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1.
Nat Prod Res ; : 1-8, 2020 Jan 05.
Artigo em Inglês | MEDLINE | ID: mdl-31903783

RESUMO

Anti-complementary activity-guided fractionation led to the isolation of a new abietane diterpene (1) and twenty-five known compounds (2-26) from the twigs and leaves of Juniperus tibetica. All the compounds were isolated from J. tibetica for the first time. The structure of 1 was assigned by spectroscopic data and X-ray crystallography analysis. Five lignans (2, 3, 7, 9 and 10), two flavones (19 and 22), and one coumarin (23) exhibited anti-complementary activity with CH50 values ranging from 0.3 to 3.69 mM.

2.
Artigo em Inglês | MEDLINE | ID: mdl-31974810

RESUMO

PURPOSE: To examine cross-sectional associations between perceived neighborhood environment and cognitive function among middle-aged and older Hispanic/Latino women and men. METHODS: Data from the Hispanic Community Health Study/Study of Latinos (2008-2011) and its Sociocultural Ancillary Study (2009-2010) were used. Participants were Hispanic/Latino women (n = 1812) and men (n = 1034) aged 45-74 years. Survey-weighted linear regression models were used to examine associations between self-reported perceived neighborhood environment (i.e., neighborhood social cohesion and problems categorized as quintiles, and neighborhood safety from crime categorized as low, medium, or high) with cognitive function (i.e., global cognition, verbal learning, memory, verbal fluency, and processing speed scores) in women and men. Final model adjusted for age, Hispanic/Latino background, language, field site, household income, education, years lived in neighborhood, and depressive symptoms. RESULTS: Women in the lowest quintile of perceived neighborhood problems (vs. highest quintile) had higher global cognition (ß 0.48, 95% CI 0.03, 0.94, p trend 0.229) and memory scores (0.60, 95% CI 0.11, 1.09, p trend: 0.060). Women in the highest quintile of perceived neighborhood social cohesion (vs. lowest quintile) had lower global cognition (ß - 0.56, 95% CI - 1.02, - 0.09, p trend 0.004), verbal learning (B - 1.01, 95% CI - 2.00, - 0.03, p trend 0.015), verbal fluency (B - 2.00, 95% CI - 3.83, - 0.16, p trend 0.006), and processing speed (B - 2.11, 95% CI - 3.87, - 0.36, p trend 0.009). There was no association between perceived neighborhood safety from crime and cognition among women, or between any perceived neighborhood environment measure and cognition among men. CONCLUSIONS: Middle-aged and older Hispanic/Latina women living in neighborhoods with the lowest perceived problems had higher global cognition and memory. Women living in neighborhoods with the highest perceived social cohesion had lower global cognition, verbal learning, verbal fluency, and processing speed.

3.
Liver Int ; 2020 Jan 21.
Artigo em Inglês | MEDLINE | ID: mdl-31965669

RESUMO

INTRODUCTION: Non-alcoholic fatty liver disease (NAFLD) disproportionately affects Hispanic/Latinos and rates of NAFLD vary among Hispanics from different background groups. Genetic variants and continental ancestry contribute to NAFLD disparities among Hispanics. We evaluated two newly identified NAFLD-associated single nucleotide polymorphisms of HSD17B13, rs72613567:TA and rs62305723:A in Hispanics/Latinos. METHODS: Clinical data, genotypes of variants of interest and estimates of continental ancestry were extracted from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) database, which includes a cohort of 16 415 US Hispanic/Latinos. Surrogate endpoints for NAFLD were suspected NAFLD based on unexplained aminotransferase elevation, continuous ALT levels and FIB-4 scores to estimate hepatic fibrosis. RESULTS: In all, 9342 participants were included for analysis. The rs72613567:TA allele was found in 15.3% and the rs62305723:A allele was identified in 4.5% of HCHS/SOL participants. rs72613567:TA was less frequent in persons with vs without suspected NAFLD (12.4% vs 15.7%, P < .001) and rs72613567:TA was associated with lower FIB-4 scores (P = .01). For persons with the NAFLD-associated PNPLA3 rs738409:G allele, the presence of rs72613567:TA was associated with a lower rate of suspected NAFD (odds ratio = 0.76, P < .001). rs72613567:TA was less frequent in Hispanic/Latino background groups with higher rates of suspected NAFLD. The rs62305723:A allele was not associated with suspected NAFLD or FIB-4 score. CONCLUSION: The rs72613567:TA allele is associated with lower rates of suspected NAFLD and lower FIB-4 scores among Hispanic/Latinos and with lower rates of suspected NAFLD in persons with the PNPLA3 rs738409:G allele. The rs72613567:TA allele contributes to NAFLD disparities among Hispanic/Latino background groups.

