both the training and the validation sets. FLD severity was related to the level of RLP-C (aOR per SD = 1.29, 95% CI 1.07-1.55, P = .008). CONCLUSION: RLP-C has a strong positive correlation with FLD occurrence and FLD severity. These results may help clinicians identify and implement interventions in individuals with high FLD risk and reduce FLD prevalence.

Association between XRCC5, 6 and 7 gene polymorphisms and the risk of breast cancer: a HuGE review and meta-analysis.

OBJECTIVE: Non-homologous end joining (NHEJ) is a pathway for repairing DNA double-strand breaks. Recent publications indicated that XRCC5, XRCC6 and XRCC7 genes may participate in the pathogenesis of breast cancer. The aim of this Human Genome Epidemiology (HuGE) review and meta-analysis was to investigate associations between XRCC5, XRCC6 and XRCC7 genetic polymorphisms in the NHEJ pathway and breast cancer risk. METHODS: Studies focusing on the relationship between genetic polymorphisms in XRCC5, XRCC6 and XRCC7 genes and susceptibility to breast cancer were selected from the Pubmed, Cochrane library, Embase, Web of Science, Springerlink, CNKI and CBM databases. Data were extracted by two independent reviewers. The meta-analysis was performed with Review Manager Version 5.1.6 and STATA Version 12.0 software. The odds ratio (OR) with 95% confidence interval (95%CI) was calculated based on the extracted data. RESULTS: According to the inclusion criteria, we final included seven studies with a total of 2,864 breast cancer cases and 3,060 healthy controls. Meta-analysis results showed that rs3835 (G>A) and rs828907 (G>T) in XRCC5 gene, and rs132793 (G>A) in XRCC6 gene might increase the risk of breast cancer, while rs132788 G>T and rs6002421 (A>G) might be protective factors. However, there was no relationship between XRCC7 genetic polymorphisms and the risk of breast cancer. CONCLUSION: This meta-analysis suggests that the rs3835 G>A and rs828907 G>T in XRCC5 gene, rs6002421 (A>G), rs132788 (G>T) and rs132793 (G>A) in XRCC6 gene might be risk factors for breast cancer, while the rs132788 (G>T) and rs6002421 (A>G) in XRCC6 gene might be protective.

Genetic variants of CYP2D6 gene and cancer risk: a HuGE systematic review and meta-analysis.

OBJECTIVE: Genetic polymorphisms in metabolic enzymes are associated with numerous cancers. A large number of single nucleotide polymorphisms (SNPs) in the CYP2D6 gene have been reported to associate with cancer susceptibility. However, the results are controversial. The aim of this Human Genome Epidemiology (HuGE) review and meta-analysis was to summarize the evidence for associations. METHODS: Studies focusing on the relationship between CYP2D6 gene polymorphisms and susceptibility to cancer were selected from the Pubmed, Cochrane library, Embase, Web of Science, Springerlink, CNKI and CBM databases. Data were extracted by two independent reviewers and the meta-analysis was performed with Review Manager Version 5.1.6 and STATA Version 12.0 software. Odds ratios (ORs) with 95% confidence intervals (95%CIs) were calculated. RESULTS: According to the inclusion criteria, forty-three studies with a total of 7,009 cancer cases and 9,646 healthy controls, were included in the meta-analysis. The results showed that there was a positive association between heterozygote (GC) of rs1135840 and cancer risk (OR=1.92, 95%CI: 1.14-3.21, P=0.01). In addition, we found that homozygote (CC) of rs1135840 might be a protective factor for cancer (OR=0.58, 95%CI: 0.34-0.97, P=0.04). Similarly, the G allele and G carrier (AG + GG) of rs16947 and heterozygote (A/del) of rs35742686 had negative associations with cancer risk (OR=0.69, 95%CI: 0.48-0.99, P=0.04; OR=0.60, 95%CI: 0.38-0.94, P=0.03; OR=0.50, 95%CI: 0.26-0.95, P=0.03; respectively). CONCLUSION: This meta-analysis suggests that CYP2D6 gene polymorphisms are involved in the pathogenesis of various cancers. The heterozygote (GC) of rs1135840 in CYP2D6 gene might increase the risk while the homozygote (CC) of rs1135840, G allele and G carrier (AG + GG) of rs16947 and heterozygote (A/del) of rs35742686 might be protective factors.

Lack of association between LIG4 gene polymorphisms and the risk of breast cancer: a HuGE review and meta-analysis.

OBJECTIVE: Non-homologous end joining (NHEJ) is one of the pathways of repair of DNA double-strand breaks. A number of genes involved in NHEJ have been implicated as breast cancer susceptibility genes such as LIG4. However, some studies have generated conflicting results. The aim of this Human Genome Epidemiology (HuGE) review and meta-analysis was to investigate association between LIG4 gene polymorphisms in the NHEJ pathway and breast cancer risk. METHODS: Studies focusing on the relationship between LIG4 gene polymorphisms and susceptibility to breast cancer were selected from the Pubmed, Cochrane library, Embase, Web of Science, Springerlink, CNKI and CBM databases. Data were extracted by two independent reviewers and the meta-analysis was performed with Review Manager Version 5.1.6 and STATA Version 12.0 software, calculating odds ratios (ORs) with 95% confidence intervals (95%CIs). RESULTS: According to the inclusion criteria, we final included seven studies with a total of 10,321 breast cancer cases and 10,160 healthy controls in the meta-analysis. The results showed no association between LIG4 gene polymorphisms (rs1805386 T>C, rs1805389 C>T, rs1805388 C>T and rs2232641 A>G) and breast cancer risk, suggesting that the mutant situation of these SNPs neither increased nor decreased the risk for breast cancer. In the subgroup analysis by Hardy-Weinberg equilibrium (HWE) and ethnicity, we also found no associations between the variants of LIG4 gene and breast cancer risk among HWE, non-HWE, Caucasians, Asians and Africans. CONCLUSION: This meta-analysis suggests that there is a lack of any association between LIG4 gene polymorphisms and the risk of breast cancer.

Vascular endothelial growth factor +936C/T polymorphism and gastric cancer risk: A meta-analysis.

The aim of this study was to determine whether the vascular endothelial growth factor (VEGF) +936C/T polymorphism confers susceptibility to gastric cancer (GC) by conducting a meta-analysis. Publications addressing the association between the VEGF +936C/T polymorphism and GC risk were selected from the Pubmed, Embase and CBM databases. Data were extracted from the studies by two independent reviewers. The meta-analysis was performed using RevMan 5.0.25 and STATA 9.2 software. From these data, the odds ratio (OR) with 95% confidence interval (CI) was calculated. Finally, 8 case-control studies were retrieved reporting a total of 2,131 gastrointestinal cancer patients and 2,670 controls. Meta-analysis results showed that there was no significant association between the VEGF +936C/T polymorphism and GC risk in all comparisons of the T allele vs. C allele (OR=1.08, 95% CI 0.90-1.30, P=0.42), CT+TT vs. CC (OR=1.08, 95% CI 0.87-1.34, P=0.49), TT vs. CC+CT (OR=1.14, 95% CI 0.85-1.53, P=0.37), TT vs. CC (OR=1.18, 95% CI 0.87-1.59, P=0.28) and TT vs. CT (OR=1.11, 95% CI 0.79-1.56, P=0.56). This meta-analysis confirms that there is a lack of association between the VEGF +936C/T polymorphism and GC risk.