Summary of best evidence for prevention and management of frailty.

BACKGROUND: Frailty in older people can seriously affect their quality of life and increase the demand for long-term care and health care expenses. Aims of this study are to provide an evidence-based basis for clinical practice of frailty in older people by systematically searching for the best current evidence on interventions for the prevention and management of frailty. METHODS: According to the '6S' evidence resource model, evidence retrieval is searched from the top-down and collected relevant guidelines, best practices, evidence summaries, systematic reviews and expert consensus. The retrieval time limit was from the database establishment to 20 March 2023. Two reviewers independently screened and evaluated the literature, and then extracted and summarised the evidence according to the JBI grading of evidence and recommendation system. RESULTS: A total of 44 publications were finally included, including 12 guidelines, 5 best practices, 4 expert consensus, 5 evidence summaries and 18 systematic reviews. Through the induction and integration of the evidence, the evidence was finally summarised from eight aspects: frailty screening, frailty assessment, exercise intervention, nutrition intervention, multi-domain intervention, drug administration, social support and health education, and 43 best evidences were formed. CONCLUSIONS: This study summarised the best evidence for the prevention and management of frailty from eight aspects, which can provide guidance for clinical or community medical staff to develop and apply frailty intervention and practice programmes for older people and improved the clinical outcome and quality of life of older people.

Effects of prehabilitation on postoperative outcomes in frail cancer patients undergoing elective surgery: a systematic review and meta-analysis.

PURPOSE: This systematic review and meta-analys is aimed to explore the effects of prehabilitation on postoperative outcomes in frail cancer patients. METHODS: A comprehensive literature search was conducted using PubMed, Cochrane Library, Embase, Web of Science, CINAHL Complete, and other databases from database inception to 15 March 2022. Studies were included if they consisted of a prehabilitation intervention in frail cancer patients undergoing elective surgery. RESULTS: A total of 9 studies encompassing 1313 patients were included in the review. Through meta-analysis, prehabilitation has a positive impact on total complications (RR = 0.83, 95% CI = 0.73 to 0.94, P = 0.004), severe complications (RR = 0.62, 95% CI = 0.43 to 0.90, P = 0.01), and the average length of hospital stay (MD = - 1.36, 95% CI = - 2.38 to - 0.35, P = 0.008). But it had no differences in 30-day and 3-month mortality and 30-day and 3-month readmission rates. Through qualitative synthesis, two studies found that prehabilitation had a favorable tendency to promote functional recovery compared with the control group. CONCLUSION: Prehabilitation had a positive effect on postoperative complications and the average length of hospital stay in frail cancer patients. A personalized and supervised multimodal prehabilitation program with exercise at its core may be more beneficial for them. More studies with extensive follow-up are needed to confirm and update the findings of these results.

Exploration of frailty trajectories and their associations with health outcomes in older gastric cancer survivors undergoing radical gastrectomy: A prospective longitudinal observation study.

BACKGROUND: Frailty is commom among gastric cancer survivors and increases the burden of care. AIMS: Our aims were to identify the frailty trajectories and investigate their associations with health outcomes in older gastric cancer survivors. METHODS: We finally recruited 381 patients aged ≧60 who underwent radical gastrectomy and recorded frailty at discharge from the hospital, 1, 3, 6, and 12 months after surgery. Growth mixture modeling was used to investigate the frailty trajectories and linear regression models were used to examine their associations with health outcomes. RESULTS: Three classes of frailty trajectories were identified: the "improving frailty", "maintaining frailty" and "deteriorating frailty". Compared with class 1, patients who followed class 2 and class 3 frailty trajectories were more likely to have more severe disability (ß = -14.22, 95 % CI: -17.92, -10.61, P < 0.001; ß = -48.34, 95 % CI: -52.25, -44.42, P < 0.001), worse quality of life (ß = 10.89, 95 % CI: 7.71,14.08, P < 0.001; ß = 34.82, 95 % CI: 31.46, 38.19, P < 0.001), and more frequency readmission within 1 year (ß = 1.02, 95 % CI: 0.98, 1.06, P < 0.001; ß = 2.10, 95 % CI: 2.01, 2.14, P < 0.001) after controlling potential confounders. However, class 2 and class 3 have no significant difference from class 1 in the total hospitalization costs (ß = 1672.12, 95 % CI: -7145.95, 10496.19, P = 0.709; ß = 7651.60, 95 % CI: -1670.28, 16793.47, P = 0.107). CONCLUSIONS: Our study suggested the significant prognostic heterogeneity in frailty trajectories, and what we need to do is to identify patients with heterogeneous trajectory and intervene in them to reduce adverse outcomes, promote rational use of resources, and reduce the burden of care.

