A Case of False Elevation of D-Dimer and Elimination Methods.

BACKGROUND: There are many methods for the detection of D-dimer in clinical laboratories. Immunoturbidimetric assays are widely used because of its high sensitivity and specificity [1-3]. However, this method may be affected by the interference of rheumatoid factor (RF), heterophilic antibodies, and other unknown proteins, and its falsity will increase, thus affecting clinical diagnosis. METHODS: This paper reports the cause analysis of a case of spurious D-dimer increase and four corresponding elimination methods: double dilution of the original specimen, detection of fibrin degradation product (FDP) level, addition of heterophilic blocking reagent, and comparison between different instruments. RESULTS: It was confirmed that there were special antibodies in the patient's body by four methods, which had non-specific reactions with D-dimer reagents, resulting in false increases of results. CONCLUSIONS: When the coagulation function results of patients show isolated increases in D-dimer, or the results are inconsistent with clinical symptoms, laboratory personnel should consider the possibility of interference factors, and conduct effective treatment to obtain correct test results, and thus reduce the occurrence of medical adverse events caused by inaccurate test results.

Clinical utility of dipstick urinalysis in assessing fitness to dive in military divers, submariners, and hyperbaric personnel.

Introduction: Routine dipstick urinalysis is part of many dive medical assessment protocols. However, this has a significant chance of producing false-positive or false-negative results in asymptomatic and healthy individuals. Studies evaluating the value of urinalysis in dive medical assessments are limited. Methods: All results from urinalysis as part of dive medical assessments of divers, submarines, and hyperbaric personnel of the Royal Netherlands Navy from 2013 to 2023 were included in this study. Additionally, any information regarding additional testing, referral, or test results concerning the aforementioned was collected. Results: There were 5,899 assessments, resulting in 46 (0.8%) positive dipstick urinalysis results, predominantly microscopic haematuria. Females were significantly overrepresented, and revisions resulted in significantly more positive test results than initial assessments. Lastly, almost half of the cases were deemed fit to dive, while the other half were regarded as temporarily unfit. These cases required additional testing, and a urologist was consulted three times. Conclusions: To our knowledge, this is the most extensive study evaluating urinalysis in dive medical assessments. In our military population, the incidence of positive test results is very low, and there have not been clinically relevant results over a period of 10 years. Therefore, routinely assessing urine in asymptomatic healthy military candidates is not cost-effective or efficacious. The authors advise taking a thorough history for fitness to dive assessments and only analysing urine when a clinical indication is present.

Impact of redefining statistical significance on P-hacking and false positive rates: An agent-based model.

In recent years, concern has grown about the inappropriate application and interpretation of P values, especially the use of P<0.05 to denote "statistical significance" and the practice of P-hacking to produce results below this threshold and selectively reporting these in publications. Such behavior is said to be a major contributor to the large number of false and non-reproducible discoveries found in academic journals. In response, it has been proposed that the threshold for statistical significance be changed from 0.05 to 0.005. The aim of the current study was to use an evolutionary agent-based model comprised of researchers who test hypotheses and strive to increase their publication rates in order to explore the impact of a 0.005 P value threshold on P-hacking and published false positive rates. Three scenarios were examined, one in which researchers tested a single hypothesis, one in which they tested multiple hypotheses using a P<0.05 threshold, and one in which they tested multiple hypotheses using a P<0.005 threshold. Effects sizes were varied across models and output assessed in terms of researcher effort, number of hypotheses tested and number of publications, and the published false positive rate. The results supported the view that a more stringent P value threshold can serve to reduce the rate of published false positive results. Researchers still engaged in P-hacking with the new threshold, but the effort they expended increased substantially and their overall productivity was reduced, resulting in a decline in the published false positive rate. Compared to other proposed interventions to improve the academic publishing system, changing the P value threshold has the advantage of being relatively easy to implement and could be monitored and enforced with minimal effort by journal editors and peer reviewers.

Strategic Retesting to Reduce False Positive SARS-CoV-2 PCR Test Results.

