Structured Learning in Time-dependent Cox Models

Cox models with time-dependent coefficients and covariates are widely used in survival analysis. In high-dimensional settings, sparse regularization techniques are employed for variable selection, but existing methods for time-dependent Cox models lack flexibility in enforcing specific sparsity patterns (i.e., covariate structures). We propose a flexible framework for variable selection in time-dependent Cox models, accommodating complex selection rules. Our method can adapt to arbitrary grouping structures, including interaction selection, temporal, spatial, tree, and directed acyclic graph structures. It achieves accurate estimation with low false alarm rates. We develop the sox package, implementing a network flow algorithm for efficiently solving models with complex covariate structures. Sox offers a user-friendly interface for specifying grouping structures and delivers fast computation. Through examples, including a case study on identifying predictors of time to all-cause death in atrial fibrillation patients, we demonstrate the practical application of our method with specific selection rules.Comment: 49 pages (with 19 pages of appendix),9 tables, 3 figure

Conducting gender-based analysis of existing databases when self-reported gender data are unavailable: the GENDER Index in a working population

Objectives Growing attention has been given to considering sex and gender in health research. However, this remains a challenge in the context of retrospective studies where self-reported gender measures are often unavailable. This study aimed to create and validate a composite gender index using data from the Canadian Community Health Survey (CCHS). Methods According to scientific literature and expert opinion, the GENDER Index was built using several variables available in the CCHS and deemed to be gender-related (e.g., occupation, receiving child support, number of working hours). Among workers aged 18–50 years who had no missing data for our variables of interest (n = 29,470 participants), propensity scores were derived from a logistic regression model that included gender-related variables as covariates and where biological sex served as the dependent variable. Construct validity of propensity scores (GENDER Index scores) were then examined. Results When looking at the distribution of the GENDER Index scores in males and females, they appeared related but partly independent. Differences in the proportion of females appeared between groups categorized according to the GENDER Index scores tertiles (p < 0.0001). Construct validity was also examined through associations between the GENDER Index scores and gender-related variables identified a priori such as choosing/avoiding certain foods because of weight concerns (p < 0.0001), caring for children as the most important thing contributing to stress (p = 0.0309), and ability to handle unexpected/difficult problems (p = 0.0375). Conclusion The GENDER Index could be useful to enhance the capacity of researchers using CCHS data to conduct gender-based analysis among populations of workers

Outpatient Nephrotoxic Medication Prescription after Pediatric Intensive Care Acute Kidney Injury

Background: Nephrotoxic medication (NTM) avoidance may prevent further kidney damage in children with acute kidney injury (AKI). We compared outpatient NTM prescriptions in children with or without AKI during pediatric intensive care (PICU) hospitalization. We hypothesize that children with AKI are prescribed NTMs at the same rate as those without it. Methods: This was a retrospective administrative data study of children &lt;18 years, admitted to two PICUs in Montreal, Canada, from 2003 to 2005, with ≥30 days of provincial drug coverage. We evaluated the presence of ≥3 outpatient NTM prescriptions during the first year and 5 years after PICU discharge. Results: Of 970 children, 23% had PICU AKI. In the 1st–5th years after discharge, 18% AKI vs. 10% non-AKI and 13% AKI vs. 4% non-AKI patients received ≥3 NTM prescriptions, respectively. There was no association between PICU AKI and prescription of ≥3 NTMs during the first year (adjusted RR 1.02 [95% CI 0.95–1.10]) nor in the first 5 years post-discharge (adjusted RR 1.04 [95%CI 0.96–1.12]). Conclusions: By offering a better understanding of the current state of outpatient NTM prescription to children with AKI, our study is a step toward considering strategies such as knowledge translation interventions for decreasing NTM exposure and improving outcomes in children with AKI

Association between cardiovascular diseases and dementia among various age groups: a population-based cohort study in older adults

Abstract The link between cardiovascular (CV) risk factors or diseases and dementia is documented. There is conflicting evidence whether age moderates the association. We need to study this gap so that research and clinical initiatives target appropriate age groups. A cohort of 320,630 adult patients without dementia was built using Quebec healthcare databases (1998–2010). The CV risk factors were hypertension, diabetes and dyslipidemia, while diseases included stroke, myocardial infarction (MI), chronic heart failure (HF), and atrial fibrillation (AF). Dementia risk and CV risk factors or diseases were assessed using incidence rate ratios and Cox regression across age groups. The cohort presented by mainly female sex (67.7%) and mean age of 74.1 years. Incident rate of dementia increased with age, ranging from 4.1 to 93.5 per 1000 person-years. Diabetes, stroke, HF and AF were significantly associated with dementia risk, hazard ratios ranged from 1.08 to 3.54. The strength of association decreased in advanced age for diabetes, stroke and HF. The results suggest that prevention of diabetes, stroke, HF and AF are crucial to mitigate dementia risk. The pathophysiology of dementia in younger and older populations seems to differ, with less impact of CV risk factors in advanced age