Frailty Model Research Articles

Sample Size Estimation Using a Partially Clustered Frailty Model for Biomarker-Strategy Designs With Multiple Treatments.

Biomarker-guided therapy is a growing area of research in medicine. To optimize the use of biomarkers, several study designs including the biomarker-strategy design (BSD) have been proposed. Unlike traditional designs, the emphasis here is on comparing treatment strategies and not on treatment molecules as such. Patients are assigned to either a biomarker-based strategy (BBS) arm, in which biomarker-positive patients receive an experimental treatment that targets the identified biomarker, or a non-biomarker-based strategy (NBBS) arm, in which patients receive treatment regardless of their biomarker status. We proposed a simulation method based on a partially clustered frailty model (PCFM) as well as an extension of Freidlin formula to estimate the sample size required for BSD with multiple targeted treatments. The sample size was mainly influenced by the heterogeneity of treatment effect, the proportion of biomarker-negative patients, and the randomization ratio. The PCFM is well suited for the data structure and offers an alternative to traditional methodologies.

Comparative study of the risk prediction model of early postoperative frailty in elderly enterostomy patients based on machine learning methods.

Based on machine learning method, four types of early postoperative frailty risk prediction model of enterostomy patients were constructed to compare the performance of each model and provide the basis for preventing early postoperative frailty of elderly patients with enterostomy. The prospective convenience sampling method was conducted and 362 early postoperative enterostomy patients were selected in three hospitals from July 2020 to November 2023 in Shanghai, four different prediction models of Support Vector Machine (SVM), Bayes, XG Boost, and Logistic regression were used and compared the test effects of the four models (MCC, F1, AUC, and Brier index) to judge the classification performance of the four models in the data of this study. A total of 21 variables were included in this study, and the predictors mainly covered demographic information, stoma-related information, quality of life, anxiety and depression, and frailty. The validated models on the test set are XGBoost, Logistic regression, SVM prediction model, and Bayes on the MCC and F1 scores; on the AUC, XGBoost, Logistic regression, Bayes, and SVM prediction model; on the Brier scores, Bayes, Logistic regression, and XGBoost. XGBoost based on machine learning method is better than SVM prediction model, Logistic regression model and Bayes in sensitivity and accuracy. Quality of life in the early postoperative period can help guide clinical patients to identify patients at high risk of frailty and reduce the incidence of early postoperative frailty in elderly patients with enterostomy.

Reliability analysis of multiple repairable systems under imperfect repair and unobserved heterogeneity

AbstractImperfect repairs (IRs) are widely applicable in reliability engineering since most equipment is not completely replaced after failure. In this sense, it is necessary to develop methodologies that can describe failure processes and predict the reliability of systems under this type of repair. One of the challenges in this context is to establish reliability models for multiple repairable systems considering unobserved heterogeneity associated with systems failure times and their failure intensity after performing IRs. Thus, in this work, frailty models are proposed to identify unobserved heterogeneity in these failure processes. In this context, we consider the arithmetic reduction of age (ARA) and arithmetic reduction of intensity (ARI) classes of IR models, with constant repair efficiency and a power‐law process distribution to model failure times and a univariate Gamma distributed frailty by all systems failure times. Classical inferential methods are used to estimate the parameters and reliability predictors of systems under IRs. An extensive simulation study is carried out under different scenarios to investigate the suitability of the models and the asymptotic consistency and efficiency properties of the maximum likelihood estimators. Finally, we illustrate the practical relevance of the proposed models on two real data sets.

