Hueso nasal como marcador de aneuploidías y resultado perinatal / Nasal bone as a marker of aneuploidies and perinatal outcome

Objetivo: Describir el resultado perinatal de los embarazos en función de la evaluación del hueso nasal como marcador de aneuploidía. Métodos: De 1006 embarazadas, 607 cumplieron con los criterios de inclusión para este estudio prospectivo, descriptivo, correlacional no causal donde se correlacionó la ausencia/presencia de hueso nasal con la presencia de síndrome de Down a través de cariotipo fetal prenatal y/o posnatal, así como examen clínico neonatal. Los datos fueron analizados mediantes frecuencias absolutas, porcentajes, capacidad diagnóstica del hueso nasal (índice de Youden), sensibilidad, especificidad, valor predictivo positivo, valor predictivo negativo y cocientes de probabilidad, positivo y negativo. Resultados: La prevalencia de síndrome de Down fue de 1,48 %, la ausencia del hueso nasal como marcador aislado, obtuvo un índice de Youden de 0,55 (0,23 - 0,88), sensibilidad de 55,56 %, especificidad de 99,50 %, valor predictivo positivo de 62,5 %, valor predictivo negativo de 99,33 %, cocientes de probabilidad positivo (hueso nasal ausente) 111 (IC 95 % 31 - 394) y cocientes de probabilidad negativo (hueso nasal presente) de 0,45 (IC 95 % 0,22 -0,93). Conclusión: La ausencia de hueso nasal en primer trimestre aumenta el riesgo de síndrome de Down en 111 veces y la presencia del mismo lo disminuye, sin valor como prueba diagnóstica sino de pesquisa debe considerarse como un marcador secundario(AU)

Objective: To know the perinatal outcome based on nasal bone evaluation as an aneuploidy marker. Methods: From 1006 pregnant women, 607 met the inclusion criteria for this prospective, descriptive, correlational not causal research correlating nasal bone absence / presence with Down syndrome through prenatal / postnatal fetal karyotype and neonatal clinical examination. Absolute frequencies and percentages, nasal bone performance as a diagnostic test (Youden índex), sensitivity, specificity, positive predictive value, negative predictive value, likelihood ratios positive and negative, were calculated. Results: 1.48 % was the Down syndrome prevalence on the sample. The nasal bone absence as an isolated marker obtained an 0,55 Youden index (0.23 to 0.88 ), sensitivity 55,56%, specificity 99,50%, positive predictive value 62,5%, negative predictive value 99,33%, likelihood ratios positive (absent nasal bone) 111, (95% CI 31-394) and likelihood ratios negative (nasal bone present ) 0,45 (95% CI 0 22 -0.93 ). Conclusion: The nasal bone absence in first trimester increases Down syndrome risk 111 times and nasal bone presence decreases it with poor performance as a diagnostic test, so it should be considered a screening test and a secondary marker. Recommendations correlate these results with other markers to improve detection rates and quantify nasal bone measurements in order to make nasal bone nomograms in first trimester pregnancies(AU)

Validation of the model medication adherence questionnaire to measure the adherence to oral medication among patients with type 2 diabetes mellitus in Sri Lanka

Background: The model medication adherence questionnaire (MMA) measures oral medication adherence among patients with type 2 diabetes (DM). The validity of the questionnaire needs to be objectively demonstrated. Methods: A descriptive cross-sectional study was carried out among adult patients with type 2 DM who attended clinics in District General Hospital (DGH) Gampaha. A sample of 150 patients was recruited consecutively to establish the criterion and construct validity. The criterion was the composite index of pill count, recital dosage and regular clinic attendance. Sensitivity and specificity with 95% confidence-intervals (CI) were established. Construct validity: convergent and discriminative, was assessed. Results were analyzed by Spearmen correlation and Man-Whitney-U test with p values. Results: The accuracy of the test was denoted by the area under the curve which is 0.87 (95% CI 0.81�93) with p<0.0001. The best cut-off point was 70. Patients who score >70 have good adherence to the medication while ?70 have average adherence. This has a sensitivity of 92.9% (95% CI 85.5�.9%), a specificity of 72.5% (95% CI 58�.7%) with a misclassification rate of 14%. The positive likelihood ratio (LR) is 10.2. High positive LR (>10) represents that adherence is very likely in a person with a score >70. The negative likelihood ratio is 0.3 and is in the intermediate range. It suggests that a score <70 is suggestive but insufficient to rule out the non-adherence. The ideal cutoff to predict the optimum HbA1C of MMA is 67. Conclusions: MMA is a valid questionnaire to measure medication adherence.

