Investigating the clinical usefulness of definitions of progression with 10-2 visual field

2021 ◽  
pp. bjophthalmol-2020-318188
Author(s):  
Shotaro Asano ◽  
Hiroshi Murata ◽  
Yuri Fujino ◽  
Takehiro Yamashita ◽  
Atsuya Miki ◽  
...  
Keyword(s):  
Visual Field ◽  
False Positive ◽  
False Positive Rate ◽  
Clinical Validity ◽  
Data Set ◽  
Humphrey Field Analyzer ◽  
Positive Rate ◽  
Using Data ◽  
Sensitivity Specificity ◽  
Higher Sensitivity

Background/AimTo investigate the clinical validity of the Guided Progression Analysis definition (GPAD) and cluster-based definition (CBD) with the Humphrey Field Analyzer 10-2 test in diagnosing glaucomatous visual field (VF) progression, and to introduce a novel definition with optimised specificity by combining the ‘any-location’ and ‘cluster-based’ approaches (hybrid definition).Methods64 400 stable glaucomatous VFs were simulated from 664 pairs of 10-2 tests (10 sets × 10 VF series × 664 eyes; data set 1). Using these simulated VFs, the specificity to detect progression and the effects of changing the parameters (number of test locations or consecutive VF tests, and percentile cut-off values) were investigated. The hybrid definition was designed as the combination where the specificity was closest to 95.0%. Subsequently, another 5000 actual glaucomatous 10-2 tests from 500 eyes (10 VFs each) were collected (data set 2), and their accuracy (sensitivity, specificity and false positive rate) and the time needed to detect VF progression were evaluated.ResultsThe specificity values calculated using data set 1 with GPAD and CBD were 99.6% and 99.8%. Using data set 2, the hybrid definition had a higher sensitivity than GPAD and CBD, without detriment to the specificity or false positive rate. The hybrid definition also detected progression significantly earlier than GPAD and CBD (at 3.1 years vs 4.2 years and 4.1 years, respectively).ConclusionsGPAD and CBD had specificities of 99.6% and 99.8%, respectively. A novel hybrid definition (with a specificity of 95.5%) had higher sensitivity and enabled earlier detection of progression.

scholarly journals Evaluation of optimal urine screening and confirmation cut-off values for opiates, at a national reference laboratory

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Çiğdem Karakükcü ◽  
Mehmet Zahid Çıracı ◽  
Derya Kocer ◽  
Mine Yüce Faydalı ◽  
Muhittin Abdulkadir Serdar
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
False Negative ◽  
Urine Samples ◽  
Reference Laboratory ◽  
National Reference Laboratory ◽  
Urine Screening ◽  
National Reference ◽  
Positive Rate ◽  
Sensitivity Specificity

Abstract Objectives To obtain optimal immunoassay screening and LC-MS/MS confirmation cut-offs for opiate group tests to reduce false positive (FP) and false negative (FN) rates. Methods A total of 126 urine samples, −50 opiate screening negative, 76 positive according to the threshold of 300 ng/mL by CEDIA method – were confirmed by a full-validated in-house LC-MS/MS method. Sensitivity, specificity, FP, and FN rates were determined at cut-off concentrations of both 300 and 2,000 ng/mL for morphine and codeine, and 10 ng/mL for heroin metabolite 6-mono-acetyl-morphine (6-MAM). Results All CEDIA opiate negative urine samples were negative for morphine, codeine and 6-MAM. Although sensitivity was 100% for each cut-off; specificity was 54.9% at CEDIA cut-off 300 ng/mL vs. LC-MS/MS cut-off 300 ng/mL and, 75% at CEDIA cut-off 2,000 ng/mL vs. LC-MS/MS cut-off 2,000 ng/mL. False positive rate was highest (45.1%) at CEDIA cut-off 300 ng/mL. At CEDIA cut-off 2,000 ng/mL vs. LC-MS/MS cut-off 300 ng/mL, specificity increased to 82.4% and FP rate decreased to 17.6%. All 6-MAM positive samples had CEDIA concentration ≥2,000 ng/mL. Conclusions 2,000 ng/mL for screening and 300 ng/mL for confirmation cut-offs are the most efficient thresholds for the lowest rate of FP opiate results.

scholarly journals A Study of the Diagnostic Accuracy of an Existing Multivariable Test to Predict Shoulder Dystocia

2019 ◽  
Vol 09 (03) ◽  
pp. e262-e267
Author(s):  
Henry Alexander Easley ◽  
Todd Michael Beste
Keyword(s):  
Diagnostic Accuracy ◽  
Prediction Model ◽  
Study Design ◽  
False Positive ◽  
False Positive Rate ◽  
Shoulder Dystocia ◽  
The Other ◽  
Predictive Values ◽  
Positive Rate ◽  
Sensitivity Specificity

