CONTEXT: It is uncertain whether terminally ill schizophrenic cancer patients are hypoalgesic or have disparities in pain management.
OBJECTIVES: To analyze the dosage of opioids used in terminally ill cancer patients with and without schizophrenia.
METHODS: This is a population-based retrospective cohort study based on data derived from the Taiwan National Health Insurance Research Database. Patients aged > 20 and newly diagnosed between 2000 and 2012 with at least one of the six most common cancers were included. After 1:4 matching, 1001 schizophrenic cancer patients comprised the schizophrenia cohort, while 4004 cancer patients without schizophrenia comprised the non-schizophrenia cohort. The percentage of opioid use, accumulated dose, and average daily dose near the end of life were analyzed for each cohort using multiple logistic and linear regression models.
RESULTS: The percentage of opioid use was lower in the schizophrenic cohort than the non-schizophrenic cohort during the last month prior to death [69.6 % versus 84.8%, odd ratio (OR) = 0.40, 95% confidence interval (CI) = 0.34-0.48]. The accumulated dose of opioid consumption was also lower in the schizophrenic cohort (2407 mg versus 3694 mg, p value <0.05).
CONCLUSION: Near the end of life, cancer patients with schizophrenia use less opioid than their non-schizophrenic counterparts. Cognitive impairment may be a cause in the disparity in end-of-life care for terminally ill schizophrenic cancer patients. Thus, we should formulate a more accurate pain scale system and pay attention to their need for pain treatment.
OBJECTIVES: Reliable national estimates of hospice use and underuse are needed. Additionally, drivers of hospice use in the United States are poorly understood, especially among noncancer populations. Thus the objectives of this study were to (1) provide reliable estimates of hospice use among adults in the United States; and (2) identify factors predicting use among decedents and within subsamples of cancer and noncancer deaths.
DESIGN: We conducted a prospective cohort study using the Health and Retirement Study survey. Excluding sudden deaths, we used data from the 2012 survey wave to predict hospice use in general, and then separately for cancer and non-cancer deaths.
SETTING: Study data were provided by a population-based sample of older adults from the U.S.
PARTICIPANTS: We constructed a sample of 1,209 participants who died between the 2012 and 2014 survey waves.
MEASUREMENTS: Hospice utilization was reported by proxy. Exposure variables included demographics, functionality (activities of daily living [ADLs]), health, depression, dementia, advance directives, nursing home residency, and cause of death.
RESULTS: Hospice utilization rate was 52.4% for the sample with 70.8% for cancer deaths and 45.4% for noncancer deaths. Fully adjusted model results showed being older (odds ratio [OR] = 1.54), less healthy (OR = .79), having dementia (OR = 1.52), and having cancer (OR = 5.47) were linked to greater odds of receiving hospice. Among cancer deaths, being older (OR = 1.64) and female (OR = 2.54) were the only predictors of hospice use. Among noncancer deaths, increased age (OR = 1.58), more education (OR = 1.56), being widowed (OR = 1.55), needing help with ADLs (OR = 1.13), and poor health (OR = .77) were associated with hospice utilization.
CONCLUSION: Findings suggest hospice remains underutilized, especially among individuals with noncancer illness. Extrapolating results to the US population, we estimate that annually nearly a million individuals who are likely eligible for hospice die without its services. Most (84%) of these decedents have a noncancer condition. Interventions are needed to increase appropriate hospice utilization, particularly in noncancer care settings.
Background: early identification of palliative patients is challenging. The Surprise Question (SQ1; Would I be surprised if this patient were to die within 12 months?) is widely used to identify palliative patients. However, its predictive value is low. Therefore, we added a second question (SQ2) to SQ1: ‘Would I be surprised if this patient is still alive after 12 months?’ We studied the accuracy of this double surprise question (DSQ) in a general practice.
Methods: We performed a prospective cohort study with retrospective medical record review in a general practice in the eastern part of the Netherlands. Two general practitioners (GPs) answered both questions for all 292 patients aged =75 years (mean age 84 years).
