Critical Value Research Articles

Cumulative Impact Assessment of Development Projects Around Campo-Ma'an National Park in Cameroon

This study assesses the extent to which cumulative impacts are considered when evaluating the environmental and social impacts of development projects in proximity to a protected area. The applicability of the Sorensen and Rau method for evaluating these impacts was also investigated. The methodological basis of this study is the content analysis of eight environmental and social impact assessment reports. These reports were assessed using an assessment grid divided into six blocks of questions. This grid was developed on the basis of good practice and implemented through exchanges with key stakeholders. It was also implemented in accordance with the four stages recommended by Sorensen and Rau. The results demonstrate that Block 1, which pertains to the role of the Campo-Ma'an National Park in the study, has a level of consideration of 79%. Block 2, which pertains to the analysis of the impact of the projects on the Park, was considered to a degree of 81%. Block 3, which addresses the consideration of cumulative impacts on the Park, was addressed to a limited extent, at 52%. Block 4, which pertains to public participation, has a compliance rate of 47%. Block 5, which pertains to the integration of the Environmental and Social Management Plan, was considered to the extent of 67%. Block 6 addressed 47% of the cumulative impacts on the park in the Environmental and Social Management Plan. The findings of the Sorensen and Rau method indicate that the component associated with great ape populations remains of significant value, with a criticality score of 19.52. Those components associated with the park's surface area, ecological corridors and habitat remain at an average criticality value of 11.4, 11.1 and 10.22, respectively. This suggests that the park's valued components could suffer from the cumulative effects of the various projects, particularly those associated with great apes. The study revealed that projects do not systematically integrate cumulative impacts due to a dearth of data, and that this shortcoming could be addressed through a combined matrix and network approach. It would be more prudent to consider the digitization of systems in relation to impact analysis at a time when digital technology is optimizing systems.

Quantitative assessment of volume-based metabolic parameters in early-stage invasive ductal breast cancer: Impact of different standardized uptake value thresholds on prognostic factors - A comprehensive analysis.

This study compares volume-based metabolic parameters in early-stage invasive ductal breast cancer using different standardized uptake value (SUV) thresholds and examines their association with immunohistochemical factors. A retrospective analysis included 135 patients with early-stage invasive ductal breast cancer who underwent preoperative fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) scans. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were derived using absolute SUV threshold methods and fixed % maximum tumor SUV threshold methods. Associations with immunohistochemical factors were explored, and receiver operating characteristic curves were generated. Metabolic tumor volume 2.5 and TLG 2.5 showed stronger correlations with maximum tumor SUV values. Metabolic tumor volume 2.0 and TLG 2.0 had superior area under the curve (AUC) values in predicting estrogen and progesterone receptor negativity. Metabolic tumor volume 2.0 and TLG 2.0 were superior in distinguishing low and high-grade tumors. Absolute SUV threshold methods with a threshold of 2.0 are recommended for calculating volume-based metabolic parameters due to their strong correlation with immunohistochemical factors in invasive ductal breast cancer.

Attention and Multi-Scale Fusion for Shadow Removal of Embedded Basketball Players

Player shadows in basketball games show complexity and diversity due to various factors such as lighting conditions, player movements, camera positions, etc. In the shadow removal task, the attention mechanism aids the model in focusing on the key areas in the image, that is, the players themselves and the shadows around them, and may ignore some details, resulting in poor effects in the shadow removal of embedded basketball game players. To this end, a shadow removal method for embedded basketball game players with design attention and multi-scale fusion is proposed. By extracting the texture of the shadow image area of the local embedded basketball player, setting the gray value threshold of the center point of the image area window, obtaining the Local Binary Patterns (LBP) code of the local texture feature structure of the image, scanning the LBP code of the shadow image of the embedded basketball player, and obtaining the final characteristic parameters of the shadow image of the embedded basketball player, the pixels of the shadow image of the embedded basketball player are balanced and adjusted, and the size of the image is determined by the slope of the transformation function, and the shadow image of the embedded basketball player is within the normal proportion range. The consistency of multi-scale detail pixels is adjusted to achieve pixel segmentation of shadow images of embedded basketball players. Analyzing the basic principles of the attention mechanism, the shadow images of embedded basketball players are collected for key-value pairs to represent action information, and a key-value set is set. Encoding is carried out by the encoder in the attention mechanism, and the dependence of the foul action after encoding is calculated and decoded to determine the shadow image of the embedded basketball player to achieve shadow recognition by obtaining the shadow pixel point chromaticity space of the embedded basketball player color vector value, we determine the chromaticity similarity difference, compare the chromaticity similarity difference with the threshold, design a multi-scale fusion embedded basketball player shadow removal model, and implement the research. Experimental results show that the proposed method can effectively remove the shadow of embedded basketball players.

