Early Symptom Warnings and Long-Term Health Conditions in Childhood Cancer Survivors: Insights from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort Study

Early Symptom Warnings and Long-Term Health Conditions in Childhood Cancer Survivors: Insights from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Early Symptom Warnings and Long-Term Health Conditions in Childhood Cancer Survivors: Insights from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort Study I-Chan Huang, Madeline Horan, Wei Liu, Deo Srivastava, Matthew Ehrhardt, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7229897/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Symptom patterns in adult survivors of childhood cancer may signal risk for health deterioration and offer a foundation for risk stratification. 735 survivors completed sequential symptom surveys (T1, T2, T3) and clinical assessment for chronic health conditions (CHCs). Survivors were classified into four clusters: 1) low physical and emotional symptoms, 2) moderate physical and low emotional symptoms, 3) moderate physical and emotional symptoms, and 4) high physical and emotional symptoms. Survivors in cluster 4 vs. cluster 1 had an elevated risk of progressive total CHC burden and vascular, respiratory, neurologic, and musculoskeletal conditions (relative risk [RR] range: 1.24–2.53). Increased/persistently high symptom burden between T1-T2 increased risk for progressive total CHC burden, respiratory, and neurologic conditions (RR range: 1.30–2.23). Increased/persistently high T2-T3 symptom burden showed similar associations (all p’s < 0.05). This proof-of-concept study provides an empirical basis for developing and validating symptom-based prediction models and warning systems to support proactive survivorship care. Biological sciences/Cancer/Paediatric cancer Health sciences/Health care/Prognosis Health sciences/Signs and symptoms Childhood Cancer Chronic Health Conditions Late Effects Patient-Reported Outcomes Survivors Symptom Clusters Figures Figure 1 Figure 2 INTRODUCTION Childhood cancer and its treatment have been associated with a wide range of late effects, 1 , 2 which can adversely impact physical and psychosocial function 3 , 4 and contribute to premature mortality. 5 The St. Jude Lifetime Cohort Study (SJLIFE) found that by age 50 years, adult survivors of childhood cancer experienced an average of 17 chronic health conditions (CHCs), of which 4.7 conditions were severe/disabling, life-threatening, or fatal, based on grades 3–5 of the Common Terminology Criteria for Adverse Events (CTCAE). 6 Screening for and preventing the onset or worsening of CHCs is a primary task of cancer survivorship care. Currently, screening guidelines for childhood cancer survivors largely rely on clinical factors (e.g., cancer diagnosis, treatment history) to address the risk of late effects and inform subsequent follow-up care. 1 , 2 , 7 , 8 This approach is challenging because survivors and their primary care providers may lack detailed knowledge of the survivor’s diagnosis, treatment, and associated risk of late effects. 9 Moreover, this strategy does not consider socio-demographics, lifestyle, or perceived symptoms that may mediate or modify the relationships between cancer treatment and long-term health outcomes. 10 Childhood cancer survivors experience symptoms across multiple domains, including cardiac, pulmonary, and sensory dysfunction, pain, fatigue, and poor memory and attention. Notably, 75% of childhood cancer survivors report multiple co-occurring symptoms, 11 and a greater symptom burden is linked to poorer quality of life (QOL). 11 When symptoms present together, their combined effect may exacerbate QOL impairments, 12 and commonly co-occurring symptoms may reflect shared underlying mechanisms that contribute to greater disease severity. 13 While prior studies have evaluated symptom clusters (defined as patterns of multiple, co-occurring symptoms) in pediatric cancer patients, 14 few have focused on adult survivors of childhood cancer. 12 Furthermore, existing studies are limited by small sample sizes (< 150 survivors) and a cross-sectional design. Expanding this line of research is crucial to guide the development of interventions aimed at reducing the health burden and QOL impairment among survivors with persistent symptom clusters. Patient-reported symptoms, representing the manifestation of health abnormalities, can prompt medical consultation in individuals with and without a cancer history. 15 In adult-onset cancer, symptom reporting during and after therapy has demonstrated independent prognostic value for survival, beyond socio-demographic and clinical factors. 16 Collecting symptom data from this population has been shown to enhance patient-doctor communication, improve QOL, reduce emergency visits, and increase survival. 17 While prognostic models for conditions, such as heart failure, ischemic heart disease/stroke, and hypertension/diabetes, have been developed in pediatric cancer survivors, 18 systematic symptom assessment using standard tools remains underutilized in survivorship care. It is clinically intuitive that symptoms often precede the diagnosis of CHCs and prompt medical attention, yet empirical evidence linking early symptom clusters to subsequent CHC development remains limited. Leveraging comprehensive longitudinal data from two well-characterized survivor cohorts, the SJLIFE and the Childhood Cancer Survivor Study (CCSS), this study examined symptom clusters and their changes over a 25-year period among adult survivors of childhood cancer, in relation to the progression of clinically ascertained CHCs, including new onset, persistent, and worsening conditions, while accounting for treatment history, socio-demographic characteristics, and lifestyle factors. METHODS Study Participants Study participants were adult survivors of childhood cancer from both SJLIFE and CCSS, two retrospective cohort studies with prospective follow-up to characterize the etiology and late effects of childhood cancer. As of December 2020, SJLIFE included over 6,000 survivors of pediatric malignancies diagnosed at St. Jude Children’s Research Hospital (SJCRH) between 1962 and 2012, who returned periodically for clinical assessments. 19 CCSS comprises 25,665 survivors diagnosed and treated at one of 31 institutions in North America, including SJCRH, between 1970 and 1999, and followed through periodic surveys. 5 Approximately 40% of SJLIFE participants also participated in CCSS. Eligible participants were survivors who 1) were aged ≥ 18 years; 2) completed at least three patient-reported outcome (PRO) surveys, including CCSS baseline (T1) and two follow-up (T2, T3) surveys via CCSS and/or SJLIFE; and 3) underwent a SJLIFE clinical assessment after T3. Survivors were excluded if PROs were proxy-reported, unevaluable, or unscored due to missing data. Of the 1,358 survivors participating in both SJLIFE and CCSS who completed the baseline CCSS survey, 595 did not complete surveys at T2 or T3, and 28 had missing data, leaving 735 participants for analyses (Supplementary Figure S1). This study was approved by the SJCRH Institutional Review Board, and all participants provided informed consent. Data Collection Participants self-reported socio-demographics, symptoms, lifestyle behaviors, and health status via online or paper surveys during three time periods: 1994–2012 (T1), 2007–2013 (T2), and 2008–2015 (T3). Clinical data were obtained from clinical assessments conducted during each visit to SJLIFE through 2020, which included medical history review, physical exams, cognitive and functional evaluations, laboratory testing, and organ function evaluations. Symptom Measurement A 37-item symptom survey was administered in both SJLIFE and CCSS, covering 10 domains: cardiac (3 items), respiratory (2 items), musculoskeletal (4 items), nausea (1 item), sensory (8 items), pain (4 items), fatigue (2 items), memory (1 item), anxiety (6 items), and depression (6 items) (Supplementary Table S1). Among 37 items, 19 were developed by CCSS investigators and 18 were adopted from the Brief Symptom Inventory-18. 20 These items align with the Children's Oncology Group Long-Term Follow-Up Guidelines (COG LTFU Guidelines) to assess treatment-related toxicities and have demonstrated sensitivity to treatment exposures. 7 , 8 This symptom measure has been reported in a previous SJLIFE publication 11 , 12 (see Supplementary Table S1 for the content and measurement properties). We used a checklist approach to classify each symptom domain as present if one or more items within that domain were endorsed by survivors. Classification of CHCs CHCs were identified through review of electronic health records (EHRs) for medical history and clinical assessments during SJLIFE visits. The severity of 47 individual CHCs was graded using a modified version of the CTCAE, categorized as none, mild (grade 1), moderate (grade 2), severe/disabling (grade 3), or life-threatening (grade 4) (Supplementary Table S2). 21 Individual CHCs were dichotomized as moderate/severe/life-threatening (grades 2–4) or absent/mild (none or grade 1). These 47 individual CHCs were classified into seven organ system-based groups: cardiac, vascular, respiratory, musculoskeletal, neurologic, endocrine, and reproductive. A given organ system was considered affected if any condition within that group was graded 2–4 in severity. Based on a previous study, 22 all conditions were combined to classify total CHC burden by none/low (all CHCs grade 0 or 1), moderate (one or more grade 2 and/or one grade 3), high (two or more grade 3 or one grade 4), and very high (two or more grade 4 or two or more grade 3 and one grade 4). Socio-demographic and Clinical Information Additional information was obtained from surveys, including age at evaluation, sex, race/ethnicity, educational attainment, marital status, and cigarette smoking status. Detailed cancer therapy data were abstracted from medical records, including cancer diagnosis, age at diagnosis, chemotherapeutic agents, regions of radiotherapy, and major surgical procedures. Statistical Analysis Principal component analysis was conducted separately at T1, T2, and T3 to identify latent factors underlying 10 symptom domains. The number of symptom factors was determined using eigenvalues > 1 and factor loadings > 0.4. Latent profile analysis was conducted using standardized factor scores derived from principal component analysis to identify specific symptom clusters, representing subgroups of survivors with distinct symptom burden patterns at each time point. The optimal number of symptom clusters was determined by lower Bayesian Information Criterion (BIC), a significant Voung-Lo-Mendell-Rubin likelihood ratio test, and higher entropy (see the Results section for the labels of individual symptom clusters). Changes in symptom clusters over time were classified as improved/persistently low symptom burden, persistently moderate symptom burden, or increased/persistently high symptom burden. Changes in CHCs over time were classified as either progression or non-progression (for classification methods, see Supplementary Table S3 for symptom cluster change, and Supplementary Table S4 for CHC progression). Modified Poisson regression was conducted to assess temporal associations across 3 models (Supplementary Figure S2): 1) T1 symptom clusters and progression of total CHC burden (i.e., increased severity or persistently high burden) from pre-T1 to post-T1; 2) changes in symptom clusters from T1-T2 and progression of total CHC burden from T1-T2 to post-T2; and 3) changes in symptom clusters from T2-T3 and progression of total CHC burden from T2-T3 to post-T3. Similar models were employed to evaluate temporal associations between symptom clusters (at T1 and changes in cluster membership) and progressive CHCs (i.e., new onset, persistence, or increased severity) within each organ system group . Models were adjusted for factors known to be associated with symptom presence and CHCs, including age at evaluation, sex, smoking status, and treatment exposures per the COG LTFU Guidelines 7 , 8 (Supplementary Table S2). All analyses were performed using SAS v9.4 (SAS Institute, Cary, NC) and Mplus v8.2 (Muthen & Muthen, Los Angeles, CA), with statistical significance set at two-sided p-value < 0.05. RESULTS Characteristics of Participants Of 735 survivors, approximately 50% were female; 90% were non-Hispanic White; 70% were treated for leukemia or lymphoma (Table 1). The mean (±SD) ages at T1, T2, and T3 survey completion were 27.0 (±5.1), 35.9 (±6.9), and 40.1 (±7.3) years, respectively. Compared with those who did not complete surveys at T2 or T3, survivors included in the analysis were older at cancer diagnosis, and more likely to have received radiotherapy (all p’s <0.05; Supplementary Table S5). Prevalence of Symptom Clusters and Cluster Change Over Time Principal component analysis identified two latent factors across 10 symptom domains at each time point, corresponding to physical-related and psychological-related factors. Based on this two-factor structure, latent profile analysis classified survivors into four consistent symptom clusters across time (Figure 1). The four clusters represented survivors with 4 symptom profiles: low physical and emotional symptoms (42.9-48.4% over time), moderate physical and low emotional symptoms (17.3-19.7%), moderate physical and emotional symptoms (20.8-27.3%), and high physical and