Age-related differences in the occurrence, severity, and distress of symptoms in older patients at the initiation of chemotherapy

Effectiveness of ePRO-based symptom management for cancer patients: a systematic review and meta-analysis of randomized controlled studies

PURPOSE

To systematically synthesize the evidence on the effectiveness of electronic patient-reported outcome (ePRO)-based symptom management on readmission rate, quality of life, symptom burden, anxiety, depression, and mortality in adult cancer patients.

METHOD

A systematic review and meta-analysis were conducted according to the PRISMA guideline in PubMed, Web of Science, EMBASE, the Cochrane Library, CINAHL, and Scopus for studies of randomized controlled trials reporting ePRO-based symptom management from January 1st, 2018, to May 31st, 2023. Two reviewers independently assessed risk-of-bias using Cochrane Risk-of-Bias version 2 and extracted the data. Subgroup analysis was conducted to identify the source of heterogeneity. Sensitivity analysis was performed by using the leave-one-out method. The study protocol was registered on the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) (DOI: https://doi.org/10.37766/inplasy2023.6.0010 ).

RESULTS

A total of 10 studies were included in our review, comprising a total of 5321 participants. The results showed ePRO-based symptom management can improve quality of life (QOL) (SMD = 4.42, 95% CI 0.14 to 8.69, P = 0.04) in cancer patients. No significant differences in the impact on the improvement of readmission rate (RR = 0.89, 95% CI 0.77 to 1.04, P = 0.15), symptom burden (SMD = 1.23, 95% CI - 1.34 to 3.79, P = 0.35), anxiety (SMD =  - 0.00, 95% CI - 0.34 to 0.34, P = 0.99), depression (SMD = 0.03, 95% CI - 0.17 to 0.24, P = 0.74), and mortality (RR = 0.59, 95% CI 0.19 to 1.83, P = 0.36) between the two groups. In the subgroup analysis, readmission rates more than 30 days were significantly lower in the intervention group compared to the control group (relative rate (RR) = 0.85, 95% CI 0.72 to 0.99, P = 0.03). Also, the intervention group's QOL significantly improved compared to the control group when assessed within 1 month after the intervention (SMD = 4.35, 95% CI 3.75 to 4.94, P < 0.00001). In the sensitivity analysis, it was found that the results for readmission rates and quality of life (QOL) were unstable, indicating that further research is needed in the future.

CONCLUSION

Cancer patients often have different symptoms. Symptom management in cancer patients is an emerging topic. However, due to the limited numbers of included studies, the long-term effect of ePRO-based symptom management still needed to be validated.

REGISTRATION DETAILS

inplasy (DOI: https://doi.org/10.37766/inplasy2023.6.0010 ).

Implicit memory reduced selectively for negative words with aging

Background

Disproportionally better memory for positive versus negative information (mnemonic positivity effect, MPE) in older versus younger adults has been reported on tests of explicit memory (direct, intentional) as measured by recall and recognition. The purpose of this investigation was to examine whether the MPE would be observed for implicit memory (indirect, unintentional) under conditions where, based on previous research using single words, it was expected that the MPE for explicit memory would be absent.

Methods

This study investigated the influence of age on explicit and implicit memory for positive, negative, and neutral single words as measured by yes/no recognition and word identification on 24 older adults (aged 66-85) and 24 younger adults (aged 18-37) recruited from community centers in South Boston, Massachusetts.

Results

Older adults had lower recognition memory accuracy for positive, negative, and neutral words than younger adults, and, consistent with most prior studies, did not exhibit an explicit memory MPE for single words. For both groups, recognition accuracy was greatest for negative words, and was similar for positive and neutral words. In contrast, older adults exhibited implicit repetition priming, as measured by superior identification performance for repeated words, that was similar to younger adults for positive and neutral words. In younger adults, implicit memory was significantly greater for negative words than for positive and neutral words, whereas in older adults there were no significant differences in implicit memory for negative, positive, and neutral words. Therefore, selectively reduced priming for negative words in older adults was found in the context of enhanced priming for negative words in the younger adults.

