Obesity-Status-Linked Affecting Factors of Dyslipidemia in Korean Young-Adult Men: Based on the Korea National Health and Nutrition Examination Survey (2019-2021).

In recent years, there has been a growing trend of obesity and dyslipidemia among young adult men in South Korea. Therefore, we aimed to identify the obesity-related factors of dyslipidemia among young adult men in Korea using 3-year data (2019-2021) from the 8th Korea National Health and Nutrition Examination Survey. We included 1559 eligible men aged 19-39 years and examined the association between dyslipidemia and participants' general characteristics, health-related characteristics, and food intake according to obesity status. Statistical analysis was performed using complex sample analysis with weighted household and individual data. The affecting factors of dyslipidemia included age, body image perception, stress, and waist circumference (WC) in the body mass index (BMI) < 25 kg/m2 group and age and WC in the BMI ≥ 25 kg/m2 group. To prevent and manage dyslipidemia in young adult men, interventions should be developed separately for the normal, underweight, and obese groups. Effective intervention requires measuring WC and focusing on body fat control. Moreover, regular screening of this population should be performed to ensure early diagnosis and management of dyslipidemia.

Prognosis and recurrence patterns in patients with early stage lung cancer: a multi-state model approach.

Background: We aimed to assess whether recurrence patterns affect survival and to use a multi-state model to predict the prognosis of early stage non-small cell lung cancer in patients who underwent surgical resection. Methods: Patients with early stage non-small cell lung cancer who underwent surgical resection at two tertiary medical centers between 2010 and 2015 were retrospectively analyzed. A multi-state model was employed with one initial state (surgery), two intermediate states (locoregional recurrence, distant metastasis), and one absorbing state (death), comprising five transitions: surgery to locoregional recurrence, surgery to distant metastasis, surgery to death without recurrence, locoregional recurrence to death, and distant metastasis to death. Cox proportional hazards models stratified for these transitions were performed with the risk factors; transition probabilities for each patient were predicted. Results: A total of 949 patients were identified [median age: 67 years, male: 614 (64.6%)]. Recurrence occurred in 194 (20.4%) patients (locoregional recurrence: 7.3%, distant metastasis: 13.1%). Hazard ratios for distant metastasis after surgery were higher for older age (hazard ratio: 1.03, 95% confidence interval: 1.01-1.06) and adenocarcinoma (hazard ratio: 1.67, 95% confidence interval: 1.06-2.61). Lower lobe location exhibited a higher hazard ratio for death after surgery without recurrence (hazard ratio: 1.59, 95% confidence interval: 1.00-2.53). Stage IIB lung cancer showed a higher probability of transition to distant metastasis after surgery than other stages. Cumulative transition hazards rapidly increased in both recurrence patterns until approximately two years after surgery (locoregional recurrence: 0.052; distant metastasis: 0.104). Patients with distant metastasis were more likely to die within 5 years of surgery than those with locoregional recurrence (6.8% and 2.6%, respectively). Conclusions: With the multi-state model, risk factors and post-relapse survival probabilities differed between locoregional recurrence and distant metastasis. These findings may enable clinicians to establish personalized follow-up strategies for patients undergoing curative resection for early stage non-small cell lung cancer.

Effect of Perceived Stress on Health-Related Quality of Life among Primary Caregiving Spouses of Patients with Severe Dementia: The Mediating Role of Depression and Sleep Quality.

Recently, there has been a rise in the number of spouses becoming primary caregivers to patients with dementia. This study identifies the mediating effects of depression and sleep quality on the relationship between perceived stress and health-related quality of life (HRQoL) among primary caregiving spouses of patients with severe dementia through a secondary data analysis of the 2018 Korea Community Health Survey by the Korea Disease Control and Prevention Agency. Data from 229 primary caregiving spouses of patients with severe dementia were analyzed using descriptive statistics, Spearman's rank correlation or Pearson's correlation analysis, and the lavaan R package, version 0.6-9. The association between perceived stress status (PSS) and the European Quality of Life Five Dimension (EQ-5D) index was highly significant. The direct effect of PSS observed in the model was nullified with both the Patient Health Questionnaire-9 and the Pittsburgh Sleep Quality Index as mediators, which implies that they mediate the effect of PSS on caregivers' EQ-5D indexes. The mediation model accounted for 33.2% of the variance in the EQ-5D index of caregivers. The results suggest the need to develop an intervention to improve sleep quality and manage depression to mitigate a decline in HRQoL for these caregivers.

