Can We Make More Accurate Prognoses During Last Days of Life?

Background: Life expectancy prediction is important for end-of-life planning. Established methods (Palliative Performance Scale [PPS], Palliative Prognostic Index [PPI]) have been validated for intermediate- to long-term prognoses, but last-weeks-of-life prognosis has not been well studied. Patients admitted to a palliative care facility often have a life expectancy of less than three weeks. Reliable last-weeks-of-life prognostic tools are needed. Objective: To improve short-term survival prediction in terminally ill patients. Method: This prospective study included all patients admitted to a palliative care facility in Montreal, Canada, over one year. PPS and PPI were assessed until patients' death. Seven prognostic clinical signs of impending death (Short-Term Prognosis Signs [SPS]) were documented daily. Results: The analyses included 273 patients (76% cancer). The median survival time for a PPS ≤20% was 2.5 days, while for a PPS ≥50% it was 44.5 days, for a PPI >8 the median survival was 3.5 days and for a PPI ≤4 it was 38.5 days. Receiver operating characteristic curves showed a high accuracy in predicting survival. Median survival after the first occurrence of any SPS was below one week. Conclusions: This study demonstrated that the PPS and PPI perform well between one week and three months extending their usefulness to shorter term survival prediction. SPS items provided survival information during the last week of life. Using SPS along with PPS and PPI during the last weeks of life could enable a more precise short-term survival prediction across various end-of-life diagnoses. The translation of this research into clinical practice could lead to a better adapted treatment, the identification of a most appropriate care setting for patients, and improved communication of prognosis with patients and families.

Prognoses Associated With Palliative Performance Scale Scores in Modern Palliative Care Practice

Importance

The Palliative Performance Scale (PPS) is one of the most widely used prognostic tools for patients with serious illness. However, current prognostic estimates associated with PPS scores are based on data that are over a decade old.

Objective

To generate updated prognostic estimates by PPS score, care setting, and illness category, and examine how well PPS predicts short- and longer-term survival.

Design, Setting, and Participants

This prognostic study was conducted at a large academic medical center with robust inpatient and outpatient palliative care practices using electronic health record data linked with data from California Vital Records. Eligible participants included patients who received a palliative care consultation between January 1, 2018, and December 31, 2020. Data analysis was conducted from November 2022 to February 2024.

Exposure

Palliative care consultation with a PPS score documented.

Main Outcomes and Measures

The primary outcomes were predicted 1-, 6-, and 12-month mortality and median survival of patients by PPS score in the inpatient and outpatient settings, and performance of the PPS across a range of survival times. In subgroup analyses, mortality risk by PPS score was estimated in patients with cancer vs noncancer illnesses and those seen in-person vs by video telemedicine in the outpatient setting.

Results

Overall, 4779 patients (mean [SD] age, 63.5 [14.8] years; 2437 female [51.0%] and 2342 male [49.0%]) had a palliative care consultation with a PPS score documented. Of these patients, 2276 were seen in the inpatient setting and 3080 were seen in the outpatient setting. In both the inpatient and outpatient settings, 1-, 6-, and 12-month mortality were higher and median survival was shorter for patients with lower PPS scores. Prognostic estimates associated with PPS scores were substantially longer (2.3- to 11.7-fold) than previous estimates commonly used by clinicians. The PPS had good ability to discriminate between patients who lived and those who died in the inpatient setting (integrated time-dependent area under the curve [iAUC], 0.74) but its discriminative ability was lower in the outpatient setting (iAUC, 0.67). The PPS better predicted 1-month survival than longer-term survival. Mortality rates were higher for patients with cancer than other serious illnesses at most PPS levels.

Conclusions and Relevance

In this prognostic study, prognostic estimates associated with PPS scores were substantially longer than previous estimates commonly used by clinicians. Based on these findings, an online calculator was updated to assist clinicians in reaching prognostic estimates that are more consistent with modern palliative care practice and specific to the patient's setting and diagnosis group.

