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PURPOSE - To use clinically measured reproducibility of volumetric CT (vCT) of lung nodules to estimate error in nodule growth rate in order to determine optimal scan interval for patient follow-up.
METHODS - We performed quantitative vCT on 89 stable non-calcified nodules and 49 calcified nodules measuring 3-13 mm diameter in 71 patients who underwent 3-9 repeat vCT studies for clinical evaluation of pulmonary nodules. Calculated volume standard deviation as a function of mean nodule volume was used to compute error in estimated growth rate. This error was then used to determine the optimal patient follow-up scan interval while fixing the false positive rate at 5%.
RESULTS - Linear regression of nodule volume standard deviation versus the mean nodule volume for stable non-calcified nodules yielded a slope of 0.057 ± 0.002 (r2 = 0.79, p<0.001). For calcified stable nodules, the regression slope was 0.052 ± 0.005 (r2 = 0.65, p = 0.03). Using this with the error propagation formula, the optimal patient follow-up scan interval was calculated to be 81 days, independent of initial nodule volume.
CONCLUSIONS - Reproducibility of vCT is excellent, and the standard error is proportional to the mean calculated nodule volume for the range of nodules examined. This relationship constrains statistical certainty of vCT calculated doubling times and results in an optimal scan interval that is independent of the initial nodule volume.
UNLABELLED - Quantification of β-amyloid (Aβ) in vivo is often accomplished using the distribution volume ratio (DVR), based on a simplified reference tissue model. We investigated the local relationships between DVR and cerebral blood flow (CBF), as well as relative CBF (R1), in nondemented older adults.
METHODS - Fifty-five nondemented participants (mean age, 78.5 y) in the Baltimore Longitudinal Study of Aging underwent (15)O-H2O PET CBF and dynamic (11)C-PiB PET. (15)O-H2O PET images were normalized and smoothed using SPM. A simplified reference tissue model with linear regression and spatial constraints was used to generate parametric DVR images. The DVR images were regressed on CBF images on a voxel-by-voxel basis using robust biologic parametric mapping, adjusting for age and sex (false discovery rate, P = 0.05; spatial extent, 50 voxels). DVR images were also regressed on R1 images, a measure of the transport rate constant from vascular space to tissue. All analyses were performed on the entire sample, and on high and low tertiles of mean cortical DVR.
RESULTS - Voxel-based analyses showed that increased DVR is associated with increased CBF in the frontal, parietal, temporal, and occipital cortices. However, this association appears to spare regions that typically show early Aβ deposition. A more robust relationship between DVR and CBF was observed in the lower tertile of DVR, that is, negligible cortical Aβ load, compared with the upper tertile of cortical DVR and Aβ load. The spatial distributions of the DVR-CBF and DVR-R1 correlations showed similar patterns. No reliable negative voxelwise relationships between DVR and CBF or R1 were observed.
CONCLUSION - Robust associations between DVR and CBF at negligible Aβ levels, together with similar spatial distributions of DVR-CBF and DVR-R1 correlations, suggest that regional distribution of DVR reflects blood flow and tracer influx rather than pattern of Aβ deposition in those with minimal Aβ load. DVR-CBF associations in individuals with a higher DVR are more likely to reflect true associations between patterns of Aβ deposition and CBF or neural activity. These findings have important implications for analysis and interpretation of voxelwise correlations with external variables in individuals with varying amounts of Aβ load.
© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.
CONTEXT - Although prostate cancer (PCa) screening reduces the incidence of advanced disease and mortality, trade-offs include overdiagnosis and resultant overtreatment.
OBJECTIVE - To review primary data on PCa overdiagnosis and overtreatment.
EVIDENCE ACQUISITION - Electronic searches were conducted in Cochrane Central Register of Controlled Trials, PubMed, and Embase from inception to July 2013 for original articles on PCa overdiagnosis and overtreatment. Supplemental articles were identified through hand searches.
EVIDENCE SYNTHESIS - The lead-time and excess-incidence approaches are the main ways used to estimate overdiagnosis in epidemiological studies, with estimates varying widely. The estimated number of PCa cases needed to be diagnosed to save a life has ranged from 48 down to 5 with increasing follow-up. In clinical studies, generally lower rates of overdiagnosis have been reported based on the frequency of low-grade minimal tumors at radical prostatectomy (1.7-46.8%). Autopsy studies have reported PCa in 18.5-38.5%, although not all are low grade or low volume. Factors influencing overdiagnosis include the study population, screening protocol, and background incidence, limiting generalizability between settings. Reported rates of overtreatment vary widely in the literature, although contemporary international studies suggest increasing use of conservative management.