4.
Cardiovasc Diabetol ; 19(1): 11, 2020 Jan 28.
Artigo em Inglês | MEDLINE | ID: mdl-31992297

RESUMO

BACKGROUND: Insulin resistance may contribute to aortic stiffening that leads to end-organ damage. We examined the cross-sectional association and prospective association of insulin resistance and aortic stiffness in older adults without diabetes. METHODS: We analyzed 2571 men and women at Visit 5 (in 2011-2013), and 2350 men and women at repeat examinations from baseline at Visit 1 (in 1987-1989) to Visit 5 (in 2011-2013). Linear regression was used to estimate the difference in aortic stiffness per standard unit of HOMA-IR, TG/HDL-C, and TyG at Visit 5. Linear mixed effects were used to assess if high, as opposed to non-high, aortic stiffness (> 75th percentile) was preceded by a faster annual rate of change in log-HOMA-IR, log-TG/HDL-C, and log-TyG from Visit 1 to Visit 5. RESULTS: The mean age of participants was 75 years, 37% (n = 957) were men, and 17% (n = 433) were African American. At Visit 5, higher HOMA-IR, higher TG/HDL-C, and higher TyG were associated with higher aortic stiffness (16 cm/s per SD (95% CI 6, 27), 29 cm/s per SD (95% CI 18, 40), and 32 cm/s per SD (95% CI 22, 42), respectively). From Visit 1 to Visit 5, high aortic stiffness, compared to non-high aortic stiffness, was not preceded by a faster annual rate of change in log-HOMA-IR from baseline to 9 years (0.030 (95% CI 0.024, 0.035) vs. 0.025 (95% CI 0.021, 0.028); p = 0.15) or 9 years onward (0.011 (95% CI 0.007, 0.015) vs. 0.011 (95% CI 0.009, 0.013); p = 0.31); in log-TG/HDL-C from baseline to 9 years (0.019 (95% CI 0.015, 0.024) vs. 0.024 (95% CI 0.022, 0.026); p = 0.06) or 9 years onward (- 0.007 (95% CI - 0.010, - 0.005) vs. - 0.009 (95% CI - 0.010, - 0.007); p = 0.08); or in log-TyG from baseline to 9 years (0.002 (95% CI 0.002, 0.003) vs. 0.003 (95% CI 0.003, 0.003); p = 0.03) or 9 years onward (0 (95% CI 0, 0) vs. 0 (95% CI 0, 0); p = 0.08). CONCLUSIONS: Among older adults without diabetes, insulin resistance was associated with aortic stiffness, but the putative role of insulin resistance in aortic stiffness over the life course requires further study.

6.
Biostatistics ; 21(1): 122-138, 2020 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-30084874

RESUMO

Potential disease-modifying therapies for neurodegenerative disorders need to be introduced prior to the symptomatic stage in order to be effective. However, current diagnosis of neurological disorders mostly rely on measurements of clinical symptoms and thus only identify symptomatic subjects in their late disease course. Thus, it is of interest to select and integrate biomarkers that may reflect early disease-related pathological changes for earlier diagnosis and recruiting pre-sypmtomatic subjects in a prevention clinical trial. Two sources of biological information are relevant to the construction of biomarker signatures for time to disease onset that is subject to right censoring. First, biomarkers' effects on disease onset may vary with a subject's baseline disease stage indicated by a particular marker. Second, biomarkers may be connected through networks, and their effects on disease may be informed by this network structure. To leverage these information, we propose a varying-coefficient hazards model to induce double smoothness over the dimension of the disease stage and over the space of network-structured biomarkers. The distinctive feature of the model is a non-parametric effect that captures non-linear change according to the disease stage and similarity among the effects of linked biomarkers. For estimation and feature selection, we use kernel smoothing of a regularized local partial likelihood and derive an efficient algorithm. Numeric simulations demonstrate significant improvements over existing methods in performance and computational efficiency. Finally, the methods are applied to our motivating study, a recently completed study of Huntington's disease (HD), where structural brain imaging measures are used to inform age-at-onset of HD and assist clinical trial design. The analysis offers new insights on the structural network signatures for premanifest HD subjects.