Tailored vs. General COVID-19 prevention for adults with mental disabilities residing in group homes: a randomized controlled effectiveness-implementation trial

BackgroundPeople with serious mental illness (SMI) and people with intellectual disabilities/developmental disabilities (ID/DD) are at higher risk for COVID-19 and more severe outcomes. We compare a tailored versus general best practice COVID-19 prevention program in group homes (GHs) for people with SMI or ID/DD in Massachusetts (MA).MethodsA hybrid effectiveness-implementation cluster randomized control trial compared a four-component implementation strategy (Tailored Best Practices: TBP) to dissemination of standard prevention guidelines (General Best-Practices: GBP) in GHs across six MA behavioral health agencies. GBP consisted of standard best practices for preventing COVID-19. TBP included GBP plus four components including: (1) trusted-messenger peer testimonials on benefits of vaccination; (2) motivational interviewing; (3) interactive education on preventive practices; and (4) fidelity feedback dashboards for GHs. Primary implementation outcomes were full COVID-19 vaccination rates (baseline: 1/1/2021–3/31/2021) and fidelity scores (baseline: 5/1/21–7/30/21), at 3-month intervals to 15-month follow-up until October 2022. The primary effectiveness outcome was COVID-19 infection (baseline: 1/1/2021–3/31/2021), measured every 3 months to 15-month follow-up. Cumulative incidence of vaccinations were estimated using Kaplan-Meier curves. Cox frailty models evaluate differences in vaccination uptake and secondary outcomes. Linear mixed models (LMMs) and Poisson generalized linear mixed models (GLMMs) were used to evaluate differences in fidelity scores and incidence of COVID-19 infections.ResultsGHs (n=415) were randomized to TBP (n=208) and GBP (n=207) including 3,836 residents (1,041 ID/DD; 2,795 SMI) and 5,538 staff. No differences were found in fidelity scores or COVID-19 incidence rates between TBP and GBP, however TBP had greater acceptability, appropriateness, and feasibility. No overall differences in vaccination rates were found between TBP and GBP. However, among unvaccinated group home residents with mental disabilities, non-White residents achieved full vaccination status at double the rate for TBP (28.6%) compared to GBP (14.4%) at 15 months. Additionally, the impact of TBP on vaccine uptake was over two-times greater for non-White residents compared to non-Hispanic White residents (ratio of HR for TBP between non-White and non-Hispanic White: 2.28, p = 0.03).ConclusionTailored COVID-19 prevention strategies are beneficial as a feasible and acceptable implementation strategy with the potential to reduce disparities in vaccine acceptance among the subgroup of non-White individuals with mental disabilities.Trial registrationClinicalTrials.gov, NCT04726371, 27/01/2021. https://clinicaltrials.gov/study/NCT04726371.

Bayesian survival analysis with INLA.

This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the INLA and INLAjoint R-packages. Such models include accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data, originally presented in the article "Bayesian survival analysis with BUGS." In addition, we illustrate the implementation of a new joint model for a longitudinal semicontinuous marker, recurrent events, and a terminal event. Our proposal aims to provide the reader with syntax examples for implementing survival models using a fast and accurate approximate Bayesian inferential approach.

Association between type of index complication and outcomes after noncardiac surgery

BackgroundFailure to rescue, or the death of a patient after a surgical complication, largely occurs in patients who develop a cascade of postoperative complications. However, it is unclear whether there are specific types of index complications that are more strongly associated with failure to rescue, additional secondary complications, or other types of postoperative outcomes. This is a national cohort study of veterans who underwent noncardiac surgery at Veterans Affairs hospitals using data from the Veterans Affairs Surgical Quality Improvement Program (January 1, 2016 to September 30, 2021). Index complications were grouped into categories (cardiovascular, venous thromboembolism, pulmonary, bleeding/transfusion, renal, central nervous system, wound, sepsis, Clostridium difficile colitis, graft, or minor [defined as complications having an associated mortality rate <1%]). The association between type of index complication and failure to rescue, secondary complications, reoperation, and postoperative length of stay was evaluated with multivariable, hierarchical regression, and risk of death assessed with shared frailty modeling. ResultsAmong 574,195 patients, 5.3% had at least 1 complication (of which 26.1% had secondary complications, and 8.2% had failure to rescue), and 4.5% had a reoperation. Secondary complication (5.0%–61.4%) and failure to rescue (0.8%–34.2%) rates varied by the type of index complication. Relative to index minor complications, index bleeding was most associated with secondary complication (subdistribution hazard ratio 1.4, 95% confidence interval [1.1–1.8]), index cardiac complications were most associated with failure to rescue (odds ratio 45.4 [34.5–59.7]), index graft complications were most associated with reoperation (odds ratio 96.0 [79.5–115.8]), and index pulmonary complications were associated with 2.6 times longer length of stay (incident rate ratio 2.6 [2.6–2.7]). Index cardiac and central nervous system complications were most strongly associated with risk of death (cardiac—hazard ratio 2.45, 95% confidence interval [2.14–2.81]; central nervous system—hazard ratio 1.84 [1.49–2.27]). ConclusionDifferent types of index complications are associated with different outcome profiles. This suggests surgical quality improvement efforts should be tailored not only to the type of index complication to be addressed but also to the desired outcome to improve.