Critically analysis for fuel oil storage facilities using FMECA method

Abstract Fuel oil storage facilities, such as the PT.X Fuel Terminal, have an important role in maintaining a stable and safe energy supply for the community. Smooth operations and reliability of equipment in the storage facility are crucial factors in ensuring an adequate and safe fuel supply. In carrying out its operations, the landfill facility is faced with various challenges. One of the main challenges is maintaining complex and diverse equipment. Equipment such as storage tanks, connecting pipes, pumps and other equipment must be maintained regularly to prevent failures that could cause operational disruptions and potential safety risks. However, traditional maintenance approaches based on routine schedules are often inefficient and less responsive to the actual condition of the equipment. In this research, criticality analysis at the fuel oil terminal was carried out. This aims to carry out condition monitoring. By analyzing criticality, it will be easier to make decisions on the next steps. In this research, the FMECA method was used. This method is very good for finding criticality values in the system.

Approaches to Increase Early Detection and Positive Biopsy Rate of Nasal Natural Killer/T-Cell Lymphoma.

To develop methods for early detection of natural killer/T-cell lymphoma, nasal type (nasal NKTL) and to evaluate the use of apparent diffusion coefficient (ADC) measurements from diffusion-weighted imaging (DWI) for selecting biopsy sites to enhance the positive biopsy rate. The clinical data of 32 cases of nasal NKTL were retrospectively collected and analyzed. Cases were graded from 1 to 5 based on endoscopic and imaging findings. Biopsy methods included the superficial forceps method and deep incisional method. Data recorded included biopsy method, time to confirmed diagnosis, number of biopsies required, and ADC values of biopsy sites. Both endoscopic and MRI lesion severity did not affect biopsy outcomes (p = 0.8248, 0.7571). The deep incisional biopsy method had a significantly higher probability of yielding positive pathological results compared to the superficial clamping method [OR (95% CI) = 23.2143 (6.0448, 89.1513) (χ2 = 26.1089, p < 0.0001)]. The ADC value at the site with a positive biopsy result is significantly lower than at the site with a negative result (p = 0.0003). The diagnostic threshold for ADC value to predict a positive biopsy result was 0.603 × 10-3 mm2/s, with a Youden index of 0.43. Nasal NKTL has distinct characteristics distinguishing it from sinusitis and other tumors. Deep incision biopsy under general anesthesia is superior to the superficial method. The location of the positive sampling site can be guided by measuring the ADC value, and the optimal diagnostic threshold of this proposed method is 0.603 × 10-3 mm2/s. 4 Laryngoscope, 2024.

The value of radiomics based on 2-[18 F]FDG PET/CT in predicting WHO/ISUP grade of clear cell renal cell carcinoma

