Associations of Symptom Clusters and Health Outcomes in Adult Survivors of Childhood Cancer: A Report From the St Jude Lifetime Cohort Study

Epidemiology of multimorbidity in childhood cancer survivors: a matched cohort study of inpatient hospitalisations in Western Australia

BACKGROUND

Childhood cancer survivors (CCS) experience an elevated burden of health complications, underscoring the importance of understanding the patterns of multimorbidity to guide the management of survivors with complex medical needs.

METHODS

We examined the patterns of hospitalisations with multimorbidity in 5-year CCS (n = 2938) and age- and sex-matched non-cancer comparisons (n = 24,792) using statewide records of inpatient admissions in Western Australia from 1987 to 2019.

RESULTS

Multimorbidity rates were higher for CCS (10.6, 95%CI 10.2-10.9) than for non-cancer comparisons (3.2, 95%CI 3.2-3.3). CCS exhibited a significantly higher adjusted hazard ratio of multimorbidity, particularly when admitted for neoplasms (14.6, 95%CI 11.2-19.1), as well as blood (7.3, 95%CI 4.9-10.7), neurological and sensory (5.2, 95%CI 4.2-6.6), and cardiovascular (3.6, 95%CI 2.6-4.8) diseases. By the age of 55 years, chronic multimorbidity was more prevalent in survivors than in comparisons (14.5% vs. 5.3%). Psychiatric disorders were common comorbidities, particularly in those admitted for neurological and sensory (71.1%), endocrine (61.5%), and digestive (59.3%) diseases. Multimorbidity during hospitalisation increased the length of hospital stay (p < 0.05). Key condition clusters included (1) psychoactive substance  dependence, alcohol misuse, and other mental disorders; (2) hypertension, diabetes, kidney disease, and musculoskeletal diseases; (3) epilepsy, hypothyroidism, and other liver diseases; and (4) hypertension, kidney disease, and other liver diseases.

CONCLUSIONS

These findings suggest that exposure to cancer in childhood elevates the risk of multimorbidity. The reconfiguration of healthcare delivery to enhance personalised care and clinical integration is essential for effectively managing multimorbidity in this population.

Childhood cancer survivors' utilization of primary care provider services and barriers to primary care

This cross-sectional study explores the types of preventive and chronic care survivors of childhood cancer and pediatric bone marrow transplant receive from their primary care providers. We also identified barriers perceived by survivors to utilization of primary care. Survivors were recruited from a large Midwestern pediatric hospital and completed a demographic and an eight-item semi-structured survey. Parents of survivors <18 years completed the survey for their child and survivors >18 years completed on their own. A total of 259 caregivers (55.7%) and 206 survivors (44.3%) participated. The mean survivor age was 19.76 (SD = 8.89). Most survivors reported having a PCP (n = 400, 87.1%). A subset of survivors self-reported visiting a PCP for chronic care (n = 79, 16.7%). Most common reasons for not having a PCP included unsure who to see (n = 27, 52.9%) and lack of insurance (n = 10, 19.6%). Annual family income (β = 1.53, 95% CI [1.26, 1.86]) and healthcare insurance (β = 6.02, 95%CI [1.25, 29.08]) were predictive of having a PCP. Despite having a PCP, few survivors visited them for chronic care. Interventions are needed to facilitate the transition of survivors to a PCP for management of chronic conditions after their cancer treatment.

The effect of traditional Chinese medicine on psychological conditions among elderly patients with cancer: a scoping review

Coping with cancer presents a multitude of challenges that encompass every aspect of a patient's life. These challenges not only strain the body but also weigh heavily on the mind, often culminating in profound psychological distress for cancer patients. The cumulative burden of these experiences can heighten the risk of developing psychiatric disorders, exacerbating the already daunting landscape of cancer care. Therefore, this study reviewed the available research with the aim of investigating the effects of traditional Chinese medicine on psychological conditions in elderly cancer patients. In this scoping review, we applied specific criteria to select studies that focused on elderly patients with cancer. We performed an extensive search across electronic databases, including Embase, Science Direct, PubMed, Google Scholar, Scopus, Cochrane Library and Web of Science. In our investigation, we identified a total of 3870 articles related to the topic under review. Following a meticulous screening process that involved evaluating titles, abstracts, and full texts, we ultimately selected five articles deemed relevant for inclusion in this review. Among these articles, three were randomised studies, while the remaining two were review articles. The outcomes of our analysis revealed that herbal decoctions, nutritional counselling, Tai Chi and acupressure, can effectively improve various psychological outcomes in elderly cancer patients. These interventions reduce fatigue, depression, anxiety, and stress, while also enhancing sleep quality and overall mental health. The present study highlights the importance of traditional Chinese medicine in addressing the needs of elderly patients with cancer. As a result, it is recommended that further extensive research be conducted to comprehensively assess the efficacy and safety of traditional Chinese medicine in managing cancer in the elderly.

