Abstract:Older cancer patients are a highly heterogeneous population in terms of global health and physiological reserves, and it is often difficult to determine the best treatment. Moreover, clinical tools currently used to assess global health require dedicated time and lack a standardized end score. Circulating markers of biological age and/or fitness could complement or partially substitute the existing screening tools. In this study we explored the relationship of potential ageing/frailty biomarkers with age and c… Show more
“…The LOFS is a GA summary score: it calculates a global GA end score that integrates 5 fundamental aspects determining a patient's fitness/frailty status (ie, his or her ability to autonomously perform activities of daily living [ADL and IADL], mental status [MMSE], nutritional status [MNA-SF], and comorbidities [CCI]) into a single semicontinuous score on a scale of 0 (severely frail) to 10 (fit) 41 (see Supporting Table 2). The LOFS is a GA summary score: it calculates a global GA end score that integrates 5 fundamental aspects determining a patient's fitness/frailty status (ie, his or her ability to autonomously perform activities of daily living [ADL and IADL], mental status [MMSE], nutritional status [MNA-SF], and comorbidities [CCI]) into a single semicontinuous score on a scale of 0 (severely frail) to 10 (fit) 41 (see Supporting Table 2).…”
BACKGROUND:The aim of this study was to determine and compare the added prognostic value of screening tools, geriatric assessment (GA) components, and GA summaries to clinical information for overall survival (OS) in older patients with cancer. METHODS: A screening and a 10-item GA were systematically performed in patients ≥70 years old with cancer. Cox regression analyses were conducted to evaluate the added prognostic value for OS of screening tools, GA, and GA summaries to clinical information (age, stage, and tumor type) in 2 cohorts (A and B). Cox models were compared on the basis of the Akaike information criterion and the concordance probability estimate. The 2 cohorts for the analyses were similar but independent. RESULTS: A complete case analysis was available for 763 patients (median age, 76 years) in cohort A and for 402 patients (median age, 77 years) in cohort B. In both cohorts, most individual GA components were independent prognostic factors for OS. Nutritional status (assessed with the Mini Nutritional Assessment Short Form) and functional status (assessed with the Instrumental Activities of Daily Living) consistently displayed a strong capacity to predict OS. Less consistent results were found for screening tools. GA summaries performed the best in comparison with the screening tools and the individual GA components. CONCLUSIONS: Most individual GA components, especially nutritional status and functional status, are prognostic factors for OS in older patients with cancer. GA summaries provide more prognostic information than individual GA components but only moderately improve the prognostic baseline model with clinical information.
“…The LOFS is a GA summary score: it calculates a global GA end score that integrates 5 fundamental aspects determining a patient's fitness/frailty status (ie, his or her ability to autonomously perform activities of daily living [ADL and IADL], mental status [MMSE], nutritional status [MNA-SF], and comorbidities [CCI]) into a single semicontinuous score on a scale of 0 (severely frail) to 10 (fit) 41 (see Supporting Table 2). The LOFS is a GA summary score: it calculates a global GA end score that integrates 5 fundamental aspects determining a patient's fitness/frailty status (ie, his or her ability to autonomously perform activities of daily living [ADL and IADL], mental status [MMSE], nutritional status [MNA-SF], and comorbidities [CCI]) into a single semicontinuous score on a scale of 0 (severely frail) to 10 (fit) 41 (see Supporting Table 2).…”
BACKGROUND:The aim of this study was to determine and compare the added prognostic value of screening tools, geriatric assessment (GA) components, and GA summaries to clinical information for overall survival (OS) in older patients with cancer. METHODS: A screening and a 10-item GA were systematically performed in patients ≥70 years old with cancer. Cox regression analyses were conducted to evaluate the added prognostic value for OS of screening tools, GA, and GA summaries to clinical information (age, stage, and tumor type) in 2 cohorts (A and B). Cox models were compared on the basis of the Akaike information criterion and the concordance probability estimate. The 2 cohorts for the analyses were similar but independent. RESULTS: A complete case analysis was available for 763 patients (median age, 76 years) in cohort A and for 402 patients (median age, 77 years) in cohort B. In both cohorts, most individual GA components were independent prognostic factors for OS. Nutritional status (assessed with the Mini Nutritional Assessment Short Form) and functional status (assessed with the Instrumental Activities of Daily Living) consistently displayed a strong capacity to predict OS. Less consistent results were found for screening tools. GA summaries performed the best in comparison with the screening tools and the individual GA components. CONCLUSIONS: Most individual GA components, especially nutritional status and functional status, are prognostic factors for OS in older patients with cancer. GA summaries provide more prognostic information than individual GA components but only moderately improve the prognostic baseline model with clinical information.
