Response-shift effects in childhood cancer survivors: A prospective study.

BACKGROUND: Treatment-related late effects can worsen over time among cancer survivors. Such worsening health states may trigger changes in internal standards, values, or conceptualization of quality-of-life (QOL). This "response-shift" phenomenon can jeopardize the validity of QOL assessment, and misrepresent QOL comparisons over time. This study tested response-shift effects in reporting future-health concerns among childhood cancer survivors who experienced progression in chronic health conditions (CHCs). METHODS: 2310 adult survivors of childhood cancer from St. Jude Lifetime Cohort Study completed a survey and clinical assessment at two or more timepoints. Based on 190 individual CHCs graded for adverse-event severity, global CHC burden was classified as "progression" or "non-progression". QOL was assessed using the SF-36TM eight domains and physical- and mental-component summary scores (PCS, MCS). A single global item measured concerns about future health. Random-effects models comparing survivors with and without progressive global CHC burden (progressors vs. non-progressors) evaluated response-shift effects (recalibration, reprioritization, reconceptualization) in reporting future-health concerns. RESULTS: Compared with non-progressors, progressors were more likely to de-emphasize (or downplay) overall physical and mental health in evaluating future-health concerns (p-values<0.05), indicating recalibration response-shift, and more likely to de-emphasize physical health earlier rather than later in follow-up (p-value<0.05), indicating reprioritization response-shift. There was evidence for a reconceptualization response-shift with progressor classification associated with worse-than-expected future-health concerns and physical health, and better-than-expected pain and role-emotional functioning (p-values<0.05). CONCLUSION: We identified three types of response-shift phenomena in reporting concerns about future health among childhood cancer survivors. Survivorship care or research should consider response-shift effects when interpreting changes in QOL over time.

Stronger association of perceived health with socio-economic inequality during COVID-19 pandemic than pre-pandemic era.

OBJECTIVE: The COVID-19 pandemic has changed peoples' routine of daily living and posed major risks to global health and economy. Few studies have examined differential impacts of economic factors on health during pandemic compared to pre-pandemic. We aimed to compare the strength of associations between perceived health and socioeconomic position (household income, educational attainment, and employment) estimated before and during the pandemic. METHODS: Two waves of nationwide survey [on 2018(T1;n = 1200) and 2021(T2;n = 1000)] were done for 2200 community adults. A balanced distribution of confounders (demographics and socioeconomic position) were achieved across the T2 and T1 by use of the inverse probability of treatment weighting. Distributions of perceived health [= (excellent or very good)/(bad, fair, or good)] for physical-mental-social-spiritual subdomains were compared between T1 and T2. Odds of bad/fair/good health for demographics and socioeconomic position were obtained by univariate logistic regression. Adjusted odds (aOR) of bad/fair/good health in lower household income(< 3000 U.S. dollars/month) were retrieved using the multiple hierarchical logistic regression models of T1 and T2. RESULTS: Perceived health of excellent/very good at T2 was higher than T1 for physical(T1 = 36.05%, T2 = 39.13%; P = 0.04), but were lower for mental(T1 = 38.71%, T2 = 35.17%; P = 0.01) and social(T1 = 42.48%, T2 = 35.17%; P < 0.001) subdomains. Odds of bad/fair/good health were significantly increased at T2 than T1 for household income (physical-mental-social; all Ps < 0.001) and educational attainment (social; P = 0.04) but not for employment (all Ps > 0.05). AORs of bad/fair/good health in lower household income were stronger in T2 than T1, for mental [aOR (95% CI) = 2.15(1.68-2.77) in T2, 1.33(1.06-1.68) in T1; aOR difference = 0.82(P < 0.001)], physical [aOR (95% CI) = 2.64(2.05-3.41) in T2, 1.50(1.18-1.90) in T1; aOR difference = 1.14(P < 0.001)] and social [aOR (95% CI) = 2.15(1.68-2.77) in T2, 1.33(1.06-1.68) in T1; aOR difference = 0.35(P = 0.049)] subdomains. CONCLUSIONS: Risks of perceived health worsening for mental and social subdomains in people with lower monthly household income or lower educational attainment became stronger during the COVID-19 pandemic compared to pre-pandemic era. In consideration of the prolonged pandemic as of mid-2022, policies aiming not only to sustain the monthly household income and compulsory education but also to actively enhance the perceived mental-social health status have to be executed and maintained.