Methods and Research Hotspots of Forensic Kinship Testing / 法医学杂志

Kinship testing is widely needed in forensic science practice. This paper reviews the definitions of common concepts, and summarizes the basic principles, advantages and disadvantages, and application scope of kinship analysis methods, including identity by state (IBS) method, likelihood ratio (LR) method, method of moment (MoM), and identity by descent (IBD) segment method. This paper also discusses the research hotspots of challenging kinship testing, complex kinship testing, forensic genetic genealogy analysis, and non-human biological samples.

Identification Strategy of Biological Half Sibling Relationship / 法医学杂志

OBJECTIVES@#To compare the application value of the likelihood ratio (LR) method and identity by state (IBS) method in the identification involving half sibling relationships, and to provide a reference for the setting of relevant standards for identification of half sibling relationship.@*METHODS@#(1) Based on the same genetic marker combinations, the reliability of computer simulation method was verified by comparing the distributions of cumulated identity by state score (CIBS) and combined full sibling index in actual cases with the distributions in simulated cases. (2) In different numbers of three genetic marker combinations, the simulation of full sibling, half sibling and unrelated individual pairs, each 1 million pairs, was obtained; the CIBS, as well as the corresponding types of cumulative LR parameters, were calculated. (3) The application value of LR method was compared with that of IBS method, by comparing the best system efficiency provided by LR method and IBS method when genetic markers in different amounts and of different types and accuracy were applied to distinguish the above three relational individual pairs. (4) According to the existing simulation data, the minimum number of genetic markers required to distinguish half siblings from the other two relationships using different types of genetic markers was estimated by curve fitting.@*RESULTS@#(1) After the rank sum test, under the premise that the real relationship and the genetic marker combination tested were the same, there was no significant difference between the simulation method and the results obtained in the actual case. (2) In most cases, under the same conditions, the system effectiveness obtained by LR method was greater than that by IBS method. (3) According to the existing data, the number of genetic markers required for full-half siblings and half sibling identification could be obtained by curve fitting when the system effectiveness reached 0.95 or 0.99.@*CONCLUSIONS@#When distinguishing half sibling from full sibling pairs or unrelated pairs, it is recommended to give preference to the LR method, and estimate the required number of markers according to the identification types and the population data, to ensure the identification effect.

Calculation of the Paternity Index for the Alleged Father Related to the Child's Mother / 法医学杂志

OBJECTIVES@#To derive the paternity index (PI) calculation formula of the alleged father (AF) when the AF is a relative (parent/child, siblings, grandparent/grandchild, uncle/nephew, first cousins) of the child's biological mother.@*METHODS@#For the case when the AF is related to the child's biological mother, the existence of the relationship in the numerator and denominator hypothesis of PI was considered. The genotype frequency of the AF was calculated by using the frequency formula in which the mother's genotype was considered, while the random male in the denominator was substituted as another relative of the mother's same rank. The PI calculation formula was derived to eliminate the effect of the relationship between AF and the child's biological mother.@*RESULTS@#When the AF and the biological mother have first, second and tertiary kinship, a more conservative PI was obtained from the PI calculation formula derived in this study compared with the PI calculation method which did not consider kinship.@*CONCLUSIONS@#The calculation method provided in this study can eliminate the effect of the relation of the AF and mother on the PI in incest cases, to obtain more accurate and conservative identification conclusions.