BACKGROUND: Nucleic acid amplification testing is the gold standard for SARS-CoV-2 diagnostics, although it may produce a certain number of false positive results. There has not been much published about the characteristics of false positive results. In this study, based on retesting, specimens that initially tested positive for SARS-CoV-2 were classified as true or false positive groups to characterize the distribution of cycle threshold (CT) values for N1 and N2 targets and number of targets detected for each group. METHODS: Specimens that were positive for N-gene on retesting and accompanied with S-gene were identified as true positives (true positive based on retesting, rTP), while specimens that retested negative were classified as false positives (false positive based on retesting, rFP). RESULTS: Of the specimens retested, 85/127 (66.9%) were rFP, 16/47 (34.0%) specimens with both N1 and N2 targets initially detected were rFP, and the CT values for each target was higher in rFP than in rTP. ROC curve analysis showed that optimal cutoff values of CT to differentiate between rTP and rFP were 34.8 for N1 and 33.0 for N2. With the optimal cutoff values of CT for each target, out of the 24 specimens that were positive for both N1 and N2 targets and classified as rTP, 23 (95.8%) were correctly identified as true positives. rFP specimens had a single N1 target in 52/61 (85.2%) and a single N2 target in 17/19 (89.5%). Notably, no true positive results were obtained from any specimens with only N2 target detected. CONCLUSIONS: These results suggest that retesting should be performed for positive results with a CT value greater than optimal cutoff value for each target or with a single N1 target amplified, considering the possibility of a false positive. This may provide guidance on indications to perform retesting to minimize the number of false positives.

Concept of a six-fold multiplex planar bioassay to distinguish endocrine agonist, antagonist, cytotoxic and false-positive responses.

To analyze a complex sample for endocrine activity, different tests must be performed to clarify androgen/estrogen agonism, antagonism, cytotoxicity, anti-cytotoxicity, and corresponding false-positive reactions. This means a large amount of work. Therefore, a six-fold planar multiplex bioassay concept was developed to evaluate up to the mentioned six endpoints or mechanisms simultaneously in the same sample analysis. Separation of active constituents from interfering matrix via high-performance thin-layer chromatography and effect differentiation via four vertical stripes (of agonists and end-products of the respective enzyme-substrate reaction) applied along each separated sample track were key to success. First, duplex endocrine bioassay versions were established. For the androgen/anti-androgen bioassay applied via piezoelectric spraying, the mean limit of biological detection of bisphenol A was 14 ng/band and its mean half maximal inhibitory concentration IC50 was 116 ng/band. Applied to trace analysis of six migrate samples from food packaging materials, 19 compound zones with agonistic or antagonistic estrogen/androgen activities were detected, with up to seven active compound zones within one migrate. For the first time, the S9 metabolism of endocrine effective compounds was studied on the same surface and revealed partial deactivation. Coupled to high-resolution mass spectrometry, molecular formulas were tentatively assigned to compounds, known to be present in packaging materials or endocrine active or previously unknown. Finally, the detection of cytotoxicity/anti-cytotoxicity and false-positives was integrated into the duplex androgen/anti-androgen bioassay. The resulting six-fold multiplex planar bioassay was evaluated with positive control standards and successfully applied to one migrate sample. The streamlined stripe concept for multiplex planar bioassays made it possible to assign different mechanisms to individual active compounds in a complex sample. The concept is generic and can be transferred to other assays.

Leveraging conformal prediction to annotate enzyme function space with limited false positives.

Machine learning (ML) is increasingly being used to guide biological discovery in biomedicine such as prioritizing promising small molecules in drug discovery. In those applications, ML models are used to predict the properties of biological systems, and researchers use these predictions to prioritize candidates as new biological hypotheses for downstream experimental validations. However, when applied to unseen situations, these models can be overconfident and produce a large number of false positives. One solution to address this issue is to quantify the model's prediction uncertainty and provide a set of hypotheses with a controlled false discovery rate (FDR) pre-specified by researchers. We propose CPEC, an ML framework for FDR-controlled biological discovery. We demonstrate its effectiveness using enzyme function annotation as a case study, simulating the discovery process of identifying the functions of less-characterized enzymes. CPEC integrates a deep learning model with a statistical tool known as conformal prediction, providing accurate and FDR-controlled function predictions for a given protein enzyme. Conformal prediction provides rigorous statistical guarantees to the predictive model and ensures that the expected FDR will not exceed a user-specified level with high probability. Evaluation experiments show that CPEC achieves reliable FDR control, better or comparable prediction performance at a lower FDR than existing methods, and accurate predictions for enzymes under-represented in the training data. We expect CPEC to be a useful tool for biological discovery applications where a high yield rate in validation experiments is desired but the experimental budget is limited.