The Value of the Illness-Death Model for Predicting Outcomes in Patients with Non-Small Cell Lung Cancer.

PURPOSE: The illness-death model (IDM) is a comprehensive approach to evaluate the relationship between relapse and death. This study aimed to illustrate the value of the IDM for identifying risk factors and evaluating predictive probabilities for relapse and death in patients with non-small cell lung cancer (NSCLC) in comparison with the disease-free survival (DFS) model. MATERIALS AND METHODS: We retrospectively analyzed 612 NSCLC patients who underwent a curative operation. Using the IDM, the risk factors and predictive probabilities for relapse, death without relapse, and death after relapse were simultaneously evaluated and compared to those obtained from a DFS model. RESULTS: The IDM provided more detailed risk factors according to the patient's disease course, including relapse, death without relapse, and death after relapse, in patients with resected lung cancer. In the IDM, history of malignancy (other than lung cancer) was related to relapse and smoking history was associated with death without relapse; both were indistinguishable in the DFS model. In addition, the IDM was able to evaluate the predictive probability and risk factors for death after relapse; this information could not be obtained from the DFS model. CONCLUSION: Compared to the DFS model, we found that the IDM provides more comprehensive information on transitions between states and disease stages and provides deeper insights with respect to understanding the disease process among lung cancer patients.

Predictors of Cognitive Function in Community-Dwelling Older Adults by Age Group: Based on the 2017 National Survey of Older Korean Adults.

Owing to a growing older adult population, dementia is emerging as an important health issue. Given that maintaining cognitive functions is crucial for the prevention of dementia, this study aimed to identify the predictors of cognitive function in community-dwelling older adults, through a secondary data analysis of the 2017 National Survey of Older Koreans. A total of 9836 participants were classified into three age groups-young-old (65-74 years), old-old (75-84 years), and oldest-old (≥85 years)-and were separately analyzed using multiple linear regression models. The final model explained 28.0%, 35.0%, and 37.0% of variance in cognitive function in the three age groups, respectively. The most potent predictors of cognitive function in the young-old were electronic device-based activities, instrumental activities of daily living (IADL), and nutrition management; the predictors for the old-old group were electronic device-based activities, IADL, and dementia screening, and those for the oldest-old group were frequency of contact with acquaintances, traveling, and religion. Thus, age group-specific interventions are needed to effectively promote cognitive function among older adults. Digital literacy education, use of community-based elderly welfare programs, opportunities for social interactions, and physical activities can help older adults in maintaining a functional status and muscle strengthening.

Assessing the Optimal Cutpoint for Tumor Size in Patients with Lung Cancer Based on Linear Rank Statistics in a Competing Risks Framework.

PURPOSE: In clinical studies, patients may experience several types of events during follow up under the competing risks (CR) framework. Patients are often classified into low- and high-risk groups based on prognostic factors. We propose a method to determine an optimal cutpoint value for prognostic factors on censored outcomes in the presence of CR. MATERIALS AND METHODS: We applied our method to data collected in a study of lung cancer patients. From September 1, 1991 to December 31, 2005, 758 lung cancer patients received tumor removal surgery at Samsung Medical Center in Korea. The proposed statistic converges in distribution to that of the supremum of a standardized Brownian bridge. To overcome the conservativeness of the test based on an approximation of the asymptotic distribution, we also propose a permutation test based on permuted samples. RESULTS: Most cases considered in our simulation studies showed that the permutation-based test satisfied a significance level of 0.05, while the approximation-based test was very conservative: the powers of the former were larger than those of the latter. The optimal cutpoint value for tumor size (unit: cm) prior to surgery for classifying patients into two groups (low and high risks for relapse) was found to be 1.8, with decent significance reflected as p values less than 0.001. CONCLUSION: The cutpoint estimator based on the maximally selected linear rank statistic was reasonable in terms of bias and standard deviation in the CR framework. The permutation-based test well satisfied type I error probability and provided higher power than the approximation-based test.

Additive-multiplicative hazards regression models for interval-censored semi-competing risks data with missing intermediate events.

