Comparative Effectiveness of the Revised American Joint Committee on Cancer Staging System.

The American Joint Committee on Cancer (AJCC) staging manual is periodically updated. This study aims to examine the staging performances in delineating stage-specific survival curves and to evaluate the reclassification of cases based on the 7th and 8th AJCC editions in Taiwan. Data were sourced from the Taiwan Cancer Registry for cases diagnosed in 2017 (7th edition) and 2018 (8th edition), each with a 2-year follow-up period. Performance was assessed using the area under the receiver operating characteristic curve and the Lorenz curve-derived Gini index, along with 2-year survival rates for evaluating patient prognoses. The 8th edition showed superior staging in four specific cancer types. Oropharyngeal cancer exhibited more variable 2-year survival rates across stages, and liver cancer showed a clearer decline in survival rates with advancing stages. The 8th edition also improved prognostic staging for non-small cell lung cancer and reclassified 26.4% of stage 4 prostate cancer patients under the 7th edition into stages 3 or 4A, showing 2-year survival rates above 90%. Our study highlights the 8th edition's refined capacity for stage-specific survival distinctions and reclassification of cases to enhance prognostication in certain cancers within Taiwan. We recommend a comprehensive evaluation when adopting a new edition or version.

Estimating effects of longitudinal and cumulative exposure to PFAS mixtures on early adolescent body composition.

Few methods have been used to characterize repeatedly measured biomarkers of chemical mixtures. We applied latent profile analysis (LPA) to serum concentrations of 4 perfluoroalkyl and polyfluoroalkyl substances (PFAS) measured at 4 time points from gestation to age 12 years. We evaluated the relationships between profiles and z scores of height, body mass index, fat mass index, and lean body mass index at age 12 years (n = 218). We compared LPA findings with an alternative approach for cumulative PFAS mixtures using g-computation to estimate the effect of simultaneously increasing the area under the receiver operating characteristic curve (AUC) for all PFAS. We identified 2 profiles: a higher PFAS profile (35% of sample) and a lower PFAS profile (relative to each other), based on their average PFAS concentrations at all time points. The higher PFAS profile had generally lower z scores for all outcomes, with somewhat larger effects for males, though all 95% CIs crossed the null. For example, the higher PFAS profile was associated with a 0.50-unit lower (ß = -0.50; 95% CI, -1.07 to 0.08) BMI z score among males but not among females (ß = 0.04; 95% CI, -0.45 to 0.54). We observed similar patterns with AUCs. We found that a higher childhood PFAS profile and higher cumulative PFAS mixtures may be associated with altered growth in early adolescence. This article is part of a Special Collection on Environmental Epidemiology.

Semisupervised transfer learning for evaluation of model classification performance.

In many modern machine learning applications, changes in covariate distributions and difficulty in acquiring outcome information have posed challenges to robust model training and evaluation. Numerous transfer learning methods have been developed to robustly adapt the model itself to some unlabeled target populations using existing labeled data in a source population. However, there is a paucity of literature on transferring performance metrics, especially receiver operating characteristic (ROC) parameters, of a trained model. In this paper, we aim to evaluate the performance of a trained binary classifier on unlabeled target population based on ROC analysis. We proposed Semisupervised Transfer lEarning of Accuracy Measures (STEAM), an efficient three-step estimation procedure that employs (1) double-index modeling to construct calibrated density ratio weights and (2) robust imputation to leverage the large amount of unlabeled data to improve estimation efficiency. We establish the consistency and asymptotic normality of the proposed estimator under the correct specification of either the density ratio model or the outcome model. We also correct for potential overfitting bias in the estimators in finite samples with cross-validation. We compare our proposed estimators to existing methods and show reductions in bias and gains in efficiency through simulations. We illustrate the practical utility of the proposed method on evaluating prediction performance of a phenotyping model for rheumatoid arthritis (RA) on a temporally evolving EHR cohort.

Diagnostic performance of shear wave measurement in the detection of hepatic fibrosis: A multicenter prospective study.

