Predictors of basic and instrumental activities of daily living among older adults with multiple chronic conditions.

BACKGROUND: Understanding the predictors of functional status can be useful for improving modifiable predictors or identifying at-risk populations. Researchers have examined the predictors of functional status in older adults, but there has not been sufficient study in this field in older adults with multiple chronic conditions, especially in Iran. Consequently, the results of this body of research may not be generalizable to Iran. Therefore, this study was conducted to determine the predictors of functional status in Iranian older adults with multiple chronic conditions. METHODS: In this cross-sectional study, 118 Iranian older adults with multiple chronic conditions were recruited from December 2022 to September 2023. They were invited to respond to questionnaires inquiring about their demographic and health information, basic activities of daily living (BADL) and instrumental activities of daily living (IADL), depression and cognitive status. The predictors included age, gender, marital status, education, number of chronic conditions, and depression. Descriptive and analytical statistical tests (univariate and multiple regression analysis) were used to analyze the data. RESULTS: The majority of participants were married (63.9%) and women (59.3%). Based on the results of the multiple regression analysis, age (B=-0.04, P = 0.04), depression (B=-0.12, P = 0.04), and IADL (B = 0.46, P < 0.001) were significant predictors for functional status in terms of BADL. Also, marital status (B=-0.51, P = 0.05), numbers of chronic conditions (B=-0.61, P = 0.002), and BADL (B = 0.46, P < 0.001) were significant predictors for functional status in terms of IADL. CONCLUSION: The findings support the predictive ability of age, marital status, number of chronic diseases, and depression for the functional status. Older adults with multiple chronic conditions who are older, single, depressed and with more chronic conditions number are more likely to have limitations in functional status. Therefore, nurses and other health care providers can benefit from the results of this study and identify and pay more attention to the high risk older adult population.

Comparison performance of the Bayesian Approach with the Weibull and Birnbaum-Saunders distributions in imputation of time-to-event censors.

Almost all survival data is censored, and censor imputation is necessary. This study aimed to investigate the performance of the Bayesian Approach (BA) in the imputation of censored records in simulated and Breast Cancer (BC) data. Due to the difference in the distribution of time to event in survival analysis, two well-known the Weibull and Birnbaum-Saunders (BS) distributions have been used to test the performance of the BA. For each of the censored, 10,000 times were simulated using the BA in R and BUGS software, and their median or mean was imputed instead of each censor. The eligibility of both imputation methods was investigated using different curves, different censoring percentages, and sample sizes, as well as the Deviance Information Criteria (DIC), Effective Sample Size, and the Geweke diagnostic in simulated and especially real BC data. The BC data, which contains 220 patients who were identified and followed up between 2015 and 2023, was made accessible on February 1, 2023. The Kaplan-Meier, the BA, and other survival curves were drawn for the observed times. Findings indicated that the performance of the BA under the Weibull and BS distributions in simulated data is similar. The DIC index in the BC data under the BS distribution (1510) is less than the Weibull distribution (1698). Therefore, the BS distribution is preferred over the Weibull for imputation of censoring times in real BC data.

Evaluation Factors Affecting on Recurrence, Metastasis, and Survival of Breast Cancer in Iranian Women by Multi-State Model Approach.

