INTRODUCTION: As children complete cancer treatment and enter survivorship, follow-up care is critical to monitor for and treat relapses, secondary malignancies, and late effects of treatment. Relative contributions of cancer and treatment variables and sociodemographic factors in engagement with follow-up care are not fully understood. This study aimed to identify risk factors for inadequate follow-up care. METHODS: The sample included a cohort of 173 children (birth-18 years) diagnosed with cancer in 2004 and treated at a children's hospital. Sociodemographics (gender, patient current age, ethnic minority status, distance from hospital, type of insurance), cancer and treatment variables (patient age at diagnosis, type of cancer, treatment modality, time off treatment, relapse, on clinical trial protocol), and follow-up care through 2009 were gathered via the hospital tumor registry and medical charts. RESULTS: In simultaneous linear regression analysis (full model: F(12, 160) = 3.49, R2 = 0.21, p = 0.001), having a liquid tumor (p < 0.05), presence of relapse (p = 0.009), and shorter distance from hospital (p = 0.006) predicted total number of follow-up visits between completion of treatment and 5 years post-diagnosis. In simultaneous logistic regression analysis (full model: χ2 (12, N = 173) = 53.27, p < 0.001), being male (p = 0.077), having a brain tumor (p = 0.055), longer time off treatment (p = 0.004), and greater distance from hospital (p = 0.003) decreased the likelihood of completing a follow-up or survivorship visit between completion of treatment and 5 years post-diagnosis. In simultaneous linear regression analysis (full model: F(12, 160) = 4.52, R2 = 0.25, p = 0.001), non-White race (p = 0.001) and having public insurance (p = 0.002) predicted total number of no shows between completion of treatment and 5 years post-diagnosis. DISCUSSION/ CONCLUSIONS: These results extend knowledge of health disparities in pediatric cancer follow-up care suggesting that cancer and treatment-related variables (type of cancer, relapse, number of treatment modalities) and sociodemographic factors (distance from treatment center, non-White race, public insurance) are important predictors of engagement in follow-up care. IMPLICATIONS FOR CANCER SURVIVORS: Survivors at risk for poor engagement may benefit from targeted interventions designed to increase likelihood of follow-up care.
INTRODUCTION: As children complete cancer treatment and enter survivorship, follow-up care is critical to monitor for and treat relapses, secondary malignancies, and late effects of treatment. Relative contributions of cancer and treatment variables and sociodemographic factors in engagement with follow-up care are not fully understood. This study aimed to identify risk factors for inadequate follow-up care. METHODS: The sample included a cohort of 173 children (birth-18 years) diagnosed with cancer in 2004 and treated at a children's hospital. Sociodemographics (gender, patient current age, ethnic minority status, distance from hospital, type of insurance), cancer and treatment variables (patient age at diagnosis, type of cancer, treatment modality, time off treatment, relapse, on clinical trial protocol), and follow-up care through 2009 were gathered via the hospital tumor registry and medical charts. RESULTS: In simultaneous linear regression analysis (full model: F(12, 160) = 3.49, R2 = 0.21, p = 0.001), having a liquid tumor (p < 0.05), presence of relapse (p = 0.009), and shorter distance from hospital (p = 0.006) predicted total number of follow-up visits between completion of treatment and 5 years post-diagnosis. In simultaneous logistic regression analysis (full model: χ2 (12, N = 173) = 53.27, p < 0.001), being male (p = 0.077), having a brain tumor (p = 0.055), longer time off treatment (p = 0.004), and greater distance from hospital (p = 0.003) decreased the likelihood of completing a follow-up or survivorship visit between completion of treatment and 5 years post-diagnosis. In simultaneous linear regression analysis (full model: F(12, 160) = 4.52, R2 = 0.25, p = 0.001), non-White race (p = 0.001) and having public insurance (p = 0.002) predicted total number of no shows between completion of treatment and 5 years post-diagnosis. DISCUSSION/ CONCLUSIONS: These results extend knowledge of health disparities in pediatric cancer follow-up care suggesting that cancer and treatment-related variables (type of cancer, relapse, number of treatment modalities) and sociodemographic factors (distance from treatment center, non-White race, public insurance) are important predictors of engagement in follow-up care. IMPLICATIONS FOR CANCER SURVIVORS: Survivors at risk for poor engagement may benefit from targeted interventions designed to increase likelihood of follow-up care.