Disparities in access to Dolutegravir in West African children, adolescents and young adults aged 0-24 years living with HIV. A IeDEA Pediatric West African cohort analysis.

We describe the 24-month incidence of Dolutegravir (DTG)-containing antiretroviral treatment (ART) initiation since its introduction in 2019 in the pediatric West African IeDEA cohorts. We included all patients aged 0-24 years on ART, from nine clinics in Côte d'Ivoire (n=4), Ghana, Nigeria, Mali, Benin, and Burkina Faso. Baseline varied by clinic and was defined as date of first DTG prescription; patients were followed-up until database closure/death/loss to follow-up (LTFU, no visit ≥ 7 months), whichever came first. We computed the cumulative incidence function for DTG initiation; associated factors were explored in a shared frailty model, accounting for clinic heterogeneity. Since 2019, 3,350 patients were included; 49% were female;79% had been on ART ≥ 12 months. Median baseline age was 12.9 years (IQR: 9-17). Median follow-up was 14 months (IQR: 7-22). The overall cumulative incidence of DTG initiation reached 35.5% (95% CI: 33.7-37.2) and 56.4% (95% CI: 54.4-58.4) at 12 and 24 months, respectively. In univariate analyses, those aged <5 years and females were overall less likely to switch. Adjusted on ART line and available viral load (VL) at baseline, females >10 years were less likely to initiate DTG compared to males of the same age (aHR among 10-14 years: 0.62, 95% CI: 0.54-0.72; among ≥15 years: 0.43, 95% CI: 0.36-0.50), as were those with detectable VL (> 50 copies/mL) compared to those in viral suppression (aHR: 0.86, 95% CI: 0.77-0.97) and those on PIs compared to those on NNRTIs (aHR after 12 months of roll-out: 0.75, 95% CI: 0.65-0.86). Conclusion: Access to paediatric DTG was incomplete and unequitable in West African settings: children <5years, females ≥ 10 years and those with detectable viral load were least likely to access DTG. Maintained monitoring and support of treatment practices is required to better ensure universal and equal access. What is already known on this topic?: Dolutegravir (DTG)-based ART regimens are recommended as the preferred first-line ART regimens recommended by the World Health Organisation in all people living with HIV since 2018, with a note of caution for pregnant women, then confirmed in all children with approved DTG dosing and adolescents since 2019.Deployment of universal DTG access in adults in West Africa has faced challenges such as infrastructure challenges, and healthcare system disparities, and was hindered by initial perinatal safety concerns affecting greatly women of childbearing age.Specific data on access to DTG in children, adolescents and young adults in West Africa is limited.What this study adds ?: This study describes the dynamic of the DTG roll-out over the first 24 months and its correlates since 2019 in a large West African multicentric cohort of children, adolescents and youth.We observed a rapid scale-up of DTG among children, adolescents and young adults living with HIV in West Africa, despite the COVID-19 pandemic.However, DTG access after 24 months was incomplete and unequitable, with adolescent girls and young women being less likely to initiate DTG compared to males, as were those with a detectable viral load (> 50 copies/mL) compared to those in success.Younger children < 5 years were also less likely to initiate DTG, explained by the later approval of paediatric formulations and their low availability.How this study might affect research, practice or policy?: Maintained monitoring, training and updating guidance for healthcare workers is essential to ensure universal access to DTG, especially for females, for whom inequity begins age 10 years.Efforts to improve access to universal DTG in West Africa require multifaceted interventions including healthcare infrastructure improvement and facilitation of paediatric antiretroviral forecasting and planification.