BACKGROUND: In clinical trials and survival analysis, participants may be excluded from the study due to withdrawal, which is often referred to as lost-to-follow-up (LTF). It is natural to argue that a disease would be censored due to death; however, when an LTF is present it is not guaranteed that the disease has been censored. This makes it important to consider both cases; the disease is censored or not censored. We also note that the illness process can be censored by LTF. We will consider a multi-state model in which LTF is not regarded as censoring but as a non-fatal event. METHODS: We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. More precisely, we employ the additive and multiplicative hazards model with log-normal frailty and construct the conditional likelihood to estimate the transition intensities among states in the multi-state model. Marginalization of the full likelihood is accomplished using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through the iterative quasi-Newton algorithm. RESULTS: Simulation is performed to investigate the finite-sample performance of the proposed estimation method in terms of the relative bias and coverage probability of the regression parameters. The proposed estimators turned out to be robust to misspecifications of the frailty distribution. PAQUID data have been analyzed and yielded somewhat prominent results. CONCLUSIONS: We propose a multi-state model for semi-competing risks data for which there exists information on fatal events, but information on non-fatal events may not be available due to lost to follow-up. Simulation results show that the coverage probabilities of the regression parameters are close to a nominal level of 0.95 in most cases. Regarding the analysis of real data, the risk of transition from a healthy state to dementia is higher for women; however, the risk of death after being diagnosed with dementia is higher for men.

Comparing survival functions with interval-censored data in the presence of an intermediate clinical event.

BACKGROUND: In the presence of an intermediate clinical event, the analysis of time-to-event survival data by conventional approaches, such as the log-rank test, can result in biased results due to the length-biased characteristics. METHODS: In the present study, we extend the studies of Finkelstein and Nam & Zelen to propose new methods for handling interval-censored data with an intermediate clinical event using multiple imputation. The proposed methods consider two types of weights in multiple imputation: 1) uniform weight and 2) the weighted weight methods. RESULTS: Extensive simulation studies were performed to compare the proposed tests with existing methods regarding type I error and power. Our simulation results demonstrate that for all scenarios, our proposed methods exhibit a superior performance compared with the stratified log-rank and the log-rank tests. Data from a randomized clinical study to test the efficacy of sorafenib/sunitinib vs. sunitinib/sorafenib to treat metastatic renal cell carcinoma were analyzed under the proposed methods to illustrate their performance on real data. CONCLUSIONS: In the absence of intensive iterations, our proposed methods show a superior performance compared with the stratified log-rank and the log-rank test regarding type I error and power.

A review on mathematical models for estimating indoor radon concentrations.

Radiation from natural sources is one of causes of the environmental diseases. Radon is the leading environmental cause of lung cancer next to smoking. To investigate the relationship between indoor radon concentrations and lung cancer, researchers must be able to estimate an individual's cumulative level of indoor radon exposure and to do so, one must first be able to assess indoor radon concentrations. In this article, we outline factors affecting indoor radon concentrations and review related mathematical models based on the mass balance equation and the differential equations. Furthermore, we suggest the necessities of applying time-dependent functions for indoor radon concentrations and developing stochastic models.

A comparative study on gene-set analysis methods for assessing differential expression associated with the survival phenotype.

BACKGROUND: Many gene-set analysis methods have been previously proposed and compared through simulation studies and analysis of real datasets for binary phenotypes. We focused on the survival phenotype and compared the performances of Gene Set Enrichment Analysis (GSEA), Global Test (GT), Wald-type Test (WT) and Global Boost Test (GBST) methods in a simulation study and on two ovarian cancer data sets. We considered two versions of GSEA by allowing different weights: GSEA1 uses equal weights, yielding results similar to the Kolmogorov-Smirnov test; while GSEA2's weights are based on the correlation between genes and the phenotype. RESULTS: We compared GSEA1, GSEA2, GT, WT and GBST in a simulation study with various settings for the correlation structure of the genes and the association parameter between the survival outcome and the genes. Simulation results indicated that GT, WT and GBST consistently have higher power than GSEA1 and GSEA2 across all scenarios. However, the power of the five tests depends on the combination of correlation structure and association parameter. For the ovarian cancer data set, using the FDR threshold of q < 0.1, the GT, WT and GBST detected 12, 6 and 8 significant pathways, respectively, whereas neither GSEA1 nor GSEA2 detected any significant pathways. In addition, among the pathways found significant by GT, WT, and GBST, three pathways--Purine metabolism, Leukocyte transendothelial migration and Jak-STAT signaling pathway--overlapped with those reported in previous ovarian cancer microarray studies. CONCLUSION: Simulation studies and a real data example indicate that GT, WT and GBST tend to have high power, whereas GSEA1 and GSEA2 have lower power. We also found that the power of the five tests is much higher when genes are correlated than when genes are independent, when survival is positively associated with genes. It seems that there is a synergistic effect in detecting significant gene sets when significant genes have within-class correlation and the association between survival and genes is positive or negative (i.e., one-direction correlation).