Exact Integral Formulas for False Discovery Rate and the Variance of False Discovery Proportion.

Multiple hypothesis testing is an integral component of data analysis for large-scale technologies such as proteomics, transcriptomics, or metabolomics, for which the false discovery rate (FDR) and positive FDR (pFDR) have been accepted as error estimation and control measures. The pFDR is the expectation of false discovery proportion (FDP), which refers to the ratio of the number of null hypotheses to that of all rejected hypotheses. In practice, the expectation of ratio is approximated by the ratio of expectation; however, the conditions for transforming the former into the latter have not been investigated. This work derives exact integral expressions for the expectation (pFDR) and variance of FDP. The widely used approximation (ratio of expectations) is shown to be a particular case (in the limit of a large sample size) of the integral formula for pFDR. A recurrence formula is provided to compute the pFDR for a predefined number of null hypotheses. The variance of FDP was approximated for a practical application in peptide identification using forward and reversed protein sequences. The simulations demonstrate that the integral expression exhibits better accuracy than the approximate formula in the case of a small number of hypotheses. For large sample sizes, the pFDRs obtained by the integral expression and approximation do not differ substantially. Applications to proteomics data sets are included.

Improved PAA algorithm for breast mass detection in mammograms.

Mammography screening is instrumental in the early detection and diagnosis of breast cancer by identifying masses in mammograms. With the rapid development of deep learning, numerous deep learning-based object detection algorithms have been explored for mass detection studies. However, these methods often yield a high false positive rate per image (FPPI) while achieving a high true positive rate (TPR). To maintain a higher TPR while also ensuring lower FPPI, we improved the Probability Anchor Assignment (PAA) algorithm to enhance the detection capability for mammographic characteristics with our previous work. We considered three dimensions: the backbone network, feature fusion module, and dense detection heads. The final experiment showed the effectiveness of the proposed method, and the TPR/FPPI values of the final improved PAA algorithm were 0.96/0.56 on the INbreast datasets. Compared to other methods, our method stands distinguished with its effectiveness in addressing the imbalance between positive and negative classes in cases of single lesion detection.

Novel paradigm enables accurate monthly gestational screening to prevent congenital toxoplasmosis and more.

BACKGROUND: Congenital toxoplasmosis is a treatable, preventable disease, but untreated causes death, prematurity, loss of sight, cognition and motor function, and substantial costs worldwide. OBJECTIVES: We asked whether high performance of an Immunochromatographic-test (ICT) could enable accurate, rapid diagnosis/treatment, establishing new, improved care-paradigms at point-of-care and clinical laboratory. METHODS: Data were obtained in 12 studies/analyses addressing: 1-feasibility/efficacy; 2-false-positives; 3-acceptability; 4-pink/black-line/all studies; 5-time/cost; 6-Quick-Information/Limit-of-detection; 7, 8-acute;-chronic; 9-epidemiology; 10-ADBio; 11,12-Commentary/Cases/Chronology. FINDINGS: ICT was compared with gold-standard or predicate-tests. Overall, ICT performance for 1093 blood/4967 sera was 99.2%/97.5% sensitive and 99.0%/99.7% specific. However, in clinical trial, FDA-cleared-predicate tests initially caused practical, costly problems due to false-positive-IgM results. For 58 persons, 3/43 seronegative and 2/15 chronically infected persons had false positive IgM predicate tests. This caused substantial anxiety, concerns, and required costly, delayed confirmation in reference centers. Absence of false positive ICT results contributes to solutions: Lyon and Paris France and USA Reference laboratories frequently receive sera with erroneously positive local laboratory IgM results impeding patient care. Therefore, thirty-two such sera referred to Lyon's Reference laboratory were ICT-tested. We collated these with other earlier/ongoing results: 132 of 137 USA or French persons had false-positive local laboratory IgM results identified correctly as negative by ICT. Five false positive ICT results in Tunisia and Marseille, France, emphasize need to confirm positive ICT results with Sabin-Feldman-Dye-test or western blot. Separate studies demonstrated high performance in detecting acute infections, meeting FDA, CLIA, WHO REASSURED, CEMark criteria and patient and physician satisfaction with monthly-gestational-ICT-screening. CONCLUSIONS/SIGNIFICANCE: This novel paradigm using ICT identifies likely false positives or raises suspicion that a result is truly positive, rapidly needing prompt follow up and treatment. Thus, ICT enables well-accepted gestational screening programs that facilitate rapid treatment saving lives, sight, cognition and motor function. This reduces anxiety, delays, work, and cost at point-of-care and clinical laboratories. TRIAL REGISTRATION: NCT04474132, https://clinicaltrials.gov/study/NCT04474132 ClinicalTrials.gov.