Long-term outcomes in hybrid versus standalone thoracoscopic ablation in patients with atrial fibrillation: a systematic review and reconstructed individual patient data meta-analysis

Abstract Background Both hybrid and standalone thoracoscopic atrial fibrillation (AF) ablation techniques have demonstrated favorable outcomes in the management of (long-standing) persistent AF patients, as compared to catheter ablation. However, it is currently unknown whether there is a difference in long-term freedom from AF when comparing these two procedures. Purpose To compare long-term freedom from atrial tachyarrhythmias (ATA) in patients undergoing hybrid and standalone thoracoscopic AF ablation. Methods A systematic search encompassing PubMed, EMBASE, and the Cochrane Library databases from January 1, 2012, to September 6, 2023, was performed using the following search terms: 'thoracoscopic ablation,' 'hybrid ablation,' 'atrial fibrillation,' and various alternative spellings. Articles were included for pooled analysis of freedom from ATA after meeting the criteria of reporting on consecutive patients and presenting Kaplan-Meier (KM) curves. Individual time-to-event data were reconstructed from the KM curves and included in a multivariable Cox and frailty Cox model with adjustments for age, sex, type of AF, AF duration, and study (frailty term in the frailty Cox model). Results In total, 18 studies were included in the meta-analysis for long-term freedom from ATA, comprising 2215 patients. Patients undergoing hybrid thoracoscopic ablation were older (62.0 vs. 58.8 years old, p=0.046), had less frequently paroxysmal AF-history (9.6% vs. 32.1%, p&amp;lt;0.01), and had a longer duration of AF-history (7.0 vs. 5.3 years, p=0.04), as compared to patients undergoing standalone thoracoscopic ablation. There were no significant differences between the two ablation procedures regarding short-term outcomes including early mortality (0.6% vs. 1.0%, p=0.07) and early stroke (1.9% vs 0.9%, p=0.11). Adjusted analysis revealed that hybrid thoracoscopic ablation was significantly associated with greater freedom from ATA (Hazard Ratio [HR]=0.59, 95%CI: 0.43-0.83, p&amp;lt;0.001) compared to standalone thoracoscopic ablation (see Figure 1A). Additionally, older age (HR=1.07, 95%CI: 1.03-1.12, p=0.002) and a higher percentage of male patients (HR=1.02, 95% CI: 1.01-1.03, p&amp;lt;0.001) were significantly associated with ATA recurrence. Adjusted freedom from ATA at 1 year, 3 years, and 5 years was 71.6%, 55.1%, and 46.8% for thoracoscopic ablation, and 82.0%, 69.9%, and 63.6% for hybrid ablation (see Figure 1B). Conclusion Hybrid thoracoscopic AF-ablation is associated with a higher level of freedom from ATA when compared to standalone thoracoscopic ablation.Figure 1

Modeling determinants of time-to-premarital cohabitation among Ethiopian women using parametric shared frailty models.

Premarital cohabitation is rampant and currently practiced worldwide, particularly in sub-Saharan Africa. It is a known cause of marital instability and divorce. It is also associated with intimate partner violence and harms the psychology of children in later life. However, in Ethiopia, there has been limited attention given to premarital cohabitation. The main goal of this study was to identify the determinants of time-to-premarital cohabitation among Ethiopian women. The 2016 EDHS data was used to achieve the study's goal. The survival information of 15683 women was analyzed based on their age at premarital cohabitation. The regional states of the women were used as a clustering effect in the models. Exponential, Weibull, and Log-logistic baseline models were used to identify factors associated with age at premarital cohabitation utilizing socioeconomic and demographic characteristics. The median age of premarital cohabitation was found to be 18 years. Surprisingly, 72.7% of participants were cohabitated in the study area. According to the Log-logistic-Gamma shared frailty model, place of residence, occupation, educational status, and being pregnant were found to be factors determining the time to premarital cohabitation. Premarital cohabitation among Ethiopian women was higher compared to women in the sub-Saharan Africa and East Africa. Place of residence, occupation, educational status, and being pregnant were found to be factors determining the time for premarital cohabitation. Therefore, we recommend the concerned bodies set out strategies to educate women about the influencing factors and dangers of premarital cohabitation.

