Internal Validation Study Research Articles

In depth investigation of the retention behavior of structurally related β-blockers on RP-HPLC column: Quality by design and quantitative structure-property relationship complementary approaches for optimization and validation

The persistent introduction of new β-blockers motivates the demand for optimizing RP-HPLC well-designed analytical procedures that could be applied to this structurally related and commonly prescribed pharmacological group in order to reduce time and chemicals consumption in quality control units. Betoxolol HCl (BEX) and Carvidolol (CAR) were selected as representative examples to conduct predictive studies based on two complementary approaches, Quality by design (QBD) and Quantitative structure property relationship (QSPR). In concern QBD, a Box-Behnken design was adopted at variable chromatographic parameters to achieve the most proper conditions that might be applied for efficient analysis of the majority of group members. On the other hand, the retention time was chosen as the target property in the QSPR study that was conducted onto seven β. blockers (the two investigated drugs in addition to five other β. blockers) to find the best correlated molecular descriptors to the retention behavior. Both external and internal validation studies have comparable quality with training levels. Hence a simple selection algorithm of conventional features provides robust confirmatory predictive QBD and QSPR models. Derringer’s desirability function as as a multi-criteria approach was applied for getting the optimum chromatographic analysis conditions. Efficient analysis of BET and CAR was achieved at column temperatures of 26.00 and 27.50 °C, respectively using acetonitrile and phosphate buffer (pH 4.55) 70:30 v/v as a mobile phase with a flow rate of 1.00 mL/min, and UV detection at 220 nm. The method was validated in accordance to ICH guidelines, and had exhibited acceptable precision, accuracy, linearity, and robustness.

Mouse Models of Lung Fibrosis.

The drug discovery pipeline, from discovery of therapeutic targets through preclinical and clinical development phases, to an approved product by health authorities, is a time-consuming and costly process, where a lead candidates' success at reaching the final stage is rare. Although the time from discovery to final approval has been reduced over the last decade, there is still potential to further optimize and streamline the evaluation process of each candidate as it moves through the different development phases. In this book chapter, we describe our preclinical strategies and overall decision-making process designed to evaluate the tolerability and efficacy of therapeutic candidates suitable for patients diagnosed with fibrotic lung disease. We also describe the benefits of conducting preliminary discovery trials, to aid in the selection of suitable primary and secondary outcomes to be further evaluated and assessed in subsequent internal and external validation studies. We outline all relevant research methodologies and protocols routinely performed by our research group and hope that these strategies and protocols will be a useful guide for biomedical and translational researchers aiming to develop safe and beneficial therapies for patients with fibrotic lung disease.

A Method to adjust for measurement error in multiple exposure variables measured with correlated errors in the absence of an internal validation study

Difficulty in obtaining the correct measurement for an individual’s longterm exposure is a major challenge in epidemiological studies that investigate the association between exposures and health outcomes. Measurement error in an exposure biases the association between the exposure and a disease outcome. Usually, an internal validation study is required to adjust for exposure measurement error; it is challenging if such a study is not available. We propose a general method for adjusting for measurement error where multiple exposures are measured with correlated errors (a multivariate method) and illustrate the method using real data. We compare the results from the multivariate method with those obtained using a method that ignores measurement error (the naive method) and a method that ignores correlations between the errors and true exposures (the univariate method). It is found that ignoring measurement error leads to bias and underestimates the standard error. A sensitivity analysis shows that the magnitude of adjustment in the multivariate method is sensitive to the magnitude of measurement error, sign, and the correlation between the errors. We conclude that the multivariate method can be used to adjust for bias in the outcome-exposure association in a case where multiple exposures are measured with correlated errors in the absence of an internal validation study. The method is also useful in conducting a sensitivity analysis on the magnitude of measurement error and the sign of the error correlation.

Prediction of Osteoporotic Fractures in Elderly Individuals: A Derivation and Internal Validation Study Using Healthcare Administrative Data.