AIM: This study aimed to establish the shear wave measurement (SWM) cut-off value for each fibrosis stage using magnetic resonance (MR) elastography values as a reference standard. METHODS: We prospectively analyzed 594 patients with chronic liver disease who underwent SWM and MR elastography. Correlation coefficients (were analyzed, and the diagnostic value was evaluated by the area under the receiver operating characteristic curve. Liver stiffness was categorized by MR elastography as F0 (<2.61 kPa), F1 (≥2.61 kPa, <2.97 kPa, any fibrosis), F2 (≥2.97 kPa, <3.62 kPa, significant fibrosis), F3 (≥3.62 kPa, <4.62 kPa, advanced fibrosis), or F4 (≥4.62 kPa, cirrhosis). RESULTS: The median SWM values increased significantly with increasing fibrosis stage (p < 0.001). The correlation coefficient between SWM and MR elastography values was 0.793 (95% confidence interval 0.761-0.821). The correlation coefficients between SWM and MR elastography values significantly decreased with increasing body mass index and skin-capsular distance; skin-capsular distance values were associated with significant differences in sensitivity, specificity, accuracy, or positive predictive value, whereas body mass index values were not. The best cut-off values for any fibrosis, significant fibrosis, advanced fibrosis, and cirrhosis were 6.18, 7.09, 8.05, and 10.89 kPa, respectively. CONCLUSIONS: This multicenter study in a large number of patients established SWM cut-off values for different degrees of fibrosis in chronic liver diseases using MR elastography as a reference standard. It is expected that these cut-off values will be applied to liver diseases in the future.

A comparative study of hepatic steatosis using two different qualitative ultrasound techniques measured based on magnetic resonance imaging-derived proton density fat fraction.

AIM: This study aimed to evaluate the diagnostic performance of attenuation measurement (ATT; dual-frequency method) and improved algorithm of ATT (iATT; reference method) for the assessment of hepatic steatosis using magnetic resonance imaging (MRI)-derived proton density fat fraction (PDFF) as the reference standard. METHODS: We prospectively analyzed 427 patients with chronic liver disease who underwent ATT, iATT, or MRI-derived PDFF. Correlation coefficients were analyzed, and diagnostic values were evaluated by area under the receiver operating characteristic curve (AUROC). The steatosis grade was categorized as S0 (<5.2%), S1 (≥5.2%, <11.3%), S2 (≥11.3%, <17.1%), and S3 (≥17.1%) according to MRI-derived PDFF values. RESULTS: The median ATT and iATT values were 0.61 dB/cm/MHz (interquartile range 0.55-0.67 dB/cm/MHz) and 0.66 dB/cm/MHz (interquartile range 0.57-0.77 dB/cm/MHz). ATT and iATT values increased significantly as the steatosis grade increased in the order S0, S1, S2, and S3 (p < 0.001). The correlation coefficients between ATT or iATT values and MRI-derived PDFF values were 0.533 (95% confidence interval [CI] 0.477-0.610) and 0.803 (95% CI 0.766-0.834), with a significant difference between them (p < 0.001). For the detection of hepatic steatosis of ≥S1, ≥S2, and ≥S3, iATT yielded AUROCs of 0.926 (95% CI 0.901-0.951), 0.913 (95% CI 0.885-0.941), and 0.902 (95% CI 0.869-0.935), with significantly higher AUROC values than for ATT (p < 0.001, p < 0.001, p = 0.001). CONCLUSION: iATT showed excellent diagnostic performance for hepatic steatosis, and was strongly correlated with MRI-derived PDFF, with AUROCs of ≥0.900.

The evaluation value of atherogenic index of plasma and high-sensitivity C-reactive protein for the degree of coronary artery lesion in premature coronary artery disease.

BACKGROUND: Premature coronary artery disease (PCAD) is prevailing. We aimed to investigate the evaluation value of atherogenic index of plasma (AIP) and high-sensitivity C-reactive protein (hs-CRP) for the occurrence and severity of coronary artery lesion in PCAD patients. METHODS: PCAD (PACD group)/non-PCAD (control group) patients were enrolled. The coronary artery lesion degree was evaluated using Gensini score (GS). PCAD patients were allocated into the low/medium/high GS groups, with general clinical baseline data analyzed. Plasma hs-CRP/AIP levels were compared in PCAD patients with different disease degree. Correlations between plasma hs-CRP/AIP with Gensini score, independent risk factors affecting the occurrence of PCAD, and the predictive value of hs-CRP/AIP/their combination for the occurrence and degree of PCAD were evaluated by Spearman correlation analysis/Logistic multivariate regression/receiver operating characteristic (ROC) curve. The differences in the area under the curve (AUC) were compared using MedCalc-Comparison of ROC curves. RESULTS: Plasma hs-CRP/AIP levels in the PCAD group were increased. Plasma hs-CRP/AIP levels varied significantly among PCAD patients with different disease degree. Plasma hs-CRP/AIP levels were markedly positively correlated with the Gensini score. Smoking history/homocysteine/fasting blood-glucose/hs-CRP/AIP were all independent risk factors affecting PCAD occurrence. The AUC of hs-CRP and AIP combination predicting the occurrence of PCAD was 0.950 (90.80% sensitivity/93.33% specificity). hs-CRP/AIP combination assisted in predicting the disease degree in PCAD patients. CONCLUSIONS: AIP and hs-CRP are independent risk factors for the occurrence of PCAD, and their combination has high predictive value for PCAD occurrence and disease degree, which are both positively correlated with coronary artery lesion degree.