Z-residual diagnostic tool for assessing covariate functional form in shared frailty models

ABSTRACT Survival analysis often involves modeling hazard functions while considering frailty to account for unobserved cluster-level factors in clustered survival data. Shared frailty models have gained popularity for this purpose, but assessing covariate functional form in these models presents unique challenges. Martingale and deviance residuals are commonly used for visually assessing covariate functional form against continuous covariates. Nevertheless, their subjective nature and lack of a reference distribution make it challenging to derive numerical statistical tests from these residuals. To address these limitations, we propose ‘Z-residuals’, a novel diagnostic tool designed for shared frailty models, leveraging the concept of randomized survival probability and introducing both graphical and numerical tests. To implement this approach, we develop an R package to compute Z-residuals for shared frailty models. Through extensive simulation studies, we demonstrate the high power of our derived numerical test for assessing the functional form of covariates. To validate the effectiveness of our method, we apply it to a real data application concerning the modelling of survival time for acute myeloid leukemia patients. Our Z-residual diagnosis results reveal the inadequacy of log-transformation of the covariate, highlighting the limitations of other diagnostic methods for effectively assessing covariate functional form in shared frailty models.

Risk of early revision in total hip arthroplasty: the relative contribution of the surgeon versus the hospital.

Early revision for total hip arthroplasty is a serious adverse outcome. There are multiple contributing risk factors for early revision. Risk factors can exist at the level of the surgeon and the level of the institution. The primary research question of this study was to determine the relative contribution of surgeon-level and hospital-level variance to rates of early revision (overall and for infection) after primary total hip arthroplasty. This is a registry-based study from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR). Data for the most commonly used stem (Exeter V40) were used to reduce prosthesis variation from the analysis. A mixed effects Cox Model (also known as a frailty model) with crossed random effects for surgeon and hospital was used. Outcomes were early revision (within 2 years) for all causes and for infection. This model allowed for the risk of early revision to be explained by the variability at the surgeon level or hospital level. There were 32 031 procedures performed by 735 surgeons across 250 hospitals between 1 January 2015 and 31 December 2019. Surgeon variability significantly contributed to overall variation in revision for any cause and revision for infection (P < 0.0001). There was no significant contribution of hospital-level variation to overall revision or for infection. Surgeon-level factors play a more important role than institution-level factors in early revision after primary total hip arthroplasty. If surgeons are identified as having a higher risk of revision, there is potential for surgeon-level practice change to reduce the risk of early revision.

Physical frailty identification using machine learning to explore the 5-item FRAIL scale, Cardiovascular Health Study index, and Study of Osteoporotic Fractures index.

Physical frailty is an important issue in aging societies. Three models of physical frailty assessment, the 5-Item fatigue, resistance, ambulation, illness and loss of weight (FRAIL); Cardiovascular Health Study (CHS); and Study of Osteoporotic Fractures (SOF) indices, have been regularly used in clinical and research studies. However, no previous studies have investigated the predictive ability of machine learning (ML) for physical frailty assessment. The aim was to use two ML algorithms, random forest (RF) and extreme gradient boosting (XGBoost), to predict these three physical frailty assessment models. Questionnaires regarding demographic characteristics, lifestyle habits, living environment, and physical frailty assessment were answered by 445 participants aged 60 years and above. The RF and XGBoost algorithms were used to assess their scores for the three physical frailty indices. Furthermore, feature importance and Shapley additive explanations (SHAP) were used to determine the important physical frailty factors. The XGBoost algorithm obtained higher accuracy for predicting the three physical frailty indices; the areas under the curve obtained by the XGBoost algorithm for the 5-Item FRAIL, CHS, and SOF indices were 0.84. 0.79, and 0.69, respectively. The feature importance and SHAP of the XGBoost algorithm revealed that systolic blood pressure, diastolic blood pressure, age, and body mass index play important roles in all three physical frailty models. The XGBoost algorithm has a more accurate predictive rate than RF across all three physical frailty assessments. Thus, ML can be a useful tool for the early detection of physical frailty.

