End-of-Life Care in the Last Three Months before Death in Older Patients with Cancer in Belgium: A Large Retrospective Cohort Study Using Data Linkage.

This study aims to describe end-of-life (EOL) care in older patients with cancer and investigate the association between geriatric assessment (GA) results and specialized palliative care (SPC) use. Older patients with a new cancer diagnosis (2009-2015) originally included in a previous multicentric study were selected if they died before the end of follow-up (2019). At the time of cancer diagnosis, patients underwent geriatric screening with Geriatric 8 (G8) followed by GA in case of a G8 score ≤14/17. These data were linked to the cancer registry and healthcare reimbursement data for follow-up. EOL care was assessed in the last three months before death, and associations were analyzed using logistic regression. A total of 3546 deceased older patients with cancer with a median age of 79 years at diagnosis were included. Breast, colon, and lung cancer were the most common diagnoses. In the last three months of life, 76.3% were hospitalized, 49.1% had an emergency department visit, and 43.5% received SPC. In total, 55.0% died in the hospital (38.5% in a non-palliative care unit and 16.4% in a palliative care unit). In multivariable analyses, functional and cognitive impairment at cancer diagnosis was associated with less SPC. Further research on optimizing EOL healthcare utilization and broadening access to SPC is needed.

Long-term health-care utilisation in older patients with cancer and the association with the Geriatric 8 screening tool: a retrospective analysis using linked clinical and population-based data in Belgium.

BACKGROUND: Little evidence is available on the long-term health-care utilisation of older patients with cancer and whether this is associated with geriatric screening results. We aimed to evaluate long-term health-care utilisation among older patients after cancer diagnosis and the association with baseline Geriatric 8 (G8) screening results. METHODS: For this retrospective analysis, we included data from three cohort studies for patients (aged ≥70 years) with a new cancer diagnosis who underwent G8 screening between Oct 19, 2009 and Feb 27, 2015, and who survived more than 3 months after G8 screening. The clinical data were linked to cancer registry and health-care reimbursement data for long-term follow-up. The occurrence of outcomes (inpatient hospital admissions, emergency department visits, use of intensive care, contacts with general practitioner [GP], contacts with a specialist, use of home care, and nursing home admissions) was assessed in the 3 years after G8 screening. We assessed the association between outcomes and baseline G8 score (normal score [>14] or abnormal [≤14]) using adjusted rate ratios (aRRs) calculated from Poisson regression and using cumulative incidence calculated as a time-to-event analysis with the Kaplan-Meier method. FINDINGS: 7556 patients had a new cancer diagnosis, of whom 6391 patients (median age 77 years [IQR 74-82]) met inclusion criteria and were included. 4110 (64·3%) of 6391 patients had an abnormal baseline G8 score (≤14 of 17 points). In the first 3 months after G8 screening, health-care utilisation peaked and then decreased over time, with the exception of GP contacts and home care days, which remained high throughout the 3-year follow-up period. Compared with patients with a normal baseline G8 score, patients with an abnormal baseline G8 score had more hospital admissions (aRR 1·20 [95% CI 1·15-1·25]; p<0·0001), hospital days (1·66 [1·64-1·68]; p<0·0001), emergency department visits (1·42 [1·34-1·52]; p<0·0001), intensive care days (1·49 [1·39-1·60]; p<0·0001), general practitioner contacts (1·19 [1·17-1·20]; p<0·0001), home care days (1·59 [1·58-1·60]; p<0·0001), and nursing home admissions (16·7% vs 3·1%; p<0·0001) in the 3-year follow-up period. At 3 years, of the 2281 patients with a normal baseline G8 score, 1421 (62·3%) continued to live at home independently and 503 (22·0%) had died. Of the 4110 patients with an abnormal baseline G8 score, 1057 (25·7%) continued to live at home independently and 2191 (53·3%) had died. INTERPRETATION: An abnormal G8 score at cancer diagnosis was associated with increased health-care utilisation in the subsequent 3 years among patients who survived longer than 3 months. FUNDING: Stand up to Cancer, the Flemish Cancer Society.

