Overestimation Of Size Research Articles

Body size estimation is influenced by actual-ideal body size discrepancy: a series of studies among Chinese adolescent girls.

Many adolescent girls desire to have a thinner body, including those of normal weight. However, it is not fully known if this reflects solely a preference for a particular body type/size, or also is influenced by holding a distorted perception of one's body size. The current series of studies aimed to examine the (in)accuracy of body size perception among adolescent girls, as well as the extent to which distorted perceptions of body size extended to perceptions of other girls' bodies. In Study 1, 48 pairs of girls who desired to be thinner were asked to estimate the circumferences of three parts (arm, waist and thigh) of their own body and that of a study partner. Participants generally overestimated the circumferences of both their own and their partner's bodies, with this overestimation stable over a four-month follow-up. In contrast, in Study 2, no body size overestimation was observed for self or partners among 44 pairs of girls who were satisfied with their body size. Study 3 further revealed significant correlations between body size overestimation and disordered eating symptomology among 43 pairs of girls who desired to be thinner. As a whole, findings demonstrated that body size overestimation was limited to adolescent girls who were dissatisfied with their body size, and that body size overestimation was associated with disordered eating symptomology. Thus, perceptual distortions in body size may play a role in both body size dissatisfaction and disordered eating among adolescents.

Hand and foot overestimation in visually impaired human adults

Previous research has shown that visual impairment results in reduced audio, tactile and proprioceptive ability. One hypothesis is that these issues arise from inaccurate body representations. Few studies have investigated metric body representations in a visually impaired population. We designed an ecologically valid behavioural task in which visually impaired adults haptically explored various sized gloves or shoes. They were asked to indicate if they perceived each clothing item as bigger than the size of their hand or foot. In the post-hoc analyses we fit psychometric curves to the data to extract the point of subjective equality. We then compared the results to age/sex matched controls. We hypothesized the blind participants body representations should be more distorted. Because previous research has shown that females are more likely to overestimate body size, we predicted sex differences in the sighted participants. However, because blind adults have no exposure to visual ideals of body size, we predicted that there would be no sex differences. Our results showed thatblind participants overestimated their hands and feetto a similar degree. Sighted controls overestimated their hands significantly more than their feet. Taken together, our results partially support our hypothesis and suggest that visual deprivation, even for short periods result in hand size overestimation.

Radar-Derived Convective Features and Atmospheric Environments of Hail-Producing Storms over the Contiguous United States

Abstract Hail smaller than 0.75 in. is known to cause economic impacts yet remains understudied due to report biases towards recording larger hail sizes (≤1 in.). In this study, we assembled ground hail reports during 2017–22 from the National Centers for Environmental Information (NCEI) Storm Data, Community Collaborative Rain, Hail and Snow Network (CoCoRaHS), and Meteorological Phenomena Identification Near the Ground (mPING) databases. Then, these reports are collocated with the attributes of radar-derived convective features from the Multi-Radar Multi-Sensor (MRMS) system and fifth major global reanalysis produced by European Centre for Medium-Range Weather Forecasts (ERA5) atmospheric vertical profiles to construct a dataset describing properties of a full spectrum of hailstorms. The characteristics of radar reflectivity and atmospheric profiles are examined for hail of different sizes reported within selected regions over the contiguous United States (CONUS). In addition to the seasonal and diurnal variations, the morphology of convective features shows apparent regional differences from west to east in CONUS. The maximum expected size of hail (MESH) performance against reported hail sizes shows underestimation of hail with significant sizes and overestimation of small hail sizes. ERA5 vertical atmospheric profiles are explored to form relationships between storm environment and hail sizes. In addition to the relationships between wind shear and hail sizes, the roles of low-level relative humidity and freezing level height in regard to hail melting are discussed.

Therapeutic ketogenic diet as treatment for anorexia nervosa.