Background: We used the multistate model to investigate how prognostic factors of breast cancer are seen to affect the disease process. Methods: This cohort study was conducted at Motamed Cancer Institute of Tehran, Iran on 2363 breast cancer patients admitted from 1978 to 2017, and they were followed up until 2018. We applied the multistate models, including four states: diagnosis, recurrence, metastasis, and final absorbing mortality state. Results: Age over 50 years, positive lymph nodes and tumor size intensified the hazard of transition from diagnosis to metastasis (P=0.002, P<0.001 and P=0.001 respectively) and they also intensified the hazard of transition from diagnosis to mortality (P=0.010, P<0.001 and P<0.001 respectively). At the same time, the educational level decreased the hazard of mentioned transitions (P<0.001). Positive estrogen receptors reduced the hazard of transition from diagnosis to metastasis (P=0.007) and positive lymph nodes also intensified the hazard of transition from metastasis to mortality (P=0.040). Tumor size had an increasing role in the transitions from diagnosis to recurrence, recurrence to metastasis, and metastasis to mortality (P=0.014, P=0.018 and P=0.002 respectively). Conclusion: Multistate model presented the detailed effects of prognostic factors on progression of breast cancer. Implementing early diagnosis strategies and providing informational programs, especially in younger ages and lower educational level patients may be helpful in reducing the hazard of transition to higher states of breast cancer and increasing the survival of Iranian women with breast cancer by controlling tumor size growth, lymph nodes involvements and estrogen receptor status.

Survival analysis of recurrent breast cancer patients using mix Bayesian network.

Introduction: Breast cancer (BC) is the most common cancer among women. Iranians have an 11% BC recurrence rate, which lowers their survival rates. Few studies have investigated cancer recurrence survival rates. This study's major purpose is to use a mixed Bayesian network (BN) to analyze recurrent patients' survival. Material and methods: This study aimed to evaluate the pathobiological features, age, gender, final status, and survival time of the patients. Bayesian imputation was used for missing data. The performance of BN was optimized through the utilization of a blacklist and prior probability. After structural and parametric learning, posterior conditional probabilities and mean survival periods for the node arcs were predicted. The hold-out technique based on the posterior classification error was used to investigate the model's validation. Results: The study included 220 cancer recurrence patients. These patients averaged 47 years old. The BN with a blacklist and prior probability has a higher network score than other networks. The hold-out technique verified structural learning. The Directed Acyclic Graph showed a statistically significant relationship between cancer biomarkers (ER, PR, and HER2 receptors), cancer stage, and tumor grade and patient survival duration. Patient death was also significantly associated with education, ER, PR, HER2, and tumor grade. The BN reports that HER2 negative, ER positive, and PR positive patients had a higher survival rate. Conclusion: Survival and death of relapsed patients depend on biomarkers. Based on the findings, patient survival can be predicted with their features.

The Effect of Continuous Care Model on Blood Pressure and Quality of Life in Patients with Hypertension: A Randomized Clinical Trial.

Introduction: Hypertension is one of the most common diseases in all populations. Since people with hypertension have a lower quality of life (QoL) compared to healthy people, it is necessary to follow up these patients according to their conditions. This study aimed to investigate the impact of a continuous care model on blood pressure and QoL in hypertensive patients. Methods: Using a random sampling method, this randomized clinical trial (RCT) included 66 patients with hypertension referring to the clinic of Shahid Madani hospital in Tabriz, Iran in 2019. Data collection tools in this research were demographic information questionnaire, sphygmomanometer control device and stethoscope and Quality of Life questionnaire (The Short Form Health Survey-12, SF-12). The patients were randomly assigned into two groups of control and experimental. After the pre-test, the patients' needs in the experimental group were assessed and the problems were resolved. Then, the post-test was performed one month and two months after the intervention. Data analysis was performed using SPSS software version 13. Results: After the intervention, there was a significant difference in the QoL score and blood pressure in the experimental group. However, this difference was not significant in the control group. Conclusion: Results indicated that using a follow-up care model had a positive effect on the blood pressure and QoL of patients with hypertension. It is recommended that further studies examine the impact of the integrated care model on QoL in other chronic diseases.

Compound Poisson frailty model with a gamma process prior for the baseline hazard: accounting for a cured fraction.

Cox model and traditional frailty models assume that all individuals will eventually experience the event of interest. This assumption is often overlooked, and situations will arise where it is not realistic. We introduce Compound Poisson frailty model for survival analysis to deal with populations in which some of the individuals will not experience the event of interest. This model assumes that the target population is a mixture of individuals with zero frailty and those with positive frailty. In this paper, we consider a compound Poisson frailty model for right-censored event times from a Bayesian perspective and compute the Bayesian estimator using the Markov Chain Monte Carlo method, where a Gamma process prior is adopted for the baseline hazard function. Furthermore, we evaluate the approach using simulation studies and demonstrate the methodology by analyzing the data from achalasia patient cohort.

