Within-subject Correlation Research Articles

A Novel Method to Predict Carbohydrate and Energy Expenditure During Endurance Exercise Using Measures of Training Load.

Sports nutrition guidelines recommend carbohydrate (CHO) intake be individualized to the athlete and modulated according to changes in training load. However, there are limited methods to assess CHO utilization during training sessions. We aimed to (1) quantify bivariate relationships between both CHO and overall energy expenditure (EE) during exercise and commonly used, non-invasive measures of training load across sessions of varying duration and intensity and (2) build and evaluate prediction models to estimate CHO utilization and EE with the same training load measures and easily quantified individual factors. This study was undertaken in two parts: a primary study, where participants performed four different laboratory-based cycle training sessions, and a validation study where different participants performed a single laboratory-based training session using one of three exercise modalities (cycling, running, or kayaking). The primary study included 15 cyclists (five female; maximal oxygen consumption [ O2max], 51.9 ± 7.2mL/kg/min), the validation study included 21 cyclists (seven female; O2max 53.5 ± 11.0mL/kg/min), 20 runners (six female; O2max 57.5 ± 7.2mL/kg/min), and 18 kayakers (five female; O2max 45.6 ± 4.8mL/kg/min). Training sessions were quantified using six training load metrics: two using heart rate, three using power, and one using perceived exertion. Carbohydrate use and EE were determined separately for aerobic (gas exchange) and anaerobic (net lactate accumulation, body mass, and O2 lactate equivalent method) energy systems and summed. Repeated-measures correlations were used to examine relationships between training load and both CHO utilization and EE. General estimating equations were used to model CHO utilization and EE, using training load alongside measures of fitness and sex. Models were built in the primary study and tested in the validation study. Model performance is reported as the coefficient of determination (R2) and mean absolute error, with measures of calibration used for model evaluation and for sport-specific model re-calibration. Very-large to near-perfect within-subject correlations (r = 0.76-0.96) were evident between all training load metrics and both CHO utilization and EE. In the primary study, all models explained a large amount of variance (R2 = 0.77-0.96) and displayed good accuracy (mean absolute error; CHO = 16-21g [10-14%], EE = 53-82kcal [7-11%]). In the validation study, the mean absolute error ranged from 16-50g [15-45%] for CHO models to 53-182kcal [9-31%] for EE models. The calibrated mean absolute error ranged from 9-20g [8-18%] for CHO models to 36-72kcal [6-12%] for EE models. At the individual level, there are strong linear relationships between all measures of training load and both CHO utilization and EE during cycling. When combined with other measures of fitness, EE and CHO utilization during cycling can be estimated accurately. These models can be applied in running and kayaking when used with a calibration adjustment.

Recovery patterns of low-frequency fatigue in elite youth soccer players after official match

This study aimed to analyze the associations between recovery of low-frequency fatigue, jump height and perceptual responses following official soccer matches. Forty-two male youth elite soccer players (age: 17.13±0.70 years; height: 179.17±5.94 cm; weight: 69.74±4.91 kg) participated in this study. Low-frequency fatigue, countermovement jump, perceived fatigue, muscle soreness and perceived recovery were assessed at -2h, +30 min, +24h and +48h relative to the match. Linear mixed models analysis showed that low-frequency fatigue was reduced at the match-end (ES=-0.679 [95% CI = -1.01; -0.34]; p<.001) but returned to baseline after 24h (ES=0.149 [95% CI = -0.26; 0.56]; p=1.00). Perceptual responses were impaired for up to 48 hours following the match (ES=-0.868–1.174; p<.001). Countermovement jump did not differ between any time point (ES=-0.204–0.216; p>0.05). Additionally, the within-subject correlation analysis showed that low-frequency fatigue pre- to post-match changes presented moderate to large associations with perceived fatigue (rm[57]=-0.43; p<.001), muscle soreness (rm[57]=-0.52; p<.001) and perceived recovery (rm[57]=0.38; p=.003). The assessment of low-frequency fatigue could serve as an additional objective measurement for monitoring post-match fatigue, as findings suggest that young elite soccer players experience transient reductions following match-play, which are strongly correlated with subjective markers of recovery.