Anorexia nervosa (AN) is a severe psychiatric disorder. However, we lack neurobiological models and interventions to explain and treat the core characteristics of food restriction, feeling fat, and body size overestimation. Research has made progress in understanding brain function involved in the pathophysiology of AN, but translating those results into biological therapies has been challenging. Studies have suggested that metabolic factors could contribute to developing and maintaining AN pathophysiology. Here, we describe a neurobiological model for why using a therapeutic ketogenic diet could address key alterations in brain function in AN and prevent the desire for weight loss and associated eating disorder-specific symptoms. This translational model is based on animal studies and human data and integrates behavioral traits, brain neural energy metabolism, and neurotransmitter function. Pilot data indicate that the intervention can dramatically reduce eating and body-related fears, although larger studies across illness stages still need to be conducted.

The effect of absorbed moisture and resin pressure on porosity in autoclave cured epoxy resin

AbstractOne of the main issues in epoxy‐based composite manufacturing is the formation of porosity derived from moisture absorption during storage and layup due to the high hydrophilicity of epoxy matrices. During the curing process, the presence of moisture and other volatile compounds can initiate the nucleation and growth of voids. In this study, the effect of both the initial water content absorbed in the uncured resin and the pressure on the porosity development in an epoxy resin was investigated. In particular, Kardos' and Ledru's models, aimed at predicting void formation in polymers, were applied to study the effect of different hydrostatic pressures in an epoxy resin during curing up to the gel point, after conditioning it at two different relative humidity levels, 50% and 95%. Subsequently, the porosity of the cured resin samples was quantified through density measurements. Comparative analysis of the microscopy images of cured samples and the predictions of both models revealed an overestimation of the final void sizes by both models, with the Kardos' model exhibiting a higher deviation. Additionally, a finite element model was employed to investigate the conditions leading to void formation, aiming to understand the factors influencing the porosity development and properly set the process parameters during composite manufacturing.Highlights Evaluation of the conditions leading to void growth in epoxy resin during curing Moisture sorption in uncured epoxy resin Effect of curing pressure on pore development Finite element analysis for void growth during resin curing

Quantification of metallic artifact on CT associated with titanium pedicle screws.

In dogs undergoing vertebral column stabilization, post-operative computed tomography (CT) evaluates implant placement. The impact on the interpretation of metallic artifact associated with titanium implants in dogs remains to be established. Our objective was to quantify metallic artifact on CT associated with titanium pedicle screws. The study design included an in vitro model and a retrospective review of 11 dogs with vertebral column stabilization. Twenty four titanium pedicle screws (6 each: 2.0 mm, 2.7 mm, 3.5 mm, and 4.5 mm) were inserted into a 20% ballistic gel, and CT scan of the construct was performed. Three blinded raters used a bone window to measure the maximum width (effective size) of each screw, one rater measured effective size using an ultrawide window and 45 titanium pedicle screws (3×2.0 mm, 5×2.7 mm, 30×3.5 mm, and 7×4.5 mm) in 11 clinical cases. Effective size measurements were compared to actual screw sizes. The effective size was 26.9-43.8%, 9.2-18.5%, and 21.1-30.5% larger than the actual size for the in vitro system (bone window), in vitro system (ultrawide window), and clinical cases, respectively. The mean gross difference for the in vitro measurements varied by implant size (p < 0.001) and was positively correlated with implant size (r = 0.846), but the mean percentage difference was negatively correlated with implant size (p < 0.001). Overestimation was larger for the in vitro model bone window compared to the ultrawide window (p < 0.001) and clinical cases (p = 0.001). Metallic artifact associated with titanium pedicle screws on CT resulted in an overestimation of screw size. This information might aid in the interpretation of implant placement on post-operative imaging.