BackgroundThe aim is to develop and validate radiomics based on 2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) parameters for predicting the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade of clear cell renal cell carcinoma (ccRCC).MethodsA total of 209 patients with 214 lesions, who underwent 2-[18F]FDG PET/CT scans between December 2016 to December 2023, were included in our study. All ccRCC lesions were categorized into low grade (WHO/ISUP grade I-II) and high grade (WHO/ISUP grade III-IV). The lesions were allocated into a training group and a testing group in a ratio of 7:3. The radiomics features were extracted by a serious of maximum standardized uptake value (SUVmax) thresholds (0,2.5%,25%,40%) with the utilization of the minimum redundancy and maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) regression algorithm. The clinical, radiomics and combined models were constructed. The receiver operating characteristic (ROC) curve, decision curve and calibration curves were plotted to assess the predicting performance.ResultsThe area under curve (AUC) of PET-0, PET-2.5%, PET-25%, PET-40% model in the training group were 0.881(95% CI: 0.822–0.940),0.883(95% CI: 0.825–0.942),0.889(95% CI: 0.831–0.946),0.887(95% CI: 0.826–0.948); and 0.878(95% CI: 0.777–0.978),0.876(95% CI: 0.776–0.977),0.871(95% CI: 0.769–0.972),0.882(95% CI: 0.786–0.979) in the testing group. Due to perfect prediction and verification performance, the volume of interest (VOI) from PET images with SUVmax threshold of 40% were selected to construct the radiomics model and combined model. The AUC of the clinical model and radiomics model was 0.859 (sensitivity = 0.846, specificity = 0.747) and 0.909 (sensitivity = 0.808, specificity = 0.751) in the training group, respectively; 0.882 (sensitivity = 0.857, specificity = 0.857) and 0.901 (sensitivity = 0.905, specificity = 0.833) in the testing group, respectively. In combined models, the AUC was 0.916, the sensitivity was 0.923 and the specificity was 0.808 in the training group; the AUC was 0.916, the sensitivity was 0.881 and the specificity was 0.792 in the training group.ConclusionRadiomics based on 2-[18F]FDG PET/CT can be helpful to predict WHO/ISUP grade of ccRCC.

Development and validation of a questionnaire to assess knowledge, attitudes, and practices regarding the addictive and detrimental effects of novel psychoactive substances among university students

BackgroundThe misuse of novel psychoactive substances (NPSs) is highly prevalent among university students, leading to significant public health and social safety concerns. To improve our drug education efforts related to NPSs, we developed a knowledge, attitudes and practices (KAP)-based questionnaire for university students.MethodsWe developed a KAP-based questionnaire after performing a comprehensive literature review and consulting experts. The questionnaire was then administered to randomly selected college students in Fujian Province. The items were evaluated using the critical ratio, correlation analysis, and Cronbach’s α coefficient. Furthermore, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to assess the construct validity of the questionnaire. Subsequently, the convergent validity, discriminant validity, and reliability of the questionnaire were evaluated.ResultsA total of 587 college students were enrolled, including 280 (47.7%) males and 550 (93.7%) students who had received anti-drug education. Item analysis revealed that 3 items did not meet the t value (t < 4) or correlation coefficient thresholds (r < 3) or that Cronbach’s α coefficient increased after removing these items. After conducting EFA, 7 items with multiple loading factors above 0.4 or loading factors below 0.4 were removed, and 5 subdimensions were observed. CFA indicated that the questionnaire model exhibited a strong fit and acceptable convergent validity. However, there were some limitations in discriminant validity. The Cronbach’s α coefficients for the overall questionnaire and each dimension exceeded 0.9, indicating excellent internal consistency. Additionally, the questionnaire exhibited excellent split-half reliability (Cronbach’s α coefficients > 0.8, Spearman-Brown value = 0.982).ConclusionThe questionnaire developed herein exhibited high levels of reliability and validity, making it a suitable KAP-based tool for evaluating NPS-related addiction and harm among university students. These findings can guide the development of drug education and behavioral interventions.

Using Time in Tight Glucose Range as a Health-Promoting Strategy in Preschoolers With Type 1 Diabetes.

Children who develop diabetes in their first years of life risk being exposed to many decades of hyperglycemia, hence having a high risk of early complications and premature death. An additional age-dependent risk is that dysglycemia, especially hyperglycemia, negatively affects the developing brain. In evaluating the outcome of insulin treatment at an individual and group level, cutoff thresholds for glucose values are needed. Time in tight range (TITR) was defined as a measurement of time spent in a state of normoglycemia. The International Society of Pediatric and Adolescent Diabetes recommended that for preschoolers with type 1 diabetes (T1D), either >70% of time with glucose in range 70-180 mg/dL (3.9-10 mmol/L) or >50% of time in a tighter range 70-140 mg/dL (TITR) can be used as continuous glucose monitoring targets. In Sweden, over the past two decades, pediatric diabetes teams set glycemic targets to 70-140 mg/dL (3.9-7.8 mmol/L). Swedish registry data show that >50% of children <7 years old have >50% TITR. The purpose of this review is to share and discuss international knowledge and experiences of working with TITR as a health-promoting strategy in preschoolers with T1D on a structural and individual level. We conclude that as insulin treatment improves, a reasonable goal is to strive for as much time in a state of normoglycemia as possible, and this can easily be explained to families of children with diabetes. For children with access to an experienced health care team and diabetes technologies a currently realistic target can be at least half of the time in normoglycemic range, i.e., TITR >50%.