Diagnostic value of antibody concentration ratio for treatment-refractory myasthenia gravis.

OBJECTIVE: This study aimed to assess the diagnostic potential of the Antibody concentration ratio in identifying treatment-refractory myasthenia gravis (MG). METHODS: A retrospective analysis was conducted on 116 MG patients who underwent antibody detection at least twice between June 1, 2015, and June 1, 2023. Demographic and clinical characteristics were collated to ascertain their association with refractory MG. The Antibody Concentration Ratio was applied to determine treatment response, using the International Consensus Guidance criteria as the reference standard. The area under nonparametric receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were calculated to assess the diagnostic efficacy of the Antibody concentration ratio following consecutive immunotherapy relative to initial antibody concentrations for refractory MG. RESULTS: 19 out of 116 patients were unequivocally diagnosed with refractory MG. A significant correlation was found between the Antibody Concentration Ratio and refractory MG status in treatment-refractory and treatment-responsive patients. Subsequently, the AUC demonstrated the robust diagnostic capability of the Antibody concentration ratio for refractory MG, with an AUC of 0.8709 (95% CI: 0.7995-0.9422, p < 0.0001). The optimal cut-off value stood at 0.8903, exhibiting a sensitivity of 94.74% (95% CI: 75.36%-99.73%), a specificity of 68.04% (95% CI: 58.23%-76.48%), and accuracy of 72.41% (95% CI: 64.28%-80.54%). CONCLUSION: Elevated Antibody Concentration Ratio is intrinsically linked with refractory MG and exhibits potential as an diagnostic biomarker for the condition.

Development and validation of an oropharyngeal obstruction evaluation score.

OBJECTIVE: To identify standard clinical parameters that can predict the presence and severity of obstructive sleep apnea. SUBJECTS AND METHODS: Adult patients with habitual snoring completed comprehensive polysomnography and anthropometric measurements, including sex, age, body mass index (BMI), neck circumference, tonsil size grading, modified Mallampati score, and nasofibroscopy-assisted Muller's maneuver (NMM). Spearman's correlation coefficient was used to screen the significant variables. Stepwise multiple linear regression analysis was then conducted to identify the independent variables. receiver operating characteristic (ROC) curve analysis was used to quantify the predictability of the formed oropharyngeal obstruction scoring system. RESULTS: A total of 163 adults (127 men) were enrolled in the study. Tonsil size grading, modified Mallampati score, and NMM grading maneuver were predictive of  OSA and incorporated into a scoring system. This score ranged between 3 and 12, and threshold values of ≥ 8 and ≥ 9 seemed to be appropriate to identify patients at an increased risk of at least mild (AHI ≥ 5/h; AUROC = 0.935, 95%CI = 0.900-0.970, P < 0.001) and severe OSA (AHI ≥ 30/h; AUROC = 0.939, 95%CI = 0.899-0.969, P < 0.001), respectively. CONCLUSION: This study established an evaluation score for assessing the degree of oropharhygeal obstruction. The findings of the study suggest that the score may help identify patients at risk of oropharyngeal-related OSA who should have a full sleep evaluation.

Diagnostic accuracy of community optometrists for age-related macular degeneration using colour fundus photographs: A pilot evaluation.

PURPOSE: The accurate diagnosis of age-related macular degeneration (AMD) represents an important step in delaying and preventing vision loss and achieving optimal patient care. Therefore, this pilot study aimed to estimate the diagnostic accuracy of community optometrists for identifying AMD using colour fundus photographs (CFPs) to support sample size calculations for subsequent definitive studies. METHODS: Five practising community optometrists were invited to classify a total of 1023 CFPs for the (1) presence of AMD, and, if applicable, (2) stage of AMD (early/intermediate/late geographic atrophy/late neovascular AMD). Diagnosis by referral centre clinicians formed the reference standard. Diagnostic accuracy was assessed by the area under the receiver operating characteristic curve (aROC). Sensitivity, specificity, positive and negative predictive values were also calculated. RESULTS: Of the 1023 CFPs included in the study, 226 images were of AMD and 797 images were of other ocular conditions or no abnormal findings. Participating community optometrists had a mean (SD) age of 30.2 (8.9) years, 60.0% (3/5) were female and the mean number of years practising in primary eye care was 5.4 (5.4) years. Community optometrists demonstrated excellent performance for diagnosing AMD, with an aROC of 0.86 (95% CI 0.83 to 0.89), sensitivity of 84.5% (95% CI 79.1 to 89.0) and specificity of 88.0% (95% CI 85.5 to 90.1). The aROC (95% CI) for diagnosing early, intermediate, late geographic atrophy and late neovascular AMD was 0.82 (0.73 to 0.91), 0.76 (0.72 to 0.81), 0.69 (0.49 to 0.90) and 0.55 (0.34 to 0.75), respectively. CONCLUSIONS: These results justify the need for an appropriately powered definitive study to assess community clinicians' diagnostic accuracy for AMD.