emotional symptoms (11.6-12.0%). Survivors with changes in symptom clusters from T1 to T2 and from T2 to T3 were grouped into three categories: improved/persistently low symptom burden (T1 to T2: 53.9%, T2 to T3: 47.3%), persistently moderate symptom burden (T1 to T2: 24.8%, T2 to T3: 28.3%), and increased/persistently high symptom burden (T1 to T2: 21.4%, T2 to T3: 24.4%) (see Supplementary Table S3 for methods in classifying cluster changes). Prevalence and Progression of CHCs The prevalence of total and grades 2-4 CHC burden increased over time across all seven groups (Figure 2). At least moderate total CHC burden was observed in approximately 44% of survivors at T1, 64% at T2, and 81% at T3. Endocrine conditions were the most common individual CHC group, affecting 21% of survivors at T1, 32% at T2, and 41% at T3. Progressive total CHC burden occurred in approximately 25% of survivors from pre-T1 to post-T1, 22% from T1-T2 to post-T2, and 15% from T2-T3 to post-T3. Vascular CHCs exhibited the highest progression rate among individual CHC groups. Temporal Associations of Symptom Clusters at T1 with Progression of CHCs (Model 1) Compared to survivors with low physical and emotional symptoms at T1, those with high physical and emotional symptoms at T1 had a relative risk (RR) of 1.64 (95% CI 1.14-2.36) for progressive total CHC burden from pre-T1 to post-T1. Survivors with moderate physical and low emotional symptoms at T1 had an RR of 1.53 (95% CI 1.14–2.06) for progressive total CHC burden during the same period (Table 2). In contrast, treatment exposures were not significantly associated with the progression of total CHC burden (Supplementary Table S6). By organ system groups, compared to low physical and emotional symptoms at T1, survivors with high physical and emotional symptoms at T1 had a significantly higher risk of progressive CHCs from pre-T1 to post-T1, particularly for neurologic (RR 2.53, 95% CI 1.81-3.53), musculoskeletal (RR 1.91, 95% CI 1.35-2.69), respiratory (RR 1.32, 95% CI 1.04-1.67), and vascular (RR 1.24, 95% CI 1.02-1.52) CHCs (Table 3). Survivors with moderate physical and low emotional symptoms at T1 had a 2.23-, 1.43-, and 1.29-fold increased risk of progressive neurologic, musculoskeletal, and respiratory CHCs, respectively (all p’s <0.05). Specific chemotherapy or radiotherapy exposures were associated with progression of select CHC groups from pre-T1 to post-T1 (Supplementary Table S7). For example, anthracycline exposure was significantly associated with an increased risk of progressive cardiac CHCs (RR 1.49), while neck/chest irradiation was associated with progressive respiratory (RR 2.11) and endocrine (RR 2.16) CHCs (all p’s <0.05). Temporal Associations of Symptom Cluster Change from T1-T2 (Model 2) and from T2-T3 (Model 3) with Progression of CHCs Survivors with increased or persistently high symptom burden between T1-T2 had a 1.63-fold higher risk of progressive total CHC burden (95% CI 1.18-2.26) from T1-T2 to post-T2, while those with a persistently moderate symptom burden had a 1.42-fold higher risk (95% CI 1.03-1.97), compared to those with improved or persistently low symptom burden (Table 2). Changes in symptom burden between T1-T2 were significantly associated with CHC progression from T1-T2 to post-T2 across CHC groups (Table 3). Specifically, survivors with increased/persistently high symptom burden had elevated risks of progressive neurologic (RR 2.23, 95% CI 1.69-2.93) and respiratory (RR 1.30, 95% CI 1.06-1.59) CHCs compared to those with improved/persistently low symptom burden between T1-T2. Additionally, survivors with persistently moderate symptom burden between T1-T2 had a 1.79-fold higher risk (95% CI 1.33-2.40) of progressive neurologic CHCs, compared to those with improved/persistently low symptom burden. Survivors with increased/persistently high symptom burden between T2-T3 had a 2.28-fold (95% CI 1.51-3.45) higher risk of progressive total CHC burden from T2-T3 to post-T3, while those with persistently moderate symptom burden had a 1.66-fold (95% CI 1.07-2.59) higher risk (Table 2). By organ system groups, increased/persistently high symptom burden between T2-T3 was significantly associated with higher risks of progressive neurologic (RR 2.81, 95% CI 2.04-3.87) and respiratory (RR 1.33, 95% CI 1.06-1.68) CHCs from T2-T3 to post-T3. Additionally, survivors with persistently moderate symptom burden during the same period had a 1.74-fold (95% CI 1.21-2.50) higher risk of progressive neurologic CHCs compared to those with improved/persistently low symptom burden. Treatment modalities were not significantly associated with progressive total CHC burden in Models 2 or 3 (Supplementary Table S6). However, certain chemotherapy and radiotherapy exposures were significantly associated with the progression of individual CHC groups (Supplementary Tables S8 and S9). For example, anthracycline exposure was associated with progressive cardiac CHCs post-T3 (RR 1.29), while neck/chest irradiation was associated with progressive respiratory CHCs (RR 2.30) and endocrine CHCs (RR 2.19) post-T3 (all p’s <0.05). DISCUSSION Using 25 years of PRO survey data and clinically ascertained CTCAE-graded CHCs, we provide the first empirical evidence that symptom clusters predict future adverse medical events in childhood cancer survivors. High physical and emotional symptom burden at baseline, as well as increased or persistently high symptom burden over time, were strongly associated with progression of total and specific CHCs. These associations remained significant after adjusting for treatment, socio-demographic, and lifestyle factors. The finding of a high symptom burden preceding CHC progression highlights a critical window for early detection and intervention. Recognizing these associations may enable timely clinical action to prevent complications and reduce healthcare costs. 23 However, current survivorship surveillance often lacks standardized, routine symptom assessment, with cost-effective screening limited to high-risk survivors for specific conditions such as cardiomyopathy or subsequent neoplasms. 24 While symptom tools are widely used during active cancer treatment, 25 , 26 their integration into long-term survivorship care remains uncommon due to persistent implementation barriers. 27 Recent advances in EHR-integrated symptom reporting have now made routine digital monitoring increasingly feasible. 28 Our findings of temporal symptom-CHC associations suggest that incorporating regular symptom assessment between clinic visits could complement existing surveillance strategies, detect early signs of CHC progression, and support timely preventive care. A growing body of evidence reinforces the clinical utility of symptom self-reporting. Observational studies across cancer and non-cancer populations have shown that self-reported symptoms can identify individuals in need of early medical evaluation. 15 Recent randomized trials further demonstrate that embedding symptom tracking in care pathways reduces symptom burden among pediatric cancer patients. 29 Building on symptom assessments recommended in the COG LTFU Guidelines, 7 , 8 our findings support the use of sequential symptom surveys to identify survivors at elevated risk for specific CHCs. Routine symptom monitoring through EHRs may facilitate early CHC detection, improve QOL, and reduce long-term complications. 30 Many symptoms and CHCs are also modifiable through lifestyle interventions, such as improving diet, increasing physical activity, promoting sleep, and reducing stress. 31 , 32 Future research should assess the feasibility, scalability, and economic viability of systematic symptom surveillance in survivorship care, particularly in low-resource settings. For example, comparative studies could investigate whether real-time digital symptom monitoring (e.g., every 6 months) yields better health outcomes than usual care, thereby demonstrating the added value of proactive symptom tracking. 33 The robust prognostic value of symptom burden for subsequent CHC development suggests that some survivors with moderate or high symptom burden may not yet have developed or been diagnosed with CHCs. When symptoms lack an identifiable structural or clinical pathology, they are often classified as “medically unexplained symptoms,” which may stem from cancer-related risk factors or other unknown reasons. These symptoms are linked to poorer QOL 23 and increased risk of depression, 34 highlighting their importance in follow-up care. Using a symptom cluster approach provides a more comprehensive view of the patient’s experience by identifying patterns across multiple co-occurring symptoms, rather than examining isolated or unexplained complaints individually. Identifying symptom clusters associated with CHC progression (e.g., increased or persistently high symptom burden linked to neurologic CHCs) can inform early clinical interventions. For high-risk survivors, integrating palliative care may help address both explained and unexplained symptoms and improve late-effect management. 35 The comparable prognostic value of baseline symptom burden and increasing symptom severity across most CHC groups suggests a shared symptom-based pattern in CHC progression. These findings provide a foundation for investigating the biological mechanisms linking specific symptoms to disease development. CHCs marked by co-occurring symptoms may share genetic risk loci or pathways. 36 Symptom burden signatures could guide the development of individualized diagnostic tools and targeted therapies to better address co-occurring symptoms. Currently, no studies have explored the biological underpinnings of multiple co-occurring symptoms, highlighting a critical gap for future research. 13 Treatment exposures likely precede both biological mechanisms and symptoms in the etiologic pathway, which occur before CHC diagnosis; however, this sequence remains untested and cannot be evaluated with the current data. To advance this line of inquiry, conceptual frameworks are needed to clarify the relationships among cancer treatment exposures, biological mechanisms, symptom clusters, and CHC progression for childhood cancer survivors. 13 Interestingly, exposure to anthracycline agents and neck/chest radiotherapy, rather than baseline symptom burden or severity changes over time, was significantly associated with progressive cardiac conditions. The absence of a symptom-based association may reflect the use of broader measures of symptom burden rather than cardiac-specific symptoms. Previous studies have shown that early-stage cardiac conditions often present with symptoms such as chest pain and dyspnea, 37 and that uncontrolled anxiety and depression are linked to adverse cardiac events in individuals with stable coronary artery disease or heart failure. 38 , 39 This study has several limitations. First, analyses were limited to survivors who completed three symptom surveys. Those who had incomplete symptom survey data or died earlier were excluded, which limits the generalizability to the broader population of adult survivors of childhood cancer. Second, the sample was predominantly white and non-Hispanic, which further restricts the applicability of findings to diverse populations. Third, symptom data were collected only during long-term survivorship (i.e., a mean of 18 years post-diagnosis at T1), excluding symptoms experienced during cancer therapy or earlier phases of survivorship. A subsequent study of young (i.e., 8–18 years of age) survivors of childhood cancer found that 38% reported moderate to high symptom burden early in survivorship. 