Efficacy of acupuncture for a cough-related symptom cluster in patients with lung cancer: A randomized controlled trial.

PURPOSE: This study was designed to evaluate the effect of acupuncture on cough, expectoration, and shortness of breath in lung cancer patients. METHODS: Between December 2021 and June 2022, a total of 130 lung cancer patients were recruited, and they were split into control and intervention groups at random. Routine nursing was provided to the control group, whereas routine nursing with acupuncture using LU7 (Lie Que), LU9 (Tai Yuan), BL13 (Fei Shu), and BL20 (Pi Shu) was administered to the intervention group for 7 days. The severity of cough, expectoration, and shortness of breath was assessed 1 day before and after the interventions using the lung cancer-specific module of the MDASI. A two-way ANOVA was performed for group comparisons. RESULTS: Compared with the control group, the symptoms of cough in the intervention group were significantly improved (F = 5.095, MD = -0.32, 95% CI, -0.59 to 0.04, P = 0.025), while expectoration (F = 0.626, MD = -0.11, 95% CI, -0.38 to 0.16, P = 0.430) and shortness of breath (F = 0.165, MD = -0.05, 95% CI, -0.27 to 0.18, P = 0.685) had no significant change. Cough also identified an obvious interaction effect (P = 0.014), and the post-intervention simple main effect test demonstrated a tangible difference between the two groups (MD = -0.66, 95% CI, -0.99 to 0.33, P < 0.001) post-intervention. CONCLUSIONS: Acupuncture using LU7, LU9, BL13, and BL20 can relieve the cough of lung cancer patients, but not relieve expectoration and shortness of breath.

Brain connectomics improve prediction of 1-year decreased quality of life in breast cancer: A multi-voxel pattern analysis.

PURPOSE: Whether brain connectomics can predict 1-year decreased Quality of Life (QoL) in patients with breast cancer are unclear. A longitudinal study was utilized to explore their prediction abilities with a multi-center sample. METHODS: 232 breast cancer patients were consecutively enrolled and 214 completed the 1-year QoL assessment (92.2%). Resting state functional magnetic resonance imaging was collected before the treatment and a multivoxel pattern analysis (MVPA) was performed to differentiate whole-brain resting-state connectivity patterns. Net Reclassification Improvement (NRI) as well as Integrated Discrimination Improvement (IDI) were calculated to estimate the incremental value of brain connectomics over conventional risk factors. RESULTS: Paracingulate Gyrus, Superior Frontal Gyrus and Frontal Pole were three significant brain areas. Brain connectomics yielded 7.8-17.2% of AUC improvement in predicting 1-year decreased QoL. The NRI and IDI ranged from 20.27 to 54.05%, 13.21-33.34% respectively. CONCLUSION: Brain connectomics contribute to a more accurate prediction of 1-year decreased QoL in breast cancer. Significant brain areas in the prefrontal lobe could be used as potential intervention targets (i.e., Cognitive Behavioral Group Therapy) to improve long-term QoL outcomes in breast cancer.

Heterogeneity in resilience patterns and its prediction of 1-year quality of life outcomes among patients with newly diagnosed cancer: An exploratory piecewise growth mixture model analysis.

PURPOSE: This study was designed to explore the impact of a new cancer diagnosis on resilience of patients and whether the resilience patterns could predict Quality of Life (QoL) in the first year. METHODS: An exploratory linear piecewise growth mixture modeling (PGMM) with one hypothetical dot (3 months since diagnosis, T1) was employed to identify different resilience patterns and growth in 289 patients with different cancer diagnoses at five assessment occasions (T0-T4). Logistic regression analysis was performed to select potential predictors and receiver operating characteristic (ROC) curve analysis was utilized to test PGMM's discriminative ability against 1-year QoL. RESULTS: Five discrete resilience trajectories with two growing trends were identified, including "Transcendence" (7.3%), "Resilient" (47.4%), "Recovery" (18.7%), "Damaged" (14.9%) and "Maladaption" (11.8%). Advanced stage, colorectal cancer, and receiving surgery therapy were significant predictors of negative resilience trajectories ("Damaged" or "Maladaption"). Discriminative ability was good for PGMM (AUC = 0.81, 95%CI, 0.76-0.85, P < 0.0001). CONCLUSION: Heterogeneity is identified in resilience growth before and after 3 months since diagnosis. 26.7% newly diagnosed patients need additional attention especially for those with advanced colorectal cancer and receiving surgery therapy.