Meta-Analysis of Diagnostic Accuracy Studies With Multiple Thresholds: Comparison of Approaches in a Simulation Study.

The development of methods for the meta-analysis of diagnostic test accuracy (DTA) studies is still an active area of research. While methods for the standard case where each study reports a single pair of sensitivity and specificity are nearly routinely applied nowadays, methods to meta-analyze receiver operating characteristic (ROC) curves are not widely used. This situation is more complex, as each primary DTA study may report on several pairs of sensitivity and specificity, each corresponding to a different threshold. In a case study published earlier, we applied a number of methods for meta-analyzing DTA studies with multiple thresholds to a real-world data example (Zapf et al., Biometrical Journal. 2021; 63(4): 699-711). To date, no simulation study exists that systematically compares different approaches with respect to their performance in various scenarios when the truth is known. In this article, we aim to fill this gap and present the results of a simulation study that compares three frequentist approaches for the meta-analysis of ROC curves. We performed a systematic simulation study, motivated by an example from medical research. In the simulations, all three approaches worked partially well. The approach by Hoyer and colleagues was slightly superior in most scenarios and is recommended in practice.

Rising Lysophosphatidylcholine Levels Post-Hepatitis C Clearance.

Hepatitis C virus (HCV) infection alters lysophosphatidylcholine (LPC) metabolism, enhancing viral infectivity and replication. Direct-acting antivirals (DAAs) effectively treat HCV and rapidly normalize serum cholesterol. In serum, LPC species are primarily albumin-bound but are also present in lipoprotein particles. This study aims to assess the impact of HCV eradication on serum LPC species levels in patients infected with HCV. Therefore, 12 different LPC species were measured by electrospray ionization tandem mass spectrometry (ESI-MS/MS) in the sera of 178 patients with chronic HCV infections at baseline, and in 176 of these patients after therapy with DAAs. All LPC species increased at 4 and 12 weeks post-initiation of DAA therapy. The serum profiles of the LPC species were similar before and after the viral cure. Patients with HCV and liver cirrhosis exhibited lower serum levels of all LPC species, except LPC 16:1, both before and after DAA treatment. Percentages of LPC 18:1 (relative to the total LPC level) were higher, and % LPC 22:5 and 22:6 were lower in cirrhotic compared to non-cirrhotic patients at baseline and at the end of therapy. LPC species levels inversely correlated with the model of end-stage liver disease score and directly with baseline and post-therapy albumin levels. Receiver operating characteristic curve analysis indicated an area under the curve of 0.773 and 0.720 for % LPC 18:1 (relative to total LPC levels) for classifying fibrosis at baseline and post-therapy, respectively. In summary, HCV elimination was found to increase all LPC species and elevated LPC 18:1 relative to total LPC levels may have pathological significance in HCV-related liver cirrhosis.

[Relationship between the percentage of energy intake from macronutrients and obesity among adult residents in 15 provinces of China in 1991-2018].

OBJECTIVE: To explore the relationship between the percentage of energy intake from macronutrients and obesity in Chinese adult residents, and analyze the cut-off values of macronutrients for predicting obesity. METHODS: Data was collected in China Health and Nutrition Survey(CHNS)in 1991-2018. Adults who participated in at least two waves of the surveys and were not obese at baseline were selected as the study subjects. Obesity was defined as body mass index(BMI)≥28.0 kg/m~2. Generalized estimating equation was used to analyze the relationship between the percentage of energy intake from macronutrients and BMI and obesity, and receiver operating characteristic curve(ROC) was used to analyze the cut-off values of percentage of energy intake from macronutrients to predict obesity. RESULTS: The percentage of energy intake from protein and fat of adult residents in 15 provinces(autonomous regions and municipalities) in China showed an increasing trend(P<0.01), and the percentage of energy intake from carbohydrate showed a decreasing trend(P<0.01) between 1991 and 2018. After adjusting for covariates, the group of percentage of energy intake from fat in 20%～30%(ß=0.05, 95%CI 0.01-0.08)and ≥30%(ß=0.15, 95%CI 0.11-0.18)were positively correlated with BMI compared with the group of percentage of energy intake from fat <20%, and the risk of obesity in 20%-30% and ≥ 30% was increased by 17%(OR=1.17, 95%CI 1.04-1.31)and 6%(OR=1.06, 95%CI 1.24-1.56), respectively. Compared with the group of the percentage of energy intake from carbohydrate < 50%, the group of 50% to 65%(ß=-0.08, 95% CI-0.11--0.05) and ≥ 65%(ß=-0.17, 95%CI-0.20--0.13) was negatively correlated with BMI, and the percentage of energy intake from carbohydrate ≥ 65% reduced the risk of obesity(OR=0.71, 95%CI 0.63-0.80). CONCLUSION: Carbohydrate intake was inversely correlated with the risk of obesity, and fat intake was positively correlated with the risk of obesity. Moderate intake of carbohydrates and reduced fat intake can prevent obesity.