40 Longitudinal symptom data from diagnosis through post-therapy and across the lifespan are needed to capture symptom evolution and its relationships with CHC progression. Future research should also determine the optimal timing, interval, and frequency for symptom assessment, ideally using systems that trigger alerts to healthcare teams when symptoms exceed predefined clinical thresholds. Lastly, our findings do not establish the predictive validity of symptom data for subsequent adverse medical events. To support risk stratification and targeted intervention for cancer survivors, future research must evaluate the predictive performance of symptom assessments (e.g., accuracy, sensitivity, specificity, predictive values) using training and test datasets, along with standard assessment tools, such as the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). In conclusion, baseline symptom clusters and their changes over time independently link to subsequent CHC development in adult survivors of childhood cancer, beyond treatment exposures and traditional risk factors. Future research should focus on developing, validating, and implementing survivor-reported symptom assessments for risk prediction. Meanwhile, incorporating serial symptom assessments into risk-based follow-up care and clinical guidelines may help identify survivors who are at an elevated risk of late effects. Declarations Funding: Research reported in this publication was supported by the National Cancer Institute under Award Numbers R21CA202210, R01CA238368, R01CA258193, U01CA195547, and U24CA055727. The content is solely the authors' responsibility and does not necessarily represent the official views of the funding agency. Support for St. Jude Children’s Research Hospital was also provided by the Cancer Center Support (CORE) grant (CA21765, C. Roberts, Principal Investigator) and the American Lebanese-Syrian Associated Charities (ALSAC). References Armstrong, G.T. , et al. Aging and risk of severe, disabling, life-threatening, and fatal events in the Childhood Cancer Survivor Study. J Clin Oncol 32 , 1218-1227 (2014). Gibson, T.M. , et al. Temporal patterns in the risk of chronic health conditions in survivors of childhood cancer diagnosed 1970-99: a report from the Childhood Cancer Survivor Study cohort. Lancet Oncol 19 , 1590-1601 (2018). Ness, K.K. , et al. Physical performance limitations in the Childhood Cancer Survivor Study cohort. J Clin Oncol 27 , 2382-2389 (2009). Krull, K.R., Hardy, K.K., Kahalley, L.S., Schuitema, I. & Kesler, S.R. Neurocognitive outcomes and interventions in long-term survivors of childhood cancer. J Clin Oncol 36 , 2181-2189 (2018). Armstrong, G.T. , et al. Reduction in late mortality among 5-year survivors of childhood cancer. N Engl J Med 374 , 833-842 (2016). Bhakta, N. , et al. The cumulative burden of surviving childhood cancer: an initial report from the St Jude Lifetime Cohort Study (SJLIFE). Lancet 390 , 2569-2582 (2017). Landier, W. , et al. Development of risk-based guidelines for pediatric cancer survivors: the Children's Oncology Group Long-Term Follow-Up Guidelines from the Children's Oncology Group Late Effects Committee and Nursing Discipline. J Clin Oncol 22 , 4979-4990 (2004). Hudson, M.M., Bhatia, S., Casillas, J. & Landier, W. Long-term follow-up care for childhood, adolescent, and young adult cancer survivors. Pediatrics 148 , 1-17 (2021). Syed, I.A. , et al. Factors associated with childhood cancer survivors' knowledge about their diagnosis, treatment, and risk for late effects. J Cancer Surviv 10 , 363-374 (2016). Alfano, C.M. , et al. Implementing personalized pathways for cancer follow-up care in the United States: proceedings from an American Cancer Society-American Society of Clinical Oncology summit. CA Cancer J Clin 69 , 234-247 (2019). Huang, I.C. , et al. Association between the prevalence of symptoms and health-related quality of life in adult survivors of childhood cancer: a report from the St. Jude Lifetime Cohort study. J Clin Oncol 31 , 4242-4251 (2013). Shin, H. , et al. Associations of symptom clusters and health outcomes in adult survivors of childhood cancer: a report from the St Jude Lifetime Cohort Study. J Clin Oncol 41 , 497-507 (2023). Miaskowski, C. , et al. Advancing symptom science through symptom cluster research: expert panel proceedings and recommendations. J Natl Cancer Inst 109 , 1-9 (2017). Hooke, M.C. , et al. Symptom clusters, physical activity, and quality of life: a latent class analysis of children during maintenance therapy for leukemia. Cancer Nurs 45 , 113-119 (2022). Jones, R., Latinovic, R., Charlton, J. & Gulliford, M.C. Alarm symptoms in early diagnosis of cancer in primary care: cohort study using General Practice Research Database. BMJ 334 , 1-8 (2007). Mierzynska, J. , et al. Prognostic value of patient-reported outcomes from international randomised clinical trials on cancer: a systematic review. Lancet Oncol 20 , e685-e698 (2019). Basch, E. , et al. Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial. J Clin Oncol 34 , 557-565 (2016). Chen, Y. , et al. Traditional cardiovascular risk factors and individual prediction of cardiovascular events in childhood cancer survivors. J Natl Cancer Inst 112 , 256-265 (2020). Howell, C.R. , et al. Cohort Profile: The St. Jude Lifetime Cohort study (SJLIFE) for paediatric cancer survivors. Int J Epidemiol 50 , 39-49 (2021). Derogatis, L. Brief Symptom Inventory 18: Administration, Scoring, and Procedures Manual , (National Computer Systems, Minneapolis: MN, 2000). Hudson, M.M. , et al. Approach for classification and severity grading of long-term and late-onset health events among childhood cancer survivors in the St. Jude Lifetime Cohort. Cancer Epidemiol Biomarkers Prev 26 , 666-674 (2017). Geenen, M.M. , et al. Medical assessment of adverse health outcomes in long-term survivors of childhood cancer. JAMA 297 , 2705-2715 (2007). Zonneveld, L.N., Sprangers, M.A., Kooiman, C.G., van 't Spijker, A. & Busschbach, J.J. Patients with unexplained physical symptoms have poorer quality of life and higher costs than other patient groups: a cross-sectional study on burden. BMC Health Serv Res 13 , 1-11 (2013). Ehrhardt, M.J. , et al. Cost-effectiveness of the International Late Effects of Childhood Cancer Guideline Harmonization Group screening guidelines to prevent heart failure in survivors of childhood cancer. J Clin Oncol 38 , 3851-3862 (2020). Kluetz, P.G., Chingos, D.T., Basch, E.M. & Mitchell, S.A. Patient-reported outcomes in cancer clinical trials: measuring symptomatic adverse events with the National Cancer Institute's Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Am Soc Clin Oncol Educ Book 35 , 67-73 (2016). Reeve, B.B., Greenzang, K.A. & Sung, L. Patient-reported outcomes in pediatric patients with cancer. Am Soc Clin Oncol Educ Book 43 , 1-9 (2023). Horan, M.R. , et al. Ten considerations for integrating patient-reported outcomes into clinical care for childhood cancer survivors. Cancers (Basel) 15 , 1-16 (2023). Gandrup, J., Ali, S.M., McBeth, J., van der Veer, S.N. & Dixon, W.G. Remote symptom monitoring integrated into electronic health records: a systematic review. J Am Med Inform Assoc 27 , 1752-1763 (2020). Dupuis, L.L. , et al. Symptom screening for hospitalized pediatric patients with cancer: a randomized clinical trial. JAMA Pediatr 179 , 11-18 (2025). Neal, R.D. , et al. Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review. Br J Cancer 112 Suppl 1 , S92-107 (2015). Dixon, S.B. , et al. Specific causes of excess late mortality and association with modifiable risk factors among survivors of childhood cancer: a report from the Childhood Cancer Survivor Study cohort. Lancet 401 , 1447-1457 (2023). Ness, K.K. , et al. Exercise intolerance, mortality, and organ system impairment in adult survivors of childhood cancer. J Clin Oncol 38 , 29-42 (2020). Velikova, G. , et al. Electronic self-reporting of adverse events for patients undergoing cancer treatment: the eRAPID research programme including two RCTs. in Programme Grants for Applied Research (NIHR Journals Library, Southampton (UK), 2022). van Westrienen, P.E., Pisters, M.F., Veenhof, C. & de Wit, N.J. Identification of patients with moderate medically unexplained physical symptoms in primary care with a five years follow-up. BMC Fam Pract 20 , 1-8 (2019). Bakitas, M.A. , et al. Early versus delayed initiation of concurrent palliative oncology care: patient outcomes in the ENABLE III randomized controlled trial. J Clin Oncol 33 , 1438-1445 (2015). Zhou, X., Menche, J., Barabasi, A.L. & Sharma, A. Human symptoms-disease network. Nat Commun 5 , 1-10 (2014). Marijon, E. , et al. Warning symptoms are associated with survival from sudden cardiac arrest. Ann Intern Med 164 , 23-29 (2016). Pimple, P. , et al. Psychological distress and subsequent cardiovascular events in individuals with coronary artery disease. J Am Heart Assoc 8 , 1-9 (2019). Rashid, S. , et al. Anxiety and depression in heart failure: an updated review. Curr Probl Cardiol 48 , 1-21 (2023). Horan, M.R. , et al. Multilevel characteristics of cumulative symptom burden in young survivors of childhood cancer. JAMA Netw Open 7 , 1-17 (2024). Tables Table 1: Characteristics of study participants (N=735) Characteristics Mean (SD) or n (%) Socio-demographic factors Mean age at symptom evaluation (in years) T1 27.0 (5.1) T2 35.9 (6.9) T3 40.1 (7.3) Mean years since cancer diagnosis T1 17.7 (4.6) T2 26.5 (6.5) T3 30.7(6.9) Sex Male 375 (51.0%) Female 360 (49.0%) Race/ethnicity White, non-Hispanic 660 (89.8%) Other 75 (10.2%) Educational attainment at T1 Below high school, high school graduate or training after high school 502 (68.3%) College graduate or postgraduate level 233 (31.7%) Lifestyle factors Cigarette smoking at T1 Never smoker 493 (67.4%) Past smoker 105 (14.3%) Current smoker 134 (18.3%) Cigarette smoking at T2 Never smoker 532 (73.0%) Past smoker 72 (9.9%) Current smoker 125 (17.2%) Cancer diagnosis Leukemia 304 (41.4%) Hodgkin lymphoma 156 (21.2%) Non-Hodgkin lymphoma 64 (8.7%) Osteosarcoma 50 (6.8%) Wilms tumor 44 (6.0%) Central nervous system tumor 32 (4.4%) Neuroblastoma 30 (4.1%) Soft tissue sarcoma/rhabdomyosarcoma 24 (3.3%) Ewing sarcoma 23 (3.1%) Other 8 (1.1%) Chemotherapy Alkylating agents 491 (66.8%) Anthracyclines 443 (60.3%) Bleomycin 50 (6.8%) Corticosteroids 411 (55.9%) High-dose methotrexate 167 (22.7%) Platinum 42 (5.7%) Vincristine 565 (76.9%) Radiotherapy Abdominal/pelvic irradiation 217 (29.5%) Brain irradiation 302 (41.1%) Neck/chest irradiation 265 (36.1%) Total body irradiation 18 (2.5%) Bone marrow transplantation 26 (3.5%) Major surgery (including limb-sparing surgery) 427 (58.1%) Table 2: Symptom clusters at T1 and cluster changes over time associated with progression of total CHC burden Symptom clusters at T1 and cluster changes over time Progression of total CHC burden RR (95% C.I.) # Model 1: Symptom clusters at T1 Progression of total CHC burden post-T1 Low physical & emotional symptom burden Reference Moderate physical & low emotional symptom burden 1.53 (1.14, 2.06)** Moderate physical & emotional symptom burden 0.94 (0.63, 1.40) High physical & emotional symptom burden 1.64 (1.14, 2.36)** Model 2: Change of symptom clusters from T1 to T2 Progression of total CHC burden from T1-T2 to post-T2 Improved or persistently low symptom burden † Reference Persistently moderate symptom burden ‡ 1.42 (1.03, 1.97)* Increased or persistently high symptom burden § 1.63 (1.18, 2.26)** Model 3: Change of symptom clusters from T2 to T3 Progression of total CHC burden from T2-T3 to post-T3 Improved or persistently low symptom burden † Reference Persistently moderate symptom burden ‡ 1.66 (1.07, 2.59)* Increased or persistently high symptom burden § 2.28 (1.51, 3.45)*** CHCs = Chronic health conditions; RR = Relative risk † Improved or persistently low symptom burden (e.g., clusters 4 to 2, clusters 1 to 1) ‡ Persistently moderate symptom burden (e.g., clusters 2 to 2, clusters 3 to 3) § Increased or persistently high symptom burden (e.g., clusters 2 to 4, clusters 4 to 4) # Adjusted for age, sex, time since diagnosis, cigarette smoking, and treatment modalities listed in Supplementary Table S2 * p <0.05; ** p<0.01; *** p<0.001 Table 3: Symptom clusters at T1 and cluster changes over time associated with progression of individual CHC groups Symptom clusters at T1 and clusters change over time Cardiac Vascular Respiratory Musculo-skeletal Neurologic Endocrine Reproductive RR (95% C.I.) RR (95% C.I.) RR (95% C.I.) RR (95% C.I.) RR (95% C.I.) RR (95% C.I.) RR (95% C.I.) Model 1: Symptom clusters at T1 Progression of individual CHC groups post-T1 † Low physical & emotional symptom burden Reference Reference Reference Reference Reference Reference Reference Moderate physical & low emotional symptom burden 1.13 (0.88, 1.44) 1.12 (0.95, 1.32) 1.29 (1.07, 1.56)** 1.43 (1.05, 1.94)* 2.23 (1.65, 3.00)*** 1.16 (0.95, 1.43) 1.32 (0.86, 2.04) Moderate physical & emotional symptom burden 0.84 (0.60, 1.16) 1.38 (1.17, 1.62)*** 0.99 (0.76, 1.30) 1.16 (0.80, 1.66) 1.29 (0.86, 1.92) 1.12 (0.87, 1.45) 0.96 (0.56, 1.65) High physical & emotional symptom burden 0.96 (0.68, 1.35) 1.24 (1.02, 1.52)* 1.32 (1.04, 1.67)* 1.91 (1.35, 2.69)*** 2.53 (1.81, 3.53)*** 1.29 (0.99, 1.68) 1.51 (0.86, 2.66) Model 2: Change of symptom clusters from T1 to T2 Progression of individual CHC groups from T1-T2 to post-T2 † Improved or persistently low symptom burden ‡ Reference Reference Reference Reference Reference Reference Reference Persistently moderate symptom burden § 1.20 (0.93, 1.55) 1.21 (1.04, 1.41)* 1.30 (1.06, 1.60)* 0.99 (0.71, 1.39) 1.79 (1.33, 2.40)*** 1.09 (0.88, 1.34) 1.52 (0.98, 2.36) Increased or persistently high symptom burden # 1.16 (0.90, 1.50) 1.12 (0.94, 1.32) 1.30 (1.06, 1.59)* 1.28 (0.94, 1.74) 2.23 (1.69, 2.93)*** 1.04 (0.82, 1.32) 1.17 (0.68, 2.03) Model 3: Change of symptom clusters from T2 to T3 Progression of individual CHC groups from T2-T3 to post-T3 † Improved or persistently low symptom burden ‡ Reference Reference Reference Reference Reference Reference Reference Persistently moderate symptom burden § 0.95 (0.69, 1.31) 1.10 (0.92, 1.32) 1.17 (0.92, 1.49) 1.49 (1.06, 2.10)* 1.74 (1.21, 2.50)** 1.28 (1.02, 1.62)* 2.41 (1.30, 4.45)** Increased or persistently high symptom burden # 1.15 (0.85, 1.55) 1.18 (0.98, 1.42) 1.33 (1.06, 1.68)* 1.23 (0.85, 1.77) 2.81 (2.04, 3.87)*** 1.30 (1.00, 1.68)* 1.80 (0.94, 3.45) CHCs = Chronic health conditions; RR = Relative risk † Adjusted for age, sex, time since diagnosis, cigarette smoking, and treatment modalities listed in Supplementary Table S2 ‡ Improved or persistently low symptom burden (e.g., clusters 4 to 2, clusters 1 to 1) § Persistently moderate symptom burden (e.g., clusters 2 to 2, clusters 3 to 3) # Increased or persistently high symptom burden (e.g., clusters 2 to 4, clusters 4 to 4) * p <0.05; ** p<0.01; *** p<0.001 Additional Declarations There is NO Competing Interest. Supplementary Files SUPPLEMENTARYMATERIALS.