Ratio Estimates Research Articles

Sequential track fusion in multi-sensor networks of unscented Kalman filters: A case of slip estimation in planetary mobile robots

Accurate wheel slip estimation facilitates Wheeled Mobile Robots (WMRs) with improved localization and traversability monitoring which are crucial to their autonomy in challenging planetary environments. Although distributed track-level fusion offers better computational efficiency, often sensor-level fusion is adopted in slip estimators of planetary rovers. Extending upon our earlier work, we develop a novel explicit track-to-track fusion algorithm for multi-sensor networks of unscented Kalman filters that has immediate application to slip ratio estimation in WMRs. The algorithm demonstrates better consistency compared to the existing fusion techniques since it implements a sub-optimal fusion rule to sequentially combine local tracks. It also saves computational power due to the recursive propagation of cross-covariance matrices based on the statistical linearization technique, instead of performing online optimizations. We prove that this recursion only requires the information of the first and last tracks in a sequence if all local tracks are unbiased. We rigorously study various key properties of the developed fusion algorithm and show its superior level of confidence when compared to the two prominent fusion methods of sequential and batch covariance intersection. The slip ratio estimation in a six-wheel WMR is considered as a case study, where the steerable wheel sets act as a network of sensors. The proposed slip estimator works based on the rigid body kinematics and readings of purely proprioceptive sensors, i.e., an inertial measurement unit and encoders. The slip estimator’s performance is evaluated in a high-fidelity software-in-the-loop simulation environment connecting MATLAB and CM Lab’s Vortex Studio software. In a comparison study that considers four rival strategies, we show the superiority of the proposed fusion method offering a balance between consistency, accuracy, and speed in real-time slip estimations.

Direct Amortized Likelihood Ratio Estimation

We introduce a new amortized likelihood ratio estimator for likelihood-free simulation-based inference (SBI). Our estimator is simple to train and estimates the likelihood ratio using a single forward pass of the neural estimator. Our approach directly computes the likelihood ratio between two competing parameter sets which is different from the previous approach of comparing two neural network output values. We refer to our model as the direct neural ratio estimator (DNRE). As part of introducing the DNRE, we derive a corresponding Monte Carlo estimate of the posterior. We benchmark our new ratio estimator and compare to previous ratio estimators in the literature. We show that our new ratio estimator often outperforms these previous approaches. As a further contribution, we introduce a new derivative estimator for likelihood ratio estimators that enables us to compare likelihood-free Hamiltonian Monte Carlo (HMC) with random-walk Metropolis-Hastings (MH). We show that HMC is equally competitive, which has not been previously shown. Finally, we include a novel real-world application of SBI by using our neural ratio estimator to design a quadcopter. Code is available at https://github.com/SRI-CSL/dnre.

Abstract 4866: To weight or not to weight? Studying the effect of selection bias in three EHR-linked biobanks with applications to colorectal cancer