Leveraging real-world data to conduct externally controlled trial for rare diseases with count-type endpoints: utilizing multiple entries – a simulation study

ABSTRACT Conducting randomized controlled trials for medications targeting rare diseases presents significant challenges, due to the scarcity of participants and ethical considerations. Under such circumstances, leveraging real-world data (RWD) to generate supporting evidence may be accepted by the regulatory agency. Constructing an external control arm (ECA) from RWD for a single-arm trial has been conducted occasionally. A complication in this design is that patients from RWD may be eligible at multiple time points. Most studies approach this by selecting one time point as the index date for ECA patients. Here, we propose a novel design for externally controlled trials that permits the inclusion of ECA patients at various entry points. Accompanying this design, we make recommendations for statistical methods to account for measured confounders, limited sample size, within-subject correlation, and potential overdispersion inherent in count data. Furthermore, we present an idea for the blinding process for this type of study. We have conducted a series of simulations to assess the performance of the design and statistical methods in terms of bias, type I error, and efficiency, as compared to the approach of selecting only one entry per ECA patient. The study and parameter setup were based on a hypothetical case inspired by a rare disease study. The results indicate that allowing multiple entries for ECA patients can lead to enhanced performance in many aspects. It provides a controlled type I error, robustness against certain model misspecifications, and a moderate power improvement compared with selecting a single entry per ECA patient.

Mediterranean Diet, ultra-processed food consumption and semen quality in healthy young men

Abstract Background Diet quality can have beneficial effects on male reproductive health, although studies are still limited, and little is known on the potential impact of ultra-processed foods (UPFs) on semen quality parameters. Methods A cross-sectional analysis was run on 126 participants (mean age 20.0 ± 1.2 y) from the FAST randomized controlled trial in 2018-2019. Food intake was assessed through a FFQ. UPF was defined following the Nova classification and calculated as the ratio (weight ratio) between UPF (g/d) and total food (g/d). Adherence to the Mediterranean Diet (MD) was ascertained by the Mediterranean Diet Score (MDS). The semen analyses were performed using a microscope for optical evaluation with a Makler counting chamber and two automated semen analysers. The primary outcomes were sperm volume, concentration, motility and morphology. A hierarchical mixed model approach was utilized to accommodate the within-subject correlation arising from the triple temporal repetition of measurements. Results Highest UPF consumption (Q4), compared to lowest (Q1), was associated with lower sperm concentration (β=-54.1×106 spz./ml; 95%CI: -92.9 to -15.4; p-trend=0.002 across quarters), and progressive motility (β=-14.2%; 95%CI: -28.2 to -0.09; p-trend=0.036). The percentage of cells with normal morphology tended to be reduced in young men consuming more UPF compared to lowest intake (β=-2.93%; 95%CI: -6.22 to 0.37; p-trend=0.071). The MDS was not associated with any of the parameters under study. Conclusions A larger dietary share of UPF was inversely associated with sperm concentration and progressive motility in young men of reproductive age. MD adherence was not associated with semen quality parameters, and this is possibly due to the low variability of MD adherence in this sample. Dietary recommendations for improving sperm health should prioritize limiting UPF in the diet. Key messages • Ultra-processed food (UPF) intake was unfavourably associated with semen quality parameters amongst young men. • Dietary recommendations for improving sperm health should recommend limiting UPF.

Integrated Online-to-Offline Model of Care for HIV Prevention and Treatment Among Men Who Have Sex With Men in Malaysia: Protocol for an Intervention Development and a Multiphase Trial.

