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•This is a guideline proposing a protocol for the validation of forensic evaluation methods.•The validation focuses on likelihood ratio methods for the inference at source level.•The guideline is general and can be applied to any forensic evaluation method producing LR values. This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes’ inference model. In the context of the inference of identity of source, the Likelihood Ratio is used to evaluate the strength of the evidence for a trace specimen, e.g. a fingermark, and a reference specimen, e.g. a fingerprint, to originate from common or different sources. Some theoretical aspects of probabilities necessary for this Guideline were discussed prior to its elaboration, which started after a workshop of forensic researchers and practitioners involved in this topic. In the workshop, the following questions were addressed: “which aspects of a forensic evaluation scenario need to be validated?”, “what is the role of the LR as part of a decision process?” and “how to deal with uncertainty in the LR calculation?”. The questions: “what to validate?” focuses on the validation methods and criteria and “how to validate?” deals with the implementation of the validation protocol. Answers to these questions were deemed necessary with several objectives. First, concepts typical for validation standards [1], such as performance characteristics, performance metrics and validation criteria, will be adapted or applied by analogy to the LR framework. Second, a validation strategy will be defined. Third, validation methods will be described. Finally, a validation protocol and an example of validation report will be proposed, which can be applied to the forensic fields developing and validating LR methods for the evaluation of the strength of evidence at source level under the following propositions:H1/Hss: The trace and reference originate from the same source.H2/Hds: The trace and reference originate from different sources.

Laboratories of anatomic pathology have to validate each analytical test before it is implemented in daily routine. However, evidence-based guidelines regarding validation of analytical tests are limited. A 2016 survey on test validation was performed in all 77 licensed Belgian anatomic pathology laboratories in order to evaluate the implementation and to highlight the current issues of test validation in Belgian anatomic pathology laboratories. Therefore, standard operating procedures for test validation and validation reports were evaluated for the presence of predefined items. Separate validation procedures for CE/IVD-labeled, laboratory-modified and laboratory-developed tests and a description of how each performance characteristic was validated were lacking in 51 (66 %) laboratories. Moreover, only 9 (12 %) laboratories reported to have written procedures for when and how analytical tests need to be revalidated. Better results were observed regarding the description of the performance characteristics, the co-workers involved, recording and archiving of results and raw data, the content of the validation report, ongoing validation, release and implementation into daily routine. Contrary to the evaluation results of the procedures for test validation, better results for the content of the validation reports were obtained. A lack of clear and predefined objective acceptance criteria for each determined performance characteristic was the most common shortcoming observed in validation reports in Belgian anatomic pathology laboratories. In conclusion, there appears to be a need for further development of guidelines for validation and revalidation of analytical tests performed in anatomic pathology laboratories.

Background: All-cause mortality consisting of several heterogeneous subgroups does not have a well-defined set of risk factors. Despite the well-described role of oral hygiene on mortality, the association between the condition of the existing dentition and mortality remains unclear. Therefore, we embarked on the current study to assess the association of oral hygiene self-care (OHS) with all-cause mortality. Methods: We assessed whether edentulism and the levels of OHS are associated with all-cause mortality in 476 subjects without missing values participating in the KOHH study using proportional hazard models. We designated the edentulous group as OHS0, and poor, fair, and good OHS groups as OHS1, OHS2, and OHS3, respectively. The self-reported OHS was validated against clinical measures of oral inflammation and dental cleanliness, i.e., gingival bleeding and plaque indices. We, then, compared all-cause mortality at three levels of OHS (poor, fair, good) to that of the edentulous group. To test whether the association of OHS to all-cause mortality was mediated by inflammation, we adjusted for CRP. Results: The validity of self-reported OHS was good demonstrating an inverse association with gingival inflammation and plaque index in a dose-response manner. The group with good OHS lived significantly longer, with a 50% lower risk of all-cause mortality. The Hazard ratio (HR) = 0.50 (95% confidence limit: 0.25–0.99), p = 0.045, in a model adjusted for age, smoking, body mass index, and education. Adjusting for CRP attenuated the association of OHS to all-cause mortality slightly, suggesting that this association was mediated, at least in part, by inflammation. In the final model, the poor OHS group exhibited HR = 0.98 (0.51–1.89), p = 0.95. The HR and p-value so close to 1 suggested poor OHS has a similar risk to edentulism. Conclusions: OHS was associated with reduced risk for all-cause mortality: the better OHS, the lower the risk for all-cause mortality. Poor oral hygiene showed a similar risk for all-cause mortality to edentulism.

This chapter focuses on how the fit‐for‐purpose method validation and assay application during drug development clinical trials can contribute to biomarker characterization. For the purpose of characterization of the biomarker of interest, fit‐for‐purpose method validation should be conducted with sufficient rigor to provide reliable data from multiple clinical studies. This should include assay range finding, accuracy and precision, selectivity, specificity, stability, and robustness (reproducibility) during prestudy method validation. Additional data is collected from in‐study assay performance, change control method validation, and long‐term storage stability. Before sample analysis begins, a written method standard operating procedure (SOP) must be in place. Often, a validation report should also be issued. Documentation of sample assay should follow the SOP in a good laboratory practice compliance manner, with traceable records. The data should be stored in a secure place for auditing.