A Context-Aligned Two Thousand Test: Toward estimating high-frequency French vocabulary knowledge for beginner-to-low intermediate proficiency adolescent learners in England

Vocabulary knowledge strongly predicts second language reading, listening, writing, and speaking. Yet, few tests have been developed to assess vocabulary knowledge in French. The primary aim of this pilot study was to design and initially validate the Context-Aligned Two Thousand Test (CA-TTT), following open research practices. The CA-TTT is a test of written form–meaning recognition of high-frequency vocabulary aimed at beginner-to-low intermediate learners of French at the end of their fifth year of secondary education. Using an argument-based validation framework, we drew on classical test theory and Rasch modeling, together with correlations with another vocabulary size test and proficiency measures, to assess the CA-TTT’s internal and external validity. Overall, the CA-TTT showed high internal and external validity. Our study highlighted the decisive role of the curriculum in determining vocabulary knowledge in instructed, low-exposure contexts. We discuss how this might contribute to under- or over-estimations of vocabulary size, depending on the relations between the test and curriculum content. Further research using the tool is openly invited, particularly with lower proficiency learners in this context. Following further validation, the test could serve as a tool for assessing high-frequency vocabulary knowledge at beginner-to-low intermediate levels, with due attention paid to alignment with curriculum content.

Model Predictability of Hail Precipitation with a Moderate Hailstorm Case. Part II: Impact of Improved Treatment of Graupel in the Thompson–Eidhammer Microphysics Scheme

Abstract Explicit simulation of hailstorms remains a challenge partly due to the lack of accurate representations of both initial conditions and microphysical processes. Using a moderate hailstorm case that occurred in Beijing on 10 June 2016, the impact of the initial conditions on explicit hail prediction has been studied in Part I of this two-part work via high-resolution data assimilation. This Part II paper examines the role of improved graupel treatment by comparing the recently upgraded Thompson–Eidhammer microphysics scheme (MP38) with two previous versions. MP38 is a double-moment hail-aware scheme with the ability to additionally predict the graupel number concentration and density. This case study showed that the addition of these predictive variables improved the simulation of the mass-weighted mean diameter of hail and thereby reduced the overestimation of hail size. However, the hail size was significantly underpredicted without the prediction of hail density, indicating that both quantities must be prognosed for skillful hail prediction. It was further shown that the revised graupel treatment also influenced hailstorm dynamics. The smaller hail size in MP38 led to a stronger graupel melting process, which further promoted a stronger cold pool and downdraft. By assessing the efficiency of the upgraded Thompson–Eidhammer microphysics scheme, the current study shed some light on the importance of the accurate representation of microphysical processes in numerical models for explicit hailstorm prediction.

The effect of an odd-one-out visual search task on attentional bias, body size adaptation, and body dissatisfaction.

Body image disturbance is a both a risk factor for, and a symptom of, many eating disorders and refers to the misperception of and dissatisfaction with one's own body. Women with high body dissatisfaction have been shown to direct more attention to low body mass index (BMI) bodies, which results in the overestimation of body size via body size adaptation. Therefore, attention may have a causal role in body image disturbance. We conducted a novel training visual search task with 142 young adult women who we trained to attend to either high or low BMI bodies. We assessed the effects of this training on attention to bodies of different sizes, body size adaptation, and body dissatisfaction. Women trained to attend to low BMI bodies decreased their perceptions of a 'normal' body size via adaptation from pre- to post-training (p < 0.001); however, women trained to attend to high BMI bodies showed no change in their perception of a 'normal' body size. We found no lasting effects of the training on attention to body size or body dissatisfaction; however, our visual search task showed poor internal consistency as a measure of attention. These findings indicate that attention to low BMI bodies may exacerbate body image disturbance in women. However, more reliable measures of attentional are required to confirm this finding.

Association of body image perception and (dis)satisfaction with adiposity in adults: The Pró-Saúde study.

