Explaining age differences in the memory-experience gap.

Emotions and symptoms are often overestimated in retrospective ratings, a phenomenon referred to as the "memory-experience gap." Some research has shown that this gap is less pronounced among older compared to younger adults for self-reported negative affect, but it is not known whether these age differences are evident consistently across domains of well-being and why these age differences emerge. In this study, we examined age differences in the memory-experience gap for emotional (positive and negative affect), social (loneliness), and physical (pain, fatigue) well-being. We also tested four variables that could plausibly explain age differences in the gap: (a) episodic memory and executive functioning, (b) the age-related positivity effect, (c) variability of daily experiences, and (d) socially desirable responding. Adults (n = 477) from three age groups (21-44, 45-64, 65+ years old) participated in a 21-day diary study. Participants completed daily end-of-day ratings and retrospective ratings of the same constructs over different recall periods (3, 7, 14, and 21 days). Results showed that, relative to young and middle-aged adults, older adults had a smaller memory-experience gap for negative affect and loneliness. Lower day-to-day variability partly explained why the gap was smaller for older adults. There was no evidence that the magnitude of the memory-experience gap for positive affect, pain or fatigue depended on age. We recommend that future research considers how variability in daily experiences can impact age differences in retrospective self-reports of well-being. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Influence of ecological momentary assessment study design features on reported willingness to participate and perceptions of potential research studies: an experimental study.

OBJECTIVE: Intensive ambulatory assessment, such as ecological momentary assessment (EMA), is increasingly used to capture naturalistic patient-reported outcomes. EMA design features (eg, study duration, prompt frequency) vary widely between studies, but it is not known if such design decisions influence potential subjects' willingness to participate in a study. We hypothesise that intentions to participate will be higher in studies that are less burdensome and have higher reward (eg, compensation). DESIGN: This experimental study examined if four EMA study design features (study duration, prompt frequency, prompt length, compensation) affected intentions to participate in a hypothetical EMA study and participation appraisals (eg, participation effort). Participants were randomly assigned to conditions (reflecting a fully crossed design of the four features, each with two levels). Each condition presented a vignette describing a study (each a unique combination of design features) and asked them to report on likelihood of participating and study appraisals. PARTICIPANTS: A convenience sample of participants (n=600; 46% female, Mage=40.39) were recruited using an online service. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcomes were willingness to participate (No/Yes) and reported participation likelihood (0-100 scale). Secondary outcomes included appraisals of interest, enjoyment, effort, and if the study makes a valuable contribution to science. RESULTS: We examined main effects, and two-way interactions for participation likelihood, across study design features. Overall, reported willingness to participate and participation likelihood were high (89%, M=83.90, respectively). Shorter study duration, fewer prompts, shorter prompts and higher compensation increased willingness to participate and elicited higher participation likelihood (each associated with ~6%-8% increases). Findings suggested that more intensive studies were judged as somewhat less interesting and enjoyable, and requiring more effort. CONCLUSION: Hypotheses were generally supported. Design features influence behavioural intentions to participate in, and appraisals of, EMA studies. Implications for participant recruitment and generalisability, and remaining research questions, are discussed.

Imagine HEALTH: Randomized Controlled Trial of a Guided Imagery Lifestyle Intervention to Improve Obesity-Related Lifestyle Behaviors in Predominantly Latinx Adolescents.

Introduction: To determine the effects of a novel lifestyle intervention combining lifestyle behavioral education with the complementary-integrative health modality of guided imagery (GI) on dietary and physical activity behaviors in adolescents. The primary aim of this study was to determine the incremental effects of the lifestyle education, stress reduction GI (SRGI), and lifestyle behavior GI (LBGI) components of the intervention on the primary outcome of physical activity lifestyle behaviors (sedentary behavior, light, moderate, and vigorous physical activity), as well as dietary intake behaviors, at the completion of the 12-week intervention. The authors hypothesized that the intervention would improve obesity-related lifestyle behaviors. Materials and Methods: Two hundred and thirty-two adolescent participants (aged 14-17 years, sophomore or junior year of high school) were cluster randomized by school into one of four intervention arms: nonintervention Control (C), Lifestyle education (LS), SRGI, and LBGI. After-school intervention sessions were held two (LS) or three (SRGI, LBGI) times weekly for 12 weeks. Physical activity (accelerometry) and dietary intake (multiple diet recalls) outcomes were assessed pre- and postintervention. Primary analysis: intention-to-treat (ITT) mixed-effects modeling with diagonal covariance matrices; secondary analysis: ad hoc subgroup sensitivity analysis using only those participants adherent to protocol. Results: ITT analysis showed that the Healthy Eating Index (HEI) increased in the LS group compared with C (p = 0.02), but there was no additional effect of GI. Among adherent participants, sedentary behavior was decreased stepwise relative to C in SRGI (d = -0.73, p = 0.004) > LBGI (d = -0.59, p = 0.04) > LS (d = -0.41, p = 0.07), and moderate + vigorous physical activity was increased in SRGI (d = 0.58, p = 0.001). Among adherent participants, the HEI was increased in LS and SRGI, and glycemic index reduced in LBGI. Conclusions: While ITT analysis was negative, among adherent participants, the Imagine HEALTH lifestyle intervention improved eating habits, reduced sedentary activity, and increased physical activity, suggesting that GI may amplify the role of lifestyle education alone for some key outcomes. Clinical Trials.gov ID: NCT02088294.

