Palliative performance status, heart rate and respiratory rate as predictive factors of survival time in terminally ill cancer patients

Vital Signs in Palliative Care: A Scoping Review

Vital signs are routinely measured in secondary healthcare settings and can be used to detect clinical problems, guide treatment, and monitor response to treatment. Vital signs are less frequently measured in palliative care settings. Reasons for this are unclear. This scoping review aimed to assess the generic use of vital signs in palliative care, and its role in prognostication for adult patients with cancer receiving palliative care. Medline, Embase, and CINAHL were searched for articles involving adult patients with advanced cancer receiving palliative care who had their vital signs measured. Twenty-six articles were identified in which one or a combination of vital signs, with or without other clinical parameters, was used to prognosticate for patients. An additional three articles investigated the generic use of vital signs in patients with advanced cancer. There was significant heterogeneity between identified studies, with some indication that changes in vital signs may indicate that a patient is close to death. However, other studies suggested that patients may maintain normal vital signs until the time of death. Further studies are needed to explore whether abnormal vital signs may be used as a prognostic indicator for patients with cancer receiving palliative care.

Body Boundary Measurement Using Multiple Line Lasers for a Focused Microwave Thermotherapy System: A Proof-of-Concept Study

A focused microwave thermotherapy system for non-invasively treating cancerous tumors has recently been actively developed. To accurately focus on the target location, the system needs information about the patient's body boundary. However, a water bolus is placed between the human body and the microwave applicators to allow the microwave to penetrate the body more easily and cool the body's skin. The structural configuration makes it difficult to measure the body boundary. In this paper, we present a body boundary measurement method using multiple line lasers and cameras for the application of a focused microwave thermotherapy system. Even with a lack of acquired boundary data, a completely closed boundary line can be reconstructed. In addition, real-time movement tracking is possible as it can be measured quickly, even in situations where the patient is moving, such as breathing and wriggling. The performance is verified with several indicators in a water-filled experimental testbed.

Characteristics and Prognosis of Hospitalized Patients at High Risk of Deterioration Identified by the Rapid Response System: a Multicenter Cohort Study

We aimed to investigate the characteristics and prognosis of high risk hospitalized patients identified by the rapid response system (RRS). A multicentered retrospective cohort study was conducted from June 2019 to December 2020. The National Early Warning Score (NEWS) was used for RRS activation. The outcome was unexpected intensive care unit (ICU) admission within 24 hours after RRS activation. The 11,459 patients with RRS activations were included. We found distinct clinical characteristics in patients who underwent ICU admission. All NEWS parameters were associated with the risk of unexpected ICU admission except body temperature. Body mass index, pulmonary disease, and cancer are related to the decreased risk of unexpected ICU admission. In conclusion, there were differences in clinical characteristics among high risk patients, and those differences were associated with unexpected ICU admissions. Clinicians should consider factors relating to unexpected ICU admission in the management of high risk patients identified by RRS.

Development and progression of cancer cachexia: Perspectives from bench to bedside

Cancer cachexia (CC) is a devastating syndrome characterized by weight loss, reduced fat mass and muscle mass that affects approximately 80% of cancer patients and is responsible for 22%–30% of cancer-associated deaths. Understanding underlying mechanisms for the development of CC are crucial to advance therapies to treat CC and improve cancer outcomes. CC is a multi-organ syndrome that results in extensive skeletal muscle and adipose tissue wasting; however, CC can impair other organs such as the liver, heart, brain, and bone as well. A considerable amount of CC research focuses on changes that occur within the muscle, but cancer-related impairments in other organ systems are understudied. Furthermore, metabolic changes in organ systems other than muscle may contribute to CC. Therefore, the purpose of this review is to address degenerative mechanisms which occur during CC from a whole-body perspective. Outlining the information known about metabolic changes that occur in response to cancer is necessary to develop and enhance therapies to treat CC. As much of the current evidences in CC are from pre-clinical models we should note the majority of the data reviewed here are from pre-clinical models.

Oxygen use and survival in patients with advanced cancer and low oxygen saturation in home care: a preliminary retrospective cohort study

Background

The role of oxygen therapy in end-of-life care for patients with advanced cancer is incompletely understood. We aimed to evaluate the association between oxygen use and survival in patients with advanced cancer and low oxygen saturation in home care.

