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Level of Palliative Care Complexity in Advanced Cancer Patients: A Multinomial Logistic Analysis.

ABSTRACT: The current treatment approach for patients in palliative care (PC) requires a health model based on shared and individualised care, according to the degree of complexity encountered. The aims of this study were to describe the levels of complexity that may be present, to determine their most prevalent elements and to identify factors that may be related to palliative complexity in advanced-stage cancer patients. An observational retrospective study was performed of patients attended to at the Cudeca Hospice. Socio-demographic and clinical data were compiled, together with information on the patients' functional and performance status (according to the Palliative Performance Scale (PPS)). The level of complexity was determined by the Diagnostic Instrument of Complexity in Palliative Care (IDC-Pal©) and classified as highly complex, complex or non-complex. The impact of the independent variables on PC complexity was assessed by multinomial logistic regression analysis. Of the 501 patients studied, 44.8% presented a situation classed as highly complex and another 44% were considered complex. The highly complex items most frequently observed were the absence or insufficiency of family support and/or caregivers (24.3%) and the presence of difficult-to-control symptoms (17.3%). The complex item most frequently observed was an abrupt change in the level of functional autonomy (47.6%). The main factor related to the presence of high vs. non-complexity was that of performance status (odds ratio (OR) = 10.68, 95% confidence interval (CI) = 2.81-40.52, for PPS values < 40%). However, age was inversely related to high complexity. This study confirms the high level of complexity present in patients referred to a PC centre. Determining the factors related to this complexity could help physicians identify situations calling for timely referral for specialised PC, such as a low PPS score.

SUBMITTER: Carrasco-Zafra MI

PROVIDER: S-EPMC7356562 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Level of Palliative Care Complexity in Advanced Cancer Patients: A Multinomial Logistic Analysis.

Carrasco-Zafra Maria Isabel MI Gómez-García Rafael R Ocaña-Riola Ricardo R Martín-Roselló Maria Luisa ML Blanco-Reina Encarnación E

Journal of clinical medicine 20200623 6

The current treatment approach for patients in palliative care (PC) requires a health model based on shared and individualised care, according to the degree of complexity encountered. The aims of this study were to describe the levels of complexity that may be present, to determine their most prevalent elements and to identify factors that may be related to palliative complexity in advanced-stage cancer patients. An observational retrospective study was performed of patients attended to at the C ...[more]

PMID: 32585859

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Project description:BackgroundThe UK National Health Service is striving to improve access to palliative care for patients with advanced cancer however limited information exists on the level of palliative care support currently provided in the UK. We aimed to establish the duration and intensity of palliative care received by patients with advanced cancer and identify which cancer patients are missing out.MethodsRetrospective cancer registry, primary care and secondary care data were obtained and linked for 2474 patients who died of cancer between 2010 and 2012 within a large metropolitan UK city. Associations between the type, duration, and amount of palliative care by demographic characteristics, cancer type, and therapies received were assessed using Chi-squared, Mann-Whitney or Kruskal-Wallis tests. Multinomial multivariate logistic regression was used to assess the odds of receiving community and/or hospital palliative care compared to no palliative care by demographic characteristics, cancer type, and therapies received.ResultsOverall 64.6% of patients received palliative care. The average palliative care input was two contacts over six weeks. Community palliative care was associated with more palliative care events (p<0.001) for a longer duration (p<0.001). Patients were less likely to receive palliative care if they were: male (p = 0.002), aged 80 years or over (p<0.05), diagnosed with lung cancer (p<0.05), had not received an opioid prescription (p<0.001), or had not received chemotherapy (p<0.001). Patients given radiotherapy were more likely to receive community only palliative care compared to no palliative care (Odds Ratio = 1.49, 95% Confidence Interval = 1.16-1.90).ConclusionTimely supportive care for cancer patients is advocated but these results suggest that older patients and those who do not receive anti-cancer treatment or opioid analgesics miss out. These patients should be targeted for assessment to identify unmet needs which could benefit from palliative care input.