[Predictive Value of the Huaxi Emotional Index in Assessing and Identifying High Suicide Risk Among Inpatients With Depression]. / åŽè¥¿å¿ƒæ™´æŒ‡æ•°åœ¨æŠ‘éƒç—‡ä½é™¢æ‚£è€ é«˜è‡ªæ€é£Žé™©è¯„ä¼°ä¸­çš„é¢„æµ‹ä½œç”¨.

Objective: This study aims to investigate the agreement between the Huaxi Emotional Index (HEI) and the Nurses' Global Assessment of Suicide Risk (NGASR) in assessing high suicide risk and to explore the predictive value of HEI in identifying high suicide risk among patients with depression. Methods: Convenience sampling was used and 386 inpatients with depression were included in this cross-sectional study. All patients were admitted to the Mental Health Center, West China Hospital between June and December 2023. The inclusion criteria were as follows, a diagnosis of depression according to the International Classification of Diseases, Tenth Revision (ICD-10), age over 18, and completion of both NGASR and HEI assessments. According to the exclusion criteria, depression patients who had other comorbid mental disorders or those who had severe cognitive impairments and were unable to communicate effectively were excluded. The study was approved by the Biomedical Ethics Review Committee of West China Hospital (Approval No. 647, 2021). Demographic data such as age, sex, ethnicity, marital status, and educational attainment were collected using a self-designed questionnaire. Both the HEI and NGASR were applied to evaluate the patients. We conducted statistical analyses with SPSS 27, employing Spearman's rank correlation for correlation analysis, Kappa tests for consistency between the two instruments, and receiver operating characteristic (ROC) curves for evaluating the predictive performance of HEI scores for high suicide risk, with the optimal HEI cutoff value determined on the basis of the Youden Index. Results: The study included 386 depression inpatients with an average age of 32 years and an average length-of-stay of 14 days. Of these participants, 252 were female (65.3%) and 134 were male (34.7%). Regarding ethnicity, most of the participants were Han Chinese (89.4%), Tibetans accounted for 7.3%, and other minorities, 3.3%. Regarding marital status, 51.3% of the participants were married, 41.2% single, 6.5% divorced, and 1.0% widowed. Regarding educational attainment, 26.2% had an undergraduate or graduate education, 20.7% had junior college education, 24.8% had high school or secondary technical school education, and 28.2% had middle school education or less. The NGASR identified 57.3% of the participants as being at high suicide risk, while the HEI identified 53.6% as having severe emotional distress. There was a moderate agreement between the HEI and the NGASR scores, with a Kappa value of 0.518 ( P<0.001), indicating statistically significant differences. At an HEI score of 17, the Youden Index peaked at 0.52, predicting high suicide risk with a specificity of 76.36%, a sensitivity of 76.02%, and an area under the ROC curve of 0.829 (95% CI: 0.787-0.871), demonstrating statistically significant differences. Conclusion: HEI and NGASR demonstrate moderate agreement in assessing high suicide risk among depression patients. The HEI questionnaire effectively predicts high suicide risk in patients with depression, with 17 being the optimal cutoff value for assessing high suicide risk.

TGFBI as a candidate biomarker for non-invasive diagnosis of early-stage endometriosis.