Abstract The use electronic health record (EHR)-linked biobanks, including All of Us (AOU), the Michigan Genomics Initiative (MGI), and the UK Biobank (UKB), has become increasingly common in cancer research. However, each has a different participant recruitment strategy resulting in non-probability samples, which can lead to selection bias. An unanswered question is whether researchers should use selections weights when analyzing these data. Using colorectal cancer as the test case, we investigate the impact of using such weights on descriptive and analytic tasks in these three biobanks. We curated sociodemographic and clinical diagnosis data for 726,841 individuals (n = 244,071, 81,243, and 401,167, in AOU, MGI, and UKB, respectively). EHR ICD (diagnosis) code data were mapped to broader 2,042 codes, called phecodes, using the new phecode X mapping table developed by researchers at Vanderbilt University. Selection weights were constructed in AOU and MGI to make them more representative of the US adult population, using data from the 2019 National Health Interview Survey; previously described weights for the UKB were used. We estimated phenomewide prevalences, pairwise correlations, and phenome dimensionality (via principal components analysis). To investigate the role of weighting on conclusions from hypothesis testing and association estimation, we conducted a colorectal cancer phenomewide association study and estimated the sex-colorectal cancer log-odds ratio, respectively. We found that phecode prevalences in AOU and MGI decreased following weighting (median prevalence ratio [MPR]: 0.82 and 0.61, respectively) while those in UKB increased (MPR: 1.06). MGI is enriched for phecodes compared to AOU (MPR: 1.15) and UKB (MPR: 6.28). Weighting PCA had minimal impact on phenome dimensionality (e.g., 732 PCs explaining 95% of cumulative variation in AOU vs. 711 after weighting). Weighted PheWAS for colorectal cancer identified 21 hits not identified in unweighted PheWAS, but only one was from a new disease category. Weighted estimates of the female-colorectal cancer log-odds ratio overlapped with the benchmark range in MGI and UKB though resulted in a null association in AOU. Weighting had limited impact on dimensionality estimation and hypothesis testing but were important to consider for prevalence and association estimation. Results from untargeted analyses should be followed up with targeted analyses using curated weights. The importance of weights depends on the estimates obtained and inference goals and can improve the representativeness of results for cancer-related outcomes based on EHR-linked biobank data. Importantly, EHR-linked biobanks should be explicit in reporting recruitment and selection mechanisms and when possible, supply selection weights to researchers for population-based inference along with a clear definition of the target population. Citation Format: Maxwell Salvatore, Ritoban Kundu, Xu Shi, Christopher R. Friese, Seunggeun Lee, Lars G. Fritsche, Alison M. Mondul, David Hanauer, Celeste L. Pearce, Bhramar Mukherjee. To weight or not to weight? Studying the effect of selection bias in three EHR-linked biobanks with applications to colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4866.

Abstract 2213: Vaping, smoking and lung cancer: A case-control study

Abstract Introduction: Nicotine exposure through the use of electronic delivery systems (vaping) has been found to elevate the risk of certain conditions of the lungs, e.g., vaping associated lung injury. However, the potential impact of vaping on lung cancer risk remains largely unexplored. We, therefore, examined the association of vaping and cigarette smoking with lung cancer risk in a case-control study conducted at The Ohio State University in Columbus, Ohio. Methods: Medical records examined from the James Cancer Hospital and Solove Research Institute revealed 4,975 cases with newly diagnosed, pathologically confirmed lung cancer during 2013-2021. These cases were compared to 27,294 controls without cancer that were group-matched on a 5:1 ratio to cases by age, gender, race and year of ascertainment. Descriptive statistics were calculated, and logistic regression analyses were performed to assess the associations between vaping, smoking and lung cancer. Results: The lung cancer cases in this study were 55% male, 88% white, with mean age at diagnosis of 62 years. The adjusted odds ratio (OR) for individuals who reported vaping and smoking was OR=21.1 (95% CI=17.1, 26.1) versus OR=6.3 (95% CI=5.8, 6.8) for smoking only. Estimates for gender and histologic cell type of lung cancer, e.g., pulmonary adenocarcinoma, squamous cell carcinoma and small cell carcinoma, were consistently over threefold higher for vaping and smoking compared to smoking only (p<0.001), and the vaping effect persisted even after adjustment for comorbidities, COPD and cardiovascular disease. Conclusion: Adjusted estimates of odds ratios (OR) revealed over threefold higher risk of lung cancer among individuals who had vaped and smoked compared to individuals who only smoked. Our results suggest that the addition of vaping to smoking greatly accelerates the risk of developing lung cancer. Future studies are needed to further confirm these results. Citation Format: Marisa A. Bittoni, David Carbone, Randall Harris. Vaping, smoking and lung cancer: A case-control study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2213.

Abstract 3407: Physical activity and post-menopausal breast cancer in the Multiethnic Cohort Study