Linking clinical and population-based data in older patients with cancer in Belgium: Feasibility and clinical outcomes.

INTRODUCTION: Geriatric screening and geriatric assessment (GS/GA) have proven their benefits in the care for older patients with cancer. However, less is known about the predictive value of GS/GA for outcomes. To research this, clinical data on GS/GA can be enriched with population-based data. In this article we describe the methods and feasibility of data linkage, and first clinical outcomes (GS/GA results and overall survival). MATERIALS AND METHODS: A large cohort study consisting of patients aged ≥70 years with a new cancer diagnosis was established using linked data from clinical and population-based databases. Clinical data were derived from a previous prospective study where older patients with cancer were screened with G8, followed by GA in case of an abnormal result (GS/GA study; 2009-2015). These data were linked to cancer registration data from the Belgian Cancer Registry (BCR), reimbursement data of the health insurance companies (InterMutualistic Agency, IMA), and hospital discharge data (Technical Cell, TCT). Cox regression analyses were conducted to evaluate the prognostic value of the G8 geriatric screening tool. RESULTS: Of the 8067 eligible patients with a new cancer diagnosis, linkage of data from the GS/GA study and data from the BCR was successful for 93.7%, resulting in a cohort of 7556 patients available for the current analysis. Further linkage with the IMA and TCT database resulted in a cohort of 7314 patients (96.8%). Based on G8 geriatric screening, 67.9% of the patients had a geriatric risk profile. Malnutrition and functional dependence were the most common GA-identified risk factors. An abnormal baseline G8 score (≤14/17) was associated with lower overall survival (adjusted HR [aHR] = 1.62 [1.50-1.75], p < 0.001). DISCUSSION: Linking clinical and population-based databases for older patients with cancer has shown to be feasible. The GS/GA results at cancer diagnosis demonstrate the vulnerability of this population and the G8 score showed prognostic value for overall survival. The established cohort of almost 8000 patients with long-term follow-up will serve as a basis in the future for detailed analyses on long-term outcomes beyond survival.

Incidence of falls and fall-related injuries and their predictive factors in frail older persons with cancer: a multicenter study.

BACKGROUND: Falls and fall-related injuries are a major public health problem. Data on falls in older persons with cancer is limited and robust data on falls within those with a frailty profile are missing. The aim of this study is to investigate the incidence and predictive factors for falls and fall-related injuries in frail older persons with cancer. METHODS: This study is a secondary data analysis from data previously collected in a large prospective multicenter observational cohort study in older persons with cancer in 22 Belgian hospitals (November 2012-February 2015). Patients ≥70 years with a malignant tumor and a frailty profile based on an abnormal G8 score were included upon treatment decision and evaluated with a Geriatric Assessment (GA). At follow-up, data on falls and fall-related injuries were documented. RESULTS: At baseline 2141 (37.2%) of 5759 included patients reported at least one fall in the past 12 months, 1427 patients (66.7%) sustained an injury. Fall-related data of 3681 patients were available at follow-up and at least one fall was reported by 769 patients (20.9%) at follow-up, of whom 289 (37.6%) fell more than once and a fall-related injury was reported by 484 patients (62.9%). Fear of falling was reported in 47.4% of the patients at baseline and in 55.6% of the patients at follow-up. In multivariable analysis, sex and falls history in the past 12 months were predictive factors for both falls and fall-related injuries at follow-up. Other predictive factors for falls, were risk for depression, cognitive impairment, dependency in activities of daily living, fear of falling, and use of professional home care. CONCLUSION: Given the high number of falls and fall-related injuries and high prevalence of fear of falling, multifactorial falls risk assessment and management programs should be integrated in the care of frail older persons with cancer. Further studies with long-term follow-up, subsequent impact on cancer treatment and interventions for fall prevention, and integration of other important topics like medication and circumstances of a fall, are warranted. TRIAL REGISTRATION: B322201215495.

