Successful validation of the palliative prognostic score in terminally ill cancer patients. Italian Multicenter Study Group on Palliative Care

Comparison of Simplified Palliative Prognostic Index and Palliative Performance Scale in Patients with Advanced Cancer in a Home Palliative Care Setting

Objective: The Palliative Performance Scale (PPS) has been reported to be as accurate as Palliative Prognostic Index (PPI). PPS is a component of the simplified PPI (sPPI). It is unknown whether PPS is as accurate as sPPI. This study aimed to compare the prognostic performance of the PPS and sPPI in patients with advanced cancer in a home palliative care setting in South Korea. Methods: This was a secondary analysis of a prospective cohort study that included Korean patients with advanced cancer who received home-based palliative care. We used the medical records maintained by specialized palliative care nurses. We computed the prognostic performance of PPS and sPPI using the area under the receiver operating characteristic curve (AUROC) and calibration plots for the 3- and 6-week survival. Results: A total of 80 patients were included, with a median overall survival of 47.0 days. The AUROCs of PPS were 0.71 and 0.69 at the 3- and 6-week survival predictions, respectively. The AUROCs of sPPI were 0.87 and 0.73 at the 3- and 6-week survival predictions, respectively. The calibration plot demonstrated satisfactory agreement across all score ranges for both the PPS and sPPI. Conclusions: This study showed that the sPPI assessed by nurses was more accurate than the PPS in a home palliative care setting in predicting the 3-week survival in patients with advanced cancer. The PPS can be used for a quick assessment.

Relationship Between Corticosteroid Administration and Survival Period in Terminal Cancer Patients

Objective: Corticosteroids are commonly used for symptom relief in patients with terminal cancer, but their use may have an impact on patient survival. We compared the survival of patients with terminal cancer who did and did not receive corticosteroid treatment for symptom relief, stratified by their predicted prognosis. Methods: We retrospectively reviewed consecutive patients with cancer who received corticosteroid treatment for symptom relief in a single palliative care unit. We stratified the patients according to their predicted prognosis using the palliative prognostic (PaP) score either before starting the corticosteroid treatment or at admission for control patients who did not receive a corticosteroid treatment. The 2 groups were compared for survival based on the PaP Scores. Results: We analyzed 204 patients treated with a corticosteroid during the study period and 139 control patients who did not receive corticosteroids during their treatment. No difference was observed in the survival between the treatment and control groups. Conclusion: Corticosteroid treatment for symptom relief in patients with terminal cancer did not affect survival time.

Comparison of Prognostic Abilities of Palliative Prognostic Index, Laboratory Prognostic Score, and Palliative Prognostic Score

CONTEXT

Few studies have compared the prognostic value of scoring systems based on physical and blood parameters in terminally ill patients with cancer.

OBJECTIVES

This study evaluated the prognostic abilities of Palliative Prognostic Index (PPI), Laboratory Prognostic Score (LPS), and Palliative Prognostic Score (PaP).

METHODS

We included 989 terminally ill patients with cancer who consulted for admission to our palliative care unit. We compared the discriminative abilities of PPI, LPS, and PaP for 7-, 14-, 30-, 60-, and 90-day mortality. Additionally, we compared the estimated median survival of PPI, LPS, and PaP with the actual survival (AS). The prediction accuracy was considered adequate if the ratio of estimated median survival in days to AS in days fell within the range of 0.66 to 1.33, optimistic when it exceeds 1.33, and pessimistic when it falls below 0.66.

RESULTS

The accuracies for 7-, 14-, 30-, 60-, and 90-day mortality were superior for PPI, LPS, LPS, PaP, and PaP (72%, 73%, 71%, 80%, and 82%), respectively, although the discriminative abilities for 7-, 14-, 30-, 60-, and 90-day mortality were similar among the three scoring systems. The prediction accuracy of survival (PAS) was similar among the three scoring systems with adequate, optimistic, and pessimistic rates of 36-41%, 20-46%, and 16-38%, respectively. PAS was superior in actual survival for 14-59 days.

CONCLUSIONS

The prognostic abilities of PPI, LPS, and PaP were comparable. The most adequate estimation occurred for patients with AS for 14-59 days. A more accurate prognostic model is needed for patients with longer survival.

Changepoint Detection in Heart Rate Variability Indices in Older Patients Without Cancer at End of Life Using Ballistocardiography Signals: Preliminary Retrospective Study

BACKGROUND

In an aging society such as Japan, where the number of older people continues to increase, providing in-hospital end-of-life care for all deaths, and end-of-life care outside of hospitals, such as at home or in nursing homes, will be difficult. In end-of-life care, monitoring patients is important to understand their condition and predict survival time; this information gives family members and caregivers time to prepare for the end of life. However, with no clear indicators, health care providers must subjectively decide if an older patient is in the end-of-life stage, considering factors such as condition changes and decreased food intake. This complicates decisions for family members, especially during home-based care.

OBJECTIVE

The purpose of this preliminary retrospective study was to determine whether and how changes in heart rate variability (HRV) indices estimated from ballistocardiography (BCG) occur before the date of death in terminally ill older patients, and ultimately to predict the date of death from the changepoint.

METHODS

This retrospective pilot study assessed the medical records of 15 older patients admitted to a special nursing home between August 2019 and December 2021. Patient characteristics and time-domain HRV indices such as the average normal-to-normal (ANN) interval, SD of the normal-to-normal (SDNN) interval, and root mean square of successive differences (RMSSD) from at least 2 months before the date of death were collected. Overall trends of indices were examined by drawing a restricted cubic spline curve. A repeated measures ANOVA was performed to evaluate changes in the indices over the observation period. To explore more detailed changes in HRV, a piecewise regression analysis was conducted to estimate the changepoint of HRV indices.

RESULTS

The 15 patients included 8 men and 7 women with a median age of 93 (IQR 91-96) years. The cubic spline curve showed a gradual decline of indices from approximately 30 days before the patients' deaths. The repeated measures ANOVA showed that when compared with 8 weeks before death, the ratio of the geometric mean of ANN (0.90, 95% CI 0.84-0.98; P=.005) and RMSSD (0.83, 95% CI 0.70-0.99; P=.03) began to decrease 3 weeks before death. The piecewise regression analysis estimated the changepoints for ANN, SDNN, and RMSSD at -34.5 (95% CI -42.5 to -26.5; P<.001), -33.0 (95% CI -40.9 to -25.1; P<.001), and -35.0 (95% CI -42.3 to -27.7; P<.001) days, respectively, before death.

CONCLUSIONS

This preliminary study identified the changepoint of HRV indices before death in older patients at end of life. Although few data were examined, our findings indicated that HRV indices from BCG can be useful for monitoring and predicting survival time in older patients at end of life. The study and results suggest the potential for more objective and accurate prognostic tools in predicting end-of-life outcomes.

Decision tree algorithm to predict mortality in incurable cancer: a new prognostic model

OBJECTIVES

To develop and validate a new prognostic model to predict 90-day mortality in patients with incurable cancer.

METHODS

In this prospective cohort study, patients with incurable cancer receiving palliative care (n = 1322) were randomly divided into two groups: development (n = 926, 70%) and validation (n = 396, 30%). A decision tree algorithm was used to develop a prognostic model with clinical variables. The accuracy and applicability of the proposed model were assessed by the C-statistic, calibration and receiver operating characteristic (ROC) curve.

RESULTS

Albumin (75.2%), C reactive protein (CRP) (47.7%) and Karnofsky Performance Status (KPS) ≥50% (26.5%) were the variables that most contributed to the classification power of the prognostic model, named Simple decision Tree algorithm for predicting mortality in patients with Incurable Cancer (acromion STIC). This was used to identify three groups of increasing risk of 90-day mortality: STIC-1 - low risk (probability of death: 0.30): albumin ≥3.6 g/dL, CRP <7.8 mg/dL and KPS ≥50%; STIC-2 - medium risk (probability of death: 0.66 to 0.69): albumin ≥3.6 g/dL, CRP <7.8 mg/dL and KPS <50%, or albumin ≥3.6 g/dL and CRP ≥7.8 mg/dL; STIC-3 - high risk (probability of death: 0.79): albumin <3.6 g/dL. In the validation dataset, good accuracy (C-statistic ≥0.71), Hosmer-Lemeshow p=0.12 and area under the ROC curve=0.707 were found.

CONCLUSIONS

STIC is a valid, practical tool for stratifying patients with incurable cancer into three risk groups for 90-day mortality.

