Marginal semiparametric accelerated failure time cure model for clustered survival data.

The semiparametric accelerated failure time mixture cure model is an appealing alternative to the proportional hazards mixture cure model in analyzing failure time data with long-term survivors. However, this model was only proposed for independent survival data and it has not been extended to clustered or correlated survival data, partly due to the complexity of the estimation method for the model. In this paper, we consider a marginal semiparametric accelerated failure time mixture cure model for clustered right-censored failure time data with a potential cure fraction.

A New Approach to Modeling the Cure Rate in the Presence of Interval Censored Data.

We consider interval censored data with a cured subgroup that arises from longitudinal followup studies with a heterogeneous population where a certain proportion of subjects is not susceptible to the event of interest. We propose a two component mixture cure model, where the first component describing the probability of cure is modeled by a support vector machine-based approach and the second component describing the survival distribution of the uncured group is modeled by a proportional hazard structure. Our proposed model provides flexibility in capturing complex effects of covariates on the probability of cure unlike the traditional models that rely on modeling the cure probability using a generalized linear model with a known link function.

A Frailty Index to Predict Mortality, Resource Utilization and Costs in Patients Undergoing Coronary Artery Bypass Graft Surgery in Ontario.

Background: People living with frailty are vulnerable to poor outcomes and incur higher health care costs after coronary artery bypass graft (CABG) surgery. Frailty-defining instruments for population-level research in the CABG setting have not been established. The objectives of the study were to develop a preoperative frailty index for CABG (pFI-C) surgery using Ontario administrative data; assess pFI-C suitability in predicting clinical and economic outcomes; and compare pFI-C predictive capabilities with other indices.

A support vector machine-based cure rate model for interval censored data.

The mixture cure rate model is the most commonly used cure rate model in the literature. In the context of mixture cure rate model, the standard approach to model the effect of covariates on the cured or uncured probability is to use a logistic function. This readily implies that the boundary classifying the cured and uncured subjects is linear.

Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial intelligence (AI) image analysis workflow for automated detection of PTEN loss on digital images for identifying patients at risk of early recurrence and metastasis. Postsurgical tissue microarray sections from the Canary Foundation (n = 1264) stained with anti-PTEN antibody were evaluated independently by pathologist conventional visual scoring (cPTEN) and an automated AI-based image analysis pipeline (AI-PTEN).

Improving marginal hazard ratio estimation using quadratic inference functions.

Clustered and multivariate failure time data are commonly encountered in biomedical studies and a marginal regression approach is often employed to identify the potential risk factors of a failure. We consider a semiparametric marginal Cox proportional hazards model for right-censored survival data with potential correlation. We propose to use a quadratic inference function method based on the generalized method of moments to obtain the optimal hazard ratio estimators.

Mean residual life cure models for right-censored data with and without length-biased sampling.

We propose a semiparametric mean residual life mixture cure model for right-censored survival data with a cured fraction. The model employs the proportional mean residual life model to describe the effects of covariates on the mean residual time of uncured subjects and the logistic regression model to describe the effects of covariates on the cure rate. We develop estimating equations to estimate the proposed cure model for the right-censored data with and without length-biased sampling, the latter is often found in prevalent cohort studies.

Measures of explained variation under the mixture cure model for survival data.

Explained variation is well understood under linear regression models and has been extended to models for survival data. In this article, we consider the mixture cure models. We propose two approaches to define explained variation under the mixture cure models, one based on the Kullback-Leibler information gain and the other based on residual sum of squares.

Mode of conception and risk of spontaneous vs. provider-initiated preterm birth: population-based cohort study.

Objective: To study the association between mode of conception and risk of preterm birth, including, spontaneous and provider-initiated subtypes.

Design: Population-based retrospective cohort study.

Setting: Not applicable.

Bystander-initiated cardiopulmonary resuscitation and automated external defibrillator use after out-of-hospital cardiac arrest: Uncovering disparities in care and survival across the urban-rural spectrum.

Aim: To evaluate the association between bystander cardiopulmonary resuscitation (CPR), automated external defibrillator (AED) use, and survival after out-of-hospital cardiac arrest (OHCA) across the urban-rural spectrum.

Methods: This was a retrospective cohort study of 325,477 adult OHCAs within the Cardiac Arrest Registry to Enhance Survival from 2013 to 2019. Bystander interventions were categorized into no bystander intervention, bystander CPR alone, and bystander AED use (with or without CPR).

An additive hazards frailty model with semi-varying coefficients.

Proportional hazards frailty models have been extensively investigated and used to analyze clustered and recurrent failure times data. However, the proportional hazards assumption in the models may not always hold in practice. In this paper, we propose an additive hazards frailty model with semi-varying coefficients, which allows some covariate effects to be time-invariant while other covariate effects to be time-varying.

Maximum likelihood estimation for length-biased and interval-censored data with a nonsusceptible fraction.

Left-truncated data are often encountered in epidemiological cohort studies, where individuals are recruited according to a certain cross-sectional sampling criterion. Length-biased data, a special case of left-truncated data, assume that the incidence of the initial event follows a homogeneous Poisson process. In this article, we consider an analysis of length-biased and interval-censored data with a nonsusceptible fraction.