Association of co-morbidities with financial hardship in survivors of adult cancer.

PURPOSE: To evaluate the impact of co-morbidities on financial hardship in adult cancer survivors and the role of health insurance and a usual source of care (i.e., a particular doctor's office/health center/other place that the person usually goes if he/she is sick or needs advice) in relieving this impact. METHODS: Using the Medical Expenditure Panel Survey, we estimated prevalence of two financial hardships, out-of-pocket (OOP) burden and financial worry, among 1196 adult cancer survivors. A modified Charlson co-morbidity index (CCI) assessed co-morbidities, which represent a medical event (e.g., a doctor's appointment) associated with co-morbid conditions within the past 1 year. Multivariable logistic regression tested the influence of health insurance and a usual source of care on associations of co-morbidities with financial hardship by middle/high vs. low-income families and by working vs. retirement-age individuals. RESULTS: Years since cancer diagnosis ranged from 0 to 76 years (mean: 10.3, SD: 9.8), 10 and 25% of survivors experienced OOP burden and financial worry. For OOP burden, increased CCI was a risk factor among survivors of low-income families, ORs: 1.91 (95% CI: 1.06, 3.46) for a CCI 1-2 and 3.37 (95% CI: 1.72, 6.61) for a CCI ≥ 3 vs. CCI of 0. For financial worry, increased CCI was a risk factor among working-age survivors, ORs: 1.58 (95% CI: 1.02, 2.47) for a CCI 1-2 and 2.15 (95% CI: 1.19, 3.87) for a CCI ≥ 3 vs. CCI of 0. However, having health insurance and a usual source of care did not mitigate impact of co-morbidities on financial hardship (P values > 0.05). CONCLUSIONS: Impact of co-morbidities on OOP and financial worry burden was greatest in survivors of low-income families and working-age, respectively. Health insurance and a usual source of care did not relieve the impact of co-morbidities on financial hardship. IMPLICATIONS: Effective strategies are warranted to mitigate financial hardship for survivors.

Natural Language Processing and Machine Learning Methods to Characterize Unstructured Patient-Reported Outcomes: Validation Study.

BACKGROUND: Assessing patient-reported outcomes (PROs) through interviews or conversations during clinical encounters provides insightful information about survivorship. OBJECTIVE: This study aims to test the validity of natural language processing (NLP) and machine learning (ML) algorithms in identifying different attributes of pain interference and fatigue symptoms experienced by child and adolescent survivors of cancer versus the judgment by PRO content experts as the gold standard to validate NLP/ML algorithms. METHODS: This cross-sectional study focused on child and adolescent survivors of cancer, aged 8 to 17 years, and caregivers, from whom 391 meaning units in the pain interference domain and 423 in the fatigue domain were generated for analyses. Data were collected from the After Completion of Therapy Clinic at St. Jude Children's Research Hospital. Experienced pain interference and fatigue symptoms were reported through in-depth interviews. After verbatim transcription, analyzable sentences (ie, meaning units) were semantically labeled by 2 content experts for each attribute (physical, cognitive, social, or unclassified). Two NLP/ML methods were used to extract and validate the semantic features: bidirectional encoder representations from transformers (BERT) and Word2vec plus one of the ML methods, the support vector machine or extreme gradient boosting. Receiver operating characteristic and precision-recall curves were used to evaluate the accuracy and validity of the NLP/ML methods. RESULTS: Compared with Word2vec/support vector machine and Word2vec/extreme gradient boosting, BERT demonstrated higher accuracy in both symptom domains, with 0.931 (95% CI 0.905-0.957) and 0.916 (95% CI 0.887-0.941) for problems with cognitive and social attributes on pain interference, respectively, and 0.929 (95% CI 0.903-0.953) and 0.917 (95% CI 0.891-0.943) for problems with cognitive and social attributes on fatigue, respectively. In addition, BERT yielded superior areas under the receiver operating characteristic curve for cognitive attributes on pain interference and fatigue domains (0.923, 95% CI 0.879-0.997; 0.948, 95% CI 0.922-0.979) and superior areas under the precision-recall curve for cognitive attributes on pain interference and fatigue domains (0.818, 95% CI 0.735-0.917; 0.855, 95% CI 0.791-0.930). CONCLUSIONS: The BERT method performed better than the other methods. As an alternative to using standard PRO surveys, collecting unstructured PROs via interviews or conversations during clinical encounters and applying NLP/ML methods can facilitate PRO assessment in child and adolescent cancer survivors.