Profiles of Fatigue and Psychological Symptoms in Long-Term Childhood, Adolescent, and Young Adult Cancer Survivors-The NOR-CAYACS Study

INTRODUCTION

Long-term childhood, adolescent, and young adult cancer survivors (CAYACS) are at risk of fatigue and psychological problems. However, their interactions remain largely unexplored. Understanding how they cluster can inform treatment and person-centered follow-up care. We aimed to identify and describe profiles of co-occurring fatigue and psychological symptoms and investigate their associations with health-related quality of life (HRQOL) in CAYACS.

METHODS

NOR-CAYACS (The Norwegian Childhood, Adolescents and Young Adult Cancer Survivors study) was a nationwide survey involving adult survivors of any childhood cancer (aged < 19 years at diagnosis) and selected young adult cancers (breast and colorectal cancers, non-Hodgkin lymphoma, leukemias, and malignant melanomas, aged 19-39 years at diagnosis) identified through the Cancer Registry of Norway. We included 1893 survivors aged ≥ 18 years, ≥ 5 years since diagnosis. We performed latent profile analysis with six continuous outcomes: physical and mental fatigue, depression, anxiety, post-traumatic stress symptoms, and fear of recurrence.

RESULTS

We identified an overall "Low" (64%), a "Moderate fatigue/high anxiety" (18%), a "High fatigue/moderate distress" (13%), and an overall "High" (5%) symptom burden profile. The "High" profile exhibited lowest physical- and mental-HRQOL with T-scores -9.8 (95% confidence interval [95% CI]: -12.5, -7.1) and -25.0 (95% CI: -26.7, -23.3) compared to the "Low" profile.

CONCLUSION

We identified four profiles, two characterized by high fatigue and two near normative fatigue levels, each with different psychological symptom burden. Greater symptom burden corresponded to lower HRQOL, with high fatigue profiles showing lower physical HRQOL. These profiles help identify at-risk individuals and allow for targeting interventions and follow-up care to survivors' unique constellation of symptoms.

Neighborhood vulnerability and associations with poor health-related quality of life among adult survivors of childhood cancer

BACKGROUND

Few studies have investigated the relationship between neighborhood vulnerability and health-related quality of life (HRQOL) in the childhood cancer population. This study evaluated the impact of neighborhood vulnerability on HRQOL among adult survivors of childhood cancer.

METHODS

This cross-sectional study included 4393 adult survivors of childhood cancer from the St Jude Lifetime Cohort Study. At the baseline (2007-2020), HRQOL was assessed using the SF36v2's physical and mental components summaries (PCS and MCS). Neighborhood vulnerability was assessed using the overall, domain, and indicator-specific scores of the Social Vulnerability Index (SVI) and Minority Health SVI (MHSVI). Multivariable logistic regression was used to evaluate associations of neighborhood vulnerability (quartiles: Q1-Q4) with impaired HRQOL (1SD below the norm), adjusting for diagnosis, demographics, personal socioeconomic status (SES), lifestyle, and chronic health condition burden. Interactions of SVI and MHSVI with personal SES on impaired HRQOL were analyzed.