Measuring resilience by cognitive diagnosis models and its prediction of 6-month quality of life in Be Resilient to Breast Cancer (BRBC).

Objective: The application of advanced Cognitive Diagnosis Models (CDMs) in the Patient Reported Outcome (PRO) is limited due to its complex statistics. This study was designed to measure resilience using CDMs and its prediction of 6-month Quality of Life (QoL) in breast cancer. Methods: A total of 492 patients were longitudinally enrolled from Be Resilient to Breast Cancer (BRBC) and administered with 10-item Resilience Scale Specific to Cancer (RS-SC-10) and Functional Assessment of Cancer Therapy-Breast (FACT-B). Generalized Deterministic Input, Noisy "And" Gate (G-DINA) was performed to measure cognitive diagnostic probabilities (CDPs) of resilience. Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) were utilized to estimate the incremental prediction value of cognitive diagnostic probabilities over total score. Results: CDPs of resilience improved prediction of 6-month QoL above conventional total score. AUC increased from 82.6-88.8% to 95.2-96.5% in four cohorts (all P < 0.001). The NRI ranged from 15.13 to 54.01% and IDI ranged from 24.69 to 47.55% (all P < 0.001). Conclusion: CDPs of resilience contribute to a more accurate prediction of 6-month QoL above conventional total score. CDMs could help optimize Patient Reported Outcomes (PROs) measurement in breast cancer.

Proteomic and metabolomic approaches elucidate the molecular mechanism of emodin against neuropathic pain through modulating the gamma-aminobutyric acid (GABA)-ergic pathway and PI3K/AKT/NF-κB pathway.

Neuropathic pain (NeP) is a major health concern. Due to the complex pathological mechanisms, management of NeP is challenging. Emodin, a natural anthraquinone derivative, exerts excellent analgesic effects. However, its mechanisms of action are still poorly understood. In this study, we investigated the mechanisms underlying pain-relief effects of emodin in the cerebral cortex using proteomic and metabolomic approaches. After 15 days of emodin administration, the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) values in the emodin groups were significantly higher than those in the chronic constriction injury (CCI) group (p < .05), suggesting emodin treatment could reverse CCI-induced hyperalgesia. Emodin treatment evoked the expression alteration of 402 proteins (153 up-regulated and 249 down-regulated) in the CCI models, which were primarily involved in PI3K/AKT signaling pathway, gamma-aminobutyric acid (GABA) receptor signaling, complement and coagulation cascades, cGMP/PKG signaling pathway, MAPK signaling pathway, and calcium signaling pathway. In parallel, emodin intervention regulated the abundance alteration of 27 brain metabolites (20 up-regulated and 7 down-regulated) in the CCI rats, which were primarily implicated in carbon metabolism, biosynthesis of amino acids, pentose phosphate pathway, and glucagon signaling pathway. After a comprehensive analysis and western blot validation, we demonstrated that emodin alleviated NeP mainly through regulating GABAergic pathway and PI3K/AKT/NF-κB pathway.

Resilience index improves prediction of 1-year decreased quality of life in breast cancer.

BACKGROUND: Resilience is important in cancer survivorship and has great potential to predict long-term quality of life (QoL) in breast cancer. The study was designed to develop a new prediction model to estimate pretest probability (PTP) of 1-year decreased QoL combing Resilience Index (RI) and conventional risk factors. METHODS: RI was extracted from 10-item Resilience Scale Specific to Cancer (RS-SC-10) based on the Principal Component Analysis (PCA). Patients were enrolled from Be Resilient to Breast Cancer (BRBC) and the prediction model was developed based on a sample of 506 consecutive patients and validated in an internal cohort (N1 = 314) and two external cohorts (N2 = 223 and N3 = 189). Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) were utilized to estimate the incremental value of RI. RESULTS: RI improved prediction above conventional risk factors. AUC increased from 0.745 to 0.862 while IDI and NRI were 8.39% and 18.44% respectively (P < 0.0001 for all). Five predictors were included in the final model: RI, age, N stage, M stage, and baseline QoL. The new model demonstrated good calibration ability in the internal and external cohorts resulting in C-indexes of 0.862 (95%CI, 0.815-0.909), 0.828 (95%CI, 0.745-0.910), 0.880 (95%CI, 0.816-0.944), and 0.869 (95%CI, 0.796-0.941). CONCLUSION: RI contributed to a more accurate estimation for PTP of 1-year decreased QoL above conventional risk factors and could help optimize decision making of treatment for breast cancer. IMPLICATIONS FOR CANCER SURVIVORS: A promising prognostic indicator of RI could improve QoL-related management in Chinese patients with breast cancer.

