Accuracy of p53 codon 72 polymorphism status determined by multiple laboratory methods: a latent class model analysis

Estimation of diagnostic test accuracy: A "Rule of Three" for data with repeated observations but without a gold standard

This article considers how to estimate the accuracy of a diagnostic test when there are repeated observations, but without the availability of a gold standard or reference test. We identify conditions under which the structure of the observed data is rich enough to provide sufficient degrees of freedom, such that a suitable latent class model can be fitted with identifiable accuracy parameters. We show that a Rule of Three applies, specifying that accuracy can be evaluated as long as there are at least three observations per individual with the given test. This rule also applies if the three observations arise from combinations of different test methods, or from a sequential design in which individuals are tested for a maximum number of times with the same test but stopping if a positive (or negative) result occurs. The rule pertains to tests having an arbitrary number of response categories. Accuracy is evaluated by parameters reflecting rates of misclassification among the response categories, and the model also provides estimates of the underlying distribution of the true disease state. These ideas are illustrated by data from two medical studies. Issues discussed include the advantages and disadvantages of analyzing the response variable as binary or multinomial, as well as the feasibility of testing goodness of fit when the model incorporates a large number of parameters. Comparisons are possible between models that do or do not assume equal accuracy rates for the observations, and between models where certain misclassification parameters are or are not assumed to be zero.

Early Identification of Preterm Neonates at Birth With a Tablet App for the Simplified Gestational Age Score (T-SGAS) When Ultrasound Gestational Age Dating Is Unavailable: Protocol for a Validation Study

Background

Although rates of preterm birth continue to increase globally, identification of preterm from low birth weight infants remains a challenge. The burden of low birth weight vs preterm is greatest in resource-limited settings, where gestational age (GA) prior to delivery is frequently not known because ultrasound in early pregnancy is not available and estimates of the date of the mother’s last menstrual period (LMP) may not be reliable. An alternative option is to assess GA at birth to optimize referral and care of preterm newborns. We previously developed and pilot-tested a system to measure the simplified gestational age score (SGAS) based on 4 easily observable neonatal characteristics.

Objective

The objective of this study is to adapt the scoring system as a tablet app (potentially scalable approach) to assess feasibility of use and to validate whether the scoring system accurately predicts prematurity by itself, over and above birth weight in a large sample of newborns.

Methods

The study is based in Nagpur, India, at the Research Unit of the National Institute of Child Health and Human Development’s Global Network for Women’s and Children’s Health Research. The Android tablet app for the SGAS (T-SGAS) displays de-identified photographs of skin, breasts, and genitalia across a range of GAs and line drawings of infant posture. Each item is associated with a score. The user is trained to choose the photograph or line drawing that most closely matches the newborn being evaluated, and the app determines the neonate’s GA category (preterm or term) from the cumulative score. The validation study will be conducted in 3 second level care facilities (most deliveries in India occur in hospitals, and women known to be at risk of preterm birth are referred to second level care facilities). Within 24 hours of delivery, women and their babies who are stable will be enrolled in the study. Two auxiliary nurse midwives (ANMs) blinded to prior GA assessments will use the T-SGAS to estimate the GA status of the newborn. An independent data collector will abstract the GA from the ultrasound recorded in the hospital chart and record the date of the mother’s LMP. Eligibility for analysis is determined by the ultrasound and LMP data being collected within 1 week of each other to have a rigorous assessment of true GA.

Results

Publication of the results of the study is anticipated in 2019.

Conclusions

Until GA dating by ultrasound is universally available and easy to use in resource-limited settings, and where there are restrictions on ultrasound use due to their use for sex determination and abortion of female fetuses, this study will determine whether the T-SGAS app can accurately assess GA in risk categories at birth.

Trial Registration

ClinicalTrials.gov NCT02408783; https://clinicaltrials.gov/ct2/show/NCT02408783 (Archived by Webcite at http://www.webcitation.org/75S2kmr3T)

International Registered Report Identifier (IRRID)

DERR1-10.2196/11913

Impact of cause of death adjudication on the results of the European prostate cancer screening trial

BACKGROUND

The European Randomised Study of Prostate Cancer Screening has shown a 21% relative reduction in prostate cancer mortality at 13 years. The causes of death can be misattributed, particularly in elderly men with multiple comorbidities, and therefore accurate assessment of the underlying cause of death is crucial for valid results. To address potential unreliability of end-point assessment, and its possible impact on mortality results, we analysed the study outcome adjudication data in six countries.

METHODS

Latent class statistical models were formulated to compare the accuracy of individual adjudicators, and to assess whether accuracy differed between the trial arms. We used the model to assess whether correcting for adjudication inaccuracies might modify the study results.

RESULTS

There was some heterogeneity in adjudication accuracy of causes of death, but no consistent differential accuracy by trial arm. Correcting the estimated screening effect for misclassification did not alter the estimated mortality effect of screening.

CONCLUSIONS

Our findings were consistent with earlier reports on the European screening trial. Observer variation, while demonstrably present, is unlikely to have materially biased the main study results. A bias in assigning causes of death that might have explained the mortality reduction by screening can be effectively ruled out.

The adapter protein CD2AP binds to p53 protein in the cytoplasm and can discriminate its polymorphic variants P72R

Proline-rich motifs are widely distributed in eukaryotic proteomes and are usually involved in the assembly of functional complexes through interaction with specific binding modules. The tumour-suppressor p53 protein presents a proline-rich region that is crucial for regulating apoptosis by connecting the p53 with a complex protein network. In humans, a common polymorphism determines the identity of residue 72, either proline or arginine, and affects the features of the motifs present in the polyproline domain. The two isoforms have different biochemical properties and markedly influence cancer onset and progression. In this article, we analyse the binding of the p53 proline-rich region with a pool of selected polyproline binding domains (i.e. SH3 and WW), and we present the first demonstration that the purified SH3 domains of the CD2AP/Cin85 protein family are able to directly bind the p53 protein, and to discriminate between the two polymorphic variants P72R.