Body image distortion and/or dissatisfaction may occur primarily due to body fat accumulation and/or distribution. The aim of this study was to evaluate the frequency of body image perception and (dis)satisfaction categories in adult men and women according to the adiposity classification. This is a cross-sectional study (n = 514; 33-79 years; 265 women) that is part of a prospective cohort (Pró-Saúde study). Adiposity measurements were determined by two methods: anthropometry, used to calculate the body mass index (BMI) and dual-energy X-ray absorptiometry (DXA), to estimate body fat percentage. Participants were grouped as "no excess adiposity" and "excess adiposity", considering BMI and body fat percentage (>30% for men, >40% for women). Perception and (dis)satisfaction with body image were evaluated using the Kakeshita scale, composed by 15 silhouettes, developed for the Brazilian population. Degree of distortion (perceived BMI - real BMI) and dissatisfaction (perceived BMI - desired BMI) were calculated. A high proportion of men (58.6%; 74.3%), and especially of women (82.6%; 86.8%), presented body size overestimation and dissatisfaction due to excess weight, respectively. A relevant fraction of the women (32.6%) and men (30.8%) who were dissatisfied due to excess weight did not present excess adiposity, especially if classified by DXA. Variability in degree of distortion was hardly explained by anthropometric and DXA variables in women (<5%) and men (∼22%). Both anthropometric and DXA measurements accounted for ∼30% and ∼50% of the variability in degree of dissatisfaction among women and men, respectively. Our results suggest a high frequency of body image distortion in Brazilian adult individuals, as well as dissatisfaction with excess weight, especially among women with excess adiposity. The findings indicate that anthropometric measurements explain much of the variability in degree of body image dissatisfaction in men, with no apparent advantage of the use of more refined DXA measurements.

Risks of regionalized stock assessments for widely distributed species like the panmictic European eel

Abstract In fisheries management, accurate stock assessment is pivotal to determine sustainable harvest levels or the scope of conservation measures. When assessment is decentralized and methods differ regionally, adopted approaches must be subjected to rigorous quality-checking, as biased assessments may mislead management decisions. To enable recovery of the critically endangered European eel, EU countries must fulfill a biomass target of potential spawner (“silver eel”) escapement, while local eel stock assessment approaches vary widely. We summarize local approaches and results of ground-truthing studies based on direct silver eel monitoring, to evaluate the accuracy of eel stock assessments in retrospect and identify bias sources. A substantial fraction of eel habitat is currently unassessed or assessed by unvalidated approaches. Across assessment models for which validation exists, demographic models frequently overestimated actual escapement, while misestimations of extrapolation (“spatial”) models were more balanced, slightly underestimating escapement. Stock size overestimation may lead to overexploitation or insufficient conservation measures, increasing the risk of stock collapse or slow recovery in coordinated frameworks. Underestimations may imply inefficient allocation of conservation efforts or negatively affect socioeconomy. Our work highlights the risks of regionalizing assessment responsibilities along with management decisions, calling for a common assessment toolbox and centralized quality-checking routines for eel.

Stacked neural network for predicting polygenic risk score

In recent years, the utility of polygenic risk scores (PRS) in forecasting disease susceptibility from genome-wide association studies (GWAS) results has been widely recognised. Yet, these models face limitations due to overfitting and the potential overestimation of effect sizes in correlated variants. To surmount these obstacles, we devised the Stacked Neural Network Polygenic Risk Score (SNPRS). This novel approach synthesises outputs from multiple neural network models, each calibrated using genetic variants chosen based on diverse p-value thresholds. By doing so, SNPRS captures a broader array of genetic variants, enabling a more nuanced interpretation of the combined effects of these variants. We assessed the efficacy of SNPRS using the UK Biobank data, focusing on the genetic risks associated with breast and prostate cancers, as well as quantitative traits like height and BMI. We also extended our analysis to the Korea Genome and Epidemiology Study (KoGES) dataset. Impressively, our results indicate that SNPRS surpasses traditional PRS models and an isolated deep neural network in terms of accuracy, highlighting its promise in refining the efficacy and relevance of PRS in genetic studies.