Abstract Much research has been conducted on the relationship between physical activity and breast cancer, with meta-analyses showing 10 – 21% reduction in breast cancer risk for postmenopausal women with high compared to low level of physical activity. However, few studies have explored this relationship in non-Caucasian women. We analyzed data from 74,177 post-menopausal African American, Caucasian, Japanese American, Latina, and Native Hawaiian women in the Multiethnic Cohort in Hawaii and California. Data on physical activity (hours and metabolic equivalents (METs)) was based on a self-administered questionnaire at baseline (1993–1996). Multivariate Cox proportional hazards models provided estimates of hazard ratios (HRs) and 95% confidence intervals (CIs) adjusted for risk factors. We observed no associations between breast cancer risk and hours of moderate/vigorous activity per week (HR=1.01, 95% CI: 0.91-1.10, Ptrend=0.71), MET-hours of moderate/vigorous activity per week (HR=1.03, 95% CI: 0.94-1.13, Ptrend=0.92), and total METs-measured as average MET level per day multiplied by 7 (HR=0.94, 95% CI: 0.86-1.03, Ptrend=0.37) when comparing the highest quartile to the lowest. When examining the data across race/ethnicity, we observed a reduction in risk of breast cancer for total METs (HR=0.75, 95% CI: 0.61-0.94, Ptrend=0.05) among Latina women. Analysis across strata of BMI showed no differences across subgroups. In this study, we did not observe any consistent protective association between physical activity and breast cancer risk. Citation Format: Jasmeet K. Gill, Gertraud Maskarinec, Song-Yi Park, Lynne Wilkens, Loic Le Marchand. Physical activity and post-menopausal breast cancer in the Multiethnic Cohort Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3407.

Comparing major and mild cognitive impairment risks in older type-2 diabetic patients: a Danish register-based study on dipeptidyl peptidase-4 inhibitors vs. glucagon-like peptide-1 analogues

IntroductionThe prevalence of major and mild cognitive impairment (CI) in type-2 diabetes older patients is 15–25% and 30–60%, respectively, thus affecting quality of life and health outcomes. There is, therefore, the need of head-to-head studies aiming at identifying the optimal treatment for individuals with type-2 diabetes at increased risk of mild and major CI. This study focuses on the risk of developing mild and major CI in Danish patients treated with dipeptidyl peptidase-4 inhibitors (DPP-4i) and glucagon-like peptide-1 analogues (GLP-1a) using administrative and healthcare registers.MethodsAn active comparator design with a 3-year follow-up period was used. The main outcome was the hospital admission with a diagnosis of mild CI or major CI. Multivariate Cox Regression analysis was performed using the high-dimensional propensity score to obtain adjusted Hazard Ratio (HR) estimates. Inverse probability of treatment weighting (IPTW) and marginal structured model were used to calculate risk differences while accounting for the variations of confounders throughout the follow-up period.ResultsOur results show a significant higher risk of major CI between DPP-4i and GLP-1a in unadjusted [HR (95% CI) = 3.13 (2.45–4.00), p < 0.001] and adjusted analyses [HR (95% CI) = 1.58 (1.22–2.06), p = 0.001]. No statistically significant differences were observed for mild CI. IPTW resulted stable throughout the follow-up period. Marginal structure modeling (β (95% CI) = 0.022 (0.020–0.024), p < 0.001) resulted in a higher risk of major CI for DPP-4i when compared to GLP-1a.DiscussionDPP-4i was associated with an increased risk of developing major CI when compared to GLP-1a among older individuals with type-2 diabetes.

Assessing the one-month mortality impact of civilian-setting prehospital transfusion: A systematic review and meta-analysis.

Based on convincing evidence for outcomes improvement in the military setting, the past decade has seen evaluation of prehospital transfusion (PHT) in the civilian emergency medical services (EMS) setting. Evidence synthesis has been challenging, due to study design variation with respect to both exposure (type of blood product administered) and outcome (endpoint definitions and timing). The goal of the current meta-analysis was to execute an overarching assessment of all civilian-arena randomized controlled trial (RCT) evidence focusing on administration of blood products compared to control of no blood products. The review structure followed the Cochrane group's Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA). Using the Transfusion Evidence Library (transfusionevidencelibrary.com), the multidatabase (e.g. PubMed, EMBASE) Harvard On-Line Library Information System (HOLLIS), and GoogleScholar, we accessed many databases and gray literature sources. RCTs of PHT in the civilian setting with a comparison group receiving no blood products with 1-month mortality outcomes were identified. In assessing a single patient-centered endpoint-1-month mortality-we calculated an overall risk ratio (RR) estimate. Analysis of three RCTs yielded a model with acceptable heterogeneity (I2 = 48%, Q-test p = 0.13). Pooled estimate revealed civilian PHT results in a statistically nonsignificant (p = 0.38) relative mortality reduction of 13% (RR 0.87, 95% CI 0.63-1.19). Current evidence does not demonstrate 1-month mortality benefit of civilian-setting PHT. This should give pause to EMS systems considering adoption of civilian-setting PHT programs. Further studies should not only focus on which formulations of blood products might improve outcomes but also focus on which patients are most likely to benefit from any form of civilian-setting PHT.

