Mean Estimates Research Articles

Systematic review and meta-analysis of Neck Disability Index and Numeric Pain Rating Scale in patients with migraine and tension-type headache.

The present study aimed to assess the burden of neck pain in adults with migraine and tension-type headache (TTH), utilizing the Neck Disability Index (NDI) and Numeric Pain Rating Scale (NPRS). A systematic literature search was conducted on PubMed and Embase to identify observational studies assessing NDI and NPRS in populations with migraine or TTH. The screening of articles was independently performed by two investigators (HMA and ZA). Pooled mean estimates were calculated through random-effects meta-analysis. The I2 statistic assessed between-study heterogeneity, and meta-regression further explored heterogeneity factors. Thirty-three clinic-based studies met the inclusion criteria. For participants with migraine, the pooled mean NDI score was 16.2 (95% confidence interval (CI) = 13.2-19.2, I2 = 99%). Additionally, the mean NDI was 5.5 (95% CI = 4.11-6.8, p < 0.001) scores higher in participants with chronic compared to episodic migraine. The pooled mean NDI score for participants with TTH was 13.7 (95% CI = 4.9-22.4, I2 = 99%). In addition, the meta-analysis revealed a mean NPRS score of 5.7 (95% CI = 5.1-6.2, I2 = 95%) across all participants with migraine. This systematic review and meta-analysis shows a greater degree of neck pain-related disability in migraine compared to TTH. Nevertheless, the generalizability of these findings is constrained by methodological variations identified in the current literature.

Validation of an AI-Powered Automated X-ray Bone Age Analyzer in Chinese Children and Adolescents: A Comparison with the Tanner-Whitehouse3 Method.

Automated bone age assessment (BAA) is of growing interest because of its accuracy and time efficiency in daily practice. In this study, we validated the clinical applicability of a commercially available artificial intelligence (AI)-powered X-ray bone age analyzer equipped with a deep learning-based automated BAA system and compared its performance with that of the Tanner-Whitehouse3 (TW-3) method. Radiographs prospectively collected from 30 centers across various regions in China, including 900 Chinese children and adolescents, were assessed independently by six doctors (three experts and three residents) and an AI analyzer for TW3 radius, ulna, and short bones (RUS) and TW3 carpal bone age. The experts' mean estimates were accepted as the gold standard. The performance of the AI analyzer was compared with that of each resident. For the estimation of TW3-RUS, the AI analyzer had a mean absolute error (MAE) of 0.48 ± 0.42. The percentage of patients with an absolute error of < 1.0years was 86.78%. The MAE was significantly lower than that of rater1 (0.54 ± 0.49, P = 0.0068); however, it was not significant for rater2 (0.48 ± 0.48) or rater3 (0.49 ± 0.46). For TW3 carpal, the AI analyzer had an MAE of 0.48 ± 0.65. The percentage of patients with an absolute error of < 1.0years was 88.78%. The MAE was significantly lower than that of rater2 (0.58 ± 0.67, P = 0.0018) and numerically lower for rater 1 (0.54 ± 0.64) and rater3 (0.50 ± 0.53). These results were consistent for the subgroups according to sex, and differences between the age groups were observed. In this comprehensive validation study conducted in China, an AI-powered X-ray bone age analyzer showed accuracies that matched or exceeded those of doctor raters. This method may improve the efficiency of clinical routines by reducing reading time without compromising accuracy.

Treatment of Menstrual Irregularities with Individualized Homeopathic Medicinal Products in Early Reproductive Females: A Double-Blind, Randomized, Placebo-Controlled Trial.