STUDY QUESTION: Can cartilage oligomeric matrix protein (COMP) and transforming growth factor-ß-induced protein ig-h3 (TGFBI) alone or in combination with cancer antigen 125 (CA-125) be considered as potential blood biomarkers of endometriosis? SUMMARY ANSWER: The results of this study indicate that COMP has no diagnostic value. TGFBI has potential as a non-invasive biomarker of the early stages of endometriosis, while TGFBI together with CA-125 has similar diagnostic characteristics as CA-125 alone for all stages of endometriosis. WHAT IS KNOWN ALREADY: Endometriosis is a common, chronic gynecological disease that significantly affects patient quality of life by causing pain and infertility. The gold standard for diagnosis is visual inspection of pelvic organs by laparoscopy, therefore there is an urgent need for discovery of non-invasive biomarkers for endometriosis to reduce diagnostic delays and allow earlier treatment of patients. The potential biomarkers for endometriosis evaluated in this study (COMP and TGFBI) were previously identified by our proteomic analysis of peritoneal fluid samples. STUDY DESIGN, SIZE, DURATION: This is a case-control study divided into a discovery (n = 56 patients) and a validation phase (n = 237 patients). All patients were treated between 2008 and 2019 in a tertiary medical center. PARTICIPANTS/MATERIALS, SETTING, METHOD: Patients were stratified based on the laparoscopic findings. The discovery phase included 32 endometriosis patients (cases) and 24 patients with confirmed absence of endometriosis (controls). The validation phase included 166 endometriosis and 71 control patients. Concentrations of COMP and TGFBI were measured by ELISA in plasma samples, whereas concentration of CA-125 was measured using a clinically validated assay for serum samples. Statistical and receiver operating characteristic (ROC) curve analyses were performed. The classification models were built using the linear support vector machine (SVM) method with the SVM built-in feature ranking method. MAIN RESULTS AND THE ROLE OF CHANCE: The discovery phase revealed significantly increased concentration of TGFBI, but not COMP, in plasma samples of patients with endometriosis compared to controls. In this smaller cohort, univariate ROC analysis showed fair diagnostic potential of TGFBI, with an AUC value of 0.77, sensitivity of 58%, and specificity of 84%. The classification model built using linear SVM and combining TGFBI and CA-125 showed an AUC value of 0.91, sensitivity of 88% and specificity of 75% in distinguishing patients with endometriosis from controls. The validation phase results revealed similar diagnostic characteristics of the SVM model combining TGFBI and CA-125, with an AUC value of 0.83, sensitivity of 83% and specificity of 67% and CA-125 alone with AUC value of 0.83, sensitivity of 73% and specificity of 80%. TGFBI exhibited good diagnostic potential for early-stage endometriosis (revised American Society for Reproductive Medicine stage I-II), with an AUC value of 0.74, sensitivity of 61% and specificity of 83% compared to CA-125, which had an AUC value of 0.63, sensitivity of 60% and specificity of 67%. An SVM model combining TGFBI and CA-125 showed a high AUC value of 0.94 and sensitivity of 95% for diagnosing moderate-to-severe endometriosis. LIMITATIONS, REASONS FOR CAUTION: The diagnostic models were built and validated from a single endometriosis center, and thus further validation and technical verification in a multicenter study with a larger cohort is needed. Additional limitation was lack of histological confirmation of disease for some patients in the validation phase. WIDER IMPLICATIONS OF THE FINDINGS: This study revealed for the first time increased concentration of TGFBI in plasma samples of patients with endometriosis, particularly those with minimal-to-mild endometriosis, compared to controls. This is the first step in considering TGFBI as a potential non-invasive biomarker for the early stages of endometriosis. It also opens a path for new basic research to investigate the importance of TGFBI in the pathophysiology of endometriosis. Further studies are needed to confirm the diagnostic potential of a model based on TGFBI and CA-125 for the non-invasive diagnosis of endometriosis. STUDY FUNDING/COMPETING INTEREST(S): The preparation of this manuscript was supported by grant J3-1755 from the Slovenian Research Agency to T.L.R and EU H2020-MSCA-RISE project TRENDO (grant 101008193). All authors declare that they have no conflicts of interest. TRIAL REGISTRATION NUMBER: NCT0459154.

Covariate adjustment in continuous biomarker assessment.

Continuous biomarkers are common for disease screening and diagnosis. To reach a dichotomous clinical decision, a threshold would be imposed to distinguish subjects with disease from nondiseased individuals. Among various performance metrics, specificity at a controlled sensitivity level (or vice versa) is often desirable because it directly targets the clinical utility of the intended clinical test. Meanwhile, covariates, such as age, race, as well as sample collection conditions, could impact the biomarker distribution and may also confound the association between biomarker and disease status. Therefore, covariate adjustment is important in such biomarker evaluation. Most existing covariate adjustment methods do not specifically target the desired sensitivity/specificity level, but rather do so for the entire biomarker distribution. As such, they might be more prone to model misspecification. In this paper, we suggest a parsimonious quantile regression model for the diseased population, only locally at the controlled sensitivity level, and assess specificity with covariate-specific control of the sensitivity. Variance estimates are obtained from a sample-based approach and bootstrap. Furthermore, our proposed local model extends readily to a global one for covariate adjustment for the receiver operating characteristic (ROC) curve over the sensitivity continuum. We demonstrate computational efficiency of this proposed method and restore the inherent monotonicity in the estimated covariate-adjusted ROC curve. The asymptotic properties of the proposed estimators are established. Simulation studies show favorable performance of the proposal. Finally, we illustrate our method in biomarker evaluation for aggressive prostate cancer.

