A novel clinical tool to estimate risk of false negative KRAS mutation in circulating tumor DNA testing.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3594-3594
Author(s):  
Stefania Napolitano ◽  
Ryan Sun ◽  
Aparna Raj Parikh ◽  
Jason Henry ◽  
Christine Megerdichian Parseghian ◽  
...  
Keyword(s):  
Kras Mutation ◽  
Posterior Probability ◽  
False Negative ◽  
False Negative Rate ◽  
Training Dataset ◽  
False Negatives ◽  
True Negative ◽  
Ras Mutations ◽  
Egfr Inhibition ◽  
Negative Rate

3594 Background: Recently, in metastatic colorectal cancer (mCRC), the detection of RAS mutations by circulating tumor (ct) DNA has recently emerged as a valid and non-invasive alternative approach, overall showing a high concordance with the standard tissue genotyping, giving information on response to EGFRi treatment and resistant mechanisms. However, RAS mutations may be missed due to low levels of any ctDNA in the blood (false-negative), and it has been difficult to distinguish this from patients without a RAS mutation in the tumor (true-negative). We propose a methodology that can be applied to multi-gene ctDNA testing panels to accurately distinguish true- and false-negative tests. Methods: 357 subjects with tissue and multi-panel ctDNA testing from MD Anderson (MDACC) were used as a training dataset and 295 subjects from Massachusetts General Hospital (MGH) dataset as the testing dataset. CtDNA panels contained between 65 and 70 genes, allowing evaluation of tumor ctDNA shedding from variant allele fraction (VAF) levels in the plasma from other genes (such as APC and TP53). Based on the relationship between KRAS and the VAFs of other gene, we established a Bayesian model providing a posterior probability of false negative in the ctDNA test, using thresholds of < 5% (low), 5-15% (medium), and > 15% (high). This model was validated on the MGH database. Results: Across both cohorts, 431 patients were ctDNA wild type for KRAS. Of those, 29 had tissue documenting a KRAS mutation for a false negative rate of 8%. The model provides the posterior probability that a KRAS mutation is indeed present in the tissue given the observed values of allele frequencies for other mutated genes in the plasma. In the validation cohort, a predicted low false negative had no false negatives (0/62, 95% CI 0%-5.8%), while a predicted medium false negative rate was associated with 3% false negative (1/32, 95% CI 0%-16%). In contrast, a high predicted false negative rate was associated with 5% false negative (5/100, 95% CI 1.6%-11%). The results demonstrate the ability of our tool to discriminate between subjects with true negative and false negatives, as a higher proportion of false negatives are observed at higher posterior probabilities. Conclusions: In conclusion, our approach provides increased confidence in KRAS ctDNA mutation testing in clinical practice, thereby facilitating the identification patients who will benefit from EGFR inhibition while reducing the risk of false negative tests. Extension of this methodology to NRAS and BRAF is possible, with clinical application enabled by a freely available online tool.

scholarly journals 0587 Convenience vs Accuracy: Negative Predictability of the Home Sleep Test in Clinical Practice

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A225-A225
Author(s):  
C D Morse ◽  
S Meissner ◽  
L Kodali
Keyword(s):  
Clinical Practice ◽  
Sleep Apnea ◽  
False Negative ◽  
False Negative Rate ◽  
True Negative ◽  
Negative Rate ◽  
High False Negative Rate ◽  
Obstructive Sleep ◽  
Respiratory Disturbance ◽  
Lost To Follow Up