Deep genetic divergence among bluefish (Pomatomus saltatrix) of the Southwestern Atlantic

AbstractNeglected cryptic diversity can lead to the permanent loss of locally adapted alleles, which can reduce resilience to rapid environmental change. It can also result in overestimation of fisheries stock sizes that can result from treating different species as if they belonged to one. Bluefish (Pomatomus saltatrix) is considered a circumtropical and subtropical species and an important fishery resource all over the world. Differences in ecologically relevant traits are observed among isolated populations. Also, in the Southwestern Atlantic, molecular data suggest multiple populations, but these are treated as a single fish stock by regulatory agencies due to a lack of definitive information. We used whole mitogenome sequences, nuclear (rho) and mitochondrial (coxI and cytb) genes, as well as microsatellites to investigate historical and current genetic population structure and parameters of bluefish in the Western Atlantic. A total of 263 samples were collected along the Brazilian coast and in the USA (New Jersey, Northwest Atlantic). Data revealed the existence of two evolutionarily significant units (ESU) of bluefish along the South American coast, later confirmed by whole mitogenome sequencing of both haplogroups. These two ESUs have a mostly parapatric distribution, with some areas of overlap, which vary along the year. We also conducted seasonal sampling in Brazil to investigate migration patterns. ESUs occur mostly north and south of parallel 23° 40′ S, with an overlap area that varied seasonally. The level of differentiation between those two ESUs in the SW Atlantic, even in sympatry, is as high as that found between them and those from the NW Atlantic and Europe. Parapatric distribution and restricted gene flow suggest the existence of ecological barriers and local adaptation. The splitting of an ancient population from the Southwestern Atlantic into two putative species is important to understand bluefish evolutionary diversification and has implications for fishery regulatory measures in Brazil.

Assessment of Tunable Resistive Pulse Sensing (TRPS) Technology for Particle Size Distribution in Vaccine Formulations - A Comparative Study with Dynamic Light Scattering.

A comparative assessment was performed to evaluate the potential of particle sizing by an ensemble based conventional dynamic light scattering (DLS) technique and an emerging technology based on tunable resistive pulse sensing (TRPS) using particle by particle approach by evaluating three different types of vaccine formulations representing three case studies and showing the limitation of each technique, instrument variability, sensitivity, and the resolution in mixed population. Three types of in-house vaccine formulations- a protein antigen, an outer membrane vesicle and viral particles were simultaneously evaluated by TRPS based Exoid and two DLS instruments-Zetatrac and Zetasizer for particle size distribution, aggregates, and resolution of polydisperse species. The data from first case study show the risk of possible size overestimation and size averaging in polydisperse samples in DLS measurements which can be addressed by the TRPS analysis. It also shows how TRPS may be utilized only to large size antigens due to its limited size range. The second case study highlights the difference in the sensitivities of two DLS instruments working on the same principle. The third case study show that how TRPS can better resolve the large aggregate species compare to DLS in polydisperse samples. This analysis shows that TRPS can be used as an orthogonal technique in addition to conventional DLS based methods for more precise and in-depth characterization. Both techniques are efficient in size characterization and produce comparable results, however the choice will depend on the type of formulation and size range to be evaluated.

Assembly collapsing versus heterozygosity oversizing: detection of homokaryotic and heterokaryotic Laccaria trichodermophora strains by hybrid genome assembly.

Genome assembly and annotation using short-paired reads is challenging for eukaryotic organisms due to their large size, variable ploidy and large number of repetitive elements. However, the use of single-molecule long reads improves assembly quality (completeness and contiguity), but haplotype duplications still pose assembly challenges. To address the effect of read length on genome assembly quality, gene prediction and annotation, we compared genome assemblers and sequencing technologies with four strains of the ectomycorrhizal fungus Laccaria trichodermophora. By analysing the predicted repertoire of carbohydrate enzymes, we investigated the effects of assembly quality on functional inferences. Libraries were generated using three different sequencing platforms (Illumina Next-Seq, Mi-Seq and PacBio Sequel), and genomes were assembled using single and hybrid assemblies/libraries. Long reads or hybrid assemby resolved the collapsing of repeated regions, but the nuclear heterozygous versions remained unresolved. In dikaryotic fungi, each cell includes two nuclei and each nucleus has differences not only in allelic gene version but also in gene composition and synteny. These heterokaryotic cells produce fragmentation and size overestimation of the genome assembly of each nucleus. Hybrid assembly revealed a wider functional diversity of genomes. Here, several predicted oxidizing activities on glycosyl residues of oligosaccharides and several chitooligosaccharide acetylase activities would have passed unnoticed in short-read assemblies. Also, the size and fragmentation of the genome assembly, in combination with heterozygosity analysis, allowed us to distinguish homokaryotic and heterokaryotic strains isolated from L. trichodermophora fruit bodies.