Objectives: Prevalence of irregular menstrual cycle ranges from 81.7% to 96.3%. Recent research suggested that homeopathy is one of the most popular choices for women with various gynecological disorders. This trial was aimed at differentiating individualized homeopathic medicinal products (IHMPs) from identical-looking placebos in the treatment of menstrual irregularities in early reproductive women. Design: Double-blind, randomized (1:1), two parallel arms, placebo-controlled trial. Setting: D. N. De Homoeopathic Medical College & Hospital, Kolkata, West Bengal, India. Subjects: Ninety-two females with menstrual irregularities. Interventions: Group verum (n = 46; IHMPs plus concomitant care) versus group control (n = 46; placebos plus concomitant care). Outcome Measures: Primary-The proportion of early reproductive females in whom menstrual irregularities can be corrected for consecutive three cycles; Secondary-Menstrual Distress Questionnaire (MDQ) total score; all of them were measured at baseline and every month, up to 4 months. Results: Intention-to-treat sample (n = 92) was analyzed. Group differences were examined by chi-squared tests with categorical outcomes, two-way repeated measure analysis of variance accounting for the time-effect interactions, and unpaired t-tests comparing the mean estimates obtained individually every month. The level of significance was set at p < 0.05 two-tailed. After 4 months of intervention, the group difference in the primary outcome was nonsignificant statistically-IHMPs: 22/46 v/s placebo: 24/46, chi-square (Yates corrected) = 0.043, p = 0.835. The improvement observed in the MDQ total score (F1,90 = 0.054, p = 0.816) and subscales scores were higher in the IHMPs group than in placebos, however statistically nonsignificant in most of the occasions, except for the behavioral change subscale (F1,90 = 0.029, p < 0.001). Pulsatilla nigricans was the most frequently prescribed medicine. Kent's Repertory and Zandvoort's Complete Repertory were the most frequently used repertories. No harm or serious adverse events were reported from either group. Conclusions: The analysis failed to demonstrate clearly that IHMPs were effective beyond placebos in all but one of the outcomes. More appropriate outcome measures may be sought for future trials. Clinical Trial Registration Number: CTRI/2022/04/041659.

Inelastic Spectra to Predict Constant-Damage Energy Factor of Structures Under Near-Fault Pulse-Type Ground Motions

ABSTRACT A simple relationship is proposed to construct constant-damage energy factor (γ DI) spectra of single-degree-of-freedom (SDOF) oscillators with different levels of damage, expressed by the Park-Ang damage index. γ DI is computed for SDOF oscillators with four hysteretic models when subjected to 80 pulse-like ground motions. The statistical dependence of γ DI on initial period, damage index, postyield stiffness ratio, and ultimate ductility factor is investigated. In comparison with the non-pulse-type ground motions, the near-fault pulse-type ground motions can significantly increase the γ DI of structures, and the magnitude of the increase can reach about 200%. Conservative estimates of mean γ DI of SDOF oscillators are proposed taking into account the combined effect of period, damage level, and ultimate ductility factor.

Nonlinear modelling of arrays of submerged wave energy converters

Studies of arrays of wave energy converters (WECs) with respect to power absorption and array interactions are often performed using linear models. However, nonlinear effects can be important and may change power estimates and optimal array designs. In this study, we have compared linear predictions of the behaviour of a shallowly submerged, buoyant point absorber with predictions from the nonlinear model SWASH with a WEC incorporated (WEC-SWASH). The latter was first comprehensively validated against 1:20 Froude scaled measured data from physical experiments. WEC-SWASH predictions of body motions and mean power absorption were generally in good agreement with measurements (absolute bias within 25%), although some discrepancies were observed in the body motions, especially when the device exhibited motion instabilities. The validated WEC-SWASH model was then compared with a linear frequency-domain model, as the latter is well-known and widely used because of its computational efficiency. Model comparisons were carried out for both an isolated WEC and small arrays (up to 5 devices). The mean power estimates from the linear model and WEC-SWASH for two representative wave farms showed good agreement for mild waves, with a difference of less than 5%. However, for larger waves, the disagreement increased to about 75 to 85% between the models (for the two wave farms tested). We found that array interactions for these arrays depend on wave amplitude and not just wave frequency. Furthermore, we discovered that the power take-off coefficients optimized using the linear model were not the optimum coefficients for the nonlinear model (WEC-SWASH).