Systems biology strategy and experimental validation to uncover the pharmacological mechanism of Xihuang Pill in treating non-small cell lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for almost 85% of lung cancer-related deaths worldwide. Xihuang Pill (XHP) is a representative anticancer Chinese patented medicine used to treat NSCLC in China. However, to date, a systematic analysis of XHP's antitumour effects and its impact on the immune microenvironment has not been performed. PURPOSE: Based on the systems biology strategy and experimental validation, the present study aimed to investigate the pharmacological mechanisms involved in treating NSCLC with XHP. METHODS: A subcutaneous tumour model was established to evaluate XHP's tumour-inhibitory effect in BALB/c nude mice. RNA sequencing (RNA-seq) and bioinformatics analysis were conducted to identify differentially expressed genes (DEGs) and signalling pathways related to XHP treatment. Network analysis based on network pharmacology and protein-to-protein networks was applied to identify the compounds and genes targeted by XHP. External data from the TCGA-NSCLC cohort were used to verify the clinical significance of XHP-targeted genes in NSCLC. The expression of survival-related candidate genes after XHP treatment was verified via qPCR. The protein expression of calcium voltage-gated channel subunit alpha 1C (CACNA1C) in different NSCLC cell lines was analysed in the Human Protein Atlas database (HPA) and DepMap Portal. Using the Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm and the single-sample gene set enrichment analysis (ssGSEA) algorithm uncovered the role of CACNA1C in the NSCLC tumour microenvironment (TME). RESULTS: XHP (2 g/kg/d) significantly inhibited the growth of transplanted A549 tumours. RNA-seq identified a total of 529 DEGs (189 upregulated and 340 downregulated). In addition, 542 GO terms, 41 significant KEGG pathways, 9 upregulated hallmarks pathways, and 18 downregulated hallmark pathways were enriched. These GO terms and signalling pathways were closely related to cell proliferation, immunity, energy metabolism, and the inflammatory response of NSCLC. In addition, XHP's network pharmacology analysis identified 301 compounds and 1,432 target genes. A comprehensive strategic analysis identified CACNA1C as a promising gene by which XHP targets and regulates the TME of NSCLC, benefiting patient survival. CACNA1C expression was positively correlated with both the immune score and stromal score but negatively correlated with the tumour purity score. Additionally, CACNA1C expression was significantly correlated with the infiltration levels of 15 types of immune cells and the expression levels of 6 well-known checkpoint genes. CONCLUSIONS: Our results show that by regulating the pathways associated with cell proliferation and immunity, XHP can suppress cancer cell growth in NSCLC. Additionally, XHP may increase the expression of CACNA1C to suppress immune cell infiltration and regulate the expression of checkpoint-related genes, thereby improving the overall survival of NSCLC patients.

Emodin inhibits invasion and migration of hepatocellular carcinoma cells via regulating autophagy-mediated degradation of snail and ß-catenin.

BACKGROUND: Previous studies reported that emodin extracted from Rheum palmatum L. exerts antiproliferation and antimetastatic effects in a variety of human cancer types. However, the role of emodin in hepatocellular carcinoma (HCC) remain unknown. METHODS: EdU and colony formation assays were performed to evaluate the effects of emodin on proliferation. The mobility capacities of HCC treated with emodin were evaluated using wound healing assay. Transwell invasion and migration assays were performed to evaluate anti-migratory and anti-invasive effects of emodin on HCC. Annexin V-FITC/PI was performed to analyze the apoptosis. PI stain was performed to analyze cell cycle. RNA sequencing technology was used to identify the differentially expressed genes (DEGs) induced by emodin in HCC. The impact of emodin on autophagic flux in HepG2 cells was examined by mCherry-GFP-LC3 analysis. Western blot was used to assess the protein expressions of epithelial-mesenchymal transition (EMT), autophagy, PI3K/AKT/mTOR and Wnt/ß-catenin signaling pathway. RESULTS: We found that emodin inhibited the growth of HepG2 cells in a dose- and time-dependent manner. In addition, emodin inhibited cell proliferation, induced S and G2/M phases arrest, and promoted apoptosis in HepG2 cells. The migration and invasion of HepG2 cells were also suppressed by emodin. Enrichment analysis revealed that DEGs involved in cell adhesion, cancer metastasis and cell cycle arrest. Moreover, western bolt results show that emodin-induced autophagy promotes Snail and ß-catenin degradation. We also found that blocking autophagic flux after emodin treatment caused EMT reversal. Furthermore, the PI3K agonist Y-P 740 significantly reversed the phosphorylation levels of GSK3ß and mTOR. These results indicated that emodin induced autophagy and inhibited the EMT in part through suppression of the PI3K/AKT/mTOR and Wnt/ß-catenin pathways. CONCLUSION: Our study indicated that emodin inhibited cell metastasis in HCC via the crosstalk between autophagy and EMT.