HIV continues to have a disproportionate impact on specific populations in Malaysia, particularly men who have sex with men (MSM). HIV self-testing (HIVST) is a strategy that has been shown to scale up HIV testing rates. However, it faces shortcomings because of concerns about self-efficacy, result interpretation, and lack of counseling and linkage to care. This underscores the need for an innovative approach that integrates HIVST with timely counseling, expert guidance, and referrals to enhance engagement in relevant HIV prevention or treatment. This study aims to describe the protocol used in developing and testing a web-based platform (ie, CINTAI) providing an HIVST kit and real-time e-counseling to support online-to-offline linkage to HIV care services for MSM in Malaysia. The methods are reported according to the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013 guidelines. In phase I, we will adapt existing HIVST web-based platforms to create a new online-to-offline HIVST and counseling platform called "CINTAI" for Malaysian MSM. In phase II, we will use a type 1 hybrid implementation trial design to determine the feasibility, acceptability, and preliminary efficacy of "CINTAI" compared with treatment as usual among Malaysian MSM, with assessments conducted over 6 months. Multilevel implementation factors will also be collected to guide future adoption and scale-up. We will enroll 78 MSM in the pilot randomized controlled trial. Baseline characteristics will be tested for homogeneity between groups using appropriate statistical tests. A generalized linear mixed model with random subject effects will account for within-subject correlation. Treatment assignment, time, interaction, and confounders will be included. The proportion of MSM tested for HIV over 6 months and other outcomes (pre-exposure prophylaxis for HIV or antiretroviral therapy linkage, HIV risk behaviors, and chemsex harm reduction) will be compared using linear contrasts. We completed phase I of the proposed study in April 2024 and started phase II in May 2024, with 15 participants recruited (7 in the CINTAI and 8 in the treatment-as-usual groups). On the basis of a series of formative works completed during phase I, we developed a fully functional, web-based platform that provides a digital platform for MSM in Malaysia to order HIVST kits for free and to receive HIV counseling, followed by offline linkage to HIV prevention services (if HIV negative) or HIV treatment services (if HIV positive). Despite being at high risk for HIV transmission, MSM in Malaysia have alarmingly low testing and linkage to HIV care services, prompting the need for innovative approaches to support HIV prevention efforts. If found to be feasible and acceptable, CINTAI can be easily adapted for a range of health outcomes and health care delivery services for MSM, including adaptation to other low- and middle-income countries. DERR1-10.2196/60962.

How well does a single blood sample represent long-term exposure for epidemiological studies of PFOA among men in the general population?

Many epidemiological studies use a single blood sample per participant to assess exposure, but it is unclear how well a single sample represents longer term exposure. We performed a simulation study using summary statistics for repeated serum PFOA measurements from several previous studies in men to generate plausible serum concentrations over time, taking within-subject correlations into account. Simulated serum concentrations for controls were categorized into quintiles at each time point, and used to determine the extent of misclassification at each time point compared to the “true” long-term average exposure. We then generated case counts by quintile needed to produce an odds ratio (OR) of 1.5 for the highest vs. lowest quintile categorized based on long term exposure, and used the same misclassification rates observed in the controls to simulate misclassified exposure quintiles for cases. Comparing long term vs. single baseline exposure measures for repeated serum samples collected within about 5–13 years of each other revealed similar effect estimates, although there was a small bias to the null. Trend tests across quintiles were mostly significant using either baseline or long-term exposure. For the general population sample of men in Norway, with 5 repeated measurements over 28 years, serum PFOA was substantially lower prior to 1987, and using either of the two earliest samples as the exposure metric, compared to the long term average, produced larger bias to the null and non-significant trend tests; however using later time points as the exposure metric resulted in only a small bias. Using data based on studies of men, single baseline serum samples represented rather well the mean of repeated samples collectedup to 13 years apart, but were not always reliable surrogates for average exposure over 3 decades, during which time PFOA exposure levels in the general population have changed substantially.

Spatial correlation between in vivo imaging and immunohistochemical biomarkers: A methodological study

In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: Ktrans (transfer constant), Ve (extravascular and extracellular space), and Vi (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm[3] voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (rrm). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: Ve and Ki-67 (rrm = -0.17, P < .001), Ve and HIF-1α (rrm = -0.12, P < .001), Ktrans and CD45 (rrm = 0.13, P < .001), Vi and CD45 (rrm = 0.16, P < .001), and Vi and Ki-67 (rrm = 0.08, P = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (rrm = 0.35, P < .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.

Machine Learning for Extraction of Image Features Associated with Progression of Geographic Atrophy

