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Risk stratification of young adult survivors of cancer to estimate hospital morbidity burden: applicability of a pediatric therapy-based approach
- Publication Year :
- 2021
- Publisher :
- Springer, 2021.
-
Abstract
- Purpose Children and young adults (CYA) are at risk of late morbidity following cancer treatment, with risk varying by disease type and treatment received. Risk-stratified levels of aftercare which stratify morbidity burden to inform the intensity of long-term follow-up care, are well established for survivors of cancer under the age of 18 years, utilizing the National Cancer Survivor Initiative (NCSI) approach. We investigated the applicability of risk-stratified levels of aftercare in predicting long-term morbidity in young adults (YA), aged 18–29 years. Methods Long-term CYA survivors followed-up at a regional center in the North of England were risk-stratified by disease and treatments received into one of three levels. These data were linked with local cancer registry and administrative health data (Hospital Episode Statistics), where hospital activity was used as a marker of late morbidity burden. Results Poisson modelling with incident rate ratios (IRR) demonstrated similar trends in hospital activity for childhood (CH) and YA cancer survivors across NCSI risk levels. NCSI levels independently predicted long-term hospitalization risk in both CH and YA survivors. Risk of hospitalization was significantly reduced for levels 1 (CH IRR 0.32 (95% CI 0.26–0.41), YA IRR 0.06 (95% CI 0.01–0.43)) and 2; CH IRR 0.46 (95% CI 0.42-0.50), YA IRR 0.49 (95% CI 0.37-0.50)), compared with level 3. Conclusions The NCSI pediatric late-effects risk stratification system can be effectively and safely applied to cancer patients aged 18–29, independent of ethnicity or socioeconomic position. Implications for Cancer Survivors To enhance quality of care and resource utilization, long-term aftercare of survivors of YA cancer can and should be risk stratified through adoption of approaches such as the NCSI risk-stratification model.
Details
- Language :
- English
- ISSN :
- 19322259
- Database :
- OpenAIRE
- Accession number :
- edsair.core.ac.uk....e7265f1c5de8f47c9184d8ca4cb04c09