Analysis of retest reliability for pregnant women undergoing cfDNA testing with a no-call result

BACKGROUND

Determining the reasons for unreportable or no-call cell-free DNA (cfDNA) test results has been an ongoing issue, and a consensus on subsequent management is still lacking. This study aimed to explore potential factors related to no-call cfDNA test results and to discuss whether retest results are reliable.

METHODS AND RESULTS

This was a retrospective study of women with singleton pregnancies undergoing cfDNA testing in 2021. Of the 9871 pregnant patients undergoing cfDNA testing, 111 had a no-call result, and their results were compared to those of 170 control patients. The no-call rate was 1.12% (111/9871), and the primary cause for no-call results was data fluctuation (88.29%, 98/111). Medical conditions were significantly more frequent in the no-call group than in the reportable results group (P < 0.001). After retesting, 107 (107/111, 96.40%) patients had a result, and the false-positive rate (FPR) of retesting was 10.09% (10.09%, 11/109). In addition, placental lesions were more frequent in the no-call group than in the reportable results group (P = 0.037), and 4 patients, all in the no-call group, experienced pregnancy loss.

CONCLUSIONS

Pregnant women with medical conditions are more likely to have a no-call result. A retest is suggested for patients with a no-call result, but retests have a high FPR. In addition, pregnant women with a no-call result are at increased risk of adverse pregnancy outcomes. In conclusion, more attention should be given to pregnant women for whom a no-call cfDNA result is obtained.

Objectivity for the research worker

In the last decade, many problematic cases of scientific conduct have been diagnosed; some of which involve outright fraud (e.g., Stapel, 2012) others are more subtle (e.g., supposed evidence of extrasensory perception; Bem, 2011). These and similar problems can be interpreted as caused by lack of scientific objectivity. The current philosophical theories of objectivity do not provide scientists with conceptualizations that can be effectively put into practice in remedying these issues. We propose a novel way of thinking about objectivity for individual scientists; a negative and dynamic approach.We provide a philosophical conceptualization of objectivity that is informed by empirical research. In particular, it is our intention to take the first steps in providing an empirically and methodologically informed inventory of factors that impair the scientific practice. The inventory will be compiled into a negative conceptualization (i.e., what is not objective), which could in principle be used by individual scientists to assess (deviations from) objectivity of scientific practice. We propose a preliminary outline of a usable and testable instrument for indicating the objectivity of scientific practice.

Hessian-MRLoG: Hessian information and multi-scale reverse LoG filter for pulmonary nodule detection

Computer-aided detection (CADe) of pulmonary nodules is an effective approach for early detection of lung cancer. However, due to the low contrast of lung computed tomography (CT) images, the interference of blood vessels and classifications, CADe has the problems of low detection rate and high false-positive rate (FPR). To solve these problems, a novel method using Hessian information and multi-scale reverse Laplacian of Gaussian (LoG) (Hessian-MRLoG) is proposed and developed in this work. Also, since the intensity distribution of the LoG operator and the lung nodule in CT images are inconsistent, and their shapes are mismatched, a multi-scale reverse Laplacian of Gaussian (MRLoG) is constructed. In addition, in order to enhance the effectiveness of target detection, the second-order partial derivatives of MRLoG are partially adjusted by introducing an adjustment factor. On this basis, the Hessian-MRLoG model is developed, and a novel elliptic filter is designed. Ultimately, in this study, the method of Hessian-MRLoG filtering is proposed and developed for pulmonary nodule detection. To verify its effectiveness and accuracy, the proposed method was used to analyze the LUNA16 dataset. The experimental results revealed that the proposed method had an accuracy of 93.6% and produced 1.0 false positives per scan (FPs/scan), indicating that the proposed method can improve the detection rate and significantly reduce the FPR. Therefore, the proposed method has the potential for application in the detection, localization and labeling of other lesion areas.

Relationship between antofloxacin concentration and QT prolongation and estimation of the possible false-positive rate

PURPOSE

To elucidate the relationship between antofloxacin (AT) plasma concentration and QT interval prolongation, compare the effects of different correction and analytical methods on conclusions, and estimate the possible false-positive rate in thorough QT (TQT) studies.

METHODS

Twenty-four healthy Chinese volunteers from a four-period crossover TQT study orally received 200 mg/d AT, 400 mg/d AT, 400 mg/d moxifloxacin, and a placebo in a random order for 5 d for each. QT interval samples were collected on d 1 and d 5. Population models were established describing the relationship between QT and AT concentration. The yardstick from ICH E14 guidelines was used to measure the effect of drugs on QT prolongation both in biostatistical and modeling analyses. A possible false-positive rate was estimated by constructing a 1000-time bootstrap to obtain the rate-of-difference values between d 1 and d 5 over 5 ms in the placebo period.

RESULTS

In the modeling analysis, the QT prolongation estimate at the mean maximal concentration of AT (4.51 μg/mL) was 3.84 ms, and its upper bound of the one-sided 95 % CI was 7.04 ms, which showed a negative effect on QT interval prolongation. The estimation for the false-positive rate was 31 % in this study.