Modelling Time to Recovery from Multidrug Resistant Tuberculosis in Southern Ethiopia

Introduction: Multidrug resistant tuberculosis (MDR-TB) is a global heath threat, resistant to key anti-TB drugs. It is ranked among the top 10 causes of death worldwide. Therefore, the current study investigated time to recovery from MDR-TB in southern Ethiopia. Data, Materials and Methods: Restrospective data from selected hospitals in SNNPR (January 2016 to December 2021) were analyzed. A cluster sample of 301 MDR-TB patients (131 NEMMCH, 121 BH, 49 AGH) was considered. Results: Among the 301 cases, 116 (38.5%) were censored. While 185 (61.5%) were recovered. Parametric shared frailty models were employed to account unobserved heterogeneity among the Hospitals and patients and AFT models were employed. the median recovery time of MDR-TB is 22 months. The clustering effect of frailty model was hospitals. Weibull-gamma shared frailty model was appropriate for this data. Conclusion: The final model showed that males have higher recovery rates than females. Extra pulmonary MDR-TB and Urban residency correleted with longer recovery times. The recovery rate increases with increasing baseline weight, education level, and occupation. But, the recovery rate decreases with smoking, co-morbidities, previous drug history, history of TB, and alcohol use Recommendation: All concerned bodies should be cognizant on the risk factors of MDR-TB in SNNP region By providing on early case detection and appropriate treatment of drug-susceptible MDR-TB, since it is essential to shorten the recovery time of MDR-TB patients in line with WHO guidelines

Cerebrospinal fluid proteomic profile of frailty: Results from the PROLIPHYC cohort.

Frailty is a clinical state reflecting a decrease in physiological reserve capacities, known to affect numerous biological pathways and is associated with health issues, including neurodegenerative diseases. However, how global protein expression is affected in the central nervous system in frail subject remains underexplored. In this post hoc cross-sectional biomarker analysis, we included 90 adults (52-85 years) suspected of normal pressure hydrocephalus (NPH) and presenting with markers of neurodegenerative diseases. We investigated the human proteomic profile of cerebrospinal fluid associated with frailty defined by an established cumulated frailty index (FI, average = 0.32), not enriched for neurology clinical features. Using a label-free quantitative proteomic approach, we identified and quantified 999 proteins of which 13 were positively associated with frailty. Pathway analysis with the top positively frailty-associated proteins revealed enrichment for proteins related to inflammation and immune response. Among the 60 proteins negatively associated with frailty, functional pathways enriched included neurogenesis, synaptogenesis and neuronal guidance. We constructed a frailty prediction model using ridge regression with 932 standardized proteins. Our results showed that the "proteomic model" could become an equivalent predictor of FI in order to study chronological age. This study represents the first comprehensive exploration of the proteomic profile of frailty within cerebrospinal fluid. It sheds light on the physiopathology of frailty, particularly highlighting processes of neuroinflammation and inhibition of neurogenesis. Our findings unveil a range of biological mechanisms that are dysregulated in frailty, in NPH subjects at risk of neurodegenerative impairment, offering new perspectives on frailty phenotyping and prediction.