A model-free test for detecting disease association signals with multiple genetic variants and covariates.

Discoveries and analyses of genetic variants at a gene or exome based on high-throughput sequencing technology are increasingly feasible. Although many well-known association tests have already been proposed in literature for testing whether a group of variants in a target region is associated with a disease of interest, however, the analytic challenges still remain profound. The power performance of these tests generally depends on the sample size, numbers of causal and neutral variants, variant frequency, effect size, and direction. Some of these factors are not easily controllable in practical applications. Further complications arise from missing genotype, population stratification or misspecification of the working model. Previous studies showed that many model-based tests might create false positive results or decrease power when there was population stratification effect or missing genotype and simple imputation was used. Here, we demonstrate by simulations that type I errors of the well-known model-based tests are often inflated as well, even the working model deviates slightly from the true model. We propose a model-free test and show this test to be almost uniformly most powerful among the competing tests under very general simulation conditions with covariates. This test does not require genotype data to be complete and hence difficult imputation can be avoided. We also discuss how to adjust for the effect of population stratification based on principal components, and use a Shanghai Breast Cancer Study to demonstrate application of the new test.

Detecting disease association signals with multiple genetic variants and covariates.

Due to the improvements in the efficiency of resequencing technologies, discoveries and analyses of rare variants in sequencing-based association studies at the gene level, or even exome-wide are becoming increasingly feasible. Powerful association tests have been suggested in literature for testing whether a group of variants in a gene region is associated with a particular disease of interest. Their performance depends on the correct assumption of regression model and conditions such as the size of the case and control sample, numbers of causal and noncausal variants (rare or common), variant frequency, effect size and directionality, rate of missing genotype, etc. Most of these model-based tests require genotype data to be complete at each variant. Our previous results showed that in the case of no covariate, the power of these tests might be greatly influenced, when there were missing genotypes and only simple imputation was used. In this paper, we demonstrate by simulations that in the presence of covariates, the type I errors of these approaches might be inflated, even when genotype missing rate was very small. We present an association test based on testing zero proportion of causal variants in the gene region, and show this test to be almost uniformly most powerful among the competing tests under very general simulation conditions. This test does not require genotype to be complete and hence is robust against missing genotype. We discuss how to adjust for population stratification based on principal components and show the power loss of this approach was small when the population stratification effect was moderate. We use a Shanghai Breast Cancer Study to demonstrate application of the tests and show the proposed test is more powerful in detecting variants related to breast cancer, and robust against the inclusion of noncausal variants.

Prospective trial of an herbal formula BYSH and Saw palmetto in patients with hormonal refractory prostate cancer: a pilot study.

OBJECTIVE: BYSH, a herbal formula, was evaluated for efficacy and safety in a pilot study for patients with advanced hormone refractory prostate cancer (HRPC). PATIENTS AND METHODS: The pilot study was designed as a single-center open-label trial. Patients with HRPC were treated with BYSH for 24 weeks. The primary end point was the changes in serum prostate-specific antigen (PSA) level. Safety parameters such as liver and renal functions were monitored during the study period. RESULTS: Ten patients were eligible for the study. Most of them had stable PSA levels while taking BYSH. However, at the end of the BYSH treatment, the level of PSA increased. The median survival from diagnosis of HRPC was 16.4 months. Liver and renal functions remained normal. BYSH was well tolerated and no patient reported adverse events during the study period. CONCLUSION: Although it is inappropriate to make a conclusion based on the pilot study results, the trend of improvement is obvious. Further investigations should be conducted to demonstrate its clinical benefits. We have also briefly reviewed some plant products which are patented and also available in market.

Comparison of the effectiveness of different immobilization systems in different body regions using daily megavoltage CT in helical tomotherapy.