In Canada and other countries, osteoporosis is monitored as part of chronic disease population surveillance programs. Although fractures are the principal manifestation of osteoporosis, very few algorithms are available to identify individuals at high risk of osteoporotic fractures in current surveillance systems. The objective of this study was to derive and validate predictive models to accurately identify individuals at high risk of osteoporotic fracture using information available in healthcare administrative data. More than 270,000 men and women aged ≥66 years were randomly selected from the Quebec Integrated Chronic Disease Surveillance System. Selected individuals were followed between fiscal years 2006-2007 and 2015-2016. Models were constructed for prediction of hip/femur and major osteoporotic fractures for follow-up periods of 5 and 10 years. A total of 62 potential predictors measurable in healthcare administrative databases were identified. Predictor selection was performed using a manual backward algorithm. The predictive performance of the final models was assessed using measures of discrimination, calibration, and overall performance. Between 20 and 25 predictors were retained in the final prediction models (eg, age, sex, social deprivation index, most of the major and minor risk factors for osteoporosis, diabetes, Parkinson's disease, cognitive impairment, anemia, anxio-depressive disorders). Discrimination of the final models was higher for the prediction of hip/femur fracture than major osteoporotic fracture and higher for prediction for a 5-year than a 10-year period (hip/femur fracture for 5 years: c-index=0.77; major osteoporotic fracture for 5 years: c-index=0.71; hip/femur fracture for 10 years: c-index=0.73; major osteoporotic fracture for 10 years: c-index=0.68). The predicted probabilities globally agreed with the observed probabilities. In conclusion, the derived models had adequate predictive performance in internal validation. As a final step, these models should be validated in an external cohort and used to develop indicators for surveillance of osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).

Development of Machine Learning Model to Predict the 5-Year Risk of Starting Biologic Agents in Patients with Inflammatory Bowel Disease (IBD): K-CDM Network Study.

Background: The incidence and global burden of inflammatory bowel disease (IBD) have steadily increased in the past few decades. Improved methods to stratify risk and predict disease-related outcomes are required for IBD. Aim: The aim of this study was to develop and validate a machine learning (ML) model to predict the 5-year risk of starting biologic agents in IBD patients. Method: We applied an ML method to the database of the Korean common data model (K-CDM) network, a data sharing consortium of tertiary centers in Korea, to develop a model to predict the 5-year risk of starting biologic agents in IBD patients. The records analyzed were those of patients diagnosed with IBD between January 2006 and June 2017 at Gil Medical Center (GMC; n = 1299) or present in the K-CDM network (n = 3286). The ML algorithm was developed to predict 5- year risk of starting biologic agents in IBD patients using data from GMC and externally validated with the K-CDM network database. Result: The ML model for prediction of IBD-related outcomes at 5 years after diagnosis yielded an area under the curve (AUC) of 0.86 (95% CI: 0.82–0.92), in an internal validation study carried out at GMC. The model performed consistently across a range of other datasets, including that of the K-CDM network (AUC = 0.81; 95% CI: 0.80–0.85), in an external validation study. Conclusion: The ML-based prediction model can be used to identify IBD-related outcomes in patients at risk, enabling physicians to perform close follow-up based on the patient’s risk level, estimated through the ML algorithm.

Screening for SARS-CoV-2: Health Policy Implications in Low- and Middle-Income Countries

Screening for SARS-CoV-2: Health Policy Implications in Low- and Middle-Income Countries

Inventario IPIP-NEO: Estabilidad y Validez de Estructura Interna, Convergente y Concurrente en Muestras Argentinas

Las principales herramientas de evaluación de la personalidad se construyeron a partir de las bases teóricas del modelo de los Cinco Factores. Particularmente, en Argentina, el IPIP-NEO es uno de los instrumentos, basados en este modelo, que presenta resultados satisfactorios en los estudios de consistencia interna (confiabilidad) y de validez mediante evidencia de estructura interna (análisis factorial exploratorio). El objetivo de este trabajo fue aportar nuevos estudios psicométricos a la escala utilizando una muestra heterogénea de argentinos (N = 499). Se estimó la estabilidad temporal de las puntuaciones a través del método test-retest y se realizó un estudio de validez de estructura interna mediante análisis factorial confirmatorio. Por otro lado, se aportó validez externa a traves de estudios de convergencia, estudios de contraste de grupos divididos por sexo y edad, y un análisis test criterio mediante regresión múltiple con actividades recreativas. Los resultados sugieren que las puntuaciones que del IPIP-NEO son estables, con adecuados índices de confiabilidad y evidencias de validez externa, lo que indica que puede ser utilizado en muestras argentinas. Se planifica la elaboración de un baremo local y nuevos estudios de validez externa con implicancias clínicas y laborales.