Background: Previous analysis of a randomized community-based trial of a multi-component intervention to increase colorectal cancer (CRC) screening among Filipino Americans (n = 548) found significantly higher screening rates in the two intervention groups compared to the control group, when using intent-to-treat analysis and selfreported screening as the outcome. This report describes more nuanced findings obtained from alternative approaches to assessing intervention effectiveness to inform future intervention implementation. Methods: The effect of the intervention on CRC screening receipt during follow-up was estimated using methods that adjusted for biases due to missing data and self-report and for different combinations of intervention components. Adjustment for self-report used data from a validation substudy. Effectiveness within demographic subgroups was also examined. Results: Analyses accounting for self-report bias and missing data supported the effectiveness of the intervention. The intervention was also broadly effective across the demographic characteristics of the sample. Estimates of the intervention effect were highest among participants whose providers received a letter as part of the intervention. Conclusions: The findings increase confidence that the intervention could be broadly effective at increasing CRC screening in this population. Subgroup analyses and attempts to deconstruct multi-component interventions can provide important information for future intervention development, implementation, and dissemination.

This chapter discusses the need to understand business considerations in implementing risk scorecards, how scorecards and management reports are used, and how strategy is developed. Once all the characteristics have been programmed, accuracy testing of the scorecard can be done. Validation reports can be produced as part of the accuracy testing to make the process more efficient. Ideally, testing should be done in the same environment where the scorecard is to be implemented. The shifts in scored and non‐scored characteristics should be consistent and explainable using logic and business considerations. Redeveloping the scorecard may not be a viable choice, since the data sample for this redevelopment will likely come from the same time period as the original scorecard. If redeveloping the scorecard is not an option, in such cases users sometimes adjust their applicant population expectations based on the new distributions. Implementation of new strategies gives the company an opportunity to revisit and enhance policy rules, especially when putting in new scorecards. Special attention needs to be paid to alignment of decisions based on scoring and policy rules, so that they do not negate each other and the effectiveness of each can be tracked and evaluated independently.

Documentation is an essential component in a GMP environment. Without proper documentation, Justification of data generation and data interpretation cannot be obtained. The old expression “If it’s not Documented it’s not Done” is well suited in a GMP/Regulatory environment. Included in this chapter are templates for several of the important documents that must available in an Analytical Department. Those described herein are Sample Submission, Technical Reports, Reports of Analysis, and Training Records.

Emotion dysregulation often emerges early in development and is a core feature of many psychological conditions. The Difficulties in Emotion Regulation Scale (DERS) is a well validated and widely used self-report measure for assessing emotion regulation problems among adolescents and adults. The DERS has six subscales with five to eight items each (36 total), suggesting multiple questions may assess similar underlying constructs. In an effort to reduce respondent burden and streamline this widely-used instrument, we created a short-form version of the DERS (DERS-SF) using confirmatory factor analysis on data from three adolescent ( n  = 257) and two adult samples ( n  = 797). Scores on the DERS-SF yielded similar correlation patterns relative to the full measure, ranging from .90 to .98 and reflecting 81–96 % shared variance. This instrument maintains the excellent psychometric properties and retains the total and subscale scores of the original measure with half the items.

Introduction The RU-SATED model – regularity, satisfaction, alertness, timing, efficiency, and duration – captures the 24-hour experience of sleep to asses multidimensional sleep health (MSH). However, most prior evidence comes from middle-aged adults. We provide updated MSH data in adolescents by leveraging objective and self-reported sleep measures. Methods We studied 377 adolescents (16.4±2.3 yr; 46.4% female; 21.5% racial/ethnic minority) from the Penn State Child Cohort, a randomly-selected population-based sample. Each MSH domain was categorized as “good” or “poor” using cut-offs informed by prior studies and expert consensus. Good cut-offs, assigned a score of 1, that were derived from actigraphy-measured data included: the standard deviation of sleep midpoint ≤1-h (RU), mean of sleep midpoint 2:00-4:00 (T), mean value of sleep efficiency ≥85% (E), and mean total sleep time ≥7.5-h (D). Good cut-offs derived from self-reported rating scales included the absence of insomnia symptoms (S) or excessive daytime sleepiness (A). Values considered poor based on these cut-offs were assigned a score of 0. Scores were summed across all domains to obtain a composite score ranging from 0 to 6, with higher scores indicating better MSH. Morningness and Tanner staging were self-reported, while Sleep and Arousal clusters scores on the Pediatric Behavior Scale were parent-reported. Results The mean composite score was 3.03 ± 1.30 and domains A and D were most commonly rated as poor (64.5% and 65.3%, respectively). Younger age (r=-0.13, p< 0.05) and identifying as non-Hispanic white (r=-0.14, p< 0.01) were significantly associated with higher MSH scores, while sex (r=-0.04, p=0.40), Tanner staging (r=-0.06, p=0.29) or BMI percentile (r=-0.07, p=0.15) were not. Greater morningness (r=-0.29, p< 0.01), less disturbed sleep (r=-0.28, p< 0.01) and higher arousal (r=-0.21, p< 0.01) scores were associated with higher MSH scores. Conclusion Our data-driven approach can be used to assess MSH in the adolescent population. Our definition captures previously identified health disparities in MSH in adults and shows optimal construct validity against self-reports of circadian preference and parent observations of adolescents’ degree of sleep disturbance and arousal. Improving sleep duration and daytime alertness appear to continue to be the most relevant domains impacting overall MSH in adolescents. Support (if any) NIH (R01HL136587,UL1TR000127)

The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) adopted Guideline M10 entitled \"Bioanalytical Method Validation and Study Sample Analysis\" in May 2022. In October 2023, approximately one year after the adoption of the ICH M10 guideline, a \"Hot Topic\" session was held during the AAPS PharmSci 360 meeting to discuss the implementation of the guideline. The session focused on items the bioanalytical community felt were challenging to implement or ambiguous within the guideline. These topics included cross-validation, parallelism, comparative bioavailability studies, combination drug stability, endogenous analyte bioanalysis, and dilution QCs. In addition, the regulatory perspective on the guideline was presented. This report provides a summary of the Hot Topic session. Graphical Abstract