Calculation of Likelihood Ratios for Incest Cases Using IBD Patterns / 法医学杂志

OBJECTIVES@#To calculate the likelihood ratios of incest cases using identity by descent (IBD) patterns.@*METHODS@#The unique IBD pattern was formed by denoting the alleles from the members in a pedigree with a same digital. The probability of each IBD pattern was obtained by multiplying the prior probability by the frequency of non-IBD alleles. The pedigree likelihoods of incest cases under different hypotheses were obtained by summing all IBD pattern probabilities, and the likelihood ratio(LR) was calculated by comparing the likelihoods of different pedigrees.@*RESULTS@#The IBD patterns and the formulae of calculating LR for father-daughter incest and brother-sister incest were obtained.@*CONCLUSIONS@#The calculations of LR for incest cases were illustrated based on IBD patterns.

Application of Microhaplotypes in Sibling Kinship Testing / 法医学杂志

OBJECTIVES@#To investigate the efficacy of different numbers of microhaplotype (MH) loci and the introduction of different reference samples on the identification of full sibling, half sibling and differentiation between full sibling and half sibling kinships, and to explore the effect of changing mutation rate on sibling testing.@*METHODS@#First, a family map involving three generations was established, and four full sibling identification models, five half sibling identification models and five models distinguishing full and half siblings were constructed for different reference samples introduced. Based on the results of the previous study, two sets of nonbinary SNP-MH containing 34 and 54 loci were selected. Based on the above MH loci, 100 000 pairs of full sibling vs. unrelated individuals, 100 000 pairs of half sibling vs. unrelated individuals and 100 000 pairs of full sibling vs. half sibling were simulated based on the corresponding sibling kinship testing models, and the efficacy of each sibling kinship testing model was analyzed by the likelihood ratio algorithm under different thresholds. The mutant rate of 54 MH loci was changed to analyze the effect of mutation rate on sibling identification.@*RESULTS@#In the same relationship testing model, the systematic efficacy of sibling testing was positively correlated with the number of MH loci detected. With the same number of MH loci, the efficacy of full sibling testing was better than that of uncle or grandfather when the reference sample introduced was a full sibling of A, but there was no significant difference in the identification efficacy of the four reference samples introduced for full sibling and half sibling differentiation testing. In addition, the mutation rate had a slight effect on the efficacy of sibling kinship testing.@*CONCLUSIONS@#Increasing the number of MH loci and introducing reference samples of known relatives can increase the efficacy of full sibling testing, half sibling testing, and differentiation between full and half sibling kinships. The level of mutation rate in sibling testing by likelihood ratio method has a slight but insignificant effect on the efficacy.

Change point analysis of normal distribution based on the likelihood ratio principle and its application in the number of outpatients analysis / 中华地方病学杂志

Objective:The authors introduced the change point analysis of normal distribution based on the likelihood ratio principle, analyzed the number of outpatients in a hospital of Luohu District, Shenzhen, to provide scientific basis for rational allocation of health resources.Methods:The authors collected totally 636 number of outpatients' data from 8: 00 to 12: 00 a.m. at 48 time windows at 5 minutes intervals in a hospital of Luohu District, Shenzhen, and analyzed it with single change point analysis of simultaneous change of mean and variance, and discussed when the change point occurred.Results:The average number of outpatient was 13.250 0 for every time window, the change point occurred at 8: 50, the probability was 0.000 025, the average number of outpatient per 5 minutes from 8: 00 to 8: 50 was 7.000 0, the average number of outpatient per 5 minutes from 8: 50 to 12: 00 was 14.897 4, and the ratio of number of outpatients before and after the change point occurred was 1∶2.Conclusion:In the case of no need to determine the base period or compare the data, the change point analysis of normal distribution based on the principle of likelihood ratio provides a new way of statistical analysis and statistical monitoring for the rational allocation of health resources based on the number of patients.