Abstract 6293: Influence of prescription opioids and recreational cannabis use on efficacy outcomes and adverse events related to immune checkpoint inhibitors

Abstract Introduction: Opioids and cannabis possess immunomodulatory properties. However, the effect of opioid receptor activity on immune function is complicated, facilitated by several mechanisms and can lead to enhancement or inhibition. Similarly, the relation between cannabinoid ligands of diverse types and endocannabinoid receptors on various immune cells is complex. We hereby delineate the effect of prescription opioids and recreational cannabis use on immune-related adverse events (IRAEs) during immune checkpoint inhibitor (ICI) therapy in various cancers, as well as efficacy outcomes in advanced non-small cell lung cancer (aNSCLC). Methods: This is a retrospective cohort study of adult patients with advanced cancers who received ICI with or without chemotherapy for at least two months at an urban safety net hospital from January 2016 to June 2022. All patients, as well as a subset of patients with aNSCLC, were divided into two arms based on whether they were prescribed opioids during ICI therapy or not (OP vs. NO). Similarly, they were grouped based on whether they reported recreational cannabis use during ICI therapy (since initiation of therapy) or not (CA vs. NC). Incidence of IRAEs, median overall survival (mOS) and median progression-free survival (mPFS) calculated per RECIST 1.1 were the outcome variables. Multivariate logistic regression and alternative log-rank test were utilized for analysis with adjustments for demographics, insurance status, BMI, ECOG, PD-L1, TMB, smoking and concurrent chemotherapy. Results: 230 patients received ICI-based therapy; 47% were female, 34% were African American and 6.5% were Hispanic. There was no significant difference in the incidence of IRAEs between OP (n=144) and NO (n=86; p=0.225). However, CA (n=44) had higher IRAEs than NC (n=186) with an odds ratio estimate of 2.023 (X2=4.18, CI 1.03-3.97, p=0.04). Among 110 patients with aNSCLC, 46% were female. Patients with aNSCLC in the OP arm (n=69) had no significant difference in mOS (HR=1.34, CI 0.8-2.25, p=0.26) or mPFS (HR=1.21, CI 0.69-2.1, p=0.51) compared to patients in the NO arm (n=51). Similarly, the two arms CA (n=21) and NC (n=89) had no difference in mOS (HR:0.96, CI 0.5-1.83, p=0.89) or mPFS (HR:1.18, CI 0.61-2.29, p=0.63) for aNSCLC. Conclusion: Recreational cannabis use during ICI therapy increased the incidence of IRAEs. Prescription opioids and recreational cannabis use did not significantly affect survival outcomes for ICI in aNSCLC. Prescription opioid use also did not significantly influence the occurrence of IRAEs. This study suggests that recreational cannabis may need to be used with caution in this patient population due to its influence on IRAEs. On the other hand, opioids appear to be a safe option for pain management in these patients. Larger studies are warranted to shed more insight into the effect of these substances on ICI therapy. Citation Format: Himil Mahadevia, Benjamin Eidenschink, An-Lin Cheng, Atharva Desai, Stephanie Harry, Lara Kujtan. Influence of prescription opioids and recreational cannabis use on efficacy outcomes and adverse events related to immune checkpoint inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6293.

Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab: An Observational Health Data Sciences and Informatics Network Study