Primary outcome was 1-year death, secondary outcomes were aspects of palliative care.
Results: SQ1 was answered with ‘no‘ for 161/292 patients. Of these, SQ2 was answered with ‘yes’ in 22 patients. Within 12 months 26 patients died, of whom 24 had been identified with SQ1 (sensitivity: 92%, specificity: 49%). Ten of them were also identified with SQ2 (sensitivity: 42%, specificity: 91%). The latter group had more contacts with their GP and more palliative care aspects were discussed.
Conclusions: The DSQ appears a feasible and easy applicable screening tool in general practice. It is highly effective in predicting patients in high need for palliative care and using it helps to discriminate between patients with different life expectancies and palliative care needs. Further research is necessary to confirm the findings of this study.
Background: The surprise question (SQ), “Would I be surprised if this patient died within one year?”, is a simple instrument to identify patients with palliative care needs. The SQ-performance has not been evaluated in patients with advanced cancer visiting the emergency department (ED).
Objective: To evaluate SQ's test characteristics and predictive value in patients with advanced cancer visiting the ED.
Design: Observational cohort study.
Setting: Patients >18 years with advanced cancer in the palliative phase visiting the ED of an academic medical center.
Methods: Attending physicians answered the SQ (not surprised [NS] or surprised [S]) and estimated Eastern Cooperative Oncology Group (ECOG)-performance status. Disease, visit, and follow-up characteristics were retrospectively collected from charts. SQ's sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and Harrell's c-index were calculated. Prognostic values of SQ and other variables were assessed by using Cox proportional hazards models.
Results: Two-hundred-and-forty-five patients were included (203 NS [83%] and 42 S [17%]), median age 62 years, 48% male. Follow-up on overall survival was updated until February 2019. At ED entry, NS-patients had worse ECOG-performance and more symptoms. At study closure, 233 patients had died (95%). Median survival was three months for NS-patients (interquartile [IQ]-range: 1–8); nine months for S-patients (IQ-range: 3–28) (p < 0.0001). SQ-performance for one-year mortality: sensitivity 89%, specificity 40%, PPV 85%, NPV 50%, c-index 0.56, and hazard ratio 2.1 for approaching death. ECOG 3–4 predicted death in NS-patients; addition to the SQ improved c-index (0.65); sensitivity (40%), specificity (92%), PPV (95%), and NPV (29%).
Conclusions: At the ED, the SQ plus ECOG 3–4 helps identifying patients with advanced cancer and a limited life expectancy. Its use supports initiating appropriate care related to urgency of palliative care needs.
Importance: Overall, 1 of 5 decedents in the United States is admitted to an intensive care unit (ICU) before death.
Objective: To describe structures, processes, and variability of end-of-life care delivered in ICUs in the United States.
Design, Setting, and Participants: This nationwide cohort study used data on 16 945 adults who were cared for in ICUs that participated in the 68-unit ICU Liberation Collaborative quality improvement project from January 2015 through April 2017. Data were analyzed between August 2018 and June 2019.
Main Outcomes and Measures: Published quality measures and end-of-life events, organized by key domains of end-of-life care in the ICU.
Results: Of 16 945 eligible patients in the collaborative, 1536 (9.1%) died during their initial ICU stay. Of decedents, 654 (42.6%) were women, 1037 (67.5%) were 60 years or older, and 1088 (70.8%) were identified as white individuals. Wide unit-level variation in end-of-life care delivery was found. For example, the median unit-stratified rate of cardiopulmonary resuscitation avoidance in the last hour of life was 89.5% (interquartile range, 83.3%-96.1%; range, 50.0%-100%). Median rates of patients who were pain free and delirium free in last 24 hours of life were 75.1% (interquartile range, 66.0%-85.7%; range, 0-100%) and 60.0% (interquartile range, 43.7%-85.2%; range, 9.1%-100%), respectively. Ascertainment of an advance directive was associated with lower odds of cardiopulmonary resuscitation in the last hour of life (odds ratio, 0.70; 95% CI, 0.49-0.99; P = .04), and a documented offer or delivery of spiritual support was associated with higher odds of family presence at the time of death (odds ratio, 1.95; 95% CI, 1.37-2.77; P < .001). Death in a unit with an open visitation policy was associated with higher odds of pain in the last 24 hours of life (odds ratio, 2.21; 95% CI, 1.15-4.27; P = .02). Unsupervised cluster analysis revealed 3 mutually exclusive unit-level patterns of end-of-life care delivery among 63 ICUs with complete data. Cluster 1 units (14 units [22.2%]) had the lowest rate of cardiopulmonary resuscitation avoidance but achieved the highest pain-free rate. Cluster 2 (25 units [39.7%]) had the lowest delirium-free rate but achieved high rates of all other end-of-life events. Cluster 3 (24 units [38.1%]) achieved high rates across all favorable end-of-life events.
