Independent validation of the modified prognosis palliative care study predictor models in three palliative care settings

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.

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.

Comparison of Symptom Severity and Progression in Advanced Cancer Patients Among Different Care Settings: A Secondary Analysis

Background

Most people in Japan wish to spend their final days at home, but the majority fail to do so; earlier studies indicated a more pronounced worsening of symptoms if treated at home.

Objectives

This study compared the prevalence of symptom worsening and explored associated factors between patients with advanced cancer receiving palliative care in palliative care units (PCUs) and at home.

Design

We conducted a secondary analysis of two multicenter, prospective cohort studies involving patients with advanced cancer receiving palliative care in PCUs or at home.

Setting/Subjects

One study was conducted at 23 PCUs (January to December 2017) and the other on 45 palliative home care services (July to December 2017) in Japan.

Measurements

Symptom changes were categorized as stable, improved, or worse.

Results

Of the 2998 registered patients, 2877 were analyzed. Among them, 1890 patients received palliative care in PCUs, and 987 at home. Patients receiving palliative care at home were more likely to have worsening of pain (17.1% vs. 3.8%; p < 0.001) and drowsiness (32.6% vs. 22.2%; p < 0.001) than those in PCUs. By multivariate logistic regression analysis, palliative care at home was significantly associated with worsening of the Palliative Prognostic Index dyspnea subscale in the unadjusted model (odds ratio, 1.42 [95% confidence interval, 1.08-1.88]; p = 0.014) but not for any symptoms in the adjusted model.

Conclusions

After adjusting for patient background, the prevalence of symptom worsening was not different between patients with advanced cancer receiving palliative care at home and in PCUs.

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.

Life-Sustaining Treatment Decision in Palliative Care Based on Electronic Health Records Analysis

AIMS AND OBJECTIVES

This study sought to explore the present status of life-sustaining treatment decisions in a tertiary hospital to improve the life-sustaining treatment decision-making process.

BACKGROUND

Life-sustaining treatment decisions are crucial for palliative care because they encompass decisions to withdraw treatments when patients cannot articulate their values and preferences. However, surrogate decisions have settled many life-sustaining treatment cases in South Korea, and this trend is prevalent.

DESIGN

We conducted a retrospective, descriptive study employing a review of electronic health records.

METHODS

We extracted and analysed electronic health records of a tertiary hospital. Our inclusion criteria included adult patients who completed life-sustaining treatment forms in 2019. A total of 2,721 patients were included in the analysis. We analysed the decision-maker, the timing of the decision, and patients' health status a week before the decision. We followed the STROBE checklist.

RESULTS

Among 1,429 deceased patients, those whose families had made life-sustaining treatment decisions totalled 1,028 (70.6%). The median interval between life-sustaining treatment documentation completion to death was three days, more specifically, two days in the family decision group and 5.5 days in the patient decision group. As the decision day neared, there were marked changes in patients' vital signs and laboratory test results, and the need for nursing care increased.

CONCLUSIONS

Life-sustaining treatment decisions were made when death was imminent, suggesting that the time required to discuss end-of-life care was generally insufficient among patients, family, and healthcare professionals in Korea.

RELEVANCE TO CLINICAL PRACTICE

Monitoring changes in laboratory test results and symptoms could help screen the patients who need the life-sustaining treatment discussion. As improving the quality of death is imperative in palliative care, institutional efforts, such as clinical ethics support services, are necessary to improve the life-sustaining treatment decision-making process for patients, families, and healthcare providers.

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.

Prognostic models of survival in patients with advanced incurable cancer: the PiPS2 observational study

BACKGROUND

The Prognosis in Palliative care Study (PiPS) prognostic survival models predict survival in patients with incurable cancer. PiPS-A (Prognosis in Palliative care Study - All), which involved clinical observations only, and PiPS-B (Prognosis in Palliative care Study - Blood), which additionally required blood test results, consist of 14- and 56-day models that combine to create survival risk categories: 'days', 'weeks' and 'months+'.

OBJECTIVES

The primary objectives were to compare PIPS-B risk categories against agreed multiprofessional estimates of survival and to validate PiPS-A and PiPS-B. The secondary objectives were to validate other prognostic models, to assess the acceptability of the models to patients, carers and health-care professionals and to identify barriers to and facilitators of clinical use.

DESIGN

This was a national, multicentre, prospective, observational, cohort study with a nested qualitative substudy using interviews with patients, carers and health-care professionals.

SETTING

Community, hospital and hospice palliative care services across England and Wales.

PARTICIPANTS

For the validation study, the participants were adults with incurable cancer, with or without capacity to consent, who had been recently referred to palliative care services and had sufficient English language. For the qualitative substudy, a subset of participants in the validation study took part, along with informal carers, patients who declined to participate in the main study and health-care professionals.

MAIN OUTCOME MEASURES

For the validation study, the primary outcomes were survival, clinical prediction of survival and PiPS-B risk category predictions. The secondary outcomes were predictions of PiPS-A and other prognostic models. For the qualitative substudy, the main outcomes were participants' views about prognostication and the use of prognostic models.

