False Positive Conclusions Research Articles

Evaluation of Diagnostics of Endobronchial Tumor Pathology Using a Narrow Spectrum Imaging System

Modern medicine has new equipment and high-tech diagnostic methods. At the same time, when using standard X-ray endoscopic diagnostic methods, 70-80% of newly diagnosed patients with lung cancer have stage III-IV disease. Among the radiation methods of examination for detecting lung cancer, fluorography, chest radiography, and computed tomography are used. The main disadvantage for diagnosing lung cancer is the low level of sensitivity and accuracy, and the proportion of false-positive and false-negative conclusions reaches 30%. According to AJCC recommendations, chest radiography is not recommended for lung cancer screening due to its low efficiency. Computed tomography is recommended for screening in risk groups. However, CT reveals tumor lesions already at the stage of peripheral lymphadenopathy. Modern bronchological examination is the main method for detecting hidden, early forms of lung cancer in the diagnosis.

Automated differentiation of calcifications and their clusters on the mammography image: the outcomes of the computer aided diagnosis system module

INTRODUCTION: Previously we developed the computer aided detection system (CAD) for mammography MammCheck II that increased the detection rate of small and difficult to detect breast carcinomas (BC). However this system was not specifically designed for calcification detection and discrimination. On the other hand, the calcifications had no influence on the CAD capability to detect BCs that appeared as a focal lesions.OBJECTIVE: To develop the approach for automated differentiation of benign and suspicious calcifications on the mammography images and assess its clinical value.MATERIALS AND METHODS: For the developed software testing we used a set of 390 mammography images with calcifications of all possible types (278 images with benign and 112 images with suspicious calcifications). For classification we used linear support vector machine (SVM) model, that was trained on the set of 126 images (70 — benign and 56 — suspicious). We developed two SVM models: with no vascular calcification analysis and with it. Statistics: for comparison between the normally distributed samples we used the Student’s T-test, for non-normally distributed — Wilcoxon signed-rank or Chi-square tests. For correlation testing of normally distributed samples the Paerson coefficient was calculated, for non-normally distributed samples — the Spearman or Kendall correlation coefficients. The statistical significance corresponded to Р-values <0,05.RESULTS: During the testing of the first model version with no vascular calcification analysis we discovered the similarity of small early vascular calcifications and the suspicious ones. As a result this model falsely classified 14 of 23 (60.87%) vascular calcification clusters as suspicious. Therefore the model was improved. The final discrimination results for all calcification types (both benign and suspicious) obtained with the help of improved model were the following: true positive conclusions — 375/390 (96.15%), false positive conclusions — 15/390 (3.84%). In both cases when suspicious calcifications were classified as benign the wrong results were een only on one mammography view. At the same time, on another view the suspicious calcifications were correctly classified.DISCUSSION: During the CAD development it seems important not only mark the suspicious areas but also suppress false positive markings corresponding to the obviously benign lesions. However it is important during this operation not to suppress the true positive markings. Therefore such systems are inevitably characterized by a certain shift to decreased prognostic value of suspicious markings at the expense of the highest possible prognostic value of benign markings. In our viewpoint, the developed approach meets this requirement. Moreover, its integration into the CAD allows to suppress the markings of soft tissue lesions associated with typical benign calcifications, appeared on the previous processing steps. This capability may decrease the false positive rate of the main CAD module.CONCLUSION: The developed approach to benign and suspicious calcification discrimination (version with vascular calcification analysis) on the mammography image provided the sensitivity — 98.21%, specificity — 95.32%, negative predictive value (benign marking) — 99.25%, positive predictive value (suspicious marking) — 89.43%.

Use of Telehealth in Autism Spectrum Disorder Assessment in Children: Evaluation of anOnline Diagnostic Protocol Includingthe Brief Observation of Symptoms of Autism.