Hyperhomocysteinemia and Disease-Is 10 μmol/L a Suitable New Threshold Limit?

Hyperhomocysteinemia (HHcy) is a medical condition characterized by an abnormally high level of homocysteine (Hcy) in the blood. Homocysteine is a toxic sulfur-containing amino acid that is produced during the metabolism of methionine. Under normal circumstances, Hcy is recycled back to methionine via the remethylation pathway, through the action of various enzymes and vitamins, particularly folic acid (vitamin B9) and B12 used when intracellular methionine levels are low, thus restoring the necessary levels to correctly maintain active protein synthesis. A second pathway, used in cases of intracellular methionine excess, (the trans-sulfuration pathway) is the one that recycles Hcy into cysteine (a precursor of glutathione), first passing through cystathionine (via the enzyme cystathionine beta-synthase), a reaction that requires vitamin B6 in its active form. HHcy has been identified as a risk factor for a variety of disorders, including cardiovascular diseases, multiple sclerosis, diabetes, Alzheimer's and Parkinson's diseases, osteoporosis and cancer. However, it remains unclear whether the slightly elevated concentration of Hcy (Hcy 7-10 μmol/L) is a causative factor or simply a marker of these pathologies. In human plasma, the concentration of Hcy ([Hcy]) is classified as mild (15 to 30 μmol/L), moderate (30 to 100 μmol/L), and severe (greater than 100 μmol/L). Interestingly, many laboratories continue to consider 25 μmol/L as normal. This review seeks to examine the controversial literature regarding the normal range of HHcy and emphasizes that even a [Hcy] level of 10 μmol/L may contribute to the development of several diseases, aiming to discuss whether it would be appropriate to lower the threshold of HHcy normal values.

Identification of novel PAD2 inhibitors using pharmacophore-based virtual screening, molecular docking, and MD simulation studies

In the realm of epigenetic regulation, Protein arginine deiminase 2 (PAD2) stands out as a therapeutic target due to its significant role in neurological disorders, rheumatoid arthritis (RA), multiple sclerosis (MS), and various cancers. To date, no in silico studies have focused on PAD2 for lead compound identification. Therefore, we conducted structure-based pharmacophore modeling, virtual screening, molecular docking, molecular dynamics (MD) simulations, and essential dynamics studies using PCA and free energy landscape analyses to identify repurposed drugs and selective inhibitors against PAD2. The best pharmacophore model, ‘Pharm_01,’ had a selectivity score of 10.485 and an excellent ROC curve quality of 0.972. Pharm1 consisted of three hydrogen bond donors (HBD) and two hydrophobic (Hy) features (DDDHH). A virtual screening of about 9.2 million compounds yielded 2575 hits using a fit value threshold of 2.5 and drug-likeness criteria. Molecular docking identified the top ten molecules, which were verified using MD simulations. Stability was verified using MM-PBSA studies, whereas conformational differences were investigated using PCA and free energy landscape analyses. Two hits (Leads 1 and 2) from the DrugBank dataset showed promise for repurposing as PAD2 inhibitors, while one hit compound (Lead 8) from the ZINC database emerged as a novel PAD2 inhibitor. These findings indicate that the discovered compounds may be potent PAD2 inhibitors, necessitating additional preclinical and clinical research to produce viable treatments for cancer and neurological disorders.