Background: Several studies have investigated various features and models in order to understand the growth and progression of the ocular disease geographic atrophy (GA). Commonly assessed features include age, sex, smoking, alcohol consumption, sedentary lifestyle, hypertension, and diabetes. There have been inconsistencies regarding which features correlate with GA progression. Chief amongst these inconsistencies is whether the investigated features are readily available for analysis across various ophthalmic institutions. Methods:In this study, we focused our attention on the association of fundus autofluorescence (FAF) imaging features and GA progression. Our method included feature extraction using radiomic processes and feature ranking by machine learning incorporating the algorithm XGBoost to determine the best-ranked features. This led to the development of an image-based linear mixed-effects model, which was designed to account for slope change based on within-subject variability and inter-eye correlation. Metrics used to assess the linear mixed-effects model included marginal and conditional R2, Pearson’s correlation coefficient (r), root mean square error (RMSE), mean error (ME), mean absolute error (MAE), mean absolute deviation (MAD), the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and loglikelihood. Results: We developed a linear mixed-effects model with 15 image-based features. The model results were as follows: R2 = 0.96, r = 0.981, RMSE = 1.32, ME = −7.3 × 10−15, MAE = 0.94, MAD = 0.999, AIC = 2084.93, BIC = 2169.97, and log likelihood = −1022.46. Conclusions: The advantage of our method is that it relies on the inherent properties of the image itself, rather than the availability of clinical or demographic data. Thus, the image features discovered in this study are universally and readily available across the board.

Awareness and Calibration: The Role of Descriptive Norms and Social Desirability in Accurate IAT Score Predictions of Food Items vs. Social Groups.

Extending research that people are able to predict the patterns of their social group biases on Implicit Association Tests (IATs), we let participants predict and complete IATs toward five different food item pairs and compared the results with the social-groups domain. Participants predicted the patterns of their IAT scores with similar accuracy in both domains, suggesting similar internal awareness (evidenced by comparable within-subjects correlations), even though food evaluations followed less descriptively-normative patterns. At the same time, participants were better-calibrated in communicating their evaluations in the domain of food than social groups (evidenced by higher between-subjects correlations). This discrepancy may partly stem from participants' tendency to refrain from using harsh labels when predicting social group biases, despite their demonstrated awareness of them: IAT scores predicted as "moderate" or "strong" for food preferences tended to be labeled "mild" for social groups. Discussion centers on the importance of distinguishing between awareness and calibration.

The relationship between parameters measured using intravoxel incoherent motion and dynamic contrast-enhanced MRI in patients with breast cancer undergoing neoadjuvant chemotherapy: a longitudinal cohort study.

The primary aim of this study was to explore whether intravoxel incoherent motion (IVIM) can offer a contrast-agent-free alternative to dynamic contrast-enhanced (DCE)-MRI for measuring breast tumor perfusion. The secondary aim was to investigate the relationship between tissue diffusion measures from DWI and DCE-MRI measures of the tissue interstitial and extracellular volume fractions. A total of 108 paired DWI and DCE-MRI scans were acquired at 1.5 T from 40 patients with primary breast cancer (median age: 44.5 years) before and during neoadjuvant chemotherapy (NACT). DWI parameters included apparent diffusion coefficient (ADC), tissue diffusion (Dt), pseudo-diffusion coefficient (Dp), perfused fraction (f), and the product f×Dp (microvascular blood flow). DCE-MRI parameters included blood flow (Fb), blood volume fraction (vb), interstitial volume fraction (ve) and extracellular volume fraction (vd). All were extracted from three tumor regions of interest (whole-tumor, ADC cold-spot, and DCE-MRI hot-spot) at three MRI visits: pre-treatment, after one, and three cycles of NACT. Spearman's rank correlation was used for assessing between-subject correlations (r), while repeated measures correlation was employed to assess within-subject correlations (rrm) across visits between DWI and DCE-MRI parameters in each region. No statistically significant between-subject or within-subject correlation was found between the perfusion parameters estimated by IVIM and DCE-MRI (f versus vb and f×Dp versus Fb; P=0.07-0.81). Significant moderate positive between-subject and within-subject correlations were observed between ADC and ve (r=0.461, rrm=0.597) and between Dt and ve (r=0.405, rrm=0.514) as well as moderate positive within-subject correlations between ADC and vd and between Dt and vd (rrm=0.619 and 0.564, respectively) in the whole-tumor region. No correlations were observed between the perfusion parameters estimated by IVIM and DCE-MRI. This may be attributed to imprecise estimates of fxDp and vb, or an underlying difference in what IVIM and DCE-MRI measure. Care should be taken when interpreting the IVIM parameters (f and f×Dp) as surrogates for those measured using DCE-MRI. However, the moderate positive correlations found between ADC and Dt and the DCE-MRI parameters ve and vd confirms the expectation that as the interstitial and extracellular volume fractions increase, water diffusion increases.