Numerical and Thermal Response of the Bacterivorous Ciliate Colpidium kleini, a Species Potentially at Risk of Extinction by Rising Water Temperatures

We investigated the food-dependent growth and thermal response of the freshwater ciliate Colpidium kleini using numerical response (NR) experiments. This bacterivorous ciliate occurs in lotic water and the pelagial of lakes and ponds. The C. kleini strain used in this work was isolated from a small alpine lake and identified by combining detailed morphological inspections with molecular phylogeny. Specific growth rates (rmax) were measured from 5 to 21 °C. The ciliate did not survive at 22 °C. The threshold bacterial food levels (0.3 − 2.2 × 106 bacterial cells mL−1) matched the bacterial abundance in the alpine lake from which C. kleini was isolated. The food threshold was notably lower than previously reported for C. kleini and two other Colpidium species. The threshold was similar to levels reported for oligotrich and choreotrich ciliates if expressed in terms of bacterial biomass (0.05 − 0.43 mg C L−1). From the NR results, we calculated physiological mortality rates at zero food concentration. The mean mortality (0.55 ± 0.17 d−1) of C. kleini was close to the mean estimate obtained for other planktonic ciliates that do not encyst. We used the data obtained by the NR experiments to fit a thermal performance curve (TPC). The TPC yielded a temperature optimum at 17.3 °C for C. kleini, a maximum upper thermal tolerance limit of 21.9 °C, and a thermal safety margin of 4.6 °C. We demonstrated that combining NR with TPC analysis is a powerful tool to predict better a species’ fitness in response to temperature and food.

PLAN: Variance-Aware Private Mean Estimation

Differentially private mean estimation is an important building block in privacy-preserving algorithms for data analysis and machine learning. Though the trade-off between privacy and utility is well understood in the worst case, many datasets exhibit structure that could potentially be exploited to yield better algorithms. In this paper we present Private Limit Adopted Noise (PLAN), a family of differentially private algorithms for mean estimation in the setting where inputs are independently sampled from a distribution D over R^d, with coordinate-wise standard deviations σ in R^d. Similar to mean estimation under Mahalanobis distance, PLAN tailors the shape of the noise to the shape of the data, but unlike previous algorithms the privacy budget is spent non-uniformly over the coordinates. Under a concentration assumption on D, we show how to exploit skew in the vector σ, obtaining a (zero-concentrated) differentially private mean estimate with l_2 error proportional to ||σ||_1. Previous work has either not taken σ into account, or measured error in Mahalanobis distance --- in both cases resulting in l_2 error proportional to sqrt{d}||σ||_2, which can be up to a factor sqrt{d} larger. To verify the effectiveness of PLAN, we empirically evaluate accuracy on both synthetic and real-world data.

Modified median quartile double ranked set sampling for estimation of population mean

Environmental monitoring and assessment aim to gather data economically, without bias, using efficient and cost-effective sampling methods. One such traditional method is Ranked Set Sampling (RSS), often employed to achieve observational economy. This article introduces an innovative two-stage sampling approach for ranked set sampling (RSS) to get a more precise estimate of the population mean. Modified Median Quartile Double Ranked Set Sampling (MMQDRSS) highlights the ranked base technique's potential as a cost-effective sampling method. To evaluate the performance of the proposed estimator by using real-life data and conducting a simulation study to compare the relative efficiency of the proposed estimator with some existing methods.

Gonial Angle in Forensic Anthropology to Determine Age and Gender: A Population-Specific Analysis.