Functional status in older patients with cancer and a frailty risk profile: A multicenter observational study.

INTRODUCTION: Functional status (FS) and frailty are significant concerns for older adults, especially those with cancer. Data on FS (Activities of Daily Living [ADL]; Instrumental Activities of Daily Living [IADL]) and its evolution during cancer treatment in older patients and a frailty risk profile are scarce. Therefore, this study examines FS and its evolution in older patients with cancer and a frailty risk profile and investigates characteristics associated with functional decline. MATERIAL AND METHODS: This secondary data-analysis, focusing on FS, uses data from a large prospective multicenter observational cohort study. Patients ≥70 years with a solid tumor and a frailty risk profile based on the G8 screening tool (score ≤ 14) were included. A geriatric assessment was performed including evaluation of FS based on ADL and IADL. At approximately three months of follow-up, FS was reassessed. Univariable and multivariable logistic regression analyses were used to identify predictive factors for functional decline in ADL and IADL. RESULTS: Data on ADL and IADL were available at baseline and follow-up in 3388 patients. At baseline 1886 (55.7%) patients were dependent for ADL, whereas 2085 (61.5%) patients were dependent at follow-up. Functional decline was observed in 23.6% of patients. For IADL 2218 (65.5%) patients were dependent for IADL, whereas 2591 (76.5%) patients were dependent at follow-up. Functional decline in IADL was observed in 41.0% of patients. In multivariable analysis, disease stage III or IV, comorbidities, falls history in the past twelve months, and FS measured by IADL were predictive factors for functional decline in both ADL and IADL. Other predictive factors for functional decline in ADL were polypharmacy, Eastern Cooperative Oncology Group-Performance Status (ECOG-PS) score 2-4, and cognitive impairment, and for functional decline in IADL were female sex, fatigue, and risk for depression. DISCUSSION: Functional impairments are frequent in older persons with cancer and a frailty risk profile, and several characteristics are identified that are significantly associated with functional decline. Therefore, FS is an essential part of the geriatric assessment which should be standard of care for this patient population. Next step is to proceed with directed interventions with the aim to limit the risk of functional decline as much as possible.

Unplanned hospitalizations in older patients with cancer: Occurrence and predictive factors.

BACKGROUND: This study aims to investigate the occurrence of unplanned hospitalizations in older patients with cancer and to determine predictive factors. METHODS: A prospective Belgian multicentre (n = 22), observational cohort study was performed. Patients ≥70 years with a malignant tumor were included. Patients underwent G8 screening followed by geriatric assessment (GA) if abnormal at baseline and were followed for unplanned hospitalizations at approximately three months. Uni- and multivariable regression models were performed to determine predictive factors associated with unplanned hospitalizations in older patients with an abnormal G8. RESULTS: In total, 7763 patients were included in the current analysis of which 2409 (31%) patients with a normal G8 score and 5354 (69%) with an abnormal G8 score. Patients with an abnormal G8 were hospitalized more frequently than patients with a normal G8 (22.9% versus 12.4%; p < 0.0001). Reasons for unplanned hospitalizations were most frequently cancer related (25.7%) or cancer therapy related (28%). In multivariable analysis, predictive factors for unplanned hospitalizations in older patients with cancer and an abnormal G8 were female gender, absence of surgery, chemotherapy, ADL dependency, malnutrition and presence of comorbidities. CONCLUSION: Older patients with cancer and an abnormal G8 screening present a higher risk (23%) for unplanned hospitalizations. Predictive factors for these patients were identified and include not only patient and treatment related factors but also GA related factors.

The prognostic value of patient-reported Health-Related Quality of Life and Geriatric Assessment in predicting early death in 6769 older (≥70 years) patients with different cancer tumors.

