When does early palliative care influence aggressive care at the end of life?

BACKGROUND

Early palliative care improves patient quality of life and influences cancer care. The time frame of early has not been established. Eight quality measures reflect aggressive care at the end of life. We retrospectively reviewed patients who died with cancer between January 1, 2018, through December 31, 2019, and compared the timing of palliative care consultation, advance directives (AD), and home palliative care with aggressive care at the end of life (ACEOL).

METHODS

Patients without ACEOL indicators were compared to patients with one or more than one indicator of ACEOL. The proportion of patients who received palliative care, completed AD, and the timing of palliative care and AD (less than 30 days, 30-90 days, and greater than 90 days prior to death) was compared for patients who had ACEOL versus those who did not. Chi-square analysis was used for categorical data, one-way ANOVA for continuous variables, and odds ratio (OR) with confidence intervals (CI) was reported as a measure of effect size. A p value ≤ 0.05 was considered significant.

RESULTS

1727 patients died, 46% were female, and the mean age was 69 (SD 11.91). Seventy-one percent had a palliative care consult, 26% completed AD, and 888 (51.4%) had at least one indicator of ACEOL. The most common indicator of ACEOL was new chemotherapy within 30 days of death, in 571 of 888 (64%) of patients experiencing ACEOL. ADs completed at any time reduced ACEOL (OR 0.80, 95%CI 0.64-0.99). Palliative care initiated at 30 days was associated with a greater risk of ACEOL (OR 5.32, 95% CI 3.94-7.18) and initiated between 30 and 90 days (OR 1.39, 95% CI 1.07-1.80) compared to no palliative care but was associated with reduced chemotherapy as an indicator of ACEOL when > 90 days (OR 0.46, 95% CI 0.38-0.57) before death.

DISCUSSION

Completed ADs were associated with reduced chemotherapy in the last 30 days of life and reduced ICU admissions. This may reflect goals of care and end-of-life discussions and transition of care to comfort measures. Palliative care paradoxically when initiated within 90 days before death was associated with greater ACEOL compared to no palliative care. This may be due to consultation late in the course of illness with a focus on crisis management in patients frequently utilizing the health care system. There is an associated reduction in the use of chemotherapy in the last 30 days of life if palliative care is consulted 90 days prior to death.

CONCLUSIONS

An initial palliative care consult greater than 90 days before death and ADs completed at any time during the disease trajectory was associated only with reduced chemotherapy in the last 30 days of life compared with no palliative care among the 7 ACEOL indicators. ADs were associated with reduced ICU admissions. Most palliative care consults occurred within 90 days of death and a palliative care consult within 90 days of death is not an optimal utilization of services.

How palliative care professionals deal with predicting life expectancy at the end of life: predictors and accuracy

PURPOSE

To assess the accuracy of hospice staff in predicting survival of subjects admitted to hospice, exploring the factors considered most helpful by the hospice staff to accurately predict survival.

METHODS

Five physicians and 11 nurses were asked to predict survival at admission of 827 patients. Actual and predicted survival times were divided into ≤ 1 week, 2-3 weeks, 4-8 weeks, and ≥ 2 months and the accuracy of the estimates was calculated. The staff members were each asked to score 17 clinical variables that guided them in predicting survival and we analyzed how these variables impacted the accuracy.

RESULTS

Physicians' and nurses' accuracy of survival of the patients was 46% and 40% respectively. Survival was underestimated in 20% and 12% and overestimated in 34% and 48% of subjects. Both physicians and nurses considered metastases, comorbidities, dyspnea, disability, tumor site, neurological symptoms, and confusion very important in predicting patients' survival with nurses assigning more importance to intestinal symptoms and pain too. All these factors, with the addition of cough and/or bronchial secretions, were associated with physicians' greater accuracy. In the multivariable models, intestinal symptoms and confusion continued to be associated with greater predictive accuracy. No factors appreciably raised nurses' accuracy.

CONCLUSIONS

Some clinical symptoms rated as relevant by the hospice staff could be important for predicting survival. However, only intestinal symptoms and confusion significantly improved the accuracy of physicians' predictions, despite the high prevalence of overestimated survival.