7.
Mol Psychiatry ; 25(2): 283-296, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31745239

RESUMO

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among civilian trauma survivors and military veterans. These APNS, as traditionally classified, include posttraumatic stress, postconcussion syndrome, depression, and regional or widespread pain. Traditional classifications have come to hamper scientific progress because they artificially fragment APNS into siloed, syndromic diagnoses unmoored to discrete components of brain functioning and studied in isolation. These limitations in classification and ontology slow the discovery of pathophysiologic mechanisms, biobehavioral markers, risk prediction tools, and preventive/treatment interventions. Progress in overcoming these limitations has been challenging because such progress would require studies that both evaluate a broad spectrum of posttraumatic sequelae (to overcome fragmentation) and also perform in-depth biobehavioral evaluation (to index sequelae to domains of brain function). This article summarizes the methods of the Advancing Understanding of RecOvery afteR traumA (AURORA) Study. AURORA conducts a large-scale (n = 5000 target sample) in-depth assessment of APNS development using a state-of-the-art battery of self-report, neurocognitive, physiologic, digital phenotyping, psychophysical, neuroimaging, and genomic assessments, beginning in the early aftermath of trauma and continuing for 1 year. The goals of AURORA are to achieve improved phenotypes, prediction tools, and understanding of molecular mechanisms to inform the future development and testing of preventive and treatment interventions.

8.
Biometrics ; 2019 Dec 18.
Artigo em Inglês | MEDLINE | ID: mdl-31850527

RESUMO

Biomarkers are often organized into networks, in which the strengths of network connections vary across subjects depending on subject-specific covariates (eg, genetic variants). Variation of network connections, as subject-specific feature variables, has been found to predict disease clinical outcome. In this work, we develop a two-stage method to estimate biomarker networks that account for heterogeneity among subjects and evaluate network's association with disease clinical outcome. In the first stage, we propose a conditional Gaussian graphical model with mean and precision matrix depending on covariates to obtain covariate-dependent networks with connection strengths varying across subjects while assuming homogeneous network structure. In the second stage, we evaluate clinical utility of network measures (connection strengths) estimated from the first stage. The second-stage analysis provides the relative predictive power of between-region network measures on clinical impairment in the context of regional biomarkers and existing disease risk factors. We assess the performance of proposed method by extensive simulation studies and application to a Huntington's disease (HD) study to investigate the effect of HD causal gene on the rate of change in motor symptom through affecting brain subcortical and cortical gray matter atrophy connections. We show that cortical network connections and subcortical volumes, but not subcortical connections are identified to be predictive of clinical motor function deterioration. We validate these findings in an independent HD study. Lastly, highly similar patterns seen in the gray matter connections and a previous white matter connectivity study suggest a shared biological mechanism for HD and support the hypothesis that white matter loss is a direct result of neuronal loss as opposed to the loss of myelin or dysmyelination.

9.
Alzheimers Dement ; 15(12): 1624-1632, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31759880

RESUMO

Hispanics/Latinos are the largest ethnic/racial group in the United States and at high risk for Alzheimer's disease and related dementia (ADRD). Yet, ADRD among diverse Latinos is poorly understood and disparately understudied or unstudied compared to other ethnic/racial groups that leave the nation ill-prepared for major demographic shifts that lay ahead in coming decades. The primary purpose of this Perspectives article was to provide a new research framework for advancing Latino ADRD knowledge, encompassing the unique sociocultural, cardiometabolic, and genomic aspects of Latino health, aging, and ADRD. In addition, we describe some of the research challenges to progress in Latino ADRD research. Finally, we present the Study of Latinos - Investigation of Neurocognitive Aging (SOL-INCA) as an example of implementing this new framework for advancing Latino ADRD research.