Long-term outcomes of non-metastatic breast cancer patients by molecular subtypes.

BACKGROUND: Today, with the progress of medical sciences, increasing the cure probability and survival time is an important goal of cancer treatment. This study compared long-term disease-free survival (DFS) of non-metastatic breast cancer patients based on different molecular subtypes. METHODS: This retrospective cohort study consisted of 1287 patients diagnosed with breast cancer and treated at Motamed Cancer Institute from 2000 to 2016 and followed up until 2018. Kaplan-Meier curve was fitted to data based on molecular subtypes. Then the semi-parametric mixture cure model was applied to determine the survival and cure probability of molecular subtypes by adjusting clinical and demographic factors. RESULTS: Among 1287 breast cancer patients, 200 (15.5%) cases died. The mean age of patients was 47.00 ± 10.72 years. Women with the HR+/HER2-subtype had the best 5-year survival rate (84.2%), whereas other subtypes had a lower rate as follows: HR+/HER2+ (77.3%), triple-negative (76.5%), and HR-/HER2+ (62.3%). Kaplan-Meier curve calculated a cure rate of about 60% and patients who survived more than 150 months were intuitively considered cured. After adjustment for clinical and demographic variables, the cure probability of HR-/Her2+ patients was substantially lower than HR+/HER2- patients (OR = 0.22), though there were no significant variations in short-term DFS based on molecular subtypes (HR = 0.91). CONCLUSIONS: Our results confirm that the most prevalent breast cancer was HR+/HER2- tumor type which had the best prognosis. It is also concluded that HR-/HER2+ patients had the worst outcomes, with the highest rates of recurrence and metastasis and the lowest overall and disease-free survival rates.

Diagnostic accuracy of maternal serum multiple marker screening for early detection of gestational diabetes mellitus in the absence of a gold standard test.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with adverse diabetic complications for both mother and child during pregnancy. The common Gold Standard (GS) for diagnosis of GDM is 75 g oral glucose tolerance test (OGTT) during 24-28 gestational weeks which seems a little late for any proper intervention. This study aimed to employ the Bayesian latent class models (LCMs) for estimating the early diagnostic power of combination of serum multiple marker in detecting GDM during 14-17 weeks of gestation. METHODS: Data from a sample of 523 pregnant women who participated in gestational diabetes screening tests at health centers affiliated to Shahid Beheshti University of Medical Sciences in Tehran, Iran from 2017 to 2018 were used. The beta-human chorionic gonadotropin (ß-hCG), unconjugated estriol (uE3), and alfa-fetoprotein (AFP) values were extracted from case records for all participants. The Bayesian LCMs were applied for estimating sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of combining the three biomarkers' results in the absence of GS, adjusting for maternal age and body mass index. RESULTS: The mean (standard deviation) maternal age of the participants was 28.76 (±5.33) years. Additionally, the mean (standard deviation) BMI was 24.57 (±3.22) kg/m2. According to the Bayesian model, the cSensitivity, cSpecificity, and cAUC for the optimal composite diagnostic test were estimated as 94% (95% credible interval (CrI) [0.91-0.99]), 86% (95% CrI [0.80-0.92]), and 0.92 (95% CrI [0.87-0.98]), respectively. CONCLUSIONS: Overall, the findings revealed that the combination of uE3, AFP, and ß-hCG results might be considered as an acceptable predictor for detecting GDM with a rather high level of accuracy in the early second trimester of pregnancy without a GS.

Application of latent class analysis in diagnosis of graft-versus-host disease by serum markers after allogeneic haematopoietic stem cell transplantation.