Finite love

ABSTRACT It seems like a problem to say that love can be merited – its value is located in its transcendence of comparative judgments. However, we commonly make judgments about who is and is not worth loving. We deem certain romantic partners, friends, and family members as worth or not worth our loving time, attention, and effort. In this paper, I argue that love can be merited, and it is merited because of a person’s intrinsic valuable qualities. However, it is not the fact that such qualities can be compared that is relevant. What is relevant is the fact that such qualities are gradable, and what it means for someone to merit love is that their qualities meet a threshold or standard of value for love. Moreover, love requires some amount of practical wisdom in discerning these thresholds and when someone meets or fails to meet them. This is important to recognize since we are creatures of finite love. We do not have the capacity to love everyone who is both worthy and unworthy of love. Given our finite capacities, I argue that making wise and discerning judgments about whom to love should be kept in mind when philosophizing about love.

Ratio of red blood cell distribution width to albumin level and risk of mortality in sarcopenic obesity

The aim of this study was to investigate the relationship between red blood cell distribution width and albumin ratio (RAR) levels and mortality in adult patients with sarcopenic obesity in the United States. The study included 1,361 adult patients with sarcopenic obesity from the National Health and Nutrition Examination Survey (1999–2006). The X-tile was used to determine the optimal subgroup thresholds for RAR values, and propensity score matching (PSM) was employed to reduce baseline bias. Cox regression analysis, Kaplan-Meier survival curves, and restricted cubic spline analysis were utilized to assess the relationship between RAR levels and all-cause and cardiovascular mortality. Subgroup analysis and the Subpopulation Treatment Effect Pattern Plot were employed to determine survival advantages across different subgroups. Time-dependent ROC analysis to evaluate the accuracy of RAR level in predicting survival outcomes at different time points. Post-PSM multifactorial Cox regression analyses revealed that RAR was a significant independent predictor of all-cause mortality (HR 1.487, 95% CI: 1.259–1.756) and an independent risk factor for cardiovascular mortality (HR 1.487, 95% CI: 1.260–1.758) in patients with sarcopenic obesity. The survival advantage was consistent across subgroups. Restricted cubic spline analysis indicated an approximate S-shaped association between RAR levels and mortality. Time-dependent ROC curves demonstrate that the areas under the all-cause mortality curves at the RAR level for 1-year, 3-year, 5-year, and 10-year are 0.79, 0.66, 0.64, and 0.63, respectively. The areas under the cardiovascular mortality curve are 0.80, 0.70, 0.66, and 0.61, respectively. Moreover, in comparison to the baseline model lacking covariates, the AUC values of the joint model exhibited heightened levels at various time points. Therefore, We demonstrated that the RAR level is an independent prognostic factor for mortality risk in the American population with sarcopenic obesity, and it is reasonable to consider the RAR level as a simple and effective risk prediction tool.

Wavelet-based vibration denoising for structural health monitoring

In the context of civil engineering applications, vibration responses are complex, exhibiting variations in time and space and often containing nonlinearity and uncertainties not considered during data collection. These responses can also be contaminated by various sources, impacting damage identification processes. A significant challenge is how to effectively remove noise from these data to obtain reliable damage indicators that are unresponsive to noise and environmental factors.This study proposes a new denoising algorithm based on discrete wavelet transform (DWT) that addresses this issue. The suggested method offers a strategy for denoising using distinct thresholds for positive and negative coefficient values at each band and applying denoising process to both detail and trend components. The results prove the effectiveness of the technique and show that Bayes thresholding performs better than the other techniques in terms of the evaluated metrics. This suggests that Bayes thresholding is a more accurate and robust technique for thresholding compared to other common techniques.

Optimizing VAT threshold: The key to improving VAT performance

The low tax ratio in Indonesia is an issue often associated with suboptimal tax revenue performance. This study examines the role of the threshold for Value Added Tax (VAT), which is suspected to significantly influence the optimization of VAT revenue, while also exploring the effect of VAT rate and Gross Domestic Product (GDP) per capita. The study analyze data from member countries of the Organization for Economic Co-operation and Development (OECD) in 2022 using multiple linear regression methods. The results show that increases in the VAT threshold and VAT rate positively impact VAT revenue performance, while an increase in per capita GDP has a negative effect. A higher VAT threshold allows the country to focus on larger taxpayers, while the Micro, Small, and Medium Enterprises (MSMEs) benefit from reduced administrative burdens. These findings can serve as a basis for government evaluation in determining the appropriate threshold and VAT rates to enhance tax revenue performance optimally.