10.
Alzheimers Dement ; 15(12): 1507-1515, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31753701

RESUMO

INTRODUCTION: We estimated the prevalence and correlates of mild cognitive impairment (MCI) among middle-aged and older diverse Hispanics/Latinos. METHODS: Middle-aged and older diverse Hispanics/Latinos enrolled (n = 6377; 50-86 years) in this multisite prospective cohort study were evaluated for MCI using the National Institute on Aging-Alzheimer's Association diagnostic criteria. RESULTS: The overall MCI prevalence was 9.8%, which varied between Hispanic/Latino groups. Older age, high cardiovascular disease (CVD) risk, and elevated depressive symptoms were significant correlates of MCI prevalence. Apolipoprotein E4 (APOE) and APOE2 were not significantly associated with MCI. DISCUSSION: MCI prevalence varied among Hispanic/Latino backgrounds, but not as widely as reported in the previous studies. CVD risk and depressive symptoms were associated with increased MCI, whereas APOE4 was not, suggesting alternative etiologies for MCI among diverse Hispanics/Latinos. Our findings suggest that mitigating CVD risk factors may offer important pathways to understanding and reducing MCI and possibly dementia among diverse Hispanics/Latinos.

11.
Ann Appl Stat ; 13(2): 1295-1318, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31673303

RESUMO

Neurological diseases are due to the loss of structure or function of neurons that eventually leads to cognitive deficit, neuropsychiatric symptoms, and impaired activities of daily living. Identifying sensitive and specific biological and clinical markers for early diagnosis allows recruiting patients into a clinical trial to test therapeutic intervention. However, many biomarker studies considered a single biomarker at one time that fails to provide precise prediction for disease age at onset. In this paper, we use longitudinally collected measurements from multiple biomarkers and measurement error-corrected clinical diagnosis ages to identify which biomarkers and what features of biomarker trajectories are useful for early diagnosis. Specifically, we assume that the subject-specific biomarker trajectories depend on unobserved states of underlying latent variables with the conditional mean follows a nonlinear sigmoid shape. We show that peak degeneration age of the biomarker trajectory is useful for early diagnosis. We propose an Expectation-Maximization (EM) algorithm to obtain the maximum likelihood estimates of all parameters and conduct extensive simulation studies to examine the performance of the proposed methods. Finally, we apply our methods to studies of Alzheimer's disease and Huntington's disease and identify a few important biomarkers that can be used for early diagnosis.

12.
Hisp Health Care Int ; : 1540415319881755, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31674199

RESUMO

INTRODUCTION: To determine the prevalence of prescription opioid (PO) use among Hispanics/Latinos with arthritis symptoms and to characterize how demographic and cultural factors are associated with PO use. METHOD: Cross-sectional analysis of baseline visit data during 2008 to 2011 from the Hispanic Community Health Study/Study of Latinos, a population-based cohort study of 16,415 Hispanics/Latinos living in Chicago, Illinois, Miami, Florida, Bronx, New York, and San Diego, California. Included participants self-reported painful inflammation or swelling in one or more joints. Multivariate models controlling for physical and mental health scores were constructed to assess how demographic and cultural factors were associated with PO use. RESULTS: A total of 9.3% were using POs at the time of the baseline visit. In multivariate models, persons of Cuban background (adjusted odds ratio [AOR] = 0.42, 95% confidence interval [CI; 0.21, 0.81]) and of Dominican background (AOR = 0.38, 95% CI [0.18, 0.80]) were significantly less likely to use POs compared with a reference group of persons of Mexican background. Greater language acculturation was also negatively associated with PO use (AOR = 0.68, 95% CI [0.53, 0.87]). CONCLUSION: POs were used relatively uncommonly, and use showed marked variation between Hispanic/Latino groups. Future study should determine mechanisms for why greater use of English among Hispanics/Latinos might influence PO use.