Methods

We conducted a retrospective cohort study at a primary care practice in suburban Tokyo. Adult patients in home care with advanced cancer demonstrating first low oxygen saturation (less than 90%) detected in home visits were consecutively included in the study. Cox proportional hazards regression was used to investigate the effect of oxygen use on overall survival and survival at home, adjusted for systolic blood pressure, decreased level of consciousness, dyspnea, oral intake, performance status, and cardiopulmonary comorbidity.

Results

Of 433 identified patients with advanced cancer, we enrolled 137 patients (oxygen use, n = 35; no oxygen use, n = 102) who developed low oxygen saturation. In multivariable analysis, the adjusted hazard ratio (HR) of oxygen use was 0.68 (95% confidence interval 0.39–1.17) for death and 0.70 (0.38–1.27) for death at home. In patients with dyspnea, the HR was 0.35 (0.13–0.89) for death and 0.33 (0.11–0.96) for death at home; without dyspnea, it was 1.03 (0.49–2.17) for death and 0.84 (0.36–1.96) for death at home.

Conclusions

Oxygen use was not significantly associated with survival in patients with advanced cancer and low oxygen saturation, after adjusting for potential confounders. It may not be necessary to use oxygen for prolongation of survival in such patients, particularly in those without dyspnea.

Patient-reported symptoms and problems at admission to specialized palliative care improved survival prediction in 30,969 cancer patients: A nationwide register-based study

BACKGROUND

Large, nationally representative studies of the association between quality of life and survival time in cancer patients in specialized palliative care are missing.

AIM

The aim of this study was to investigate whether symptoms/problems at admission to specialized palliative care were associated with survival and if the symptoms/problems may improve prediction of death within 1 week and 1 month, respectively.

SETTING/PARTICIPANTS

All cancer patients who had filled in the EORTC QLQ-C15-PAL at admission to specialized palliative care in Denmark in 2010-2017 were included through the Danish Palliative Care Database. Cox regression was used to identify clinical variables (gender, age, type of contact (inpatient vs outpatient), and cancer site) and symptoms/problems significantly associated with survival. To test whether symptoms/problems improved survival predictions, the overall accuracy (area under the receiver operating characteristic curve) for different prediction models was compared. The validity of the prediction models was tested with data on 5,508 patients admitted to palliative care in 2018.

RESULTS

The study included 30,969 patients with an average age of 68.9 years; 50% were women. Gender, age, type of contact, cancer site, and most symptoms/problems were significantly associated with survival time. The predictive value of symptoms/problems was trivial except for physical function, which clearly improved the overall accuracy for 1-week and 1-month predictions of death when added to models including only clinical variables.

CONCLUSION

Most symptoms/problems were significantly associated with survival and mainly physical function improved predictions of death. Interestingly, the predictive value of physical function was the same as all clinical variables combined (in hospice) or even higher (in palliative care teams).

Predicting survival in patients with advanced cancer in the last weeks of life: How accurate are prognostic models compared to clinicians' estimates?

BACKGROUND

It is unclear if validated prognostic scores such as the Palliative Performance Scale, Palliative Prognostic Index, and Palliative Prognostic Score are more accurate than clinician prediction of survival in patients admitted to an acute palliative care unit with only days of survival.

AIM

We compared the prognostic accuracy of Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival in this setting.

DESIGN

This is a pre-planned secondary analysis of a prospective study.

SETTING/PARTICIPANTS

We assessed Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival at baseline. We computed their prognostic accuracy using the Concordance index and area under the receiver operating characteristics curve for 7-, 14-, and 30-day survival.

RESULTS

A total of 204 patients were included with a median overall survival of 10 days (95% confidence interval: 8-11 days). The Concordance index for Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival were 0.74, 0.71, 0.70, and 0.75, respectively. The areas under the curve for these approaches were 0.82-0.87 for 30-day survival, 0.75-0.80 for 14-day survival, and 0.74-0.81 for 7-day survival. The four prognostic approaches had similar accuracies, with the exception of 7-day survival in which clinician prediction of survival was significantly more accurate than Palliative Prognostic Score (difference: 7%) and Palliative Prognostic Index (difference: 8%).

CONCLUSION

In patients with advanced cancer with days of survival, clinician prediction of survival and Palliative Performance Scale alone were as accurate as Palliative Prognostic Score and Palliative Prognostic Index. These four approaches may be useful for prognostication in acute palliative care units. Our findings highlight how patient population may impact the accuracy of prognostic scores.