Background The study highlights the gonial angle as a key craniofacial landmark for age and gender determination in forensic cases. It emphasizes population-specific analysis, enhancing precision by recognizing variations between populations. By clarifying the gonial angle's forensic use, the study offers clear guidelines, improving forensic practices. Moreover, the gonial angle and age and gender correlations are thoroughly examined, offering important information on their forensic relevance. The results highlight how crucial population-specific research is to improving the precision and dependability of forensic age and gender estimation techniques, which advances forensic anthropology and supports forensic investigations around the globe. Aim and objective The purpose of this study is to assess the accuracy of age and gender estimates using gonial angles. The objectives of this research are to evaluate the precision of age and gender estimates utilizing the gonial angle. Materials and methods This present study comprises two groups based on age groups: Group I belongs to 51 to 60 years of age, and Group II belongs to 61 to 70 years of age. Making use of G-Power software (version 3.1.9.4, Düsseldorf, Germany), the sample size was determined. The calculation ensured 95% statistical power at a significance level (alpha error probability) of 0.05. To achieve sufficient statistical power, a total of 1000 samples were included, with a projected required sample size of 92. A total of 1000 samples, consisting of 500 male and 500 female panoramic radiographs,were meticulously selected for the study. The samples picked were within the age range of 51 to 70 years. Orthopantomograms were determined using Planmeca software (Planmeca Romexis®, Version 6.0, USAInc.). Descriptive statistics, including prediction classification analysis of age and gender, were conducted using SPSS Statistics version 16.0 (SPSS Inc., Released 2007, SPSS for Windows, Version 16.0, Chicago, SPSS Inc.). Results According to this study, the mean gonial angle of males aged 51 to 60 years is larger (124.7370degrees) than that of females (119.6371degrees). The female group's mean estimates are more accurate, as seen by the smaller standard error (0.20844) compared to the male group's (0.60998). A statistically significant difference in mean gonial angles between the genders is evident, with males having a larger gonial angle (p-value <0.001). In the age range of 61 to 70 years, the mean gonial angle of females is higher (128.4322degrees) than that of males (124.0529degrees). In this instance, the male group's standard error is smaller (0.14968) than the female group's (0.30028), indicating more accurate mean estimates. Once more, a statistically significant difference is indicated by a p-value of less than 0.001, with females having a larger gonial angle than males. Conclusion Our study revealed that the gonial angle of the mandible can be considered a reliable parameter for gender identification. The study's limitation is its inability to reliably identify gender in the subadult population and in cases of edentulousness. An orthopantomogram is a trustworthy and accurate method for taking the different measurements needed to identify the gender of a particular mandible.

A PINN-DeepONet framework for extracting turbulent combustion closure from multiscalar measurements

In this study, we develop a novel framework to extract turbulent combustion closure, including closure for species chemical source terms, from multiscalar and velocity measurements in turbulent flames. The technique is based on a physics-informed neural network (PINN) that combines models for velocity and scalar measurements and a deep operator network (DeepONet) to accommodate spatial measurements and experimental parameters as separate input streams. An additional key innovation is the estimate of the unconditional means of the species’ chemical source terms as additional “observations” to constrain the prediction of these rates. This estimate is based on a convolution of the means of species reaction rates conditioned on principal components of the multiscalar data and the joint probability density functions of these principal components. The PINN-DeepONet method is implemented on the so-called Sydney flames, where training is carried out on 3 flames and validated on 4 flames. The results show that, despite the limited samples of experimental parameters, including the inlet flow and the fuel jet recess length within the air flow, the PINN-DeepONet approach can construct velocity and scalar fields along with important closure terms for turbulent transport and reaction rates.

Quality factors of an English as a Medium of Instruction program associated with students’ satisfaction

This study examines the association between key quality factors of an English as a Medium of Instruction (EMI) program delivered at a Spanish university with the students’ satisfaction. The significant growth of demand and offer of bilingual and plurilingual studies in Higher Education in the last decade in many non-Anglo-Saxon countries, recommends conducting more evaluation research studies aimed at measuring quality and impact of EMI programs on students’ performance and satisfaction. To respond to that need, this ex-post facto research study included a sample of 131 self-selected students. The dependent variable student satisfaction was measured with a questionnaire (α=0.82 and a ω= 0.85) delivered through a computer-assisted web interviewing technique. Nonparametric regression analysis results confirm partially two out of the four hypotheses tested with an average of the mean estimate of 3.7 (on a 5 points scale) and the (only) average marginal significant effect of teachers teaching practices estimated to be 0.7, p &lt; 0.01. The model (M6) with all predictions and controls explains 40.69% of the variation of the dependent variable. Finally, some conclusions and recommendations are drawn to increase future students’ satisfaction about this type of Higher Education.