13.
Biometrics ; 2019 Nov 14.
Artigo em Inglês | MEDLINE | ID: mdl-31724739

RESUMO

The pharmaceutical industry and regulatory agencies are increasingly interested in conducting bridging studies in order to bring an approved drug product from the original region (eg, United States or European Union) to a new region (eg, Asian-Pacific countries). In this article, we provide a new methodology for the design and analysis of bridging studies by assuming prior knowledge on how the null and alternative hypotheses in the original, foreign study are related to the null and alternative hypotheses in the bridging study and setting the type I error for the bridging study according to the strength of the foreign-study evidence. The new methodology accounts for randomness in the foreign-study evidence and controls the average type I error of the bridging study over all possibilities of the foreign-study evidence. In addition, the new methodology increases statistical power, when compared to approaches that do not use foreign-study evidence, and it allows for the possibility of not conducting the bridging study when the foreign-study evidence is unfavorable. Finally, we conducted extensive simulation studies to demonstrate the usefulness of the proposed methodology.

14.
Alzheimers Dement (N Y) ; 5: 533-541, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31650010

RESUMO

Introduction: Higher cognitive stimulation (CS) is associated with improved cognition. Sources of CS among Hispanics/Latinos are understudied. Methods: In the Hispanic Community Health Study/Study of Latinos 2008 to 2011 (n = 9438), we used finite mixture models to generate latent CS profiles, and multivariate linear regressions to examine associations with cognition in Hispanic/Latino adults (45-74 years). CS included education, occupation, social network, and acculturation. Cognitive measures included the Six-Item Screener, Brief-Spanish English Verbal Learning Test Sum and Recall, Controlled Oral Word Association Test, Digit Symbol Substitution, and Global Cognition. Results: Two CS profiles emerged, and were labeled "typical" and "enhanced." The enhanced CS profile (22%) had more family connections, bicultural engagements, skilled/professional occupations, education, and higher cognitive scores. Discussion: An enhanced CS profile emerged from contextual and culturally relevant factors, and was associated with higher cognitive scores across all measures. This provides initial evidence on how factors coalesce to shape cognitive protection in Hispanics/Latinos.

15.
Alzheimers Dement ; 2019 Oct 03.
Artigo em Inglês | MEDLINE | ID: mdl-31606367

RESUMO

INTRODUCTION: To determine if sleep-disordered breathing (SDB), daytime sleepiness, insomnia, and sleep duration predict seven-year neurocognitive decline in US Hispanics/Latinos (N = 5247). METHODS: The exposures were baseline SDB, daytime sleepiness, insomnia, and sleep duration. The outcomes were change in episodic learning and memory (B-SEVLT-Sum and SEVLT-Recall), language (word fluency [WF]), processing speed (Digit Symbol Substitution), and a cognitive impairment screener (Six-item Screener [SIS]). RESULTS: Mean age was 63 ± 8 years, with 55% of the population being female with 7.0% Central American, 24.5% Cuban, 9.3% Dominican, 35.9% Mexican, 14.4% Puerto Rican, and 5.1% South American background. Long sleep (>9 hours), but not short sleep (<6 hours), was associated with decline (standard deviation units) in episodic learning and memory (ßSEVLT-Sum = -0.22 [se = 0.06]; P < .001; ßSEVLT-Recall = -0.13 [se = 0.06]; P < .05), WF (ßWF = -0.20 [se = 0.06]; P < .01), and SIS (ßSIS = -0.16 [se = 0.06]; P < .01), but not processing speed, after adjusting for covariates. SDB, sleepiness, and insomnia were not associated with neurocognitive decline. CONCLUSION: Long sleep duration predicted seven-year cognitive decline.

16.
J Am Stat Assoc ; 114(527): 1232-1240, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31588157

RESUMO

Health sciences research often involves both right- and interval-censored events because the occurrence of a symptomatic disease can only be observed up to the end of follow-up, while the occurrence of an asymptomatic disease can only be detected through periodic examinations. We formulate the effects of potentially time-dependent covariates on the joint distribution of multiple right- and interval-censored events through semiparametric proportional hazards models with random effects that capture the dependence both within and between the two types of events. We consider nonparametric maximum likelihood estimation and develop a simple and stable EM algorithm for computation. We show that the resulting estimators are consistent and the parametric components are asymptotically normal and efficient with a covariance matrix that can be consistently estimated by profile likelihood or nonparametric bootstrap. In addition, we leverage the joint modelling to provide dynamic prediction of disease incidence based on the evolving event history. Furthermore, we assess the performance of the proposed methods through extensive simulation studies. Finally, we provide an application to a major epidemiological cohort study. Supplementary materials for this article are available online.