Malignancy-related ascites in palliative care units: prognostic factor analysis

OBJECTIVES

The prognostic factors in patients with malignancy-related ascites (MA) have been poorly investigated. This study aimed to evaluate both the prognostic impact of MA on terminally ill patients with cancer and the prognostic factors in those with MA.

METHODS

This was a post hoc analysis of a multicentre, prospective cohort study. Patients with advanced cancer admitted to palliative care units at 23 institutions and aged≥18 years were enrolled between January and December 2017. Overall survival (OS) was compared according to MA. A multivariate analysis was conducted to explore prognostic factors in patients with MA.

RESULTS

Of 1896 eligible patients, gastrointestinal and hepatobiliary pancreatic cancers accounted for 42.5%. 568 (30.0%) of the total had MA. Patients with MA had significantly shorter OS than those without MA (median, 14 vs 22 days, respectively; HR, 1.55; 95% CI, 1.39 to 1.72; p<0.01). A multivariate analysis showed that MA was a poor prognostic factor (HR, 1.30; 95% CI, 1.13 to 1.50; p<0.01) and that among patients with MA, significant poor prognostic factors were liver metastasis, moderately to severely reduced oral intake, delirium, oedema, gastric cancer, high serum creatinine, high serum C reactive protein, high serum total bilirubin, dyspnoea and fatigue, while significant good prognostic factors were female sex, good performance status, high serum albumin and colorectal cancer.

CONCLUSIONS

MA had a negative impact on survival in terminally ill patients with cancer. A multivariate analysis revealed several prognostic factors in patients with terminal cancer and MA.

Appropriateness of Mini-Invasive Approaches for Nausea and Vomiting Refractory to Medical Therapy in Palliative Care Setting: A Case Report

Introduction

Nausea and vomiting are frequent multifactorial symptoms in oncological patients. These manifestations, mainly affecting the advanced disease stages, may lead to existential, psychological, and physical suffering, with a negative impact on the quality of life (QoL) of the individual and his family. The medical approach makes use of a wide range of drugs, with different antiemetic potency and various mechanisms of action, taking into account the etiology and the patient's response to the different therapeutic strategies. In recent years, in addition to pharmacological treatments, some endoscopic procedures have been integrated into clinical practice as promising palliative approaches.

Case Presentation

Herein, we describe and discuss a case of a 64-year-old female affected by advanced stage pancreatic adenocarcinoma, in which different techniques - both medical and endoscopic - have been used to approach a refractory symptomatology with a negative impact on the patient's QoL. In the context of a multidisciplinary approach in primary palliative care, a tailored intervention encompassing invasive methods for palliative purposes, may be considered adequate and appropriate when the prognostic expectation and the physical functionality indices allow it.

Conclusion

Minimally invasive palliative interventions should be offered to patients with advanced cancer when symptoms become refractory to standard medical therapies, as part of the holistic approach in modern treatments. Therefore, the integration of an early palliative approach into the patient's therapeutic path becomes essential for the management of all the individual's needs.

Usefulness of the Palliative Prognostic Index in Predicting Prognosis when Considering the Transition from Hospital to Home Care in Patients with Terminal Stage Cancer

BACKGROUND

No accurate prognostic tool is available for patients with cancer who spend their final days at home. In this study, we examined whether performance status (PS) and the palliative prognostic index (PPI), a well-known prognostic tool in palliative care units, could be used to predict prognosis in the home care setting at the time of intervention by home physicians.

SUBJECTS AND METHODS

Using medical records, we conducted a retrospective analysis of 132 patients who were referred to the Home Clinic Naginoki for home care for terminal stages of carcinoma in situ. Based on the status at the time of the first visit, the PPI-Low group was defined as those scoring six or below and the PPI-High group as those scoring greater than six.

RESULTS

The PPI-high group had a significantly poorer prognosis within 21 days than the PPI-low group (21-day-OS; Low 71.4% vs. High 13.2%; p<0.001). The Eastern Cooperative Oncology Group (ECOG) PS alone predicted better prognosis in the group with PS of one or two (21-day survival 90.1%), and the PPI score further significantly stratified the prognosis for patients with PS three or four, with a trend toward poor prognosis (p ≤ 0.005).

CONCLUSION

ECOG PS 1 or 2 has a favorable prognosis and that using PPI in ECOG PS 3 or 4 leads to a more accurate prognosis prediction. PPI evaluated during the hospital-based treatment of patients with terminal cancer can also be used to predict prognosis if the patient is transitioned to a home care environment.

Routine laboratory parameters to support decision on parenteral nutrition in palliative care

Introduction

Parenteral nutrition (PN) is widely used in palliative care (PC), but there is limited evidence to support its use at the end of life (EOL). This aim of this was to investigate the relationship between routine laboratory parameters and survival in patients receiving PN, and to develop a decision tree model to support clinicians decide whether to start or forgo PN.

Methods

The laboratory parameters of 113 patients with advanced diseases who were admitted to a specialized palliative care unit (PCU) were analyzed at two points in time: T0 = before PN, T1 = two weeks after initiation of PN. Univariate Mann-Whitney U-tests and multivariate linear regression models, as well as a decision tree analysis were computed; all in relation to survival time.

Results

The final regression model was significant with p = 0.001 (adjusted R2 = 0.15) and included two predictors for survival time after PN initiation: the CRP/albumin ratio and urea at T1 (ps = 0.019). Decision tree analysis revealed three important predictors for classification of survival time after PN initiation: CRP, urea, and LDH (all at T0).

Discussion

The decision tree model may help to identify patients likely to benefit from PN, thus supporting the clinical decision whether or not to start PN.

Facing uncertainty - Pilot testing of a palliative prognostic index training with hospital aged care assessment teams

BACKGROUND

Prognostic avoidance can delay discussions about older hospital patients' life expectancy. This pilot study examined the effects of a prognostic training program on hospital clinicians' knowledge and confidence in identifying older patients at risk of dying.

METHODS

Fifty-seven clinicians from aged care assessment teams at two Australian hospitals were introduced to the Palliative Prognostic Index, a 5-item checklist indicating prognoses between 3 and 6 weeks. Mixed-methods training evaluation included pre-post-training surveys and semi-structured interviews, conducted three months post-training.

RESULTS

Clinicians used a combination of experience, knowledge, and intuition as strategies to generate prognoses. Allied health staff relied on intuition more often than medical and nursing staff. Prognostic tools were rarely used. Pre-post-training comparisons showed significant improvements in clinicians' knowledge and confidence in identifying signs of dying, particularly amongst allied health. Follow-up interviews highlighted advantages and challenges of using prognostic tools. Recommendations are made for addressing these.

Evaluating the Potential of Machine Learning and Wearable Devices in End-of-Life Care in Predicting 7-Day Death Events Among Patients With Terminal Cancer: Cohort Study

BACKGROUND

An accurate prediction of mortality in end-of-life care is crucial but presents challenges. Existing prognostic tools demonstrate moderate performance in predicting survival across various time frames, primarily in in-hospital settings and single-time evaluations. However, these tools may fail to capture the individualized and diverse trajectories of patients. Limited evidence exists regarding the use of artificial intelligence (AI) and wearable devices, specifically among patients with cancer at the end of life.

OBJECTIVE

This study aimed to investigate the potential of using wearable devices and AI to predict death events among patients with cancer at the end of life. Our hypothesis was that continuous monitoring through smartwatches can offer valuable insights into the progression of patients at the end of life and enable the prediction of changes in their condition, which could ultimately enhance personalized care, particularly in outpatient or home care settings.

METHODS

This prospective study was conducted at the National Taiwan University Hospital. Patients diagnosed with cancer and receiving end-of-life care were invited to enroll in wards, outpatient clinics, and home-based care settings. Each participant was given a smartwatch to collect physiological data, including steps taken, heart rate, sleep time, and blood oxygen saturation. Clinical assessments were conducted weekly. The participants were followed until the end of life or up to 52 weeks. With these input features, we evaluated the prediction performance of several machine learning-based classifiers and a deep neural network in 7-day death events. We used area under the receiver operating characteristic curve (AUROC), F1-score, accuracy, and specificity as evaluation metrics. A Shapley additive explanations value analysis was performed to further explore the models with good performance.

RESULTS

From September 2021 to August 2022, overall, 1657 data points were collected from 40 patients with a median survival time of 34 days, with the detection of 28 death events. Among the proposed models, extreme gradient boost (XGBoost) yielded the best result, with an AUROC of 96%, F1-score of 78.5%, accuracy of 93%, and specificity of 97% on the testing set. The Shapley additive explanations value analysis identified the average heart rate as the most important feature. Other important features included steps taken, appetite, urination status, and clinical care phase.