Conclusions and Relevance: In this study, end-of-life care delivery varied substantially among ICUs in the United States, and the patterns of care observed suggest that units can be characterized as higher and lower performing. To achieve optimal care for patients who die in an ICU, future research should target unit-level variation and disseminate the successes of higher-performing units.
Background: Barriers to palliative care still exist in long-term care settings for older people, which can mean that people with advanced dementia may not receive of adequate palliative care in the last days of their life; instead, they may be exposed to aggressive and/or inappropriate treatments. The aim of this multicentre study was to assess the clinical interventions and care at end of life in a cohort of nursing home (NH) residents with advanced dementia in a large Italian region.
Methods: This retrospective study included a convenience sample of 29 NHs in the Lombardy Region. Data were collected from the clinical records of 482 residents with advanced dementia, who had resided in the NH for at least 6 months before death, mainly focusing on the 7 days before death.
Results: Most residents (97.1%) died in the NH. In the 7 days before death, 20% were fed and hydrated by mouth, and 13.4% were tube fed. A median of five, often inappropriate, drugs were prescribed. Fifty-seven percent of residents had an acknowledgement of worsening condition recorded in their clinical records, a median of 4 days before death.
Conclusions: Full implementation of palliative care was not achieved in our study, possibly due to insufficient acknowledgement of the appropriateness of some drugs and interventions, and health professionals’ lack of implementation of palliative interventions. Future studies should focus on how to improve care for NH residents.
Context: Despite the preference to pass away at home, many dementia patients die in institutions, resulting in a paucity of studies examining end-of-life care outcomes in the home setting.
Objective: To identify modifiable factors associated with the comfort of dementia patients dying at home and families’ satisfaction with care.
Methods: This is a prospective cohort study conducted from October 2014 to April 2019 in Singapore. Dementia patients at Stage 7 on the Functional Assessment Staging Scale, with albumin<35g/L, enteral feeding or pneumonia were recruited from a palliative homecare programme. Independent variables included demographics, medical information and care preferences. The Comfort Assessment in Dying with Dementia scale assessed dying patients’ comfort while the Satisfaction with Care at the End-of-Life in Dementia scale evaluated family caregivers’ satisfaction two months post-bereavement. Gamma regression identified factors independently associated with comfort and satisfaction.
Results: The median age of 202 deceased patients whose comfort was assessed was 88 years. Anti-cholinergic prescription (60.4% of patients) [ß(95% CI)=1.823(0.660 – 2.986), p=0.002] was positively associated with comfort, while opioid prescription (89.6%) [ß(95% CI)=-2.179(-4.107- -0.251), p=0.027] and >1 antibiotic courses used in the last 2 weeks of life (77.2%) [ß(95% CI)=-1.968(-3.196 – -0.740), p=0.002] were negatively associated. Independent factors associated with families’ satisfaction with care were comfort [ß(95% CI)=0.149(0.012 – 0.286), p=0.033] and honouring of medical intervention preferences (96.0%) [ß(95% CI)=3.969(1.485 – 6.453), p=0.002].
Conclusion: Achieving comfort and satisfaction with care for dementia patients dying at home involves an interplay of modifiable factors. Honouring medical intervention preferences, such as those with palliative intent associated with patients’ comfort determined families’ satisfaction with care.