Radical Cystectomy and Perioperative Sexual Function: A Cross-Sectional Analysis

BackgroundCancer-related changes in sexual function (SF) negatively impact quality of life and intimate partner relationships. There is a lack of data regarding SF among patients who underwent radical cystectomy (RC). AimTo comparatively evaluate perioperative SF among patients who underwent RC. MethodsA prospective cohort of 150 patients undergoing RC for bladder cancer and participating in an internal validation study at a single institution from 2016 to 2019 were eligible for analysis. The European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire–Bladder Cancer Muscle Invasive (EORTC QLQ–BLM 30) and Functional Assessment of Cancer Therapy–Bladder were administered; those completing the SF subscale of the EORTC QLQ–BLM 30 were included in final analysis. Analysis was performed using descriptive statistics and generalized linear modeling. OutcomesThe primary outcome was interest or engagement in sexual activity within 4 weeks of survey completion, whereas the secondary outcome was a mean score on the EORTC QLQ–BLM 30 SF subscale. ResultsOverall, 132 of 150 (88%) of patients were eligible, of whom 82% were male, and the median age was 68.5 years. 53% reported at least a little interest in sexual activity, and 40% endorsed sexual activity within the last 4 weeks. The mean SF subscale score was 61.5 ± 25.2. Women had significantly worse mean scores of 72.9 ± 27.1 versus 59.1 ± 24.2 for men (P = .02). On multivariate analysis, both age and female gender were independently associated with higher SF domain scores. Clinical ImplicationsA substantial portion of patients who underwent RC endorse being sexually active or express interest in sexually activity in the perioperative period. Given the recent increase in attention given to SF outcomes and quality of life, this work supports further efforts to explore this area and develop novel interventions to improve outcomes. Strengths and LimitationsStrengths include rigorously collected, cross-sectional data using standardized methodology. Limitations include a relatively small sample size of female patients and unknown meaningful clinical difference. ConclusionsA substantial portion of patients report sexual interest and activity in the perioperative period; however, female gender is associated with worse SF domain scores. These findings support further inquiry into this topic.Westerman ME, Kokorovic A, Wang XS, et al. Radical Cystectomy and Perioperative Sexual Function: A Cross-Sectional Analysis. J Sex Med 2020;17:1995–2004.

PD-L1 IHC 22C3 pharmdx demonstrates precision and reproducibility in detecting PD-L1 expression in triple negative breast cancer.

e13104 Background: PD-L1 IHC 22C3 pharmDx is an FDA-approved, companion diagnostic assay intended for use in the detection of PD-L1 protein in formalin-fixed paraffin-embedded (FFPE) non-small cell lung cancer (NSCLC), gastric or gastroesophageal junction (GEJ) adenocarcinoma, esophageal squamous cell carcinoma (ESCC), cervical cancer, urothelial carcinoma, and head and neck squamous cell carcinoma (HNSCC) tissues. Methods: Additionally, device precision (inter- and intra-observer, inter-instrument, inter-operator, inter-day, inter-lot, and intra-run) and robustness have been validated at Dako North America for triple negative breast cancer (TNBC) using the Combined Positive Score (CPS) ≥1 cutoff. Device precision (excluding inter- and intra-observer) has also been validated for TNBC using the CPS ≥10 cutoff. External validation studies for TNBC (inter- and intra-site, inter- and intra-observer) were conducted at three CAP-accredited and/or CLIA-licensed laboratories using the CPS ≥1 and CPS ≥10 cutoffs. Results: The precision, robustness, and external validation studies achieved point estimates greater than 85% for positive, negative, and overall percent agreement. Conclusions: Internal and external validation studies demonstrate that PD-L1 IHC 22C3 pharmDx is sensitive, specific, precise, robust, and reproducible in evaluating PD-L1 expression at CPS ≥1 and CPS ≥10 cutoffs using TNBC tissue.

Machine learning for early detection of sepsis: an internal and temporal validation study.