CONCLUSIONS

We demonstrated the successful prediction of patient deaths within the next 7 days using a combination of wearable devices and AI. Our findings highlight the potential of integrating AI and wearable technology into clinical end-of-life care, offering valuable insights and supporting clinical decision-making for personalized patient care. It is important to acknowledge that our study was conducted in a relatively small cohort; thus, further research is needed to validate our approach and assess its impact on clinical care.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05054907; https://classic.clinicaltrials.gov/ct2/show/NCT05054907.

Guidelines for goals of care discussions in patients with gynecologic cancer

This article represents a distillation of literature to provide guidance for goals of care discussions with patients who have gynecologic malignancies. As clinicians who provide surgical care, chemotherapy, and targeted therapeutics, gynecologic oncology clinicians are uniquely positioned to form longitudinal relationships with patients that can enable patient-centered decision making. In this review, we describe optimal timing, components, and best practices for goals of care discussions in gynecologic oncology.

Liver-specific metastases as an independent prognostic factor in cancer patients receiving hospice care in hospital

BACKGROUND

Survival prediction is important in cancer patients receiving hospice care. Palliative prognostic index (PPI) and palliative prognostic (PaP) scores have been used to predict survival in cancer patients. However, cancer primary site with metastatic status, enteral feeding tubes, Foley catheter, tracheostomy, and treatment interventions are not considered in aforementioned tools. The study aimed to investigate the cancer features and potential clinical factors other than PPI and PaP to predict patient survival.

METHODS

We conducted a retrospective study for cancer patients admitted to a hospice ward between January 2021 and December 2021. We examined the correlation of PPI and PaP scores with survival time since hospice ward admission. Multiple linear regression was used to test the potential clinical factors other than PPI and PaP for predicting survival.

RESULTS

A total of 160 patients were enrolled. The correlation coefficients for PPI and PaP scores with survival time were -0.305 and -0.352 (both p < 0.001), but the predictabilities were only marginal at 0.087 and 0.118, respectively. In multiple regression, liver metastasis was an independent poor prognostic factor as adjusted by PPI (β = -8.495, p = 0.013) or PaP score (β = -7.139, p = 0.034), while feeding gastrostomy or jejunostomy were found to prolong survival as adjusted by PPI (β = 24.461, p < 0.001) or PaP score (β = 27.419, p < 0.001).

CONCLUSIONS

Association between PPI and PaP with patient survival in cancer patients at their terminal stages is low. The presence of liver metastases is a poor survival factor independent of PPI and PaP score.

Cancer-associated cachexia - understanding the tumour macroenvironment and microenvironment to improve management

Cachexia is a devastating, multifactorial and often irreversible systemic syndrome characterized by substantial weight loss (mainly of skeletal muscle and adipose tissue) that occurs in around 50-80% of patients with cancer. Although this condition mainly affects skeletal muscle (which accounts for approximately 40% of total body weight), cachexia is a multi-organ syndrome that also involves white and brown adipose tissue, and organs including the bones, brain, liver, gut and heart. Notably, cachexia accounts for up to 20% of cancer-related deaths. Cancer-associated cachexia is invariably associated with systemic inflammation, anorexia and increased energy expenditure. Understanding these mechanisms is essential, and the progress achieved in this area over the past decade could help to develop new therapeutic approaches. In this Review, we examine the currently available evidence on the roles of both the tumour macroenvironment and microenvironment in cancer-associated cachexia, and provide an overview of the novel therapeutic strategies developed to manage this syndrome.

Prognostic evaluation in patients with advanced cancer in the last months of life: ESMO Clinical Practice Guideline

•This ESMO Clinical Practice Guideline provides key recommendations for using prognostic estimates in advanced cancer. •The guideline covers recommendations for patients with cancer and an expected survival of months or less. •An algorithm for use of clinical predictions, prognostic factors and multivariable risk prediction models is presented. •The author group encompasses a multidisciplinary group of experts from different institutions in Europe, USA and Asia. •Recommendations are based on available scientific data and the authors’ collective expert opinion.

Psycho-Educational and Rehabilitative Intervention to Manage Cancer Cachexia (PRICC) for Advanced Patients and Their Caregivers: Lessons Learned from a Single-Arm Feasibility Trial

Background: Key elements in cancer cachexia (CC) management are personalized and multimodal interventions, but it is hard for some patients to follow programs based on several components. We examined the feasibility of a bimodal intervention, including a psycho-educational component and exercises, to support patients and their caregivers in managing CC; Methods: Prospective mixed-methods pilot study explored feasibility data, changes in patient-reported outcomes, and performance outcomes over time in a convenient sample of 30 consecutive CC patients and their caregivers. Results: Twenty-four dyads consented to participate. Twenty dyads received at least two psycho-educational sessions, so the psycho-educational component was feasible for 83.3% of the sample. Six dyads participated in at least fourteen out of twenty-seven rehabilitation sessions, so the exercise program was feasible for 25.0% of the sample. Six dyads showed compliance greater than 50% for both components of the bimodal intervention. Conclusions: While we did not meet our primary feasibility endpoint and had mixed acceptability, our experience provides insight into the challenges and lessons learned in implementing a primary palliative care intervention for CC. More robust studies are needed to help clinicians understand the best exercise program for CC patients, to be included in a multimodal intervention.

Predicting survival in metastatic non-small cell lung cancer patients with poor ECOG-PS: A single-arm prospective study

BACKGROUND

Patients with advanced non-small cell lung cancer (NSCLC) are a heterogeneous population with short lifespan. We aimed to develop methods to better differentiate patients whose survival was >90 days.

METHODS

We evaluated 83 characteristics of 106 treatment-naïve, stage IV NSCLC patients with Eastern Cooperative Oncology Group Performance Status (ECOG-PS) >1. Automated machine learning was used to select a model and optimize hyperparameters. 100-fold bootstrapping was performed for dimensionality reduction for a second ("lite") model. Performance was measured by C-statistic and accuracy metrics in an out-of-sample validation cohort. The "lite" model was validated on a second independent, prospective cohort (N = 42). Network analysis (NA) was performed to evaluate the differences in centrality and connectivity of features.

RESULTS

The selected method was ExtraTrees Classifier, with C-statistic of 0.82 (p < 0.01) and accuracy of 0.81 (p = 0.01). The "lite" model had 16 variables and obtained C-statistic of 0.84 (p < 0.01) and accuracy of 0.75 (p = 0.039) in the first cohort, and C-statistic of 0.706 (p < 0.01) and accuracy of 0.714 (p < 0.01) in the second cohort. The networks of patients with lower survival were more interconnected. Features related to cachexia, inflammation, and quality of life had statistically different prestige scores in NA.

CONCLUSIONS

Machine learning can assist in the prognostic evaluation of advanced NSCLC. The model generated with a reduced number of features showed high accessibility and reasonable metrics. Features related to quality of life, cachexia, and performance status had increased correlation and importance scores, suggesting that they play a role at later disease stages, in line with the biological rationale already described.

Prognostic factors in patients in the terminal phase of haematological malignancies who are receiving home medical care

Although there are many prognostic models for patients in the terminal phase of solid tumours, a reliable prognostic scoring system in patients in the terminal phase of haematological malignancies (HM) has not been established. We retrospectively evaluated 180 patients in the terminal phase of HM who were receiving home medical care (HMC). Multivariate analyses revealed that clinician's estimate, consciousness, loss of appetite, dyspnoea, neutrophil count, lymphocyte count, and lactate dehydrogenase were associated with overall survival (OS). Based on this result, we developed a novel prognostic scoring system, the Japan palliative haematological oncology prognostic estimates, in which four risk groups were shown to clearly differ in survival (p < 0.001): a low-risk group (n = 41, median OS of 434 days), an intermediate-low-risk group (n = 80, median OS of 112 days), an intermediate-high-risk group (n = 38, median OS of 31.5 days), and a high-risk group (n = 21, median OS of 10 days). This is the first investigation of prognostic factors that influence the OS of patients in the terminal phase of HM who are receiving HMC. Providing patients with reliable information about their prognosis is important for them to consider how to spend their remaining life.

Risk factors of sudden unexpected death in patients with advanced cancer near the end of life

BACKGROUND

The definition of sudden unexpected death (SUD) in patients with advanced cancer near the end of life (EOL) was unclear.