CONTEXT: Advanced breast cancer patients have low rates of survival that can be associated with symptom burden.
OBJECTIVES: This study seeks to characterize the effect of longitudinally-collected symptom scores on predicting time to death for advanced breast cancer patients.
METHODS: A cohort of 993 Stage IV breast cancer patients was constructed using linked population-level health administrative databases that captured longitudinally-collected symptom data using the Edmonton Symptom Assessment System. Data was captured on individual symptom scores (20,371 assessments) for pain, tiredness, drowsiness, nausea, appetite, dyspnea, depression, anxiety and wellbeing, as well as three summative scores of total symptom distress score (TSDS), physical symptom score, and psychological symptom score. A joint modelling approach was undertaken to simultaneously model repeated measures longitudinal data and time-to-event data.
RESULTS: Of patients who died in the study, 56.11% survived for a mean time of less than three years and had lower mean symptom scores for all symptoms except shortness of breath, in comparison to patients who lived for greater than three years. Symptom burden was predictive of patient time to death for all symptoms, with risk of death increasing with worsening symptom scores. For TSDS, age at diagnosis (0.009, p<0.05), chemotherapy (-0.63, p<0.001) and palliative care (3.15, p<0.001) were significant predictors of patient time to death.
CONCLUSIONS: Patients with advanced breast cancer experience chronic, ongoing low symptom burden which predicts patient time to death. Future research should examine the mechanisms by which patient characteristics, treatment, supportive and palliative care can have an impact on patient survival.
OBJECTIVE: Opioids are the primary therapy for cancer-related pain in patients receiving palliative care. More states are legalizing medical cannabis, which may provide a pain management alternative for some of these patients. This study aimed to estimate the effect of cannabis on opioid use in patients with cancer receiving palliative care.
METHODS: This was a retrospective cohort study of patients with cancer at an academic medical center palliative care clinic. The primary outcome was change in morphine equivalent daily dose (MEDD) from baseline to 84-day follow-up in the cannabis plus opioid group compared to that in the opioid-only group.
RESULTS: A total of 83 patients were included: 61 in the opioid monotherapy group and 22 in the cannabis plus opioid group. An increase in MEDD from the baseline to 84 days was seen in both the opioid monotherapy and opioid plus cannabis group (28.8 vs. 10.8); however, the study lacked power to detect a statistical difference.
CONCLUSION: A possibly meaningful difference in MEDD increase was seen when comparing the opioid monotherapy group with the opioid plus cannabis group. However, the study was not powered to test this hypothesis; the findings suggest that further research is warranted to determine the impact of cannabis use on opioid dosing in patients receiving palliative care for cancer.
OBJECTIVE: To assess the impact of intercenter variation and patient factors on end-of-life care practices for infants who die in regional neonatal intensive care units (NICUs).
STUDY DESIGN: We conducted a retrospective cohort analysis using the Children's Hospital Neonatal Database during 2010-2016. A total of 6299 nonsurviving infants cared for in 32 participating regional NICUs were included to examine intercenter variation and the effects of gestational age, race, and cause of death on 3 end-of-life care practices: do not attempt resuscitation orders (DNR), cardiopulmonary resuscitation within 6 hours of death (CPR), and withdrawal of life-sustaining therapies (WLST). Factors associated with these practices were used to develop a multivariable equation.
RESULTS: Dying infants in the cohort underwent DNR (55%), CPR (21%), and WLST (73%). Gestational age, cause of death, and race were significantly and differently associated with each practice: younger gestational age (<28 weeks) was associated with CPR (OR 1.7, 95% CI 1.5-2.1) but not with DNR or WLST, and central nervous system injury was associated with DNR (1.6, 1.3-1.9) and WLST (4.8, 3.7-6.2). Black race was associated with decreased odds of WLST (0.7, 0.6-0.8). Between centers, practices varied widely at different gestational ages, race, and causes of death.
CONCLUSIONS: From the available data on end-of-life care practices for regional NICU patients, variability appears to be either individualized or without consistency.
