The incidence of colorectal cancer (CRC) among young adults has been increasing over the past three decades. Data from the Surveillance, Epidemiology, and End Results registry indicate that the incidence of colon cancer in persons aged 20 to 40 years increased 17% between 1973 and 1999. Moreover, the incidence of rectal cancer in this age group increased 75% over this time period [1, 2]. Due to improvements in disease-specific survival, a large percentage of these patients now survive 5 years or more after diagnosis of CRC . However, these survivors remain at a higher risk for late effects such as late mortality and second cancers. Using the same population-based cohort discussed in this paper, a recent study by Forbes et al. (2010) found young adult survivors of CRC have a significantly higher risk of long-term death than matched controls (HR=8.2, 95% CI (5.8, 11.6)) .
Despite the increasing number of young adult CRC survivors long-term health effects of CRC – a disease frequently requiring multi-modal therapy including surgery, chemotherapy and irradiation – in a young population have not been well studied [1, 3]. In older adults, long-term survivors of CRC are known to have an increased risk of small bowel obstruction [4, 5], and treatment may result in substantial genito-urinary dysfunction [6, 7]. Other disorders, including pelvic fractures  dementia, diabetes and osteoporosis , may also be associated with CRC survival. Although late effects may occur, this has not been well studied in CRC survivors, particularly in comparison to other malignancies, perhaps because of the advanced age of most patients with CRC at diagnosis. Long-term effects of CRC diagnosis and treatment may have a more substantial impact on younger survivors – younger survivors have been found to have worse quality of life and experience more role restrictions than older CRC survivors , and certainly young CRC survivors have a longer potential time span to experience late-effects. .The impact of CRC on hospital admissions, an indicator of significant illness, among young adult survivors compared to the general population is unknown. The risk of hospitalization over time may be greater than in younger CRC patients, however, some late effects associated with hospitalization, such as pelvic fracture after irradiation may be less common in young adults than older survivors who are at higher baseline risk. By comparing rates of hospitalization in long-term survivors and a control population we can assess long-term morbidity due to significant medical illness attributable to CRC and treatment in a group of young survivors. Additionally, higher rates of hospitalizations would imply that this population of CRC survivors has an increasing impact on the Canadian health care system and an increasing demand for hospital services .
Data on repeated hospitalizations over time are often referred to in the statistical literature as recurrent event data. Standard analyses are based on Poisson or negative binomial models – these approaches estimate the rate of hospitalizations by simply modeling each patient’s total number of hospitalizations over their observation period. However if one is interested in taking the timing of each hospitalization into account, then various counting process or gap time models can be adopted. In many cases, a terminal event such as death occurs which precludes the occurrence of future recurrent events. In the models mentioned above, the time of death is often treated as a censoring time, implying that patients are still at risk of experiencing further recurrent events. To overcome this issue a multistate analysis is recommended - it models the terminal event as an absorbing state, since no recurrent events can occur after this point.
Multistate models examine disease processes by describing changes in a patient’s health condition over time . These models classify a patient into one of a finite number of distinct states at any given time during their follow-up . Events correspond to transitions from one state to another, and the event times correspond to the transition times [13, 14]. Recently, multistate models have been extended to examine recurrent event data in which a terminal event may occur [15, 16]. Examples include organ transplant studies where transient graft rejection episodes are terminated by total graft rejection or death , and studies of cancer patients with bone metastases where the occurrence of new metastases is terminated by death . Although multistate methods have been developed under such settings, the application of these models is limited in the epidemiology and clinical literature. This paper’s main objective is to study trends in hospitalizations among a cohort of young adult survivors of colorectal cancer and their matched cancer-free controls using a flexible multistate model.