Why is a small sample size not enough?

Clinical studies are often limited by resources available, which results in constraints on sample size. We use simulated data to illustrate study implications when the sample size is too small. Using 2 theoretical populations each with N = 1000, we randomly sample 10 from each population and conduct a statistical comparison, to help make a conclusion about whether the 2 populations are different. This exercise is repeated for a total of 4 studies: 2 concluded that the 2 populations are statistically significantly different, while 2 showed no statistically significant difference. Our simulated examples demonstrate that sample sizes play important roles in clinical research. The results and conclusions, in terms of estimates of means, medians, Pearson correlations, chi-square test, and P values, are unreliable with small samples.

Variability in zoobenthic blue carbon storage across a southern polar gradient

The seabed of the Antarctic continental shelf hosts most of Antarctica's known species, including taxa considered indicative of vulnerable marine ecosystems (VMEs). Nonetheless, the potential impact of climatic and environmental change, including marine icescape transition, on Antarctic shelf zoobenthos, and their blue carbon-associated function, is still poorly characterised. To help narrow knowledge gaps, four continental shelf study areas, spanning a southern polar gradient, were investigated for zoobenthic (principally epi-faunal) carbon storage (a component of blue carbon), and potential environmental influences, employing a functional group approach. Zoobenthic carbon storage was highest at the two southernmost study areas (with a mean estimate of 41.6 versus 7.2 g C m−2) and, at each study area, increased with morphotaxa richness, overall faunal density, and VME indicator density. Functional group mean carbon content varied with study area, as did each group's percentage contribution to carbon storage and faunal density. Of the environmental variables explored, sea-ice cover and primary production, both likely to be strongly impacted by climate change, featured in variable subsets most highly correlating with assemblage and carbon storage (by functional groups) structures. The study findings can underpin biodiversity- and climate-considerate marine spatial planning and conservation measures in the Southern Ocean.

Spawning history, fecundity, and potential sperm limitation of female blue crabs in Chesapeake Bay

The blue crab (Callinectes sapidus) is an ecologically and economically important species in estuaries of the Western Atlantic Ocean and Gulf of Mexico. Given the importance of reproductive output and spawner demography on population dynamics, blue crab management may be improved if individual-based changes in egg production are identified and incorporated into management advice. We determined the spawning history, batch fecundity, and stored sperm quantity of 126 ovigerous blue crabs in 2022 to estimate the reproductive potential of female blue crabs in Chesapeake Bay. Our mean estimate of fecundity, 2.17 million eggs/female, is similar to a fecundity estimate from 1986 (2.6 million eggs/female), but lower than an estimate from 1987 (4.0 million eggs/female). The 1987 estimate was likely biased high due to methodological differences. In 2022, size-specific fecundity did not differ from that in 1986. Size-specific fecundity was lower by 0.28 million eggs in multiparous females (i.e., those that produced at least one previous egg mass) compared with primiparous females (i.e., those producing their first egg mass). Size-specific fecundity was also greater in July and August than in June, however, females in June had a greater capacity for future reproductive potential because their average stored sperm quantity was three times greater than that of females in July and August. Most females in June were primiparous and would become multiparous females in July and August with higher size-specific fecundity. Our study is the first to pair individual fecundity, stored sperm quantity, and spawning history for blue crabs, which allows for a robust assessment of reproductive potential. Generally, the reproductive potential of individual female blue crabs was high at the individual level, such that sperm limitation is unlikely at the population level. Population-level production may be increased by protecting primiparous spawners as these crabs have the highest capacity to contribute offspring to the population. Furthermore, fisheries management may be improved by using our updated estimate of size-specific fecundity (Fecundity = 268,337 × exp(0.015 × Carapace Width)) and incorporating month or spawner history in models of stock production.