METHODS

This study was conducted as a single-center retrospective analysis. We analyzed 1,282 patients who died of advanced cancer from August 2011 to August 2019 retrospectively. We divided into patients who died within 24 h after the acute change of general condition or others and analyzed risk factors by a multiple logistics method. The reason for SUD was found, the reason is detected by using an electronic medical record retrospectively. The risk factors in SUD were analyzed using age, sex, EOL symptom and treatment, the primary site of cancer, metastatic site of cancer, comorbidly, chemotherapy, and Eastern Cooperative Oncology Group Performance Status. The primary endpoint was to identify the frequency and risk factors of SUD in patients with advanced cancer near the EOL.

RESULTS

As a background, the median age is 73 years old, 690 males, 592 females, 227 gastroesophageal cancers, 250 biliary pancreatic cancers, 54 hepatocellular carcinomas, 189 colorectal cancer, 251 lung cancers, 71 breast cancers, 58 urological malignancies, 60 gynecological malignancies, 47 head and neck cancer, 31 hematological malignancies, and 22 sarcomas. The number of patients who died suddenly was 93 (7.2%) at EOL. In a multivariate analysis, Age (ORs 0.619), sex (ORs 1.700), patients with EOL delirium (ORs 0.483), nausea and vomiting (ORs 2.263), 1L or more infusion (ORs 3.479), EOL opioids (ORs 0.465), EOL sedations (ORs 0.339), and with cardiac comorbidity (ORs 0.345) were independent risk factors.

CONCLUSIONS

The frequency of patients who died suddenly was 7.2% (n = 93) at EOL. Age, sex, EOL symptom, EOL treatment, and cardiac comorbidity were independent risk factors in patients with advanced cancer near the EOL. Information on these risk factors is useful to explaining their EOL in advance.

The Palliative Prognostic (PaP) Score without Clinical Evaluation Predicts Early Mortality among Advanced NSCLC Patients Treated with Immunotherapy

Background: An acceptable risk-benefit ratio may encourage the prescription of immune checkpoint inhibitors (ICI) near the late stage of life. The lung immune prognostic index (LIPI) was validated in advanced non-small cell lung cancer (NSCLC) patients treated with ICIs. The palliative prognostic (PaP) score without clinical prediction of survival (PaPwCPS) predicts early mortality probability in terminal cancer patients. Methods: We performed a retrospective study including 182 deceased advanced NSCLC patients, treated with single-agent ICI at our Institution. Two prognostic categories of high and low mortality risk were identified through ROC curve analysis for PaPwCPS and LIPI scores. Results: Most were >65 years of age (68.3%) and received second-line ICI (61.2%). A total of 29 (15.9%) and 131 (72.0%) patients died within 30 and 90 days from treatment start, respectively. A total of 81 patients (44.5%) received ICI during the last month of life. Baseline PaPwCPS and LIPI scores were assessable for 78 patients. The AUC of ROC curves was significantly increased for PaPwCPS as compared with LIPI score for both 30-day and 90-day mortality. A high PaPwCPS score was associated in multivariate analysis with increased 30-day (HR 2.69, p = 0.037) and 90-day (HR 4.01, p < 0.001) mortality risk. A high LIPI score was associated with increased 90-day mortality risk (p < 0.001). Conclusion: We found a tendency towards ICI prescription near the late stage of life. The PaPwCPS score was a reliable predictor of 30- and 90-day mortality.

Prognostication in palliative radiotherapy—ProPaRT: Accuracy of prognostic scores

Background

Prognostication can be used within a tailored decision-making process to achieve a more personalized approach to the care of patients with cancer. This prospective observational study evaluated the accuracy of the Palliative Prognostic score (PaP score) to predict survival in patients identified by oncologists as candidates for palliative radiotherapy (PRT). We also studied interrater variability for the clinical prediction of survival and PaP scores and assessed the accuracy of the Survival Prediction Score (SPS) and TEACHH score.

Materials and methods

Consecutive patients were enrolled at first access to our Radiotherapy and Palliative Care Outpatient Clinic. The discriminating ability of the prognostic models was assessed using Harrell’s C index, and the corresponding 95% confidence intervals (95% CI) were obtained by bootstrapping.

Results

In total, 255 patients with metastatic cancer were evaluated, and 123 (48.2%) were selected for PRT, all of whom completed treatment without interruption. Then, 10.6% of the irradiated patients who died underwent treatment within the last 30 days of life. The PaP score showed an accuracy of 74.8 (95% CI, 69.5–80.1) for radiation oncologist (RO) and 80.7 (95% CI, 75.9–85.5) for palliative care physician (PCP) in predicting 30-day survival. The accuracy of TEACHH was 76.1 (95% CI, 70.9–81.3) and 64.7 (95% CI, 58.8–70.6) for RO and PCP, respectively, and the accuracy of SPS was 70 (95% CI, 64.4–75.6) and 72.8 (95% CI, 67.3–78.3).

Conclusion

Accurate prognostication can identify candidates for low-fraction PRT during the last days of life who are more likely to complete the planned treatment without interruption.

All the scores showed good discriminating capacity; the PaP had the higher accuracy, especially when used in a multidisciplinary way.

The ostrich approach - Prognostic avoidance, strategies and barriers to assessing older hospital patients' risk of dying

BACKGROUND

Predicting older patients' life expectancy is an important yet challenging task. Hospital aged care assessment teams advise treating teams on older patients' type and place of care, directly affecting quality of care. Yet, little is known about their experiences with prognostication.

METHODS

Twenty semi-structured interviews were conducted with seven geriatricians/ registrars, ten nurses and three allied health staff from aged care assessment teams across two hospitals in Melbourne, Australia. Data were analysed thematically.

RESULTS

To generate prognoses, clinicians used analytical thinking, intuition, assessments from others, and pattern matching. Prognostic tools were an underutilised resource. Barriers to recognition of dying included: diffusion of responsibility regarding whose role it is to identify patients at end-of-life; lack of feedback about whether a prognosis was correct; system pressures to pursue active treatment and vacate beds; avoidance of end-of-life discussions; lack of confidence, knowledge and training in prognostication and pandemic-related challenges.

Development and Validation of the PaP Score Nomogram for Terminally Ill Cancer Patients

The validated Palliative Prognostic (PaP) score predicts survival in terminally ill cancer patients, assigning patients to three different risk groups according to a 30-day survival probability: group A, >70%; group B, 30−70%; and group C, <30%. We aimed to develop and validate a PaP nomogram to provide individualized prediction of survival at 15, 30 and 60 days. Three cohorts of consecutive terminally ill cancer patients were used: one (n = 519) for nomogram development and internal validation, and a second (n = 451) and third (n = 549) for external validation. Multivariate analyses included dyspnea, anorexia, Karnofsky performance status, clinical prediction of survival, total white blood count and lymphocyte percentage. The predictive accuracy of the nomogram was determined by Harrell’s concordance index (95% CI), and calibration plots were generated. The nomogram had a concordance index of 0.74 (0.72−0.75) and showed good calibration. The internal validation showed no departures from ideal prediction. The accuracy of the nomogram at 15, 30 and 60 days was 74% (70−77), 89% (85−92) and 72% (68−76) in the external validation cohorts, respectively. The PaP nomogram predicts the individualized estimate of survival and could greatly facilitate clinical care decision-making at the end of life.

End-of-life care in cancer patients: how much drug therapy and how much palliative care? Record linkage study in Northern Italy

OBJECTIVES

Investigating end-of-life use of anticancer drugs and of palliative care services.

DESIGN

Population based cohort linked to mortality registry and administrative databases.

SETTING

Emilia-Romagna Region (Northern Italy).

PARTICIPANTS

55 625 residents who died of cancer between 2017 and 2020.

PRIMARY AND SECONDARY OUTCOME MEASURES

Multivariate analyses were carried out to assess the relationship between cancer drug therapy and palliative care services, and their association with factors related to tumour severity.