Median regression model with interval censored data.

Quantile regression methods have been used to estimate upper and lower quantile reference curves as the function of several covariates. Especially, in survival analysis, median regression models to the right-censored data are suggested with several assumptions. In this article, we consider a median regression model for interval-censored data and construct an estimating equation based on weights derived from interval-censored data. In a simulation study, the performances of the proposed method are evaluated for both symmetric and right-skewed distributed failure times. A well-known breast cancer data are analyzed to illustrate the proposed method.

A generalized log-rank-type test for comparing survivals with doubly interval-censored data.

In doubly interval-censored data, the survival time of interest is defined as the elapsed time between an initial event and a subsequent event, but the occurrences of both events cannot be observed exactly. Instead, only right- or interval-censored observations on the occurrence times are available. Our purpose is to develop a generalized log-rank-type test for comparing survival functions of several groups. For the same problem, Sun (The Statistical Analysis of Interval-censored Failure Time Data, Springer, New York) suggested a nonparametric test based on the estimated marginal survival functions of the two related events. We consider a new method using uniform weights, which depend only on the size of the risk set at each observed time. The proposed method does not require the estimation of marginal survival functions and furthermore can reduce to the log-rank test for right-censored data. Results from a simulation study show that our test performs well in terms of size and power. We analyze the AIDS cohort study data taken from Kim et al. (Biometrics 49, 13-22).

Cost-effective mammography screening in Korea: high incidence of breast cancer in young women.

The epidemiological characteristics of breast cancer in Korean women are different from the characteristics reported in Western women. The highest incidence rate occurs in Korean women in their 40s. The purpose of this study was to determine the most cost-effective screening interval and target age range for Korean women from the perspective of the national healthcare system. A stochastic model was used to simulate breast cancer screenings by varying both the screening intervals and the age ranges. The effectiveness of mammography screening was defined as the probability of detecting breast cancer in the preclinical state and the cost was based on the direct cost of mammography screening and the confirmative tests. The age-specific mean sojourn times and the sensitivity of the mammography were applied in the stochastic model. An optimal cost-effectiveness was determined by the incremental cost-effectiveness ratio and lifetime schedule sensitivity. Sensitivity analyses were undertaken to assess parameter uncertainty. The selected cost-effective strategies were: (1) the current biennial mammography screenings for women who are at least 40 years old; (2) biennial screening for women between the ages of 35 and 75 years; and (3) a combination strategy consisting of biennial screening for women aged between 45 and 54 years, and 3-year interval screening for women aged between 40 and 44 years and 55 and 65 years. Further studies should follow to investigate the effectiveness of mammography screening in women younger than 40 years in Asia as well as in Korea.

Scheduling mammography screening for the early detection of breast cancer in Korean women.

OBJECTIVE: To propose an efficient screening schedule for breast cancer among Korean women using the stochastic model in which the age-specific incidence rate was considered. SETTING: Female breast cancer data in the Korea Central Cancer Registry 2002. METHODS: The stochastic model was based on the threshold method, in which the schedule is determined by a pre-specified threshold value. The threshold value was defined as the probability of being in a preclinical state of breast cancer at age 40 years. The sensitivity of the mammography was specified as 0.7. Two models for mean sojourn time (MST) in the preclinical state were considered; MSTs for Model I were 2 (ages < 50 years), 3 (ages 50-59 years), and 4 years (ages > or = 60 years), and MSTs for Model II were 3, 4, and 5 years for the corresponding age groups. RESULTS: The threshold method for Model I generated 19 examinations within the screening ages of 40-69 years. Each screening time was determined at ages 40.0, 41.6, 43.2, 44.8, 46.0, 47.2, 48.4, 49.6, 50.7, 51.7, 52.7, 53.7, 54.7, 56.2, 57.8, 59.4, 61.3, 63.1, and 64.9 years. The schedule sensitivity of Model I was 64.2%, which was higher than that (57.5%) of the biennial periodic schedule. Model II included 11 screenings between the ages of 40 and 69 years and also showed a higher schedule sensitivity, especially for women aged 40 years as compared with the biennial screening. CONCLUSIONS: This finding suggests that the threshold screening schedule for breast cancer increase the schedule sensitivity by reflecting the age-specific incidence rate of a population.

Haplotype-based score test for linkage in nuclear families.