Efficacy of Ibandronate Loading Dose on Rapid Pain Relief in Patients With Non-Small Cell Lung Cancer and Cancer Induced Bone Pain: The NVALT-9 Trial

Introduction: Approximately 80% of non-small cell lung cancer (NSCLC) patients with bone metastases have cancer induced bone pain (CIBP).

Methods: The NVALT-9 was an open-label, single arm, phase II, multicenter study. Main inclusion criterion: bone metastasized NSCLC patients with uncontrolled CIBP [brief pain inventory [BPI] ≥ 5 over last 7 days]. Patients were treated with six milligram ibandronate intravenously (day 1–3) once a day. Main exclusion criteria: active secondary malignancy, systemic anti-tumor treatment and radiotherapy ≤4 weeks before study start, previous bisphosphonate treatment. Statistics: Simon's Optimal two-stage design with a 90% power to declare the treatment active if the pain response rate is ≥ 80% and 95% confidence to declare the treatment inactive if the pain response rate is ≤ 60%. If pain response is observed in ≤ 12 of the first 19 patients further enrollment will be stopped. Primary endpoint: bone pain response, defined as 25% decrease in worst pain score (PSc) over a 3-day period (day 5–7) compared to baseline PSc with maximum of 25% increase in mean analgesic consumption during the same period. Secondary endpoints: BPI score, quality of life, toxicity and World Health Organization Performance Score.

Results: Of the 19 enrolled patients in the first stage, 18 were evaluable for response. All completed ibandronate treatment according to protocol. In 4 (22.2%), a bone pain response was observed. According to the stopping rule, further enrollment was halted.

Discussion: Ibandronate loading doses lead to insufficient pain relief in NSCLC patients with CIBP.

Prognostic Awareness in Adult Oncology and Palliative Care

Communicating prognosis clearly and empathically can foster accurate prognostic awareness in patients with advanced cancer and their family members. Whereas patients and doctors desire clear prognostic communication, it presents many challenges in oncologic and palliative care settings. Patients with advanced cancer often have poor prognostic awareness as a result of deficiencies in doctor communication and understandable-and potentially adaptive-attempts by patients and families to reduce the threat of death and maintain hope. Interventions to promote prognostic discussion have largely succeeded in increasing the frequency, but not necessarily the quality, of such discussions, yet have failed to improve prognostic awareness. Because clear communication of prognosis is an ethical mandate, more research is needed to provide an evidence base for teaching and practice in this area.

Association between palliative care and end-of-Life care for patients with hematological malignancies: A population-based study

To date, few studies have examined the end-of-life (EOL) care for patients with hematological malignancies (HMs). We evaluated the effects of palliative care on the quality of EOL care and health care costs for adult patients with HMs in the final month of life.We conducted a population-based study and analyzed data from Taiwan's Longitudinal Health Insurance Database, which contains claims information for patient medical records, health care costs, and insurance system exit dates (our proxy for death) between 2000 and 2011.A total of 724 adult patients who died of HMs were investigated. Of these patients, 43 (5.9%) had received only inpatient palliative care (i-Pal group), and 19 (2.6%) received home palliative care (h-Pal group). The mean health care costs during the final month of life were not significantly different between the non-Pal and Pal groups (p=0.315) and between the non-Pal, i-Pal, and h-Pal groups (p=0.293) either. By the multivariate regression model, the i-Pal group had lower risks of chemotherapy, ICU admission, and receipt of CPR, but higher risks of at least two hospitalizations and dying in hospital after adjustments. The h-Pal group had the similar trends as the i-Pal group but lower risk of dying in hospital after adjustments.Patients with HMs who had received palliative care could benefit from less aggressive EOL cancer care in the final month of life. However, 8.6% patients with HMs received palliative care. The related factors of more hospitalizations and dying in hospital warrant further investigation.

Ambulatory Advanced Cancer Patients' and Oncologists' Estimates of Life Expectancy Are Associated with Patient Psychological Characteristics But Not Chemotherapy Use

BACKGROUND

Patients with advanced cancer often face distressing decisions about chemotherapy. There are conflicting data on the relationships among perceived prognosis, psychological characteristics, and chemotherapy use, which impair the refinement of decision support interventions.