Objective or PurposeA) To characterize the incidence of kidney failure associated with intravitreal anti-vascular endothelial growth factor (VEGF) exposure, and B) compare the risk of kidney failure in patients treated with ranibizumab, aflibercept, or bevacizumab. DesignRetrospective cohort study across 12 databases in the Observational Health Data Sciences and Informatics (OHDSI) network. Subjects, Participants, and/or ControlsSubjects aged ≥18 years with ≥3 monthly intravitreal anti-VEGF medications for a blinding disease (diabetic retinopathy, diabetic macular edema, exudative age-related macular degeneration, or retinal vein occlusion). Methods, Intervention, or TestingA) The standardized incidence proportions and rates of kidney failure while on treatment with anti-VEGF were calculated. B) For each comparison (e.g., aflibercept versus ranibizumab), patients from each group were matched 1:1 using propensity scores. Cox proportional hazards models were used to estimate the risk of kidney failure while on treatment. A random-effects meta-analysis was performed to combine each database’s hazard ratio (HR) estimate into a single network-wide estimate. Main Outcome MeasuresIncidence of kidney failure while on anti-VEGF treatment, and time from cohort entry to kidney failure. ResultsOf the 6.1 million patients with blinding diseases, 37,189 who received ranibizumab, 39,447 aflibercept, and 163,611 bevacizumab were included; the total treatment exposure time was 161,724 person-years. The average standardized incidence proportion of kidney failure was 678 per 100,000 persons (range 0 to 2389), and incidence rate 743 per 100,000 person-years (0 to 2661). The meta-analysis HR of kidney failure comparing aflibercept to ranibizumab was 1.01 (95% confidence interval (CI) 0.70, 1.47, p=0.45), ranibizumab to bevacizumab 0.95 (95% CI 0.68, 1.32, p=0.62), and aflibercept to bevacizumab 0.95 (95% CI 0.65, 1.39, p=0.60). ConclusionsThere was no substantially different relative risk for kidney failure between those who received ranibizumab, bevacizumab, or aflibercept. Practicing ophthalmologists and nephrologists should be aware of the risk for kidney failure among patients receiving intravitreal anti-VEGF medications and that there is little empirical evidence to preferentially choose among the specific intravitreal anti-VEGF agents.

A unified expression for estimating Poisson’s ratio from a hinged–hinged beam with a use for abnormality detection

Cycle fatigue weakens a structure. Poisson’s ratio is a sensitive indicator of cycle fatigue. The amount of fatigue is proportional to the severity of an abnormality, such as a crack, delamination or other imperfection. Our prior work confirms that direct estimates of Poisson’s ratio by Cornu’s method must be identical for all antinodes of a mode shape of a homogeneous, thin, hinged–hinged beam. Therefore, if a direct estimate at any antinode was found to be significantly different from the other estimates at the other antinodes, then that would simultaneously indicate fatigue and identify the location of the abnormality. We use simulations of Besselograms and apply Cornu’s method to directly estimate Poisson’s ratio at all antinodes of a beam. We transform finite element simulations of the out-of-plane bending displacements of mode shapes by simulating time-average scanning digital holography. We show that amount of disagreement between the direct estimation Poisson’s ratio and the true value of Poisson’s ratio depends on the ratio of the distance between nodes of a mode shape divided by the width of the beam. We call this distance between the nodes of a mode shape the ‘Span’. We then define a unified expression for predicting the simulated direct estimate given the true value of Poisson’s ratio and the Span-to-Width ratio. Next, we invert the unified expression, which enables us to use the Span-to-Width ratio and simulated direct estimates of Poisson’s ratio as the independent variables to compute the adjusted value of Poisson’s ratio. We find that our inverse expression makes it possible to obtain an estimate of Poisson’s ratio that is within ±2% of the true value for thin hinged–hinged beams and plates that have a Span-to-Width ratio greater than 1. We also find that if the material is known to have a Poisson’s ratio greater than zero, which can be assessed by our previous statement, then we can extend our confidence to Span-to-Width ratios greater than 0.1. That was the lower limit of our testing. Finally, we show how to use direct estimates of Poisson’s ratio to statistically detect and localize an abnormality along a hinged–hinged plate or beam. We believe that our combination of Cornu’s method and time-averaging could eventually offer the ability to directly estimate Poisson’s ratio from hinged–hinged beams and plates as well as to unambiguously monitor cycle fatigue for changes in effective material properties, predict time-to-failure, and do so without contact.

Restricted time win ratio: from estimands to estimation

The win ratio is a novel approach to analyzing prioritized composite endpoints in clinical trials. The win ratio has grown increasingly popular and has been applied in many ongoing cardiovascular clinical trials. Despite the intuitive interpretation of win ratio statistics, the traditionally used win ratio estimands are heavily influenced by the pattern of censoring. Treating missing values or censored data as ties is generally not a reliable way of handling missing values even in the estimation procedure. To avoid this complication, we propose the restricted time win ratio, which is the win ratio at a pre-specified time point τ and can be written in terms of the expectations of potential outcomes. To estimate the proposed estimand, we develop an approximately fully conditional specification algorithm which imputes the missing data of longitudinal and clinical outcomes jointly up to τ . The imputation algorithm can be easily revised to adjust a different hierarchical structure of the sequential comparisons specified by the users. Simulation studies in realistic settings show that the proposed imputation algorithm provides an unbiased and robust estimation of the restricted time win ratio. Finally, real data from a cardiovascular clinical trial are used to illustrate the proposed method.