OBJECTIVE: Effective immobilization is crucial for the accurate delivery of radiotherapy. This study aimed to compare the effectiveness of the commonly used immobilization systems for different body regions using megavoltage CT (MVCT). METHODS: Daily treatment set-up data from 212 patients treated by helical tomotherapy (Accuray, Sunnyvale, CA) in 6 body regions (52 head and neck, 41 chest, 38 abdomen, 36 pelvis, 18 breast and 27 cranium) were obtained. Based on a verification tool using the pre-treatment MVCT, set-up corrections for each patient were recorded. Mean systematic and random errors of lateral, longitudinal, vertical and roll directions and three-dimensional vectors were compared between immobilization systems of each region. RESULTS: Smaller set-up deviations were observed in the Orfit system (Orfit Industries NV, Wijnegem, Belgium) of the head and neck region, while the performance of immobilization systems for the chest, abdomen and pelvis regions was similar. Larger differences were noted in the breast group, where the prone BodyFIX® system (Medical Intelligence, Medizintechnik GmbH, Schwabmünchen, Germany) was less stable than the supine VacLok® system (CIVCO Medical Solutions, Orange City, IA). CONCLUSION: Differences were found between the immobilization systems in the head and neck region, in which the Orfit system was relatively more effective, whereas the VacLok and BodyFIX systems performed similarly in the chest, abdomen and pelvis regions. For the breast case, the supine position with VacLok was much more stable than the prone breast technique. The results provided references for the estimation of clinical target volume-planning target volume margins. ADVANCES IN KNOWLEDGE: This is the first article on comprehensive comparisons performed in immobilization systems for main body regions that provides some practical recommendations.

A powerful association test of multiple genetic variants using a random-effects model.

There is an emerging interest in sequencing-based association studies of multiple rare variants. Most association tests suggested in the literature involve collapsing rare variants with or without weighting. Recently, a variance-component score test [sequence kernel association test (SKAT)] was proposed to address the limitations of collapsing method. Although SKAT was shown to outperform most of the alternative tests, its applications and power might be restricted and influenced by missing genotypes. In this paper, we suggest a new method based on testing whether the fraction of causal variants in a region is zero. The new association test, T REM , is derived from a random-effects model and allows for missing genotypes, and the choice of weighting function is not required when common and rare variants are analyzed simultaneously. We performed simulations to study the type I error rates and power of four competing tests under various conditions on the sample size, genotype missing rate, variant frequency, effect directionality, and the number of non-causal rare variant and/or causal common variant. The simulation results showed that T REM was a valid test and less sensitive to the inclusion of non-causal rare variants and/or low effect common variants or to the presence of missing genotypes. When the effects were more consistent in the same direction, T REM also had better power performance. Finally, an application to the Shanghai Breast Cancer Study showed that rare causal variants at the FGFR2 gene were detected by T REM and SKAT, but T REM produced more consistent results for different sets of rare and common variants.

Inflammatory state of type II diabetic patients with chronic ulcers in response to herbal treatment.

BACKGROUND: Type II diabetic patients easily develop ulcers over their feet which heal with great difficulties and not infrequently, end up in amputations. In the quest for innovative means to avoid amputation, herbal medicine has been used in China to heal ulcers. METHOD: A randomized placebo controlled clinical trial involving 80 patients was conducted to test whether a herbal formula taken orally could help to preserve the ulcerated leg. Other parameters measured included granulation maturation time, skin temperature and circulation, and tumor necrosis factor alpha (TNF-α). RESULTS: showed a 85% limb rescue with the herbal treatment group showing superiority over placebo group. TNF-α decline was observed with gradual ulcer healing and the herbal supplement group showed a more impressive decline (p=0.037).

Assessing the joint effect of population stratification and sample selection in studies of gene-gene (environment) interactions.

BACKGROUND: It is well known that the presence of population stratification (PS) may cause the usual test in case-control studies to produce spurious gene-disease associations. However, the impact of the PS and sample selection (SS) is less known. In this paper, we provide a systematic study of the joint effect of PS and SS under a more general risk model containing genetic and environmental factors. We provide simulation results to show the magnitude of the bias and its impact on type I error rate of the usual chi-square test under a wide range of PS level and selection bias. RESULTS: The biases to the estimation of main and interaction effect are quantified and then their bounds derived. The estimated bounds can be used to compute conservative p-values for the association test. If the conservative p-value is smaller than the significance level, we can safely claim that the association test is significant regardless of the presence of PS or not, or if there is any selection bias. We also identify conditions for the null bias. The bias depends on the allele frequencies, exposure rates, gene-environment odds ratios and disease risks across subpopulations and the sampling of the cases and controls. CONCLUSION: Our results show that the bias cannot be ignored even the case and control data were matched in ethnicity. A real example is given to illustrate application of the conservative p-value. These results are useful to the genetic association studies of main and interaction effects.