Graft-versus-host disease (GVHD) is one of the major causes of morbidity and mortality in 25-70% of patients. The gold standard (GS) test to confirm the diagnosis of GVHD has some limitations. The current study was conducted to evaluate the accuracy of three serum markers in diagnosing GVHD without a GS. 94 patients who were hospitalized for allogeneic transplantation were studied. Mean levels from day of haematopoietic stem cell transplantation (HSCT) to discharge of serum uric acid (UA), lactate dehydrogenase (LDH), and creatinine (Cr) were measured for all participants. We adapted a Bayesian latent class analysis to modelling the results of each marker and combination of markers. The Sensitivity, Specificity, and area under receiver operating characteristic curve (AUC) for LDH were as 51%, 81%, and 0.70, respectively. For UA, the Sensitivity, Specificity, and AUC were 54%, 75%, and 0.71, respectively. The estimated Sensitivity, Specificity, and AUC of Cr were 72%, 94%, and 0.86, respectively. Adjusting for covariates, the combined Sensitivity, Specificity, and AUC of the optimal marker combination were 76%, 83%, and 0.94, respectively. To conclude, our findings suggested that Cr had the strongest diagnosis power for GVHD. Moreover, the classification accuracy of the three-marker combination outperforms the other combinations.

Prognostic factors associated with locoronal relapses, metastatic relapses, and death among women with breast cancer. Population-based cohort study.

BACKGROUND: This study was designed to identify the prognostic factors associated with two types of relapses of breast neoplasms. The aim of this study was to evaluate the association between two possible relapses for the increased incidence of distant metastases observed in patients with local relapses injuries, using multivariate statistical models. DESIGN: And Setting: A population-based cohort study that was designed as a single center: the cancer research center, Shahid Beheshti University of medical sciences. METHODS: This study was conducted on 1815 patients with breast cancer having age of 22 or more. This study considers the analysis of recurrence and survival by joint modeling of three correlated outcomes: local recurrence, distant recurrence (metastasis) and death. The goals are to find out the effects of treatments on recurrences and death, the effects of relapses on death and the correlation between local and distant recurrences. RESULTS: According to obtained results of the fitted models, the risk of local and metastatic relapses or death increased for patients with at least one positive lymph node (N+) or for patients with a grade greater than I. Also, the variable HR+ was significantly associated with the hazards of locoronal, metastatic recurrence and the death for both reduced and proposed models (P < 0.05). CONCLUSIONS: We concluded that if the association between these outcomes are not taken into account, we may lose important information. Given the small number of recurrent events, these results should be considered with caution.

Identification of associated risk factors for the severity of generalized anxiety disorder among Iranian infertile people: An ordinal regression analysis with a flexible link function.

BACKGROUND: Generalized anxiety disorder (GAD) is a common disorder in infertile people. The aim of this study was the identification of associated risk factors for the severity of GAD in infertile people using an ordinal model with a flexible link function. MATERIALS AND METHODS: This cross-sectional study was conducted on 1146 individuals with a couple's infertility problem selected from an infertility center in Tehran, Iran. Data collected using self-administered questionnaires include demographic/clinical information and GAD-7. We used a Bayesian-ordered symmetric power logit (splogit) model to identify the risk factors for the severity of GAD. Furthermore, we implemented standard ordinal models to compare with the ordered splogit model. RESULTS: Female gender (B coefficient 0.48, 95% credible interval [CrI]: 0.34-0.62), longer duration of infertility (B coefficient 0.03, 95% CrI: 0.01-0.04), previous treatment failure (B coefficient 0.17, 95% CrI: 0.03-0.30), and self-cause of infertility (B coefficient 0.12, 95% CrI: 0.01-0.23) were associated factors with the severity of GAD. The splogit model had a better fit and performance to determine the associated risk factor for the severity of GAD as compared to standard models. It provided more precise estimates of risk factors and one more significant risk factor. CONCLUSION: Infertile people with female gender, longer duration of infertility, failure in previous treatments, and self-cause infertility are more likely to experience higher severity levels of GAD and require additional psychological, and support interventions. Furthermore, it can be argued that the ordinal splogit model is more powerful to identify the associated risk factors for the severity of GAD.