Melting curve analysis reveals false-positive norovirus detection in a molecular syndromic panel.

BACKGROUND: Molecular syndromic panels can improve rapidity of results and ease clinical laboratory workflow, although caution has been raised for potential false-positive results. Upon implementation of a new panel for infectious diarrhea (BioFire® FilmArray® Gastrointestinal [GI] Panel, bioMérieux) in our clinical laboratory, a higher than expected number of stool samples with norovirus were detected. OBJECTIVES: The goal of this study was to investigate positive percent agreement and the false-positive rate of norovirus detected by the multiplex BioFire GI panel compared to a singleplex commercial assay. STUDY DESIGN: From October 2023 to January 2024, all prospective stool samples with a positive norovirus result by BioFire had melting curves reviewed manually using the BioFire FilmArray Torch System. Stool samples further underwent testing by a supplementary real-time RT-PCR assay (Xpert® Norovirus, Cepheid) for comparative analysis. RESULTS: Of the 50 stool samples with norovirus detected by BioFire, 18 (36 %) tested negative by Xpert (deemed "false-positives"). Furthermore, melting curve analysis revealed nearly all of these samples had atypical melting curve morphologies for the "Noro-1" target on BioFire (16/18, 89 %), which was statistically significant (Odds Ratio 173.2, 95 % CI [22.2, 5326.9], p < 0.0001). Stool samples with multiple pathogens detected by BioFire including norovirus were not more likely to produce false-positive norovirus results (Odds Ratio 1, 95 % CI [0.3, 3.3], p = 1). CONCLUSIONS: Although not described in the manufacturer's Instructions for Use, we propose routine manual review of melting curves for the BioFire GI panel prior to reporting, to mitigate potential false-positive norovirus results.

Fine needle aspiration diagnosis of benign oncocytic lesions of the head and neck associated with false positive 18F-fluorodeoxyglucose uptake on positron emission tomography scan.

INTRODUCTION: 18F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT) has become the mainstay for staging and post-therapy surveillance of cancer as malignant neoplasms generally demonstrate higher FDG uptake that benign entities. However, there are certain benign lesions, most notably oncocytic tumors, that can display very high uptake and fine needle aspiration (FNA) is usually done to confirm malignancy. Therefore, it is important to recognize that benign oncocytic lesions of the head and neck may also present as FDG-avid lesions to avoid a diagnostic pitfall. METHODS: Electronic search of institutional surgical and cytopathology archives was conducted to identify cases of benign oncocytic lesions involving the head and neck region diagnosed by FNA from January 2012 to April 2022. Chart review was used to assess whether lesions were initially discovered via PET scanning. RESULTS: One hundred and twenty-five cases of oncocytic lesions were identified; 12 (9%) PET positive lesions were identified in the head and neck region from patients being evaluated for metastasis or for suspicion of malignancy. Cytopathology of all 12 cases demonstrated benign oncocytic lesions; eight (67%) of these cases were consistent with Warthin tumor, one (8.3%) was a benign oncocytic lesion, and one (8.3%) was consistent wit a parathyroid adenoma. Most (58%) of the PET-positive lesions were in parotid region, two from thyroid gland (17%), one from submandibular gland (8%), one from paratracheal area (8%). The PET scan SUVs ranged from 3.3 to 19.5 g mL-1. CONCLUSIONS: Oncocytic lesions including Warthin tumors can result in false-positive FDG uptake on PET scans. Clinicians and cytopathologists should be aware of PET-positive benign oncocytic head and neck lesions.