Objectives To evaluate the diagnostic accuracy of a multivariable prediction model, the Shoulder Screen (Perigen, Inc.), and compare it with the American College of Obstetricians and Gynecologists (ACOG) guidelines to prevent harm from shoulder dystocia. Study Design The model was applied to two groups of 199 patients each who delivered during a 4-year period. One group experienced shoulder dystocia and the other group delivered without shoulder dystocia. The model's accuracy was analyzed. The performance of the model was compared with the ACOG guideline. Results The sensitivity, specificity, positive, and negative predictive values of the model were 23.1, 99.5, 97.9, and 56.4%, respectively. The sensitivity of the ACOG guideline was 10.1%. The false-positive rate of the model was 0.5%. The accuracy of the model was 61.3%. Conclusion A multivariable prediction model can predict shoulder dystocia and is more accurate than ACOG guidelines.

An approach to optimize delta checks in test panels – The effect of the number of rules included

2020 ◽  
Vol 57 (3) ◽  
pp. 215-222 ◽  
Author(s):  
Rui Zhen Tan ◽  
Corey Markus ◽  
Tze Ping Loh
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Original Data ◽  
Random Permutation ◽  
Full Blood Count ◽  
Hypothesis Tests ◽  
Data Set ◽  
Laboratory Results ◽  
Positive Rate ◽  
Common Laboratory

Objectives The interpretation of delta check rules in a panel of tests should be different to that at the single analyte level, as the number of hypothesis tests conducted (i.e. the number of delta check rules) is greater and needs to be taken into account. Methods De-identified paediatric laboratory results were extracted, and the first two serial results for each patient were used for analysis. Analytes were grouped into four common laboratory test panels consisting of renal, liver, bone and full blood count panels. The sensitivities and specificities of delta check limits as discrete panel tests were assessed by random permutation of the original data-set to simulate a wrong blood in tube situation. Results Generally, as the number of analytes included in a panel increases, the delta check rules deteriorate considerably due to the increased number of false positives, i.e. increased number hypothesis tests performed. To reduce high false-positive rates, patient results may be rejected from autovalidation only if the number of analytes failing the delta check limits exceeds a certain threshold of the total number of analytes in the panel (N). Our study found that the use of the ([Formula: see text] rule) for panel results had a specificity >90% and sensitivity ranging from 25% to 45% across the four common laboratory panels. However, this did not achieve performance close to some analytes when considered in isolation. Conclusions The simple [Formula: see text] rule reduces the false-positive rate and minimizes unnecessary, resource-intensive investigations for potentially erroneous results.

Is D2 surgery necessary for clinical T1 gastric cancer with nodal swelling?

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 288-288
Author(s):  
Takeyuki Wada ◽  
Takaki Yoshikawa ◽  
Ayako Kamiya ◽  
Keichi Date ◽  
Tsutomu Hayashi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
False Positive ◽  
False Positive Rate ◽  
False Positivity ◽  
Positive Rate ◽  
D2 Surgery ◽  
Sensitivity Specificity

288 Background: D2 surgery is required for clinical T1 gastric cancer with nodal swelling, however, D2 has a higher risk for morbidity than D1/D1+. Moreover, previous study demonstrated that the false positive rate for nodal diagnosis in clinical T1 was very high. To select optimal surgery with high probability, we explored risk factors for false positivity in clinical T1 disease. Methods: Patients who underwent radical gastrectomy for clinical T1 gastric cancer between April 2015 and June 2019 were enrolled. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for nodal diagnosis were retrospectively investigated. The risk factors for false positivity were also analyzed by the following factors; age, sex, histological type, tumor size, tumor depth, location, tumor type, presence of ulcer, and timing of CT that is (1) the patients who underwent primary endoscopic mucosal dissection (ESD) but resulted in non-curative resection, then received CT to proceed to surgery (delayed CT group) or (2) the other patients who had received CT before primary surgery or before non-curative ESD (primary CT group). Results: A total of 679 patients were examined in the present study. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 83.5% (567/679), 14.3% (13/91), 94.2% (554/588), 27.7% (13/47), and 87.7% (554/632), respectively. The false positive rate was 72.3% (34/47). In univariate analysis, differentiated tumor ( p= 0.012) and delayed CT (p < 0.001) were associated with the false positivity. Multivariate analysis revealed that delayed CT (OR, 4.534; p < 0.001) was a sole significant risk factor for false positivity. False positive rate was 100% (13/13) in the delayed CT group and 61.8% (21/34) in the primary CT group ( p= 0.009). Conclusions: False positive rate was high in clinical T1 disease, especially when the patients received delayed CT after non-curative ESD. D2 surgery would be unnecessary even though nodal swelling was detected in CT after non-curative ESD.