RESULTS

In the last month of life, 15.3% of study population received anticancer drugs (from 12.5% to 16.9% across the eight Local Health Authorities-LHA) and 40.2% received palliative care services (from 36.2% to 43.7%). Drug therapy was inversely associated with receiving palliative care services within the last 30 days (OR 0.92, 95% CI 0.87 to 0.97), surgery within the last 6 months (OR 0.59, 95% CI 0.52 to 0.67), aggressive tumours (OR 0.88, 95% CI 0.84 to 0.93) and increasing age (OR 0.95, 95% CI 0.95 to 0.95). Drug therapy was more likely among those with haematologic tumours (OR 2.15, 95% CI 2.00 to 2.30) and in case of hospital admissions within the last 6 months (OR 1.63, 95% CI 1.55 to 1.72). Palliative care was less likely among those with haematologic compared with other tumours (OR 0.52, 95% CI 0.49 to 0.56), in case of surgery (OR 0.44, 95% CI 0.39 to 0.49) or hospital admissions (OR 0.70, 95% CI 0.67 to 0.72) within the last 6 months, if receiving anticancer drugs during the last 30 days (OR 0.90, 95% CI 0.85 to 0.94) and for each year of increasing age (OR 0.99, 95% CI 0.99 to 0.99). Palliative care was more likely in the presence of aggressive tumours (OR 1.12, 95% CI 1.08 to 1.16).

CONCLUSION

Use of anticancer drugs and palliative care in the last month of life were inversely associated, showing variability across different LHAs. While administrative data have limits, our findings are in line with conclusions of other studies.

Identifying Patients in Need of Goals of Care Conversations: Reliability, Acceptability, and Prognostic Significance of the Preference-Aligned Communication and Treatment Conversation Trigger Tool for Patients with Cancer

Background: Simple methods to help teams identify patients with goals of care (GOC) conversation needs are lacking. Objectives: To develop a tool to identify hospitalized patients who may benefit from GOC conversations. Methods: The Preference-Aligned Communication and Treatment (PACT) Conversation Trigger Tool was implemented as part of a quality improvement initiative in 10 Illinois hospitals and validated in a cohort of patients admitted to the coordinating site's oncology unit (n = 135). Results: The tool was reliable and acceptable to clinicians using it across sites. Thirty percent (n = 40) of patients screened at the coordinating site's oncology unit triggered positive. These patients were more likely to have a do-not-resuscitate order (43% vs. 11%) and palliative care consult (53% vs. 20%) and had lower mean survival time (125 vs. 248 days) than those who did not trigger (p < 0.001). Conclusions: The tool is reliable, acceptable, and can identify hospitalized oncology patients who may benefit from GOC conversations.

Kidney Function Worsening is Linked to Parenteral-Nutrition-Dependent Survival in Palliative Care Patients

Background. Parenteral nutrition (PN) is frequently administered in palliative care patients suffering from cachexia. The evidence regarding the use of PN in terminally ill patients is scarce. Routine laboratory parameters might help to decide whether to start or forgo PN, which could decrease overtreatment at the end of life. Kidney failure was frequently associated with survival. However, a relation between kidney function parameters and parenteral nutrition has not been observed thus far. The aim of this retrospective cohort study was to analyze kidney function parameters in palliative care patients under PN, as well as the relation between these parameters and overall survival. Methods. Patients who were admitted to the Department of Palliative Medicine at the Medical University of Vienna were screened for PN treatment. Whether kidney function parameters at baseline or their dynamics over the course of two weeks were associated with survival was assessed with descriptive and interferential statistics. Results. In total, 113 of 443 palliative care patients were administered parenteral nutrition for the first time. The overall survival (OS) for all patients with increased kidney function parameters at baseline was lower (creatinine: hazard ratio (HR) = 1.808, p < 0.001; urea: HR = 1.033, p < 0.001; uric acid HR = 1.055, p = 0.015). No significant increase in creatinine blood levels was observed in the first 2 weeks after the initiation of PN when compared to the non-PN group (p = 0.86). However, if creatinine blood levels increased within the PN group, lower overall survival was found (HR = 2.046, p = 0.007). Conclusion. Increased kidney function parameters, such as creatinine, urea and uric acid, might be used as negative prognostic markers in palliative care patients under PN. Moreover, an increase in creatinine during the administration of parenteral nutrition in the first 2 weeks is linked to worse outcomes. These findings may help future studies to establish objective markers for clinicians to determine whether to start or end PN in palliative cancer patients and decrease potential overtreatment at the end of life.

A prognostic model to identify short survival expectancy of medical oncology patients at the time of hospital discharge

Background

Hospitalization of cancer patients is associated with poor overall survival, but prognostic misclassification may lead to suboptimal therapeutic decisions and transitions of care. No model is currently available for stratifying the heterogeneous population of oncological patients after a hospital admission to a general Medical Oncology ward. We developed a multivariable prognostic model based on readily available and objective clinical data to estimate survival in oncological patients after hospital discharge.

Methods

A multivariable model and nomogram for overall survival after hospital discharge was developed in a retrospective training cohort and prospectively validated in an independent set of adult patients with solid tumors and a first admission to a unit of medical oncology. Performance of the model was assessed by C-index and Kaplan–Meier survival curves stratified by risk categories.

Results

From a population of 1089 patients with a first hospitalization, 757 patients were included in the training group [median survival, 43 weeks; 95% confidence interval (CI), 37-51 weeks] and 200 patients in the validation cohort (median survival, 44 weeks; 95% CI, 34 weeks-not reached). An accelerated failure time log-normal model was built, including five variables (primary tumor, stage, cause of admission, active treatment, and age). The C-index was 0.71 (95% CI, 0.69-0.73), with a good calibration, and adequate validation in the prospective cohort (C-index: 0.69; 95% CI, 0.65-0.74). Median survival in three predefined model-based risk groups was 10.7 weeks (high), 27.0 weeks (intermediate), and 3 years (low) in the training cohort, with comparable values in the validation cohort.

Conclusions

In oncological patients, individualized predictions of survival after hospitalization were provided by a simple and validated model. Further evaluation of the model might determine whether its use improves shared decision making at discharge.

•

Hospitalization of poor prognosis oncology patients is a frequently missed opportunity for transition to palliative care.

•

We developed and validated a prognostic index for cancer patients at hospital discharge based on five objective variables.

•

Adequate prognostic stratification at discharge may facilitate transitions of care and shared decision making.

Development and internal validation of laboratory prognostic score to predict 14-day mortality in terminally ill patients with gastrointestinal malignancy

BACKGROUND

Few studies have developed an easy scoring system for the short-term survival of patients with gastrointestinal (GI) malignancy.

METHODS

A total of 816 terminally ill patients with GI malignancy were admitted to our palliative care unit. They were randomly divided into the investigation (n = 490) and validation (n = 326) groups. A total of 19 laboratory blood parameters were analyzed. Receiver-operating characteristic analysis was performed for each blood factor, and the area under the curve was calculated to determine the predictive value for 14-day survival after the blood test. Multivariable logistic regression analysis was performed to identify significant independent prognostic factors for 14-day mortality. To develop a scoring system for 14-day mortality, the laboratory prognostic score for gastrointestinal malignancy (GI-LPS) was calculated using the sum of indices of the independent prognostic factors.

RESULTS

Multivariable analysis showed that 5 of 19 indices, namely total bilirubin ≥ 2.1 mg/dL, blood urea nitrogen ≥ 28 mg/dL, eosinophil percentage ≤ 0.5%, neutrophil-to-lymphocyte ratio ≥ 9.2, and platelet count ≤ 194 × 10³/μL, were significant independent factors of 14-day survival. GI-LPS showed acceptable accuracy for 14-day mortality in the investigation and validation groups. GI-LPS 3 (including any three factors) predicted death within 14 days, with a sensitivity of 56-58%, a specificity of 82-87%, a positive predictive value of 48-50%, and a negative predictive value of 87-90%.

CONCLUSIONS

GI-LPS showed an acceptable ability to predict 14-day survival and can provide additional information to conventional prognostic scores.

Knowledge and use of prognostic scales by oncologists and palliative care physicians in adult patients with advanced cancer: A national survey (ONCOPRONO study)

BACKGROUND

Prognostic scales exist to estimate patient survival in advanced cancer. However, there are no studies evaluating their use and practice. The objective of this study was to evaluate in a nationwide study the proportion of oncologists and palliative care physicians who had knowledge of these scales.

METHODS

A descriptive, national, cross-sectional study was conducted via an online questionnaire to oncologists and palliative care physicians across France.

RESULTS

Palliative care physicians had better knowledge of the scales than oncologists (42.3% (n = 74) vs. 27.8% (n = 33), p = 0.015). The Palliative Performance Status (PPS) and Pronopall Scale were the best-known (51.4% (n = 55) and 65.4% (n = 70), respectively) and the most widely used (35% (n = 28) and 60% (n = 48), respectively). Improved training in the use of these scales was requested by 85.4% (n = 251) of participants, while 72.8% (n = 214) reported that they did not use them at all. Limited training and lack of consensus on which scale to use were cited as the main obstacles to use.