BACKGROUND: To look for genetic linkage between angiotensin-I converting enzyme(ACE) gene and hypertension in a Korean adolescent cohort, we developed a powerful test using the covariances between marginal differences and their variances in a transmission/non-transmission table. RESULTS: We estimated haplotype frequencies using the parental and affected offspring's genotypes and then constructed a transmission/non-transmission table for the parental haplotypes transmitted to the offspring. We then proposed a test for checking the marginal homogeneity in the table. Because the cells in the table were dependent due to the uncertainty of the parental haplotypes, we adopted a randomization procedure to estimate the significance of the observed test statistic. Simulations show that our test performs well on a nominal level and has a monotone power, which increases as the relative risk increases. With our test, there was no evidence of genetic linkage between the ACE gene and hypertension in the Korean adolescent cohort. CONCLUSION: We developed a score test for linkage and used simulations to demonstrate that our test performs well at a nominal level. Under some situations where the diversity of haplotypes is low, the proposed test gained a little power over the method based on only variances between marginal differences in a transmission/non-transmission table.

[A study on scheduling periodic examinations for the early detection of breast cancer in Korea].

OBJECTIVES: The purposes of this study were to propose a screening schedule for the early detection of breast cancer among Korean women, as based on the statistical model, and to compare the efficacy of the proposed screening schedule with the current recommendations. METHODS: The development of the screening schedule for breast cancer closely followed the work of Lee and Zelen (1998). We calculated the age-specific breast cancer incidence rate from the Korea Central Cancer Registry (2003), and then we estimated the scheduling of periodic examinations for the early detection of breast cancer, using mammography, and based on the threshold method. The efficacy of the derived screening schedule was evaluated by the schedule sensitivity. RESULTS: For estimating the screening schedule threshold method, we set the threshold value as the probability of being in the preclinical stage at age 35, the sensitivity of mammography as 0.9 and the mean sojourn time in the preclinical stage as 4 years. This method generated 14 examinations within the age interval [40, 69] of 40.0, 41.3, 42.7, 44.1, 45.4, 46.7, 48.0, 49.3, 51.0, 53.2, 55.3, 57.1, 59.0 and 63.6 years, and the schedule sensitivity was 75.4%. The proposed screening schedule detected 85.2% (74.5/87.4) of the cases that could have been detected by annual screening, but it required only about 48.7% (14.0/30.0) of the total number of examinations. We also examined the threshold screening schedules for a range of sensitivities of mammography and the mean sojourn time in the preclinical stage. CONCLUSIONS: The proposed screening schedule for breast cancer with using the threshold method will be helpful to provide guidelines for a public health program for choosing an effective screening schedule for breast cancer among Korean women.

Statistical algorithm in genetic linkage based on haplotypes.

OBJECTIVES: This study was conducted to propose a new transmission/disequilibrium test (TDT) to test the linkage between genetic markers and diseasesusceptibility genes based on haplotypes. Simulation studies were performed to compare the proposed method with that of Zhao et al. in terms of type I error probability and powers. METHODS: We estimated the haplotype frequencies using the expectation-maximization (EM) algorithm with parents' genotypes taken from a trio dataset, and then constructed a two-way contingency table containing estimated frequencies to all possible pairs of parents' haplotypes. We proposed a score test based on differences between column marginals and their corresponding row marginals. The test also involved a covariance structure of marginal differences and their variances. In simulation, we considered a coalescent model with three genetic markers of biallele to investigate the performance of the proposed test under six different configurations. RESULTS: The haplotype-based TDT statistics, our test and Zhao et al.'s test satisfied a type I error probability, but the TDT test based on single locus showed a conservative trend. As expected, the tests based on haplotypes also had better powers than those based on single locus. Our test and that of Zhao et al. were comparable in powers. CONCLUSIONS: We proposed a TDT statistic based on haplotypes and showed through simulations that our test was more powerful than the single locus-based test. We will extend our method to multiplex data with affected and/or unaffected sibling (s) or simplex data having only one parent's genotype.

Nonparametric quantile estimation with correlated failure time data.

In biomedical studies, correlated failure time data arise often. Although point and confidence interval estimation for quantiles with independent censored failure time data have been extensively studied, estimation for quantiles with correlated failure time data has not been developed. In this article, we propose a nonparametric estimation method for quantiles with correlated failure time data. We derive the asymptotic properties of the quantile estimator and propose confidence interval estimators based on the bootstrap and kernel smoothing methods. Simulation studies are carried out to investigate the finite sample properties of the proposed estimators. Finally, we illustrate the proposed method with a data set from a study of patients with otitis media.