A 14-year-old girl with premature ovarian insufficiency but with a positive pregnancy test.

OBJECTIVES: Childhood cancer survivors are at risk for premature ovarian insufficiency, especially after treatment with alkylating agents. The objective of this report is to highlight a case in which this phenomenon caused a false-positive pregnancy test. CASE PRESENTATION: A workup was performed in a 14-year-old girl with a positive pregnancy test. She was diagnosed with stage IV neuroblastoma of the left adrenal gland at the age of 4 years. She received extensive treatment, including alkylating agents, and had been diagnosed with premature ovarian insufficiency. An LH/hCG suppression test was performed using high dose 17 bèta-estradiol: hCG levels normalized. CONCLUSIONS: The pregnancy test was false-positive due to production of low amounts of hCG by the pituitary gland as a result of high LH concentrations following premature ovarian insufficiency. It may be helpful to perform the LH/hCG suppression test to prove pituitary origin of the hCG overproduction.

Reducing False-Positives Due to Urinary Stagnation in the Prostatic Urethra on 18 F-DCFPyL PSMA PET/CT With MRI.

PURPOSE: Prostate-specific membrane antigen (PSMA)-targeting PET radiotracers reveal physiologic uptake in the urinary system, potentially misrepresenting activity in the prostatic urethra as an intraprostatic lesion. This study examined the correlation between midline 18 F-DCFPyL activity in the prostate and hyperintensity on T2-weighted (T2W) MRI as an indication of retained urine in the prostatic urethra. PATIENTS AND METHODS: Eighty-five patients who underwent both 18 F-DCFPyL PSMA PET/CT and prostate MRI between July 2017 and September 2023 were retrospectively analyzed for midline radiotracer activity and retained urine on postvoid T2W MRIs. Fisher's exact tests and unpaired t tests were used to compare residual urine presence and prostatic urethra measurements between patients with and without midline radiotracer activity. The influence of anatomical factors including prostate volume and urethral curvature on urinary stagnation was also explored. RESULTS: Midline activity on PSMA PET imaging was seen in 14 patients included in the case group, whereas the remaining 71 with no midline activity constituted the control group. A total of 71.4% (10/14) and 29.6% (21/71) of patients in the case and control groups had urethral hyperintensity on T2W MRI, respectively ( P < 0.01). Patients in the case group had significantly larger mean urethral dimensions, larger prostate volumes, and higher incidence of severe urethral curvature compared with the controls. CONCLUSIONS: Stagnated urine within the prostatic urethra is a potential confounding factor on PSMA PET scans. Integrating PET imaging with T2W MRI can mitigate false-positive calls, especially as PSMA PET/CT continues to gain traction in diagnosing localized prostate cancer.

A Semiautonomous Deep Learning System to Reduce False Positives in Screening Mammography.