OBJECTIVES: We studied a cohort of cancer patients that underwent curative-intent radiation within the last year of life (LYOL). Given the unexpectedly short survival, we evaluated the proportion with relapsed/refractory disease, determined causes of death, and explored whether treatment intent was associated with aggressiveness of care at the end of life.
MATERIALS AND METHODS: We extracted and linked claims data and radiotherapy records for patients seen at a single academic institution that died between October 1, 2014, and September 30, 2015.
RESULTS: Among 870 cancer patients, 290 were irradiated within the LYOL, of which 287 had treatment intent recorded (101 curative-intent, 186 palliative-intent). The majority of curative-intent patients had hematologic malignancies and/or underwent transplant (44.6%), followed by head and neck (9.9%) and gastrointestinal malignancies (9.9%). Half (n=49; 48.5%) had relapsed/refractory disease at the time of curative-intent radiation, including 13 with metastatic disease. Tumor progression (n=65; 64.4%) was the most common cause of death, followed by treatment-related mortality (n=27; 26.7%), of which transplant/hematologic malignancy patients (n=19) were the majority. Compared with palliative-intent patients, curative-intent patients had significantly higher rates of chemotherapy use within 14 days of death (P=0.04), intensive care unit stay within 30 days of death (P<0.00001), and death in the intensive care unit (P=0.001).
CONCLUSIONS: Cancer patients that receive curative-intent radiation in the LYOL appear to be heterogeneous and receive more aggressive care at the end of life compared with palliative-intent patients. Categorizing radiation as curative in patients with metastatic disease may reflect inappropriate decision-making among physicians. Additional studies are needed to understand how radiation oncologists categorize treatment as curative and whether prognostication models may help discriminate patients undergoing curative-intent radiation that have limited life expectancies.
Background: The literature describing the incidence of sleep difficulty in CNS cancers is very limited, with exploration of a sleep difficulty symptom trajectory particularly sparse in people with advanced disease. We aimed to establish the prevalence and longitudinal trajectory of sleep difficulty in populations with CNS cancers receiving palliative care nationally, and to identify clinically modifiable predictors of sleep difficulty.
Methods: A consecutive cohort of 2406 patients with CNS cancers receiving palliative care from sites participating in the Australian national Palliative Care Outcomes Collaboration were evaluated longitudinally on patient-reported sleep difficulty from point-of-care data collection, comorbid symptoms, and clinician-rated problems. Multilevel models were used to analyze patient-reported sleep difficulty.
Results: Reporting of mild to severe sleep difficulties ranged from 10% to 43%. Sleep scores fluctuated greatly over the course of palliative care. While improvement in patients' clinical status was associated with less sleep difficulty, the relationship was not clear when patients deteriorated. Worsening of sleep difficulty was associated with higher psychological distress (P < .0001), greater breathing problems (P < .05) and pain (P < .05), and higher functional status (P < .001) at the beginning of care.
Conclusions: Sleep difficulty is prevalent but fluctuates widely in patients with CNS cancers receiving palliative care. A better-tailored sleep symptom assessment may be needed for this patient population. Early interventions targeting psychological distress, breathing symptoms, and pain for more functional patients should be explored to see whether it reduces sleep difficulties late in life.
Importance: Although palliative care (PC) historically focused on patients with cancer and those near the end of life, evidence increasingly demonstrates a benefit to patients with a broad range of serious illnesses and to those earlier in their illness. The field of PC has expanded and evolved rapidly, resulting in a need to characterize practice over time to understand whether it reflects evolving evidence and guidelines.
Objective: To characterize current practice and trends among patients cared for and outcomes achieved by inpatient specialty PC services in the United States.
Design, Setting, and Participants: This retrospective cohort study was performed from January 1, 2013, to December 31, 2017, at 88 US hospitals in which PC teams voluntarily participate in the Palliative Care Quality Network (PCQN), a national quality improvement collaborative. A total of 135 197 patients were referred to PCQN teams during the study period. Initial analyses of the study data were conducted from March 3 to March 21, 2018.