ObjectiveDetermine if deep learning detects sepsis earlier and more accurately than other models. To evaluate model performance using implementation-oriented metrics that simulate clinical practice.Materials and MethodsWe trained internally and temporally validated a deep learning model (multi-output Gaussian process and recurrent neural network [MGP–RNN]) to detect sepsis using encounters from adult hospitalized patients at a large tertiary academic center. Sepsis was defined as the presence of 2 or more systemic inflammatory response syndrome (SIRS) criteria, a blood culture order, and at least one element of end-organ failure. The training dataset included demographics, comorbidities, vital signs, medication administrations, and labs from October 1, 2014 to December 1, 2015, while the temporal validation dataset was from March 1, 2018 to August 31, 2018. Comparisons were made to 3 machine learning methods, random forest (RF), Cox regression (CR), and penalized logistic regression (PLR), and 3 clinical scores used to detect sepsis, SIRS, quick Sequential Organ Failure Assessment (qSOFA), and National Early Warning Score (NEWS). Traditional discrimination statistics such as the C-statistic as well as metrics aligned with operational implementation were assessed.ResultsThe training set and internal validation included 42 979 encounters, while the temporal validation set included 39 786 encounters. The C-statistic for predicting sepsis within 4 h of onset was 0.88 for the MGP–RNN compared to 0.836 for RF, 0.849 for CR, 0.822 for PLR, 0.756 for SIRS, 0.619 for NEWS, and 0.481 for qSOFA. MGP–RNN detected sepsis a median of 5 h in advance. Temporal validation assessment continued to show the MGP–RNN outperform all 7 clinical risk score and machine learning comparisons.ConclusionsWe developed and validated a novel deep learning model to detect sepsis. Using our data elements and feature set, our modeling approach outperformed other machine learning methods and clinical scores.

Reliability of point-of-care coagulometer measurements in patients with acute ischaemic stroke receiving intravenous fibrinolysis

BackgroundSpeed of administration conditions the effectiveness of intravenous fibrinolysis in treating acute ischaemic stroke. To reduce the risk of haemorrhagic complications, the intervention is contraindicated in certain cases, such as where the International Normalised Ratio (INR) is ≥1.7. This study aimed to determine the reliability of point-of-care INR readings (POC-INR) taken using the CoaguChek® XS portable coagulometer compared to laboratory results (L-INR). MethodsWe conducted a retrospective observational study of consecutive patients admitted to our centre with acute ischaemic stroke and who were treated with intravenous fibrinolysis, over a period of 4 years. Patients’ INR was measured with a portable coagulometer and in the laboratory. Results were compared using the paired-sample t test; using L-INR results as a reference value, ROC analysis was performed to determine POC-INR with greater predictive value. ResultsThe study included 210 patients with a mean age of 74.3±11.5 years old; 18 (8.6%) were taking vitamin K antagonist oral anticoagulants (OAC). There were no significant differences between the 2 INR measurements in the population as a whole (POC-INR–L-INR difference: 0.001±0.085; P=.82). In subgroup analysis, the results coincided for patients taking OACs (0.001±0.081; P=.42) and those with L-INR ≤ 1.2 (0.008±0.081; P=.16). For L-INR>1.2, however, the portable coagulometer underestimated INR (0.058±0.095; P=.01). Through ROC analysis, POC-INR <1.6 was found to be the cut-off point with greatest sensitivity (100%) and specificity (98.97%) for identifying patients eligible for intravenous fibrinolysis (L-INR <1.7). ConclusionsPOC-INR shows a good correlation with L-INR. Our results suggest that the best threshold to predict an L-INR <1.7 is POC-INR <1.6. Internal validation studies for POC-INR should be considered in all treatment centres.

Internal deterministic record linkage using indirect identifiers for matching of same-patient hospital transfers and early readmissions after acute coronary syndrome in a nationwide hospital discharge database: a retrospective observational validation study

ObjectivesTo assess validity of record linkage using multiple indirect personal identifiers to identify same-patient hospitalisations and definition of episode of care (EC) due to acute coronary syndrome (ACS).MethodsUsing national hospital...

Internal validation of GlobalFilerTM kit using reduced reaction volume

For approximately two decades, Microsatellites or Short Tandem Repeat (STR) markers have been the backbone for human identification testing in the forensic field. The expansion of STR multiplex kits can improve global sharing of STR profiles, rapid DNA typing, and DNA typing Flores et al. (2014). GlobalFiler™ kit is highly sensitive and has extremely high power of discrimination. An internal validation of GlobalFiler™ Kit was carried out to test the robustness of this kit through a range of internal validation studies including half volume reaction, reproducibility, sensitivity, specificity, stability, mixture, analytical threshold, sensitivity & stochastic threshold, heterozygous balance & stutter threshold studies in accordance with SGWDAM guidelines Scientific Working Group on DNA . Reference and real casework samples previously tested using other autosomal STR kits from forensic cases were used during the validation. It was demonstrated that the GlobalFiler™ kit has enhanced discrimination power, is robust and extremely useful for forensic casework.

Gestational Weight Gain and Adverse Birth Outcomes in Twin Pregnancies.