The population genetics of partial diapause, with applications to the aestivating malaria mosquito Anopheles coluzzii.

Diapause, a form of dormancy to delay or halt the reproductive development during unfavourable seasons, has evolved in many insect species. One example is aestivation, an adult-stage diapause enhancing malaria vectors' survival during the dry season (DS) and their re-establishment in the next rainy season (RS). This work develops a novel genetic approach to estimate the number or proportion of individuals undergoing diapause, as well as the breeding sizes of the two seasons, using signals from temporal allele frequency dynamics. Our modelling shows the magnitude of drift is dampened at early RS when previously aestivating individuals reappear. Aestivation severely biases the temporal effective population size ( ), leading to overestimation of the DS breeding size by across 1 year, where is the aestivating proportion. We find sampling breeding individuals in three consecutive seasons starting from an RS is sufficient for parameter estimation, and perform extensive simulations to verify our derivations. This method does not require sampling individuals in the dormant state, the biggest challenge in most studies. We illustrate the method by applying it to a published data set for Anopheles coluzzii mosquitoes from Thierola, Mali. Our method and the expected evolutionary implications are applicable to any species in which a fraction of the population diapauses for more than one generation, and are difficult or impossible to sample during that stage.

Subcooled forced convection boiling flow measured using high-resolution techniques at the COSMOS-L facility and accompanying CFD simulation employing an interface-tracking scheme

This paper describes state-of-the-art experimental measurement techniques and computational fluid dynamics methods applied to subcooled forced convection boiling flow at 2-3 bar, both featuring high spatial- and time-resolution measurements. The objectives are: (i) to provide the measured boiling flow data, e.g. average and RMS profiles of axial and radial velocities and bubble size distributions, and (ii) to evaluate the capabilities of state-of-the-art numerical simulation techniques to model the observed phenomena, by comparison between measured data and numerical prediction. In the experiment, the bubble velocities in the axial and radial directions were measured using laser Doppler anemometry, and the bubble size was estimated by a shadowgraphy method. The simulation results, incorporating an interface capturing technique, showed good agreement with measurement in terms of the wall temperature and axial velocity, but underestimation of the radial velocity, and overestimation of bubble sizes. The paper shows that the discrepancies between measurement and simulation may be traced to: (i) the uncertainties in the nucleation site density model; (ii) too coarse a grid being adopted, which is not able to resolve the thermal boundary layer around the bubbles; and (iii) spurious numerical bubble coalescence, a feature not seen in the experiment. The mechanism of bubble lift-off from the hot surface, without any sliding motion, as observed in the experiment, is discussed in detail, based on the simulation results, and the condensation on the bubble cap as the bubble is ‘sucked’ into the bulk flow is also examined.

The role of contrast-enhanced mammography in the preoperative evaluation of invasive lobular carcinoma of the breast