Establishing the relationship between subjective perception and neural responses: Insights from correlation analysis and representational similarity analysis

Exploring the relationship between sensory perception and brain responses holds important theoretical and clinical implications. However, commonly used methodologies like correlation analysis performed either intra- or inter- individually often yield inconsistent results across studies, limiting their generalizability. Representational similarity analysis (RSA), a method that assesses the perception-response relationship by calculating the correlation between behavioral and neural patterns, may offer a fresh perspective to reveal novel findings. Here, we delivered a series of graded sensory stimuli of four modalities (i.e., nociceptive somatosensory, non-nociceptive somatosensory, visual, and auditory) to/near the left or right hand of 107 healthy subjects and collected their single-trial perceptual ratings and electroencephalographic (EEG) responses. We examined the relationship between sensory perception and brain responses using within- and between-subject correlation analysis and RSA, and assessed their stability across different numbers of subjects and trials. We found that within-subject and between-subject correlations yielded distinct results: within-subject correlation revealed strong and reliable correlations between perceptual ratings and most brain responses, while between-subject correlation showed weak correlations that were vulnerable to the change of subject number. In addition to verifying the correlation results, RSA revealed some novel findings, i.e., correlations between behavioral and neural patterns were observed in some additional neural responses, such as “γ-ERS” in the visual modality. RSA results were sensitive to the trial number, but not to the subject number, suggesting that consistent results could be obtained for studies with relatively small sample sizes. In conclusion, our study provides a novel perspective on establishing the relationship between behavior and brain activity, emphasizing that RSA holds promise as a method for exploring this pattern relationship in future research.

Decorrelated empirical likelihood for generalized linear models with high-dimensional longitudinal data

This paper focuses on decorrelated empirical likelihood-based inference for longitudinal data with ultrahigh-dimensional covariates. The primary issues we aim to address involve parameter estimation and hypothesis testing for a low-dimensional parameter of interest. Under the framework of the generalized linear model, we initially consider the within-subject correlation by linearizing the precision matrix with certain known matrices, which retains optimality even if the working correlated structure is misspecified. Coupled with the decorrelated matrix, we then eliminate the influence of nuisance parameters on the estimation procedure. The proposed approach not only yields more efficient estimators compared to generalized decorrelated estimating equations but also shares the same asymptotic variance as quadratic decorrelated inference function based methods. Furthermore, we define the decorrelated empirical log-likelihood ratio test statistic to assess the significance of regression coefficients. Finally, to evaluate the performance of the proposed procedure, we conduct simulation studies and apply it to a real data example.

Time trajectories and within-subject correlations of matrix metalloproteinases 3, 8, 9, 10, 12, and 13 serum levels and their ability to predict mortality in polytraumatized patients: a pilot study

BackgroundManaging polytrauma victims poses a significant challenge to clinicians since applying the same therapy to patients with similar injury patterns may result in different outcomes. Using serum biomarkers hopefully allows for treating each multiple injured in the best possible individual way. Since matrix metalloproteinases (MMPs) play pivotal roles in various physiological processes, they might be a reliable tool in polytrauma care.MethodsWe evaluated 24 blunt polytrauma survivors and 12 fatalities (mean age, 44.2 years, mean ISS, 45) who were directly admitted to our Level I trauma center and stayed at the intensive care unit for at least one night. We determined their MMP3, MMP8, MMP9, MMP10, MMP12, and MMP13 serum levels at admission (day 0) and on days 1, 3, 5, 7, and 10.ResultsMedian MMP8, MMP9, and MMP12 levels immediately rose after the polytrauma occurred; however, they significantly decreased from admission to day 1 and significantly increased from day 1 to day 10, showing similar time trajectories and (very) strong correlations between each two of the three enzyme levels assessed at the same measurement point. For a two-day lag, autocorrelations were significant for MMP8 (− 0.512) and MMP9 (− 0.302) and for cross-correlations between MMP8 and MMP9 (− 0.439), MMP8 and MMP12 (− 0.416), and MMP9 and MMP12 (− 0.307). Moreover, median MMP3, MMP10, and MMP13 levels significantly increased from admission to day 3 and significantly decreased from day 3 to day 10, showing similar time trajectories and an (almost) strong association between every 2 levels until day 7. Significant cross-correlations were detected between MMP3 and MMP10 (0.414) and MMP13 and MMP10 (0.362). Finally, the MMP10 day 0 level was identified as a predictor for in-hospital mortality. Any increase of the MMP10 level by 200 pg/mL decreased the odds of dying by 28.5%.ConclusionsThe time trajectories of the highly varying individual MMP levels elucidate the involvement of these enzymes in the endogenous defense response following polytrauma. Similar time courses of MMP levels might indicate similar injury causes, whereas lead–lag effects reveal causative relations between several enzyme pairs. Finally, MMP10 abundantly released into circulation after polytrauma might have a protective effect against dying.