Adverse Events in Home Care: Identifying and Responding with interRAI Scales and Clinical Assessment Protocols

Outcomes of adverse events in home care are varied and multifactorial. This study tested a framework combining two health measures to identify home care recipients at higher risk of long-term care placement or death within one year. Both measures come from the Resident Assessment Instrument-Home Care (RAI-HC), a standardized comprehensive clinical assessment. Persons scoring high in the Method for Assigning Priority Levels (MAPLe) algorithm and Changes in Health, End-stage disease, Signs and Symptoms (CHESS) scale were at the greatest risk of placement or death and more than twice as likely to experience either outcome earlier than others. The target group was more likely to trigger mood, social relationship, and caregiver distress issues, suggesting mental health and psychosocial interventions might help in addition to medical care and/or personal support services. Home care agencies can use this framework to identify home care patients who may require a more intensive care coordinator approach.

Prognostic Tools in Patients With Advanced Cancer: A Systematic Review

PURPOSE

In 2005, the European Association for Palliative Care made recommendations for prognostic markers in advanced cancer. Since then, prognostic tools have been developed, evolved, and validated. The aim of this systematic review was to examine the progress in the development and validation of prognostic tools.

METHODS

Medline, Embase Classic and Embase were searched. Eligible studies met the following criteria: patients with incurable cancer, >18 years, original studies, population n ≥100, and published after 2003. Descriptive and quantitative statistical analyses were performed.

RESULTS

Forty-nine studies were eligible, assessing seven prognostic tools across different care settings, primary cancer types, and statistically assessed survival prediction. The Palliative Performance Scale was the most studied (n = 21,082), comprising six parameters (six subjective), was externally validated, and predicted survival. The Palliative Prognostic Score composed of six parameters (four subjective and two objective), the Palliative Prognostic Index composed of nine parameters (nine subjective), and the Glasgow Prognostic Score composed of two parameters (two objective) and were all externally validated in more than 2000 patients with advanced cancer and predicted survival.

CONCLUSION

Various prognostic tools have been validated but vary in their complexity, subjectivity, and therefore clinical utility. The Glasgow Prognostic Score would seem the most favorable as it uses only two parameters (both objective) and has prognostic value complementary to the gold standard measure, which is performance status. Further studies comparing all proved prognostic markers in a single cohort of patients with advanced cancer are needed to determine the optimal prognostic tool.

Longitudinal temporal and probabilistic prediction of survival in a cohort of patients with advanced cancer

CONTEXT

Survival prognostication is important during the end of life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized.

OBJECTIVES

The aims of the study were to examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches.

METHODS

Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at Day -14 (baseline) with accuracy at each time point using a test of proportions.

RESULTS

A total of 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 days (4-20 days). Temporal CPS had low accuracy (10%-40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (P < .05 at each time point) but decreased close to death.

CONCLUSION

Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary.

A simple 5-point scoring system, NaURSE (Na+, urea, respiratory rate and shock index in the elderly), predicts in-hospital mortality in oldest old

BACKGROUND

the mortality is high in acutely ill oldest old patients. Understanding the prognostic factors which influence mortality will help clinicians make appropriate management decisions.

METHODS

we analysed prospective mortality audit data (November 2008 to January 2009) to identify variables associated with in-patient mortality in oldest old. We selected those with P < 0.10 from univariate analysis and determined at which cut-point they served as the strongest predictor of mortality. Using these cut-off points, we constructed multivariate logistic regression models. A 5-point score was derived from cut-off points which were significantly associated with mortality tested in a smaller independent re-audit sample conducted in October 2011.

RESULTS

a total of 405 patients (mean 93.5 ± 2.7 years) were included in the study. The mean length of stay was 18.5 ± 42.4 days and 13.8% died as in-patients. Variables (cut-off values) found to be significantly associated with in-patient mortality were admission sodium (>145 mmol/l), urea (≥14 mmol/l), respiratory rate (>20/min) and shock index (>1.0): creating a 5-point score (NaURSE: NaURS in the Elderly). The crude mortality rates were 9.5, 19.9, 34.4, 66.7, and 100% for scores 0, 1, 2, 3 and 4, respectively. Using the cut-off point of ≥2, the NaURSE score has a specificity of 87% (83.1-90.3) and sensitivity of 39% (28.5-50.0), with an AUC value of 0.69 (0.63-0.76). An external independent validation study (n = 121) showed similar results.