Abstract Introduction Sleep apnea is a serious disorder associated with numerous health conditions. In clinical practice, providers order screening home sleep testing (HST) for obstructive sleep apnea (OSA); however, there is limited research about the negative predictive value (NPV) and false negative rate of this test. Providers may not understand HST limitations; therefore, what is the NPV and false negative rate in clinical practice? Methods A retrospective study of non-diagnostic HST is conducted in a Northeastern US rural community sleep clinic. The study population includes adult patients ≥ 18 years old who underwent HST from 2016-2019. The non-diagnostic HST result is compared to the gold standard, the patient’s nocturnal polysomnogram (NPSG). The results provide the NPV (true negative/total) and false negative (true positive/total) for the non-diagnostic HST. Results We identified 211 potential patients with a mean age of 43 years, of which 67% were female. Of those, 85% (n=179) underwent NPSG, with the others declining/delaying testing or lost to follow up. The non-diagnostic HST showed 15.6% NPV for no apnea using AHI&lt;5 and 8.4% NPV using respiratory disturbance index (tRDI)&lt;5. The false negative rate for AHI/tRDI was 84.4% and 91.6%, respectively. The AHI for positive tests ranged from 5-89 per hour (mean AHI 14.9/tRDI 16/hour), of which OSA was identified with an elevated AHI (≥5) ranging from 54.2% mild, 21.8% moderate, and 8.4% severe. Conclusion The high false negative rate of the HST is alarming. Some providers and patients may forgo NPSG after non-diagnostic HST due to a lack of understanding for the HST’s limitations. Knowing that the non-diagnostic HST is a very poor predictor of no sleep apnea will help providers advise patients appropriately for the necessity of the NPSG. The subsequent NPSG provides an accurate diagnosis and, therefore, an informed decision about pursuing or eschewing sleep apnea treatment. Support none

scholarly journals SARS-CoV2 Testing: The Limit of Detection Matters

2020 ◽  
Author(s):  
Ramy Arnaout ◽  
Rose A. Lee ◽  
Ghee Rye Lee ◽  
Cody Callahan ◽  
Christina F. Yen ◽  
...  
Keyword(s):  
Limit Of Detection ◽  
Diagnostic Testing ◽  
False Negative ◽  
False Negative Rate ◽  
Fold Increase ◽  
Test Results ◽  
Rt Pcr ◽  
False Negatives ◽  
Healthcare Network ◽  
Negative Rate

AbstractResolving the COVID-19 pandemic requires diagnostic testing to determine which individuals are infected and which are not. The current gold standard is to perform RT-PCR on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of ~100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss more infected patients, resulting in more false negatives. However, the false-negative rate for a given LoD remains unknown. Here we address this question using over 27,500 test results for patients from across our healthcare network tested using the Abbott RealTime SARS-CoV-2 EUA. These results suggest that each 10-fold increase in LoD is expected to increase the false negative rate by 13%, missing an additional one in eight infected patients. The highest LoDs on the market will miss a majority of infected patients, with false negative rates as high as 70%. These results suggest that choice of assay has meaningful clinical and epidemiological consequences. The limit of detection matters.

scholarly journals The Effect of a Diverse Dataset for Transfer Learning in Thermal Person Detection

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1982 ◽  
Author(s):  
Noor Ul Huda ◽  
Bolette D. Hansen ◽  
Rikke Gade ◽  
Thomas B. Moeslund
Keyword(s):  
Transfer Learning ◽  
Privacy Preservation ◽  
False Negative ◽  
False Negative Rate ◽  
Model Adaptation ◽  
True Negative ◽  
True Negative Rate ◽  
Negative Rate ◽  
Thermal Cameras ◽  
The Impact

Thermal cameras are popular in detection for their precision in surveillance in the dark and for privacy preservation. In the era of data driven problem solving approaches, manually finding and annotating a large amount of data is inefficient in terms of cost and effort. With the introduction of transfer learning, rather than having large datasets, a dataset covering all characteristics and aspects of the target place is more important. In this work, we studied a large thermal dataset recorded for 20 weeks and identified nine phenomena in it. Moreover, we investigated the impact of each phenomenon for model adaptation in transfer learning. Each phenomenon was investigated separately and in combination. the performance was analyzed by computing the F1 score, precision, recall, true negative rate, and false negative rate. Furthermore, to underline our investigation, the trained model with our dataset was further tested on publicly available datasets, and encouraging results were obtained. Finally, our dataset was also made publicly available.

scholarly journals Introducing Bayesian Thinking to High-Throughput Screening for False-Negative Rate Estimation

2013 ◽  
Vol 18 (9) ◽  
pp. 1121-1131 ◽  
Author(s):  
Xin Wei ◽  
Lin Gao ◽  
Xiaolei Zhang ◽  
Hong Qian ◽  
Karen Rowan ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
False Negative ◽  
False Negative Rate ◽  
Training Data ◽  
Distribution Profile ◽  
False Negatives ◽  
Data Set ◽  
Active Compounds ◽  
Negative Rate