The Associations Between Psychological Distress and Academic Burnout: A Mediation and Moderation Analysis.

Background: Psychological distress is reported to be associated with academic burnout in students while the mediation and moderation effect of resilience and personality are less explored. Purpose: The current study was designed to estimate the mediating effect of resilience and the moderation effect of personality between psychological distress and academic burnout. Participants and methods: A total of 613 students were enrolled from two medical universities between December 2020 and January 2021. They were administered with Academic Burnout Scale, 10-item Kessler Psychological Distress Scale (K10), Connor-Davidson Resilience Scale (CD-RISC-10) and NEO Five-Factor Inventory (NEO-FFI). Latent profile analysis and moderated mediation analysis were performed. Results: Three personalities were identified and named as resilient (13.4%), over-controlled (50.2%) and under-controlled (36.4%). Resilience significantly mediated the relationship between psychological distress and academic burnout while personality significantly moderated the relationship between psychological distress and resilience. Conclusion: Resilience and personality may be two important mediators between psychological distress and academic burnout. More attentions should be paid to students with under-controlled personality and resilience-enhancing interventions could be developed to prevent or alleviate academic burnout in future research.

Heterogeneity in Psychological Resilience and Mental Health among Newly Graduated Nursing Students: A Latent Profile and Generalized Additive Model Analysis.

Background: Psychological resilience is important to mental health and professional development in newly graduated nursing students (NGNSs). However, the association between psychological resilience and mental health in NGNSs is less explored. Purpose: The current study was designed to determine mental health profiles measured by the Kessler 10 scale (K10) and evaluate the non-linear association between psychological resilience and mental health in NGNSs. Methods: A total of 472 NGNSs from the Be Resilient to Nursing Career program were assessed using the K10 and ten-item Connor-Davidson Resilience Scale (CD-RISC 10). Latent profile analysis and generalized additive model analysis were performed. Results: A four-class model based on the K10 was identified: lowest (28.0%), lower-middle (36.4%), upper-middle (26.1%), and highest (9.5%) subgroups. Academic degree and psychological resilience were significant indicators of mental health profiles. Psychological resilience was negatively and nonlinearly correlated with mental health when the CD-RISC 10 score was >17. Conclusion: There exists heterogeneity in NGNSs' mental health. The negative and nonlinear association between psychological resilience and mental health can only be confirmed in NGNSs with moderate and high resilience levels.

Self-Efficacy and Professional Identity Among Freshmen Nursing Students: A Latent Profile and Moderated Mediation Analysis.

This study was designed to estimate the associations between self-efficacy and professional identity. A total of 1,051 freshmen nursing students (FNSs) from the Be Resilient to Nursing Career (BRNC) program were recruited from four universities between September and November 2020. A latent profile and moderated meditation analysis were performed. Four profiles of self-efficacy were identified and named as Lowest (15.6%), Med-low (45.0%), Med-high (32.7%), and Highest (6.7%). The mediating role of resilience and the moderating effect of role models were also identified. Therefore, self-efficacy, resilience, and role models may be three important factors to professional identity in FNSs and these relationships should be further validated in longitudinal or interventional studies.

New resilience instrument for family caregivers in cancer: a multidimensional item response theory analysis.

OBJECTIVE: Resilience instruments specific to family caregivers (FCs) in cancer are limited. This study was designed to validate the 10-item Resilience Scale Specific to Cancer (RS-SC-10) in FCs using multidimensional item response theory (MIRT) analysis. METHODS: 382 FCs were enrolled from Be Resilient to Cancer Program (BRCP) and administered with RS-SC-10 and 36-item Short Form Health Survey (SF-36). MIRT was performed to evaluate item parameters while Generalized Additive Model (GAM) and Latent Profile Analysis (LPA) were performed to test the non-linear relationship between resilience (RS-SC-10) and Quality of Life (QoL, SF-36). RESULTS: RS-SC-10 retained 10 items with high multidimensional discrimination, monotonous thresholds and its original two-factor structure (Generic and Shift-Persist). Four latent resilience subgroups were identified and a non-linear dose-response pattern between resilience and QoL was confirmed (per-SD increase OR = 1.62, 95% CI 1.16-2.13, p = 0.0019). CONCLUSION: RS-SC-10 is a brief and suitable resilience instrument for FCs in cancer. The resilience screening of patients and FCs can be performed simultaneously in clinical practice.