Palliative prognostic scores for survival prediction of cancer patients: a systematic review and meta-analysis

BACKGROUND

The palliative prognostic score is the most widely validated prognostic tool for cancer survival prediction, with modified versions available. A systematic evaluation of palliative prognostic score tools is lacking. This systematic review and meta-analysis aimed to evaluate the performance and prognostic utility of palliative prognostic score, delirium-palliative prognostic score, and palliative prognostic score without clinician prediction in predicting 30-day survival of cancer patients and to compare their performance.

METHODS

Six databases were searched for peer-reviewed studies and grey literature published from inception to June 2, 2023. English studies must assess palliative prognostic score, delirium-palliative prognostic score, or palliative prognostic score without clinician-predicted survival for 30-day survival in adults aged 18 years and older with any stage or type of cancer. Outcomes were pooled using the random effects model or summarized narratively when meta-analysis was not possible.

RESULTS

A total of 39 studies (n = 10 617 patients) were included. Palliative prognostic score is an accurate prognostic tool (pooled area under the curve [AUC] = 0.82, 95% confidence interval [CI] = 0.79 to 0.84) and outperforms palliative prognostic score without clinician-predicted survival (pooled AUC = 0.74, 95% CI = 0.71 to 0.78), suggesting that the original palliative prognostic score should be preferred. The meta-analysis found palliative prognostic score and delirium-palliative prognostic score performance to be comparable. Most studies reported survival probabilities corresponding to the palliative prognostic score risk groups, and higher risk groups were statistically significantly associated with shorter survival.

CONCLUSIONS

Palliative prognostic score is a validated prognostic tool for cancer patients that can enhance clinicians' confidence and accuracy in predicting survival. Future studies should investigate if accuracy differs depending on clinician characteristics. Reporting of validation studies must be improved, as most studies were at high risk of bias, primarily because calibration was not assessed.

Performance of the Palliative Prognostic Index for cancer patients: A systematic review and meta-analysis

BACKGROUND

Clinician predicted survival for cancer patients is often inaccurate, and prognostic tools may be helpful, such as the Palliative Prognostic Index (PPI). The PPI development study reported that when PPI score is greater than 6, it predicted survival of less than 3 weeks with a sensitivity of 83% and specificity of 85%. When PPI score is greater than 4, it predicts survival of less than 6 weeks with a sensitivity of 79% and specificity of 77%. However, subsequent PPI validation studies have evaluated various thresholds and survival durations, and it is unclear which is most appropriate for use in clinical practice. With the development of numerous prognostic tools, it is also unclear which is most accurate and feasible for use in multiple care settings.

AIM

We evaluated PPI model performance in predicting survival of adult cancer patients based on different thresholds and survival durations and compared it to other prognostic tools.

DESIGN

This systematic review and meta-analysis was registered in PROSPERO (CRD42022302679). We calculated the pooled sensitivity and specificity of each threshold using bivariate random-effects meta-analysis and pooled diagnostic odds ratio of each survival duration using hierarchical summary receiver operating characteristic model. Meta-regression and subgroup analysis were used to compare PPI performance with clinician predicted survival and other prognostic tools. Findings which could not be included in meta-analyses were summarised narratively.

DATA SOURCES

PubMed, ScienceDirect, Web of Science, CINAHL, ProQuest and Google Scholar were searched for articles published from inception till 7 January 2022. Both retrospective and prospective observational studies evaluating PPI performance in predicting survival of adult cancer patients in any setting were included. The Prediction Model Risk of Bias Assessment Tool was used for quality appraisal.