High-throughput screening (HTS) has been widely used to identify active compounds (hits) that bind to biological targets. Because of cost concerns, the comprehensive screening of millions of compounds is typically conducted without replication. Real hits that fail to exhibit measurable activity in the primary screen due to random experimental errors will be lost as false-negatives. Conceivably, the projected false-negative rate is a parameter that reflects screening quality. Furthermore, it can be used to guide the selection of optimal numbers of compounds for hit confirmation. Therefore, a method that predicts false-negative rates from the primary screening data is extremely valuable. In this article, we describe the implementation of a pilot screen on a representative fraction (1%) of the screening library in order to obtain information about assay variability as well as a preliminary hit activity distribution profile. Using this training data set, we then developed an algorithm based on Bayesian logic and Monte Carlo simulation to estimate the number of true active compounds and potential missed hits from the full library screen. We have applied this strategy to five screening projects. The results demonstrate that this method produces useful predictions on the numbers of false negatives.

scholarly journals FAST: a Flexible, Accurate and Speedy Test for COVID-19

2020 ◽  
Author(s):  
Linjiajie Fang ◽  
Bing-Yi Jing ◽  
Shen Ling ◽  
Qing Yang
Keyword(s):  
Close Contact ◽  
False Negative ◽  
Group Testing ◽  
False Negative Rate ◽  
Rt Pcr ◽  
False Negatives ◽  
Improve Efficiency ◽  
Negative Rate ◽  
Pcr Test

AbstractAs the COVID-19 pandemic continues worldwide, there is an urgent need to detect infected patients as quickly and accurately as possible. Group testing proposed by Technion [1][2] could improve efficiency greatly. However, the false negative rate (FNR) would be doubled. Using USA as an example, group testing would have over 70,000 false negatives, compared to 35,000 false negatives by individual testing.In this paper, we propose a Flexible, Accurate and Speedy Test (FAST), which is faster and more accurate than any existing tests. FAST first forms small close contact subgroups, e.g. families and friends. It then pools subgroups to form larger groups before RT-PCR test is done. FAST needs a similar number of tests to Technion’s method, but sharply reduces the FNR to a negligible level. For example, FAST brings down the number of false negatives in USA to just 2000, and it is seven times faster than individual testing.

scholarly journals LINKCALCULATOR – AN EFFICIENT LINK-BASED PHISHING DETECTION TOOL

2020 ◽  
Vol 4 (2) ◽  
pp. 37-44
Author(s):  
Orunsolu Abiodun ◽  
Sodiya A.S ◽  
Kareem S.O
Keyword(s):  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
True Positive Rate ◽  
True Negative ◽  
Negative Rate ◽  
Positive Rate ◽  
Link Information ◽  
Phishing Detection ◽  
Mobile Market

The problem of phishing attacks continues to demand new solutions as existing solutions are limited by various challenges such as high computational requirements, zero-day attacks, needs for updates, complex ruled-based, etc. Besides, the emerging mobile market demands simple solutions to phishing due to several factors such as memory, fragmentation, etc. In response to the above challenges, a simple anti-phishing tool called LinkCalculator is presented. The proposed LinkCalculator anti-phishing scheme is based on an algorithm designed to extract link characteristics from loading URLs to determine their legitimacy. Unlike the other link-based extraction approaches, the proposed approach introduced the concept of weight to represent the different links found in a URL. This is because certain link information within parsed webpages or requests is sufficient to classify them as phishing without loss of generality. The approach is experimented using a dataset of 300 instances consisting of 150 legitimate URLs and 150 phishing URLs from openly-available research datasets. The experimental results indicate a significance performance of 100%. True Negative Rate and 0.00% False Positive Rate for legitimate instances and True Positive Rate of 96.67% with 0.03 % False Negative Rate for phishing instances which indicate that the approach offers a more efficient lightweight approach to phishing detection.

scholarly journals An Efficient Adaptive Load Balancing Scheme for Mitigating Reduction of Quality-Based DDOS Attack on Cloud File Storage Environment

2019 ◽  
Vol 8 (4) ◽  
pp. 8450-8456
Keyword(s):  
Load Balancing ◽  
Hypothesis Test ◽  
False Negative ◽  
False Negative Rate ◽  
Statistical Testing ◽  
Detection Accuracy ◽  
True Negative ◽  
Ddos Attack ◽  
Negative Rate ◽  
Cloud Users