Alterations in the gut microbiota and metabolite profiles in the context of neuropathic pain.

The aim of this study was to explore the relationships among gut microbiota disturbances and serum and spinal cord metabolic disorders in neuropathic pain. 16S rDNA amplicon sequencing and serum and spinal cord metabolomics were used to identify alterations in the microbiota and metabolite profiles in the sham rats and the chronic constriction injury (CCI) model rats. Correlations between the abundances of gut microbiota components at the genus level, the levels of serum metabolites, and pain-related behavioural parameters were analysed. Ingenuity pathway analysis (IPA) was applied to analyse the interaction networks of the differentially expressed serum metabolites. First, we found that the composition of the gut microbiota was different between rats with CCI-induced neuropathic pain and sham controls. At the genus level, the abundances of Helicobacter, Phascolarctobacterium, Christensenella, Blautia, Streptococcus, Rothia and Lactobacillus were significantly increased, whereas the abundances of Ignatzschineria, Butyricimonas, Escherichia, AF12, and Corynebacterium were significantly decreased. Additionally, 72 significantly differentially expressed serum metabolites and 17 significantly differentially expressed spinal cord metabolites were identified between the CCI rats and the sham rats. Finally, correlation analysis showed that changes in the gut microbiota was significantly correlated with changes in serum metabolite levels, suggesting that dysbiosis of the gut microbiota is an important factor in modulating metabolic disturbances in the context of neuropathic pain. In conclusion, our research provides a novel perspective on the potential roles of the gut microbiota and related metabolites in neuropathic pain.

Resilience patterns and transitions in the Be Resilient To Breast Cancer trial: an exploratory latent profile transition analysis.

OBJECTIVE: Be Resilient to Breast Cancer (BRBC), a theoretically-derived, resilience-based, culturally-tailored, supportive-expressive group therapy (SEGT), has been developed to help promote patients' resilience in breast cancer. Data from patients receiving BRBC intervention was utilized to explore and define characteristics of resilience patterns and their transitions over time. METHODS: Resilience was used as a primary outcome and 391 patients completed Resilience Scale Specific to Cancer at enrollment (T0), 2 months (T1), 6 months(T2), and 12 months (T3) after intervention. latent profile transition analysis was performed to model the change in resilience and predict positive transitioning probabilities between resilience patterns (from one pattern to another pattern with a higher level) over time. RESULTS: One hundred and forty four resilience patterns were identified after BRBC intervention. 33.1%, 50.3%, and 40.5% of patients experienced positive resilience transitions from T0 to T1, T1 to T2, and T2 to T3, respectively. Patients with middle age, unmarried status, higher education level, and less advanced tumor stage were more likely to experience positive resilience transitions. CONCLUSION: Different transitions of resilience patterns are observed after BRBC intervention. Age, marital status, education, and tumor stage may be four factors affecting the efficacy of SEGT intervention in breast cancer.

Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma.

BACKGROUND: Due to tumor heterogeneity, the diagnosis, treatment, and prognosis of patients with lung squamous cell carcinoma (LUSC) are difficult. DNA methylation is an important regulator of gene expression, which may help the diagnosis and therapy of patients with LUSC. METHODS: In this study, we collected the clinical information of LUSC patients in the Cancer Genome Atlas (TCGA) database and the relevant methylated sequences of the University of California Santa Cruz (UCSC) database to construct methylated subtypes and performed prognostic analysis. RESULTS: Nine hundred sixty-five potential independent prognosis methylation sites were finally identified and the genes were identified. Based on consensus clustering analysis, seven subtypes were identified by using 965 CpG sites and corresponding survival curves were plotted. The prognostic analysis model was constructed according to the methylation sites' information of the subtype with the best prognosis. Internal and external verifications were used to evaluate the prediction model. CONCLUSIONS: Models based on differences in DNA methylation levels may help to classify the molecular subtypes of LUSC patients, and provide more individualized treatment recommendations and prognostic assessments for different clinical subtypes. GNAS, FZD2, FZD10 are the core three genes that may be related to the prognosis of LUSC patients.

Treatment Decision Making and Regret in Parents of Children With Incurable Cancer.