Accelerated failure time frailty model for modeling multiple systems subject to minimal repair

AbstractThis article presents accelerated failure time models with and without frailty for modeling multiple systems subject to minimal repair. The study considers the conventional accelerated failure time model, the accelerated failure time model with Gamma frailty, and proposes the accelerated failure time model with weighted Lindley frailty, which has attractive properties such as a closed‐form Laplace transform. The proposed model extends the accelerated failure time model with the intensity function of a power law process. It retains the direct physical interpretation of the original accelerated failure time model, in which the role of covariates is to accelerate or decelerate the time to each repair. This framework includes parametric approaches to model fitting, which we consider for estimating the vector of regression parameters under this model and the parameter in the baseline intensity functions. The methodology is illustrated with a simulation study and a toy example to demonstrate the applicability of these models in the industrial context.

Comparative Analysis of Women's Breast Cancer Survival Time at Three Selected Government Referral Hospitals in Ethiopia's Amhara Region Using Parametric Shared Frailty Models.

One in five people will eventually develop cancer, and one in eleven women will lose their lives to the disease. The main aim of this study is to determinants of survival time of women with breast cancer using appropriate Frailty models. A study involving 632 Ethiopian women with breast cancer was conducted between 2018 and 2020, utilizing medical records from Felege-Hiwot Referral Hospital, the University of Gondar, and Dessie Referral Hospital. To compare survival, the Kaplan-Meier plot (s) and Log rank test were employed; to assess mean survival, one-way analysis of variance and the t test were utilized. The factors influencing women's survival times from breast cancer were identified using the parametric shared frailty model and the accelerated failure time model. The median time to die for breast cancer patients treated at FHRH, UoGCSH, and DRH was 14.91 months, 11.14 months, and 12.32 months, respectively. The parametric model of shared frailty fit those who were statistically significant in univariate analysis. The results showed that survival of women with breast cancer was significantly influenced by age, tumor size, comorbidity, nodal status, stage, histologic grade, and type of primary treatment initiated. When comparing mean survival times between hospitals, the results showed a significant difference; patients who were treated in FHRH live significantly longer than patients treated in UoGCSH and DRH, whereas patients treated in UoGCSH have comparatively lower survival. Women with stage IV and comorbidities have 22.4% and 27.1% shorter expected survival, respectively. This finding suggests that improving the availability and accessibility of radiation therapy and surgery, eliminating disparities between hospitals, raising awareness of early signs and symptoms of breast cancer and encouraging women to seek clinical help, and highlighting women with comorbidities at diagnosis are important ways to increase survival time.

Time to first birth and its predictors among reproductive-age women in Ethiopia: multilevel analysis using shared frailty model

ObjectiveTo determine the time to first birth and its predictors among reproductive-age women in Ethiopia.Design, setting and participantsNationwide secondary data analysis using mini Ethiopian Demographic and Health Survey, 2019. A...

P158 Cutaneous vasculitis in systemic lupus erythematosus: trends of incidence and risk factors

Abstract Background/Aims Cutaneous vasculitis (CV) is the most common form of vasculitis observed in patients with SLE; however, the precise epidemiological trends and underlying risk factors remain uncertain. The aim of this study was to define the incidence, prevalence, and risk factors of CV in systemic lupus erythematosus (SLE) patients over a period of 20 years. Methods The Birmingham Lupus Cohort is a longitudinal observational cohort of patients with SLE. All patients fulfilled the 1997 ACR Updated Classification Criteria for SLE. Inception patients were recruited within three years of their fourth ACR criterion. Disease activity was assessed using the classic BILAG index and laboratory results recorded. The BILAG vascular domain was used to determine the incidence rate, which refers to the rate at which new cases of minor and major CV attributed to active SLE occur. Cox proportional hazards frailty models were developed to identify clinical and laboratory variables associated with development of CV. Results We analysed 392 patients, of whom 375 (92.5%) were females. There were 213 (55.0%) White, 72 (18.6%) African-Caribbean, 82 (21.1%) South Asian, 9 (2.3%) East Asian, and 11 (2.8%) other ethnicities. The median (IQR) age at enrolment was 33 (26 - 44) years and the median duration of follow up was 9.2 (5.1 - 14.7) years. The incidence rates of minor and major CV were reported in Table 1. In Cox proportional hazards models, there was a positive association between CV and discoid rash (hazard ratio [HR] 2.16 [95% CI: 1.01, 4.61]), Raynaud’s phenomenon (HR 5.67 [95% CI: 4.11, 7.81]), livedo reticularis (HR = 4.69 [95% CI: 1.83, 12.0]), arthritis (HR 3.02 [95% CI: 2.20, 4.15]), renal involvement (OR 2.40 [95% CI: 1.55, 3.71]), haematological involvement (HR = 2.46 [95% CI: 1.80, 3.36]), and Afro-Caribbean descent (HR 1.96 [95% CI: 1.03, 3.74]). In addition, CV was positively associated with anti-dsDNA (HR = 2.33 [95% CI: 1.67, 3.27]), low C3 or C4 (HR 2.29 [95% CI: 2.18, 4.10]), and history of anti-Ro or anti-La (HR = 1.92 [95% CI: 1.15, 3.21]). Conclusion The incidence rates of CV decrease over the duration of follow-up and are associated with defined clinical and serological features. Disclosure A. Saleh: Grants/research support; A.S. is a sponsored PhD student by the Egyptian ministry of higher education represented by The Egyptian Bureau for Cultural &amp; Educational Affairs in London. C. Gordon: None. J. Reynolds: None.