CONCLUSIONS - Epidemiological, clinical, and autopsy studies have been used to examine PCa overdiagnosis, with estimates ranging widely from 1.7% to 67%. Correspondingly, estimates of overtreatment vary widely based on patient features and may be declining internationally. Careful patient selection for screening and reducing overtreatment are important to preserve the benefits and reduce the downstream harms of prostate-specific antigen testing. Because all of these estimates are extremely population and context specific, this must be considered when using these data to inform policy.
PATIENT SUMMARY - Screening reduces spread and death from prostate cancer (PCa) but overdiagnoses some low-risk tumors that may not have caused harm. Because treatment has potential side effects, it is critical that not all patients with PCa receive aggressive treatment.
Published by Elsevier B.V.
Safe use of tacrolimus relies on regular whole-blood drug monitoring. Of the methods used to assess whole-blood tacrolimus concentration, antibody-conjugated magnetic immunoassay is mostly used for therapeutic drug monitoring because it requires only a minimal sample preparation and no pretreatment procedure. However, several cases recently have been reported in which abnormally false elevated tacrolimus concentrations were measured by antibody-conjugated magnetic immunoassay (>15 ng/mL), despite the absence of clinical symptoms. We present 2 cases of falsely detected tacrolimus concentrations that did not show abnormally high values within the therapeutic range. Whole-blood tacrolimus concentrations obtained by antibody-conjugated magnetic immunoassay showed well-controlled concentrations (approximately 2-8 ng/mL), whereas those obtained by another immunoassay and in washed erythrocytes were below the assay range (< 1.2 ng/mL). Thus, antibody-conjugated magnetic immunoassay can elicit falsely positive results of tacrolimus concentrations, even though they are within the therapeutic range.
BACKGROUND - Various interferences can cause spurious results for common laboratory tests. Although rare, heterophilic antibodies may produce false elevations in PSA that could prompt unnecessary therapy in men previously treated for prostate cancer. The aim of this study was to determine the prevalence of small, spurious PSA elevations, and the role of heterophilic antibodies.
METHODS - Phase I: all PSA tests drawn and measured between 27 October 2008 and 26 October 2010 at Vanderbilt University Medical Center were analyzed (n=17 133). Patients who had been treated for prostate cancer with PSA values that changed from undetectable to detectable were evaluated. Phase II: patients with a detectable PSA ≤0.5 ng ml(-1) measured between 24 October 2010 and 19 January 2011 were studied prospectively (n=1288). If any patient had a previously undetectable PSA value, their serum was tested for heterophilic antibody interference.
RESULTS - Phase I: 11 men had a spuriously elevated PSA after curative treatment for prostate cancer (0.3%). Mean time to PSA elevation was 3.4±5.5 years, and mean elevation in PSA was 0.33±0.28 ng ml(-1). Each patient's PSA was undetectable after being repeated, and no patient went on to unnecessary treatment. Phase II: 10 men had a newly detectable PSA, 9 of whom had a history of prostate cancer. Each tested negative for interfering heterophilic antibodies when their PSA test was repeated with a heterophilic antibody-blocking reagent.
CONCLUSIONS - In a large cohort, we estimate the prevalence of spuriously elevated PSA values in our population to be 0.3%. No patient with a prostate cancer history was subjected to unnecessary diagnostic evaluation or treatment. On prospective evaluation of PSA conversion to low detectable levels, no patient had evidence of interfering heterophilic antibodies. When using PSA for post-treatment surveillance, it is crucial to confirm all concerning values and consider the presence of a spurious elevation in PSA if the value does not correlate with the clinical scenario.
BACKGROUND - The European Society of Cardiology (ESC) recently published revised criteria for ECG interpretation in the athlete.
OBJECTIVE - To examine the performance of the 2010 ESC ECG criteria in a population of athletes undergoing preparticipation cardiovascular disease screening.