To assess the performance of contrast-enhanced mammography (CEM) in the preoperative staging of invasive lobular carcinoma (ILC) of the breast. The present study was a multicentre, multivendor, multinational retrospective study of women with a histological diagnosis of ILC who had undergone CEM from December 2013 to December 2021. Index lesion size and multifocality were recorded for two-dimensional (2D) mammography, CEM, and when available magnetic resonance imaging (MRI). Comparison with histological data was undertaken for women treated by primary surgical excision. Pearson correlation coefficients and Bland-Altman's analysis of agreement were used to assess differences with a significance level of 0.05. One hundred and fifteen ILC lesions were included, 46 (40%) presented symptomatically and 69 were screening detected. CEM demonstrated superior sensitivity when compared to standard mammography. The correlation between the histological size measured on the surgical excision specimen size was greater than with standard mammography (r=0.626 and 0.295 respectively, p=0.001), with 19% of lobular carcinomas not visible without a contrast agent. The sensitivity of CEM for multifocal disease was greater than standard mammography (70% and 20% respectively, p<0.0001). CEM overestimated tumour size by an average of 1.5 times, with the size difference increasing for larger tumour. When MRI was performed (n=22), tumour size was also overestimated by an average of 1.3 times. The degree of size overestimation was similar for both techniques, with the tumour size on CEM being on average 0.5 cm larger than MRI. CEM is a useful tool for the local staging of lobular carcinomas and could be an alternative to breast MRI.

Automated Buffer Sizing of Dataflow Applications in a High-level Synthesis Workflow

High-Level Synthesis (HLS) tools are mature enough to provide efficient code generation for computation kernels on FPGA hardware. For more complex applications, multiple kernels may be connected by a dataflow graph. Although some tools, such as Xilinx Vitis HLS, support dataflow directives, they lack efficient analysis methods to compute the buffer sizes between kernels in a dataflow graph. This article proposes an original method to safely approximate such buffer sizes. The first contribution computes an initial overestimation of buffer sizes without knowing the memory access patterns of kernels. The second contribution iteratively refines those buffer sizes, thanks to cosimulation. Moreover, the article introduces an open source framework using these methods to facilitate dataflow programming on FPGA using HLS. The proposed methods and framework have been tested on seven dataflow applications and outperform Vitis HLS cosimulation in five benchmarks, either in terms of BRAM and LUT usage, or in terms of exploration time. In the two other benchmarks, our best method gets results similar to Vitis HLS. Last but not least, our method admits directed cycles in the application graphs.

Delayed treatment effect predicting (DTEP) model for guiding immuno-oncology trial designs

BackgroundThe presence of delayed treatment effects (DTE) is common in immuno-oncology trials. However, conventional trial designs often overlook the potential presence of DTE, which can result in an underestimation of the required sample size and loss of statistical power. Conversely, when there is actually no apparent delay in treatment effects, alternative trial designs for addressing DTE may lead to an overestimation of sample size and unnecessary prolongation of the trial duration. To mitigate this challenge, we propose the use of a DTE predicting (DTEP) model to better guide immuno-oncology trial designs. MethodsThe DTEP model was developed and validated using data from 147 published randomized immuno-oncology trials. The eligible trials were divided into a training set (approximately 75% of the trials) and a test set (approximately 25%). We employed linear discriminant analysis (LDA) to develop the DTEP model for predicting the DTE status using baseline characteristics available at the trial design stage. The receiver operating characteristic (ROC) curve was utilized to assess the ability of the model to distinguish between trials with and without DTE. We further re-conducted the JUPITER-02 trial in a simulation setting, employing three design approaches to assess the potential benefits of utilizing the DTEP model. ResultsBaseline characteristics available during the trial design stage, including cancer type, line of treatment, and experimental and control arm regimens were incorporated, and high accuracy in predicting the DTE status in both the training set (area under the operating characteristic curve (AUC), 0.79; 95% confidence interval (CI), 0.71–0.88) and test set (AUC, 0.78; 95% CI, 0.66–0.90) was achieved. Notably, the model successfully predicted the DTE status in two randomized trials among the test sets that were conducted by our team (ESCORT-1st (absence of DTE) and JUPITER-02 (presence of DTE)). In silico re-conduct of the JUPITER-02 trial further showed that the statistical power would be markedly improved when trial designs were guided by the DTEP model. ConclusionsThe DTEP model can significantly enhance the precision and effectiveness of immuno-oncology trial designs, thereby facilitating the discovery of effective immunotherapeutics in a more streamlined and expedited manner.