Likelihood Ratio And Repertory: A Useful Tool To Update Our Repertories

Background:Homoeopathic Science is focusing on the scientific explanation regarding its medicinal action and prescriptions in language of Research and Methodology. Whenever the word Research is there in any area, statistics comes automatically for presentation of theresearch findings. Homoeopathy accepts various Statistical Methods in its research studies to show their efficacy in Medical Science. Likelihood ratio is one of the statistical tools that help Physicians to develop skill in diagnosis of the various disease conditions. In Homoeopathic Science, this tool is not only helpful in case management but also help us to update our Repertories with its scientific data obtained by various case studies. So, let’s explore this tool named Likelihood ratio and its utilityin Homoeopathic Tool named Repertory. Material And Methods:It is a type of analytical study with following inclusion and exclusion criteria.Inclusion criteria:Most frequently cited articles of likelihood ratio were included. Exclusion criteria: publications of article based on likelihood ratio before year 2000 AD were excluded from study.Result:Less than 9 articles with most frequent citation wereeligible for study. There was scarcityof data regarding likelihood ratio in Homoeopathic Science.Conclusion:Many research papersregarding utility of likelihood ratio and repertories are present in Homoeopathic world but still the concept is not able to put a great impact on Homoeopath’s mind.Acceptance of this tool may help us to improve our Homoeopathic practice as well as standards of our Homoeopathy in Medical Science.

Desempeño de biomarcadores de las imágenes con tensor de difusión en regiones tumorales del glioblastoma. Análisis exploratorio de datos mediante gráficos de zombie y pruebas de diagnóstico / Diffusion tensor imaging-derived biomarkers performance in glioblastoma tumor regions: exploratory data analysis using zombie plots and diagnostic tests

Resumen Introducción: Han sido reportados 11 biomarcadores de imágenes con tensor de difusión (DTI) en las regiones tumorales del glioblastoma. Objetivo: Comparar la eficacia de biomarcadores de glioblastoma mediante gráficos de zombie, que permiten la comparación simultánea en función de razones de verosimilitud. Métodos: Cohorte retrospectiva de 29 sujetos con glioblastoma a quienes se efectuó resonancia magnética cerebral de 3 T. Los eigenvalores mayor, intermedio y menor de ITD se utilizaron para calcular 11 biomarcadores en cinco regiones tumorales: sustancia blanca de apariencia normal (NAWM), edema proximal y distal, tumoral viable y necrosis. Las tablas de contingencia con resultados verdaderos y falsos positivos y negativos permitieron calcular gráficos de zombie basados en el factor de Bayes y pruebas diagnósticas previamente no reportadas. Resultados: Los biomarcadores DM, AF, q, L, Cl, Cp, AR actúan en la zona óptima para el diagnóstico de NAWM. Las regiones de edema proximal y distal, tejido tumoral que se realza con contraste y necrosis no poseen biomarcadores que las identifiquen en un nivel de rendimiento óptimo. Conclusiones: Los biomarcadores DM, AF, q, L, Cl, Cp, AR discriminan el tejido cerebral normal en la zona óptima, pero el rendimiento de otras regiones tumorales se ubica en las zonas de inclusión diagnóstica, exclusión diagnóstica y mediocre.

Abstract Introduction: Using diffusion tensor imaging (DTI), 11 biomarkers have been reported in different glioblastoma regions. Objective: To compare the efficacy of glioblastoma biomarkers using "zombie plots". Methods: Retrospective cohort of 29 subjects with glioblastoma who underwent 3-Tesla brain magnetic resonance imaging. DTI major, intermediate and minor eigenvalues were used to calculate biomarkers at five tumor regions: normal-appearing white matter (NAWM), proximal and distal edema, tumor tissue and necrosis. Contingency tables with true and false positive and negative results allowed the calculation of zombie plots based on the Bayes factor and previously unreported diagnostic tests. Results: The MD, FA, q, L, Cl, Cp and RA biomarkers had a good performance at the optimal zone for NAWM diagnosis. The proximal and distal edema, enhancing rim and necrosis regions do not have biomarkers that identify them with an optimal performance level. Conclusions: Zombie plots allow simultaneous comparison of biomarkers based on likelihood ratios. MD, FA, q, L, Cl, Cp, RA discriminated NAWM normal brain tissue at the optimal zone, but performance for other regions was at the mediocre, diagnostic inclusion and diagnostic exclusion zones.