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7229897","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":512046840,"identity":"0ee30a00-7a2f-4915-bc4c-b3d6a9592031","order_by":0,"name":"I-Chan Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYBACNjBiYEgA8z4wMDDD2MRpYZzBYEBYCwOyFmYeBgMGglr4GJifPfi5gyHP4PjZw69t/vxhNziefIDh455aPFawmRv2nmEoNjiTl2ad22bAbHDmWQLjjGfHcWuRf8MmwdvGkLjhQI6ZcW4DUMuNHANmngPH8NjCwyb5F6Tl/BszY4s/IC35HwhqkQbbciPH+DEDG9gWYDgcqMHnFzNp2TaJxJk33pgx9rYZM0ueeWZwcMaBAzi1yDcwP5N822aT2Hc+x/jDjz9yyXzHkx8++HCgDqcWKJAA2wgik0EsoBWHCWkBA2ZgemGwg3II2jIKRsEoGAUjBwAAR2VSoUK/JmQAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-1194-3923","institution":"St. Jude Children's Research Hospital","correspondingAuthor":true,"prefix":"","firstName":"I-Chan","middleName":"","lastName":"Huang","suffix":""},{"id":512046841,"identity":"440e890f-ad2c-415b-86c6-c40dcc92fc48","order_by":1,"name":"Madeline Horan","email":"","orcid":"","institution":"Wake Forest University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Madeline","middleName":"","lastName":"Horan","suffix":""},{"id":512046842,"identity":"06f71669-8b14-4ffd-8142-0c9346d32b23","order_by":2,"name":"Wei Liu","email":"","orcid":"","institution":"PHASTAR","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Liu","suffix":""},{"id":512046843,"identity":"65754563-8a0a-4c24-9cb4-8f3a4651c76b","order_by":3,"name":"Deo Srivastava","email":"","orcid":"https://orcid.org/0000-0001-6693-8120","institution":"St. Jude Children's Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Deo","middleName":"","lastName":"Srivastava","suffix":""},{"id":512046844,"identity":"a5c02004-a2ef-40b8-95cf-d6a0ab1e42af","order_by":4,"name":"Matthew Ehrhardt","email":"","orcid":"https://orcid.org/0000-0003-2781-9983","institution":"St. Jude Children's Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"","lastName":"Ehrhardt","suffix":""},{"id":512046845,"identity":"5e892368-4be8-4846-850f-ca4a6bf7f5bb","order_by":5,"name":"Daniel Mulrooney","email":"","orcid":"https://orcid.org/0000-0003-2351-9115","institution":"St. Jude Children's Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Mulrooney","suffix":""},{"id":512046846,"identity":"0d330b13-644d-4711-94db-eb9bf0d4214d","order_by":6,"name":"Wassim Chemaitilly","email":"","orcid":"","institution":"University of Pittsburgh Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Wassim","middleName":"","lastName":"Chemaitilly","suffix":""},{"id":512046847,"identity":"fb7504fa-fd22-4c2f-876a-1bd0b470ce97","order_by":7,"name":"Kirsten Ness","email":"","orcid":"https://orcid.org/0000-0002-2084-1507","institution":"St. Jude Children's Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kirsten","middleName":"","lastName":"Ness","suffix":""},{"id":512046848,"identity":"35927e01-c01f-4f9f-b7ec-0579057a877d","order_by":8,"name":"Justin Baker","email":"","orcid":"","institution":"Stanford University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Justin","middleName":"","lastName":"Baker","suffix":""},{"id":512046849,"identity":"7c13f75a-8b46-4d86-b8f4-e69b5d631c14","order_by":9,"name":"Gregory Armstrong","email":"","orcid":"","institution":"St. Jude Children's Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Gregory","middleName":"","lastName":"Armstrong","suffix":""},{"id":512046850,"identity":"6a7553ac-13de-4390-a65c-54fae619ea9b","order_by":10,"name":"Melissa Hudson","email":"","orcid":"","institution":"St. Jude Children's Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Melissa","middleName":"","lastName":"Hudson","suffix":""},{"id":512046851,"identity":"8f4d3fde-4c39-489f-8283-039b2c723d03","order_by":11,"name":"Kevin Krull","email":"","orcid":"https://orcid.org/0000-0002-0476-7001","institution":"Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"","lastName":"Krull","suffix":""}],"badges":[],"createdAt":"2025-07-28 05:20:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7229897/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7229897/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91363845,"identity":"1ff06473-be1b-4182-84b6-f9bb99948302","added_by":"auto","created_at":"2025-09-15 17:03:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45111,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of 10 symptom domains (Panel A) and symptom clusters\u003csup\u003e†\u003c/sup\u003e (Panel B) at each time point and the change of symptom clusters over time (Panel C).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e# \u003c/sup\u003eIncreased or persistently high symptom burden (e.g., clusters 2 to 4, clusters 4 to 4)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e† \u003c/sup\u003eSee Supplementary Table S3 for the classification method of the change of symptom clusters\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e‡ \u003c/sup\u003eImproved or persistently low symptom burden (e.g., clusters 4 to 2, clusters 1 to 1)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e§ \u003c/sup\u003ePersistently moderate symptom burden (e.g., clusters 2 to 2, clusters 3 to 3)\u0026nbsp;\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7229897/v1/ba8588d6221a780d49dc6c01.png"},{"id":91363843,"identity":"954cadb6-d7ce-45d6-85e0-37615ffa8455","added_by":"auto","created_at":"2025-09-15 17:03:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44793,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of CHCs\u003csup\u003e†\u003c/sup\u003e by time points (Panel A) and change over time (Panel B) at the total\u003csup\u003e‡\u003c/sup\u003e and individual group\u003csup\u003e§\u003c/sup\u003e levels.\u003c/p\u003e\n\u003cp\u003eCHCs = Chronic health conditions\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e† \u003c/sup\u003eIndividual 47 CHCs were graded and grouped by 7 CHC groups. Each of 47 CHCs was graded by modified CTCAE criteria as no conditions, Grade 1 (mild), Grade 2 (moderate), Grade 3 (severe/disabling) and Grade 4 (life-threatening). The highest grade of a specific CHC within a corresponding CHC group was chosen to represent the severity of a CHC group; Grades ≥2 represented the presence of a specific CHC group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e‡ \u003c/sup\u003eTotal CHC burden was classified as none/low, moderate, high, and very high. None/low category represented having any Grade 1 CHCs, moderate category for having ≥1 Grade 2 and/or 1 Grade 3 CHCs, high category for ≥2 Grade 3, or 1 Grade 4 and 1 Grade 3 CHCs, and very high category for ≥2 Grade 4 or ≥2 Grade 3 and 1 Grade 4 CHCs. Moderate, high or very high category represented the presence of total CHC burden. \u0026nbsp;\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7229897/v1/374655455ca3b50d2c53e154.png"},{"id":91365627,"identity":"cc8d7082-61c0-486b-a479-6f850ddbd36e","added_by":"auto","created_at":"2025-09-15 17:35:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1017752,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7229897/v1/461610a6-b9c9-4eb0-ae39-8bbce663e774.pdf"},{"id":91363855,"identity":"df4c9a91-e812-42c3-ad78-985c29c86afe","added_by":"auto","created_at":"2025-09-15 17:03:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":214027,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIALS.docx","url":"https://assets-eu.researchsquare.com/files/rs-7229897/v1/31cac2b89ed4b058caf08ffe.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Early Symptom Warnings and Long-Term Health Conditions in Childhood Cancer Survivors: Insights from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eChildhood cancer and its treatment have been associated with a wide range of late effects,\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e which can adversely impact physical and psychosocial function\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and contribute to premature mortality.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The St. Jude Lifetime Cohort Study (SJLIFE) found that by age 50 years, adult survivors of childhood cancer experienced an average of 17 chronic health conditions (CHCs), of which 4.7 conditions were severe/disabling, life-threatening, or fatal, based on grades 3\u0026ndash;5 of the Common Terminology Criteria for Adverse Events (CTCAE).\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eScreening for and preventing the onset or worsening of CHCs is a primary task of cancer survivorship care. Currently, screening guidelines for childhood cancer survivors largely rely on clinical factors (e.g., cancer diagnosis, treatment history) to address the risk of late effects and inform subsequent follow-up care.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e This approach is challenging because survivors and their primary care providers may lack detailed knowledge of the survivor\u0026rsquo;s diagnosis, treatment, and associated risk of late effects.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Moreover, this strategy does not consider socio-demographics, lifestyle, or perceived symptoms that may mediate or modify the relationships between cancer treatment and long-term health outcomes.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eChildhood cancer survivors experience symptoms across multiple domains, including cardiac, pulmonary, and sensory dysfunction, pain, fatigue, and poor memory and attention. Notably, 75% of childhood cancer survivors report multiple co-occurring symptoms,\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e and a greater symptom burden is linked to poorer quality of life (QOL).\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e When symptoms present together, their combined effect may exacerbate QOL impairments,\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and commonly co-occurring symptoms may reflect shared underlying mechanisms that contribute to greater disease severity.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e While prior studies have evaluated symptom clusters (defined as patterns of multiple, co-occurring symptoms) in pediatric cancer patients,\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e few have focused on adult survivors of childhood cancer.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Furthermore, existing studies are limited by small sample sizes (\u0026lt;\u0026thinsp;150 survivors) and a cross-sectional design. Expanding this line of research is crucial to guide the development of interventions aimed at reducing the health burden and QOL impairment among survivors with persistent symptom clusters.\u003c/p\u003e\u003cp\u003ePatient-reported symptoms, representing the manifestation of health abnormalities, can prompt medical consultation in individuals with and without a cancer history.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e In adult-onset cancer, symptom reporting during and after therapy has demonstrated independent prognostic value for survival, beyond socio-demographic and clinical factors.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Collecting symptom data from this population has been shown to enhance patient-doctor communication, improve QOL, reduce emergency visits, and increase survival.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e While prognostic models for conditions, such as heart failure, ischemic heart disease/stroke, and hypertension/diabetes, have been developed in pediatric cancer survivors,\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e systematic symptom assessment using standard tools remains underutilized in survivorship care.\u003c/p\u003e\u003cp\u003eIt is clinically intuitive that symptoms often precede the diagnosis of CHCs and prompt medical attention, yet empirical evidence linking \u003cem\u003eearly symptom clusters\u003c/em\u003e to subsequent CHC development remains limited. Leveraging comprehensive longitudinal data from two well-characterized survivor cohorts, the SJLIFE and the Childhood Cancer Survivor Study (CCSS), this study examined symptom clusters and their changes over a 25-year period among adult survivors of childhood cancer, in relation to the progression of clinically ascertained CHCs, including new onset, persistent, and worsening conditions, while accounting for treatment history, socio-demographic characteristics, and lifestyle factors.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Participants\u003c/h2\u003e\u003cp\u003eStudy participants were adult survivors of childhood cancer from both SJLIFE and CCSS, two retrospective cohort studies with prospective follow-up to characterize the etiology and late effects of childhood cancer. As of December 2020, SJLIFE included over 6,000 survivors of pediatric malignancies diagnosed at St. Jude Children\u0026rsquo;s Research Hospital (SJCRH) between 1962 and 2012, who returned periodically for clinical assessments.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e CCSS comprises 25,665 survivors diagnosed and treated at one of 31 institutions in North America, including SJCRH, between 1970 and 1999, and followed through periodic surveys.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Approximately 40% of SJLIFE participants also participated in CCSS.\u003c/p\u003e\u003cp\u003eEligible participants were survivors who 1) were aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years; 2) completed at least three patient-reported outcome (PRO) surveys, including CCSS baseline (T1) and two follow-up (T2, T3) surveys via CCSS and/or SJLIFE; and 3) underwent a SJLIFE clinical assessment after T3. Survivors were excluded if PROs were proxy-reported, unevaluable, or unscored due to missing data. Of the 1,358 survivors participating in both SJLIFE and CCSS who completed the baseline CCSS survey, 595 did not complete surveys at T2 or T3, and 28 had missing data, leaving 735 participants for analyses (Supplementary Figure S1). This study was approved by the SJCRH Institutional Review Board, and all participants provided informed consent.