OBJECTIVE

Clarify the relationships among patient and oncologist estimates of life expectancy for 6 and 12 months, chemotherapy use, and patient psychological characteristics.

DESIGN

Secondary analysis of data from two cross-sectional studies.

SETTING/SUBJECTS

One hundred sixty-six patients with advanced stage cancer recruited from ambulatory cancer clinics.

MEASUREMENTS

All data were obtained at study enrollment. Patients completed the Adult Hope Scale, Hospital Anxiety and Depression Scale, and Life Orientation Test-Revised. Patients and their oncologists provided estimates of surviving beyond 6 and 12 months. Chemotherapy use was determined by chart review.

RESULTS

There were no significant associations between life-expectancy estimates and chemotherapy use nor patient anxiety, depression, hope, or optimism and chemotherapy use. Patients' life expectancy estimates for 12 months and oncologists' for 6 months were associated with higher patient anxiety and depression. Finally, both oncologist and patient estimates of life expectancy for 6 and 12 months were associated with increased levels of trait hope.

CONCLUSION

Advanced cancer patients who provide less optimistic estimates of life expectancy have increased anxiety and depression, but do not use chemotherapy more often. Increased patient trait hope is associated with more favorable oncologist estimates. These findings highlight the need for interventions to support both patients and oncologists as they clarify prognostic expectations and patients cope with the psychological distress of a limited life expectancy.

Development of Imminent Mortality Predictor for Advanced Cancer (IMPAC), a Tool to Predict Short-Term Mortality in Hospitalized Patients With Advanced Cancer

PURPOSE

End-of-life care for patients with advanced cancer is aggressive and costly. Oncologists inconsistently estimate life expectancy and address goals of care. Currently available prognostication tools are based on subjective clinical assessment. An objective prognostic tool could help oncologists and patients decide on a realistic plan for end-of-life care. We developed a predictive model (Imminent Mortality Predictor in Advanced Cancer [IMPAC]) for short-term mortality in hospitalized patients with advanced cancer.

METHODS

Electronic health record data from 669 patients with advanced cancer who were discharged from Yale Cancer Center/Smilow Cancer Hospital were extracted. Statistical learning techniques were used to develop a tool to estimate survival probabilities. Patients were randomly split into training (70%) and validation (30%) sets 20 times. We tested the predictive properties of IMPAC for mortality at 30, 60, 90, and 180 days past the day of admission.

RESULTS

For mortality within 90 days at a 40% sensitivity level, IMPAC has close to 60% positive predictive value. Patients estimated to have a greater than 50% chance of death within 90 days had a median survival time of 47 days. Patients estimated to have a less than 50% chance of death had a median survival of 290 days. Area under the receiver operating characteristic curve for IMPAC averaged greater than .70 for all time horizons tested. Estimated potential cost savings per patient was $15,413 (95% CI, $9,162 to $21,665) in 2014 constant dollars.

CONCLUSION

IMPAC, a novel prognostic tool, can generate life expectancy probabilities in real time and support oncologists in counseling patients about end-of-life care. Potentially avoidable costs are significant.

Critical care of patients with cancer

Answer questions and earn CME/CNE The increasing prevalence of patients living with cancer in conjunction with the rapid progress in cancer therapy will lead to a growing number of patients with cancer who will require intensive care treatment. Fortunately, the development of more effective oncologic therapies, advances in critical care, and improvements in patient selection have led to an increased survival of critically ill patients with cancer. As a consequence, critical care has become an important cornerstone in the continuum of modern cancer care. Although, in many aspects, critical care for patients with cancer does not differ from intensive care for other seriously ill patients, there are several challenging issues that are unique to this patient population and require special knowledge and skills. The optimal management of critically ill patients with cancer necessitates expertise in oncology, critical care, and palliative medicine. Cancer specialists therefore have to be familiar with key principles of intensive care for critically ill patients with cancer. This review provides an overview of the state-of-the-art in the individualized management of critically ill patients with cancer. CA Cancer J Clin 2016;66:496-517. © 2016 American Cancer Society.