RESULTS

Among survivors, 51.9% were male, averaging 30.3 years of age at evaluation and 21.5 years since diagnosis. Comparing neighborhoods with higher vs lower vulnerability (Q4 vs Q1), overall (odds ratio [OR] = 1.60, 95% confidence interval [CI] = 1.19 to 2.16) and domain-specific vulnerability (socioeconomic: OR = 1.59, 95% CI = 1.18 to 2.15; household composition: OR = 1.54, 95% CI = 1.16 to 2.06; housing and transportation: OR = 1.33, 95% CI = 1.00 to 1.76; medical vulnerability: OR = 1.60, 95% CI = 1.22 to 2.09) were significantly associated with impaired PCS, but not MCS. Residing in neighborhoods lacking urgent care clinics was significantly associated with impaired PCS (OR = 1.39, 95% CI = 1.08 to 1.78). Having lower vs higher personal education and living in higher vulnerability neighborhoods were associated with more impaired PCS (Pinteraction = .021).

CONCLUSIONS

Specific aspects of neighborhood vulnerability increase the risk for impaired physical HRQOL. Addressing these neighborhood factors is essential to enhance the HRQOL of survivors.

Using mHealth Technology to Evaluate Daily Symptom Burden among Adult Survivors of Childhood Cancer: A Feasibility Study

BACKGROUND

Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer to evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL).

METHODS

This prospective study used an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after the symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. These surveys comprised a PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models were used to analyze total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression was used to analyze the association between daily symptom burden in the first month and HRQOL in the third month, adjusted for covariates.

RESULTS

Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL in each study week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95% CI: 4.10-9.02), depression (6.32; 95% CI: 3.18-9.47), fatigue (7.93; 95% CI: 5.11-10.80), sleep (6.07; 95% CI: 3.43-8.70), pain (5.16; 95% CI: 2.11-8.22), and cognitive function (-6.89; 95% CI: -10.00 to -3.79) in the third month.

CONCLUSIONS

Daily assessment revealed fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability.

Review of the microbiome and metabolic pathways associated with psychoneurological symptoms in children with cancer

Children with cancer often endure a range of psychoneurological symptoms (PNS), including pain, fatigue, cognitive impairment, anxiety, depressive symptoms, and sleep disturbance. Despite their prevalence, the underlying pathophysiology of PNS remains unclear. Hypotheses suggest an interplay between the gut microbiome and the functional metabolome, given the immune, neurological, and inflammatory influences these processes exert. This mini-review aims to provide a synopsis of the literature that examines the relationship between microbiome-metabolome pathways and PNS in children with cancer, drawing insights from the adult population when applicable. While there is limited microbiome research in the pediatric population, promising results in adult cancer patients include an association between lower microbial diversity and compositional changes, including decreased abundance of the beneficial microbes Fusicatenibacter, Ruminococcus, and Odoribacter, and more PNS. In pediatric patients, associations between peptide, tryptophan, carnitine shuttle, and gut microbial metabolism pathways and PNS outcomes were found. Utilizing multi-omics methods that combine microbiome and metabolome analyses provide insights into the functional capacity of microbiomes and their associated microbial metabolites. In children with cancer receiving chemotherapy, increased abundances of Intestinibacter and Megasphaera correlated with six metabolic pathways, notably carnitine shuttle and tryptophan metabolism. Interventions that target the underlying microbiome-metabolome pathway may be effective in reducing PNS, including the use of pre- and probiotics, fecal microbiome transplantation, dietary modifications, and increased physical activity. Future multi-omics research is needed to corroborate the associations between the microbiome, metabolome, and PNS outcomes in the pediatric oncology population.

Estimation of Personal Symptom Networks Using the Ising Model for Adult Survivors of Childhood Cancer: A Simulation Study with Real-World Data Application

Purpose

Childhood cancer survivors experience interconnected symptoms, patterns of which can be elucidated by network analysis. However, current symptom networks are constructed based on the average survivors without considering individual heterogeneities. We propose to evaluate personal symptom network estimation using the Ising model with covariates through simulations and estimate personal symptom network for adult childhood cancer survivors.

Patients and Methods

We adopted the Ising model with covariates to construct networks by employing logistic regressions for estimating associations between binary symptoms. Simulation experiments assessed the robustness of this method in constructing personal symptom network. Real-world data illustration included 1708 adult childhood cancer survivors from the St. Jude Lifetime Cohort Study (SJLIFE), a retrospective cohort study with prospective follow-up to characterize the etiology and late effects for childhood cancer survivors. Patients' baseline symptoms in 10 domains (cardiac, pulmonary, sensation, nausea, movement, pain, memory, fatigue, anxiety, depression) and individual characteristics (age, sex, race/ethnicity, attained education, personal income, and marital status) were self-reported using survey. Treatment variables (any chemo or radiation therapy) were obtained from medical records. Personal symptom network of 10 domains was estimated using the Ising model, incorporating individual characteristics and treatment data.