The COVID-19 pandemic revealed the need to develop the field of remote assessment for autism spectrum disorders (ASD). The purpose of the study was to evaluate an online assessment protocol that includes the Brief Observation of Symptoms of Autism (BOSA). The online protocol consisting of BOSA and the Autism Diagnostic Interview-Revised (ADI-R) was administered by experienced examiners to 29 children with suspected ASD. The participants were then evaluated by clinical psychologists in a standard clinical setting using the Autism Diagnostic Observation Schedule-2 (ADOS-2) and other methods, and the ASD diagnosis was confirmed or ruled out. The results show substantial to moderate inter-rater agreement between the online and face-to-face raters with the value of Cohen's Kappa = 0.66 (P < 0.001); this corresponds with 79.8% agreement. The sensitivity of the protocol was approx. 94.7%, the specificity was 70%, the positive predictive value was 85.7%, and the negative predictive value was 87.5%. Further, direct false positive or false negative diagnostic conclusions based on the online protocol were absent when the possible conclusion of "I cannot decide" was included. The items B9 Showing, B10 Spontaneous Initiation of Joint Attention, B1 Unusual Eye Contact, B3 Facial Expressions Directed to Others, and C2 Imagination/Creativity were shown to be well observable in BOSA when related to ADOS-2 scoring. The results indicate that the protocol consisting of BOSA and ADI-R administered by an experienced examiner is a promising combination of tools for remote autism assessment.

Abstract B015: Duodenal aspiration biopsy in diagnosis of pancreatic neoplasms

Abstract Introduction Intraductal papillary mucinous neoplasms (IPMNs) are a subset of lesions with elevated malignant potential, warranting their inclusion in screening standards. Despite endoscopic ultrasound (EUS) with fine-needle aspiration biopsy (FNAB) serving as the standard for verification, the occurrence of erroneous conclusions remains significant. Consequently, analysis of pancreatic juice is considered as a potential adjunctive diagnostic method. However, the absence of methods for obtaining pancreatic juice in adequate volume and quality poses a barrier to the widespread adoption of this approach.Materials and MethodsA method of duodenal aspiration biopsy (DAB) was developed involving active aspiration from the lumen of duodenum, yielding large volume of the mix of pancreatic juice and bile uncontaminated by gastric juice. Patients diagnosed with pancreatic neoplasms utilizing EUS with FNAB, were enrolled and ALB was implemented as an adjunctive diagnostic procedure. Cytological analysis of the material obtained was performed along with measuring the level of carcinoembryonic antigen (CEA). The level &amp;gt;192 ng/mL was considered significant, according to the Fukuoka 2017 guidelines.ResultsIn patients with cystic neoplasms of the pancreas undergoing DAB, results of cytological examination were non-informative in certain cases. However, analysis of CEA levels in the pancreatic juice and bile mixture always demonstrated strong concordance with the degree of dysplasia. In some instances, elevated CEA values facilitated the adoption of a more aggressive treatment strategy, leading to the detection of carcinoma. Conversely, low CEA levels prompted the decision to opt for observation rather than radical surgery in other cases.ConclusionDiagnosing precancerous transformations of the pancreas remains a challenging task, characterized by a notable rate of false-positive or false-negative conclusions. The DAB method offers a promising solution, seamlessly integrating into routine clinical practice and offering supplementary data to enhance the verification of pancreatic cancer. Citation Format: Aleksei Kashintsev, Vitali Proutski. Duodenal aspiration biopsy in diagnosis of pancreatic neoplasms [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B015.

Beyond the Classical Type I Error: Bayesian Metrics for Bayesian Designs Using Informative Priors

There is growing interest in Bayesian clinical trial designs with informative prior distributions, for example for extrapolation of adult data to pediatrics, or use of external controls. While the classical Type I error is commonly used to evaluate such designs, it cannot be strictly controlled and it is acknowledged that other metrics may be more appropriate. We focus on two common situations—borrowing control data or information on the treatment contrast—and discuss several fully probabilistic metrics to evaluate the risk of false positive conclusions. Each metric requires specification of a design prior, which can differ from the analysis prior and permits understanding of the behavior of a Bayesian design under scenarios where the analysis prior differs from the true data generation process. The metrics include the average Type I error and the pre-posterior probability of a false positive result. When borrowing control data, our empirical cases demonstrate that the average Type I error is asymptotically controlled (in certain cases strictly) when the analysis and design prior coincide. We illustrate use of these Bayesian metrics with real applications, and discuss how they could facilitate discussions between sponsors, regulators and other stakeholders about the appropriateness of Bayesian borrowing designs for pivotal studies.