Conclusion

These findings show that there was an implicit memory MPE in older adults for words even under conditions where there was no explicit memory MPE in the older adults. Dampening of negative valence implicit memory with aging expands the perimeter of the age-related positivity framework.

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.

Stability and consistency of symptom clusters in younger versus older patients receiving chemotherapy

BACKGROUND

By 2035, the number of newly diagnosed cancer cases will double and over 50% will be in older adults. Given this rapidly growing demographic, a need exists to understand how age influences oncology patients' symptom burden. The study purposes were to evaluate for differences in the occurrence, severity, and distress of 38 symptoms in younger (< 60 years) versus older (≥ 60 years) oncology patients undergoing chemotherapy and to evaluate for differences in the stability and consistency of symptom clusters across the two age groups.

METHODS

A total of 1329 patients were dichotomized into the younger and older groups. Patients completed demographic and clinical questionnaires prior to the initiation of their second or third cycle of chemotherapy. A modified version of Memorial Symptom Assessment Scale was used to evaluate the occurrence, severity, and distress of 38 common symptoms associated with cancer and its treatment. Differences between the two age groups in demographic and clinical characteristics and ratings of occurrence, severity, and distress for the 38 symptoms were evaluated using parametric and nonparametric tests. Exploratory factor analyses were done within each age group to identify symptom clusters using symptom occurrence rates.

RESULTS

Compared to the younger group (14.8 (± 7.0)), older adults reported a lower mean number of symptoms (12.9 (± 7.2)). Older patients experienced lower occurrence rates for almost 50% of the symptoms. Regarding symptom clusters, an eight-factor solution was selected for both age groups. Across the two age groups, the eight symptom clusters (i.e., physical and cognitive fatigue, respiratory, psychological, hormonal, chemotherapy-related toxicity, weight gain, gastrointestinal, epithelial) were stable. However, symptoms within the physical and cognitive, chemotherapy-related toxicity, and gastrointestinal clusters were not consistent across the age groups.

CONCLUSIONS

To be able to provide tailored and effective symptom management interventions to older oncology patients, routine assessments of the core symptoms unique to the symptom clusters identified for this group warrants consideration. The underlying mechanism(s) for these inconsistencies in symptom burden is an important focus for future studies.

Common and distinct risk factors that influence more severe and distressing shortness of breath profiles in oncology outpatients

BACKGROUND

Shortness of breath occurs in 10%-70% of oncology patients. Very little is known about interindividual variability in its severity and distress and associated risk factors. Using latent profile analyses (LPAs), purpose was to identify subgroups of patients with distinct severity and distress profiles for shortness of breath as single symptom dimensions. In addition, a joint LPA was done using patients' severity AND distress ratings. For each of the three LPAs, differences among the shortness of breath classes in demographic, clinical, symptom, stress, and resilience characteristics were evaluated.

METHODS

Patients completed ratings of severity and distress from shortness of breath a total of six times over two cycles of chemotherapy. All of the other measures were completed at enrollment (i.e., prior to the second or third cycle of chemotherapy). Separate LPAs were done using ratings of severity and distress, as well as a joint analysis using severity AND distress ratings. Differences among the latent classes were evaluated using parametric and nonparametric tests.

RESULTS

For severity, two classes were identified (Slight to Moderate [91.6%] and Moderate to Severe [8.4%]). For distress, two classes were identified (A Little Bit to Somewhat [83.9%] and Somewhat to Quite a Bit [16.1%]). For the joint LPA, two classes were identified (Lower Severity and Distress [79.9%] and Higher Severity and Distress [20.1%]). While distinct risk factors were associated with each of the LPAs, across the three LPAs, the common risk factors associated with membership in the worse class included: a past or current history of smoking, poorer functional status, and higher comorbidity burden. In addition, these patients had a higher symptom burden and higher levels of cancer-specific stress.

CONCLUSIONS

Clinicians can use the information provided in this study to identify high-risk patients and develop individualized interventions.