Results

Simulations confirmed the robustness of the Ising model with covariates in constructing personal symptom networks. Real-world data analysis identified age, sex, race/ethnicity, education, marital status, and treatment (any chemo and radiation therapy) as major factors influencing symptom co-occurrence. Older childhood cancer survivors showed stronger cardiac-fatigue associations. Survivors of racial/ethnic minorities had stronger pain-fatigue associations. Female survivors with above-college education demonstrated stronger pain-anxiety associations. Unmarried survivors who received radiation had stronger association between movement and memory problems.

Conclusion

The Ising model with covariates accurately estimates personal symptom networks. Individual heterogeneities exist in symptom co-occurrence patterns for childhood cancer survivors. The estimated personal symptom network offers insights into interconnected symptom experiences.

Health-related quality of life and DNA methylation-based aging biomarkers among survivors of childhood cancer

BACKGROUND

Childhood cancer survivors are at high risk for morbidity and mortality and poor patient-reported outcomes, typically health-related quality of life (HRQOL). However, associations between DNA methylation-based aging biomarkers and HRQOL have not been evaluated.

METHODS

DNA methylation was generated with Infinium EPIC BeadChip on blood-derived DNA (median for age at blood draw = 34.5 years, range = 18.5-66.6 years), and HRQOL was assessed with age at survey (mean = 32.3 years, range = 18.4-64.5 years) from 2206 survivors in the St Jude Lifetime Cohort. DNA methylation-based aging biomarkers, including epigenetic age using multiple clocks (eg, GrimAge) and others (eg, DNAmB2M: beta-2-microglobulin; DNAmADM: adrenomedullin), were derived from the DNAm Age Calculator (https://dnamage.genetics.ucla.edu). HRQOL was assessed using the Medical Outcomes Study 36-Item Short-Form Health Survey to capture 8 domains and physical and mental component summaries. General linear models evaluated associations between HRQOL and epigenetic age acceleration (EAA; eg, EAA_GrimAge) or other age-adjusted DNA methylation-based biomarkers (eg, ageadj_DNAmB2M) after adjusting for age at blood draw, sex, cancer treatments, and DNA methylation-based surrogate for smoking pack-years. All P values were 2-sided.

RESULTS

Worse HRQOL was associated with greater EAA_GrimAge (physical component summaries: β = -0.18 years, 95% confidence interval [CI] = -0.251 to -0.11 years; P = 1.85 × 10-5; and 4 individual HRQOL domains), followed by ageadj_DNAmB2M (physical component summaries: β = -0.08 years, 95% CI = -0.124 to -0.037 years; P = .003; and 3 individual HRQOL domains) and ageadj_DNAmADM (physical component summaries: β = -0.082 years, 95% CI = -0.125 to -0.039 years; P = .002; and 2 HRQOL domains). EAA_Hannum (Hannum clock) was not associated with any HRQOL.

CONCLUSIONS

Overall and domain-specific measures of HRQOL are associated with DNA methylation measures of biological aging. Future longitudinal studies should test biological aging as a potential mechanism underlying the association between poor HRQOL and increased risk of clinically assessed adverse health outcomes.

Using an mHealth approach to collect patient-generated health data for predicting adverse health outcomes among adult survivors of childhood cancer

Introduction

Cancer therapies predispose childhood cancer survivors to various treatment-related late effects, which contribute to a higher symptom burden, chronic health conditions (CHCs), and premature mortality. Regular monitoring of symptoms between clinic visits is useful for timely medical consultation and interventions that can improve quality of life (QOL). The Health Share Study aims to utilize mHealth to collect patient-generated health data (PGHD; daily symptoms, momentary physical health status) and develop survivor-specific risk prediction scores for mitigating adverse health outcomes including poor QOL and emergency room admissions. These personalized risk scores will be integrated into the hospital-based electronic health record (EHR) system to facilitate clinician communications with survivors for timely management of late effects.