On hidden factors and design-associated errors that may lead to data misinterpretation: An example from preclinical research on the potential seasonality of neonatal seizures.

Unintentional misinterpretation of research in published biomedical reports that is not based on statistical flaws is often underrecognized, despite its possible impact on science, clinical practice, and public health. Important causes of such misinterpretation of scientific data, resulting in either false positive or false negative conclusions, include design-associated errors and hidden (or latent) variables that are not easily recognized during data analysis. Furthermore, cognitive biases, such as the inclination to seek patterns in data whether they exist or not, may lead to misinterpretation of data. Here, we give an example of these problems from hypothesis-driven research on the potential seasonality of neonatal seizures in a rat model of birth asphyxia. This commentary aims to raise awareness among the general scientific audience about the issues related to the presence of unintentional misinterpretation in published reports.

NEURAL NETWORK SYSTEM FOR ANALYSIS OF UNBALANCED HETEROGENEOUS DERMATOLOGICAL DATA ON THE BASIS OF A MULTIMODAL NEURAL NETWORK

To date, skin cancer is the most frequently diagnosed form of oncopathology. Visual diagnosis of this cancer type in the early stages is difficult due to similar visual manifestations in benign and malignant types of pigmented formations, and its accuracy depends on the experience of dermatologist. Artificial intelligence technologies are able to equal and surpass accuracy of visual diagnostic methods, but there is a risk of false positive prognosis, when malignant pigmented formation may be recognized as benign. One of the possible ways to improve recognition accuracy and reduce false positive conclusions is simultaneous use of different preprocessing methods, heterogeneous data analysis, and use of modified learning loss functions to eliminate negative impact of unbalanced dermatological data. The study presents an intelligent system for unbalanced heterogeneous dermatological data analyzing based on a multimodal neural network trained using modified cross-entropy loss function. The accuracy of classification of pigmented skin lesions in 10 diagnostically significant categories in the proposed system based on the AlexNet convolutional neural network architecture reached 83.87%. Due to the emerging synergy when using various methods to improve performance quality of intelligent systems, the number of false positive forecasts of the intelligent system was reduced, and the accuracy was increased by 1.31-4.91 percentage points, depending on the convolutional neural network architecture. Implementation of the developed system as a tool for auxiliary diagnostics can reduce the consumption of financial and labor resources involved in the medical industry, as well as increase the chance of early detection of pigmentary oncopathologies.

A Hierarchy in Majorana Non-Abelian Tests and Hidden Variable Models

The recent progress of the Majorana experiments paves a way for the future tests of non-Abelian braiding statistics and topologically protected quantum information processing. However, a deficient design in those tests could be very dangerous and reach false-positive conclusions. A careful theoretical analysis is necessary so as to develop loophole-free tests. We introduce a series of classical hidden variable models to capture certain key properties of Majorana system: non-locality, topologically non-triviality, and quantum interference. Those models could help us to classify the Majorana properties and to set up the boundaries and limitations of Majorana non-Abelian tests: fusion tests, braiding tests and test set with joint measurements. We find a hierarchy among those Majorana tests with increasing experimental complexity.

Efficacy and safety of paxlovid (nirmatrelvir/ritonavir) in the treatment of COVID-19: An updated meta-analysis and trial sequential analysis.

Our study is aimed to access the efficacy and safety outcomes for coronavirus disease 2019 (COVID-19) patients treated with Paxlovid. According to inclusion and exclusion criteria, databases were used to retrieve articles from 1 January 2020 to 1 January 2023. Article screening, quality evaluation and data extraction were completed and cross-checked. The meta-analysis and trial sequential analysis (TSA) were conducted using RevMan, StataMP, and TSA software. A total of 42 original articles were included. Overall meta-analysis results showed that for death, hospitalisation, death or hospitalisation, emergency department (ED) visit, intensive care unit (ICU) admission, and extra oxygen requirement outcomes, every odds ratio (OR) was <1 and p<0.05. For rebound outcome, the OR was >1 and p>0.05. For adverse events (AEs) outcome, the OR was >1 and p<0.05. In conclusion, Paxlovid effectively reduced the risks of death, hospitalisation, death or hospitalisation, ED visit, ICU admission, and extra oxygen requirement. There was no significant statistical difference considering rebound, but people should pay attention to possible AEs. However, for rebound and AEs outcomes, observations in certain subgroups suggested conclusions contrary to the overall meta-analysis. Trial sequential analysis indicated these two outcomes have a risk of false negative or false positive conclusions, so additional original studies are needed for further validation.