RESULTS

Thirty-nine studies evaluating PPI performance in predicting survival of adult cancer patients were included (n = 19,714 patients). Across meta-analyses of 12 PPI score thresholds and survival durations, we found that PPI was most accurate for predicting survival of <3 weeks and <6 weeks. Survival prediction of <3 weeks was most accurate when PPI score>6 (pooled sensitivity = 0.68, 95% CI 0.60-0.75, specificity = 0.80, 95% CI 0.75-0.85). Survival prediction of <6 weeks was most accurate when PPI score>4 (pooled sensitivity = 0.72, 95% CI 0.65-0.78, specificity = 0.74, 95% CI 0.66-0.80). Comparative meta-analyses found that PPI performed similarly to Delirium-Palliative Prognostic Score and Palliative Prognostic Score in predicting <3-week survival, but less accurately in <30-day survival prediction. However, Delirium-Palliative Prognostic Score and Palliative Prognostic Score only provide <30-day survival probabilities, and it is uncertain how this would be helpful for patients and clinicians. PPI also performed similarly to clinician predicted survival in predicting <30-day survival. However, these findings should be interpreted with caution as limited studies were available for comparative meta-analyses. Risk of bias was high for all studies, mainly due to poor reporting of statistical analyses. while there were low applicability concerns for most (38/39) studies.

CONCLUSIONS

PPI score>6 should be used for <3-week survival prediction, and PPI score>4 for <6-week survival. PPI is easily scored and does not require invasive tests, and thus would be easily implemented in multiple care settings. Given the acceptable accuracy of PPI in predicting <3- and <6-week survival and its objective nature, it could be used to cross-check clinician predicted survival especially when clinicians have doubts about their own judgement, or when clinician estimates seem to be less reliable. Future studies should adhere to the reporting guidelines and provide comprehensive analyses of PPI model performance.

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.

Comparison of survival times of advanced cancer patients with palliative care at home and in hospital

OBJECTIVES

One primary concern about receiving care at home is that survival might be shortened because the quality and quantity of treatment provided at home will be inferior to that given in the hospital. Although our previous study demonstrated a longer survival of those with home-based palliative care (PC), it lacked adjustment for some potential confounders including symptoms and treatments during the stay. We aimed to compare the survival times among advanced cancer patients receiving home-based and hospital-based PC with adjusting for symptoms and treatments.

METHOD

We compared survival time of participants who enrolled two multicenter, prospective cohort studies of advanced cancer patients at 45-home-based PC services between July 2017 and December 2017, and at 23-hospital-based PC services between January 2017 and December 2017. We analyzed with stratification by the estimated survival of Days, Weeks, and Months, which were defined by modified Prognosis in Palliative care Study predictor models-A. We conducted a Cox regression analysis with adjusting for potential confounders including symptoms and treatments during the stay.

RESULTS

A total of 2,998 patients were enrolled in both studies and 2,878 patients were analyzed; 988 patients receiving home-based PC and 1,890 receiving hospital-based PC. The survival time of patients receiving home-based PC was significantly longer than that of patients receiving hospital-based PC for the Days Prognosis (estimated median survival time: 10 days [95% CI 8.1-11.8] vs. 9 days [95% CI 8.3-10.4], p = 0.157), the Weeks prognosis (32 days [95% CI 28.9-35.4] vs. 22 days [95% CI 20.3-22.9], p < 0.001), and the Months Prognosis, (65 days [95% CI 58.2-73.2] vs. 32 days [95% CI 28.9-35.4], p < 0.001).

CONCLUSION

In this cohort of advanced cancer patients with a Weeks or Months prognosis, those receiving home-based PC survived longer than those receiving hospital-based PC after adjusting for symptoms and treatments.

Changes in the palliative performance scale may be as important as the initial palliative performance scale for predicting survival in terminal cancer patients

OBJECTIVE

The accurate estimation of expected survival in terminal cancer patients is important. The palliative performance scale (PPS) is an important factor in predicting survival of hospice patients. The purpose of this study was to examine how initial status of PPS and changes in PPS affect the survival of hospice patients in Korea.