CONCLUSION

This is the first national study on the use of prognostic scales in advanced cancer. Our findings highlight a need to improve training in these scales and to reach a consensus on scale selection.

Perimortem changes in clinical parameters in patients undergoing maintenance hemodialysis

Background

End-of-life medical care for patients receiving maintenance hemodialysis (HD) therapy has become an increasingly important issue worldwide. Thus far, no clear indicators and/or biomarkers exist regarding the timing of HD therapy withdrawal.

Methods

To clarify the perimortem circumstances, we examined temporal changes in multiple clinical parameters during the last 10 serial HD sessions of 65 terminal patients with end-stage renal disease who had undergone maintenance HD and died in our hospital.

Results

The results showed that, while most of the laboratory data were unaltered, the physical parameters, such as systolic blood pressure and consciousness levels, gradually and significantly deteriorated toward the last HD session prior to death. The frequency of the use of vasopressors and O2 inhalation tended to increase. The accumulation of such severe conditions was observed at the last HD session. Of interest, the accumulation of severe conditions at the last HD session in patients with malignancies was significantly less than those with cardiovascular diseases or infectious diseases. The accumulation of severe conditions at the last HD session did not differ between patients who withdrew HD versus those who continued HD.

Conclusion

The results of the present study suggest that predicting the timing of maintenance HD therapy withdrawal is likely to be difficult and that the timing of maintenance HD therapy termination may differ among patient groups with distinct comorbid conditions.

Clinician estimates of prognosis: accuracy and impact-a retrospective inpatient hospice study

OBJECTIVE

To evaluate the accuracy and impact of clinicians' estimates of prognosis (CEP) in patients referred for hospice inpatient care.

METHODS

Retrospective review of 12 months' referrals to a London hospice unit. Data extracted included date of referral, admission and death and CEP.

RESULTS

N=383. Mean age 72 years (range 24-101). CEP accuracy: Median survival where CEP was 'days' (n=141) was 7 days (0-164); CEP 'weeks' (n=167) was 14 days (1-538); CEP 'months' (n=75) was 32 days (2-507). Kaplan-Meier survival curves showed significant difference between CEP of 'months' and 'weeks' (p<0.0001); 'months' and 'days' (p<0.0001); but not 'days' and 'weeks' (p=0.1). CEP impact: admission waiting time increased with increasing CEP: CEP 'days' (n=105) median 1 day (0-14); CEP 'weeks' (n=154) median 2 days (0-46); CEP 'months' (n=69) median 3 days (0-46). No significant difference was demonstrated in the number of discharge planning conversations between groups (0.9/patient).

CONCLUSIONS

CEP was accurate in over half of the cases but did not adequately discriminate between those with prognoses of days or weeks. CEP may affect the prioritisation given to patients by hospices. Inaccurate CEP on referral forms may influence other aspects of care; however, further research is needed.

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data

BACKGROUND

Scoring systems are highly interpretable and widely used to evaluate time-to-event outcomes in healthcare research. However, existing time-to-event scores are predominantly created ad-hoc using a few manually selected variables based on clinician's knowledge, suggesting an unmet need for a robust and efficient generic score-generating method.

METHODS

AutoScore was previously developed as an interpretable machine learning score generator, integrating both machine learning and point-based scores in the strong discriminability and accessibility. We have further extended it to the time-to-event outcomes and developed AutoScore-Survival, for generating time-to-event scores with right-censored survival data. Random survival forest provided an efficient solution for selecting variables, and Cox regression was used for score weighting. We implemented our proposed method as an R package. We illustrated our method in a study of 90-day survival prediction for patients in intensive care units and compared its performance with other survival models, the random survival forest, and two traditional clinical scores.

RESULTS

The AutoScore-Survival-derived scoring system was more parsimonious than survival models built using traditional variable selection methods (e.g., penalized likelihood approach and stepwise variable selection), and its performance was comparable to survival models using the same set of variables. Although AutoScore-Survival achieved a comparable integrated area under the curve of 0.782 (95% CI: 0.767-0.794), the integer-valued time-to-event scores generated are favorable in clinical applications because they are easier to compute and interpret.

CONCLUSIONS

Our proposed AutoScore-Survival provides a robust and easy-to-use machine learning-based clinical score generator to studies of time-to-event outcomes. It gives a systematic guideline to facilitate the future development of time-to-event scores for clinical applications.

COVID-19-related mortality in cancer patients in an Irish setting

Background

The COVID-19 pandemic has impacted significantly on healthcare across the globe. It has been reported to have higher incidence and be associated with worse outcomes in patients with cancer.

Aim

To examine the characteristics of patients with cancer who were diagnosed with COVID-19 and to identify factors which may predict a poorer outcome.

Methods

Patients attending oncology services in Beaumont Hospital who were diagnosed with COVID-19 between March and May 2020 were included. Demographics and outcomes were determined by chart review.

Results

Twenty-seven patients were included in the study. The median age was 62; 59% were male. Ten patients (37%) died all of whom had metastatic or incurable locally advanced disease. Patients with lung cancer had a higher rate of COVID-19 and poorer outcomes. Those with a performance status (PS) ≥ 3 were more likely to die than those with PS ≤ 2. Compared to those who recovered, patients who died had a higher number of organs affected by cancer and a higher mean Palliative Prognostic Score.

Conclusion

Patients attending oncology services during the initial phase of the COVID-19 pandemic had an increased rate of SARS-CoV-2 infection and a higher mortality rate than the general population. Those who died had more advanced cancer as demonstrated by poorer performance status, a greater burden of metastatic disease and a higher Palliative Prognostic Score.

Assessment of Changes in Symptoms Is Feasible and Prognostic in the Last Weeks of Life: An International Multicenter Cohort Study

Background: Symptoms are not typically part of established various prognostic factors and scoring systems but are among the most frequently assessed issues in patient care. Objectives: To evaluate that, changes in symptoms can provide additional useful prognostic information. Design: A secondary analysis of an international cohort study in Japan, Korea, and Taiwan. Setting/Subjects: Subjects were adult patients with advanced cancer (n = 2074) who were admitted to 37 palliative care units (PCUs) in 3 countries from January 2017 to September 2018. Measurements: Symptoms (dyspnea, fatigue, dry mouth, and drowsiness) were assessed at admission and one-week later. Dyspnea was assessed by the presence of resting and exertional dyspnea, whereas other symptoms were assessed using the Integrated Palliative care Outcome Scales (IPOS) (range 0-4). For analysis, we grouped patients by symptom change, as either Improved, Stable, or Worsened (by having at least a one increment decrease, no change, or at least a one increment increase, respectively). Results: Worsened groups had the shortest survival (median survival 15-21 days) compared with those with Improved (median survival 23-31 days) and Stable symptoms (median survival 27-29 days) across all four symptoms (dyspnea, fatigue, dry mouth, and drowsiness). Survival differences were statistically significantly different across all three groups for all symptoms (all p < 0.001). Interestingly, Improved symptoms were associated with similar survival compared with Stable groups, with no statistical differences. Conclusions: Worsened symptoms at one week after admission were useful predictors of survival for patients with advanced cancer in PCUs during the final weeks of life. Longitudinal assessments are needed to reflect passage of time as well as impact of treatments.

Comparing the performance of the palliative prognostic (PaP) score with clinical predictions of survival: A systematic review

BACKGROUND

In patients with advanced cancer, prognosis is usually determined using clinicians' predictions of survival (CPS). The palliative prognostic (PaP) score is a prognostic algorithm that was developed to predict survival in patients with advanced cancer. The score categorises patients into three risk groups in accordance with their probability of surviving for 30 days. The relative accuracy of PaP and CPS is unclear.

DESIGN

This was a systematic review of MEDLINE, Embase, AMED, CINAHL Plus and the Cochrane Database of Systematic Reviews and Trials from inception up to June 2021. The inclusion criteria were studies in adults with advanced cancer reporting data on performance of both PaP and CPS. Data were extracted on accuracy of prognoses and where available on discrimination (area under the receiver operating characteristic curve or C-index) and/or diagnostic performance (sensitivity, specificity).

RESULTS

Eleven studies were included. One study reported a direct comparison between PaP risk groups and equivalent risk groups defined by CPS and found that PaP was as accurate as CPS. Five studies reported discrimination of PaP as a continuous total score (rather than using the previously validated risk categories) and reported C-statistics that ranged from 0.64 (95% confidence interval [CI] 0.54, 0.74) up to 0.90 (95% CI 0.87, 0.92). Other studies compared PaP against CPS using non-equivalent metrics (e.g. comparing probability estimates against length of survival estimates).