THE EFFECT DIRECTION SHOULD BE TAKEN INTO ACCOUNT WHEN ASSESSING SMALL-STUDY EFFECTS.

Studies with statistically significant results are frequently more likely to be published than those with non-significant results. This phenomenon leads to publication bias or small-study effects and can seriously affect the validity of the conclusion from systematic reviews and meta-analyses. Small-study effects typically appear in a specific direction, depending on whether the outcome of interest is beneficial or harmful, but this direction is rarely taken into account in conventional methods. We propose to use directional tests to assess potential small-study effects. The tests are built on a one-sided testing framework based on the existing Egger's regression test. We performed simulation studies to compare the proposed one-sided regression tests, conventional two-sided regression tests, as well as two other competitive methods (Begg's rank test and the trim-and-fill method). Their performance was measured by type I error rates and statistical power. Three real-world meta-analyses on measurements of infrabony periodontal defects were also used to examine the various methods' performance. Based on simulation studies, the one-sided tests could have considerably higher statistical power than competing methods, particularly their two-sided counterparts. Their type I error rates were generally controlled well. In the case study of the three real-world meta-analyses, by accounting for the favored direction of effects, the one-sided tests could rule out potential false-positive conclusions about small-study effects. They also are more powerful in assessing small-study effects than the conventional two-sided tests when true small-study effects likely exist. We recommend researchers incorporate the potential favored direction of effects into the assessment of small-study effects.

Improving the validity of neuroimaging decoding tests of invariant and configural neural representation.

Many research questions in sensory neuroscience involve determining whether the neural representation of a stimulus property is invariant or specific to a particular stimulus context (e.g., Is object representation invariant to translation? Is the representation of a face feature specific to the context of other face features?). Between these two extremes, representations may also be context-tolerant or context-sensitive. Most neuroimaging studies have used operational tests in which a target property is inferred from a significant test against the null hypothesis of the opposite property. For example, the popular cross-classification test concludes that representations are invariant or tolerant when the null hypothesis of specificity is rejected. A recently developed neurocomputational theory suggests two insights regarding such tests. First, tests against the null of context-specificity, and for the alternative of context-invariance, are prone to false positives due to the way in which the underlying neural representations are transformed into indirect measurements in neuroimaging studies. Second, jointly performing tests against the nulls of invariance and specificity allows one to reach more precise and valid conclusions about the underlying representations, particularly when the null of invariance is tested using the fine-grained information from classifier decision variables rather than only accuracies (i.e., using the decoding separability test). Here, we provide empirical and computational evidence supporting both of these theoretical insights. In our empirical study, we use encoding of orientation and spatial position in primary visual cortex as a case study, as previous research has established that these properties are encoded in a context-sensitive way. Using fMRI decoding, we show that the cross-classification test produces false-positive conclusions of invariance, but that more valid conclusions can be reached by jointly performing tests against the null of invariance. The results of two simulations further support both of these conclusions. We conclude that more valid inferences about invariance or specificity of neural representations can be reached by jointly testing against both hypotheses, and using neurocomputational theory to guide the interpretation of results.

Computed Tomography Angiography (CTA) in Selected Scenarios with Risk of Possible False-Positive or False-Negative Conclusions in Diagnosing Brain Death.

It is widely accepted that brain death (BD) is a diagnosis based on clinical examination. However, false-positive and false-negative evaluation results may be serious limitations. Ancillary tests are used when there is uncertainty about the reliability of the neurologic examination. Computed tomography angiography (CTA) is an ancillary test that tends to have the lowest false-positive rates. However, there are various influencing factors that can have an unfavorable effect on the validity of the examination method. There are inconsistent protocols regarding the evaluation criteria such as scoring systems. Among the most widely used different scoring systems the 4-point CTA-scoring system has been accepted as the most reliable method. Appropriate timing and/or Doppler pre-testing could reduce the number of possible premature examinations and increase the sensitivity of CTA in diagnosing cerebral circulatory arrest (CCA). In some cases of inconclusive CTA, the whole brain computed tomography perfusion (CTP) could be a crucial adjunct. Due to the increasing significance of CTA/CTP in determining BD, the methodology (including benefits and limitations) should also be conveyed via innovative electronic training tools, such as the BRAINDEXweb teaching tool based on an expert system.