CONCLUSIONS

the NaURSE score may be particularly useful in identifying oldest old who are likely to die in that admission to guide appropriate care.

Symptoms tell it all: a systematic review of the value of symptom assessment to predict survival in advanced cancer patients

PURPOSE

To determine the prognostic meaning of symptoms in patients with advanced cancer.

DESIGN

Medline, Embase, Cochrane and Cinahl databases were systematically explored. The predicting symptoms were also evaluated in the three stages of palliative care: disease-directed palliation, symptom-oriented palliation and palliation in the terminal stage.

RESULTS

Out of 3167 papers, forty-four papers satisfied all criteria. Confusion, anorexia, fatigue, cachexia, weight loss, cognitive impairment, drowsiness, dyspnea, dysphagia, dry mouth and depressed mood were associated with survival in ≥ 50% of the studies evaluating these symptoms. Multivariate analysis showed confusion, anorexia, fatigue, cachexia, weight loss, dyspnea and dysphagia as independent prognostic factors in 30-56% of the studies. In the stage of disease-directed palliation anorexia, cachexia, weight loss, dysphagia and pain and in the stage of symptom-oriented palliation confusion, fatigue, cachexia, weight loss, dyspnea, dysphagia and nausea were shown to be independent predictors of survival in >30% of the studies.

CONCLUSION

Symptoms with independent predictive value are confusion, anorexia, fatigue, cachexia, weight loss, dyspnea and dysphagia. New insights are added by the variance between the three palliative stages.

A 2-week prognostic prediction model for terminal cancer patients in a palliative care unit at a Japanese general hospital

OBJECTIVE

We aimed to develop a prognostic prediction model for 2-week survival among patients with terminal cancer in a palliative care unit (PCU).

METHODS

A prospective cohort study was conducted on terminal cancer patients in the PCU for 11 months at a general hospital in Tokyo, Japan. We collected data regarding demographics, treatment history, performance status, symptoms, and laboratory results. Patients who survived more than 2 weeks were labeled 'long survivors' and those who died within 2 weeks were grouped as 'short survivors'. Stepwise logistic regression model was constructed for the model development and bootstrapping was used for the internal model validation.

RESULTS

In 158 subjects whose data were available for the analysis, 109 (69%) subjects were categorized as long survivors and 49 (31%) subjects as short survivors. A prognostic prediction model with a total score of 8 points was constructed as follows: 2 points each for anorexia, dyspnea, and edema; 1 point each for blood urea nitrogen >25 mg/dl and platelets <260,000/mm(3). Area under the receiver operating characteristic (ROC) curve of this model was 83.2% (95% CI: 75.3-91.0%). Bootstrapped validation beta coefficients of the predictors were similar to the original cohort beta coefficients.

CONCLUSION

Our prognostic prediction model for estimating 14-day survival for patients with terminal cancer on the PCU ward included five clinical predictors that are readily available in the clinical setting and showed a relatively high accuracy. External validation is needed to confirm the model's generalizability.

Heart rate variability and length of survival in hospice cancer patients

We examined the association between heart rate variability (HRV) and survival duration to evaluate the usefulness of HRV as a prognostic factor for hospice cancer patients. In terminally ill cancer patients who visited the Hospice clinic, we checked demographic data, Karnofsky performance scale (KPS), HRV, dyspnea, anorexia, as well as fasting blood glucose and total cholesterol. After following up their duration of survival, we examined meaningful prognostic factors for predicting life expectancy through the survival analysis. A total of 68 patients were included in final analysis. As KPS was lower, or when combined with dyspnea or anorexia, the survival duration was much shorter. HRV parameters except heart rate were all impaired in most patients. In particular, the group with mean heart rate of 100 or more beats per minute and the group with standard deviations of normal-to-normal R-R intervals (SDNN) of 21.3 ms (75 percentile) or less showed significantly shorter survival duration. The final multivariate analysis adjusting for age, gender, fasting blood glucose, and total cholesterol showed that KPS, dyspnea, anorexia, and SDNN were significant prognostic factors in survival duration. For the first time, we report that SDNN is a prognostic factor in terminal cancer patients.

