Background and aims This living and systematic review aimed to provide an updated summary of the available evidence on pain undertreatment prevalence in patients with cancer; correlations with some potential determinants and confounders were also carried out. Materials and methods We updated a systematic review published on 2014, including observational and experimental studies reporting the use of the pain management index (PMI) in adults with cancer and pain, from 2014 to 2020. We conducted searches in PubMed/MEDLINE, Embase, and Google Scholar. We performed univariate and multivariable regression analyses to describe the relationship between PMI and a list of potential explanatory variables. Results Twenty new papers were identified, yielding a total sample size of 66 studies. The proportion of patients classified as undertreated according to the year of study publication shows a higher decrease from 1994 to 2013 (−13% as relative change) than the most recent years 2014–2020 (−11%). The quality of the included studies has increased over the years (from 80% to 93%). At the multivariable analysis, a statistically significant relationship was confirmed between undertreatment and the year of the publication of the study and with a low–medium economic level of the countries, where the studies were conducted. Discussion Despite the improvement when compared to the period 1994–2000, still about 40% of the cases identified received an analgesic treatment inadequate to the intensity of pain, according to the PMI. Despite its intrinsic limitations, PMI continues to be widely used, and it could allow a continuous monitoring of pain management across a different mix of studies and patients.
Delirium occurs in 50-80% of end-of-life patients but is often misdiagnosed. Identification of clinical factors potentially associated with delirium onset can lead to a correct early diagnosis. To this aim, we conducted a prospective cohort study on patients from an Italian palliative care unit (PCU) admitted in 2018-2019. We evaluated the presence of several clinical factors at patient admission and compared their presence in patients who developed delirium and in those who did not develop it during follow-up. Among 503 enrolled patients, after a median follow-up time of 16 days (interquartile range 6-40 days), 95 (18.9%) developed delirium. Hazard ratios (HR) and corresponding 95% confidence intervals were computed using Cox proportional hazard models. In univariate analyses, factors significantly more frequent in patients with delirium were care in hospice, compromised performance status, kidney disease, fever, renal fail-
Delirium occurs in 50-80% of end-of-life patients but it is often misdiagnosed. Identification of clinical factors potentially associated with delirium onset can lead to a correct early diagnosis. To this aim, we conducted an observational prospective study on patients from an Italian Palliative Care Unit (PCU) in 2018-2019 and evaluated the presence of clinical factors at patients’ admission. We then compared their presence in patients who developed delirium and in those who did not during follow-up. On 503 enrolled patients, 95 (18.9%) developed delirium. In univariate analyses, factors significantly more frequent in patients with delirium were advanced age, care in hospice, very compromised performance status, hypoxia, high number of simultaneous clinical factors, presence of breathlessness, poor well-being, severe drowsiness, and background therapy with haloperidol and drugs acting on CNS. In multivariate analyses, setting of care (odds ratio, OR, 1.68 for hospice versus home care, 95% confidence interval, CI 1.02-2.75; p=0.040), and administration of psychiatric drugs (OR 1.74 for administration versus no administration, 95% CI 1.08-2.81; p=0.023) were significantly associated with the risk of developing delirium, while the associations with age (OR 1.82 for > 80 years versus ≤ 70 years, 95% CI=0.98-3.36; p=0.046) and presence of breathlessness (OR 1.70, 95%, CI 0.99-2.89, p=0.053) were of borderline significance. The study indicates that some clinical factors are associated with the probability of delirium onset. Their evaluation in PC patients could help the healthcare professionals to timely identify the development of delirium in those patients.
Purpose Various prognostic indexes have been proposed to improve physicians’ ability to predict survival time in advanced cancer patients admitted to palliative care (PC), but no optimal score has still been identified. The study therefore aims to develop and externally validate a new multivariable predictive model in this setting.Methods We developed the model on 1020 cancer patients prospectively enrolled to home care palliative care at VIDAS Milan, Italy, between May 2018 and February 2020 and followed-up to June 2020. The model was then validated among two separate samples of 544 home care and 247 hospice patients. Overall survival was considered as the primary outcome to develop and validate the model; Cox and flexible parametric Royston-Parmar regression models were used.Results Through a four-step modelling process, among 68 clinical factors considered, five predictors were included in the predictive model, i.e., rattle, heart rate, anorexia, liver failure, and the Karnofsky performance status. Patient’s survival probability at various time points was estimated. The predictive model showed a good calibration and moderate discrimination (area under the receiver operating characteristic curve between 0.72 and 0.79) in the home care validation set, but model calibration was suboptimal in hospice patients.Conclusions The new multivariable predictive model for palliative cancer patients’ survival (PACS model) includes clinical parameters routinely at patient’s admission to PC and can be easily used to facilitate immediate and appropriate clinical decisions for PC cancer patients in the home setting.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.