Left atrial appendage occlusion should be offered only to select atrial fibrillation patients.

Left atrial appendage occlusion should be offered only to select atrial fibrillation patients.

The Importance of Random Slopes in Mixed Models for Bayesian Hypothesis Testing

Mixed models are gaining popularity in psychology. For frequentist mixed models, previous research showed that excluding random slopes—differences between individuals in the direction and size of an effect—from a model when they are in the data can lead to a substantial increase in false-positive conclusions in null-hypothesis tests. Here, I demonstrated through five simulations that the same is true for Bayesian hypothesis testing with mixed models, which often yield Bayes factors reflecting very strong evidence for a mean effect on the population level even if there was no such effect. Including random slopes in the model largely eliminates the risk of strong false positives but reduces the chance of obtaining strong evidence for true effects. I recommend starting analysis by testing the support for random slopes in the data and removing them from the models only if there is clear evidence against them.

Colocalization analysis of pancreas eQTLs with risk loci from alcoholic and novel non-alcoholic chronic pancreatitis GWAS suggests potential disease causing mechanisms

BackgroundPrevious genome-wide association studies (GWAS) identified genome-wide significant risk loci in chronic pancreatitis and investigated underlying disease causing mechanisms by simple overlaps with expression quantitative trait loci (eQTLs), a procedure which may often result in false positive conclusions. MethodsWe conducted a GWAS in 584 non-alcoholic chronic pancreatitis (NACP) patients and 6040 healthy controls. Next, we applied Bayesian colocalization analysis of identified genome-wide significant risk loci from both, our recently published alcoholic chronic pancreatitis (ACP) and the novel NACP dataset, with pancreas eQTLs from the GTEx V8 European cohort to prioritize candidate causal genes and extracted credible sets of shared causal variants. ResultsVariants at the CTRC (p = 1.22 × 10−21) and SPINK1 (p = 6.59 × 10−47) risk loci reached genome-wide significance in NACP. CTRC risk variants colocalized with CTRC eQTLs in ACP (PP4 = 0.99, PP4/PP3 = 95.51) and NACP (PP4 = 0.99, PP4/PP3 = 95.46). For both diseases, the 95% credible set of shared causal variants consisted of rs497078 and rs545634. CLDN2-MORC4 risk variants colocalized with CLDN2 eQTLs in ACP (PP4 = 0.98, PP4/PP3 = 42.20) and NACP (PP4 = 0.67, PP4/PP3 = 7.18), probably driven by the shared causal variant rs12688220. ConclusionsA shared causal CTRC risk variant might unfold its pathogenic effect in ACP and NACP by reducing CTRC expression, while the CLDN2-MORC4 shared causal variant rs12688220 may modify ACP and NACP risk by increasing CLDN2 expression.

Controlling for spurious moderation in marketing: A review of statistical techniques

Studies in marketing rarely control for spurious moderation, which occurs when unmeasured nonlinear terms affect researchers’ moderation analyses. Spurious moderation can lead to false-positive research conclusions. With a focus on testing moderation hypotheses with multiple regression analysis and covariance-based structural equation modelling, we discuss techniques and, where relevant, develop programming code for modifying these methods so that spurious moderation can be controlled for. After demonstrating the control techniques’ effectiveness with simulated data, we set out guidelines for their use, with particular attention paid to confirmatory research traditions in marketing research.