Association of metabolic syndrome and frailty with postoperative complications in older gastric cancer patients: A body composition perspective.

OBJECTIVES: To compare the characteristics of body compositions between metabolic syndrome (MetS) and frailty, and determine the independent and overlapping of MetS and frailty with postoperative complications among older patients with gastric cancer. DESIGN: A prospectively observational study. SETTING AND PARTICIPANTS: Two hundred and eighty six older patients from 60 to 80 years undergoing radical gastrectomy for the first time. MEASUREMENTS: MetS was diagnosed by the criteria from the 2020 edition of Chinese guideline for the prevention and treatment of type 2 diabetes mellitus, and frailty was defined by frailty phenotype. An InBody770 impedance analyzer was used to measure body compositions and with 10 fat- and muscle-related indicators being included in this study. Based on the presence of frailty and MetS, patients were divided into the frailty group, MetS group, frailty+MetS group, and normal group, and the body compositions indicators of these groups were compared. Clavien-Dindo classification was used to grade the severity of postoperative complications. Univariate and multivariate regression models were performed to explore the independent and joint association of MetS and frailty with postoperative complications. RESULTS: The incidence rate of MetS, frailty, and frailty+MetS being 20.3%, 15.7%, and 4.2% respectively. Compared with the normal group, both fat and muscle compositions were decreased significantly in the frailty group (p < 0.05), while the statistically significant difference of fat-to-muscle mass ratio (FMR) and skeletal muscle mass to visceral fat area ratio (SVR) were not observed (p > 0.05). In contrast, except SVR, the other indicators of the MetS group were higher than the normal group (p < 0.05). As to the frailty+MetS group, there was a significant increase in fat compositions and FMR, as well as a significant decline in SVR (p < 0.05), while the difference of muscle compositions was not statistically significant (p > 0.05). There was an association of frailty with postoperative total (OR = 3.068, 95% CI: 1.402-6.713) and severe (OR = 9.423, 95% CI: 2.725-32.589) complications, but no association was found of MetS alone. MetS coexisting with frailty was associated with the highest risk of both total (OR = 3.852, 95% CI: 1.020-14.539) and severe (OR = 12.096, 95% CI: 2.183-67.024) complications. CONCLUSIONS: Both frailty and MetS coexisting with frailty had adverse effects on postoperative complications, which appeared greatly different characteristics in body compositions and therefore reinforced the importance of targeted nutritional or metabolic intervention. Although MetS alone were not significantly associated with postoperative complications, it is essential to focus on the causal relationship and development trend between MetS and frailty to prevent MetS from shifting into frailty, considering the highest risk in their coexistence state.

A dynamic online nomogram for predicting the heterogeneity trajectories of frailty among elderly gastric cancer survivors.

BACKGROUND: Frailty is very common among older people with gastric cancer and seriously affects their prognosis. The development of frailty is continuous and dynamic, increasing the difficulty and burden of care. OBJECTIVES: The aims of this study were to delineate the developmental trajectory of frailty in older people with gastric cancer 1 year after surgery, identify heterogeneous frailty trajectories, and further explore their predictors to construct a nomogram for prediction. DESIGN: We conducted a prospective longitudinal observation study. Clinical evaluation and data collection were performed at discharge, and at 1, 3, 6, and 12 months. SETTING AND PARTICIPANTS: This study was conducted in a tertiary hospital and 381 gastric cancer patients over 60 years who underwent radical gastrectomy completed the 1-year follow-up. METHODS: A growth mixture model (GMM) was used to delineate the frailty trajectories, and identify heterogeneous trajectories. A regression model was performed to determine their predictors and further construct a nomogram based on the predictors. Bootstrap with 1000 resamples was used for internal validation of nomogram, a receiver operating characteristic (ROC) curve to evaluate discrimination, calibration curves to evaluate calibration and decision curve analysis (DCA) to evaluate the clinical value. RESULTS: GMM identified three classes of frailty trajectories: "frailty improving", "frailty persisting" and "frailty deteriorating". The latter two were referred to as heterogeneous frailty trajectories. Regression analysis showed 8 independent predictors of heterogeneous frailty trajectories and a nomogram was constructed based on these predictors. The area under ROC curve (AUC) of the nomogram was 0.731 (95 % CI = 0.679-0.781), the calibration curves demonstrated that probabilities predicted by the nomogram agreed well with the actual observation with a mean absolute error of 0.025, and the DCA of nomogram indicated that the net benefits were higher than that of the other eight single factors. CONCLUSIONS: Older gastric cancer patients have heterogeneous frailty trajectories of poor prognosis during one-year postoperative survival. Therefore, early assessment to predict the occurrence of heterogeneous frailty trajectories is essential to improve the outcomes of elderly gastric cancer patients. Scientific and effective frailty interventions should be further explored in the future to improve the prognosis of older gastric cancer patients. CONTRIBUTION OF THE PAPER STATEMENTS: This study constructed a static and dynamic online nomogram with good discrimination and calibration, which can help to screen high-risk patients, implement preoperative risk stratification easily and promote the rational allocation of medical resources greatly. REGISTRATION: ClinicalTrials.gov (Number: NCT05982899). TWEETABLE ABSTRACT: Our findings identified three frailty trajectories and constructed a nomogram to implement preoperative risk stratification and improve patient outcomes.