Availability of cloud resources to the cloud users is considered as the serious challenge that pose security essentialities during the process of on-demand service provision. Moreover, a specific type of attack named Reduction of Quality (RoQ)-based DDoS attack is determined to be vulnerable in the cloud computing since it exploits the benefits of the embedded adaptive load balancing and admission control methods of the environment. In this paper, an Efficient Adaptive Load Balancing Scheme-based on Wilcoxon–Mann–Whitney Hypothesis Test (EALBS-WMW-HT) is proposed for mitigating Reduction of Quality-based DDoS attack in order to minimize its influence for enhancing the degree of availability to the cloud users. This proposed EALBS-HT scheme uses the merits of statistical testing on the traffic flow and contributes to the detection of RoQ-based DDoS attack such that they does not disturb the inherent load balancing process of the cloud environment. The experiments of the proposed EALBS-HT scheme revealed an excellent detection accuracy, true positive rate and true negative rate with minimized false negative rate studied on par with the baseline approaches considered for analysis.

Clinically Meaningful Change

Methodology ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 97-105
Author(s):  
Rodrigo Ferrer ◽  
Antonio Pardo
Keyword(s):  
Effect Size ◽  
False Negative ◽  
False Negative Rate ◽  
Point Of View ◽  
Skewed Distribution ◽  
Effect Sizes ◽  
False Negatives ◽  
Large Size ◽  
Before And After ◽  
Post Test

Abstract. In a recent paper, Ferrer and Pardo (2014) tested several distribution-based methods designed to assess when test scores obtained before and after an intervention reflect a statistically reliable change. However, we still do not know how these methods perform from the point of view of false negatives. For this purpose, we have simulated change scenarios (different effect sizes in a pre-post-test design) with distributions of different shapes and with different sample sizes. For each simulated scenario, we generated 1,000 samples. In each sample, we recorded the false-negative rate of the five distribution-based methods with the best performance from the point of view of the false positives. Our results have revealed unacceptable rates of false negatives even with effects of very large size, starting from 31.8% in an optimistic scenario (effect size of 2.0 and a normal distribution) to 99.9% in the worst scenario (effect size of 0.2 and a highly skewed distribution). Therefore, our results suggest that the widely used distribution-based methods must be applied with caution in a clinical context, because they need huge effect sizes to detect a true change. However, we made some considerations regarding the effect size and the cut-off points commonly used which allow us to be more precise in our estimates.

Effects of Previous Surgery on the Detection of Sentinel Nodes in Women With Vulvar Cancer

2011 ◽  
Vol 21 (9) ◽  
pp. 1679-1683 ◽  
Author(s):  
Tessa A. Ennik ◽  
David G. Allen ◽  
Ruud L.M. Bekkers ◽  
Simon E. Hyde ◽  
Peter T. Grant
Keyword(s):  
Vulvar Cancer ◽  
False Negative ◽  
False Negative Rate ◽  
Blue Dye ◽  
Previous Surgery ◽  
Detection Rates ◽  
Reliable Technique ◽  
Appearance Time ◽  
Negative Rate ◽  
Significant Difference

BackgroundThere is a growing interest to apply the sentinel node (SN) procedure in the treatment of vulvar cancer. Previous vulvar surgery might disrupt lymphatic patterns and thereby decrease SN detection rates, lengthen scintigraphic appearance time (SAT), and increase SN false-negative rate. The aims of this study were to evaluate the SN detection rates at the Mercy Hospital for Women in Melbourne and to investigate whether previous vulvar surgery affects SN detection rates, SAT, and SN false-negative rate.MethodsData on all patients with vulvar cancer who underwent an SN procedure (blue dye, technetium, or combined technique) from November 2000 to July 2010 were retrospectively collected.ResultsSixty-five SN procedures were performed. Overall detection rate was 94% per person and 80% per groin. Detection rates in the group of patients who underwent previous excision of the primary tumor were not lower compared with the group without previous surgery or with just an incisional biopsy. There was no statistical significant difference in SAT between the previous excision group and the other patients. None of the patients with a false-negative SN had undergone previous excision.ConclusionsResults indicate that previous excision of a primary vulvar malignancy does not decrease SN detection rates or increase SN false-negative rate. Therefore, the SN procedure appears to be a reliable technique in patients who have previously undergone vulvar surgery. Previous excision did not significantly lengthen SAT, but the sample size in this subgroup analysis was small.

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