Unpredictable threat increases early event-related potential amplitudes and cardiac acceleration: A brain-heart coupling study.

In the face of unpredictable threat, rapid processing of external events and behavioral mobilization through early psychophysiological responses are crucial for survival. While unpredictable threat generally enhances early processing, it would seem adaptive to particularly increase sensitivity for unexpected events as they may signal danger. To examine this possibility, n = 77 participants performed an auditory oddball paradigm and received unpredictable shocks in threat but not in safe contexts while a stream of frequent (standard) and infrequent (deviant) tones was presented. We assessed event-related potentials (ERP), heart period (HP), and time-lagged within-subject correlations of single-trial EEG and HP (cardio-EEG covariance tracing, CECT) time-locked to the tones. N1 and P2 ERP amplitudes were generally enhanced under threat. The P3 amplitude was enhanced to deviants versus standards and this effect was reduced in the threat condition. Regarding HP, both threat versus safe and unexpected versus expected tones led to stronger cardiac acceleration, suggesting separate effects of threat and stimulus expectancy on HP. Finally, CECTs revealed two correlation clusters, indicating that single-trial EEG magnitudes in the N1/P2 and P3 time-windows predicted subsequent cardiac acceleration. The current results show that an unpredictable threat context enhances N1 and P2 amplitudes and cardiac acceleration to benign auditory stimuli. They further suggest separable cortical correlates of different effects on cardiac activity: an early N1/P2 correlate associated with threat-effects on HP and a later P3 correlate associated with expectedness-effects. Finally, the results indicate that unpredictable threat attenuates rather than enhances the processing of unexpected benign events during the P3 latency.

Bayesian estimation in generalized linear models for longitudinal data with hyperspherical coordinates

Under the framework of generalized linear models (GLM), the generalized estimating equation (GEE) method is typically applied for longitudinal data analysis. However, there are a series of problems due to the misspecification of the within-subject correlation structure, especially in Bayesian estimation. To handle these difficulties, in this paper, we construct a class of generalized estimating equations for longitudinal data with hyperspherical coordinates (HPC) and propose a Bayesian approach established through empirical likelihood (EL). Additionally, an efficient Markov chain Monte Carlo (MCMC) procedure is developed for the required computation of the posterior distribution. As proved by the simulation studies and an application to a real longitudinal data set, our method not only performs better than traditional empirical likelihood estimation and Bayesian estimation with partial autocorrelations (PAC) but also is suitable for non-Gaussian data.

Coupling Between Human Brain Cortical Thickness and Glucose Metabolism from Regional to Connective Level: A Positron Emission Tomography/Magnetic Resonance Imaging Study.

Background: Balance between brain structure and function is implicated in aging and many brain disorders. This study aimed to investigate the coupling between brain structure and function using 18F-fludeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI). Methods: One hundred thirty-eight subjects who underwent brain 18F-FDG PET/MRI were recruited. The structural and functional coupling at the regional level was explored by calculating within-subject Spearman's correlation between glucose metabolism (GluM) and cortical thickness (CTh) across the cortex for each subject, which was then correlated with age to explore its physiological effects. Then, subjects were divided into groups of middle-aged and young adults and older adults (OAs); structural connectivity (SC) based on CTh and functional connectivity (FC) based on GluM were constructed for the two groups, respectively, followed by exploring the connective-level structural and functional coupling on SC and FC matrices. The global and local efficiency values of the brain SC and FC were also evaluated. Results: Of the subjects, 97.83% exhibited a significant negative correlation between regional CTh and GluM (r = -0.24 to -0.71, p < 0.05, FDR correction), and this CTh-GluM correlation was negatively correlated with age (R = -0.35, p < 0.001). For connectivity matrices, many regions showed positive correlation between SC and FC, especially in the OA group. Besides, FC exhibited denser connections than SC, resulting in both higher global and local efficiency, but lower global efficiency when the network size was corrected. Conclusions: This study found couplings between CTh and GluM at both regional and connective levels, which reflected the aging progress, and might provide new insight into brain disorders. Impact statement The intricate interplay between brain structures and functions plays a pivotal role in unraveling the complexities inherent in the aging process and the pathogenesis of neurological disorders. This study revealed that 97.83% subjects showed negative correlation between the brain's regional cortical thickness and glucose metabolism, while at the connective level, many regions showed positive correlations between structural and functional connectivity. The observed coupling at the regional and connective levels reflected physiological progress, such as aging, and provides insights into the brain mechanisms and potential implications for the diagnosis and treatment of brain disorders.