METHOD

We retrospectively examined 315 patients who were admitted to our hospice unit between January 2017 and December 2018. The patients were divided based on the PPS of ≥50% (group A) and ≤40% (group B). We performed survival analysis for factors associated with the length of survival (LOS) in group A. Based on the hospice team's weekly evaluation of PPS, we examined the effect of initial levels and changes in group A on the prognosis of patients who survived for 2 weeks or more.

RESULTS

At the time of admission to hospice, 265 (84.1%) patients were PPS ≥50%, and 50 (15.9%) were PPS ≤40%. The median LOS of PPS ≥50% and PPS ≤40% were 15 (2-158 days) and 9 (2-43 days), respectively. Male, gastrointestinal cancer, and lower initial PPS all predicted poor prognosis in group A. Male, gastrointestinal cancer, and a PPS change of 10% or greater, compared with initial status 1 week and 2 weeks of hospitalization, were all predictors of poor prognosis in group A patients who survived for 2 weeks or longer.

SIGNIFICANCE OF RESULTS

Our research demonstrates the significance of PPS change at 1 week and 2 weeks, suggesting the importance of evaluating not only initial PPS but also change in PPS.

The application of the palliative prognostic index in predicting the life expectancy of patients in palliative care: a systematic review and meta-analysis

BACKGROUND

The palliative prognostic index (PPI) is a commonly used tool to predict the life expectancy in palliative care patients. However, there is no universal cutoff, and the accuracy of different cutoffs varies. Therefore, we conducted this meta-analysis to explore the validity and accuracy of different PPI scores for different survival time in palliative care setting.

METHODS

PubMed, Embase, Cochrane, Scopus and Chinese CNKI databases were searched to identify studies using the PPI as a prognostic tool to predict survival time in palliative care. We calculated pooled hazard ratios (HRs) with corresponding 95% confidence intervals (CIs), and subgroup analyses were also conducted by different cutoffs. After extracting data, we estimated the pooled sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

We identified 15 studies with 7455 assessments. Seven of these studies were synthesized for a combined HR. The pooled HR was 1.94 (95% CI 1.54-2.44) when cutoffs were 2 and 4, and 2.34 (95% CI 1.50-3.66) when cutoffs were 4 and 6. Of all the studies, 13 studies reported their accuracy, of which four studies were assessed by meta-analysis. The sensitivity of the PPI for 3-week survival ranged from 51 to 92% and specificity ranged from 60.0 to 94.0%, respectively. The sensitivity and specificity of the PPI for 6-week survival were from 46.0 to 89.1% and from 51.7 to 84.4%, respectively. The pooled sensitivity and specificity of the PPI for 3-week survival were 68% (6 as cutoff) and 76% (6 as cutoff), respectively. As for 6-week survival prediction, the pooled sensitivity and specificity were 68% (4 as cutoff) and 82% (4 as cutoff), respectively.

CONCLUSION

The PPI is a useful prognosticator of life expectancy of patients in palliative care, especially for patients with short survival time. However, there were no universal cutoff, and the predicted life span varies. Our data eliminated that using 4 and 6 as cutoffs can better predict the patients' survival time for 3 or 6 weeks. Due to small number of studies and poor qualities of them, result may alter as more studies with better quality are enrolled in the future.

Using the Palliative Performance Scale to Estimate Survival for Patients at the End of Life: A Systematic Review of the Literature

BACKGROUND

The Palliative Performance Scale (PPS) has been widely used for survival prediction among patients with cancer; however, few studies have reviewed PPS scores in heterogeneous palliative care populations across multiple care settings.

OBJECTIVE

The aim of this systematic review was to determine how the PPS tool has been used to estimate survival at the end of life.

METHODS

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed, Embase, and the Cochrane Library were searched for the existing literature published from 2008 to 2017. We synthesized study characteristics, the PPS scores at baseline, and primary outcomes, and explored differences in survival estimates by diagnosis. The quality of the studies was assessed using the Good ReseArch for Comparative Effectiveness (GRACE) checklist.

