Causal Latent Class Analysis with Distal Outcomes: A Modified Three-Step Method Using Inverse Propensity Weighting.

Bias-adjusted three-step latent class (LC) analysis is a popular technique for estimating the relationship between LC membership and distal outcomes. Since it is impossible to randomize LC membership, causal inference techniques are needed to estimate causal effects leveraging observational data. This paper proposes two novel strategies that make use of propensity scores to estimate the causal effect of LC membership on a distal outcome variable.

Need for numbers: assessing cancer survivors' needs for personalized and generic statistical information.

Background: Statistical information (e.g., on long-term survival or side effects) may be valuable for healthcare providers to share with their patients to facilitate shared decision making on treatment options.

The association of circadian parameters and the clustering of fatigue, depression, and sleep problems in breast cancer survivors: a latent class analysis.

Purpose: Circadian rhythms control a wide range of physiological processes and may be associated with fatigue, depression, and sleep problems. We aimed to identify subgroups of breast cancer survivors based on symptoms of fatigue, insomnia, and depression; and assess whether circadian parameters (i.e.

Prediction of recovery in trauma patients using Latent Markov models.

Purpose: Patients' expectations during recovery after a trauma can affect the recovery. The aim of the present study was to identify different physical recovery trajectories based on Latent Markov Models (LMMs) and predict these recovery states based on individual patient characteristics.

Methods: The data of a cohort of adult trauma patients until the age of 75 years with a length of hospital stay of 3 days and more were derived from the Brabant Injury Outcome Surveillance (BIOS) study.

Communication in decision aids for stage I-III colorectal cancer patients: a systematic review.

Objectives: To assess the communicative quality of colorectal cancer patient decision aids (DAs) about treatment options, the current systematic review was conducted.

Design: Systematic review.

Data Sources: DAs (published between 2006 and 2019) were identified through academic literature (MEDLINE, Embase, CINAHL, Cochrane Library and PsycINFO) and online sources.

Heterogeneity in Quality of Life of Long-Term Colon Cancer Survivors: A Latent Class Analysis of the Population-Based PROFILES Registry.

Background: Long-term colon cancer survivors present heterogeneous health-related quality of life (HRQOL) outcomes. We determined unobserved subgroups (classes) of survivors with similar HRQOL patterns and investigated their stability over time and the association of clinical covariates with these classes.

Materials And Methods: Data from the population-based PROFILES registry were used.