Neonatal Abstinence Signs during Treatment: Trajectory, Resurgence and Heterogeneity.

Neonatal abstinence syndrome (NAS) presents with a varying severity of withdrawal signs and length of treatment (LOT). We examined the course and relevance of each of the NAS withdrawal signs during treatment in a sample of 182 infants with any prenatal opioid exposure, gestational age ≥ 35 weeks, without other medical conditions, and meeting the criteria for pharmacological treatment. Infants were monitored using the Finnegan Neonatal Abstinence Scoring Tool. Daily mean Finnegan scores were estimated using linear mixed models with random subject effects to account for repeated withdrawal scores from the same subject. Daily item prevalence was estimated using generalized estimating equations with a within-subject exchangeable correlation structure. The median LOT was 12.86 days. The prevalence of withdrawal signs decreased from day one to day three of treatment. However, certain central nervous system (CNS) and gastrointestinal (GI) signs showed sporadic increases in prevalence notable around two weeks of treatment, accounting for increases in Finnegan scores that guided pharmacotherapy. We question whether the resurgence of signs with a prolonged LOT is mainly a consequence of opioid tolerance or withdrawal. Monitoring CNS and GI signs throughout treatment is crucial. Future studies directed to better understand this clinical phenomenon may lead to the refining of NAS pharmacotherapy and perhaps the discovery of treatment alternatives.

Preliminary reliability of the FACT-RNT in standard-of-care Lu-PSMA therapy of metastatic castration-resistant prostate cancer.

99 Background: The Functional Assessment of Cancer Therapy-Radionuclide Therapy (FACT-RNT) was recently developed as the first patient-reported outcome (PRO) measure designed to monitor RNT-relevant symptoms and toxicities for patients with advanced metastatic castrate-resistant prostate cancer (mCRPC). This study aimed to examine preliminary reliability of the FACT-RNT in patients receiving RNT as part of standard of care. Methods: Patients scheduled to start 177Lu-PSMA-617 for advanced mCRPC December 2022 – August 2023 who were fluent in English or Spanish completed the FACT-RNT on day 1 of each RNT cycle administered at UCLA. The FACT-RNT is a 15-item measure assessing symptoms and toxicities on a 0-4 scale; total scores range from 0-60, with higher scores indicating better quality of life. Reliability was assessed in R using data from cycles 1-4 with Cronbach’s alpha test of internal consistency, Guttman’s Lamba 6 test of split-half reliability, inter-item correlations, and test-retest reliability. Results: Patients (N=43) were, on average, 69 years old (SD = 9, range = 51-91) at RNT cycle 1, were mostly non-Hispanic (79%) and White (58%) with Gleason score ≥ 7 (67%) at diagnosis. Patients had undergone surgery (35%), chemotherapy (98%), radiation (65%), hormone therapy (100%), and/or immunotherapy (28%). Some patients who recently began therapy were not yet due for follow-up cycles, and 9 (21%) died during the study period. Completion of the FACT-RNT ranged from n=43 (Cycle 1) to n=19 (Cycle 4). The FACT-RNT total score ranged from 18-60 across cycles. Internal consistency reliability ranged from 0.82 (good) to 0.91 (excellent), and split-half reliability ranged from 0.92 to 0.99 (excellent). Average inter-item correlations were acceptable for scaling purposes (all exceeding 0.20). Within-subject correlations between scores were r=0.75 for cycles 2 vs. 3 and r=0.94 for cycles 3 vs. 4, indicating good measurement stability across cycles. Conclusions: In preliminary analyses, the FACT-RNT demonstrates good to excellent internal consistency across the first four cycles, moderate to strong consistency of measuring a common underlying construct, and good measurement stability. Findings support reliability of the FACT-RNT and its use in future research.