scholarly journals Evaluating the usefulness of breast strain elastography for intraductal lesions

2021 ◽  
Author(s):  
Yumi Kokubu ◽  
Keiko Yamada ◽  
Masahiko Tanabe ◽  
Ayumi Izumori ◽  
Chieko Kato ◽  
...  
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Intraductal Papilloma ◽  
Breast Diseases ◽  
Strain Elastography ◽  
Negative Rate ◽  
Positive Rate ◽  
Sensitivity Specificity

Abstract Purpose Strain elastography for imaging lesion stiffness is being used as a diagnostic aid in the malignant/benign discrimination of breast diseases. While acquiring elastography in addition to B-mode images has been reported to help avoid performing unnecessary biopsies, intraductal lesions are difficult to discriminate whether they are malignant or benign using elastography. An objective evaluation of strain in lesions was performed in this study by measuring the elasticity index (E-index) and elasticity ratio (E-ratio) of lesions as semi-quantitative numerical indicators of the color distribution of strain. We examined whether ductal carcinoma in situ (DCIS) and intraductal papilloma could be distinguished using these semi-quantitative numerical indicators. Methods In this study, 170 ultrasonographically detected mass lesions in 162 cases (106 malignant lesions and 64 benign lesions)—in which tissue biopsy by core needle biopsy and vacuum-assisted biopsy, or surgically performed histopathological diagnosis, was performed—were selected as subjects from among 1978 consecutive cases (from January 2014 to December 2016) in which strain elastography images were acquired, in addition to standard B-mode breast ultrasonography, by measuring the E-index and E-ratio. Results The cut-off values for E-index and E-ratio in the malignant/benign discrimination of breast lesions were determined to be optimal values at 3.5 and 4.2, respectively, based on receiver operating characteristic (ROC) curve analysis. E-index sensitivity, specificity, accuracy, and AUC value (area under the curve) were 85%, 86%, 85%, and 0.860, respectively, while those for E-ratio were 78%, 74%, 74%, and 0.780, respectively. E-index yielded superior results in all aspects of sensitivity, specificity, accuracy, and AUC values, compared to those of E-ratio. The mean E-index values for malignant tumors and benign tumors were 4.46 and 2.63, respectively, indicating a significant difference (P < 0.001). E-index values of 24 DCIS lesions and 25 intraductal papillomas were 3.88 and 3.35, respectively, which showed a considerably close value, while the false-negative rate for DCIS was 29.2%, and the false-positive rate for intraductal papilloma was as high as 32.0%. Conclusion E-index in strain elastography yielded better results than E-ratio in the malignant/benign discrimination of breast diseases. On the other hand, E-index has a high false-negative rate and false-positive rate for intraductal lesions, a factor which should be taken into account when making ultrasound diagnoses.

scholarly journals Does the Porter formula hold its promise? A weight estimation formula for macrosomic fetuses put to the test

2019 ◽  
Vol 301 (1) ◽  
pp. 129-135
Author(s):  
Christoph Weiss ◽  
Sabine Enengl ◽  
Simon Hermann Enzelsberger ◽  
Richard Bernhard Mayer ◽  
Peter Oppelt
Keyword(s):  
Clinical Practice ◽  
False Positive ◽  
False Positive Rate ◽  
Normal Weight ◽  
Fetal Weight ◽  
Weight Estimation ◽  
Data Set ◽  
Detection Rates ◽  
Estimation Formula ◽  
Positive Rate

Abstract Purpose Estimating fetal weight using ultrasound measurements is an essential task in obstetrics departments. Most of the commonly used weight estimation formulas underestimate fetal weight when the actual birthweight exceeds 4000 g. Porter et al. published a specially designed formula in an attempt to improve detection rates for such macrosomic infants. In this study, we question the usefulness of the Porter formula in clinical practice and draw attention to some critical issues concerning the derivation of specialized formulas of this type. Methods A retrospective cohort study was carried out, including 4654 singleton pregnancies with a birthweight ≥ 3500 g, with ultrasound examinations performed within 14 days before delivery. Fetal weight estimations derived using the Porter and Hadlock formulas were compared. Results Of the macrosomic infants, 27.08% were identified by the Hadlock formula, with a false-positive rate of 4.60%. All macrosomic fetuses were detected using the Porter formula, with a false-positive rate of 100%; 99.96% of all weight estimations using the Porter formula fell within a range of 4300 g ± 10%. The Porter formula only provides macrosomic estimates. Conclusions The Porter formula does not succeed in distinguishing macrosomic from normal-weight fetuses. High-risk fetuses with a birthweight ≥ 4500 g in particular are not detected more precisely than with the Hadlock formula. For these reasons, we believe that the Porter formula should not be used in clinical practice. Newly derived weight estimation formulas for macrosomic fetuses must not be based solely on a macrosomic data set.