17.
Stat Sin ; 29(4): 1851-1871, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31579362

RESUMO

Large cohort studies are commonly launched to study risk of genetic variants or other risk factors on age at onset (AAO) of a chronic disorder. In these studies, family history data including AAO of disease in family members are collected to provide additional information and can be used to improve efficiency. Statistical analysis of these data is challenging due to missing genotypes in family members and the heterogeneous dependence attributed to both shared genetic back-ground and shared environmental factors (e.g., life style). In this paper, we propose a class of semiparametric transformation models with multilevel random effects to tackle these challenges. The proposed models include both proportional hazards model and proportional odds model as special cases. The multilevel random effects contain individual-specific random effects including kinship correlation structure dependent on the family pedigree, and a shared random effect to account for unobserved environment exposure. We use nonparametric maximum likelihood approach for inference and propose an expectation-maximization algorithm for computation in the presence of missing genotypes among family members. The obtained estimators are shown to be consistent, asymptotically normal, and semiparametrically efficient. Simulation studies demonstrate that the proposed method performs well with finite sample sizes. Finally, the proposed method is applied to study genetic risks in an Alzheimer's disease study.

18.
Stat Sin ; 29(4): 1633-1655, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31534307

RESUMO

Estimating optimal individualized treatment rules (ITRs) in single or multi-stage clinical trials is one key solution to personalized medicine and has received more and more attention in statistical community. Recent development suggests that using machine learning approaches can significantly improve the estimation over model-based methods. However, proper inference for the estimated ITRs has not been well established in machine learning based approaches. In this paper, we propose a entropy learning approach to estimate the optimal individualized treatment rules (ITRs). We obtain the asymptotic distributions for the estimated rules so further provide valid inference. The proposed approach is demonstrated to perform well in finite sample through extensive simulation studies. Finally, we analyze data from a multi-stage clinical trial for depression patients. Our results offer novel findings that are otherwise not revealed with existing approaches.

19.
Dermatol Surg ; 2019 Sep 02.
Artigo em Inglês | MEDLINE | ID: mdl-31490300

RESUMO

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic, inflammatory condition characterized by recurrent nodules, sinus tracts, comedones, and scarring. Hidradenitis suppurativa is often associated with pain and decreased quality of life. Limited clinical trial data exist regarding the management of acute HS lesions, but clinical experience and a prospective case series suggest that intralesional triamcinolone may be useful. OBJECTIVE: To compare the efficacy of intralesional triamcinolone to placebo for the treatment of HS inflammatory lesions. MATERIALS AND METHODS: This is a double-blind, randomized, placebo-controlled trial comparing intralesional triamcinolone 10 mg/mL, triamcinolone 40 mg/mL, and normal saline (NS). Thirty-two subjects at University of North Carolina Dermatology and Skin Cancer Centers were enrolled for a total of 67 lesions. Subjects reported pain scores, days to resolution, and satisfaction on a standardized survey over a 14-day period. RESULTS: When intralesional injections of triamcinolone 10 mg/mL, triamcinolone 40 mg/mL, and NS were compared, no significant difference was found for days to HS inflammatory lesion clearance, pain reduction at Day 5, or patient satisfaction. CONCLUSION: No statistically significant difference was found between varying concentrations of triamcinolone and NS for the treatment of HS lesions. Steroid injections may be less effective for the management of acute HS than typically presumed.

20.
Electron J Stat ; 13(1): 1717-1743, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31440323

RESUMO

Treatment rules based on individual patient characteristics that are easy to interpret and disseminate are important in clinical practice. Properly planned and conducted randomized clinical trials are used to construct individualized treatment rules. However, it is often a concern that trial participants lack representativeness, so it limits the applicability of the derived rules to a target population. In this work, we use data from a single trial study to propose a two-stage procedure to derive a robust and parsimonious rule to maximize the benefit in the target population. The procedure allows a wide range of possible covariate distributions in the target population, with minimal assumptions on the first two moments of the covariate distribution. The practical utility and favorable performance of the methodology are demonstrated using extensive simulations and a real data application.

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