Preparing for Value-Based Payment: A Stepwise Approach for Cancer Centers

Most cancer centers are ill-equipped to pursue value-based payment (VBP) because of limited information on their population’s cost of care. Herein, we outline the stepwise approach used by Smilow Cancer Hospital at Yale-New Haven in our pursuit of better value care. First, we addressed institutional barriers. A move toward value required demonstration to Yale-New Haven Health System leadership that OCM would improve patient care, fund new infrastructure, and provide the opportunity to gain experience with VBP without a major threat to the financial stability of the health system. We evaluated patterns of care and found that of patients presenting to the emergency department (ED), 88% were admitted, 62% arrived during the workday, and 50% could have been stabilized with urgent care services. Within 30 days of death, 27% were admitted to the intensive care unit, 38% presented to the ED, and 52% were admitted. To quantify total cost of care, we accessed the 5% Medicare Limited Data Set to map out total cost of care for patients receiving chemotherapy at Smilow Cancer Hospital. Costs increased as patients moved through 6-month episodes, used the ED (patients with two or more visits were twice as expensive as those with one or fewer), or died during an episode (costs were twice as high as episodes in which the patient lived). To determine strategic interventions to improve value, we targeted investments in urgent care to reduce ED utilization, care management to prevent hospital admissions, and referral to palliative care for clarification of goals of care and avoidance of costly futile treatment. Developing internal metrics to evaluate success will require monitoring our interventions by having utilization measures for each site of care and individual provider.

A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

Background

Prognostic accuracy in palliative care is valued by patients, carers, and healthcare professionals. Previous reviews suggest clinicians are inaccurate at survival estimates, but have only reported the accuracy of estimates on patients with a cancer diagnosis.

Objectives

To examine the accuracy of clinicians’ estimates of survival and to determine if any clinical profession is better at doing so than another.

Data Sources

MEDLINE, Embase, CINAHL, and the Cochrane Database of Systematic Reviews and Trials. All databases were searched from the start of the database up to June 2015. Reference lists of eligible articles were also checked.

Eligibility Criteria

Inclusion criteria: patients over 18, palliative population and setting, quantifiable estimate based on real patients, full publication written in English. Exclusion criteria: if the estimate was following an intervention, such as surgery, or the patient was artificially ventilated or in intensive care.

Study Appraisal and Synthesis Methods

A quality assessment was completed with the QUIPS tool. Data on the reported accuracy of estimates and information about the clinicians were extracted. Studies were grouped by type of estimate: categorical (the clinician had a predetermined list of outcomes to choose from), continuous (open-ended estimate), or probabilistic (likelihood of surviving a particular time frame).

Results

4,642 records were identified; 42 studies fully met the review criteria. Wide variation was shown with categorical estimates (range 23% to 78%) and continuous estimates ranged between an underestimate of 86 days to an overestimate of 93 days. The four papers which used probabilistic estimates tended to show greater accuracy (c-statistics of 0.74–0.78). Information available about the clinicians providing the estimates was limited. Overall, there was no clear “expert” subgroup of clinicians identified.

Limitations

High heterogeneity limited the analyses possible and prevented an overall accuracy being reported. Data were extracted using a standardised tool, by one reviewer, which could have introduced bias. Devising search terms for prognostic studies is challenging. Every attempt was made to devise search terms that were sufficiently sensitive to detect all prognostic studies; however, it remains possible that some studies were not identified.

Conclusion

Studies of prognostic accuracy in palliative care are heterogeneous, but the evidence suggests that clinicians’ predictions are frequently inaccurate. No sub-group of clinicians was consistently shown to be more accurate than any other.

Implications of Key Findings

Further research is needed to understand how clinical predictions are formulated and how their accuracy can be improved.

The average lifespan of patients discharged from hospital with heart failure

BACKGROUND

There are no life-tables quantifying the average life-spans of post-hospitalized heart failure populations across various strata of risk.

OBJECTIVE

To quantify the life-expectancies (i.e., average life-spans) of heart failure patients at the time of hospital discharge according to age, gender, predictive 30-day mortality heart failure risk index, and comorbidity burden.