The Association of the Health Management Strategy with Subjective Health and Well-being Outcomes in General Population.

BACKGROUND: People face many obstacles to overcoming crisis in life and proactively manage life crises. This study aimed to evaluate the association of self-management strategy with subjective health and well-being for the general South Korean population. METHODS: We recruited 1,200 respondents using an equal-probability sampling method from March to May 2018. A questionnaire including life version of the Smart Management Strategy for Health Assessment Tool (SAT-Life), the five Health Status Questionnaire, Short Form-12, McGill Quality of Life Questionnaire (MQOL), Patient Health Questionnaire-9 (PHQ-9), and Satisfaction With Life Scale (SWLS) was administered to participants. RESULTS: In multiple stepwise logistic regression model adjusted with basic demographic variables (age, sex, region, education and monthly income level), core strategy was independently associated with physical, mental, social, spiritual, and general health status (adjusted odds ratios [aORs], 1.97-2.92). Preparation strategy was independently associated with physical, mental, spiritual, and general health status (aORs, 2.36-3.31). Implementation strategy was independently associated with physical, social, spiritual, and general health status (aORs, 2.22-2.42). Core strategy and implementation strategy were independently associated with higher Physical Component Score (aORs, 2.21-2.29) and higher Mental Component Score (aORs, 1.68-1.76). Core strategy and preparation strategy were independently associated with lower PHQ-9 (aORs, 2.63-3.74). Pearson's correlation coefficients between scores on SAT-Life and the other factors (MQOL social support, MQOL spiritual well-being, and SWLS) explain having significant correlations ranging from 0.41-0.43. CONCLUSION: Self-management strategies of health might be encouraged to manage subjective health and well-being outcomes.

Efficacy of health coaching and a web-based program on physical activity, weight, and distress management among cancer survivors: A multi-centered randomised controlled trial.

OBJECTIVES: To investigate the efficacy of health coaching and a web-based program on survivor physical activity (PA), weight, and distress management among stomach, colon, lung and breast cancer patients. METHODS: This randomised, controlled, 1-year trial conducted in five hospitals recruited cancer survivors within 2 months of completing primary cancer treatment who had not met ≥1 of these behavioural goals: (i) conducting moderate PA for at least 150 minutes/week or strenuous exercise for over 75 minutes per week or, in the case of lung cancer patients, low or moderate intensity exercise for over 12.5 MET per week, (ii) maintaining normal weight, and (iii) attaining a score >72 in the Post Traumatic Growth Inventory (PTGI). Participants were randomly assigned to one of three groups: the control group, a web-only group, or a health coaching + web group. The primary endpoint was based on a composite of PA, weight, and PTGI score at 12 months. RESULTS: Patients in the health coaching + web group (difference = 6.6%, P = .010) and the web-only group (difference = 5.9%, P = .031) had greater overall improvements across the three-outcome composite than the control group. The health coaching + web group had greater overall improvement in PTGI (difference = 12.6%; P < .001) than the control group, but not in PA and weight. CONCLUSION: The web-based program, with or without health coaching, may improve health behaviours including PA, weight, and distress management among cancer survivors within 2 months of completing primary cancer treatment. The web-based program with health coaching was mainly effective for reducing psychological distress.