To evaluate the association between gestational weight gain in twin pregnancies and small-for-gestational-age (SGA) and large-for-gestational-age (LGA) birth, preterm birth before 32 weeks of gestation, cesarean delivery, and infant death within each prepregnancy body mass index (BMI) category. Data in this population-based study came from Pennsylvania-linked infant birth and death records (2003-2013). We studied 54,836 twins born alive before 39 weeks of gestation. Total pregnancy weight gain (kg) was converted to gestational age-standardized z scores. Multivariable modified Poisson regression models stratified by prepregnancy BMI were used to estimate associations between z scores and outcomes. A probabilistic bias analysis, informed by an internal validation study, evaluated the effect of BMI and weight gain misclassification. Gestational weight gain z score was negatively associated with SGA and positively associated with LGA and cesarean delivery in all BMI groups. The relation between weight gain and preterm birth was U-shaped in nonobese women. An increased risk of infant death was observed for very low weight gain among normal-weight women and for high weight gain among women without obesity. Most excess risks of these outcomes were observed at weight gains at 37 weeks of gestation that are equivalent to less than 14 kg or more than 27 kg in underweight or normal-weight women, less than 11 kg or more than 28 kg in overweight women, and less than 6.4 kg or more than 26 kg in women with obesity. The bias analysis supported the validity of the conventional analysis. Very low or very high weight gains were associated with the adverse outcomes we studied. If the associations we observed are even partially reflective of causality, targeted modification of pregnancy weight gain in women carrying twins might improve pregnancy outcomes.

Internal validation study of the next generation sequencing of Globalfiler™ PCR amplification kit for the Ion Torrent S5 sequencer

In the last few years, massively parallel sequencing (MPS) techniques have improved greatly in the field of forensic genetics, providing several advantages over the traditionally capillary electrophoresis (CE) system in terms of resolution, scalability, and throughput [1,2]. Nevertheless, before implementing MPS into routine forensic applications, both workflow and output results must be rigorously validated with respect to robustness, performance and compatibility to CE-based data [3].We present the validation study of MPS technology for short tandem repeat (STR) genotyping using Precision ID GlobalFiler™ NGS STR Panel v2 on the Ion S5™ platform (both Thermo Fisher Scientific), that include experiments to assess concordance, sensitivity, reliability and mixture analysis.MPS allowed to generate a concordant result with those by CE system, demonstrating the reliability of both methods. Sensitivity study revealed that single source full-profile could be obtained using a significantly less amount of DNA compared to the quantity recommended in the protocol. In addition, STR genotypes obtained were reproducible and consistent among multiple typing replicates. Partial STR genotypes of minor contribute could be detected up to a 1:80 mixture. However, analysis of MPS-based STR revealed more noise artefacts (e.g. stutter artefacts) respect to CE, that were not independently filtered by Converge™ software NGS Analysis Module supported by Life Technologies platform.

Validation study and forensic applications of investigator 24plex QS Kit

The Investigator 24plex QS Kit (Qiagen) is used for multiplex PCR in forensic human identity and paternity testing. The PCR simultaneously amplifies 22 polymorphic STR markers: the Combined DNA Index System (CODIS) core loci, the European Standard Set (ESS) loci, SE33, DYS391 and Amelogenin. The Investigator 24plex QS Kit is specifically designed for rapid and reliable generation of DNA profiles from blood, buccal swabs, and forensic stains. The kit utilizes QIAGEN’s fast-cycling PCR technology, allowing amplification in around 60 min and provides highly robust results with inhibitor-resistant chemistry. The Investigator 24plex QS Kit Primer Mix contains two innovative internal PCR controls (Quality Sensor QS1 and QS2), which are amplified simultaneously with the polymorphic STR markers, to yield helpful information about the efficiency of the PCR and the presence of PCR inhibitors. The Investigator 24plex QS Kit User Guide describes instrument setup and sample preparation of PCR products using the Applied Biosystems 3500 Series Data Collection Software and the GeneMapper ID-X Software, but an internal validation is always needed.In this study, we report the successful analysis of amplicons obtained with Investigator 24plex QS Kit on the 3500 Genetic Analyzer. We performed internal validation studies following the European Network of Forensic Science Institutes (ENFSI) and the European DNA Profiling Group (EDNAP) guidelines, testing several critical areas of kit performance such as sensibility, sensitivity, DNA mixtures and inhibited samples.