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eParticipants self-reported socio-demographics, symptoms, lifestyle behaviors, and health status via online or paper surveys during three time periods: 1994\u0026ndash;2012 (T1), 2007\u0026ndash;2013 (T2), and 2008\u0026ndash;2015 (T3). Clinical data were obtained from clinical assessments conducted during each visit to SJLIFE through 2020, which included medical history review, physical exams, cognitive and functional evaluations, laboratory testing, and organ function evaluations.\u003c/p\u003e\n\u003ch3\u003eSymptom Measurement\u003c/h3\u003e\n\u003cp\u003eA 37-item symptom survey was administered in both SJLIFE and CCSS, covering 10 domains: cardiac (3 items), respiratory (2 items), musculoskeletal (4 items), nausea (1 item), sensory (8 items), pain (4 items), fatigue (2 items), memory (1 item), anxiety (6 items), and depression (6 items) (Supplementary Table S1). Among 37 items, 19 were developed by CCSS investigators and 18 were adopted from the Brief Symptom Inventory-18.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e These items align with the Children's Oncology Group Long-Term Follow-Up Guidelines (COG LTFU Guidelines) to assess treatment-related toxicities and have demonstrated sensitivity to treatment exposures.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e This symptom measure has been reported in a previous SJLIFE publication\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e (see Supplementary Table S1 for the content and measurement properties). We used a checklist approach to classify each symptom domain as present if one or more items within that domain were endorsed by survivors.\u003c/p\u003e\n\u003ch3\u003eClassification of CHCs\u003c/h3\u003e\n\u003cp\u003eCHCs were identified through review of electronic health records (EHRs) for medical history and clinical assessments during SJLIFE visits. The severity of 47 individual CHCs was graded using a modified version of the CTCAE, categorized as none, mild (grade 1), moderate (grade 2), severe/disabling (grade 3), or life-threatening (grade 4) (Supplementary Table S2).\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Individual CHCs were dichotomized as moderate/severe/life-threatening (grades 2\u0026ndash;4) or absent/mild (none or grade 1). These 47 individual CHCs were classified into seven organ system-based groups: cardiac, vascular, respiratory, musculoskeletal, neurologic, endocrine, and reproductive. A given organ system was considered affected if any condition within that group was graded 2\u0026ndash;4 in severity. Based on a previous study,\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e all conditions were combined to classify total CHC burden by none/low (all CHCs grade 0 or 1), moderate (one or more grade 2 and/or one grade 3), high (two or more grade 3 or one grade 4), and very high (two or more grade 4 or two or more grade 3 and one grade 4).\u003c/p\u003e\n\u003ch3\u003eSocio-demographic and Clinical Information\u003c/h3\u003e\n\u003cp\u003eAdditional information was obtained from surveys, including age at evaluation, sex, race/ethnicity, educational attainment, marital status, and cigarette smoking status. Detailed cancer therapy data were abstracted from medical records, including cancer diagnosis, age at diagnosis, chemotherapeutic agents, regions of radiotherapy, and major surgical procedures.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003ePrincipal component analysis was conducted separately at T1, T2, and T3 to identify latent factors underlying 10 symptom domains. The number of symptom factors was determined using eigenvalues\u0026thinsp;\u0026gt;\u0026thinsp;1 and factor loadings\u0026thinsp;\u0026gt;\u0026thinsp;0.4. Latent profile analysis was conducted using standardized factor scores derived from principal component analysis to identify specific symptom clusters, representing subgroups of survivors with distinct symptom burden patterns at each time point. The optimal number of symptom clusters was determined by lower Bayesian Information Criterion (BIC), a significant Voung-Lo-Mendell-Rubin likelihood ratio test, and higher entropy (see the Results section for the labels of individual symptom clusters).\u003c/p\u003e\u003cp\u003eChanges in symptom clusters over time were classified as improved/persistently low symptom burden, persistently moderate symptom burden, or increased/persistently high symptom burden. Changes in CHCs over time were classified as either progression or non-progression (for classification methods, see Supplementary Table S3 for symptom cluster change, and Supplementary Table S4 for CHC progression). Modified Poisson regression was conducted to assess temporal associations across 3 models (Supplementary Figure S2): 1) T1 symptom clusters and progression of \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003etotal CHC burden\u003c/span\u003e (i.e., increased severity or persistently high burden) from pre-T1 to post-T1; 2) changes in symptom clusters from T1-T2 and progression of total CHC burden from T1-T2 to post-T2; and 3) changes in symptom clusters from T2-T3 and progression of total CHC burden from T2-T3 to post-T3. Similar models were employed to evaluate temporal associations between symptom clusters (at T1 and changes in cluster membership) and progressive CHCs (i.e., new onset, persistence, or increased severity) within \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eeach organ system group\u003c/span\u003e. Models were adjusted for factors known to be associated with symptom presence and CHCs, including age at evaluation, sex, smoking status, and treatment exposures per the COG LTFU Guidelines\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e (Supplementary Table S2). All analyses were performed using SAS v9.4 (SAS Institute, Cary, NC) and Mplus v8.2 (Muthen \u0026amp; Muthen, Los Angeles, CA), with statistical significance set at two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eCharacteristics of Participants\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf 735 survivors, approximately 50% were female; 90% were non-Hispanic White; 70% were treated for leukemia or lymphoma (Table 1). The mean (\u0026plusmn;SD) ages at T1, T2, and T3 survey completion were 27.0 (\u0026plusmn;5.1), 35.9 (\u0026plusmn;6.9), and 40.1 (\u0026plusmn;7.3) years, respectively. Compared with those who did not complete surveys at T2 or T3, survivors included in the analysis were older at cancer diagnosis, and more likely to have received radiotherapy (all p\u0026rsquo;s \u0026lt;0.05; Supplementary Table S5).\u003c/p\u003e\n\u003cp\u003ePrevalence of Symptom Clusters and Cluster Change Over Time\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis identified two latent factors across 10 symptom domains at each time point, corresponding to physical-related and psychological-related factors. Based on this two-factor structure, latent profile analysis classified survivors into four consistent symptom clusters across time (Figure 1). The four clusters represented survivors with 4 symptom profiles: low physical and emotional symptoms (42.9-48.4% over time), moderate physical and low emotional symptoms (17.3-19.7%), moderate physical and emotional symptoms (20.8-27.3%), and high physical and emotional symptoms (11.6-12.0%). Survivors with changes in symptom clusters from T1 to T2 and from T2 to T3 were grouped into three categories: improved/persistently low symptom burden (T1 to T2: 53.9%, T2 to T3: 47.3%), persistently moderate symptom burden (T1 to T2: 24.8%, T2 to T3: 28.3%), and increased/persistently high symptom burden (T1 to T2: 21.4%, T2 to T3: 24.4%) (see Supplementary Table S3 for methods in classifying cluster changes). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevalence and Progression of CHCs\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe prevalence of total and grades 2-4 CHC burden increased over time across all seven groups (Figure 2). At least moderate total CHC burden was observed in approximately 44% of survivors at T1, 64% at T2, and 81% at T3. Endocrine conditions were the most common individual CHC group, affecting 21% of survivors at T1, 32% at T2, and 41% at T3. Progressive total CHC burden occurred in approximately 25% of survivors from pre-T1 to post-T1, 22% from T1-T2 to post-T2, and 15% from T2-T3 to post-T3. Vascular CHCs exhibited the highest progression rate among individual CHC groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTemporal Associations of Symptom Clusters at T1 with Progression of CHCs (Model 1)\u003c/p\u003e\n\u003cp\u003eCompared to survivors with low physical and emotional symptoms at T1, those with high physical and emotional symptoms at T1 had a relative risk (RR) of 1.64 (95% CI 1.14-2.36) for progressive total CHC burden from pre-T1 to post-T1. Survivors with moderate physical and low emotional symptoms at T1 had an RR of 1.53 (95% CI 1.14\u0026ndash;2.06) for progressive total CHC burden during the same period (Table 2). In contrast, treatment exposures were not significantly associated with the progression of total CHC burden (Supplementary Table S6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBy organ system groups, compared to low physical and emotional symptoms at T1, survivors with high physical and emotional symptoms at T1 had a significantly higher risk of progressive CHCs from pre-T1 to post-T1, particularly for neurologic (RR 2.53, 95% CI 1.81-3.53), musculoskeletal (RR 1.91, 95% CI 1.35-2.69), respiratory (RR 1.32, 95% CI 1.04-1.67), and vascular (RR 1.24, 95% CI 1.02-1.52) CHCs (Table 3). Survivors with moderate physical and low emotional symptoms at T1 had a 2.23-, 1.43-, and 1.29-fold increased risk of progressive neurologic, musculoskeletal, and respiratory CHCs, respectively (all p\u0026rsquo;s \u0026lt;0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpecific chemotherapy or\u0026nbsp;radiotherapy exposures were associated with progression of select CHC groups from pre-T1 to post-T1 (Supplementary Table S7). For example, anthracycline exposure was significantly associated with an increased risk of progressive cardiac CHCs (RR 1.49), while neck/chest irradiation was associated with progressive respiratory (RR 2.11) and endocrine (RR 2.16) CHCs (all p\u0026rsquo;s \u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eTemporal Associations of Symptom Cluster Change from T1-T2 (Model 2) and from T2-T3 (Model 3) with Progression of CHCs\u003c/p\u003e\n\u003cp\u003eSurvivors with increased or persistently high symptom burden between T1-T2 had a 1.63-fold higher risk of progressive total CHC burden (95% CI 1.18-2.26) from T1-T2 to post-T2, while those with a persistently moderate symptom burden had a 1.42-fold higher risk (95% CI 1.03-1.97), compared to those with improved or persistently low symptom burden (Table 2). Changes in symptom burden between T1-T2 were significantly associated with CHC progression from T1-T2 to post-T2 across CHC groups (Table 3). Specifically, survivors with increased/persistently high symptom burden had elevated risks of progressive neurologic (RR 2.23, 95% CI 1.69-2.93) and respiratory (RR 1.30, 95% CI 1.06-1.59) CHCs compared to those with improved/persistently low symptom burden between T1-T2. Additionally, survivors with persistently moderate symptom burden between T1-T2 had a 1.79-fold higher risk (95% CI 1.33-2.40) of progressive neurologic CHCs, compared to those with improved/persistently low symptom burden.\u003c/p\u003e\n\u003cp\u003eSurvivors with increased/persistently high symptom burden between T2-T3 had a 2.28-fold (95% CI 1.51-3.45) higher risk of progressive total CHC burden from T2-T3 to post-T3, while those with persistently moderate symptom burden had a 1.66-fold (95% CI 1.07-2.59) higher risk (Table 2). By organ system groups, increased/persistently high symptom burden between T2-T3 was significantly associated with higher risks of progressive neurologic (RR 2.81, 95% CI 2.04-3.87) and respiratory (RR 1.33, 95% CI 1.06-1.68) CHCs from T2-T3 to post-T3. Additionally, survivors with persistently moderate symptom burden during the same period had a 1.74-fold (95% CI 1.21-2.50) higher risk of progressive neurologic CHCs compared to those with improved/persistently low symptom burden.\u003c/p\u003e\n\u003cp\u003eTreatment modalities were not significantly associated with progressive total CHC burden in Models 2 or 3 (Supplementary Table S6). However, certain chemotherapy and radiotherapy exposures were significantly associated with the progression of individual CHC groups (Supplementary Tables S8 and S9). For example, anthracycline exposure was associated with progressive cardiac CHCs post-T3 (RR 1.29), while neck/chest irradiation was associated with progressive respiratory CHCs (RR 2.30) and endocrine CHCs (RR 2.19) post-T3 (all p\u0026rsquo;s \u0026lt;0.05).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eUsing 25 years of PRO survey data and clinically ascertained CTCAE-graded CHCs, we provide the first empirical evidence that symptom clusters predict future adverse medical events in childhood cancer survivors. High physical and emotional symptom burden at baseline, as well as increased or persistently high symptom burden over time, were strongly associated with progression of total and specific CHCs. These associations remained significant after adjusting for treatment, socio-demographic, and lifestyle factors.