Exposure: Inpatient PC consultation.
Main Outcomes and Measures: A total of 23 standardized data elements collected by PCQN teams that provided information about the characteristics of referred patients, including age, sex, Palliative Performance Scale score, and primary diagnosis leading to PC consult; reason(s) given for the consultation; and processes of care provided by the PC team, including disciplines involved, number of family meetings held, advance care planning documentation completed, and screened for and intervened on needs.
Results: A total of 135 197 patients were referred to inpatient PC (51.0% female; mean age, 71.3 years [range, 57.8-82.5 years]) and were significantly debilitated (mean Palliative Performance Scale score, 34.7%; range, 14.9%-56.8%). Cancer was the most common primary diagnosis (32.0%; range, 11.3%-93.9%), although rates decreased from 2013 to 2017 (odds ratio [OR], 0.84; 95% CI, 0.79-0.91; P < .001). Pain and other symptoms were common and improved significantly during the consultation period (pain: 2 = 5234.4, P < .001; anxiety: 2 = 2020.7, P < .001; nausea: 2 = 1311.8, P < .001; dyspnea: 2 = 1993.5, P < .001). Most patients were discharged alive (78.7%; range, 44.7%-99.4%), and this number increased over time (OR, 1.36; 95% CI, 1.27-1.46; P < .001). Compared with 2013, rates of discharge referral to clinic-based (OR, 4.00; 95% CI, 2.95-5.43; P < .001) and home-based PC (OR, 2.63; 95% CI, 1.92-3.61; P < .001) also increased significantly by 2017, whereas referrals to hospice decreased (OR, 0.56; 95% CI, 0.51-0.62; P < .001).
Conclusions and Relevance: Inpatient PC teams cared for an increasing percentage of patients with diagnoses other than cancer and saw more patients discharged alive, consistent with guidelines recommending specialty PC for all patients with serious illness earlier in their illnesses. Most patients with symptoms improved quickly. Variation in practice and outcomes among PCQN members suggests that there are opportunities for further improvements in care.
Background: Understanding current patterns of functional decline will inform patient care and has health service and resource implications.
Aim: This prospective consecutive cohort study aims to map the shape of functional decline trajectories at the end of life by diagnosis.
Design: Changes in functional status were measured using the Australia-modified Karnofsky Performance Status Scale. Segmented regression was used to identify time points prior to death associated with significant changes in the slope of functional decline for each diagnostic cohort. Sensitivity analyses explored the impact of severe symptoms and late referrals, age and sex.
Setting/participants: In all, 115 specialist palliative care services submit prospectively collected patient data to the national Palliative Care Outcomes Collaboration across Australia. Data on 55,954 patients who died in the care of these services between 1 January 2013 and 31 December 2015 were included.
Results: Two simplified functional decline trajectories were identified in the last 4 months of life. Trajectory 1 has an almost uniform slow decline until the last 14 days of life when function declines more rapidly. Trajectory 2 has a flatter more stable trajectory with greater functional impairment at 120 days before death, followed by a more rapid decline in the last 2 weeks of life. The most rapid rate of decline occurs in the last 2 weeks of life for all cohorts.
Conclusions: Two simplified trajectories of functional decline in the last 4 months of life were identified for five patient cohorts. Both trajectories present opportunities to plan for responsive healthcare that will support patients and families.
Importance: Palliative care is a patient-centered approach associated with improvements in quality of life; however, results regarding its association with a survival benefit have been mixed, which may be a factor in its underuse.
Objective: To assess whether early palliative care is associated with a survival benefit among patients with advanced lung cancer.
Design, setting, and participants: This retrospective population-based cohort study was conducted among patients with lung cancer who were diagnosed with cancer between January 1, 2007, and December 31, 2013, with follow-up until January 23, 2017. Participants comprised 23 154 patients with advanced lung cancer (stage IIIB and stage IV) who received care in the Veterans Affairs health care system. Data were analyzed from February 15, 2019, to April 28, 2019.