“…Another explanation could be the severity of inflammation. A study performed in breast cancer patients showed the IL-6 level significantly associated with frailty, but the CMV status was not reported (Brouwers et al 2015). In long-term care geriatric patients, higher baseline hs-CRP and IL-6 levels were associated with worse physical performance and gait speed at 12 months independent of age and comorbidity (Langmann et al 2017).…”
Cytomegalovirus (CMV) is an important pathogen for both clinical and population settings. There is a growing body of research implicating CMV in multiple health outcomes across the life course. At the same time, there is mounting evidence that individuals living in poverty are more likely to be exposed to CMV and more likely to experience many of the chronic conditions for which CMV has been implicated. Further research on the causal role of CMV for health and wellbeing is needed. However, the strong evidence implicating CMV in type 2 diabetes, autoimmunity, cancer, cardiovascular disease, vaccination, and age-related alterations in immune function warrants clinical and public health action. This imperative is even higher among individuals living in socioeconomically disadvantaged settings and those exposed to high levels of chronic psychosocial stress.
“…Therefore, we evaluated the following biomarkers that have been associated with functional decline in the elderly: IL-6[28, 39, 55], D-dimers[56], albumin[57], IGF-1 & IGFBP3[58, 59], TNF-alpha[60] in plasma samples.…”
Section: Methodsmentioning
confidence: 99%
“…Chemotherapy treatment has potential to increase senescent cells leading to an increase in inflammatory and DNA damage burden[34], which could interfere with muscle function [35, 36]. Elevated pro-inflammatory cytokines are correlated with fatigue in breast cancer survivors[37], patients with cancer in general [38] and frailty in breast cancer survivors [39]. …”
Background
Chemotherapy is less often prescribed in older individuals due to concerns about post-treatment morbidity and quality of life. We evaluated the physical performance of breast cancer survivors treated with and without adjuvant chemotherapy.
Methods
We conducted a case-control study in 56 estrogen receptor positive breast cancer survivors (BCS) on adjuvant aromatase inhibitors 1-2 years after definitive surgery. Cases had received adjuvant chemotherapy (n = 27; age 70.5±3.6 yrs) versus age-matched controls who had not (n = 29; age 70.0±4.3 yrs). Measures of grip strength, physical activity and performance, walking speed, fatigue, and self-reported physical function were collected. Biological correlates of inflammation, frailty and markers of DNA and RNA oxidation were compared.
Results
Grip strength (Controls: 21±7.4 vs. Cases: 29.7±5.0 kg, p=0.20), physical activity (5403±3204 vs. 6801±9320 steps/day, p=0.45), physical performance (Short Physical Performance Battery score: 10.1±1.8 vs. 10.4±1.1, p=0.52), long-distance walking speed (1.2±0.21 vs. 1.3±0.41 m/sec, p=0.17) were similar between the two groups. Self-reported physical function was marginally lower in cases than controls (Controls: 72±24 vs. Cases: 57±34 AU, p=0.07). Fatigue disruptiveness was not different between groups (Controls: 11.1±13.0 vs. Cases: 15.7±16.2 AUs, p=0.24). Similarly, the inflammation, oxidation, and frailty markers did not present a significant difference between groups, except for vitamin D levels (p=0.04).
Conclusion
Older women who received chemotherapy reported having slightly lower physical function, but a similar physical performance compared to women who did not. These data suggest that older BCS treated with chemotherapy recover to an extent similar to survivors who only received hormonal therapy.
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