BACKGROUND: The treatment-related decision-making process is a highly emotional time for parents of children with incurable cancer, and they tend to continue the cancer-directed treatment even when they realize that there is no cure for their child. OBJECTIVE: To evaluate whether parents involved in different treatment decisions regretted their treatment decision after their child's death. METHODS: We collected prospective data from 418 parents of children who died of incurable cancer after receiving cancer care at 1 of 4 hospitals. We assessed parent decisional regret and its association with the type of treatment decision made (non-cancer-directed vs cancer-directed). Propensity score-matched analysis (at a ratio of 1:1) was performed. RESULTS: One hundred forty-eight parents (35.4%) reported heightened regret. Two isonumerical arms with 103 (non-cancer-directed) and 103 (cancer-directed) resulted after propensity score matching. Parents with a cancer-directed treatment decision (relative risk, 1.53; 95% confidence interval, 1.24-1.90; P = .002) were more likely to report decisional regret compared with those with a non-cancer-directed decision. CONCLUSION: Bereaved parents with a cancer-directed treatment decision are more likely to experience increased regret for their decision than bereaved parents involved in a non-cancer-directed treatment decision. IMPLICATIONS: Shared-decision aids should be prepared for young parents with low education to improve disease-related knowledge, accurate risk perceptions, and options congruent with parents' values.

Minimum clinical important difference for resilience scale specific to cancer: a prospective analysis.

BACKGROUND: The minimum clinical important differences (MCIDs) of resilience instruments in patients with cancer have not been comprehensively described. This study was designed to evaluate MCIDs of 10-item and 25-item resilience scales specific to cancer (RS-SC-10 and RS-SC-25). METHODS: From June 2015 to December 2018, RS-SCs were longitudinally measured in 765 patients with different cancer diagnoses at baseline (T0) and 3 months later (T1). The EORTC QLQ-C30, Connor-Davidson Resilience Scale, Hospital Anxiety and Depression Scale, and Allostatic Load Index were measured concurrently as anchors. Anchor-based methods (linear regression, within-group), distribution-based methods(within-group), and receiver operating characteristic curves (ROCs, within-subject) were performed to evaluate the MCIDs. RESULTS: 623 of 765 (84.1%) patients had paired RS-SCs scores. Moderate correlations were identified between the change in RS-SCs and change in anchors (r = 0.38-0.44, all p < 0.001). Linear regression estimated + 8.9 and - 6.7 as the MCIDs of RS-SC-25, and + 3.4 and - 2.5 for RS-SC-10. Distribution-based methods estimated + 9.9 and - 9.9 as the MCIDs of RS-SC-25, and + 4.0 and - 4.0 for RS-SC-10. ROC estimated + 5.5 and - 4.5 as the MCIDs of RS-SC-25, and + 2.0 and - 1.5 for RS-SC-10. CONCLUSIONS: The most reliable MCID is around 5 points for RS-SC-25 and 2 points for RS-SC-10. RS-SCs are more responsive to the worsening status of resilience in patients with cancer and these estimates could be useful in future resilience-based intervention trials.

State or trait? Measuring resilience by generalisability theory in breast cancer.

PURPOSE: Whether resilience should be conceptualised as a state or trait is debated. The precise distinction between state versus trait aspects of resilience can help identify dynamic targets for resilience-based intervention trials involving cancer patients. This study was designed to disentangle the state and trait components of resilience in patients with breast cancer with the help of Generalisability Theory (GT) methods. METHODS: The relative contributions of state (temporary) and trait (enduring) aspects of resilience were calculated using a 10-item Resilience Scale Specific to Cancer (RS-SC-10) and GT methods. In all, 391 patients were enrolled from the 'Be Resilient to Breast Cancer ' (BRBC) trial, and data from 317 patients (81.7%) were collected at baseline, 3 months, 6 months, and 12 months after the intervention. RESULTS: The subscale of Generic Elements demonstrated high generalisability value (relative G-coefficient = 0.81) across different occasions and captured 79% of the variance attributed to enduring aspects of resilience. The subscale of Shift-Persist showed low generalisability value (relative G-coefficient = 0.31) and identified 59% of the variance attributed to temporary aspects of resilience. The GT studies suggested that 5-7 items per scale and three measurement occasions were adequate for score reliability evaluation. CONCLUSION: Resilience should be conceptualised as a state-trait mixed psychological variable in breast cancer patients. The subscale of Shift-Persist in RS-SC-10 is amenable to intervention and could be utilised as a primary outcome in resilience-based intervention trials. CLINICAL TRIAL REGISTRATION: None.