scholarly journals Development of USI-Kit for Evaluation of Iodine Content in Iodized Salt

2020 ◽  
Vol 17 (10) ◽  
pp. 1149-1156
Author(s):  
Sakaewan OUNJAIJEAN ◽  
Kongsak BOONYAPRANAI ◽  
Kanokwan KULPRACHAKARN ◽  
Kittipan RERKASEM
Keyword(s):  
Spectrophotometric Method ◽  
False Positive ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Iodine Content ◽  
Kappa Coefficient ◽  
Test Kit ◽  
Positive Rate ◽  
Sensitivity Specificity

Iodine deficiency has been considered as a serious public health problem for the past decades. Universal salt iodization program is introduced and implemented to address such problem. To encourage this program in an effective and sustainable way, it is essential to regularly monitor whether salt is adequately iodized at various points along the supply chain. The traditional iodometric titration method has problems related to accessibility, cost, and time. Colorimetric test kits have been used extensively to measure coverage of iodized salt in household surveys due to its expediency and affordability. In Thailand, “I-KIT” is the most widely used. The visualization of intensive color, however, is inconvenient for untrained-user in determining the adequacy of iodine content. Thus, an improvement to make testing more precise and affordable is still required. In this respect, a new test kit namely USI-Kit was developed to assess iodine quality and semi-quantity in edible salt. The kit was tested to evaluate its performance, by comparing the result with the I-KIT and with the spectrophotometric method. Compared with I-Kit, the USI-Kit exerted the relative accuracy, sensitivity, specificity, false positive rate, false negative rate and Kappa coefficient value of 74.0, 76.3, 72.6, 27.4, 23.7 and 0.47, respectively. Compared to the spectrophotometric method, USI-Kit exerted the relative accuracy, sensitivity, specificity, false positive rate, false negative rate and Kappa coefficient value of 85.4, 80.1, 89.3, 10.7, 19.9 and 0.70, respectively. The finding suggested that a newly developed iodine test kit holds promise to be used in field inspection of iodine content in salt.

scholarly journals Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data

2020 ◽  
pp. 247255522095024
Author(s):  
Johanna Nyffeler ◽  
Derik E. Haggard ◽  
Clinton Willis ◽  
R. Woodrow Setzer ◽  
Richard Judson ◽  
...  
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Signal Strength ◽  
Distance Metrics ◽  
Data Set ◽  
Positive Rate ◽  
High Concordance ◽  
Screening Assays ◽  
Hit Identification ◽  
Global Fitting

Phenotypic profiling assays are untargeted screening assays that measure a large number (hundreds to thousands) of cellular features in response to a stimulus and often yield diverse and unanticipated profiles of phenotypic effects, leading to challenges in distinguishing active from inactive treatments. Here, we compare a variety of different strategies for hit identification in imaging-based phenotypic profiling assays using a previously published Cell Painting data set. Hit identification strategies based on multiconcentration analysis involve curve fitting at several levels of data aggregation (e.g., individual feature level, aggregation of similarly derived features into categories, and global modeling of all features) and on computed metrics (e.g., Euclidean and Mahalanobis distance metrics and eigenfeatures). Hit identification strategies based on single-concentration analysis included measurement of signal strength (e.g., total effect magnitude) and correlation of profiles among biological replicates. Modeling parameters for each approach were optimized to retain the ability to detect a reference chemical with subtle phenotypic effects while limiting the false-positive rate to 10%. The percentage of test chemicals identified as hits was highest for feature-level and category-based approaches, followed by global fitting, whereas signal strength and profile correlation approaches detected the fewest number of active hits at the fixed false-positive rate. Approaches involving fitting of distance metrics had the lowest likelihood for identifying high-potency false-positive hits that may be associated with assay noise. Most of the methods achieved a 100% hit rate for the reference chemical and high concordance for 82% of test chemicals, indicating that hit calls are robust across different analysis approaches.