Reliability and validity studies of the Turkish version of Humor Styles Questionnaire for Children

This article presents the investigation of the psychometric properties of the Turkish version of the Humor Styles Questionnaire for Children (CHSQ Turkish). Four studies were assessed using a sample of Turkish secondary school students in two different schools located in Istanbul and a total of 717 students participated in these four studies. Factor analyses and internal consistency (study 1), test-retest reliability (study 2), concurrent validity (study 3), convergent and discriminant validity (study 4) were investigated in this research. In study 1, the results of the confirmatory and exploratory factor analysis indicated that the four-factor structure (aggressive, affiliative, self-enhancing, self-defeating) of a modified 17-item version was confirmed. In addition, corrected item-total correlations (.50–.70) and internal consistency values of the four factors were acceptable (.82, .83, .80, .73, respectively). Test-retest reliabilities during a 4-week period (.69, .82, .74, .72, respectively) were adequate in study 2. In study 3, concurrent validity of the scale was supported with reference to depression and anxiety. In study 4, convergent and discriminant validity of the CHSQ Turkish were confirmed by assessing AVE, square root of AVE and correlations between four factors. Additionally, the correlations of the four factors of the scale with sensation seeking and loneliness were additional evidence for convergent validity. The CHSQ Turkish was assessed to be a valid and reliable measure.

Understanding the relation between Zika virus infection during pregnancy and adverse fetal, infant and child outcomes: a protocol for a systematic review and individual participant data meta-analysis of longitudinal studies of pregnant women and their infants and children

IntroductionZika virus (ZIKV) infection during pregnancy is a known cause of microcephaly and other congenital and developmental anomalies. In the absence of a ZIKV vaccine or prophylactics, principal investigators (PIs)...

CAUSAL INFERENCE IN THE CONTEXT OF AN ERROR PRONE EXPOSURE: AIR POLLUTION AND MORTALITY.

We propose a new approach for estimating causal effects when the exposure is measured with error and confounding adjustment is performed via a generalized propensity score (GPS). Using validation data, we propose a regression calibration (RC)-based adjustment for a continuous error-prone exposure combined with GPS to adjust for confounding (RC-GPS). The outcome analysis is conducted after transforming the corrected continuous exposure into a categorical exposure. We consider confounding adjustment in the context of GPS subclassification, inverse probability treatment weighting (IPTW) and matching. In simulations with varying degrees of exposure error and confounding bias, RC-GPS eliminates bias from exposure error and confounding compared to standard approaches that rely on the error-prone exposure. We applied RC-GPS to a rich data platform to estimate the causal effect of long-term exposure to fine particles (PM2.5) on mortality in New England for the period from 2000 to 2012. The main study consists of 2202 zip codes covered by 217,660 1 km × 1 km grid cells with yearly mortality rates, yearly PM2.5 averages estimated from a spatio-temporal model (error-prone exposure) and several potential confounders. The internal validation study includes a subset of 83 1 km × 1 km grid cells within 75 zip codes from the main study with error-free yearly PM2.5 exposures obtained from monitor stations. Under assumptions of noninterference and weak unconfoundedness, using matching we found that exposure to moderate levels of PM2.5 (8 < PM2.5 ≤ 10 μg/m3) causes a 2.8% (95% CI: 0.6%, 3.6%) increase in all-cause mortality compared to low exposure (PM2.5 ≤ 8 μg/m3).

Internal validation study of a newly developed 24-plex Y-STRs genotyping system for forensic application.

Prior to implementing a new kit into application, developmental validation should be conducted to demonstrate the robustness and applicability of the kit. In this study, 24 Y-STR loci from the AGCU Y SUPP STR kit were tested including 11 loci overlapping with other commercial kits (DYS385a/b, DYS635, DYS533, DYS481, DYS549, DYS460, DYS527a/b, DYS522, and DYS444) and 13 new loci (DYS531, DYS630, DYS622, DYS552, DYS510, DYS459a/b, DYS446, DYS443, DYS587, Y-GATA-A10, DYS520, and DYS557). Developmental validation including PCR-related studies, sensitivity, stability, and species specificity studies were conducted. The performance of the kit in genotyping case-type samples was also estimated. The results indicated that the kit is robust, accurate and sensitive and is able to detect male samples without being affected by female samples or other species. Population data were obtained with this kit in Chinese Xibe group as well. Totally 139 different haplotypes were obtained from 167 male samples and demonstrated that this typing system is relatively discriminative.