Phase II study of fezolinetant for treatment of vasomotor symptoms associated with menopause in Japan

Objective The phase II STARLIGHT study was conducted to investigate the efficacy/safety of fezolinetant in Japanese women and identify the optimal dose for future evaluation. Method Participants were perimenopausal/postmenopausal women aged ≥40 to ≤65 years from 36 centers in Japan seeking treatment/relief for vasomotor symptoms (VMS) associated with menopause. After screening, participants were randomized 1:1:1, stratified by menopausal status, to receive fezolinetant 15 or 30 mg or placebo orally once daily for 12 weeks. Participants completed a daily VMS diary. The primary endpoint was mean change in frequency of VMS of any severity from baseline to week 8. Secondary endpoints included mean change in VMS frequency from baseline each week up to week 12 and frequency/severity of adverse events. Results A total of 147 participants were randomized (placebo, n = 47; fezolinetant 15 mg, n = 53; fezolinetant 30 mg, n = 47). Fezolinetant 15 and 30 mg demonstrated statistically significant reductions in mean VMS frequency at week 8 versus placebo. Least-squares mean estimates of mean change in frequency of VMS from baseline to week 8 were −7.04 for fezolinetant 15mg, −6.31 for fezolinetant 30mg, and −4.55 for placebo. The difference in least-squares mean estimates was −2.50 (95% CI: −4.03, −0.96), p = 0.002 for fezolinetant 15mg and placebo, and was −1.76 (95% confidence interval [CI]: −3.35, −0.17), p = 0.030 for fezolinetant 30mg and placebo. Reductions from baseline in mean VMS frequency versus placebo were seen after week 1 of treatment, maintained throughout 12 weeks. Fezolinetant was well tolerated, with no safety signals of concern for either dose to week 12. Conclusion Oral fezolinetant at once-daily doses of 15 or 30 mg was efficacious and well tolerated for treatment of mild, moderate and severe VMS associated with menopause in this Japanese study.

In Vitro Investigation of Insulin Dynamics During 4 Hours of Simulated Cardiopulmonary Bypass.

Hyperglycemia is common in patients undergoing cardiovascular surgery with cardiopulmonary bypass. We hypothesize that intraoperative hyperglycemia may be, at least partially, attributable to insulin loss due to adhesion on artificial surfaces and/or degradation by hemolysis. Thus, our primary aim was to investigate the loss of insulin in 2 different isolated extracorporeal circulation circuits (ECCs), that is, a conventional ECC (cECC) with a roller pump, and a mini-ECC (MiECC) system with a centrifugal pump. The secondary aim was to assess and compare the relationship between changes in insulin concentration and the degree of hemolysis in our 2 ECC models. Six cECC and 6 MiECC systems were primed with red packed blood cells and thawed fresh-frozen plasma (1:1). Four additional experiments were performed in cECC using only thawed fresh-frozen plasma. Human insulin (Actrapid) was added, targeting a plasma insulin concentration of 400 mU/L. Insulin concentration and hemolysis index were measured at baseline and hourly thereafter. The end points were the change in insulin level after 4 hours compared to baseline and hemolysis index after 4 hours. The insulin concentration and hemolysis index were analyzed by means of a saturated linear mixed-effect regression model with a random offset for each experiment to account for the repeated measure design of the study, resulting in mean estimates and 95% confidence intervals (CIs) of the primary end points as well as of pairwise contrasts with respect to ECC type. Insulin concentration decreased by 63% (95% CI, 48%-77%) in the MiECC and 92% (95% CI, 77%-106%) in the cECC system that contained red blood cells. Insulin loss was significantly higher in the cECC system compared to the MiECC (P = .022). In the cECC with only plasma, insulin did not significantly decrease (-4%; 95% CI, -21% to 14%). Hemolysis index in MiECC increased from 68 (95% CI, 46-91) to 76 (95% CI, 54-98) after 4 hours, in cECC from 81 (95% CI, 59-103) to 121 (95% CI, 99-143). Hemolysis index and percent change of insulin showed an excellent relationship (r = -0.99, P < .01). Our data showed that insulin levels substantially decreased during 4 hours of simulated cardiopulmonary bypass only in the ECC that contained hemoglobin. The decrease was more pronounced in the cECC, which also exhibited a greater degree of hemolysis. Our results suggest that insulin degradation by hemolysis products may be a stronger contributor to insulin loss than adhesion of insulin molecules to circuit surfaces.