Authors: Maud M Geenen; Mathilde C Cardous-Ubbink; Leontien C M Kremer; Cor van den Bos; Helena J H van der Pal; Richard C Heinen; Monique W M Jaspers; Caro C E Koning; Foppe Oldenburger; Nelia E Langeveld; Augustinus A M Hart; Piet J M Bakker; Huib N Caron; Flora E van Leeuwen Journal: JAMA Date: 2007-06-27 Impact factor: 56.272
Authors: Wendy L Hobbie; Susan K Ogle; Maureen Reilly; Jill P Ginsberg; Mary Rourke; Sarah Ratcliffe; Janet A Deatrick Journal: J Pediatr Oncol Nurs Date: 2010 Jul-Aug Impact factor: 1.636
Authors: Amanda K Shaw; Lisa Pogany; Kathy N Speechley; Elizabeth Maunsell; Maru Barrera; Leslie S Mery Journal: Cancer Date: 2006-04-15 Impact factor: 6.860
Authors: Elyse R Park; Frederick P Li; Yan Liu; Karen M Emmons; Arthur Ablin; Leslie L Robison; Ann C Mertens Journal: J Clin Oncol Date: 2005-12-20 Impact factor: 50.717
Authors: Kevin C Oeffinger; Ann C Mertens; Charles A Sklar; Toana Kawashima; Melissa M Hudson; Anna T Meadows; Debra L Friedman; Neyssa Marina; Wendy Hobbie; Nina S Kadan-Lottick; Cindy L Schwartz; Wendy Leisenring; Leslie L Robison Journal: N Engl J Med Date: 2006-10-12 Impact factor: 176.079
Authors: Paul C Nathan; Mark L Greenberg; Kirsten K Ness; Melissa M Hudson; Ann C Mertens; Martin C Mahoney; James G Gurney; Sarah S Donaldson; Wendy M Leisenring; Leslie L Robison; Kevin C Oeffinger Journal: J Clin Oncol Date: 2008-09-20 Impact factor: 50.717
Authors: Melissa M Hudson; Ann C Mertens; Yutaka Yasui; Wendy Hobbie; Hegang Chen; James G Gurney; Mark Yeazel; Christopher J Recklitis; Neyssa Marina; Leslie R Robison; Kevin C Oeffinger Journal: JAMA Date: 2003-09-24 Impact factor: 157.335
Authors: J M Vahl; A von Witzleben; C Welke; J Doescher; M N Theodoraki; M Brand; P J Schuler; J Greve; T K Hoffmann; S Laban Journal: Eur Arch Otorhinolaryngol Date: 2021-04-20 Impact factor: 2.503
Authors: Katie A Devine; Adrienne Viola; Peter Capucilli; Olle Jane Z Sahler; Jeffrey R Andolina Journal: J Pediatr Hematol Oncol Date: 2017-04 Impact factor: 1.289
Authors: Alexandra M Psihogios; Helen Pauly-Hubbard; Lisa Schwartz; Jill P Ginsberg; Wendy Hobbie; Dava Szalda Journal: J Cancer Educ Date: 2018-10 Impact factor: 2.037
Authors: Kelley K Hutchins; Süreyya Savaşan; Ronald L Thomas; Laura A Strathdee; Zhihong J Wang; Jeffrey W Taub Journal: J Pediatr Hematol Oncol Date: 2019-01 Impact factor: 1.289
Authors: Alexandra M Psihogios; Lisa A Schwartz; Janet A Deatrick; Elizabeth S Ver Hoeve; Lindsay M Anderson; Elicia C Wartman; Dava Szalda Journal: J Cancer Surviv Date: 2019-07-04 Impact factor: 4.442
Authors: K Reynolds; M Spavor; Y Brandelli; C Kwok; Y Li; M Disciglio; L E Carlson; F Schulte; R Anderson; P Grundy; J Giese-Davis Journal: J Cancer Surviv Date: 2019-06-27 Impact factor: 4.442
Authors: Rebekah H Nagler; Elaine Puleo; Kim Sprunck-Harrild; K Viswanath; Karen M Emmons Journal: Support Care Cancer Date: 2014-04-13 Impact factor: 3.603
Authors: Dava Szalda; Lisa Piece; Lauren Brumley; Yimei Li; Marilyn M Schapira; Monika Wasik; Wendy L Hobbie; Jill P Ginsberg; Lisa A Schwartz Journal: J Adolesc Health Date: 2016-10-27 Impact factor: 5.012