Methods

This prospective study will recruit 600 adult survivors of childhood cancer from the St. Jude Lifetime Cohort study. Data collection include 20 daily symptoms via a smartphone, objective physical health data (physical activity intensity, sleep performance, and biometric data including resting heart rate, heart rate variability, oxygen saturation, and physical stress) via a wearable activity monitor, patient-reported outcomes (poor QOL, unplanned healthcare utilization) via a smartphone, and clinically ascertained outcomes (physical performance deficits, onset of/worsening CHCs) assessed in the survivorship clinic. Participants will complete health surveys and physical/functional assessments in the clinic at baseline, 2) report daily symptoms, wear an activity monitor, measure blood pressure at home over 4 months, and 3) complete health surveys and physical/functional assessments in the clinic 1 and 2 years from the baseline. Socio-demographic and clinical data abstracted from the EHR will be included in the analysis. We will invite 20 cancer survivors to investigate suitable formats to display predicted risk information on a dashboard and 10 clinicians to suggest evidence-based risk management strategies for adverse health outcomes.

Analysis

Machine and statistical learning will be used in prediction modeling. Both approaches can handle a large number of predictors, including longitudinal patterns of daily symptoms/other PGHD, along with cancer treatments and socio-demographics.

Conclusion

The individualized risk prediction scores and added communications between providers and survivors have the potential to improve survivorship care and outcomes by identifying early clinical presentations of adverse events.

Symptom cluster among cancer survivors from a nationally representative survey: a network analysis

PURPOSE

To identify the symptom cluster among cancer survivors and examine their subgroup differences via network analysis based on nationally representative data.

METHODS

This cross-sectional study included 2966 survivors participating in the 2020 National Health Interview Survey (NHIS). Participants self-reported the presence of 14 symptoms capturing four clusters (physical, somatic, sleep, and psychologic problems). Network analysis models were used to reveal the relationships between symptoms and those interactions. Network comparison tests were applied to compare subgroups.

RESULTS

The core symptoms of the symptom cluster were fatigue (Bet = 33, Clo = 0.0067, Str = 0.9397), pain (Bet = 11, Clo = 0.0060, Str = 0.9226), wake up well rested (Bet = 25, Clo = 0.0057, Str = 0.8491), and anxiety (Bet = 5, Clo = 0.0043, Str = 0.9697) among cancer survivors. The core symptoms, network structure, and global strength were invariant between time since diagnoses (< 2 years vs. ≥ 2 years) or between numbers of cancers (1 vs. ≥ 2), yet varied between the comorbidity group and non-comorbidity group (≥ 1 vs. 0).

CONCLUSIONS

Fatigue would be a potential target for alleviating other symptoms through a negative feedback loop of other related symptoms of cancer survivors. In particular, cancer survivors with other chronic diseases should be the focus of attention and strengthen targeted intervention.

Exploring Inflammation and Stress as Biological Correlates of Symptoms in Children With Advanced Cancer: A Longitudinal Feasibility Study

Background: Few studies have examined biomarkers of stress and inflammation as underlying mechanisms of symptoms in adolescents and young adults with cancer. This study determined the feasibility of collecting blood and saliva samples across time, described the range and distribution of biomarkers, and explored the association of biomarkers with symptom adverse events (AEs). Method: This longitudinal, prospective repeated-measures single-site feasibility study recruited N  =  10 children (M = 12.5 years) receiving treatment for advanced cancer. Symptom AE data and inflammation (cytokines and C-reactive protein) and physiologic response to stress (salivary cortisol and salivary alpha-amylase) biomarker levels were collected at three time points. Descriptive statistics were used to examine feasibility and acceptability and to summarize symptom AE, stress, and inflammatory biomarker data. A linear regression model was used to determine cortisol diurnal slopes. The relationship between symptom and inflammatory biomarker data was explored and Hedges's g statistic was used to determine its effect size. Results: Participants provided 83% of saliva samples (n  =  199/240) and 185 samples were sufficient to be analyzed. Nurses collected 97% (n  =  29/30) of blood samples. Participants reported the saliva collection instructions, kits, and reminders were clear and helpful. Insomnia, pain, fatigue, and anxiety demonstrated the most medium and large negative effects with inflammatory markers. Symptom AEs demonstrated the highest number of medium and large negative effects with interleukin-8 and tumor necrosis factor-alpha (-0.53 to -2.00). Discussion: The results indicate longitudinal concurrent collection of symptom and biomarker data is feasible and inflammatory and stress biomarkers merit consideration for inclusion in future studies.