A robust TDT-type association test under informative parental missingness.

Many family-based association tests rely on the random transmission of alleles from parents to offspring. Among them, the transmission/disequilibrium test (TDT) may be considered to be the most popular statistical test. The TDT statistic and its variations were proposed to evaluate nonrandom transmission of alleles from parents to the diseased children. However, in family studies, parental genotypes may be missing due to parental death, loss, divorce, or other reasons. Under some missingness conditions, nonrandom transmission of alleles may still occur even when the gene and disease are not associated. As a consequence, the usual TDT-type tests would produce excessive false positive conclusions in association studies. In this paper, we propose a novel TDT-type association test which is not only simple in computation but also robust to the joint effect of population stratification and informative parental missingness. Our test is model-free and allows for different mechanisms of parental missingness across subpopulations. We use a simulation study to compare the performance of the new test with TDT and point out the advantage of the new method.

Classical reflux symptoms, hiatus hernia and overweight independently predict pharyngeal acid exposure in patients with suspected reflux laryngitis.

BACKGROUND: Gastro-oesophageal reflux disease (GERD) has been associated with reflux laryngitis. AIMS: To investigate the risk factors and the predictors of pharyngeal acid reflux (PAR) in Taiwanese patients with suspected reflux laryngitis. METHODS: With referral from ENT physicians, 104 patients with symptoms and signs suggestive of reflux laryngitis completed a validated symptom questionnaire, an upper endoscopy exam and ambulatory 24-h pH tests with three sensors located at the hypopharynx, proximal and distal oesophagus. Patients with one or more episodes of PAR were considered abnormal. RESULTS: Pharyngeal acid reflux was identified in 17% (18/104) of patients. In multivariate logistic regression analysis, PAR was independently associated with classical reflux symptoms [adjusted odds ratio (aOR) = 3.5, 95% confidence interval (CI): 1.0-12.8], hiatus hernia (aOR = 6.7, 95% CI: 1.5-30.2) and overweight (aOR = 3.4, 95% CI: 1.0-11.0). In predicting PAR, classical reflux symptoms had a sensitivity of 78% and hiatus hernia had a specificity of 95%. With all three factors, the positive predictive value for PAR was 80%. Classical reflux symptoms included heartburn, chest pain, dyspepsia and acid regurgitation. CONCLUSIONS: Classical reflux symptoms, hiatus hernia and overweight are independent risk factors that may predict pharyngeal acid reflux in patients with suspected reflux laryngitis.

An easy-to-implement approach for analyzing case-control and case-only studies assuming gene-environment independence and Hardy-Weinberg equilibrium.

The case-control study is a simple and an useful method to characterize the effect of a gene, the effect of an exposure, as well as the interaction between the two. The control-free case-only study is yet an even simpler design, if interest is centered on gene-environment interaction only. It requires the sometimes plausible assumption that the gene under study is independent of exposures among the non-diseased in the study populations. The Hardy-Weinberg equilibrium is also sometimes reasonable to assume. This paper presents an easy-to-implement approach for analyzing case-control and case-only studies under the above dual assumptions. The proposed approach, the 'conditional logistic regression with counterfactuals', offers the flexibility for complex modeling yet remains well within the reach to the practicing epidemiologists. When the dual assumptions are met, the conditional logistic regression with counterfactuals is unbiased and has the correct type I error rates. It also results in smaller variances and achieves higher powers as compared with using the conventional analysis (unconditional logistic regression).

Studying the joint effects of population stratification and sampling in case-control association studies.

Population stratification (PS) is referred to the systematic difference in allele frequencies between subpopulations in a population. It could cause a false-positive conclusion in a case-control association study, where the association is due to the structure of the underlying population, not a disease-associated locus. In this paper, we study the joint effects of PS and data sampling when the genetic effect is null. The level of the PS effect depends on the variation of the baseline genotype frequency across subpopulations and matching effectiveness of the sampling. In the case of simple random sampling (SRS), the matching effectiveness equals the inverse of the variation of the disease odds, and thus the PS bias is null under constant disease risk. However, if the latter condition holds but the sampling is not SRS, the bias may still exist. The magnitude of the bias increases as the deviation between the true sampling and SRS increases. We also derive bounds for the bias. If the bounds are approximately known or estimable, we show that this information can be used to compute a conservative p value for the usual association test. We give two real examples to demonstrate the application of the new method.