A metric-based adaptive mesh refinement criterion under constrain for solving elliptic problems on quad/octree grids

In this work we propose and investigate the performance of a metric-based refinement criteria for adaptive meshing used for improving the numerical solution of an elliptic problem. We show that in general, when solving elliptic equations such as the Poisson-Helmholtz equation, the minimization of the interpolation error often used as local refinement criteria does not always guarantee the minimization of the total numerical error. Numerical and theoretical arguments are given to unveil the critical role of the mesh compression – the size aspect ratio between the finest cell size and the mean cell size of an adapted mesh – to determine whether the estimated error is purely local meaning that the interpolation error is a good enough error model for the total error or if other, non-local, sources of error need to be accounted for. We show through particular examples that a slightly sub-optimal mesh in terms of interpolation error may significantly reduce the total error of a numerical solution, depending on the value of the compression ratio and not on the number of grid points. Based on this observation, we propose a new method to exclude the grids where non-local errors can control the accuracy of the solution. This is achieved by an automatic estimation of the optimal compression ratio, which is imposed as an additional constraint in the minimal element size during the mesh adaptation process. The method is tested on quadtree and octree grids, showing very satisfactory performances in reducing the total numerical error despite the additional constrain imposed.

The first measurements of carbon isotopic ratios in post-RGB stars: SZ Mon and DF Cyg

ABSTRACT Dusty post-red giant branch (post-RGB) stars are low- and intermediate-mass stars where the RGB evolution was prematurely terminated by a poorly understood binary interaction. These binary stars are considered to be low-luminosity analogues of post-asymptotic giant branch (post-AGB) binary stars. In this study, we investigated the chemical composition of two dusty post-RGB binary stars, SZ Mon and DF Cyg, using multiwavelength spectroscopic data from HERMES/Mercator (optical) and the APOGEE survey (near-infrared). Owing to challenges posed by existing spectral analysis tools for the study of evolved stars with complex atmospheres, we developed E-iSpec: a dedicated spectral analysis tool for evolved stars, to consistently determine atmospheric parameters, elemental abundances, and carbon isotopic ratios. Our abundance analysis revealed that observed depletion patterns and estimated depletion efficiencies resemble those found in post-AGB binary stars. However, the onset of chemical depletion in post-RGB targets occurs at higher condensation temperatures ($T_{\rm turn-off,~post-RGB}\approx 1\, 400$ K), than in most post-AGB stars ($T_{\rm turn-off,~post-AGB}\approx 1\, 100$ K). Additionally, our study resulted in the first estimates of carbon isotopic ratios for post-RGB stars (12C/13CSZ Mon = 8 ± 4, 12C/13CDF Cyg = 12 ± 3). We found that the observationally derived CNO abundances and the carbon isotopic ratios of our post-RGB binary targets are in good agreement with theoretical predictions from the ATON single star evolutionary models involving first dredge-up and moderately deep extra mixing. This agreement emphasizes that in post-RGB binary targets, the observed CNO abundances reflect the chemical composition expected from single star nucleosynthesis (i.e. convective and non-convective mixing processes) occurring during the RGB phase before it is terminated.

An Improvement in Regression Estimator Through Exponential Estimator Using Two Auxiliary Variables

For the case of simple random sampling, we are introducing a new regression estimator for the population mean with the supporting values of two auxiliary variables. The results for the mean square error (MSE) of the new form of regression estimator is fined. The mean square error’s results have also been checked through numerical illustration. It is observed that our introduced estimator is having less mean square error than the traditional ratio and regression estimator for two auxiliary variables.