Multilevel Characteristics of Cumulative Symptom Burden in Young Survivors of Childhood Cancer

Importance

Symptom burden and its characteristics among survivors of pediatric cancers aged 8 to 18 years remain understudied.

Objective

To examine the prevalence of symptom burden among young childhood cancer survivors and identify associations with sociodemographic, clinical, and psychological resilience skills, and health-related quality of life (HRQOL).

Design, Setting, and Participants

A cross-sectional analysis using data collected from November 1, 2017, to January 31, 2019, in a survivorship clinic at a US-based comprehensive cancer center was conducted. Participants included 302 dyads of children aged 8 to 18 years who survived at least 5 years beyond diagnosis and their primary caregivers. Data analysis was performed from March 13, 2023, to February 29, 2024.

Exposures

Diagnosis, caregiver-reported family conflict, self-reported caregiver anxiety, neighborhood-level social vulnerability, and survivor-reported meaning and purpose.

Main Outcomes and Measures

Novel symptom-level burden, integrating the attributes of severity and daily activity interference using the pediatric version of the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events, global cumulative symptom burden, and HRQOL using the EuroQol-5D. Multinomial logistic regression identified characteristics associated with symptom burden; linear regression assessed symptom burden and HRQOL associations.

Results

Among 302 survivors (mean [SD] age, 14.2 [2.9] years, mean [SD] time since diagnosis, 10.9 [2.9] years; 153 [50.7%] male), 186 (62.0%) had low, 77 (25.7%) moderate, and 37 (12.3%) high global cumulative symptom burden. Greater caregiver anxiety was associated with moderate (risk ratio [RR], 1.56; 95% CI, 1.09-2.24) global symptom burden. Greater neighborhood deprivation was associated with moderate global symptom burden (RR, 4.86; 95% CI, 1.29-18.26). Survivors with greater meaning/purpose were less likely to have moderate (RR, 0.42; 95% CI, 0.29-0.61) and high (RR, 0.27; 95% CI, 0.16-0.46) global symptom burden. The burden of individual symptoms displayed similar patterns. Low (Cohen d, -0.60; 95% CI, -0.87 to -0.32) and moderate/high (d, -0.98; 95% CI, -1.53 to -0.43) general pain, moderate/high numbness (d, -0.99; 95% CI, -1.69 to -0.29), and moderate/high worry (d, -0.55; 95% CI, -0.99 to -0.11) were associated with lower HRQOL.

Conclusions and Relevance

In this cross-sectional study of young childhood cancer survivors, symptom burden was prevalent. Caregiver anxiety and disparity-related neighborhood factors were associated with greater symptom burden, whereas meaning and purpose was a protective factor. Greater specific symptom burden contributed to poorer HRQOL. The findings suggest that interventions targeting resilience and neighborhood adversity may alleviate symptom burden and improve HRQOL.

Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis

PURPOSE

Research on symptom clusters in oncology is progressing, but knowledge gaps remain. One question is whether the number and types of symptom subgroups (i.e., latent classes) differ based on cancer diagnosis. The purpose of this study was to: (1) identify and compare latent class subgroups based on four highly prevalent symptoms (pain, fatigue, sleep disturbance, and depression), and (2) examine the differences in sociodemographic and clinical factors in the identified latent classes across the seven cancer types (i.e., prostate, non-small cell lung, non-Hodgkin's lymphoma, breast, uterine, cervical, and colorectal cancer).

METHODS

This study is a cross-sectional secondary analysis of data obtained from the My-Health study in partnership with four Surveillance, Epidemiology, and End Results (SEER) cancer registries located in California (two), Louisiana, and New Jersey. The sample included 4,762 cancer survivors 6-13 months following diagnosis of one of the seven cancer types mentioned. Latent class profile analysis was used.

RESULTS

Subjects were primarily young (59% age 21-64 years), Caucasian (41%), married/cohabitating (58%) and unemployed (55%). The number and types of symptom subgroups varied across these seven cancer populations: four-subgroups were the common in prostate, lung, non-Hodgkin's lymphoma, and breast cancer survivors. Unmarried, low education, and unemployment status were associated with high risk of symptom burden across the cancer types.