\u003c/p\u003e\u003cp\u003eThe finding of a high symptom burden preceding CHC progression highlights a critical window for early detection and intervention. Recognizing these associations may enable timely clinical action to prevent complications and reduce healthcare costs.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e However, current survivorship surveillance often lacks standardized, routine symptom assessment, with cost-effective screening limited to high-risk survivors for specific conditions such as cardiomyopathy or subsequent neoplasms.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e While symptom tools are widely used during active cancer treatment,\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e their integration into long-term survivorship care remains uncommon due to persistent implementation barriers.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Recent advances in EHR-integrated symptom reporting have now made routine digital monitoring increasingly feasible.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Our findings of temporal symptom-CHC associations suggest that incorporating regular symptom assessment between clinic visits could complement existing surveillance strategies, detect early signs of CHC progression, and support timely preventive care.\u003c/p\u003e\u003cp\u003eA growing body of evidence reinforces the clinical utility of symptom self-reporting. Observational studies across cancer and non-cancer populations have shown that self-reported symptoms can identify individuals in need of early medical evaluation.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Recent randomized trials further demonstrate that embedding symptom tracking in care pathways reduces symptom burden among pediatric cancer patients.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Building on symptom assessments recommended in the COG LTFU Guidelines,\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e our findings support the use of sequential symptom surveys to identify survivors at elevated risk for specific CHCs. Routine symptom monitoring through EHRs may facilitate early CHC detection, improve QOL, and reduce long-term complications.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Many symptoms and CHCs are also modifiable through lifestyle interventions, such as improving diet, increasing physical activity, promoting sleep, and reducing stress.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Future research should assess the feasibility, scalability, and economic viability of systematic symptom surveillance in survivorship care, particularly in low-resource settings. For example, comparative studies could investigate whether real-time digital symptom monitoring (e.g., every 6 months) yields better health outcomes than usual care, thereby demonstrating the added value of proactive symptom tracking.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe robust prognostic value of symptom burden for subsequent CHC development suggests that some survivors with moderate or high symptom burden may not yet have developed or been diagnosed with CHCs. When symptoms lack an identifiable structural or clinical pathology, they are often classified as \u0026ldquo;medically unexplained symptoms,\u0026rdquo; which may stem from cancer-related risk factors or other unknown reasons. These symptoms are linked to poorer QOL \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and increased risk of depression,\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e highlighting their importance in follow-up care. Using a symptom cluster approach provides a more comprehensive view of the patient\u0026rsquo;s experience by identifying patterns across multiple co-occurring symptoms, rather than examining isolated or unexplained complaints individually. Identifying symptom clusters associated with CHC progression (e.g., increased or persistently high symptom burden linked to neurologic CHCs) can inform early clinical interventions. For high-risk survivors, integrating palliative care may help address both explained and unexplained symptoms and improve late-effect management.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe comparable prognostic value of baseline symptom burden and increasing symptom severity across most CHC groups suggests a shared symptom-based pattern in CHC progression. These findings provide a foundation for investigating the biological mechanisms linking specific symptoms to disease development. CHCs marked by co-occurring symptoms may share genetic risk loci or pathways.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e Symptom burden signatures could guide the development of individualized diagnostic tools and targeted therapies to better address co-occurring symptoms. Currently, no studies have explored the biological underpinnings of multiple co-occurring symptoms, highlighting a critical gap for future research.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Treatment exposures likely precede both biological mechanisms and symptoms in the etiologic pathway, which occur before CHC diagnosis; however, this sequence remains untested and cannot be evaluated with the current data. To advance this line of inquiry, conceptual frameworks are needed to clarify the relationships among cancer treatment exposures, biological mechanisms, symptom clusters, and CHC progression for childhood cancer survivors.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eInterestingly, exposure to anthracycline agents and neck/chest radiotherapy, rather than baseline symptom burden or severity changes over time, was significantly associated with progressive cardiac conditions. The absence of a symptom-based association may reflect the use of broader measures of symptom burden rather than cardiac-specific symptoms. Previous studies have shown that early-stage cardiac conditions often present with symptoms such as chest pain and dyspnea,\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e and that uncontrolled anxiety and depression are linked to adverse cardiac events in individuals with stable coronary artery disease or heart failure.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, analyses were limited to survivors who completed three symptom surveys. Those who had incomplete symptom survey data or died earlier were excluded, which limits the generalizability to the broader population of adult survivors of childhood cancer. Second, the sample was predominantly white and non-Hispanic, which further restricts the applicability of findings to diverse populations. Third, symptom data were collected only during long-term survivorship (i.e., a mean of 18 years post-diagnosis at T1), excluding symptoms experienced during cancer therapy or earlier phases of survivorship. A subsequent study of young (i.e., 8\u0026ndash;18 years of age) survivors of childhood cancer found that 38% reported moderate to high symptom burden early in survivorship.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e Longitudinal symptom data from diagnosis through post-therapy and across the lifespan are needed to capture symptom evolution and its relationships with CHC progression. Future research should also determine the optimal timing, interval, and frequency for symptom assessment, ideally using systems that trigger alerts to healthcare teams when symptoms exceed predefined clinical thresholds. Lastly, our findings do not establish the predictive validity of symptom data for subsequent adverse medical events. To support risk stratification and targeted intervention for cancer survivors, future research must evaluate the predictive performance of symptom assessments (e.g., accuracy, sensitivity, specificity, predictive values) using training and test datasets, along with standard assessment tools, such as the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE).\u003c/p\u003e\u003cp\u003eIn conclusion, baseline symptom clusters and their changes over time independently link to subsequent CHC development in adult survivors of childhood cancer, beyond treatment exposures and traditional risk factors. Future research should focus on developing, validating, and implementing survivor-reported symptom assessments for risk prediction. Meanwhile, incorporating serial symptom assessments into risk-based follow-up care and clinical guidelines may help identify survivors who are at an elevated risk of late effects.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eResearch reported in this publication was supported by the National Cancer Institute under Award Numbers R21CA202210, R01CA238368, R01CA258193, U01CA195547, and U24CA055727. The content is solely the authors' responsibility and does not necessarily represent the official views of the funding agency. Support for St. Jude Children’s Research Hospital was also provided by the Cancer Center Support (CORE) grant (CA21765, C. Roberts, Principal Investigator) and the American Lebanese-Syrian Associated Charities (ALSAC).\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArmstrong, G.T.\u003cem\u003e, et al.\u003c/em\u003e Aging and risk of severe, disabling, life-threatening, and fatal events in the Childhood Cancer Survivor Study. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 1218-1227 (2014).\u003c/li\u003e\n\u003cli\u003eGibson, T.M.\u003cem\u003e, et al.\u003c/em\u003e Temporal patterns in the risk of chronic health conditions in survivors of childhood cancer diagnosed 1970-99: a report from the Childhood Cancer Survivor Study cohort. \u003cem\u003eLancet Oncol\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 1590-1601 (2018).\u003c/li\u003e\n\u003cli\u003eNess, K.K.\u003cem\u003e, et al.\u003c/em\u003e Physical performance limitations in the Childhood Cancer Survivor Study cohort. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 2382-2389 (2009).\u003c/li\u003e\n\u003cli\u003eKrull, K.R., Hardy, K.K., Kahalley, L.S., Schuitema, I. \u0026amp; Kesler, S.R. Neurocognitive outcomes and interventions in long-term survivors of childhood cancer. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 2181-2189 (2018).\u003c/li\u003e\n\u003cli\u003eArmstrong, G.T.\u003cem\u003e, et al.\u003c/em\u003e Reduction in late mortality among 5-year survivors of childhood cancer. \u003cem\u003eN Engl J Med\u003c/em\u003e \u003cstrong\u003e374\u003c/strong\u003e, 833-842 (2016).\u003c/li\u003e\n\u003cli\u003eBhakta, N.\u003cem\u003e, et al.\u003c/em\u003e The cumulative burden of surviving childhood cancer: an initial report from the St Jude Lifetime Cohort Study (SJLIFE). \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e390\u003c/strong\u003e, 2569-2582 (2017).\u003c/li\u003e\n\u003cli\u003eLandier, W.\u003cem\u003e, et al.\u003c/em\u003e Development of risk-based guidelines for pediatric cancer survivors: the Children\u0026apos;s Oncology Group Long-Term Follow-Up Guidelines from the Children\u0026apos;s Oncology Group Late Effects Committee and Nursing Discipline. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 4979-4990 (2004).\u003c/li\u003e\n\u003cli\u003eHudson, M.M., Bhatia, S., Casillas, J. \u0026amp; Landier, W. Long-term follow-up care for childhood, adolescent, and young adult cancer survivors. \u003cem\u003ePediatrics\u003c/em\u003e \u003cstrong\u003e148\u003c/strong\u003e, 1-17 (2021).\u003c/li\u003e\n\u003cli\u003eSyed, I.A.\u003cem\u003e, et al.\u003c/em\u003e Factors associated with childhood cancer survivors\u0026apos; knowledge about their diagnosis, treatment, and risk for late effects. \u003cem\u003eJ Cancer Surviv\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 363-374 (2016).\u003c/li\u003e\n\u003cli\u003eAlfano, C.M.\u003cem\u003e, et al.\u003c/em\u003e Implementing personalized pathways for cancer follow-up care in the United States: proceedings from an American Cancer Society-American Society of Clinical Oncology summit. \u003cem\u003eCA Cancer J Clin\u003c/em\u003e \u003cstrong\u003e69\u003c/strong\u003e, 234-247 (2019).\u003c/li\u003e\n\u003cli\u003eHuang, I.C.\u003cem\u003e, et al.\u003c/em\u003e Association between the prevalence of symptoms and health-related quality of life in adult survivors of childhood cancer: a report from the St. Jude Lifetime Cohort study. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 4242-4251 (2013).\u003c/li\u003e\n\u003cli\u003eShin, H.\u003cem\u003e, et al.\u003c/em\u003e Associations of symptom clusters and health outcomes in adult survivors of childhood cancer: a report from the St Jude Lifetime Cohort Study. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 497-507 (2023).\u003c/li\u003e\n\u003cli\u003eMiaskowski, C.\u003cem\u003e, et al.\u003c/em\u003e Advancing symptom science through symptom cluster research: expert panel proceedings and recommendations. \u003cem\u003eJ Natl Cancer Inst\u003c/em\u003e \u003cstrong\u003e109\u003c/strong\u003e, 1-9 (2017).\u003c/li\u003e\n\u003cli\u003eHooke, M.C.\u003cem\u003e, et al.\u003c/em\u003e Symptom clusters, physical activity, and quality of life: a latent class analysis of children during maintenance therapy for leukemia. \u003cem\u003eCancer Nurs\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 113-119 (2022).\u003c/li\u003e\n\u003cli\u003eJones, R., Latinovic, R., Charlton, J. \u0026amp; Gulliford, M.C. Alarm symptoms in early diagnosis of cancer in primary care: cohort study using General Practice Research Database. \u003cem\u003eBMJ\u003c/em\u003e \u003cstrong\u003e334\u003c/strong\u003e, 1-8 (2007).