Multistate Models: Accurate and Dynamic Methods to Improve Predictions of Thrombotic Risk in Patients with Cancer

• DOI: 10.1055/s-0039-1694012
• Publication Date: 2019-08-28T23:49:35Z
• Authors: Alberto Carmona-B...; Paula Jimenez-Fon...; Marcelo Garrido; Ana Custodio; Raquel Hernandez; Alejandra Lacalle; Juana María Cano; Gema Aguado; Eva Martínez de C...; Felipe Alvarez Ma...; Ismael Macias; Laura Visa; Marta Martín Richard; Monserrat Mangas; Manuel Sánchez Cá...; Federico Longo; Leticia Iglesias Rey; Nieves Martínez Lago; Alfonso Martín Ca...; Ana Sánchez; Aitor Azkárate; María Luisa Limón; Carolina Hernánde...; Avinash Ramchandani; Paola Pimentel; Paula Cerdá; Raquel Serrano; Aitziber Gil-Negrete; Miguel Marín; Alicia Hurtado; Rodrigo Sánchez B...; Javier Gallego
• Keywords: multistate models; Adult; Male; 610; time-varying effects; Risk Assessment; Decision Support Techniques; 03 medical and health sciences; 0302 clinical medicine; Fibrinolytic Agents; Predictive Value of Tests; Risk Factors; Stomach Neoplasms; Cause of Death; 616; cancer; Humans; Registries; thrombosis; Aged; Retrospective Studies; Aged, 80 and over; flexible models; Incidence; Middle Aged; Progression-Free Survival; 3. Good health; Spain; Disease Progression; Female

AbstractResearch into cancer-associated thrombosis (CAT) entails managing dynamic data that pose an analytical challenge. Thus, methods that assume proportional hazards to investigate prognosis entail a risk of misinterpreting or overlooking key traits or time-varying effects. We examined the AGAMENON registry, which collects data from 2,129 patients with advanced gastric cancer. An accelerated failure time (AFT) multistate model and flexible competing risks regression were used to scrutinize the time-varying effect of CAT, as well as to estimate how covariates dynamically predict cumulative incidence. The AFT model revealed that thrombosis shortened progression-free survival and overall survival with adjusted time ratios of 0.72 and 0.56, respectively. Nevertheless, its prognostic effect was nonproportional and disappeared over time if the subject managed to survive long enough. CAT that occurred later had a more pronounced prognostic effect. In the flexible competing risks model, multiple covariates were seen to have significant time-varying effects on the cumulative incidence of CAT (Khorana score, secondary thromboprophylaxis, high tumor burden, and cisplatin-containing regimen), whereas other predictors exerted a constant effect (signet ring cells and primary thromboprophylaxis). The model that assumes proportional hazards was incapable of capturing the effect of these covariates and predicted the cumulative incidence in a biased way. This study evinces that flexible and multistate models are a useful and innovative method to describe the dynamic effect of variables associated with CAT and should be more widely used.