Distribution characteristics of choroidal thickness in normal population and the diagnostic cut-off value for pachychoroid / 中华实验眼科杂志

Objective:To characterize the distribution characteristics of choroidal thickness in healthy normal subjects and to define the diagnostic cut-off value for pachychoroid.Methods:A cross-sectional study design was carried out.Four hundred and forty-six eyes of 230 healthy subjects from the pachychoroid disease spectrum (PCD) cohort in Beijing Tongren Hospital from April 2018 to June 2021, were enrolled for the choroidal thickness distribution analysis.Three hundred and fourteen eyes of 274 patients with PCD including 149 eyes of 113 patients with central serous chorioretinopathy, 95 eyes of 81 patients with polypoid choroidal vasculopathy, 70 eyes of 60 patients with neovascular age-related macular degeneration, along with 382 eyes of 199 normal subjects matched for refractive error, age and gender with PCD were selected for likelihood ratio analysis.Routine eye examinations including the best corrected visual acuity, intraocular pressure, slit-lamp microscopy, dilated fundus examination and color fundus photography were performed in all subjects.Swept-source optical coherence tomography (SS-OCT) of 9 mm×9 mm scanning mode was used to measure the subfoveal choroidal thickness (SFCT) automatically in nine macular regions according to the Early Treatment Diabetic Retinopathy Study classification system using TOPCON Advanced Boundary Segmentation (TABS) software.Pearson linear correlation analysis and Spearman rank correlation analysis were adopted to evaluate the correlations between SFCT and age, diopter.Multiple linear regression was employed to analyze the factors affecting SFCT.After age and refractive error adjustment, the likelihood ratio test was used to determine the diagnostic cut-off value for pachychoroid.This study adhered to the Declaration of Helsinki.The study protocol was approved by an Ethics Committee of Beijing Tongren Hospital (No.TRECKY2016-054). Written informed consent was obtained from each subject prior to entering the cohort.Results:A negative correlation was found between SFCT and age in normal eyes ( r=-0.34, P<0.001), in both normal male and female subjects ( r=-0.43, P<0.001; r=-0.38; P<0.001). A weak positive correlation was found between SFCT and diopter ( rs=0.19, P<0.001). It was found that age and diopter were strongly correlated with SFCT (both at P<0.001). The cut-off values for pachychoroid in 20-39 years group, 40-59 years group, 60-79 years group and ≥80 years group were 320-330 μm, 330-340 μm, 250-275 μm and 200-225 μm, respectively.The percentages of eyes with pachychoroid in 20-39 years group, 40-59 years group and ≥60 years group were 14.71%(10/68), 24.48%(47/192) and 28.89%(55/184), respectively, showing statistically significant differences among them ( χ2=6.170, P=0.046; LR=6.579, P=0.037). The proportion of pachychoroid in ≥60 years group was significantly higher than that of 20-39 years group, showing a statistically significant difference ( χ2=5.982, P=0.014; LR=6.479, P=0.011). Conclusions:The distribution characteristics of pachychoroid vary in normal subjects over age.Age and diopter are the independent influencing factors of SFCT.

Decisions on what diagnostic tests to request

@#In Evidence-based Family Practice, requesting a diagnostic test should be based on two issues. First is whether the test is accurate and thus will significantly help in clinical decision making. Second is whether the test is appropriate and acceptable for the patient. This involves careful discussion of risks and benefits based on the physician’s knowledge and experience and the patient’s values and preferences.