Risk Ratio Estimation in Longitudinal Studies.

Longitudinal studies are very common in medical, behavioral, and interventional sciences. One measure of effect of interest in longitudinal studies is risk ratio, naturally estimated by log-binomial regression which suffers from convergence problem. Odds ratio does not well approximate risk ratio when the outcome is common, so alternative methods have been introduced in cohort studies with one follow-up visit. In this paper, we illustrate 2 simple methods, COPY method and modified log-Poisson regression for risk ratio estimation in longitudinal data setting. Our unpublished simulation study on risk ratio estimation in longitudinal data setting suggests that COPY method performs well in terms of closeness of the risk ratio estimate and true risk ratio (mean square error) and so we suggest this method for risk ratio estimation in longitudinal Longitudinal studies are very common in medical, behavioral, and interventional sciences. One measure of effect of interest in longitudinal studies is risk ratio, naturally estimated by log-binomial regression which suffers from convergence problems. Odds ratio (OR) does not approximate risk ratio (RR) well when the outcome is common, so alternative methods have been introduced in cohort studies with one follow-up visit. In this paper, we illustrate two simple methods: the COPY method and the modified log-Poisson regression for RR estimation in longitudinal data setting. Our unpublished simulation study on RR estimation in longitudinal data setting suggests that the COPY method performs well in terms of closeness of the RR estimate and true RR (mean square error) and so we suggest this method for RR estimation in longitudinal data setting.data setting.

Health-related quality of life and medication adherence in elderly patients with epilepsy.

OBJECTIVE: Considering the high prevalence of epilepsy in the elderly and the importance of maximising their quality of life (QoL), this study aimed to investigate the relationship between medication adherence and QoL, and the mediating effects of medication adherence on the association between serum antiepileptic drug (AED) level and seizure severity with QoL in elderly epileptics. METHODS: In a longitudinal study, 766 elderly patients with epilepsy who were prescribed a minimum of one antiepileptic drug were selected by convenience sampling method. A Medication Adherence Report Scale (MARS-5) questionnaire was completed at the baseline. Seizure severity and QoL were assessed after six months using the Liverpool Seizure Severity Scale (LSSS) and the QoL in Epilepsy (QOLIE-31) questionnaires respectively. Serum level of AED was also measured at six-month follow-up. RESULTS: Medication adherence was significantly correlated with both seizure severity (ß = -0.33, p < 0.0001) and serum AED level (ß = 0.29, p < 0.0001) after adjusting for demographic and clinical characteristics. Neither QoL nor its sub-classes were correlated with seizure severity. In addition, a significant correlation was not observed between serum AED level and QoL. However, medication adherence was significantly correlated with QoL (ß = 0.30, p < 0.0001). The mediating effects of medication adherence on the association between serum AED level (Z = 3.39, p < 0.001) and seizure severity (Z = -3.47, p < 0.001) with QoL were supported by the Sobel test. CONCLUSION: This study demonstrates that medication adherence has a beneficial impact on QoL in elderly epileptics. Therefore, adherence to treatment should be monitored to improve their QoL.

Modeling In Vitro Fertilization Data Considering Multiple Outcomes Observed among Iranian Infertile Women.