\u003c/li\u003e\n\u003cli\u003eMierzynska, J.\u003cem\u003e, et al.\u003c/em\u003e Prognostic value of patient-reported outcomes from international randomised clinical trials on cancer: a systematic review. \u003cem\u003eLancet Oncol\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, e685-e698 (2019).\u003c/li\u003e\n\u003cli\u003eBasch, E.\u003cem\u003e, et al.\u003c/em\u003e Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 557-565 (2016).\u003c/li\u003e\n\u003cli\u003eChen, Y.\u003cem\u003e, et al.\u003c/em\u003e Traditional cardiovascular risk factors and individual prediction of cardiovascular events in childhood cancer survivors. \u003cem\u003eJ Natl Cancer Inst\u003c/em\u003e \u003cstrong\u003e112\u003c/strong\u003e, 256-265 (2020).\u003c/li\u003e\n\u003cli\u003eHowell, C.R.\u003cem\u003e, et al.\u003c/em\u003e Cohort Profile: The St. Jude Lifetime Cohort study (SJLIFE) for paediatric cancer survivors. \u003cem\u003eInt J Epidemiol\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 39-49 (2021).\u003c/li\u003e\n\u003cli\u003eDerogatis, L. \u003cem\u003eBrief Symptom Inventory 18: Administration, Scoring, and Procedures Manual\u003c/em\u003e, (National Computer Systems, Minneapolis: MN, 2000).\u003c/li\u003e\n\u003cli\u003eHudson, M.M.\u003cem\u003e, et al.\u003c/em\u003e Approach for classification and severity grading of long-term and late-onset health events among childhood cancer survivors in the St. Jude Lifetime Cohort. \u003cem\u003eCancer Epidemiol Biomarkers Prev\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 666-674 (2017).\u003c/li\u003e\n\u003cli\u003eGeenen, M.M.\u003cem\u003e, et al.\u003c/em\u003e Medical assessment of adverse health outcomes in long-term survivors of childhood cancer. \u003cem\u003eJAMA\u003c/em\u003e \u003cstrong\u003e297\u003c/strong\u003e, 2705-2715 (2007).\u003c/li\u003e\n\u003cli\u003eZonneveld, L.N., Sprangers, M.A., Kooiman, C.G., van \u0026apos;t Spijker, A. \u0026amp; Busschbach, J.J. Patients with unexplained physical symptoms have poorer quality of life and higher costs than other patient groups: a cross-sectional study on burden. \u003cem\u003eBMC Health Serv Res\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 1-11 (2013).\u003c/li\u003e\n\u003cli\u003eEhrhardt, M.J.\u003cem\u003e, et al.\u003c/em\u003e Cost-effectiveness of the International Late Effects of Childhood Cancer Guideline Harmonization Group screening guidelines to prevent heart failure in survivors of childhood cancer. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e38\u003c/strong\u003e, 3851-3862 (2020).\u003c/li\u003e\n\u003cli\u003eKluetz, P.G., Chingos, D.T., Basch, E.M. \u0026amp; Mitchell, S.A. Patient-reported outcomes in cancer clinical trials: measuring symptomatic adverse events with the National Cancer Institute\u0026apos;s Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). \u003cem\u003eAm Soc Clin Oncol Educ Book\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 67-73 (2016).\u003c/li\u003e\n\u003cli\u003eReeve, B.B., Greenzang, K.A. \u0026amp; Sung, L. Patient-reported outcomes in pediatric patients with cancer. \u003cem\u003eAm Soc Clin Oncol Educ Book\u003c/em\u003e \u003cstrong\u003e43\u003c/strong\u003e, 1-9 (2023).\u003c/li\u003e\n\u003cli\u003eHoran, M.R.\u003cem\u003e, et al.\u003c/em\u003e Ten considerations for integrating patient-reported outcomes into clinical care for childhood cancer survivors. \u003cem\u003eCancers (Basel)\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1-16 (2023).\u003c/li\u003e\n\u003cli\u003eGandrup, J., Ali, S.M., McBeth, J., van der Veer, S.N. \u0026amp; Dixon, W.G. Remote symptom monitoring integrated into electronic health records: a systematic review. \u003cem\u003eJ Am Med Inform Assoc\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 1752-1763 (2020).\u003c/li\u003e\n\u003cli\u003eDupuis, L.L.\u003cem\u003e, et al.\u003c/em\u003e Symptom screening for hospitalized pediatric patients with cancer: a randomized clinical trial. \u003cem\u003eJAMA Pediatr\u003c/em\u003e \u003cstrong\u003e179\u003c/strong\u003e, 11-18 (2025).\u003c/li\u003e\n\u003cli\u003eNeal, R.D.\u003cem\u003e, et al.\u003c/em\u003e Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review. \u003cem\u003eBr J Cancer\u003c/em\u003e \u003cstrong\u003e112 Suppl 1\u003c/strong\u003e, S92-107 (2015).\u003c/li\u003e\n\u003cli\u003eDixon, S.B.\u003cem\u003e, et al.\u003c/em\u003e Specific causes of excess late mortality and association with modifiable risk factors among survivors of childhood cancer: a report from the Childhood Cancer Survivor Study cohort. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e401\u003c/strong\u003e, 1447-1457 (2023).\u003c/li\u003e\n\u003cli\u003eNess, K.K.\u003cem\u003e, et al.\u003c/em\u003e Exercise intolerance, mortality, and organ system impairment in adult survivors of childhood cancer. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e38\u003c/strong\u003e, 29-42 (2020).\u003c/li\u003e\n\u003cli\u003eVelikova, G.\u003cem\u003e, et al.\u003c/em\u003e Electronic self-reporting of adverse events for patients undergoing cancer treatment: the eRAPID research programme including two RCTs. in \u003cem\u003eProgramme Grants for Applied Research\u003c/em\u003e (NIHR Journals Library, Southampton (UK), 2022).\u003c/li\u003e\n\u003cli\u003evan Westrienen, P.E., Pisters, M.F., Veenhof, C. \u0026amp; de Wit, N.J. Identification of patients with moderate medically unexplained physical symptoms in primary care with a five years follow-up. \u003cem\u003eBMC Fam Pract\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 1-8 (2019).\u003c/li\u003e\n\u003cli\u003eBakitas, M.A.\u003cem\u003e, et al.\u003c/em\u003e Early versus delayed initiation of concurrent palliative oncology care: patient outcomes in the ENABLE III randomized controlled trial. \u003cem\u003eJ Clin Oncol\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 1438-1445 (2015).\u003c/li\u003e\n\u003cli\u003eZhou, X., Menche, J., Barabasi, A.L. \u0026amp; Sharma, A. Human symptoms-disease network. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 1-10 (2014).\u003c/li\u003e\n\u003cli\u003eMarijon, E.\u003cem\u003e, et al.\u003c/em\u003e Warning symptoms are associated with survival from sudden cardiac arrest. \u003cem\u003eAnn Intern Med\u003c/em\u003e \u003cstrong\u003e164\u003c/strong\u003e, 23-29 (2016).\u003c/li\u003e\n\u003cli\u003ePimple, P.\u003cem\u003e, et al.\u003c/em\u003e Psychological distress and subsequent cardiovascular events in individuals with coronary artery disease. \u003cem\u003eJ Am Heart Assoc\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 1-9 (2019).\u003c/li\u003e\n\u003cli\u003eRashid, S.\u003cem\u003e, et al.\u003c/em\u003e Anxiety and depression in heart failure: an updated review. \u003cem\u003eCurr Probl Cardiol\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, 1-21 (2023).\u003c/li\u003e\n\u003cli\u003eHoran, M.R.\u003cem\u003e, et al.\u003c/em\u003e Multilevel characteristics of cumulative symptom burden in young survivors of childhood cancer. \u003cem\u003eJAMA Netw Open\u003c/em\u003e\u003cstrong\u003e7\u003c/strong\u003e, 1-17 (2024).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Characteristics of study participants (N=735) \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eCharacteristics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eMean (SD) or n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocio-demographic factors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eMean age at symptom evaluation (in years)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;T1 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e27.0 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;T2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e35.9 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;T3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e40.1 (7.3)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eMean years since cancer diagnosis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;T1 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e17.7 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;T2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e26.5 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;T3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e30.7(6.9)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e375 (51.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e360 (49.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eRace/ethnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;White, non-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e660 (89.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e75 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eEducational attainment at T1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Below high school, high school graduate or training after high school\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e502 (68.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;College graduate or postgraduate level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e233 (31.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLifestyle factors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eCigarette smoking at T1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Never smoker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e493 (67.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Past smoker \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e105 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Current smoker \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e134 (18.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003eCigarette smoking at T2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Never smoker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e532 (73.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Past smoker \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e72 (9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Current smoker \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e125 (17.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer diagnosis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Leukemia \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e304 (41.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Hodgkin lymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e156 (21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Non-Hodgkin lymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e64 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; Osteosarcoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e50 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Wilms tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e44 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Central nervous system tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e32 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Neuroblastoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e30 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Soft tissue sarcoma/rhabdomyosarcoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e24 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; Ewing sarcoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e23 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Other\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e8 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChemotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Alkylating agents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e491 (66.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Anthracyclines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e443 (60.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Bleomycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e50 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Corticosteroids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e411 (55.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;High-dose methotrexate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e167 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Platinum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e42 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Vincristine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e565 (76.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Abdominal/pelvic irradiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e217 (29.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Brain irradiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e302 (41.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Neck/chest irradiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e265 (36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Total body irradiation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e18 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBone marrow transplantation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e26 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMajor surgery (including limb-sparing surgery)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e427 (58.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2: Symptom clusters at T1 and cluster changes over time associated with progression of total CHC burden \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"888\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 432px;\"\u003e\n \u003cp\u003eSymptom clusters at T1 and cluster changes over time\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eProgression of total CHC burden\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eRR (95% C.I.)