Cancer is the leading cause of disease-related death in the Adolescent and young adult (AYA) population; and though strides have been made in survival of children with cancer, cancer patients diagnosed between 15 and 39 years have not had survival improvement in more than 20 years. Individuals within this population may possess a greater need of particular health services in order to cope with disease. AYA cancer patients may present with co-morbidities that pre-date their cancer treatment and could create challenges for appropriate treatment. Previous studies have demonstrated that co-morbidities can result in increased hospitalizations, difficulties with treatment, high health care costs, reduced quality of life and higher mortality. Although the extent of co-morbidities and their association with poor outcomes have been examined extensively in the adult cancer population, there is little data on children, and even less in the AYA cancer population.

Methods:

In order to determine what co-morbidities exist in the AYA cancer population, we examined the prevalence of co-morbidities in the National Cancer Institute’s Adolescent and Young Adult Health Outcomes and Patient Experience (AYA HOPE) Study, a population-based cohort of AYAs recently diagnosed with cancer. All co-morbidities were abstracted from the medical record at the time of initial diagnosis and during the first course of treatment. We compared the fitness of current co-morbidity indices for chronic conditions (Charlson and National Cancer Institute Index (NCI)) and created an AYA HOPE index that covers more clinically relevant chronic co-morbid conditions in AYA cancer survivors. We examined self-reported services needed or received, and self-reported health status with the count of co-morbidities in the AYA HOPE cohort using the AYA HOPE Index.

Results:

Four hundred and eighty-five patients were eligible for this study; the mean age of diagnoses was 28 years. The prevalence of co-morbidities in the AYA HOPE participants was examined using the Charlson index, the NCI index and the AYA Hope index. For diabetes, HIV/AIDS, hypertension, liver, asthma/respiratory, and rheumatologic/autoimmune, the co-morbidity counts were the same for the three co-morbidity indices. Mental health and obesity/overweight were not included in the Charlson or the NCI indices but included in the AYA HOPE Index. When compared to Charlson and NCI indices, the prevalence of co-morbidities was higher for cardiovascular, endocrine, gastrointestinal and neurologic conditions with the AYA HOPE index. The prevalence of mental health co-morbid conditions was 8.2% within the population, with 17 of the 40 individuals affected (42.5%) reporting a depressive disorder. Also, the prevalence of obesity/overweight conditions was 5.8%. Of the 485 patients examined, 70 (14.4%) had 2 or more co-morbid conditions using the AYA HOPE index, which was much higher than the number of patients determined to have multiple co-morbidities based on the Charlson and NCI indices (4.9% and 2.7%, respectively). Overall, 39.6% of AYA patients responding to the survey 6-14 months after diagnosis reported needing some type of health service with the most common service needed being mental health (25.2%), followed by support group (17.7%). After controlling for significant clinical factors (e.g., cancer site, health status and treatment received) and socio-demographic predictors (e.g., age, sex, race), AYA patients with 2 or more co-morbidities based on the AYA HOPE index had twice the odds of needing mental health services as those with no co-morbidity (OR: 2.00; 95% CI 1.05-3.81). AYA patients with 2 or more co-morbidities were also three times more likely to report their health status as fair/poor (OR: 3.15; 95% CI 1.56-6.37).

Conclusion:

The AYA HOPE index is the first co-morbidity index to be developed specifically for the AYA cancer population. The inclusion of mental health and obesity, and the expansion of neurologic and gastrointestinal categories enhances the predictive ability of the AYA HOPE index and allows for a more accurate picture of the conditions prevalent in this unique population; in doing so, it aids in prediction of common healthcare services that should be directed to this population.

Disclosures

No relevant conflicts of interest to declare.

Author notes

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Asterisk with author names denotes non-ASH members.

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