BACKGROUND: Women undergoing in vitro fertilization (IVF) cycles should successfully go through multiple points during the procedure (i.e., implantation, clinical pregnancy, no spontaneous abortion and delivery) to achieve live births. In this study, data from multiple cycles and multiple points during the IVF cycle are collected for each individual to model the effects of factors associated with success at different stages of IVF cycles in Iranian infertile women. MATERIALS AND METHODS: This historical cohort study includes 996 assisted reproductive technology (ART) cycles of 511 infertile women. Covariates considered in this study were women's age, type of cycle (fresh or frozen embryo transfer), number of embryos transferred and having polycystic ovarian syndrome during IVF cycles. Generalized estimating equations were used for calculation of odds ratio (OR) and 95% confidence intervals (95% CI) of success at different stages during IVF cycles. Cluster-weighted generalized estimating equations (CWGEE) was also fitted to handle informative cluster size. RESULTS: After adjusting for potential confounders, it was seen that receiving frozen embryo transfer was associated with higher odds of success compared to receiving fresh embryo transfer (adj OR: 2.26, 95% CI: 1.66-3.07); however, cycles with fresh embryo transfer exhibited better results in clinical pregnancy compared to those receiving frozen embryo. Being in the age category of 38 to 40 was associated with lower odds of success compared to the reference category (p<35) in CWGEE model (adj OR: 0.67, 95% CI: 0.45-1.00). The number of embryos transferred was positively associated with the odds of success in CWGEE (adj OR: 1.21, 95% CI: 1.03-1.42) as well as the GEE model. CONCLUSION: Receiving frozen embryo was positively associated with odds of success compared to cycles with fresh embryo. The number of embryos transferred and women's age were significantly associated with odds of success.

Association between Multiple Recurrent Events with Multivariate Modeling: A Retrospective Cohort Study.

BACKGROUND: Recurrent event data are often encountered in biomedical research, for example, recurrent infections or recurrent hospitalizations for patients after renal transplant. In many studies, there are more than one type of events of interest. We aimed to identify the association between two types of events using multivariate joint modeling and then apply this statistical method in the clinical data set. STUDY DESIGN: A retrospective cohort study. METHODS: Overall, 342 subjects with breast cancer whose records were registered for follow-up in a Cancer Research Center at Shohadaye Tajrish Hospital, Tehran, Iran from 2006 to 2015 were investigated. These patients were monitored for at least 6 months after diagnosis and their latest status were recorded. Joint frailty model was used for modeling the relationship between two types of recurrences with Frailty package in R software. RESULTS: When the terminal event was considered as death, three-year and five-year survival rates for the patients were 0.79 and 0.68, respectively. Given the results obtained from a fitted joint frailty model, the risk of multiple recurrences (local and metastases) increased for the patients with tumor grades greater than I. CONCLUSION: With regard to the significant variance of the frailty component of the metastases event, it can be inferred that patients with the same predictive variables are prone to different levels of metastases risk and, on the other hand, given the low frequency of types of recurrences, caution should be exercised when considering the obtained results.

Investigation factors affecting the first recurrence of coronary artery disease in patients undergone angioplasty using cox survival model.

Background: The incidence of restenosis in patients suffering from coronary artery disease after undergoing angioplasty is of paramount importance. Accordingly, this study aimed to investigate factors affecting the time of the first incidence of restenosis in patients undergone angioplasty in the city of Zanjan, Iran. Methods: This retrospective cohort study was conducted on 421 patients who referred to Ayatollah Musavi hospital in Zanjan for angioplasty during 2009 to 2012. The time of the incidence of restenosis after angioplasty constituted the dependent variable of the study. Independent variables of the study included signs of diabetes, hypertension, hyperlipidemia, kidney disease, carotid stenosis, lung disease, anemia, angina history, and MI. The Cox regression model with the significance level of 0.05 was deployed for the statistical analysis. Results: According to the Cox regression model, hazard ratio of the first incidence of restenosis in patients with hypertension and angina was 22.8% and 29.5% less than other patients, respectively. However, hazard ratio of the first incidence of restenosis was 7.4 times more in patients suffering from carotid stenosis than other patients (p<0.05). Conclusion: The results of this study revealed that as time goes on, the risk of the incidence of restenosis in angioplasty patients increases such that patients' survival decreases dramatically after a year. To determine the role of effective factors on the incidence of restenosis, conducting a prospective interventional study is highly recommended.