scholarly journals Evaluation by Data Mining Techniques of Fluconazole Breakpoints Established by the Clinical and Laboratory Standards Institute (CLSI) and Comparison with Those of the European Committee on Antimicrobial Susceptibility Testing (EUCAST)

2010 ◽  
Vol 54 (4) ◽  
pp. 1541-1546 ◽  
Author(s):  
Isabel Cuesta ◽  
Concha Bielza ◽  
Manuel Cuenca-Estrella ◽  
Pedro Larrañaga ◽  
Juan L. Rodríguez-Tudela
Keyword(s):  
Roc Curve ◽  
False Positive ◽  
False Positive Rate ◽  
Predictor Variable ◽  
Original Cohort ◽  
Data Set ◽  
Supervised Classifiers ◽  
Positive Rate ◽  
Set Up ◽  
Simple Logistic

ABSTRACT The EUCAST and the CLSI have established different breakpoints for fluconazole and Candida spp. However, the reference methodologies employed to obtain the MICs provide similar results. The aim of this work was to apply supervised classification algorithms to analyze the clinical data used by the CLSI to establish fluconazole breakpoints for Candida infections and to compare these data with the results obtained with the data set used to set up EUCAST fluconazole breakpoints, where the MIC for detecting failures was >4 mg/liter, with a sensitivity of 87%, a false-positive rate of 8%, and an area under the receiver operating characteristic (ROC) curve of 0.89. Five supervised classifiers (J48 and CART decision trees, the OneR decision rule, the naïve Bayes classifier, and simple logistic regression) were used to analyze the original cohort of patients (Rex's data set), which was used to establish CLSI breakpoints, and a later cohort of candidemia (Clancy's data set), with which CLSI breakpoints were validated. The target variable was the outcome of the infections, and the predictor variable was the MIC or dose/MIC ratio. For Rex's data set, the MIC detecting failures was >8 mg/liter, and for Clancy's data set, the MIC detecting failures was >4 mg/liter, in close agreement with the EUCAST breakpoint (MIC > 4 mg/liter). The sensitivities, false-positive rates, and areas under the ROC curve obtained by means of CART, the algorithm with the best statistical results, were 52%, 18%, and 0.7, respectively, for Rex's data set and 65%, 6%, and 0.72, respectively, for Clancy's data set. In addition, the correlation between outcome and dose/MIC ratio was analyzed for Clancy's data set, where a dose/MIC ratio of >75 was associated with successes, with a sensitivity of 93%, a false-positive rate of 29%, and an area under the ROC curve of 0.83. This dose/MIC ratio of >75 was identical to that found for the cohorts used by EUCAST to establish their breakpoints (a dose/MIC ratio of >75, with a sensitivity of 91%, a false-positive rate of 10%, and an area under the ROC curve of 0.90).

scholarly journals The Use of an Activity Monitoring System for the Early Detection of Health Disorders in Young Bulls

Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 924 ◽  
Author(s):  
Mohammed Anouar Belaid ◽  
Maria Rodriguez-Prado ◽  
Eric Chevaux ◽  
Sergio Calsamiglia
Keyword(s):  
Early Detection ◽  
False Positive ◽  
False Positive Rate ◽  
False Negative ◽  
Clinical Signs ◽  
Activity Monitoring ◽  
Match Pair ◽  
Normal Behavior ◽  
Positive Rate ◽  
Sensitivity Specificity

Bulls (n = 770, average age = 127 days, SD = 53 days of age) were fitted with an activity monitoring device for three months to study if behavior could be used for early detection of diseases. The device measured the number of steps, lying time, lying bouts, and frequency and time of attendance at the feed bunk. All healthy bulls (n = 699) throughout the trial were used to describe the normal behavior. A match-pair test was used to assign healthy bulls for the comparison vs. sick bulls. The model was developed with 70% of the data, and the remaining 30% was used for the validation. Healthy bulls did 2422 ± 128 steps/day, had 28 ± 1 lying bouts/day, spent 889 ± 12 min/day lying, and attended the feed bunk 8 ± 0.2 times/d for a total of 95 ± 8 min/day. From the total of bulls enrolled in the study, 71 (9.2%) were diagnosed sick. Their activities changed at least 10 days before the clinical signs of disease. Bulls at risk of becoming sick were predicted 9 days before clinical signs with a sensitivity and specificity of 79% and 81%, respectively. The validation of the model resulted in a sensitivity, specificity, and accuracy of 92%, 42%, and 82 %, respectively, and a 50% false positive and 12.5% false negative rates. Results suggest that activity-monitoring systems may be useful in the early identification of sick bulls. However, the high false positive rate may require further refinement.

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