A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer

OBJECTIVE

The aim of the present study is to compare the accuracy in using laboratory data or clinical factors, or both, in predicting probability of dying within 7 days of hospice admission in terminal cancer patients.

METHODS

We conducted a prospective cohort study of 727 patients with terminal cancer. Three models for predicting the probability of dying within 7 days of hospice admission were developed: (i) demographic data and laboratory data (Model 1); (ii) demographic data and clinical symptoms (Model 2); and (iii) combination of demographic data, laboratory data and clinical symptoms (Model 3). We compared the models by using the area under the receiver operator curve using stepwise multiple logistic regression.

RESULTS

We estimated the probability dying within 7 days of hospice admission using the logistic function, P = Exp(betax)/[1 + Exp(betax)]. The highest prediction accuracy was observed in Model 3 (82.3%), followed by Model 2 (77.8%) and Model 1 (75.5%). The log[probability of dying within 7 days/(1 - probability of dying within 7 days)] = -6.52 + 0.77 x (male = 1, female = 0) + 0.59 x (cancer, liver = 1, others = 0) + 0.82 x (ECOG score) + 0.59 x (jaundice, yes = 1, no = 0) + 0.54 x (Grade 3 edema = 1, others = 0) + 0.95 x (fever, yes = 1, no = 0) + 0.07 x (respiratory rate, as per minute) + 0.01 x (heart rate, as per minute) - 0.92 x (intervention tube = 1, no = 0) - 0.37 x (mean muscle power).

CONCLUSIONS

We proposed a computer-assisted estimated probability formula for predicting dying within 7 days of hospice admission in terminal cancer patients.

A framework for assessment in oncology rehabilitation

Although the incidence of cancer in the United States is high, improvements in early diagnosis and treatment have significantly increased survival rates in recent years. Many survivors of cancer experience lasting, adverse effects caused by either their disease or its treatment. Physical therapy interventions, both established and new, often can reverse or ameliorate the impairments (body function and structure) found in these patients, improving their ability to carry out daily tasks and actions (activity) and to participate in life situations (participation). Measuring the efficacy of physical therapy interventions in each of these dimensions is challenging but essential for developing and delivering optimal care for these patients. This article describes the acute and long-term effects of cancer and its treatment and the use of the World Health Organization's International Classification of Functioning, Disability and Health (ICF) as a basis for selection of assessment or outcome tools and diagnostic or screening tools in this population.

The distribution of Yin-Deficient symptoms and their relationship on survival rate in cancer patients with Yin-Deficiency

Yin-Deficiency (YD), representing a status of the human body under lack of nutrition and fluid in traditional Chinese medicine, is commonly seen in late stage of cancer patients. It is not known whether the severity of YD related symptoms/signs can predict the survival rate of cancer patients. This study evaluated the distribution of Yin-deficiency symptoms/signs (YDS) in cancer patients with YD, and investigated whether the severity of YDS can predict the survival rate of cancer patients with YD. From 5 January 2007 to 5 May 2007, we selected 43 cancer patients with diagnosis of YD from hospitalized patients and outpatients. The severity of YD was evaluated by a questionnaire. We further estimated the cumulative probabilities of the survival rates over 4 months since the start of study by the Kaplan-Meier product-limit method, and compared the differences among groups with various severities in each symptom/sign with the use of the log-rank test. The results revealed that, the 3 most common YDS were sleeplessness with annoyance, less or non-coated tongue with or without redness and dry mouth. In the survival rate analysis, only 2 parameters, rapidly small pulse (p = 0.002) and less-or non-coated tongue with paleness (p = 0.017), were found to be related to the decrease of cancer patients with YD. This suggests that, both rapidly small pulse and less-or non-coated tongue without redness may be used as predictors for the estimation of survival rate in cancer patients with YD.

Pronóstico de supervivencia en el cáncer avanzado

Accurate prognoses are important in the care of patients with advanced cancer to assist clinicians in their decision making, and to help patients set their goals and priorities. Several studies have demonstrated that doctors are inaccurate and overly optimistic when predicting the survival of patients with advanced and terminal cancer. To improve prognostic accuracy, clinicians can use a number of factors that have proven to be associated with life expectancy: performance status, some signs and symptoms and some laboratory markers. Prognostic scores including most of the factors are also developed. Patients and their families can benefit from realistic prognostic information in a simple and empathetic manner.