The quasi-xgamma frailty model with survival analysis under heterogeneity problem, validation testing, and risk analysis for emergency care data.

Frailty models are important for survival data because they allow for the possibility of unobserved heterogeneity problem. The problem of heterogeneity can be existed due to a variety of factors, such as genetic predisposition, environmental factors, or lifestyle choices. Frailty models can help to identify these factors and to better understand their impact on survival. In this study, we suggest a novel quasi xgamma frailty (QXg-F) model for the survival analysis. In this work, the test of Rao-Robson and Nikulin is employed to test the validity and suitability of the probabilistic model, we examine the distribution's properties and evaluate its performance in comparison with many relevant cox-frailty models. To show how well the QXg-F model captures heterogeneity and enhances model fit, we use simulation studies and real data applications, including a fresh dataset gathered from an emergency hospital in Algeria. According to our research, the QXg-F model is a viable replacement for the current frailty modeling distributions and has the potential to improve the precision of survival analyses in a number of different sectors, including emergency care. Moreover, testing the ability and the importance of the new QXg-F model in insurance is investigated using simulations via different methods and application to insurance data.

Comorbidities affecting re-admission and survival in COVID-19: Application of joint frailty model.

One of the common concerns of healthcare systems is the potential for re-admission of COVID-19 patients. In addition to adding costs to the healthcare system, re-admissions also endanger patient safety. Recognizing the factors that influence re-admission, can help provide appropriate and optimal health care. The aim of this study was to assess comorbidities that affect re-admission and survival in COVID-19 patients using a joint frailty model. This historical cohort study was done using data of patients with COVID-19 who were re-hospitalized more than twice in a referral hospital in North of Iran. We used the joint frailty model to investigate prognostic factors of survival and recurrence, simultaneously using R version 3.5.1 (library "frailtypack"). P-values less than 0.05 were considered as statistically significant. A total of 112 patients with mean (SD) age of 63.76 (14.58) years old were recruited into the study. Forty-eight (42.9%) patients died in which 53.83% of them were re-admitted for a second time. Using adjusted joint model, the hazard of re-admission increased with cancer (Hazard ratio (HR) = 1.92) and hyperlipidemia (HR = 1.22). Furthermore, the hazard of death increased with hyperlipidemia (HR = 4.05) followed by age (HR = 1.76) and cancer (HR = 1.64). It Also decreased with lung disease (HR = 0.11), hypothyroidism (HR = 0.32), and hypertension (HR = 0.97). Considering the correlation between re-admission and mortality in the joint frailty model, malignancy and hyperlipidemia increased the risk of both re-admission and mortality. Moreover, lung disease probably due to the use of corticosteroids, was a protective factor against both mortality and re-admission.