CONCLUSIONS

PaP risk categories and CPS are equally able to discriminate between patients with different survival probabilities. Total PaP scores show good discrimination between patients in accordance with their length of survival. The role of PaP in clinical practice still needs to be defined.

TRIAL REGISTRATION

PROSPERO (CRD42021241074, 5th March 2021).

Diagnostic models for impending death in terminally ill cancer patients: A multicenter cohort study

Background

Accurately predicting impending death is essential for clinicians to clarify goals of care. We aimed to develop diagnostic models to predict death ≤3 days in cancer patients.

Methods

In this multicenter cohort study, we consecutively enrolled advanced cancer patients admitted to 23 inpatient hospices in 2017. Fifteen clinical signs related to impending death were documented daily from the day when the Palliative Performance Scale (PPS) declined to ≤20–14 days later. We conducted recursive partitioning analysis using the entire data set and performed cross‐validation to develop the model (prediction of 3‐day impending death‐decision tree [P3did‐DT]). Then, we summed the number of systems (nervous/cardiovascular/respiratory/musculoskeletal), where any sign was present to underpin P3did score (range = 0–4).

Results

Data following PPS ≤20 were obtained from 1396 of 1896 inpatients (74%). The mean age was 73 ± 12 years, and 399 (29%) had gastrointestinal tract cancer. The P3did‐DT was based on three variables and had four terminal leaves: urine output (u/o) ≤200 ml/day and decreased response to verbal stimuli, u/o ≤200 ml/day and no decreased response to verbal stimuli, u/o >200 ml/day and Richmond Agitation‐Sedation Scale (RASS) ≤−2, and u/o >200 ml/day and RASS ≥−1. The 3‐day mortality rates were 80.3%, 53.3%, 39.9%, and 20.6%, respectively (accuracy = 68.3%). In addition, 79.6%, 62.9%, 47.2%, 32.8%, and 17.4% of patients with P3did scores of 4, 3, 2, 1, and 0, respectively, died ≤3 days.

Conclusion

We successfully developed diagnostic models for death ≤3 days. These may further help clinicians predict impending death and help patients/families prepare for their final days.

Experience of symptom control, anxiety and associating factors in a palliative care unit evaluated with Support Team Assessment Schedule Japanese version

Various physical and psychosocial difficulties including anxiety affect cancer patients. Patient surroundings also have psychological effects on caregiving. Assessing the current status of palliative care intervention, specifically examining anxiety and its associated factors, is important to improve palliative care unit (PCU) patient quality of life (QOL). This study retrospectively assessed 199 patients admitted to a PCU during August 2018–June 2019. Data for symptom control, anxiety level, disease insight, and communication level obtained using Support Team Assessment Schedule Japanese version (STAS-J) were evaluated on admission and after 2 weeks. Palliative Prognostic Index (PPI) and laboratory data were collected at admission. Patient anxiety was significantly severer and more frequent in groups with severer functional impairment (p = 0.003) and those requiring symptom control (p = 0.006). Nevertheless, no relation was found between dyspnea and anxiety (p = 0.135). Patients with edema more frequently experienced anxiety (p = 0.068). Patient survival was significantly shorter when family anxiety was higher after 2 weeks (p = 0.021). Symptoms, edema, and disabilities in daily living correlate with patient anxiety. Dyspnea is associated with anxiety, but its emergence might be attributable mainly to physical factors in this population. Family members might sensitize changes reflecting worsened general conditions earlier than the patients.

Improving time to palliative care review with predictive modeling in an inpatient adult population: study protocol for a stepped-wedge, pragmatic randomized controlled trial

Background

Palliative care is a medical specialty centered on improving the quality of life (QOL) of patients with complex or life-threatening illnesses. The need for palliative care is increasing and with that the rigorous testing of triage tools that can be used quickly and reliably to identify patients that may benefit from palliative care.

Methods

To that aim, we will conduct a two-armed stepped-wedge cluster randomized trial rolled out to two inpatient hospitals to evaluate whether a machine learning algorithm accurately identifies patients who may benefit from a comprehensive review by a palliative care specialist and decreases time to receiving a palliative care consult in hospital. This is a single-center study which will be conducted from August 2019 to November 2020 at Saint Mary’s Hospital & Methodist Hospital both within Mayo Clinic Rochester in Minnesota. Clusters will be nursing units which will be chosen to be a mix of complex patients from Cardiology, Critical Care, and Oncology and had previously established relationships with palliative medicine. The stepped wedge design will have 12 units allocated to a design matrix of 5 treatment wedges. Each wedge will last 75 days resulting in a study period of 12 months of recruitment unless otherwise specified. Data will be analyzed with Bayesian hierarchical models with credible intervals denoting statistical significance.

Discussion

This intervention offers a pragmatic approach to delivering specialty palliative care to hospital patients in need using machine learning, thereby leading to high value care and improved outcomes. It is not enough for AI to be utilized by simply publishing research showing predictive performance; clinical trials demonstrating better outcomes are critically needed. Furthermore, the deployment of an AI algorithm is a complex process that requires multiple teams with varying skill sets. To evaluate a deployed AI, a pragmatic clinical trial can accommodate the difficulties of clinical practice while retaining scientific rigor.

Trial registration

ClinicalTrials.gov NCT03976297. Registered on 6 June 2019, prior to trial start.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05546-5.

Chemotherapy use in end-of-life digestive cancer patients: a retrospective AGEO observational study

BACKGROUND

The use of chemotherapy (CT) near the end-of-life (EOL) is an important issue in oncology since it could degrade quality of life. CT near EOL is still poorly studied, with no dedicated study in gastrointestinal (GI) cancer patients.

AIM

To analyze in GI cancer patients the factors associated with the use of CT within 3- and 1-month before patients' death.

METHODS AND PARTICIPANTS

All consecutive patients who died from a GI cancer in 10 French tertiary care hospitals during 2014 were included in this retrospective study. Clinical, demographical and biological data were collected and compared between patients receiving or not CT within 3- and 1-month before death. Variables associated with overall survival (OS) was also determined using of univariate and multivariate analyses with a Cox model.

RESULTS

Four hundred and thirty-seven patients with a metastatic GI cancer were included in this study. Among them, 293 pts (67.0%) received CT within 3-months before death, and 121 pts (27.7%) received CT within 1-month before death. Patients receiving CT within 3-months before death were significantly younger (median age: 65.5 vs 72.8 years, p < 0.0001), with a better PS (PS 0 or 1: 53.9 vs 29.3%, p < 0.0001) and a higher albumin level (median: 32.8 vs 31.0 g/L, p = 0.048). Similar results were found for CT within 1 month before death. Palliative care team intervention was less frequent in patients who received CT in their last month of life (39.7% vs 51.3%, p = 0.02). In multivariate analysis, median OS from diagnosis was shorter in the group receiving CT within 1-month before death (HR = 0.59; 95% CI [0.48-0.74]).

CONCLUSION

In GI-cancer patients, CT is administered within 3- and 1-month before death, in two and one third of patients, respectively. Patients receiving CT within 1-month before death, had more aggressive disease with poor OS. Palliative care team intervention was associated with less administration of CT in the last month of life. These results highlight the need to better anticipate the time to stop CT treatment in the end-of-life and the importance of an active collaboration between oncology and palliative care teams.

Prospective observational study of palliative care in hematological malignancies: Report of one year of practice

INTRODUCTION

Palliative care is an approach that improves the quality of life of patients with advanced disease.

OBJECTIVE

The aim of this study is to evaluate the process of palliative care in patients with hematologic malignancies.

METHODS

In this prospective observational study, we included patients with hematologic malignancies who received palliative care over a 12 month period from June 1, 2019, to May 31, 2020 at the day care hospital of the hematology department in University Hospital of Sfax, Tunisia. Blood transfusion was used to relieve symptoms of anemia and bleeding.

RESULTS

Fifty-five patients were included. The median age was 68 years. Forty-three percent of patients were diagnosed with acute leukemia and 41.8% with myelodysplastic syndrome. Red cell and platelet transfusions were indicated in 94.5% and 36.3% of cases respectively. Patients reported improvement after blood transfusion in 50% of cases. Twenty-five transfusion reactions (45%) were noted. Fever was noted in 33 patients (60%), with documented sites of infection in 84.8% of them. Pulmonary infection was frequently noted (50%). Antimicrobial treatment was prescribed in all febrile cases. Pain was reported in 22 patients and in 77.5% of these cases, it was nociceptive. Patients who received analgesics showed clinical improvement in pain in 81% of cases. Anorexia with malnutrition was reported in 23% of cases which was treated with enteral nutrition in 75% of cases. Sleep disturbance (20 patients), anxiety (7 patients), and depression (4 patients) were mentioned respectively.