Project description:BackgroundPalliative sedation (PS) is an intervention to treat refractory symptoms and to relieve suffering at the end of life. Its prevalence and practice patterns vary widely worldwide. The aim of our study was to evaluate the frequency, clinical indications and outcomes of PS in advanced cancer patients admitted to our tertiary comprehensive cancer center.MethodsWe retrospectively studied the use of PS in advanced cancer patients who died between March 1st, 2012 and December 31st, 2014. PS was defined as the use of continuous infusion of midazolam or neuroleptics for refractory symptoms in the end of life. This study was approved by the Research Ethics Committee of our institution (project number 2481-15).ResultsDuring the study period, 552 cancer patients died at the institution and 374 met the inclusion criteria for this study. Main reason for exclusion was death in the Intensive Care Unit. Among all included patients, 54.2% (n?=?203) received PS. Patients who received PS as compared to those not sedated were younger (67.8 vs. 76.4 years-old, p?<?0.001) and more likely to have a diagnosis of lung cancer (23% vs. 14%, p?=?0.028). The most common indications for sedation were dyspnea (55%) and delirium (19.7%) and the most common drugs used were midazolam (52.7%) or midazolam and a neuroleptic (39.4%). Median initial midazolam infusion rate was 0.75 mg/h (interquartile range - IQR - 0.6-1.5) and final rate was 1.5 mg/h (IQR 0.9-3.0). Patient survival (length of hospital stay from admission to death) of those who had PS was more than the double of those who did not (33.6 days vs 16 days, p?<?0.001). The palliative care team was involved in the care of 12% (n?=?25) of sedated patients.ConclusionsPS is a relatively common practice in the end-of-life of cancer patients at our hospital and it is not associated with shortening of hospital stay. Involvement of a dedicated palliative care team is strongly recommended if this procedure is being considered. Further research is needed to identify factors that may affect the frequency and outcomes associated with PS.

Project description:ImportanceLimited data suggest that early palliative care (EPC) improves quality of life (QOL) and survival in patients with advanced cancer.ObjectiveTo evaluate whether comprehensive EPC improves QOL; relieves mental, social, and existential burdens; increases survival rates; and helps patients develop coping skills.Design, setting, and participantsThis nonblinded randomized clinical trial (RCT) recruited patients from 12 hospitals in South Korea from September 2017 to October 2018. Patients aged 20 years or older with advanced cancer who were not terminally ill but for whom standard chemotherapy has not been effective were eligible. Participants were randomized 1:1 to the control (receiving usual supportive oncological care) or intervention (receiving EPC with usual oncological care) group. Intention-to-treat data analysis was conducted between September and December 2022.InterventionsThe intervention group received EPC through a structured program of self-study education materials, telephone coaching, and regular assessments by an integrated palliative care team.Main outcomes and measuresThe primary outcome was the change in overall QOL score (assessed with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative Care) from baseline to 24 weeks after enrollment, with evaluations also conducted at 12 and 18 weeks. Secondary outcomes were social and existential burdens (assessed with the McGill Quality of Life Questionnaire) as well as crisis-overcoming capacity and 2-year survival.ResultsA total of 144 patients (83 males [57.6%]; mean [SD] age, 60.7 (7.2) years) were enrolled, of whom 73 were randomized to the intervention group and 71 to the control group. The intervention group demonstrated significantly greater changes in scores in overall health status or QOL from baseline, especially at 18 weeks (11.00 [95% CI, 0.78-21.22] points; P = .04; effect size = 0.42). However, at 12 and 24 weeks, there were no significant differences observed. Compared with the control group, the intervention group also showed significant improvement in self-management or coping skills over 24 weeks (20.51 [95% CI, 12.41-28.61] points; P < .001; effect size = 0.93). While the overall survival rate was higher in the intervention vs control group, the difference was not significant. In the intervention group, however, those who received 10 or more EPC interventions (eg, telephone coaching sessions and care team meetings) showed a significantly increased probability of 2-year survival (53.6%; P < .001).Conclusions and relevanceThis RCT demonstrated that EPC enhanced QOL at 18 weeks; however, no significant improvements were observed at 12 and 24 weeks. An increased number of interventions sessions was associated with increased 2-year survival rates in the intervention group.Trial registrationClinicalTrials.gov Identifier: NCT03181854.

Dataset Information

Level of Palliative Care Complexity in Advanced Cancer Patients: A Multinomial Logistic Analysis.

Publications

Level of Palliative Care Complexity in Advanced Cancer Patients: A Multinomial Logistic Analysis.

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