CONCLUSION

Identifying symptom subgroups by cancer diagnosis has the potential to develop innovative and effective targeted interventions in cancer survivors. Further research is needed to establish extensive knowledge in symptom clustering between treatment regimens, and short-term and long-term cancer survivors.

A multiphase study protocol of identifying, and predicting cancer-related symptom clusters: applying a mixed-method design and machine learning algorithms

Objectives

In recent years, there has been increasing attention on the cluster approach to symptom management. Two significant challenges in the symptom cluster (SC) approach are identifying and predicting these clusters. This multiphase protocol aims to identify SCs in patients with advanced cancer as the primary objective, with the secondary objective of developing machine learning algorithms to predict SCs identified in the first phase.

Methods

The 2-MIXIP study consists of two main phases. The first phase involves identifying SCs, and the second phase focuses on developing predictive algorithms for the identified SCs. The identification of SCs involves a parallel mixed-method design (quantitative and qualitative). Quantitative and qualitative methods are conducted simultaneously and given equal importance. The data are collected and analyzed independently before being integrated. The quantitative part is conducted using a descriptive-analytical method. The qualitative analysis is conducted using a content analysis approach. Then, the identified SCs from both parts are integrated to determine the final clusters and use them in the second phase. In the second phase, we employ a tree-based machine learning method to create predictive algorithms for SCs using key demographic and clinical patient characteristics.

Conclusion

The findings of the 2-MIXIP study can help manage cancer patients' symptoms more effectively and enhance clinical decision-making by using SCs prediction. Furthermore, the results of this study can provide guidance for clinical trials aimed at managing symptoms.

Lifetime Burden of Psychological Symptoms, Disorders, and Suicide Due to Cancer in Childhood, Adolescent, and Young Adult Years: A Systematic Review and Meta-analysis

Importance

A cancer diagnosis and treatment may result in highly traumatic periods with lasting psychological consequences for children, adolescent, and young adult patients with cancer (CYACs). Early identification and management may prevent long-term psychological morbidity and suicide.

Objective

To analyze risk, severity, and risk factors for depression, anxiety, psychotic disorders, and suicide in CYACs and noncancer comparators.

Data Sources

Literature search of PubMed, MEDLINE, Embase, PsycINFO, CINAHL, and PubMed Central from January 1, 2000, to November 18, 2022.

Study Selection

Full-length articles in peer-reviewed journals that measured and reported risk and/or severity of depression, anxiety, psychotic disorders, and suicide mortality in CYACs and a noncancer comparator group.

Data Extraction and Synthesis

Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines were followed with prospective PROSPERO registration.

Main Outcomes and Measures

Risk ratios (RRs) were used for dichotomous outcomes, and standardized mean differences (SMDs) were used for continuous outcomes. SMDs were defined as follows: 0.2, small; 0.5, medium; and 0.8, large. Sources of heterogeneity and risk factors were investigated using sensitivity, subgroup, and meta-regression analyses.

Results

From 7319 records, 52 studies were included. Meta-analyses revealed that CYACs were at increased lifetime risk of severe symptoms or a disorder of depression (RR, 1.57; 95% CI, 1.29-1.92), anxiety (RR, 1.29; 95% CI, 1.14-1.47), and psychotic disorders (RR, 1.56; 95% CI, 1.36-1.80) relative to both matched controls and their siblings. Overall suicide mortality was not significantly elevated (RR, 1.63; 95% CI, 0.78-3.40). The mean severity of depression was found to be elevated in CYACs receiving treatment (SMD, 0.44; 95% CI, 0.13-0.74) and long-term survivors (SMD, 0.18; 95% CI, 0.02-0.33). The mean severity of anxiety was found to be elevated only during treatment (SMD, 0.16; 95% CI, 0.03-0.20).

Conclusions and Relevance

Findings of this systematic review and meta-analysis suggest that CYACs may experience lasting psychological burden long into survivorship. Timely identification, preventive efforts, and psycho-oncological intervention for psychological comorbidity are recommended.