OBJECTIVES: We aimed to determine the prognostic value of baseline Health-Related Quality Of Life (HRQOL) and geriatric assessment (GA) to predict three-month mortality in older patients with cancer undergoing treatment. METHODS: Logistic regressions analysed HRQOL, as measured with the EORTC Global Health Status (GHS) scale, and geriatric information prognostic for early mortality controlling for oncology variables. The assessment was established with the odds ratio (OR), 95% confidence interval (CI) and level of significance set at p < 0.05. Discriminative power was evaluated with area under the curve (AUC). RESULTS: In total, 6769 patients were included in the study, of whom 1259 (18.60%) died at three months. Our model showed higher odds of early death for patients with lower HRQOL (GHS, OR 0.98, 95% CI 0.98-0.99; p < 0.001), a geriatric risk profile (G8 Screening Tool, 1.94, 1.14-3.29; p = 0.014), cognitive decline (Mini Mental State Examination, 1.41, 1.15-1.72; p = 0.001), being at risk for malnutrition (Mini Nutritional Assessment-Short Form, 1.54, 1.21-1.98; p = 0.001), fatigue (Visual Analogue Scale for Fatigue, 1.45, 1.16-1.82; p = 0.012) and comorbidities (Charlson Comorbidity index, 1.23, 1.02-1.49; p = 0.033). Additionally, older age, poor ECOG PS and being male increased the odds of early death, although the magnitude differed depending on tumor site and stage, and treatment (all p < 0.05). Predictive accuracy increased with 3.7% when including HRQOL and GA in the model. CONCLUSION: The results suggest that, in addition to traditional clinical measures, HRQOL and GA provide additional prognostic information for early death, but the odds differ by patient and tumor characteristics.

Health related quality of life in older patients with solid tumors and prognostic factors for decline.

OBJECTIVES: This study aims to investigate health-related quality of life (HRQOL) at baseline and at follow-up in older patients with cancer and to determine prognostic factors for HRQOL decline. METHODS: A prospective Belgian multicentre (n = 22) study was performed. Patients ≥70 years with a malignant tumor and abnormal G8 (≤14/17) screening tool were included. Patients underwent geriatric assessment (GA) and HRQOL evaluation with follow up at three months. Uni- and multivariate regression models were performed to determine factors associated (p < .05) with baseline HRQOL and HRQOL decline at follow-up. RESULTS: Results reflect data collected from 3673 patients. A multivariate analysis showed that younger patients, and those with poor Eastern Cooperative Oncology Group - Performance Status (ECOG-PS), specific tumor types (gastrointestinal, gynaecological and thorax) and higher stage had lower baseline HRQOL. In addition worse functional status and presence of pain, fatigue, depression and malnutrition were associated with lower baseline HRQOL. During treatment (n = 2972), improvement in HRQOL was observed in 1037 patients (35%) and a decline in 838 patients (28.2%). In multivariate analysis, stage and presence of baseline comorbidities, pain, fatigue or malnutrition were associated with HRQOL evolution. CONCLUSION: Baseline HRQOL in older patients with cancer and an abnormal G8 depends on tumor and age related parameters. During follow-up, HRQOL improved in one third of patients, indicating that they may benefit from cancer treatment while one quarter demonstrated a HRQOL decline for which prognostic factors were identified.

[Is pulse oximetry a reliable tool for detection of aspiration?]. / Is pulse oximetrie een bruikbaar instrument om aspiratie op te sporen?

This study was designed to determine whether significant differences in saturation levels existed among patients with aspiration and patients without and wether pulse oximetry can reliably detect aspiration in patients with dysphagia. We also examined the effects of gender and disease (neurologic versus non neurologic) on saturation levels. We studied 38 patients. They all underwent a videofluoroscopic study of swallowing (VFSS). Twenty patients aspirated on videofluoroscopic study of swallowing: ten patients were solid aspirators, ten patients were liquid aspirators. In each group (liquid aspirators, solid aspirators or non aspirators) we found no significant difference in saturation levels. We found however a significant difference in saturation levels between each group before, during and after videofluoroscopic study of swallowing. Both gender and disease had an effect on saturation levels. We conclude that pulse oximetry can not serve as a screening tool for detection of aspiration as saturation levels are dependent on many factors. Therefore one can not reliably predict aspiration with a single saturation screening.