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

Abstract

Research 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.

Dynamic assessment of venous thromboembolism risk in patients with cancer by longitudinal D‐Dimer analysis: A prospective study

“…Seven limitations of our study should be discussed. First, although we analyzed one of the strongest known risk factors for cancer‐associated VTE (D‐Dimer), it is reasonable to assume that other static and dynamic factors such as type of chemotherapy, intercurrent infections or invasive diagnostic procedures, and cancer remission status will further modify VTE risk in a dynamic fashion 35,36 . Moreover, it can be reasonably speculated that these and potentially also other unmeasured risk factors may not only modify VTE risk but also the D‐dimer trajectory.…”

Dynamics of D‐dimer in non‐small cell lung cancer patients receiving radical surgery and its association with postoperative venous thromboembolism

“…Indeed, to extend the following timeline, other dynamic risk factors may reasonably impact on D-dimer concentration and modify VTE risk. 44 Ongoing prospective research aims to assess the risk profile by adopting a wider range of biomarkers and track their changes, in combination with other clinical risk factors in order to create a risk stratification tool employing simple biomarkers to provide an appropriate thromboprophylaxis strategy for NSCLC patients after commencing antitumor treatment. 45 Actually, incorporating follow-up research would include more patients who received adjuvant therapy with more complete tracking of VTE development in the full process of treatment, which is a further step for us.…”

Second-line treatment in advanced gastric cancer: Data from the Spanish AGAMENON registry

“…The patient population assessed derive from the Spanish AGAMENON registry that enlists the collaboration of 34 Spanish hospitals and one center in Chile and recruits consecutive cases of unresectable or metastatic, locally advanced adenocarcinoma of the stomach, gastroesophageal junction, or distal esophagus [31][32][33][34][35][36][37][38][39].…”