Empirical Inferences Under Bayesian Framework to Identify Cellwise Outliers

Outliers are typically identified using frequentist methods. The data are classified as “outliers” or “not outliers” based on a test statistic that measures the magnitude of the difference between a value and the majority part of the data. The threshold for a data value to be an outlier is typically defined by the user. However, a subjective choice of the threshold increases the uncertainty associated with outlier status for each data value. A cellwise outlier detection algorithm named FuzzyHRT is used to automate the editing process in repeated surveys. This algorithm uses Bienaymé–Chebyshev’s inequality and fuzzy logic to detect four different types of outliers resulting from format inconsistencies, historical, tail, and relational anomalies. However, fuzzy logic is not suited for probabilistic reasoning behind the identification of anomalous cells. Bayesian methods are well suited for quantifying the uncertainty associated with the identification of outliers. Although, as suggested by the literature, there exist well-developed Bayesian methods for record-level outlier detection, Bayesian methods for identifying outliers within individual records (i.e., at the cell level) remain unexplored. This paper presents two approaches from the Bayesian perspective to study the uncertainty associated with identifying outliers. A Bayesian bootstrap approach is explored to study the uncertainty associated with the output scores from the FuzzyHRT algorithm. Empirical likelihoods in a Bayesian setting are also considered for probabilistic reasoning behind the identification of anomalous cells. NASS survey data for livestock and major crop yield (such as corn) are considered for comparing the performances of the two proposed approaches with recent cellwise outlier methods.

Minimal vertex model explains how the amnioserosa avoids fluidization during Drosophila dorsal closure.

During embryogenesis, cells in tissues can undergo significant shape changes. Many epithelial tissues fluidize, i.e. cells exchange neighbors, when the average cell shape index increases above a threshold value, consistent with the standard vertex model. During dorsal closure in Drosophila melanogaster , however, the amnioserosa tissue remains solid even as the average cell shape index increases well above threshold. We introduce perimeter polydispersity and allow the preferred cell perimeters, usually held fixed in vertex models, to decrease linearly with time as seen experimentally. With these extensions to the standard vertex model, we capture experimental observations quantitatively. Our results demonstrate that vertex models can describe the behavior of the amnioserosa in dorsal closure by allowing normally fixed parameters to vary with time.

Deal Value Threshold and M&amp;A: A Competition Law Analysis

In 2023, the Indian Parliament introduced amendments to the Competition Act, 2002. The primary focus of these amendments is to provide regulatory certainty, ensure faster market correction, and provide a trust-based business environment in India. These amendments also aim to give the Competition Commission of India (CCI) adequate power to ensure that no anti-competitive practices are undertaken in India. A plethora of amendments have been enacted, and one of the key amendments impacting M&amp;A is the introduction of the Deal Value Threshold (DVT) while retaining the asset and turnover test. The rationale for this amendment is to ensure digital markets are covered within the ambit of DVT and to ensure that no anti-competitive M&amp;A deals are undertaken in the digital market space. The impact of the new additional threshold in India has been analyzed, and the loopholes in the DVT framework have been highlighted. The impact of DVT on M&amp;A deals undertaken in India has been showcased. In addition, solutions have been provided that can be adopted by the CCI in order to plug the loopholes in this new framework to make it comprehensive.

Evidenced-Based Prior for Estimating the Treatment Effect of Phase III Randomized Trials in Oncology.