Efficacy of an Electronic Health Management Program for Patients With Cardiovascular Risk: Randomized Controlled Trial.

BACKGROUND: In addition to medication, health behavior management is crucial in patients with multiple risks of cardiovascular mortality. OBJECTIVE: This study aimed to examine the efficacy of a 3-month Smart Management Strategy for Health-based electronic program (Smart Healthing). METHODS: A 2-arm randomized controlled trial was conducted to assess the efficacy of Smart Healthing in 106 patients with at least one indicator of poor disease control and who had hypertension, diabetes, or hypercholesterolemia. The intervention group (n=53) took part in the electronic program, which was available in the form of a mobile app and a Web-based PC application. The program covered 4 areas: self-assessment, self-planning, self-learning, and self-monitoring by automatic feedback. The control group (n=53) received basic educational material concerning disease control. The primary outcome was the percentage of participants who achieved their clinical indicator goal after 12 weeks into the program: glycated hemoglobin (HbA1c) <7.0%, systolic blood pressure (SBP) <140 mmHg, or low-density lipoprotein cholesterol <130 mg/dL. RESULTS: The intervention group showed a significantly higher success rate (in comparison with the control group) for achieving each of 3 clinical indicators at the targeted goal levels (P<.05). Only the patients with hypertension showed a significant improvement in SBP from the baseline as compared with the control group (72.7% vs 35.7%; P<.05). There was a significant reduction in HbA1c in the intervention group compared with the control group (difference=0.54%; P≤.05). In the intervention group, 20% of patients with diabetes exhibited a ≥1% decrease in HbA1c (vs 0% among controls; P≤.05). CONCLUSIONS: A short-term self-management strategy-based electronic program intervention may improve clinical outcomes among patients with cardiovascular risks. TRIAL REGISTRATION: ClinicalTrials.gov NCT03294044; https://clinicaltrials.gov/ct2/show/NCT03294044.

Erratum: Correction of the Text in the Article "Table": Discordance between Physician and the General Public Perceptions of Prognostic Disclosure to Children with Serious Illness: a Korean Nationwide Study.

This corrects the article on e327 in vol. 33, PMID: 30505258.

Correction to: Priorities of a "good death" according to cancer patients, their family caregivers, physicians, and the general population: a nationwide survey.

While recently extending that research, however, we discovered that 236 members of the general population were mistakenly duplicated by the investigating agency (Word Research) and 1241 were reported rather than 1005. Here, we present corrections and discuss the relevant data.

Regional Differences in Colorectal Cancer Mortality Between 2000 and 2013 in Republic of Korea.

OBJECTIVE: Colorectal cancer (CRC) is the fourth most common site for cancer death in the Republic of Korea. The aim of this study was to describe the trends of colorectal cancer mortality by region. METHODS: CRC mortality trends in Republic of Korea were described by region using a Joinpoint regression model in both sexes. The annual percent changes (APCs) were calculated for each segment. Visualization of the changes in mortality rate of colorectal cancer death rates by 16 geographic areas in both sexes between 2000-2004 and 2009-2013 were also conducted. RESULTS: CRC mortality rates of men showed decreasing trend after increase in Daegu, Gyeongsangnam-do, and Chungcheongbuk-do between 2000 and 2013 based on the joinpoint model, while Gwangju, Jeollabuk-do, Jeollanam-do, and Gyeongsangbuk-do showed increase in CRC mortality during the same period. For women, CRC mortality of Seoul, Incheon, Daejeon, and Gyeongsangnam-do started to decrease in 2005, 2003, 2007, and 2006, respectively. The mortality rate for CRC in the eastern regions, which had relatively low rates of CRC among men in 2000 through 2004, reached a level similar to that in the northwestern regions of 2009 through 2013, while the highest CRC mortality rates in women was observed in Chungcheongbuk-do. CONCLUSIONS: Reduction in CRC mortality varied across 16 metropolitan cities and provinces in men, and the visualization pattern showed that the east side of South Korea had the least progress in mortality reduction.