Niveles de ferritina en artritis idiopática juvenil de inicio sistémico comparada con otras fiebres de origen desconocido: estudio multicéntrico de pruebas diagnósticas / Ferritin levels in children with juvenile idiopathic arthritis of systemic onset and children with other causes of fever of unknown origin: A multicenter study of diagnostic tests

Resumen | Introducción. No se dispone de pruebas sensibles ni específicas para diagnosticar la artritis idiopática juvenil sistémica. Objetivo. Evaluar la utilidad diagnóstica de niveles de ferritina total cinco veces por encima del valor normal (ferritina total>5N) y el porcentaje disminuido (menor de o igual a 20 % de la ferritina total) de la ferritina glucosilada (ferritina glucosilada<20 %) para el diagnóstico de artritis idiopática juvenil sistémica en pacientes con fiebre de origen desconocido evaluados por reumatología pediátrica. Materiales y métodos. Se hizo un estudio observacional de pruebas diagnósticas de corte transversal en menores de 16 años hospitalizados entre el 2010 y el 2014. El patrón diagnóstico de referencia fue el cumplimiento de los criterios de clasificación o diagnóstico confirmado en el seguimiento. Se determinaron las medidas de utilidad de las pruebas. Resultados. Se incluyeron 40 pacientes con fiebre de origen desconocido: 11 con artritis idiopática juvenil sistémica y 29 con otros diagnósticos. La mediana de la ferritina total fue mayor en la artritis idiopática juvenil sistémica (3.992 ng/ml) comparada con otras causas de fiebre de origen desconocido (155 ng/ml) (p=0,0027), así como la ferritina total>5N (90,91 % Vs. 51,72 %) (p=0,023). El porcentaje de ferritina glucosilada≤20 % fue de 96,5 % en otras fiebres de origen desconocido en comparación con la artritis idiopática juvenil sistémica (81,8 %) (p=0,178). La ferritina total>5N tuvo una sensibilidad del 91 %, una especificidad del 48 %; un cociente de probabilidades (Likelihood Ratio, LR) positivo de 1,76 y uno negativo de 0,19, demostrando mayor utilidad para el diagnóstico que la combinación de la ferritina total>5N y ferritina glucosilada≤20 %, cuya sensibilidad fue del 81,8 %, la especificidad del 48,3 %, un cociente de probabilidades LR positivo de 1,58 y un LR negativo de 0,38. Conclusión. En pacientes con fiebre de origen desconocido evaluados por reumatología pediátrica, la ferritina total>5N demostró ser útil como prueba de tamización para el diagnóstico de artritis idiopática juvenil sistémica.

Abstract | Introduction: There are no sensitive or specific tests available to diagnose systemic juvenile idiopathic arthritis (sJIA). Objective: To assess the utility as diagnostic tests of total ferritin (TF) levels greater than 5 times the normal value (TF>5N) and the decreased percentage (less than or equal to 20% of TF) of glycosylated ferritin (GF≤20%) for the diagnosis of sJIA in patients with fever of unknown origin evaluated by pediatric rheumatology. Materials and methods: We conducted an observational, cross-sectional study of diagnostic tests in children under 16 years of age hospitalized between 2010 and 2014. The reference diagnostic standard was the fulfillment of the classification criteria or confirmed diagnosis at follow-up. We determined the measures of utility of the tests. Results: We included 40 patients with fever of unknown origin, 11 with sJIA, and 29 with other diagnoses. The median TF was higher in sAIJ (3992 ng/ml) versus other causes of fever of unknown origin (155 ng/ml) (p=0.0027), as well as TF>5N (90.91% versus 51.72%) (p=0.023). The percentage of GF≤20% was higher in patients with other causes of fever of unknown origin (96.5%) compared to sJIA (81.8%) (p=0.178). TF>5N had a sensitivity of 91%, specificity of 48%, positive likelihood ratio (LR) of 1.76, and negative LR of 0.19 demonstrating greater utility for the diagnosis of sJIA than the combination of FT> 5N with GFR <20%, with a sensitivity of 81.8%, specificity of 48.3%, positive LR of 1.58, and negative LR of 0.38. Conclusion: In patients with FUO evaluated by pediatric rheumatology, TF> 5N proved useful as a screening test for the diagnosis of sJIA.

