Kellee Parker, Mallorie Heneghan, Qian W Li, Ann Brunson, Judy Ou, Heydon K Kaddas, Renata Abrahão, Jessica Chubak, Karen J Wernli, Brad Zebrack, Erin E Hahn, Lawrence H Kushi, Hazel B Nichols, Theresa Keegan, Anne C Kirchhoff
{"title":"Identifying clustering in patterns of late effects among survivors of adolescent and young adult hodgkin lymphoma.","authors":"Kellee Parker, Mallorie Heneghan, Qian W Li, Ann Brunson, Judy Ou, Heydon K Kaddas, Renata Abrahão, Jessica Chubak, Karen J Wernli, Brad Zebrack, Erin E Hahn, Lawrence H Kushi, Hazel B Nichols, Theresa Keegan, Anne C Kirchhoff","doi":"10.1093/jncics/pkaf094","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>We examined late effects clustering among adolescent and young adult (AYA; age 15-39 years at diagnosis) Hodgkin Lymphoma (HL) survivors and identified characteristics associated with each cluster.</p><p><strong>Methods: </strong>We included AYAs with HL in 2006-2018 from the California and Utah Cancer Registries linked to statewide hospitalization, emergency department, and ambulatory surgery visit data. We identified severe late effects >2 years after cancer diagnosis in nine late effects categories. Latent class analysis (LCA) was used to identify late effects clusters. Multinomial logistic regression models estimated adjusted associations of demographic and treatment characteristics with LCA late effect group.</p><p><strong>Results: </strong>We identified 4,635 AYA HL survivors with median follow-up of 8.2 years and four late effects groups: 77.1% had a low probability of any late effect (Low Morbidity), 12.8% had high probability of Thyroid disorders, 8.0% had high probability of Cardiovascular Disease (CVD), and 2.1% had high probability of Multiple Conditions (CVD, diabetes/pancreatic, thyroid, and renal diseases). Publicly insured AYAs were more likely than those with private insurance to be in the CVD (OR = 1.53, 95%CI = 1.18-1.98) and Multiple Conditions (OR = 2.17, 95%CI = 1.29-3.66) than the Low Morbidity group. AYAs with radiation were more likely to be in the Multiple Conditions (OR = 2.31, 95%CI = 1.41-3.78) and Thyroid (OR = 2.81, 95%CI = 2.20-3.58) groups. Hematopoietic cell transplantation was associated with Multiple Conditions (OR = 9.50, 95%CI = 5.82-15.50), CVD (OR = 3.82, 95%CI = 2.96-4.93), and Thyroid (OR = 2.86, 95%CI = 2.12-3.85) groups.</p><p><strong>Conclusions: </strong>While most AYA HL survivors were in the Low Morbidity group, those with public insurance or intense treatment may be at higher risk for multiple conditions.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JNCI Cancer Spectrum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jncics/pkaf094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: We examined late effects clustering among adolescent and young adult (AYA; age 15-39 years at diagnosis) Hodgkin Lymphoma (HL) survivors and identified characteristics associated with each cluster.
Methods: We included AYAs with HL in 2006-2018 from the California and Utah Cancer Registries linked to statewide hospitalization, emergency department, and ambulatory surgery visit data. We identified severe late effects >2 years after cancer diagnosis in nine late effects categories. Latent class analysis (LCA) was used to identify late effects clusters. Multinomial logistic regression models estimated adjusted associations of demographic and treatment characteristics with LCA late effect group.
Results: We identified 4,635 AYA HL survivors with median follow-up of 8.2 years and four late effects groups: 77.1% had a low probability of any late effect (Low Morbidity), 12.8% had high probability of Thyroid disorders, 8.0% had high probability of Cardiovascular Disease (CVD), and 2.1% had high probability of Multiple Conditions (CVD, diabetes/pancreatic, thyroid, and renal diseases). Publicly insured AYAs were more likely than those with private insurance to be in the CVD (OR = 1.53, 95%CI = 1.18-1.98) and Multiple Conditions (OR = 2.17, 95%CI = 1.29-3.66) than the Low Morbidity group. AYAs with radiation were more likely to be in the Multiple Conditions (OR = 2.31, 95%CI = 1.41-3.78) and Thyroid (OR = 2.81, 95%CI = 2.20-3.58) groups. Hematopoietic cell transplantation was associated with Multiple Conditions (OR = 9.50, 95%CI = 5.82-15.50), CVD (OR = 3.82, 95%CI = 2.96-4.93), and Thyroid (OR = 2.86, 95%CI = 2.12-3.85) groups.
Conclusions: While most AYA HL survivors were in the Low Morbidity group, those with public insurance or intense treatment may be at higher risk for multiple conditions.