CONCLUSION

The effect of AT on QT interval prolongation may not have been significant at the dosage of 400 mg. Baseline and placebo adjustments were necessary in TQT studies. Population modeling has demonstrated clear superiority in making full use of data to accurately analyze the relationship between drugs and QT intervals.

Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference

OBJECTIVES

To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests).

STUDY DESIGN AND SETTING

We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach.

RESULTS

We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction.

CONCLUSION

The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and specificity. Bayesian methods fully quantify uncertainty and their ability to incorporate external evidence may be useful for imprecisely estimated parameters.

Impacting the effect of fMRI noise through hardware and acquisition choices - Implications for controlling false positive rates

We review the components of time-series noise in fMRI experiments and the effect of image acquisition parameters on the noise. In addition to helping determine the total amount of signal and noise (and thus temporal SNR), the acquisition parameters have been shown to be critical in determining the ratio of thermal to physiological induced noise components in the time series. Although limited attention has been given to this latter metric, we show that it determines the degree of spatial correlations seen in the time-series noise. The spatially correlations of the physiological noise component are well known, but recent studies have shown that they can lead to a higher than expected false-positive rate in cluster-wise inference based on parametric statistical methods used by many researchers. Based on understanding the effect of acquisition parameters on the noise mixture, we propose several acquisition strategies that might be helpful reducing this elevated false-positive rate, such as moving to high spatial resolution or using highly-accelerated acquisitions where thermal sources dominate. We suggest that the spatial noise correlations at the root of the inflated false-positive rate problem can be limited with these strategies, and the well-behaved spatial auto-correlation functions (ACFs) assumed by the conventional statistical methods are retained if the high resolution data is smoothed to conventional resolutions.

False-Positive Error Rates for Reliable Digit Span and Auditory Verbal Learning Test Performance Validity Measures in Amnestic Mild Cognitive Impairment and Early Alzheimer Disease

OBJECTIVE

The objective is to examine failure on three embedded performance validity tests [Reliable Digit Span (RDS), Auditory Verbal Learning Test (AVLT) logistic regression, and AVLT recognition memory] in early Alzheimer disease (AD; n = 178), amnestic mild cognitive impairment (MCI; n = 365), and cognitively intact age-matched controls (n = 206).

METHOD

Neuropsychological tests scores were obtained from subjects participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

RDS failure using a ≤7 RDS threshold was 60/178 (34%) for early AD, 52/365 (14%) for MCI, and 17/206 (8%) for controls. A ≤6 RDS criterion reduced this rate to 24/178 (13%) for early AD, 15/365 (4%) for MCI, and 7/206 (3%) for controls. AVLT logistic regression probability of ≥.76 yielded unacceptably high false-positive rates in both clinical groups [early AD = 149/178 (79%); MCI = 159/365 (44%)] but not cognitively intact controls (13/206, 6%). AVLT recognition criterion of ≤9/15 classified 125/178 (70%) of early AD, 155/365 (42%) of MCI, and 18/206 (9%) of control scores as invalid, which decreased to 66/178 (37%) for early AD, 46/365 (13%) for MCI, and 10/206 (5%) for controls when applying a ≤5/15 criterion. Despite high false-positive rates across individual measures and thresholds, combining RDS ≤ 6 and AVLT recognition ≤9/15 classified only 9/178 (5%) of early AD and 4/365 (1%) of MCI patients as invalid performers.

CONCLUSIONS

Embedded validity cutoffs derived from mixed clinical groups produce unacceptably high false-positive rates in MCI and early AD. Combining embedded PVT indicators lowers the false-positive rate.

Confirmation rates of array-CGH in day-3 embryo and blastocyst biopsies for preimplantation genetic screening

PURPOSE

The purpose of this study was to compare the confirmation rate of day-3 embryo biopsy (blastomere) and trophectoderm biopsy using array-comparative genomic hybridization (array-CGH) technology.

METHODS

A blinded study was conducted to re-analyse 109 embryos previously diagnosed as chromosomally abnormal by array-CGH. Preimplantation genetic screening (PGS) was performed using array-CGH on day 3 (n = 50) or day 5 (n = 59). Partial chromosome gains or losses were excluded (n=6), and only whole chromosome aneuploidies were considered. Re-analysis of whole blastocysts was carried out following the same array-CGH protocol used for PGS.

RESULTS

The PGS result was confirmed in the whole blastocyst in (a) 49/50 (98 %) abnormal embryos after day-3 biopsy and (b) 57/59 (96.6 %) abnormal embryos after trophectoderm biopsy. One embryo (1/50; 2 %) was diagnosed as abnormal, with monosomy 18, on day 3, and software analysis of the whole blastocyst gave a euploid result; however, a mosaic pattern was observed for monosomy 18 in the whole blastocyst. Two trophectoderm biopsy cases (3.4 %) did not have the abnormalities (trisomy 7, and trisomy 1 and 4, respectively) verified in the whole embryo. Concordance rates for both biopsy strategies and for individual chromosomes were evaluated by Fisher's exact test and showed no significant differences.

CONCLUSIONS

Both types of biopsies showed similar high concordance rates with whole blastocyst results. Therefore, regarding the confirmation rates shown in this work, day-3 embryo biopsies can be representative of the whole embryo and both types of biopsy can be used for clinical analysis in PGS following the described array-CGH protocol.