A powerful two-stage association test using case-control and case-parents genotype data.

OBJECTIVE: The performance of association tests based on case-control or case-parents substudy alone can be improved by jointly using genetic data from two substudies. However, genetic data from different sources may not be combinable due to population stratification. We propose a two-stage association test based on using combinability tests in stage 1 and association tests in stage 2. METHODS: The combinability tests are designed for testing that genotype data from different sources have same genotype frequencies and relative risks. The association tests are well known tests in the literature. We propose a method to adjust the significance levels at two stages so that the overall type I error rate of the two-stage test can be controlled at the desired level. RESULTS: The simulation results confirm that the two-stage test has empirical type I error rates approximately equal to the predetermined levels while making substantially fewer false negatives than the usual test based only on case-parents substudy. CONCLUSION: It is advantageous to combinecase-control and case-parents data into a single analysis.The two-stage test has significant power improvement when the family-based test has weak or moderate power performance and is robust to the effect of population stratification.

Increasing prevalence of erosive esophagitis among Taiwanese aged 40 years and above: a comparison between two time periods.

BACKGROUND: Earlier prevalence studies have reported an increasing trend of gastroesophageal reflux disease in Asia, and obesity may be the promoting factor. GOALS: This study compared the prevalence of erosive esophagitis and obesity status among the same source of subjects in Taiwan between 1995 and 2002. STUDY: In the same routine health checkup unit, we recruited 1902 apparently healthy adults in 2002 matched by sex and age with 2044 individuals recruited in 1995. The prevalence of esophagitis and body mass index between these 2 groups were compared. RESULTS: The crude prevalence of esophagitis increased from 5% in 1995 to 12.6% in 2002 (P<0.0001). Comparing by age stratum, there was an increase of esophagitis among subjects aged 40 years and above, with a dose-response relationship of adjusted prevalence ratios 2.65 [95% confidence interval (CI): 1.10, 4.20] in those aged 40 to 49 years, 3.15 (95% CI: 1.51, 4.79) in those aged 50 to 59 years, and 4.33 (95% CI: 2.56, 6.11) in those aged 60 years and above. The prevalence of esophagitis increased in both sexes. BMI was positively associated with the presence of esophagitis in women, but the proportion of overweight or obesity did not increase in women aged 40 years and above over time. CONCLUSIONS: There was a 2.5-fold of increase in prevalence of erosive esophagitis among Taiwanese adults from 1995 to 2002, particularly in those aged 40 years and above. Factors other than obesity seem to contribute to the increasing trend of erosive esophagitis in Taiwanese women.

Combining unrelated family studies to improve the power of genetic association test.

Family-based studies provide powerful inferences regarding associations between genetic variants and risks, but have limitations. Since very often, the availability of the parental genotypes can pose a problem for using family-based design, especially when the disease of interest has a late age of onset. To improve the efficiency of the studies, a popular approach is to reconstruct the missing genotypes from the genotypes of their offspring and correct the biases resulting from the reconstruction. In this paper, the author shows that two or more unrelated family studies, for the same candidate marker but different diseases, can also be combined to construct a more efficient test for association analysis. The usual case-control study with parental genotypes is a special case of the data discussed here. The author used a simulation study to compare the performance of the new method with other well-known methods. The results showed that the new test has an advantage of having larger power when there is no effect of population stratification between two study samples. However, if there is effect of population stratification between the two samples, the new test still maintains the expected type I error rate and has comparable power performance. Since the unrelated family studies not for the disease of interest are often readily accessible with minimal cost, the proposed method has practical value. The new approach can also be easily modified to allow for missing parental data.

The effects of misclassification in studies of gene-environment interactions.

Differential Misclassification of genotype may cause usual tests producing spurious gene-disease associations or unable to detect important associations. To control for the resulting bias, many model-based approaches have been proposed using validation data. However, the effects of joint misclassification of genotype and environmental exposure in studies of gene-environment interaction are still not clear. In this paper, we focus on quantifying the effects of misclassification in case-control and case-only studies of interaction without specifying any model for misclassification probabilities. By using the derived results, we are able to identify important conditions, under which the presence of misclassification does not introduce bias in case-control or case-only studies. We have conducted a simulation study, using parameter values from real examples, to confirm our theoretical findings. The simulation results show that under the identified conditions, many regular tests for the hypothesis of no interaction maintain correct type I error rates in the presence of differential misclassification. However, their powers may be decreased as misclassification error rates increase.