Mental Health Resource Use Among Patients Undergoing Curative Intent Treatment for Bladder Cancer.

Background: Patients with bladder cancer may experience mental health distress. Mental health-care service (MHS) use can quantify the magnitude of the problem.

Methods: The Ontario Cancer Registry was used to identify all patients with bladder cancer treated with curative-intent cystectomy or radiotherapy in Ontario, Canada (2004-2013).

Prescription opioid characteristics at initiation for non-cancer pain and risk of treated opioid use disorder: A population-based study.

Background: Long-term prescription opioid use has been associated with adverse health outcomes, including opioid use disorder (OUD). We examined a population of opioid naïve individuals who initiated prescription opioids for non-cancer pain and investigated the associations between opioid prescription characteristics at initiation and time to treated OUD.

Methods: We conducted a retrospective population-based cohort study in Ontario, Canada among opioid naïve individuals aged 15 years and older dispensed an opioid for non-cancer pain between 2013 and 2016.

Long-Term Mental Health Service Utilization Among Survivors of Testicular Cancer: A Population-Based Cohort Study.

Purpose: Testicular cancer survivors may experience mental illness as a consequence of their cancer diagnosis and treatment.

Methods: All incident cases of testicular cancer treated with orchiectomy in Ontario, Canada (2000-2010), were identified using the Ontario Cancer Registry. Cases were matched to controls in a 1:5 ratio on age and geography.

Joint analysis of longitudinal measurements and survival times with a cure fraction based on partly linear mixed and semiparametric cure models.

In a joint analysis of longitudinal quality of life (QoL) scores and relapse-free survival (RFS) times from a clinical trial on early breast cancer conducted by the Canadian Cancer Trials Group, we observed a complicated trajectory of QoL scores and existence of long-term survivors. Motivated by this observation, we proposed in this paper a flexible joint model for the longitudinal measurements and survival times. A partly linear mixed effect model is used to capture the complicated but smooth trajectory of longitudinal measurements and approximated by B-splines and a semiparametric mixture cure model with the B-spline baseline hazard to model survival times with a cure fraction.

A threshold linear mixed model for identification of treatment-sensitive subsets in a clinical trial based on longitudinal outcomes and a continuous covariate.

Identification of a subset of patients who may be sensitive to a specific treatment is an important problem in clinical trials. In this paper, we consider the case where the treatment effect is measured by longitudinal outcomes, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. A threshold linear mixed model is introduced, and a smoothing maximum likelihood method is proposed to obtain the estimation of the parameters in the model.

Risk Stratification of Prostate Cancer Through Quantitative Assessment of PTEN Loss (qPTEN).

Background: Phosphatase and tensin homolog (PTEN) loss has long been associated with adverse findings in early prostate cancer. Studies to date have yet to employ quantitative methods (qPTEN) for measuring of prognostically relevant amounts of PTEN loss in postsurgical settings and demonstrate its clinical application.

Methods: PTEN protein levels were measured by immunohistochemistry in radical prostatectomy samples from training (n = 410) and validation (n = 272) cohorts.

Variable selection via penalized generalized estimating equations for a marginal survival model.

Clustered and multivariate survival times, such as times to recurrent events, commonly arise in biomedical and health research, and marginal survival models are often used to model such data. When a large number of predictors are available, variable selection is always an important issue when modeling such data with a survival model. We consider a Cox's proportional hazards model for a marginal survival model.

Investigating the diagnostic capacity of uric acid in the occurrence of preeclampsia.

Objectives: To compare the distribution of uric acid (UA) concentration in women with normal and preeclamptic pregnancy, to investigate the significance of UA concentration in diagnosis of preeclampsia, and to estimate the UA rate of change over time before delivery.

Study Design: A case-control study of singleton pregnancies was completed at a tertiary care center in Kingston, Ontario. Patients with preeclampsia were recruited through two prospective cohort studies (n = 218); the Preeclampsia New Emerging Team (September 2003-October 2009) and the Maternal Health Clinic (May 2011-June 2016).

Region-specific glucocorticoid receptor promoter methylation has both positive and negative prognostic value in patients with estrogen receptor-positive breast cancer.

Background: The glucocorticoid receptor (NR3C1, GR) is frequently downregulated in breast tumors, and evidence suggests it acts as a tumor suppressor in estrogen receptor-positive (ER+) breast cancer. We previously found that methylation of the GR promoter CpG island represses gene expression and occurs in ER+ breast tumors. In this study, the prognostic and predictive value of GR methylation was examined in ER+ patients from the CCTG MA.

Estimating the optimal perioperative chemotherapy utilization rate for muscle-invasive bladder cancer.

Background: Identifying optimal chemotherapy (CT) utilization rates can drive improvements in quality of care. We report a benchmarking approach to estimate the optimal rate of perioperative CT for muscle-invasive bladder cancer (MIBC).

Methods: The Ontario Cancer Registry and linked treated records were used to identify neoadjuvant and adjuvant CT rates among patients with MIBC during 2004-2013.