Covariate-specific evaluation of continuous biomarker.

Diagnostic tests usually need to operate at a high sensitivity or specificity level in practice. Accordingly, specificity at the controlled sensitivity, or vice versa, is a clinically sensible performance metric for evaluating continuous biomarkers. Meanwhile, the performance of a biomarker may vary across sub-populations as defined by covariates, and covariate-specific evaluation can be informative. In this article, we develop a novel modeling and estimation method for covariate-specific specificity at a controlled sensitivity level. Unlike existing methods which typically adopt elaborate models of covariate effects over the entire biomarker distribution, our approach models covariate effects locally at a specific sensitivity level of interest. We also extend our proposed model to handle the whole continuum of sensitivities via dynamic regression and derive covariate-specific ROC curves. We provide the variance estimation through bootstrapping. The asymptotic properties are established. We conduct extensive simulation studies to evaluate the performance of our proposed methods in comparison with existing methods, and further illustrate the applications in two clinical studies for aggressive prostate cancer.

Clinical Value of Serum miR-106a in the Diagnosis and Prognosis of Human Papillomavirus-Positive Cervical Cancer.

INTRODUCTION: Cervical cancer (CC) is a prevailing malignant tumor in women, mainly caused by human papillomavirus (HPV) infection. This study investigated miR-106a expression in the serum of HPV-positive CC patients and estimated its value in diagnosis and prognosis. METHODS: We enrolled 120 CC patients as study subjects, with another 80 healthy women as controls. Clinical baseline data and clinicopathological indexes including age, tumor size, differentiation degree, FIGO stage, lymph node metastasis, and squamous cell carcinoma antigen (SCC-Ag) were recorded. Serum miR-106a expression was measured using reverse transcription-quantitative polymerase chain reaction. Receiver operating characteristic curve was employed to estimate the efficacy of miR-106a in diagnosing CC or HPV-positive CC. Under a 5-year follow-up, patient survival was recorded, and the impact of miR-106a on overall survival rate was analyzed by the Kaplan-Meier method. The logistic regression model was used to analyze whether miR-106a was an independent prognostic factor for HPV infection in CC patients. RESULTS: Serum miR-106a was upregulated in CC patients and the level >1.365 assisted the CC diagnosis. miR-106a expression in HPV-positive CC patients was elevated relative to HPV-negative CC patients, and serum miR-106a level >1.300 distinguishing HPV positive and HPV negative. HPV positivity was linked with tumor differentiation degree, FIGO stage, lymph node metastasis, and SCC-Ag in CC patients, but not with age and tumor size. High expression of miR-106a in HPV-positive CC patients increased the risk of poor prognosis, and miR-106a expression is an independent prognostic factor for HPV infection in CC patients. CONCLUSION: High expression of miR-106a assists in the diagnosis of HPV-positive CC and predicts poor prognosis.

Correlation of serum complement factor 5a level with inflammatory response and cognitive function in patients with Alzheimer's disease of different severity.

BACKGROUND: Alzheimer's disease (AD) is a common cause of dementia. Serum complement factor 5a (C5a) is exceedingly implicated in AD. We explored the role of C5a levels in AD patients of different severity. METHODS: Mild, moderate, and severe AD patients, and healthy controls were included. C5a and pro-inflammatory factor (TNF-α, IL-1ß, IL-6, CRP) levels were assessed by ELISA, and cognitive function was evaluated by Mini-Mental state examination (MMSE) score. The correlations between C5a, inflammatory factor levels, MMSE score, and plasma Aß42/Aß40 ratio were analyzed by Pearson tests. Independent risk factors for AD aggravation were assessed by logistic multivariate regression analysis. According to the cut-off value of receiver operating characteristic (ROC) curve analysis of C5a level, AD patients were assigned into low/high expression groups, and severe AD incidence was compared. Severe AD cumulative incidence was analyzed by Kaplan-Meier curve. RESULTS: Serum C5a, TNF-α, IL-1ß, IL-6 and CRP levels were raised, and MMSE score was lowered in AD. Serum C5a, TNF-α, IL-1ß, IL-6 and CRP levels in severe AD patients were higher than those in mild/moderate AD patients, but there were no significant differences in these cytokines between moderate and mild AD groups. The MMSE score of severe AD patients was lower than that of mild/moderate AD patients. Serum C5a level was positively correlated with serum TNF-α, IL-1ß, IL-6, and CRP levels, and negatively correlated with MMSE score, with no obvious correlation with plasma Aß42/Aß40 ratio. Serum C5a level was one of the independent risk factors for AD aggravation. The occurrence of severe AD might be related to an increase in serum C5a level. CONCLUSION: Serum C5a level increased with AD severity, and its expression was positively correlated with serum pro-inflammatory factor levels, and negatively correlated with cognitive function.