Characteristics associated with rerevision of primary inlay and onlay reverse shoulder arthroplasty. Analysis from the Australian Orthopaedic Association National Joint Replacement Registry

BackgroundTwo designs of primary reverse total shoulder arthroplasty (rTSA), inlay reverse total shoulder arthroplasty (in-rTSA) and onlay reverse total shoulder arthroplasty (on-rTSA) that had undergone an aseptic revision were compared to determine differences in the rate of rerevision. MethodsIn this comparative observational national registry study between January 1, 2012, and December 31, 2021, all rTSA utilizing either a modular inlay or onlay metaphyseal humeral component that had been revised for aseptic reasons formed 2 cohort groups. The cumulative percentage rerevision (2nd CPR) was determined using Kaplan-Meier estimates of survivorship and hazard ratios (HRs) from Cox proportional hazard models adjusted for age and sex. A minor category revision involved exchange of parts not fixed to bone whilst major revisions did. The primary and revision diagnoses, surgeon primary volume experience, and revision category were compared. Shoulder Modular Replacement (SMR)/SMR L1 or L2 combination (Lima Corporate, San Daniele del Friuli, Italy) was excluded at subanalysis. ResultsThe 2nd CPR at 3 years was 20.4% (95% confidence interval 17.1, 24.1) for in-rTSA (n = 571) and 16.1%(11.6, 22.2) for on-rTSA (n = 249). The risk of rerevision was not different between the 2 cohort groups. Primary diagnosis fracture was associated with an increased risk of rerevision for on-rTSA (entire period on-rTSA HR = 3.16(1.50, 6.68), P = .002), and in-rTSA at subanalysis (entire period on-rTSA HR = 2.91(1.33, 6.33), P = .007). 59.9% of in-rTSA and 24.1% of on-rTSA aseptic revisions were minor. The revision diagnosis, the surgical experience of rTSA and if the revision was major or minor did not change the rate of rerevision. The most common reason for both in-rTSA (50%) and (43.2%) on-rTSA rerevision was instability/dislocation. DiscussionRerevision rates of in-rTSA and on-rTSA after aseptic revision are high. The primary rather the revision diagnosis changed rerevision rates in contemporary rTSA surgery. Minor revisions did not reduce rerevision rates for in-rTSA or on-rTSA compared to humeral/glenoid revision. Increased surgical experience of primary rTSA did not change the rate of rerevision of in-rTSA or on-rTSA.

Almost Unbiased Optimum Ratio-type Estimator for Estimating Population Mean in Stratified Sampling in Presence of Non-response

In this paper we have proposed classes of ratio-type estimators for finite population mean in presence of non-response in stratified sampling. The properties of the estimators have been discussed. We have also derived optimum choices of scalar constant to reduce the bias in the estimators which make suggested classes of estimators almost unbiased. The expressions of mean square error (MSE) have been derived up to the first order of approximation. We have compared our proposed classes of estimators with natural ratio estimators and with estimator under complete response. Results are also supported by empirical study.

Systematic review and pooled analysis of the impact of treatment-induced lymphopenia on survival of glioblastoma patients

Purpose/objective(s)Treatment related lymphopenia is a known toxicity for glioblastoma (GBM) patients and several single-institution studies have linked lymphopenia with poor survival outcomes. We performed a systematic review and pooled analysis to evaluate the association between lymphopenia and overall survival (OS) for GBM patients undergoing chemotherapy and radiation therapy (RT).Materials/methodsFollowing PRISMA guidelines, a systematic literature review of the MEDLINE database and abstracts from ASTRO, ASCO, and SNO annual meetings was conducted. A pooled analysis was performed using inverse variance-weighted random effects to generate a pooled estimate of the hazard ratio of association between lymphopenia and OS.ResultsTen of 104 identified studies met inclusion criteria, representing 1,718 patients. The lymphopenia cutoff value varied (400–1100 cells/uL) and as well as the timing of its onset. Studies were grouped as time-point (i.e., lymphopenia at approximately 2-months post-RT) or time-range (any lymphopenia occurrence from treatment-start to approximately 2-months post-RT. The mean overall pooled incidence of lymphopenia for all studies was 31.8%, and 11.8% vs. 39.9% for time-point vs. time-range studies, respectively. Lymphopenia was associated with increased risk of death, with a pooled HR of 1.78 (95% CI 1.46–2.17, P < 0.00001) for the time-point studies, and a pooled HR of 1.38 (95% CI 1.24–1.55, P < 0.00001) for the time-point studies. There was no significant heterogeneity between studies.ConclusionThese results strengthen observations from previous individual single-institution studies and better defines the magnitude of the association between lymphopenia with OS in GBM patients, highlighting lymphopenia as a poor prognostic factor.