METHODS - University athletes (n=508) underwent routine medical history/physical examination and ECG before athletic participation. Transthoracic echocardiography (TTE) was also performed on each participant to detect or exclude cardiac findings with relevance to sport participation. Screening test statistics were calculated to determine the performance of the 2010 ESC criteria, and the performance of the 2010 criteria was compared with the 2005 criteria.
RESULTS - Application of the 2010 ESC criteria, compared with the 2005 criteria, reduced the number of participants with abnormal ECG findings from 83/508 (16.3%) to 49/508 (9.6%). The reduction in the number of abnormal ECGs was driven by the reclassification of participants with isolated QRS voltage criteria for left ventricular hypertrophy from abnormal to normal. Of the 49 participants with abnormal ECGs, 14/49 (29%) had a single ECG abnormality and 35/49 (71%) had two or more abnormalities. The use of the 2010 criteria was associated with improved specificity (reduction in the false positive rate) and preserved sensitivity when compared with the 2005 criteria.
CONCLUSION - Application of the 2010 ESC criteria for ECG interpretation in the athlete improves the accuracy of an ECG-inclusive preparticipation screening strategy by reducing the rate of false positive ECGs.
BACKGROUND - MicroRNA regulate mRNA levels in a tissue specific way, either by inducing degradation of the transcript or by inhibiting translation or transcription. Putative mRNA targets of microRNA identified from seed sequence matches are available in many databases. However, such matches have a high false positive rate and cannot identify tissue specificity of regulation.
RESULTS - We describe a simple method to identify direct mRNA targets of microRNA dysregulated in cancers from expression level measurements in patient matched tumor/normal samples. The word "direct" is used here in a strict sense to: a) represent mRNA which have an exact seed sequence match to the microRNA in their 3'UTR, b) the seed sequence match is strictly conserved across mouse, human, rat and dog genomes, c) the mRNA and microRNA expression levels can distinguish tumor from normal with high significance and d) the microRNA/mRNA expression levels are strongly and significantly anti-correlated in tumor and/or normal samples. We apply and validate the method using clear cell Renal Cell Carcinoma (ccRCC) and matched normal kidney samples, limiting our analysis to mRNA targets which undergo degradation of the mRNA transcript because of a perfect seed sequence match. Dysregulated microRNA and mRNA are first identified by comparing their expression levels in tumor vs normal samples. Putative dysregulated microRNA/mRNA pairs are identified from these using seed sequence matches, requiring that the seed sequence be conserved in human/dog/rat/mouse genomes. These are further pruned by requiring a strong anti-correlation signature in tumor and/or normal samples. The method revealed many new regulations in ccRCC. For instance, loss of miR-149, miR-200c and mir-141 causes gain of function of oncogenes (KCNMA1, LOX), VEGFA and SEMA6A respectively and increased levels of miR-142-3p, miR-185, mir-34a, miR-224, miR-21 cause loss of function of tumor suppressors LRRC2, PTPN13, SFRP1, ERBB4, and (SLC12A1, TCF21) respectively. We also found strong anti-correlation between VEGFA and the miR-200 family of microRNA: miR-200a*, 200b, 200c and miR-141. Several identified microRNA/mRNA pairs were validated on an independent set of matched ccRCC/normal samples. The regulation of SEMA6A by miR-141 was verified by a transfection assay.
CONCLUSIONS - We describe a simple and reliable method to identify direct gene targets of microRNA in any cancer. The constraints we impose (strong dysregulation signature for microRNA and mRNA levels between tumor/normal samples, evolutionary conservation of seed sequence and strong anti-correlation of expression levels) remove spurious matches and identify a subset of robust, tissue specific, functional mRNA targets of dysregulated microRNA.
Microbiology results are reported in semi-structured formats and have a high content of useful patient information. We developed and validated a hybrid regular expression and natural language processing solution for processing blood culture microbiology reports. Multi-center Veterans Affairs training and testing data sets were randomly extracted and manually reviewed to determine the culture and sensitivity as well as contamination results. The tool was iteratively developed for both outcomes using a training dataset, and then evaluated on the test dataset to determine antibiotic susceptibility data extraction and contamination detection performance. Our algorithm had a sensitivity of 84.8% and a positive predictive value of 96.0% for mapping the antibiotics and bacteria with appropriate sensitivity findings in the test data. The bacterial contamination detection algorithm had a sensitivity of 83.3% and a positive predictive value of 81.8%.