Optimal training of Mean Variance Estimation neural networks

This paper focusses on the optimal implementation of a Mean Variance Estimation network (MVE network) (Nix and Weigend, 1994). This type of network is often used as a building block for uncertainty estimation methods in a regression setting, for instance Concrete dropout (Gal et al., 2017) and Deep Ensembles (Lakshminarayanan et al., 2017). Specifically, an MVE network assumes that the data is produced from a normal distribution with a mean function and variance function. The MVE network outputs a mean and variance estimate and optimizes the network parameters by minimizing the negative loglikelihood.In our paper, we present two significant insights. Firstly, the convergence difficulties reported in recent work can be relatively easily prevented by following the simple yet often overlooked recommendation from the original authors that a warm-up period should be used. During this period, only the mean is optimized with a fixed variance. We demonstrate the effectiveness of this step through experimentation, highlighting that it should be standard practice. As a sidenote, we examine whether, after the warm-up, it is beneficial to fix the mean while optimizing the variance or to optimize both simultaneously. Here, we do not observe a substantial difference. Secondly, we introduce a novel improvement of the MVE network: separate regularization of the mean and the variance estimate. We demonstrate, both on toy examples, multiple benchmark UCI regression data sets, and on the UTKFace data set, that following the original recommendations and the novel separate regularization can lead to significant improvements.

A comparative study of 3D measuring methods for monitoring breast volume changes

Three-dimensional (3D) imaging techniques are promising new tools for measuring breast volume, for example in gender-affirming therapy. Transgender individuals can be treated with gender-affirming hormone therapy (GAHT). A robust method for monitoring breast volume changes is critical to be able to study the effects of feminizing GAHT. The primary aim of this study was to compare the accuracy of three 3D devices (Vectra XT, Artec LEO and iPhone XR) for measuring modest breast volume differences using a mannequin. The secondary aim of this study was to evaluate these methods in several performance domains. We used reference prostheses of increasing volumes and compared the volumes using GOM-inspect software. For Vectra XT 3D images, manufacturer-provided software was used to calculate volumes as well. The scanning methods were ranked based on their performance in a total of five categories: volume estimations, costs, user-friendliness, test subject-friendliness and technical aspects. The 3D models analyzed with GOM-inspect showed relative mean estimate differences from the actual volumes of 9.1% for the Vectra XT, 7.3% for the Artec LEO and 14% for the iPhone XR. For the Vectra XT models analyzed with the built-in software this was 6.2%. Root mean squared errors (RMSE) calculated based on the GOM-inspect volume analyses showed mean RMSEs of 2.27, 2.54 and 8.93 for the Vectra XT, Artec LEO and iPhone XR, respectively. The Vectra software had a mean RMSE of 3.00. In the combined performance ranking, the Vectra XT had the most favorable ranking, followed by the Artec LEO and the iPhone XR. The Vectra XT and Artec LEO are the preferred scanners to monitor breast development due to the combination of higher accuracy and overall performance. The current study shows that 3D techniques can be used to adequately measure modest breast volume differences and therefore will be useful to study for example breast changes in transgender individuals using feminizing GAHT. These observations may also be relevant in other fields of 3D imaging research.

Baseline PSMA PET/CT as a predictive biomarker for toxicity and patient-reported outcomes in mCRPC patients undergoing 177Lu-PSMA radioligand therapy.