RESULTS

Seventeen studies were included in this review (nine with cancer and eight with mixed diagnoses). All included studies reported that the PPS exhibited a significant association with survival. Survival estimates ranged from 1 to 3 days for patients with PPS scores of 10% compared with 5 to 36 days for those with scores of 30%. The categorical cut-points for the PPS scores were not consistently reported across studies.

CONCLUSION

This review provides a broad overview on the prognostic value of the PPS tool for survival among multiple patient populations across care settings. Consistent reporting of PPS scores would facilitate the comparison of survival estimates across end-of-life diagnoses.

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.

The association between different opioid doses and the survival of advanced cancer patients receiving palliative care

Background

Concerns that opioids may hasten death can be a cause of the physicians’ reluctance to prescribe opioids, leading to inadequate symptom palliation. Our aim was to find if there was an association between different opioid doses and the survival of the cancer patients that participated in our palliative care program.

Methods

A retrospective study was conducted at Ramathibodi Hospital, Bangkok between January 2013 and December 2015. All of the cancer patients that were referred to palliative care teams by their primary physicians were included in the study. The study data included the patients’ demographics, disease status, comorbidities, functional status, type of services, cancer treatments, date of consultation, and the date of the patient’s death or last follow-up. The information concerning opioid use was collected by reviewing the medical records and this was converted to an oral morphine equivalent (OME), following a standard ratio. The time-varying covariate in the Cox regression analysis was applied in order to determine the association between different doses of opioids and patient survival.

Results

A total of 317 cancer patients were included in the study. The median (IQR) of the OME among our patients was 6.43 mg/day (0.53, 27.36). The univariate Cox regression analysis did not show any association between different opioid doses (OME ≤ 30 mg/day and > 30 mg/day) and the patients’ survival (p = 0.52). The PPS levels (p < 0.01), palliative care clinic visits (HR 0.32, 95%CI 0.24–0.43), home visits (HR 0.75, 95%CI 0.57–0.99), chemotherapy (HR 0.32, 95%CI 0.22–0.46), and radiotherapy (HR 0.53, 95%CI 0.36–0.78) were identified as factors that increased the probability of survival.

Conclusions

Our study has demonstrated that different opioid doses in advanced cancer patients are not associated with shortened survival period.

A Prognostic Indicator for Patients Hospitalized with Heart Failure

BACKGROUND

Current methods for identifying patients at risk of dying within six months suffer from clinician biases resulting in underestimation of this risk. As a result, patients who are potentially eligible for hospice and palliative care services frequently do not benefit from these services until they are very close to the end of their lives.

OBJECTIVE

To develop a prospective prognostic indicator based on actual survival within Centers for Medicare and Medicaid Services (CMS) claims data that identifies patients with congestive heart failure (CHF) who are at risk of six-month mortality.

METHODS

CMS claims data from January 1, 2008 to June 30, 2009 were reviewed to find the first hospitalization for CHF patients with episode of care diagnosis-related groups (DRGs) 291, 292, and 293. Univariate and multivariable analyses were used to determine the associations between demographic and clinical factors and six-month mortality. The resulting model was evaluated for discrimination and calibration.

RESULTS

The resulting prospective prognostic model demonstrated fair discrimination with an ROC of 0.71 and good calibration with a Hosmer-Lemshow statistic of 0.98. Across all DRGs, 5% of discharged patients had a six-month mortality risk of greater than 50%.

CONCLUSION

This prospective approach appears to provide a method to identify patients with CHF who would potentially benefit from a clinical evaluation for referral to hospice care or for a palliative care consult due to high predicted risk of dying within 180 days after discharge from a hospital. This approach can provide a model to match at-risk patients with evidenced-based care in a more consistent manner. This method of identifying patients at risk needs further prospective evaluation to see if it has value for clinicians, increases referrals to hospice and palliative care services, and benefits patients and families.