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1: Symptom clusters at T1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eProgression of total CHC burden post-T1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eLow physical \u0026amp; emotional symptom burden\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eModerate physical \u0026amp; low emotional symptom burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003e1.53 (1.14, 2.06)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eModerate physical \u0026amp; emotional symptom burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003e0.94 (0.63, 1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eHigh physical \u0026amp; emotional symptom burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003e1.64 (1.14, 2.36)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2: Change of symptom clusters from T1 to T2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eProgression of total CHC burden\u0026nbsp;\u003c/p\u003e\n \u003cp\u003efrom T1-T2 to post-T2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eImproved or persistently low symptom burden\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003ePersistently moderate symptom burden\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003e1.42 (1.03, 1.97)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eIncreased or persistently high symptom burden\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003e1.63 (1.18, 2.26)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3: Change of symptom clusters from T2 to T3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eProgression of total CHC burden\u0026nbsp;\u003c/p\u003e\n \u003cp\u003efrom T2-T3 to post-T3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eImproved or persistently low symptom burden\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003ePersistently moderate symptom burden\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003e1.66 (1.07, 2.59)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 432px;\"\u003e\n \u003cp\u003eIncreased or persistently high symptom burden\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 456px;\"\u003e\n \u003cp\u003e2.28 (1.51, 3.45)***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCHCs = Chronic health conditions; RR = Relative risk\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eImproved or persistently low symptom burden (e.g., clusters 4 to 2, clusters 1 to 1)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003ePersistently moderate symptom burden (e.g., clusters 2 to 2, clusters 3 to 3)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003eIncreased or persistently high symptom burden (e.g., clusters 2 to 4, clusters 4 to 4)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e#\u003c/sup\u003e Adjusted for age, sex, time since diagnosis, cigarette smoking, and treatment modalities listed in Supplementary Table S2\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e* p \u0026lt;0.05; ** p\u0026lt;0.01; *** p\u0026lt;0.001\u003c/p\u003e\n\u003cp\u003eTable 3: Symptom clusters at T1 and cluster changes over time associated with progression of individual CHC groups \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"876\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003eSymptom clusters at T1 and clusters change over time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eCardiac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eVascular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRespiratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eMusculo-skeletal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eNeurologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eEndocrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReproductive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003cp\u003e(95% C.I.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003cp\u003e(95% C.I.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003cp\u003e(95% C.I.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003cp\u003e(95% C.I.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003cp\u003e(95% C.I.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003cp\u003e(95% C.I.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003cp\u003e(95% C.I.)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1: Symptom clusters at T1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" style=\"width: 696px;\"\u003e\n \u003cp\u003eProgression of individual CHC groups post-T1\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eLow physical \u0026amp; emotional symptom burden\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eModerate physical \u0026amp; low emotional symptom burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003cp\u003e(0.88, 1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003cp\u003e(0.95, 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003cp\u003e(1.07, 1.56)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003cp\u003e(1.05, 1.94)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003cp\u003e(1.65, 3.00)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003cp\u003e(0.95, 1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003cp\u003e(0.86, 2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eModerate physical \u0026amp; emotional symptom burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003cp\u003e(0.60, 1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003cp\u003e(1.17, 1.62)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e(0.76, 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.16\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.80, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003cp\u003e(0.86, 1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003cp\u003e(0.87, 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003cp\u003e(0.56, 1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eHigh physical \u0026amp; emotional symptom burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003cp\u003e(0.68, 1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003cp\u003e(1.02, 1.52)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003cp\u003e(1.04, 1.67)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.91\u003c/p\u003e\n \u003cp\u003e(1.35, 2.69)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003cp\u003e(1.81, 3.53)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003cp\u003e(0.99, 1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003cp\u003e(0.86, 2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2: Change of symptom clusters from T1 to T2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" style=\"width: 696px;\"\u003e\n \u003cp\u003eProgression of individual CHC groups from T1-T2 to post-T2\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eImproved or persistently low symptom burden\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003ePersistently moderate symptom burden\u003csup\u003e\u0026sect;\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003cp\u003e(0.93, 1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003cp\u003e(1.04, 1.41)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003cp\u003e(1.06, 1.60)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e(0.71, 1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003cp\u003e(1.33, 2.40)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003cp\u003e(0.88, 1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003cp\u003e(0.98, 2.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eIncreased or persistently high symptom burden\u003csup\u003e#\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003cp\u003e(0.90, 1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003cp\u003e(0.94, 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003cp\u003e(1.06, 1.59)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003cp\u003e(0.94, 1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003cp\u003e(1.69, 2.93)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003cp\u003e(0.82, 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003cp\u003e(0.68, 2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3: Change of symptom clusters from T2 to T3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" style=\"width: 696px;\"\u003e\n \u003cp\u003eProgression of individual CHC groups from T2-T3 to post-T3\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eImproved or persistently low symptom burden\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003ePersistently moderate symptom burden\u003csup\u003e\u0026sect;\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003cp\u003e(0.69, 1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003cp\u003e(0.92, 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003cp\u003e(0.92, 1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003cp\u003e(1.06, 2.10)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003cp\u003e(1.21, 2.50)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003cp\u003e(1.02, 1.62)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003cp\u003e(1.30, 4.45)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003eIncreased or persistently high symptom burden\u003csup\u003e#\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003cp\u003e(0.85, 1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003cp\u003e(0.98, 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003cp\u003e(1.06, 1.68)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003cp\u003e(0.85, 1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.81\u003c/p\u003e\n \u003cp\u003e(2.04, 3.87)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003cp\u003e(1.00, 1.68)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003cp\u003e(0.94, 3.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCHCs = Chronic health conditions; RR = Relative risk\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAdjusted for age, sex, time since diagnosis, cigarette smoking, and treatment modalities listed in Supplementary Table S2\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eImproved or persistently low symptom burden (e.g., clusters 4 to 2, clusters 1 to 1)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003ePersistently moderate symptom burden (e.g., clusters 2 to 2, clusters 3 to 3)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e#\u0026nbsp;\u003c/sup\u003eIncreased or persistently high symptom burden (e.g., clusters 2 to 4, clusters 4 to 4)\u003c/p\u003e\n\u003cp\u003e* p \u0026lt;0.05; ** p\u0026lt;0.01; *** p\u0026lt;0.001\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Childhood Cancer, Chronic Health Conditions, Late Effects, Patient-Reported Outcomes, Survivors, Symptom Clusters","lastPublishedDoi":"10.21203/rs.3.rs-7229897/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7229897/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSymptom patterns in adult survivors of childhood cancer may signal risk for health deterioration and offer a foundation for risk stratification. 735 survivors completed sequential symptom surveys (T1, T2, T3) and clinical assessment for chronic health conditions (CHCs). Survivors were classified into four clusters: 1) low physical and emotional symptoms, 2) moderate physical and low emotional symptoms, 3) moderate physical and emotional symptoms, and 4) high physical and emotional symptoms. Survivors in cluster 4 vs. cluster 1 had an elevated risk of progressive total CHC burden and vascular, respiratory, neurologic, and musculoskeletal conditions (relative risk [RR] range: 1.24\u0026ndash;2.53). Increased/persistently high symptom burden between T1-T2 increased risk for progressive total CHC burden, respiratory, and neurologic conditions (RR range: 1.30\u0026ndash;2.23). Increased/persistently high T2-T3 symptom burden showed similar associations (all p\u0026rsquo;s\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This proof-of-concept study provides an empirical basis for developing and validating symptom-based prediction models and warning systems to support proactive survivorship care.\u003c/p\u003e","manuscriptTitle":"Early Symptom Warnings and Long-Term Health Conditions in Childhood Cancer Survivors: Insights from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-15 17:03:47","doi":"10.21203/rs.3.rs-7229897/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-medicine","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsmed","sideBox":"Learn more about [Communications Medicine](http://www.nature.com/commsmed)","snPcode":"43856","submissionUrl":"https://mts-commsmed.nature.com/cgi-bin/main.plex","title":"Communications Medicine","twitterHandle":"@commsmedicine","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"366b1564-ff90-4652-9a12-7f1582bdccf0","owner":[],"postedDate":"September 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":54386284,"name":"Biological sciences/Cancer/Paediatric cancer"},{"id":54386285,"name":"Health sciences/Health care/Prognosis"},{"id":54386286,"name":"Health sciences/Signs and symptoms"}],"tags":[],"updatedAt":"2026-03-04T05:46:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-15 17:03:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7229897","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7229897","identity":"rs-7229897","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}