e17058 Background: The phase III VISION trial demonstrated that 177Lu-PSMA-617 (PSMA-RLT) prolonged overall survival in patients with metastatic castration-resistant prostate cancer (mCRPC). Common side effects of PSMA-RLT include xerostomia, bone pain, and myelosuppression. The objective of this study is to evaluate the role of baseline PSMA PET/CT (bPET) in predicting hematologic toxicity and patient-reported outcomes in mCRPC patients undergoing PSMA-RLT. Methods: Patients treated with 177Lu-PSMA-617 in the Expanded Access Program at UCLA with available bPET, toxicity data, and patient-reported outcomes (BPI, FACT-P, and Xerostomia Questionnaire) were included in this retrospective analysis. TRAQinform IQ technology (AIQ Solutions-Madison, WI) was used to conduct region of interest (ROI)-based analyses at bPET. SUVmean, SUVmax, volume (cm3), and total lesion PSMA (TLP; SUVmean x volume) of the whole-body tumor burden, healthy bone, and the salivary glands were extracted. We evaluated the following associations: 1) Whole-body tumor parameters on bPET with time to worsening of FACT-P scores (defined as a decrease of &gt;10 points from baseline) and time to first occurrence of Grade 3 or 4 hematologic toxicity (Multivariate Cox regression model); 2) Healthy bone parameters on bPET with time to worsening of BPI Pain Severity and Pain Interference scores (defined as a 30% increase or at least 2 points from baseline) and time to first occurrence of Grade 3 or 4 hematologic toxicity (Multivariate Cox regression model); 3) Salivary gland parameters on bPET with Xerostomia Questionnaire scores (Mixed-effect linear regression model). Results: 61 mCRPC patients were included. When evaluating associations between healthy bone SUVmean, SUVmax, and TLP with time to first occurrence of Grade 3 or 4 hematologic toxicity, baseline hemoglobin was associated with a longer time to first occurrence (HR = 0.61, p = 0.005; HR = 0.59, p = 0.002; HR = 0.62, p = 0.005 respectively). When evaluating associations between bPET and time to worsening of FACT-P scores, whole-body tumor SUVmean, SUVmax, and TLP were associated with a longer time to worsening (HR = 0.74, p = 0.033; HR = 0.82, p = 0.01; HR = 0.91, p = 0.028 respectively). When evaluating associations between salivary gland SUVmean, volume, SUVmax, and TLP with Xerostomia Questionnaire scores, the number of cycles was associated with higher scores (mean estimate: 0.63, p = 0.003; mean estimate: 0.64, p = 0.003; mean estimate: 0.64, p = 0.003; mean estimate: 0.63, p = 0.003 respectively). Conclusions: In this retrospective analysis of 61 mCRPC patients treated with PSMA-RLT, bPET parameters were generally not predictive of hematologic toxicity or patient-reported outcomes. Of note, whole-body tumor SUV was associated with a longer time to worsening of FACT-P scores. Validation in a larger, prospective cohort is warranted.

BANK TECHNICAL EFFICIENCY OF COUNTRY GROUPS: A META-REGRESSION ANALYSIS

Purpose- This study endeavors to examine studies using Data Envelopment Analysis in calculating the banking sector efficiency across country groups and to determine the factors affecting their technical efficiency through meta-regression analysis. Methodology- As of November 22, 2023, relevant works were systematically reviewed using Web of Science, Scopus, and Google Scholar. The literature review employed a comprehensive search encompassing all files with the keywords such as ‘‘technical efficiency (All Field) AND bank (All Field)’’. The research process adhered to the PRISMA guidelines. This study reviewed all studies published between 1932 and 2023 identifying 64599 studies in the initial scan by the author. The author independently scrutinized the titles, abstracts, keywords, text, and references of all manuscripts to mitigate selection bias and reveal whether eligibility criteria were met. Exclusions from the scope encompassed duplicate downloads, papers, books and book chapters, together with studies having low quality scores, no full-text versions, and those that are irrelevant to the subject. Findings- The results of meta-regression analysis revealed that the data collection year of the studies and the income groups of the countries did not have an impact on the mean technical efficiency. The number of banks, number of observations, publication year, and number of countries were statistically significant on the mean technical efficiency estimate. Conclusion- The study further standardized variables and methodological assumptions used in bank sector efficiency studies within country groups through meta-regression analysis. Empirical findings in the literature were combined. This study enhances accessibility to the existing body of knowledge for researchers in the field