Does Western or Chinese Zodiac Sign Predict COVID Infections and Death?

Humans have been fascinated by and studying the sky since the beginning of time. Beliefs in Chinese and Western astrology persist in modern society and have gained increasing interest in light of the COVID-19 pandemic. Zodiac signs are typified by certain qualities, for example, obsessive-compulsive traits in Libras and Virgos or the highly social traits in Leos and Geminis. We investigate whether the various characteristics or personalities purported of assigned birth signs may alter the predisposition to COVID-19 infections or mortality. This is a retrospective, single-center cohort study of 2545 adult patients with confirmed COVID-19 infection presenting to the emergency room over a 14-month period (September 2020 to November 2021). COVID-19 infectivity was determined based on polymerase chain reaction (PCR) testing. Western and Chinese Zodiac signs were designated using date of birth. Both Zodiac signs were evaluated for risk of infection and death. Mortality rates across the zodiac and astrology signs showed no statistical difference using the 12-sample test for equality of proportions. Coincidentally, the mean age for the deceased was 74.5 years, and it was 53.9 years for those alive, resulting in a difference of 20.6 years. A two-sample t-test confirms that the observed difference of 20.6 years of age between the two groups is statistically significant with a p-value <0.05. The coefficient of the predictor age is statistically significant. The odds ratio estimate of age is 1.06, with the corresponding 95% confidence interval (CI) being (1.048, 1.073). This means that the odds of dying increase by 6% for every additional year. Astrology once held a significant impact on beliefs in medicine and continues in Chinese and Ayurvedic medicine. Our study utilized local data to determine if COVID-19 infection rates and mortality might have a relationship to astrological designations of Chinese and Western zodiac signs. Data analysis demonstrated that there was no statistical significance found between Western and Chinese Zodiac signs and mortality or infections. Similar to many previous studies, age can be a risk factor for mortality.

Simultaneous inference procedures for the comparison of multiple characteristics of two survival functions.

Survival time is the primary endpoint of many randomized controlled trials, and a treatment effect is typically quantified by the hazard ratio under the assumption of proportional hazards. Awareness is increasing that in many settings this assumption is a priori violated, for example, due to delayed onset of drug effect. In these cases, interpretation of the hazard ratio estimate is ambiguous and statistical inference for alternative parameters to quantify a treatment effect is warranted. We consider differences or ratios of milestone survival probabilities or quantiles, differences in restricted mean survival times, and an average hazard ratio to be of interest. Typically, more than one such parameter needs to be reported to assess possible treatment benefits, and in confirmatory trials, the according inferential procedures need to be adjusted for multiplicity. A simple Bonferroni adjustment may be too conservative because the different parameters of interest typically show considerable correlation. Hence simultaneous inference procedures that take into account the correlation are warranted. By using the counting process representation of the mentioned parameters, we show that their estimates are asymptotically multivariate normal and we provide an estimate for their covariance matrix. We propose according to the parametric multiple testing procedures and simultaneous confidence intervals. Also, the logrank test may be included in the framework. Finite sample type I error rate and power are studied by simulation. The methods are illustrated with an example from oncology. A software implementation is provided in the R package nph.

Estimation of the odds ratio from multi-stage randomized trials.

A multi-stage design for a randomized trial is to allow early termination of the study when the experimental arm is found to have low or high efficacy compared to the control during the study. In such a trial, an early stopping rule results in bias in the maximum likelihood estimator of the treatment effect. We consider multi-stage randomized trials on a dichotomous outcome, such as treatment response, and investigate the estimation of the odds ratio. Typically, randomized phase II cancer clinical trials have two-stage designs with small sample sizes, which makes the estimation of odds ratio more challenging. In this paper, we evaluate several existing estimation methods of odds ratio and propose bias-corrected estimators for randomized multi-stage trials, including randomized phase II cancer clinical trials. Through numerical studies, the proposed estimators are shown to have a smaller bias and a smaller mean squared error overall.