Pruebas diagnósticas: Razones de probabilidad / Diagnostic tests: Probability Ratios

La utilidad de una prueba diagnóstica se cuantifica mediante el cálculo de las medidas de probabilidad y las medidas de razones de probabilidad. Las medidas de probabilidad son la sensibilidad, la especificidad, valor predictivo positivo y el valor predictivo negativo. La sensibilidad y la especificidad se usan para escoger la mejor prueba a utilizar, entre varias disponibles; sin embargo, no pueden ser utilizadas para estimar la probabilidad de determinada enfermedad en un paciente en particular. En la práctica clínica es esencial saber cuál es la probabilidad de que un paciente con un resultado positivo en una prueba diagnóstica presente la enfermedad y cuál es la probabilidad de que un paciente con un resultado negativo en una prueba diagnóstica no presente la enfermedad. Los valores predictivos positivos y negativos nos brindan la respuesta a esta cuestión, sin embargo, dependen tanto de la sensibilidad y especificidad, como de la prevalencia de la enfermedad en la muestra del estudio. Las medidas de razones de probabilidad también describen el rendimiento o utilidad de una prueba diagnóstica y poseen dos propiedades importantes: resumen el mismo tipo de información que la sensibilidad y la especificidad, y pueden utilizarse para calcular la probabilidad de la enfermedad después de una prueba positiva o negativa. El propósito de esta publicación fue definir el concepto de razones de probabilidad, exponer sus principales fortalezas y explicar cómo se calculan las razones de probabilidad cuando la prueba de interés expresa sus resultados en forma dicotómica, en más de dos categorías o de forma ordinal

The usefulness of a diagnostic test is quantified by calculating the probability measures and the probability ratio measures. Probability measures are sensitivity, specificity, positive predictive value, and negative predictive value. Sensitivity and specificity are used to choose the best test to use, among several available; however, they cannot be used to estimate the probability of a certain disease in a particular patient. In clinical practice it is essential to know what is the probability that a patient with a positive result in a diagnostic test will present the disease and what is the probability that a patient with a negative result in a diagnostic test will not present the disease. The positive and negative predictive values provide us with the answer to this question, however, it depends both on the sensitivity and specificity, and on the prevalence of the disease in the study sample. Probability ratio measures also describe the performance or usefulness of a diagnostic test and possess two important properties: they summarize the type of information that sensitivity and specificity, and they can be used to calculate the probability of disease after a positive or positive test. negative. The purpose of this publication was to define the concept of probability ratio measures, expose its main strengths, and explain how probability ratio measures are calculated when the test of interest expresses its results dichotomously, in more than two categories or ordinally

How to use χ2 test correctly——the likelihood ratio test and the implementation of SAS software / 四川精神卫生

The purpose of this article was to introduce the likelihood ratio test and the SAS implementation. Specifically， three definitions of the likelihood ratio test statistics and six more commonly used likelihood ratio test statistics were introduced. The three definitions were called based on the spatial size of the parameter vector to construct the likelihood ratio test statistic， based on the two nested statistical models to construct the likelihood ratio test statistic and based on the full model and partial model to construct the likelihood ratio test statistic； the six commonly used likelihood ratio test statistics were the general likelihood ratio χ2 test statistic，the adjusted likelihood ratio χ2 test statistic，the profile likelihood ratio χ2 test statistic，the quasi-likelihood ratio χ2 test statistic，the pseudo-likelihood ratio χ2 test statistic，and the Rao-Scott likelihood ratio χ2 test statistic. In the paper， through two examples， and with the help of the SAS software， the likelihood ratio χ2 tests were realized， the SAS calculation results were output and explained， and statistical and professional conclusions were made.