CONCLUSION

Palliative care in hematology should be a multidisciplinary care approach with a global management of the various physical, psychological and sociological complications.

Clinical indicators useful in decision-making about palliative chemotherapy for end-of-life ovarian cancer patients

PURPOSE

Chemotherapy for end-of-life ovarian cancer patients is a complex and delicate problem. We evaluated whether active palliative chemotherapy is beneficial for such patients using inflammatory parameters, nutritional indicators, and the PPI (Palliative Prognostic Index), which predicts short-term prognosis.

METHODS

Thirty-six patients among 49 patients who died from ovarian cancer from 2014 to 2019 at our hospital were enrolled, whom clinical and laboratory data just before starting their final chemotherapy regimen could be obtained. Associations between the time from last chemotherapy to death and the following parameters were investigated: age, performance status, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio, Modified Glasgow Prognostic Score (mGPS), Prognostic Nutritional Index (PNI) score, and PPI score.

RESULTS

The median age was 57 (range 19-80) years. The median time from last chemotherapy to death was 45.5 (range 11-110) days. Eight patients (22%) died within 30 days of their last chemotherapy regimen. In univariate analysis, median survival time was significantly shorter in patients with higher NLR, mGPS 2, and higher PPI values; NLR (≥ median vs. < median): 32 (range 11-80) days vs. 54 (range 35-110) days, p = 0.008; mGPS (2 vs. 0-1): 42 (range 11-80) days vs. 96 (range 49-110) days, p = 0.012; and PPI score (≥ median vs. < median): 38 (range 11-74) days vs. 60 (range 18-110) days, p = 0.005. However, in multivariate analysis, no factors were identified as independent prognostic factors for survival.

CONCLUSION

Parameters, such as NLR, mGPS, and PPI score, may be indicators for discontinuation of palliative chemotherapy, and may be useful for maximizing end-of-life care for ovarian cancer patients.

Expanding Application of the Long-Term Quality of Life Instrument to the Population of Women Undergoing Treatment of Advanced Breast Cancer

BACKGROUND

The Long-Term Quality of Life (LTQL) instrument was designed for female cancer survivors who have completed treatment and includes an existential spirituality subscale that is omitted in many other quality of life scales. Women with advanced breast cancer are now living longer, while also expressing greater spiritual concerns.

OBJECTIVE

The objective of this analysis was to test the psychometric properties of the LTQL among women undergoing treatment of advanced breast cancer.

METHODS

This secondary analysis was based on a sample of 385 women. Validity was evaluated using a confirmatory factor analysis and associations with Functional Assessment of Cancer Therapy-Breast Cancer. Internal consistency reliability was assessed using Cronbach's α for each subscale of the LTQL.

RESULTS

The mean age was 56 years, 84% of participants were white, and 69% had metastasis. Model fit indices for the confirmatory factor analysis were acceptable, with the root mean square error of approximation of 0.076 (90% confidence interval, 0.071-0.081) and a comparative fit index of 0.91. The LTQL subscale scores were significantly correlated with the subscales of the Functional Assessment of Cancer Therapy-Breast Cancer of similar conceptual content. Internal consistency reliability for the subscales ranged from 0.80 to 0.86.

CONCLUSIONS

The factor structure of the LTQL was consistent with previous findings in long-term female cancer survivors. The instrument has adequate psychometric properties for use among women with advanced breast cancer.

IMPLICATIONS FOR PRACTICE

The LTQL can be used to assess the physical, psychosocial, and existential spiritual domains of quality of life among women with advanced breast cancer as well as in long-term female cancer survivors.

Prognosis palliative care study, palliative prognostic index, palliative prognostic score and objective prognostic score in advanced cancer: a prospective comparison

BACKGROUND

Predicting how long a patient with far advanced cancer has to live is a significant part of hospice and palliative care. Various prognostic models have been developed, but have not been fully compared in South Korea.

OBJECTIVES

We aimed to compare the accuracy of the Prognosis in Palliative Care Study (PiPS), Palliative Prognostic Index (PPI), Palliative Prognostic Score (PaP) and Objective Prognostic Score (OPS) for patients with far advanced cancer in a palliative care unit in South Korea.

METHODS

This prospective study included patients with far advanced cancer who were admitted to a single palliative care unit at the National University Hospital. Variables for calculating the prognostic models were recorded by a palliative care physician. The survival rate was estimated using the Kaplan-Meier method. The sensitivity, specificity, positive predictive value and negative predictive value of each model were calculated.

RESULTS

A total of 160 patients participated. There was a significant difference in survival rates across all groups, each categorised through the five prognostic models. The overall accuracy (OA) of the prognostic models ranged between 54.5% and 77.6%. The OA of clinicians' predictions of survival ranged between 61.9% and 81.3%.

CONCLUSION

The PiPS, PPI, PaP and OPS were successfully validated in a palliative care unit of South Korea. There was no difference in accuracy between the prognostic models, and OA tended to be lower than in previous studies.

Personality matters: relationship between personality characteristics, spirituality, demoralization, and perceived quality of life in a sample of end-of-life cancer patients

PURPOSE

Personality could be an interesting dimension to explore in end-of-life cancer patients, in order to investigate how personality affects quality of life. Thus, this study aimed to investigate the relationship among personality through the Big Five Inventory (BFI), spirituality, and demoralization and to explore their impact on their quality of life.

METHODS

A sample of 210 end-of-life Italian cancer patients were assessed with the BFI, the Demoralization Scale (DS), the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being (FACIT-SP-12), the Functional Assessment of Cancer Therapy Scale-General Measure (FACT-G), and the Karnofsky performance status.

RESULTS

Correlational analysis highlighted a significantly negative relationship between extraversion and agreeableness traits and all the demoralization dimensions. On the other side, neuroticism trait was significantly and positively correlated with the Demoralization Scale (p < 0.01). To understand the impact of these variables on quality of life (FACT-G), we performed a hierarchical multiple regression: in the final model, demoralization remained the strongest contributing factor (β =  - 0.509, p < 0.001), followed by neuroticism (β =  - 0.175, p < 0.001), spirituality (β = 0.163, p = 0.015), and Karnofsky index (β = 0.115, p = 0.012).

CONCLUSION

Our data underlined how both the neuroticism trait and demoralization are correlated with a worst health status in terminal cancer patients, whereas spirituality is a protective factor. The study of personality may allow to better understand the inner patient's experience and improve communication between patient and healthcare staff in order to build and apply better-tailored psychological treatment.

Accuracy of the Palliative Prognostic Score With or Without Clinicians' Prediction of Survival in Patients With Far Advanced Cancer

CONTEXT

Previous studies suggest that clinicians' prediction of survival (CPS) may have reduced the accuracy of objective indicators for prognostication in palliative care.

OBJECTIVES

We aimed to examine the accuracy of CPS alone, compared to the original Palliative Prognostic Score (PaP), and five clinical/laboratory variables of the PaP in patients with far advanced cancer.

METHODS

We compared the discriminative accuracy of three prediction models (the PaP-CPS [the score of the categorical CPS of PaP], PaP without CPS [sum of the scores of only the objective variables of PaP], and PaP total score) across 3 settings: inpatient palliative care consultation team, palliative care unit, and home palliative care. We computed the area under receiver operating characteristic curve (AUROC) for 30-day survival and concordance index (C-index) to compare the discriminative accuracy of these three models.

RESULTS

We included a total of 1534 subjects with median survival of 34.0 days. The AUROC and C-index in the three settings were 0.816-0.896 and 0.732-0.799 for the PaP total score, 0.808-0.884 and 0.713-0.782 for the PaP-CPS, and 0.726-0.815 and 0.672-0.728 for the PaP without CPS, respectively. The PaP total score and PaP-CPS showed similar AUROCs and C-indices across the three settings. The PaP total score had significantly higher AUROCs and C-indices than the PaP without CPS across the three settings.

CONCLUSION

Overall, the PaP total score, PaP-CPS, and PaP without CPS showed good discriminative performances. However, the PaP total score and PaP-CPS were significantly more accurate than the PaP without CPS.