DESIGN

Population-based retrospective cohort study.

SETTING

Ontario, Canada.

PATIENTS

7,865 heart failure patients discharged from Ontario hospitals between 1999 and 2000.

MEASUREMENTS

Data were obtained from the Enhanced Feedback for Effective Cardiac Treatment EFFECT provincial quality improvement initiative. All patients were linked to administrative data, and tracked longitudinally until March 31, 2010. Detailed clinical variables were obtained from medical chart abstraction, and death data were obtained from vital statistics. Average life-spans were calculated using Cox Proportion Hazards models in conjunction with the Declining Exponential Approximation of Life Expectancy (D.E.A.L.E) method to extrapolate life-expectancy, adjusting for age, gender, predicted 30-day mortality, left ventricular function and comorbidity, and was reported according to key prognostic risk-strata.

RESULTS

The average life-span of the cohort was 5.5 years (STD +/- 10.0) ranging from 19.5 years for low-risk women of less than 50 years old to 2.9 years for high-risk octogenarian males. Average life-spans were lower by 0.13 years among patients with impaired as compared with preserved left ventricular function, and by approximately one year among patients with three or more as compared with no concomitant comorbidities. In total, 17.4 % and 27 % of patients had died within 6 months and 1 year respectively, despite having predicted life-spans exceeding one-year.

LIMITATIONS

Data regarding changes in patient clinical status over time were unavailable.

CONCLUSIONS

The development of risk-adjusted life-tables for heart failure populations is feasible and mirrored those with advanced malignant diseases. Average life span varied widely across clinical risk strata, and may be less accurate among those at or near their end of life.

The eligibility of advanced non-small-cell lung cancer patients for targeted therapy clinical trials

BACKGROUND

The selection criteria for phase III trials are often stringent. We aimed to determine how many advanced non-small-cell lung cancer (NSCLC) patients would have been eligible for phase III targeted therapy trials and the proportion receiving anticancer treatment.

PATIENTS AND METHODS

From March 2007 to May 2008, all advanced NSCLC patients presented at our lung cancer multidisciplinary team meeting were included to assess eligibility for the targeted therapy trials: ECOG-4599, AVAiL, FLEX, TALENT, INTACT-1, INTACT-2, ESCAPE, NEXUS and MONET1. Medical records were examined to determine treatment utilisation and overall survival.

RESULTS

A total of 62 patients were registered: 63% male; median age 71 years; 61% stage IIIB disease. Percentages that met criteria were: ECOG-4599 31%, AVAiL 24%, FLEX 69%, TALENT 27%, INTACT-1 50%, INTACT-2 42%, ESCAPE 39%, NEXUS 63% and MONET1 34%. Common reasons for ineligibility were insufficient life expectancy, poor performance status, abnormal bloods, proteinuria and associated cancer problems. Systemic therapies were received by 66% of patients and median survival was 10.3 months.

CONCLUSION

Only 24%-69% were eligible for targeted therapy trials but 66% received anticancer treatment. Clinical trials in patients with advanced NSCLC need to be more representative of the majority of patients.

Deciding what information is necessary: do patients with advanced cancer want to know all the details?

Communicating effectively with patients who have advanced cancer is one of the greatest challenges facing physicians today. Whilst guiding the patient through complex diagnostic and staging techniques, treatment regimens and trials, the physician must translate often imprecise or conflicting data into meaningful personalized information that empowers the patient to make decisions about their life and body. This requires understanding, compassion, patience, and skill. This narrative literature review explores current communication practices, information preferences of oncology patients and their families, and communication strategies that may assist in these delicate interactions. Overwhelmingly, the literature suggests that whilst the majority of patients with advanced cancer do want to know their diagnosis and receive detailed prognostic information, this varies not only between individuals but also for a given individual over time. Barriers to the delivery and understanding of information exist on both sides of the physician-patient relationship, and family dynamics are also influential. Despite identifiable trends, the information preferences of a particular patient cannot be reliably predicted by demographic, cultural, or cancer-specific factors. Therefore, our primary recommendation is that the physician regularly asks the patient what information they would like to know, who else should be given the information and be involved in decision making, and how that information should be presented.