The primary results of phase III oncology trials may be challenging to interpret, given that results are generally based on P value thresholds. The probability of whether a treatment is beneficial, although more intuitive, is not usually provided. Here, we developed and released a user-friendly tool that calculates the probability of treatment benefit using trial summary statistics. We curated 415 phase III randomized trials enrolling 338,600 patients published between 2004 and 2020. A phase III prior probability distribution for the treatment effect was developed on the basis of a three-component zero-mean mixture distribution of the observed z-scores. Using this prior, we computed the probability of clinically meaningful benefit (hazard ratio [HR] <0.8). The distribution of signal-to-noise ratios and power of phase III oncology trials were compared with that of 23,551 randomized trials from the Cochrane Database. The signal-to-noise ratios of phase III oncology trials tended to be much larger than randomized trials from the Cochrane Database. Still, the median power of phase III oncology trials was only 49% (IQR, 14%-95%), and the power was <80% in 65% of trials. Using the phase III oncology-specific prior, only 53% of trials claiming superiority (114 of 216) had a ≥90% probability of clinically meaningful benefits. Conversely, the probability that the experimental arm was superior to the control arm (HR <1) exceeded 90% in 17% of trials interpreted as having no benefit (34 of 199). By enabling computation of contextual probabilities for the treatment effect from summary statistics, our robust, highly practical tool, now posted on a user-friendly webpage, can aid the wider oncology community in the interpretation of phase III trials.

Development of a Composite Score Based on Carbohydrate Antigen 19-9 Dynamics to Predict Survival in Carbohydrate Antigen 19-9-Producing Patients With Pancreatic Ductal Adenocarcinoma After Neoadjuvant Treatment.

Dynamics of carbohydrate antigen 19-9 (CA19-9) often inform treatment decisions during and after neoadjuvant chemotherapy (NAT) of patients with pancreatic ductal adenocarcinoma (PDAC). However, considerable dispute persists regarding the clinical relevance of specific CA19-9 thresholds and dynamics. Therefore, we aimed to define optimal thresholds for CA19-9 values and create a biochemically driven composite score to predict survival in CA19-9-producing patients with PDAC after NAT. Patients with PDAC who underwent NAT and surgical resection from 2012 to 2022 were retrospectively identified from three high-volume centers. CA19-9 nonproducers and patients with 90-day mortality, and macroscopically incomplete resections were excluded. A composite score was created on the basis of relative CA19-9 change and newly defined optimal thresholds of pre- and postneoadjuvant values for overall survival (OS) using patients from two centers and validated using data from the third center. A total of 492 patients met inclusion criteria in the development cohort. Optimal CA19-9 cutoff values for predicting a difference in OS were 202 U/mL for preneoadjuvant and 78 U/mL for postneoadjuvant levels. Furthermore, increase in CA19-9 during neoadjuvant treatment was associated with worse OS (median-OS, 17.5 months v 26.0 months; P = .008). Not surpassing any or only one of these thresholds (composite score of 0-1) was associated with improved OS compared with patients with 2-3 points (median-OS, 29.9 months v 15.8 months; P < .001). Major serological response (90% decrease of CA19-9) had a positive and negative predictive value of 32% and 88%, respectively. The composite score consisting of CA19-9 levels at diagnosis, after neoadjuvant treatment, and its dynamics demonstrates prognostic discrimination between low and high scores. However, better predictive biomarkers are needed to facilitate treatment decisions during neoadjuvant treatment.

Preliminary Evaluation of the Value of a Small-Molecule Probe Targeting DNMT1 in Detecting the Methylation of PAX1 in Cervical Cancer.

To investigate the screening value of a small-molecule probe to assess the methylation of PAX1 in cervical cancer. The diagnostic threshold of the grayscale values for cervical lesions was assessed by plotting the Receiver Operating Characteristic (ROC) curve of subjects. Grayscale values were significantly different among the four groups (p<0.05). Compared with the LSIL and cervicitis groups, a considerably higher grayscale value was found in the CA and high-grade squamous intraepithelial lesion (HSIL) groups (both p<0.05). The differential ROC curves of the grayscale values showed that the diagnostic Area Under Curve of the probe for cervicitis and low-grade squamous intraepithelial lesion (LSIL) was 0.8724 (95% CI=0.7762-0.9685, p<0.0001), for cervicitis and CA was 1.0000 (p<0.0001), for the LSIL and HSIL was 0.5484 (95% CI = 0.3826-0.7142, p=0.5755), and for the LSIL and CA was 0.7724 (95% CI = 0.6016-0.9432, p = 0.0138). The small molecular probe has certain application value in differentiating the type of cervical lesions and has better efficacy in distinguishing cervical inflammatory and precancerous lesions from carcinogenesis, but less efficacy in determining the type of precancerous lesions.