BMI trajectories, associations with outcomes and predictors in elderly gastric cancer patients undergoing radical gastrectomy: a prospective longitudinal observation study.

OBJECTIVES: Elderly gastric cancer patients undergoing radical gastrectomy are prone to experience unexpected weight loss. Preoperative weight risk prediction may be a promising way to prevent weight loss and improve prognosis. The objectives of this study were to explore the BMI trajectory of elderly gastric cancer patients one year after surgery, evaluate theirs the association with outcomes, and explore their related predictors, so as to provide evidence for weight management and prognosis improvement. METHODS: 412 gastric cancer patients were included and recorded BMI at 6 time points. The trajectories of BMI were analyzed by growth mixture modeling, and the associations of BMI trajectories with outcomes as well as their predictors were investigated by regression models. RESULTS: We identified 3 classes of BMI trajectories: the "slow-decreasing BMI", "rapid-decreasing BMI" and "maintaining BMI". Compared with class1, patients in class 2 were more likely to have a higher frequency of readmission within 1-year(ß = 0.59, 95%CI: 0.29, 0.89, P < 0.001) and a higher rate of mortality within 1-year(ß = 24.74, 95%CI: 9.60, 63.74, P < 0.001) ; patients in class 3 were more likely to have a higher quality of life (ß=-10.46, 95%CI: -17.70, -3.22, P = 0.005) and fewer readmission times within one year (ß=-0.43, 95%CI: -0.77, -0.09, P = 0.015). Predictors of decreasing BMI trajectories were TNM stage, comorbidity, anxiety, family cohesion and social support(P < 0.05). CONCLUSIONS: Our findings can provide a basis for screening high-risk elderly gastric cancer patients with poor prognosis, implementing risk stratification, formulating accurate weight management programs and improving prognosis. IMPLICATIONS FOR CANCER SURVIVORS: The results of our study can provide gastric cancer survivors with preoperative risk screening based on predictive factors so that nutritional support and weight management can be implemented in a timely manner to improve prognosis.

Preoperative low handgrip strength (HGS) with HGS asymmetry is associated with adverse outcomes among older adults with gastric cancer.

INTRODUCTION: This study aimed to explore the associations of low hand grip strength (HGS), HGS asymmetry, their combinations, and frailty on hospital readmissions, total complications, and prolonged length of stay (PLOS) among older adults with gastric cancer. MATERIALS AND METHODS: This study included 342 patients with gastric cancer aged ≥60 years who were scheduled to undergo radical surgery. The Tilburg Frailty Indicator (TFI) was used to collect information on frailty. HGS was measured twice for each hand using an electronic handgrip dynamometer. The highest HGS readings on each hand were used for calculating the HGS asymmetry ratio: non-dominant HGS (kg)/dominant HGS (kg). The Fine and Gray proportional subdistribution hazard model and the logistic regression model were used for the analyses, with covariates adjusted. RESULTS: Low HGS (subdistribution hazard ratios [SHR] = 2.10, 95% confidence interval [CI] = 1.05-3.93, P = 0.036) and low HGS with HGS asymmetry (SHR = 3.95, 95% CI = 1.50-10.36, P = 0.005) were significantly associated with hospital readmissions. Frailty was associated with total complications (odds ratio [OR] = 2.87, 95% CI = 1.61-5.13, P < 0.001) and PLOS (OR = 1.98, 95% CI = 1.19-3.29, P < 0.001). Low HGS, HGS asymmetry, and their combinations were not significantly associated with total complications and PLOS. DISCUSSION: Preoperative low HGS and low HGS with HGS asymmetry were associated with hospital readmissions, while frailty was associated with total complications and PLOS among older adults with gastric cancer. In the future, more rigorously designed studies are needed to verify our results further to improve preoperative clinical assessment and frailty evaluation among older adults with gastric cancer.