Global Impact of Monoclonal Antibodies (mAbs) in Children: A Focus on Anti-GD2

Monoclonal antibodies (mAbs), as the name implies, are clonal antibodies that bind to the same antigen. mAbs are broadly used as diagnostic or therapeutic tools for neoplasms, autoimmune diseases, allergic conditions, and infections. Although most mAbs are approved for treating adult cancers, few are applicable to childhood malignancies, limited mostly to hematological cancers. As for solid tumors, only anti-disialoganglioside (GD2) mAbs are approved specifically for neuroblastoma. Inequities of drug access have continued, affecting most therapeutic mAbs globally. To understand these challenges, a deeper dive into the complex transition from basic research to the clinic, or between marketing and regulatory agencies, is timely. This review focuses on current mAbs approved or under investigation in pediatric cancer, with special attention on solid tumors and anti-GD2 mAbs, and the hurdles that limit their broad global access. Beyond understanding the mechanisms of drug resistance, the continual discovery of next generation drugs safer for children and easier to administer, the discovery of predictive biomarkers to avoid futility should ease the acceptance by patient, health care professionals and regulatory agencies, in order to expand clinical utility. With a better integration into the multimodal treatment for each disease, protocols that align with the regional clinical practice should also improve acceptance and cost-effectiveness. Communication and collaboration between academic institutions, pharmaceutical companies, and regulatory agencies should help to ensure accessible, affordable, and sustainable health care for all.

Severity and Longitudinal Course of Depression, Anxiety and Post-Traumatic Stress in Paediatric and Young Adult Cancer Patients: A Systematic Review and Meta-Analysis

BACKGROUND

A diagnosis of cancer and treatment may constitute a highly traumatic period for paediatric cancer patients (PYACPs). However, no review has comprehensively analysed how the mental health of PYACPs is acutely affected and the longitudinal course.

METHODS

This systematic review followed PRISMA guidelines. Comprehensive searches of databases were conducted to identify studies of depression, anxiety and post-traumatic stress symptoms in PYACPs. Random effects meta-analyses were used for the primary analysis.

RESULTS

From 4898 records, 13 studies were included. Acutely after diagnosis, depressive and anxiety symptoms were significantly elevated in PYACPs. Depressive symptoms only significantly decreased after 12 months (standardised mean difference, SMD = -0.88; 95% CI: -0.92, -0.84). This downward trajectory persisted to 18 months (SMD = -1.862; 95% CI: -1.29, -1.09). Anxiety symptoms similarly only decreased after 12 (SMD = -0.34; 95% CI: -0.42, -0.27) up to 18 months (SMD = -0.49; 95% CI: -0.60, -0.39) after the cancer diagnosis. Post-traumatic stress symptoms showed protracted elevations throughout follow-up. Overall, significant predictors of poorer psychological outcomes included unhealthy family functioning, concomitant depression or anxiety, poor cancer prognosis or experiencing cancer and treatment-related side effects.

CONCLUSIONS

While depression and anxiety may improve over time with a favourable environment, post-traumatic stress may have a protracted course. Timely identification and psycho-oncological intervention are critical.

Ten Considerations for Integrating Patient-Reported Outcomes into Clinical Care for Childhood Cancer Survivors

Patient-reported outcome measures (PROMs) are subjective assessments of health status or health-related quality of life. In childhood cancer survivors, PROMs can be used to evaluate the adverse effects of cancer treatment and guide cancer survivorship care. However, there are barriers to integrating PROMs into clinical practice, such as constraints in clinical validity, meaningful interpretation, and technology-enabled administration of the measures. This article discusses these barriers and proposes 10 important considerations for appropriate PROM integration into clinical care for choosing the right measure (considering the purpose of using a PROM, health profile vs. health preference approaches, measurement properties), ensuring survivors complete the PROMs (data collection method, data collection frequency, survivor capacity, self- vs. proxy reports), interpreting the results (scoring methods, clinical meaning and interpretability), and selecting a strategy for clinical response (integration into the clinical workflow). An example framework for integrating novel patient-reported outcome (PRO) data collection into the clinical workflow for childhood cancer survivorship care is also discussed. As we continuously improve the clinical validity of PROMs and address implementation barriers, routine PRO assessment and monitoring in pediatric cancer survivorship offer opportunities to facilitate clinical decision making and improve the quality of survivorship care.