Relugolix versus leuprolide in combination with radiotherapy for localized prostate cancer (REVELUTION trial): An initial analysis of patient treatment preferences and quality of life.

301 Background: Relugolix, an oral gonadotropin releasing hormone (GnRH) antagonist, has superior testosterone suppression and may lower cardiovascular (CV) toxicity compared with more commonly used injectable GnRH agonists, such as leuprolide. The Relugolix Versus Leuprolide Trial (REVELUTION, NCT 05320406) is an ongoing, investigator-initiated, randomized trial comparing radiotherapy (XRT) plus relugolix versus XRT plus leuprolide for men with localized prostate cancer (PCa). Primary endpoint is change in coronary plaque on cardiac computed tomography from baseline to 12 months following treatment. Secondary endpoints include patient-reported outcomes (PRO). Herein, we report patient-specific treatment preferences prior to randomization and acute treatment-associated toxicity. Methods: Men with non-metastatic intact or biochemically recurrent PCa pursuing pelvic XRT (1.8-2.5 Gy per fraction) with ≥ 6 months of androgen deprivation therapy (ADT) were enrolled and randomized 1:1 to leuprolide (IM/SC 45 mg q6mo) or relugolix (PO 360 mg day 1, 120 mg daily thereafter). Prior to randomization, each patient completed an ADT preference questionnaire after reviewing an education brochure describing both drugs’ administration, testosterone kinetics, and common toxicities. PROs were assessed by International Prostate Symptom Score (IPSS) and Expanded Prostate Index Composite (EPIC-CP) at baseline and 3-/6-months after XRT initiation, with higher scores indicating more severe toxicity. Scores were compared using linear mixed-effects models accounting for within-subject correlations. Results: Between 06/2022 and 07/2023, 65 men were randomized (34 leuprolide, 31 relugolix). Median follow-up was 5 months (IQR 4-8). Prior to randomization, 61 (94%) preferred relugolix over leuprolide, due to faster testosterone recovery (n=36, 59%), lower CV risk (n=23, 38%), or oral administration (n=2, 3%); the four patients who preferred leuprolide all had compliance concerns with a daily oral pill. Compared with XRT+leuprolide, XRT+relugolix was associated with less impact on IPSS urinary score (mean difference [MD] -3.68, p=0.04). There was no difference in EPIC-CP incontinence (MD +0.07, p=0.91), bowel (MD +0.39, p=0.44), sexual (MD -0.74, p=0.43), or vitality (MD +0.17, p=0.80). Conclusions: In this trial of men with localized PCa treated with XRT plus ADT, most preferred relugolix over leuprolide. Relugolix, compared with leuprolide, mitigated acute urinary toxicity from XRT, perhaps due to superior castration resulting in greater prostate gland downsizing and less obstructive uropathy. Longer-term follow up is ongoing, and primary CV toxicity endpoint is expected to be complete in 2024. Clinical trial information: NCT05320406 .

Estimation and inference for multi-kink expectile regression with nonignorable dropout

In this paper, we consider parameter estimation, kink points testing and statistical inference for a longitudinal multi-kink expectile regression model with nonignorable dropout. In order to accommodate both within-subject correlations and nonignorable dropout, the bias-corrected generalized estimating equations are constructed by combining the inverse probability weighting and quadratic inference function approaches. The estimators for the kink locations and regression coefficients are obtained by using the generalized method of moments. A selection procedure based on a modified BIC is applied to estimate the number of kink points. We theoretically demonstrate the number selection consistency of kink points and the asymptotic normality of all estimators. A weighted cumulative sum type statistic is proposed to test the existence of kink effects at a given expectile, and its limiting distributions are derived under both the null and the local alternative hypotheses. Simulation studies show that the proposed estimators and test have desirable finite sample performance in both homoscedastic and heteroscedastic errors. An application to the Nation Growth, Lung and Health Study dataset is also presented.