Purpose To evaluate the ability of a semiautonomous artificial intelligence (AI) model to identify screening mammograms not suspicious for breast cancer and reduce the number of false-positive examinations. Materials and Methods The deep learning algorithm was trained using 123 248 two-dimensional digital mammograms (6161 cancers) and a retrospective study was performed on three nonoverlapping datasets of 14 831 screening mammography examinations (1026 cancers) from two U.S. institutions and one U.K. institution (2008-2017). The stand-alone performance of humans and AI was compared. Human plus AI performance was simulated to examine reductions in the cancer detection rate, number of examinations, false-positive callbacks, and benign biopsies. Metrics were adjusted to mimic the natural distribution of a screening population, and bootstrapped CIs and P values were calculated. Results Retrospective evaluation on all datasets showed minimal changes to the cancer detection rate with use of the AI device (noninferiority margin of 0.25 cancers per 1000 examinations: U.S. dataset 1, P = .02; U.S. dataset 2, P < .001; U.K. dataset, P < .001). On U.S. dataset 1 (11 592 mammograms; 101 cancers; 3810 female patients; mean age, 57.3 years ± 10.0 [SD]), the device reduced screening examinations requiring radiologist interpretation by 41.6% (95% CI: 40.6%, 42.4%; P < .001), diagnostic examinations callbacks by 31.1% (95% CI: 28.7%, 33.4%; P < .001), and benign needle biopsies by 7.4% (95% CI: 4.1%, 12.4%; P < .001). U.S. dataset 2 (1362 mammograms; 330 cancers; 1293 female patients; mean age, 55.4 years ± 10.5) was reduced by 19.5% (95% CI: 16.9%, 22.1%; P < .001), 11.9% (95% CI: 8.6%, 15.7%; P < .001), and 6.5% (95% CI: 0.0%, 19.0%; P = .08), respectively. The U.K. dataset (1877 mammograms; 595 cancers; 1491 female patients; mean age, 63.5 years ± 7.1) was reduced by 36.8% (95% CI: 34.4%, 39.7%; P < .001), 17.1% (95% CI: 5.9%, 30.1%: P < .001), and 5.9% (95% CI: 2.9%, 11.5%; P < .001), respectively. Conclusion This work demonstrates the potential of a semiautonomous breast cancer screening system to reduce false positives, unnecessary procedures, patient anxiety, and medical expenses. Keywords: Artificial Intelligence, Semiautonomous Deep Learning, Breast Cancer, Screening Mammography Supplemental material is available for this article. Published under a CC BY 4.0 license.

Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Taqman PACMAN: a simple molecular approach for positive rapid antigen test confirmation during periods of low prevalence.

Antigen-based rapid diagnostic tests (Ag-RDTs) were widely deployed to enhance SARS-CoV-2 testing capacity during the COVID-19 pandemic. Consistent with national guidance for low prevalence settings, positive Ag-RDTs were confirmed using nucleic acid amplification tests (NAATs) to avoid false positive results. However, increasing demands for positive Ag-RDT confirmation competed with other testing priorities in clinical laboratories. This work hypothesized that real-time RT-PCR without nucleic acid extraction (NAE) would be sufficiently sensitive to support positive Ag-RDT confirmation. Ag-RDT and NAAT results from community-based asymptomatic testing sites prior to the omicron variant wave were compared to calculate the weekly false positive rate (FPR) and false detection rate (FDR). Real-time RT-PCR was compared with and without NAE using 752 specimens previously tested positive for SARS-CoV-2 using commercial NAATs and 344 specimens from Ag-RDT-positive individuals. The impact of SARS-CoV-2 prevalence on laboratory resources required to sustain Ag-RDT confirmation was modeled for the RT-PCR with and without NAE. Overall, FPR was low [0.07% (222/330,763)] in asymptomatic testing sites, but FDR was high [30.7% (222/724)]. When RT-PCR was compared with and without NAE, 100% concordance was obtained with NAAT-positive specimens, including those from Ag-RDT-positive individuals. NAE-free RT-PCR significantly reduced time to results, human resources, and overall costs. A 30.7% FDR reaffirms the need for NAAT-based confirmation of positive Ag-RDT results during low SARS-CoV-2 prevalence. NAE-free RT-PCR was shown to be a simple and cost-sparing NAAT-based solution for positive Ag-RDT confirmation, and its implementation supported data-driven broader Ag-RDT deployment into communities, workplaces, and households. IMPORTANCE: Rapid antigen testing for SARS-CoV-2 was widely deployed during the COVID-19 pandemic. In settings of low prevalence, national guidance recommends that positive antigen test results be confirmed with molecular testing. Given the high testing burden on clinical laboratories during the COVID-19 pandemic, the high volume of positive antigen tests submitted for confirmatory testing posed challenges for laboratory workflow. This study demonstrated that a simple PCR method without prior nucleic acid purification is an accurate and cost-effective solution for positive rapid antigen test confirmation. Implementing this method allowed molecular confirmatory testing for positive antigen tests to be sustained as antigen testing was expanded into large populations such as workplaces, schools, and households.