Frailty Index and Frailty Phenotype in elderly patients with cancer

Population Pharmacokinetic Model for Tramadol and O-desmethyltramadol in Older Patients

BACKGROUND AND OBJECTIVES

Tramadol is commonly prescribed to manage chronic pain in older patients. However, there is a gap in the literature describing the pharmacokinetic parameters for tramadol and its active metabolite (O-desmethyltramadol [ODT]) in this population. The objective of this study was to develop and evaluate a population pharmacokinetic model for tramadol and ODT in older patients.

METHODS

Twenty-one patients who received an extended-release oral tramadol dose (25-100 mg) were recruited. Tramadol and ODT concentrations were determined using a validated liquid chromatography/tandem mass spectrometry method. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. The performance of the model was assessed by visual predictive check.

RESULTS

A two-compartment, first-order absorption model with linear elimination best described the tramadol concentration data. The absorption rate constant was 2.96/h (between-subject variability [BSV] 37.8%), apparent volume of distribution for the central compartment (V₁/F) was 0.373 l (73.8%), apparent volume of distribution for the peripheral compartment (V₂/F) was 0.379 l (97.4%), inter-compartmental clearance (Q) was 0.0426 l/h (2.19%) and apparent clearance (CL/F) was 0.00604 l/h (6.61%). The apparent rate of metabolism of tramadol to ODT (k_t) was 0.0492 l/h (78.5%) and apparent clearance for ODT (CL_m) was 0.143 l/h (21.6%). Identification of Seniors at Risk score (ISAR) and creatinine clearance (CrCL) were the only covariates included in the final model, where a higher value for the ISAR increased the maximum concentration (C_max) of tramadol and reduced the BSV in Q from 4.71 to 2.19%. A higher value of CrCL reduced tramadol C_max and half-life (T_1/2) and reduced the BSV in V₂/F (from 148 to 97.4%) and in CL/F (from 78.9 to 6.61%).

CONCLUSION

Exposure to tramadol increased with increased frailty and reduced CrCL. Prescribers should consider patients frailty status and CrCL to minimise the risk of tramadol toxicity in such cohort of patients.

No Difference in the Phenotypic Expression of Frailty among Elderly Patients Recently Diagnosed with Cancer Vs Cancer Free Patients

OBJECTIVES

To examine frailty determinants differences in patients with a recent diagnosis of cancer compared to non-cancer patients among older adult. Revealing those differences will allow us to individualize the exact frailty management in those patients diagnosed with cancer.

DESIGN

This is an observational cross-sectional, monocentric study.

SETTING

Patients were evaluated at the Geriatric Frailty Clinic (GFC), in the Toulouse University Hospital, France, between October 2011 and February 2016.

PARTICIPANTS

1996 patients aged 65 and older were included (1578 patients without cancer and 418 patients with solid and hematological cancer recently diagnosed).

MEASUREMENTS

Frailty was established according to the frailty phenotype. The frailty phenotype measures five components of frailty: weight loss, exhaustion, low physical activity, weakness and slow gait. Frailty phenotype was categorized as robust, pre-frail and frail.

RESULTS

In a multinomial logistic regression, cancer, compared to the non-cancer group, is not associated with an increased likelihood of being classified as pre frail (RRR 0.9, 95% CI [0.5 ; 1.6 ], p 0.9) or frail (RRR 1.2, 95% CI [0.7 ; 2.0], p 0.4) rather than robust. When considering each Fried criterion, a significant higher odd of weight loss was observed in older patients with cancer compared to the non-cancer patients (OR 2.3, 95% CI [1.8; 3.0], p <0.001) but no statistically significant differences was found among the four other Fried criteria. Sensitivity analysis on the frailty index showed that cancer was not associated with a higher FI score compared to non-cancer (β 0.002, 95%CI [-0.009; 0.01], p 0.6).

CONCLUSION

In this real-life study evaluating elderly patients with and without cancer, we didn't confirm our hypothesis, in fact we found that cancer was not associated with frailty severity using both a phenotypic model and a deficit accumulation approach. Cancer may contribute, at least additively, to the development of frailty, like any other comorbidity, rather than a global underlying condition of vulnerability.

Frailty and usage of health care systems: Results from the South Australian Monitoring and Surveillance System (SAMSS)

OBJECTIVES

Little is known about frailty and its impact on health-care systems. Using large-scale population health surveillance data, this study determined the prevalence of frailty, its associated factors, and the impact it places on health care services.

STUDY DESIGN

A cross-sectional snapshot of the 2013-2015 South Australian Monitoring and Surveillance System (SAMSS) database was used, focusing on individuals aged ≥65years. Frailty was assessed by the Frailty Index (FI), and classified as robust (scores≤0.1), pre-frail (>0.1 to ≤0.25), and frail (>0.25).

RESULTS

7207 people (53.7% female) were included; mean (SD) age was 74.8 (7.17) years. The mean (SD) FI score was 0.23 (0.11), with a 99% upper limit of 0.53. Over a third (36.3% (95% CI 34.8-37.9)) were classified as frail and over half (53.6% (95% CI 52.0-55.1)) as pre-frail. Frailty was less common in rural areas, and was associated with age, lower education level, and higher socioeconomic disadvantage. After adjustment for confounders, multivariable analyses showed a gradient effect by frailty classification with regard to both hospital- and non-hospital-based services. Frail older adults were more likely to present to hospital Emergency Departments (EDs) than their pre-frail or robust counterparts, yet visited the GP at the same rate as older adults with pre-frailty.

CONCLUSION

Frail older adults were higher users of health care services, with the exception of GPs. Knowledge of the health service usage patterns of frail older adults can be used to direct public health policy and plan future GP provision.

An overview of osteoporosis and frailty in the elderly

Osteoporosis and osteoporotic fractures remain significant public health challenges worldwide. Recently the concept of frailty in relation to osteoporosis in the elderly has been increasingly accepted, with emerging studies measuring frailty as a predictor of osteoporotic fractures. In this overview, we reviewed the relationship between frailty and osteoporosis, described the approaches to measuring the grades of frailty, and presented current studies and future research directions investigating osteoporosis and frailty in the elderly. It is concluded that measuring the grades of frailty in the elderly could assist in the assessment, management and decision-making for osteoporosis and osteoporotic fractures at a clinical research level and at a health care policy level.