Exposure: Palliative care defined as a specialist-delivered palliative care encounter received after lung cancer diagnosis.
Main outcomes and measures: The primary outcome was survival. The association between palliative care and place of death was also examined. Propensity score and time-varying covariate methods were used to calculate Cox proportional hazards and to perform regression modeling.
Results: Of the 23 154 patients enrolled in the study, 57% received palliative care. The mean (SD) age of participants was 68 (9.5) years, and 98% of participants were men. An examination of the timing of palliative care receipt relative to cancer diagnosis found that palliative care received 0 to 30 days after diagnosis was associated with decreases in survival (adjusted hazard ratio [aHR], 2.13; 95% CI, 1.97-2.30), palliative care received 31 to 365 days after diagnosis was associated with increases in survival (aHR, 0.47; 95% CI, 0.45-0.49), and palliative care received more than 365 days after diagnosis was associated with no difference in survival (aHR, 1.00; 95% CI, 0.94-1.07) compared with nonreceipt of palliative care. Receipt of palliative care was also associated with a reduced risk of death in an acute care setting (adjusted odds ratio, 0.57; 95% CI, 0.52-0.64) compared with nonreceipt of palliative care.
Conclusions and relevance: The results suggest that palliative care was associated with a survival benefit among patients with advanced lung cancer. Palliative care should be considered a complementary approach to disease-modifying therapy in patients with advanced lung cancer.
Context: The effect of methadone on corrected QT interval (QTc) in patients with cancer pain is not well-known.
Objectives: To describe and characterize the effect of low-, moderate-, and high-dose enteral methadone on QTc interval in patients with cancer.
Methods: Retrospective cohort study including patients prescribed enteral methadone during the 27-month study period. Participants were divided into 3 methadone daily dose groups: <30 (low dose), 30 to 59 (moderate dose), =60 (high dose) mg. The primary outcome was the incidence of QTc prolongation (>450 ms for females and >430 ms for males). Secondary outcomes included the magnitude of change in QTc after starting methadone, the incidence of clinically significant QTc prolongation (>500 ms) and the prevalence of torsades de pointes and syncope.
Results: Two hundred three patients met study inclusion criteria: 91 (45%) low dose, 52 (26%) moderate dose, and 60 (29%) high dose. Incidence of QTc prolongation for low-, moderate-, and high-dose groups was 50 (55%), 37 (71%), and 43 (72%), respectively (P = .039, low vs high dose). Incidence of clinically significant QTc prolongation was 10 (11%), 4 (8%), and 7 (12%) for low-, moderate-, and high-dose groups. For patients without QTc prolongation prior to initiating methadone, 62% of moderate-dose patients and 67% of high-dose patients had QTc prolongation, while taking methadone.
Conclusion: This study found a notably high incidence of QTc prolongation in patients with cancer using enteral methadone. Future studies should aim to determine the risk of adverse cardiac effects in the cancer population and determine appropriate monitoring of methadone for pain management.
Background: To avoid aggressive treatments at the end-of-life and to provide palliative care (PC), physicians need to terminate futile anti-cancer treatments and define the palliative goal of the treatment in time. This single center study assesses the practices used to make the decision that leads to treatment with a palliative goal, i.e., the PC decision and its effect on anti-cancer treatments at the end of life.
Material and methods: Patients with a cancer diagnosis treated in tertiary hospital during 1st January 2013 – 31st December 2014 and deceased by the end of 2014 were identified in the hospital database (N = 2737). Of these patients, 992 were randomly selected for this study. The PC decision was screened from patient records, i.e., termination of cancer-specific treatments and a focus on symptom-centered PC.
Results: The PC decision was defined in 82% of the patients during the last year of life (49% >30 days and 33% =30 days before death, 18% with no decision). The median time from the decision to death was 46 days. Systemic cancer therapy was given during the last month of life in 1%, 36% and 38% (p < .001) and radiotherapy 22%, 40% and 31% (p = .03) cases, respectively; referral to a PC unit was made in 62%, 22% and 11%, respectively (p < .001). In logistic regression analyses younger age, shorter duration of the disease trajectory and type of cancer (e.g., breast cancer) were associated with a lack or late timing of the PC decision.