The clinic-based predictive modeling for prognosis of patients with cryptococcal meningitis.

BACKGROUND: Cryptococcal meningitis (CM) is the most common fungal infection of the central nervous system that can cause significant morbidity and mortality. Although several prognostic factors have been identified, their clinical efficacy and use in combination to predict outcomes in immunocompetent patients with CM are not clear. Therefore, we aimed to determine the utility of those prognostic factors alone or in combination in predicting outcomes of immunocompetent patients with CM. METHODS: The demographic and clinical data of patients with CM were collected and analyzed. The clinical outcome was graded by the Glasgow outcome scale (GOS) at discharge, and patients were divided into good (score of 5) and unfavorable (score of 1-4) outcome groups. Prognostic model was created and receiver-operating characteristic curve analyses were conducted. RESULTS: A total of 156 patients were included in our study. Patients with higher age at onset (p = 0.021), ventriculoperitoneal shunt placement (p = 0.010), Glasgow Coma Scale (GCS) score of less than 15(p< 0.001), lower CSF glucose concentration (p = 0.037) and immunocompromised condition (p = 0.002) tended to have worse outcomes. Logistic regression analysis was used to create a combined score which had a higher AUC (0.815) than those factors used alone for predicting outcome. CONCLUSIONS: Our study shows that a prediction model based on clinical characteristics had satisfactory accuracy in prognostic prediction. Early recognition of CM patients at risk of poor prognosis using this model would be helpful in providing timely management and therapy to improve outcomes and to identify individuals who warrant early follow-up and intervention.

Differential Expression of LOXL1-AS1 in Coronary Heart Disease and its Regulatory Mechanism in ox-LDL-Induced Human Coronary Artery Endothelial Cell Pyroptosis.

OBJECTIVE: Coronary heart disease (CHD) is a notable contributor to the burden of human health. Dysregulated long non-coding RNAs (lncRNAs) are implicated in the pathogenesis of CHD. This study investigated the expression pattern of lncRNA LOXL1-AS1 in CHD and its regulatory mechanism in oxidized low-density lipoprotein (ox-LDL)-induced human coronary artery endothelial cell (HCAEC) pyroptosis. METHODS: Serum was collected from 62 CHD patients and 62 healthy volunteers for the detection of LOXL1-AS1 expression. The value of LOXL1-AS1 in CHD diagnosis and major cardiovascular adverse event (MACE) prediction was analyzed using the ROC curve. LOXL1-AS1, miR-16-5p, and SNX16 expressions in ox-LDL-treated HCAECs were determined using RT-qPCR. NLPR3, cleaved-caspase-1, and GSDMD-N protein levels were measured using Western blot. IL-1ß and IL-18 concentrations were measured using ELISA. The binding relationships between LOXL1-AS1 and miR-16-5p and miR-16-5p and SNX16 were verified. Functional rescue experiment was performed to verify the role of miR-16-5p in HCAEC pyroptosis. RESULTS: LOXL1-AS1 was highly expressed in CHD patients. LOXL1-AS1 had diagnostic value for CHD and predictive value for MACE occurrence. ox-LDL-treated HCAECs showed reduced viability, increased IL-1ß and IL-18 concentrations, and elevated NLPR3, cleaved-caspase-1, and GSDMD-N levels. LOXL1-AS1 silencing promoted cell viability and reduced pyroptosis. LOXL1-AS1 bound to miR-16-5p and miR-16-5p targeted SNX16. Inhibition of miR-16-5p reversed the inhibitory effect of LOXL1-AS1 silencing on HCAEC pyroptosis. CONCLUSION: LOXL1-AS1 was elevated in CHD patients with a good diagnostic value for CHD and predictive value for MACE. LOXL1-AS1 downregulated miR-16-5p expression by binding to miR-16-5p to enhance ox-LDL-induced HCAEC pyroptosis, which may be associated with upregulation of SNX16 transcription.