How to use χ2 test correctly——the likelihood ratio test and the six nonparametric tests of the survival data and the implementation of the SAS software / 四川精神卫生

The purpose of this article was to introduce the likelihood ratio test， six nonparametric tests， and the SAS implementation of the survival data. Based on the assumption that the survival data had the exponential distribution， the likelihood ratio test method was derived， the main difference between six nonparametric test methods was that they had different weight functions. Under the conditions of non-stratification and stratification， the seven survival data hypothesis testing methods mentioned above could be used， and their common point was that their test statistics all followed the χ2 distribution. Through two examples and by means of the SAS software， the article realized the various hypothesis tests for two or more groups of survival data， outputed and explained SAS calculation results， and made statistical and professional conclusions.

How to use χ2 test correctly—— the goodness of fit tests and the implementation of the SAS software / 四川精神卫生

The purpose of this article was to introduce the goodness of fit test and its SAS implementation. The main contents included the following four aspects： ① Pearson΄s goodness of fit test； ② deviance or likelihood ratio goodness of fit test； ③ Hosmer-Lemeshow goodness of fit test； ④ goodness of fit test for the sparse data. In the aforementioned “fourth aspect”， there were six specific test approaches， namely “information matrix test” “information matrix diagonal test” “Osius-Rojek test” “unweighted residual sum of squares test” “Spiegelhalter test” and “Stukel test”. The paper implemented the four types of the goodness of fit tests mentioned above with the help of the SAS software through an example， explained the output results， and made statistical and professional conclusions.

How to use χ2 test correctly—— χ2 test for the data of four-fold tables collected from the cross-sectional design / 四川精神卫生

The purpose of this article was to introduce the χ2 test for the data of four-fold tables collected from the cross-sectional design and the realization of SAS and R software. Specifically， three methods were introduced， namely " Pearson΄s χ2 test"， "corrected Pearson΄s χ2 test" and "likelihood ratio χ2 test". The contents involved the test hypotheses， calculation principles and formulas， prerequisites， implementation of SAS and R software， interpretation of results and statement of conclusions of the aforementioned three statistical analysis methods.

Application of ITO Method in Determination of Special Half-Sibling Relationship / 法医学杂志

OBJECTIVES@#To identify whether the relationship between Zhang A, Zhang B, Zhang C and Zhang X is the half-sibling relationship whose mother is sister (hereinafter referred to as the special half-sibling relationship) or the common first cousin relationship and discuss the application of ITO method in discriminating the special kinship.@*METHODS@#DNA was extracted from blood stain of four identified individuals, PowerPlex® 21 System and AGCU 21+1 STR kit were used to detect autosomal STR genetic markers. Investigator® Argus X-12 QS kit was used to detect the X chromosome STR genetic markers, the special half-sibling index (SHSI) and first cousin index (FCI) and their likelihood ratio (LR) were calculated by ITO method.@*RESULTS@#The LR results of SHSI to FCI, which were calculated based on autosomal STR genotyping and the analysis of X-STR genotyping results suggested that the relationship between Zhang A, Zhang B, Zhang C and Zhang X was inclined to be a special half-sibling relationship.@*CONCLUSIONS@#For the identification of special kinship, it is necessary to comprehensively apply various genetic markers according to the case. After the conclusion that shared alleles cannot be excluded from the analysis, ITO method can be further used to establish discriminant assumptions according to the specific case to obtain objective and reliable identification opinions.

Generating DNA profile from low copy number DNA: Strategies and associated risks

Many shreds of evidence found on the crime scenes contain a trace amount of DNA which results in insignificant profiling results for subsequent comparison. This can nullify the potential evidence material and hamper investigation process. Over the years, different strategies have been employed by various DNA testing laboratories to create interpretable DNA profiles generated from low template of DNA. This review highlights different strategies used by forensic laboratories worldwide for creating complete DNA profiles from low copy number template for comparison purposes along with its associated risks for forensic purposes.