Conclusion: The decision to initiate a palliative goal for the treatment was frequently made for cancer patients but occurred late for every third patient. Younger age and certain cancer types were associated with late PC decisions, thus leading to anti-cancer treatments continuing until close to the death with low access to a PC unit.
Objectives: To explore the influence of hospital and patient characteristics on deaths at home among inpatients facing impending death.
Method: In this historical cohort study, 95,626 inpatients facing impending death from 362 hospitals in 2011 were recruited. The dependent variable was the place of death. The independent variables were the characteristics of the hospitals and the patients. A two-level hierarchical generalized linear model was used.
Results: In total, 41.06% of subjects died at home. The hospital characteristics contributed to 29.25% of the total variation of the place of death. Private hospitals (odds ratio [OR] = 1.32, 95% confidence interval [CI] = 1.00-1.75), patients >65 years old (OR = 1.48, 95% CI. = 1.42-1.54), married (OR = 3.15, 95% CI. = 2.93-3.40) or widowed (OR = 3.39, 95% CI. = 3.12-3.67), from near-poor households (OR = 5.16, 95% CI. = 4.57-5.84), having diabetes mellitus (OR = 1.79, 95% CI. = 1.65-1.94), and living in a subcounty (OR = 2.27, 95% CI. = 2.16-2.38) were all risk factors for a death at home.
Conclusion: Both hospital and patient characteristics have an effect of deaths at home among inpatients facing impending death. The value of the inpatient mortality rate as a major index of hospital accreditation should be interpreted intrinsically with the rate of deaths at home.
Context: Programs identifying patients needing palliative care and promoting advance care planning (ACP) are rare in Asia.
Objectives: This interventional cohort study aimed to identify hospitalized patients with palliative care needs using a validated Palliative Care Screening Tool (PCST), examine the ability of the PCST to predict mortality, and explore effects of a pragmatic ACP program targeted by PCST on the utilisation of life-sustaining treatment during the last three months of life.
Methods: In this prospective study, we used PCST to evaluate patients’ palliative care needs between 2015 and 2016 and followed patients for 3 months. ACP with advance directives (AD) were systematically offered to all patients with PCST score =4.
Results: Of 47,153 hospitalized patients, 10.4% had PCST score =4. During follow-up, 2,121 individuals died within three months of palliative care screening: 1,225 (25.0%) with PCST score =4 and 896 (2.1%) with PCST score <4. After controlling for co-variates, PCST score =4 was significantly associated with a higher mortality within 3 months of screening (adjusted odds ratio [AOR], 6.86; 95% confident interval [CI], 6.16-7.63). Moreover, ACP consultation (AOR=0.78, 95%CI: (0.66-0.92) and AD completion (AOR=0.49, 95%CI: 0.36-0.65) were associated with a lower likelihood of receiving life-sustaining treatments during the last 3 months of life.
Conclusions: We demonstrated the feasibility of implementing a comprehensive palliative care program to identify patients with palliative care needs and promote ACP and AD in East Asia. ACP consultation and AD completion were associated with reduced utilization of life-sustaining treatments during the last 3 months of life.
Aggressive resource utilization for patients with cancer at the end of life has been associated with poor outcomes for patients and their families. To our knowledge, no previous studies have characterized resource utilization as a proxy for quality end-of-life care in hospitalized patients awaiting discharge to hospice by physician and advanced practice providers (APPs). We conducted a retrospective cohort study to examine resource utilization and the quality metrics for end-of-life care in patients at Memorial Sloan Kettering Cancer Center from the date of hospice decision to discharge. Patients under the care of APP teams were less likely to receive laboratory testing (50% vs 59%, P = .046) and received fewer tests than those with house staff teams, though performance on end-of-life quality metrics was similar. Our findings suggest APPs may improve quality of end-of-life care by avoiding unnecessary or aggressive measures compared to house staff.