Detection of biosignatures in terrestrial Mars analogs: Strategical and technical assessments

The search for potential signs of Martian life has been planned and implemented by worldwide countries for decades. Due to the high expenditure on Mars exploration, more easily accessible Mars-like regions on Earth are invaluable targets for astrobiology research to understand the detection of potential Martian biosignatures. In order to detect potential life signals beyond Earth, questions on how to define life and biosignatures need to be carefully inspected. This review summarizes scientific instrumental techniques, our “eyes” and “hands”, that facilitate identifying and quantifying biosignatures on Mars. Scientific devices that can be applied in astrobiology include electromagnetic spectrum-based spectrometers, mass spectrometers, redox potential indicators, circular dichroism polarimeters, in situ nucleic acid sequencers, life isolation/cultivation systems, and imagers. These techniques should be first tested in Mars analog extreme environments on Earth to validate their practicality on Mars. To better understand the instrumental detectability of biosignatures on Mars through its evolutionary history, terrestrial Mars analogs are divided into four major categories according to their similarities to different geological ages of Mars (the Early-Middle Noachian Period, the Late Noachian-Early Hesperian Period, the Late Hesperian-Early Amazonian Period, and the Middle-Late Amazonian Period). Future missions are suggested to explore more on the early terrains in Mars’ Southern Hemisphere once the landing issue is solved engineeringly, since these explorations permit investigating a continuum of the habitability shift through Mars geological history. Moreover, practical applications of scientific instruments listed above are briefly reviewed based on the four categories of Mars analogs, and instruments applied for autonomous robotic rover tests in Mars analogs are further discussed. For engineering efficiency, a Mars rover ought to be equipped with as few assemblable instruments as possible. Therefore, once candidate landing regions on Mars are defined, the portable suites of instruments should be smartly devised on the basis of the geological, geochemical, geomorphological, and chronological characteristics of the landing regions. Laboratory-based experiments without engineering restrictions are further encouraging and appealing if Mars sample-return missions are successfully completed. To exclude false positive and false negative conclusions in life discovery, the combined use and replication studies of multiple analytical techniques must be performed to confirm the observational results.

Interpretation of meta-analyses

Our article provides guidance on how to interpret a meta-analysis and introduces the reader to the basics of the underlying statistical analysis. The multiple steps of a meta-analysis including systematic literature search, risk of bias assessment, data extraction and data aggregation are addressed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach allows to score the quality of the evidence of the results revealed by a meta-analysis. Trial sequential analysis has been suggested in recent years as a method to assess the power of a meta-analysis and the risks of false positive or false negative conclusions. We also provide information on other more complex meta-analytical approaches including network meta-analysis for the comparison of several treatments as well as recent developments such as individual patient data meta-analysis and living meta-analysis.

Planning, design and logistics of a decision analysis study: The FBI/Ames study involving forensic firearms examiners

This paper describes design and logistical aspects of a decision analysis study to assess the performance of qualified firearms examiners working in accredited laboratories in the United States in terms of accuracy (error rate), repeatability, and reproducibility of decisions involving comparisons of fired bullets and cartridge cases. The purpose of the study was to validate current practice of the forensic discipline of firearms/toolmarks (F/T) examination. It elicited error rate data by counting the number of false positive and false negative conclusions. Preceded by the experimental design, decisions, and logistics described herein, testing was ultimately administered 173 qualified, practicing F/T examiners in public and private crime laboratories. The first round of testing evaluated accuracy, while two subsequent rounds evaluated repeatability and reproducibility of examiner conclusions. This project expands on previous studies by involving many F/T examiners in challenging comparisons and by executing the study in the recommended double-blind format.

A Comparative Investigation of Interturn Faults in Induction Motors Suggesting a Novel Transient Diagnostic Method Based on the Goerges Phenomenon

Early interturn short circuits are among the most challenging faults to detect in electrical machines. It is not only difficult to identify the fault, but the diagnosis and decision-making time are crucial since the severity of this fault increases very fast, leading to a catastrophic breakdown. Despite the importance of this fault&#x0027;s prompt detection, it has been lately shown that classical methods may be insensitive to early severity conditions leading to false-positive diagnostic conclusions. This article investigates the validity and reliability of current-based approaches to those utilizing the magnetic flux performing a comparative critical assessment. The work is carried out with a finite-element analysis and experimental testing while both the steady-state and transient operations are examined. The article demonstrates the incapability of classical approaches to reliably detect early interturn faults while flux-based methods prove to be sensitive and superior to the current-based ones at the steady state. Moreover, a transient method based on the Goerges phenomenon is proposed in the article for the first time.