A web-based calculator combining Geriatric Nutritional Risk Index (GNRI) and Tilburg Frailty Indicator (TFI) predicts postoperative complications among young elderly patients with gastric cancer.

AIM: Nutritional status and frailty are significant indicators reflecting physiological reserve. We sought to establish and validate a web-based calculator containing the Geriatric Nutritional Risk Index (GNRI) and the Tilburg Frailty Indicator (TFI) together with general clinical information to predict total complications among elderly patients with gastric cancer. METHODS: This was a prospective cohort study of 582 elderly patients with gastric cancer in a tertiary hospital in China. Nutritional status and frailty were assessed by the GNRI and the TFI, respectively. The nomogram was built and further converted into a web-based calculator. The receiver operating characteristic analysis was performed to evaluate the discrimination of the nomogram. Calibration was assessed using the calibration curve and Hosmer-Lemeshow test via the bootstrap resampling procedure. The decision curve analyses (DCAs) were employed to quantify the net benefits of a certain threshold probability for assessing the clinical values. RESULTS: The GNRI (odds ratio [OR], 0.921; 95% confidence interval [CI], 0.895-0.949; P < 0.001), the TFI (OR, 1.243; 95% CI, 1.113-1.386; P < 0.001), surgical approach (OR, 1.913; 95% CI, 1.073-3.408; P = 0.028) and comorbidity (OR = 1.599, 95%CI = 1.028-2.486, P = 0.037) were independently associated with total complications. The nomogram demonstrated good discrimination (area under the receiver operating characteristic curve: training cohort, 0.735; validation cohort, 0.777) and calibration (P = 0.135). The DCA curves of the nomogram also showed good positive net benefits. CONCLUSIONS: The web-based calculator incorporating the GNRI, the TFI, surgical approach, and comorbidity could successfully predict total complications among elderly patients with gastric cancer with good accuracy in a convenient manner. Geriatr Gerontol Int 2023; 23: 205-212.

Adverse outcomes and health-ecological influencing factors of preoperative frailty among elderly patients with gastric cancer.

PURPOSE: Frailty is defined as a state of decreased physiologic reserves arising from cumulative deficits in multiple homeostatic systems, which is important in the field of clinical oncology. We aimed to explore the relationship between preoperative frailty and adverse outcomes, and systematically analyze the factors influencing frailty based on the health ecology model among elderly gastric cancer patients. METHODS: A observational study was conducted to select 406 elderly patients who would undergo gastric cancer surgery at a tertiary hospital. The logistic regression model was used to examine the relationship between preoperative frailty and adverse outcomes, including total complications, prolonged length of stay (PLOS), and 90-day hospital readmission. Based on the health ecology model, the factors which may influence frailty were collected from four levels. Univariate and multivariate analysis were utilized to determine the factors influencing preoperative frailty. RESULTS: Preoperative frailty was associated with total complications (odds ratio [OR] 2.776, 95% confidence interval [CI] 1.588-4.852), PLOS (OR 2.338, 95%CI 1.342-4.073), and 90-day hospital readmission (OR 2.640, 95% CI 1.275-5.469). Besides, nutritional risk (OR 4.759, 95% CI 2.409-9.403), anemia (OR 3.160, 95% CI 1.751-5.701), number of comorbidity ≥ 2 (OR 2.318, 95% CI 1.253-4.291), low physical activity level (OR 3.069, 95% CI 1.164-8.092), apathetic attachment (OR 2.656, 95% CI 1.457-4.839), personal monthly income ≤ 1000 yuan (OR 2.033, 95% CI 1.137-3.635) and anxiety (OR 2.574, 95% CI 1.311-5.053) were independent risk factors for frailty. High physical activity level (OR 0.413, 95% CI 0.208-0.820) and improved objective support (OR 0.818, 95% CI 0.683-0.978) were independent protective factors for frailty. CONCLUSIONS: Preoperative frailty was associated with multiple adverse outcomes and could be affected by factors of different dimensions from the health ecology perspective, including nutrition, anemia, comorbidity, physical activity, attachment style, objective support, anxiety, and income, which can guide the formation of a comprehensive prehabilitation for frailty among elderly gastric cancer patients.