RESULTS

For the validation study, 1833 participants were recruited. PiPS-B risk categories were as accurate as agreed multiprofessional estimates of survival (61%; p = 0.851). Discrimination of the PiPS-B 14-day model (c-statistic 0.837, 95% confidence interval 0.810 to 0.863) and the PiPS-B 56-day model (c-statistic 0.810, 95% confidence interval 0.788 to 0.832) was excellent. The PiPS-B 14-day model showed some overfitting (calibration in the large -0.202, 95% confidence interval -0.364 to -0.039; calibration slope 0.840, 95% confidence interval 0.730 to 0.950). The PiPS-B 56-day model was well-calibrated (calibration in the large 0.152, 95% confidence interval 0.030 to 0.273; calibration slope 0.914, 95% confidence interval 0.808 to 1.02). PiPS-A risk categories were less accurate than agreed multiprofessional estimates of survival (p < 0.001). The PiPS-A 14-day model (c-statistic 0.825, 95% confidence interval 0.803 to 0.848; calibration in the large -0.037, 95% confidence interval -0.168 to 0.095; calibration slope 0.981, 95% confidence interval 0.872 to 1.09) and the PiPS-A 56-day model (c-statistic 0.776, 95% confidence interval 0.755 to 0.797; calibration in the large 0.109, 95% confidence interval 0.002 to 0.215; calibration slope 0.946, 95% confidence interval 0.842 to 1.05) had excellent or reasonably good discrimination and calibration. Other prognostic models were also validated. Where comparisons were possible, the other prognostic models performed less well than PiPS-B. For the qualitative substudy, 32 health-care professionals, 29 patients and 20 carers were interviewed. The majority of patients and carers expressed a desire for prognostic information and said that PiPS could be helpful. Health-care professionals said that PiPS was user friendly and may be helpful for decision-making and care-planning. The need for a blood test for PiPS-B was considered a limitation.

LIMITATIONS

The results may not be generalisable to other populations.

CONCLUSIONS

PiPS-B risk categories are as accurate as agreed multiprofessional estimates of survival. PiPS-A categories are less accurate. Patients, carers and health-care professionals regard PiPS as potentially helpful in clinical practice.

FUTURE WORK

A study to evaluate the impact of introducing PiPS into routine clinical practice is needed.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN13688211.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 28. See the NIHR Journals Library website for further project information.

The Prognosis in Palliative care Study II (PiPS2): A prospective observational validation study of a prognostic tool with an embedded qualitative evaluation

Background

Prognosis in Palliative care Study (PiPS) models predict survival probabilities in advanced cancer. PiPS-A (clinical observations only) and PiPS-B (additionally requiring blood results) consist of 14- and 56-day models (PiPS-A14; PiPS-A56; PiPS-B14; PiPS-B56) to create survival risk categories: days, weeks, months. The primary aim was to compare PIPS-B risk categories against agreed multi-professional estimates of survival (AMPES) and to validate PiPS-A and PiPS-B. Secondary aims were to assess acceptability of PiPS to patients, caregivers and health professionals (HPs).

Methods and findings

A national, multi-centre, prospective, observational, cohort study with nested qualitative sub-study using interviews with patients, caregivers and HPs. Validation study participants were adults with incurable cancer; with or without capacity; recently referred to community, hospital and hospice palliative care services across England and Wales. Sub-study participants were patients, caregivers and HPs. 1833 participants were recruited. PiPS-B risk categories were as accurate as AMPES [PiPS-B accuracy (910/1484; 61%); AMPES (914/1484; 61%); p = 0.851]. PiPS-B14 discrimination (C-statistic 0.837) and PiPS-B56 (0.810) were excellent. PiPS-B14 predictions were too high in the 57–74% risk group (Calibration-in-the-large [CiL] -0.202; Calibration slope [CS] 0.840). PiPS-B56 was well-calibrated (CiL 0.152; CS 0.914). PiPS-A risk categories were less accurate than AMPES (p<0.001). PiPS-A14 (C-statistic 0.825; CiL -0.037; CS 0.981) and PiPS-A56 (C-statistic 0.776; CiL 0.109; CS 0.946) had excellent or reasonably good discrimination and calibration. Interviewed patients (n = 29) and caregivers (n = 20) wanted prognostic information and considered that PiPS may aid communication. HPs (n = 32) found PiPS user-friendly and considered risk categories potentially helpful for decision-making. The need for a blood test for PiPS-B was considered a limitation.

Conclusions

PiPS-B risk categories are as accurate as AMPES made by experienced doctors and nurses. PiPS-A categories are less accurate. Patients, carers and HPs regard PiPS as potentially helpful in clinical practice.

Study registration

ISRCTN13688211.

Comparison of the prevalence and associated factors of hyperactive delirium in advanced cancer patients between inpatient palliative care and palliative home care

Background

Hyperactive delirium is known to increase family distress and the burden on health care providers. We compared the prevalence and associated factors of agitated delirium in advanced cancer patients between inpatient palliative care and palliative home care on admission and at 3 days before death.

Methods

This was a post hoc exploratory analysis of two multicenter, prospective cohort studies of advanced cancer patients, which were performed at 23 palliative care units (PCUs) between Jan and Dec 2017, and on 45 palliative home care services between July and Dec 2017.

Results

In total, 2998 patients were enrolled and 2829 were analyzed in this study: 1883 patients in PCUs and 947 patients in palliative home care. The prevalence of agitated delirium between PCUs and palliative home care was 5.2% (95% CI: 4.2% ‐ 6.3%) vs. 1.4% (0.7% ‐ 2.3%) on admission (p < 0.001) and 7.6% (6.4% ‐ 8.9%) vs. 5.4% (4.0% ‐ 7.0%) 3 days before death (p < 0.001). However, multivariate logistic regression analysis revealed that the place of care was not significantly associated with the prevalence of agitated delirium at 3 days before death after adjusting for prognostic factors, physical risk factors, and symptoms.

Conclusions

There was no significant difference in the prevalence of agitated delirium at 3 days before death between inpatient palliative care and palliative home care after adjusting for the patient background, prognostic factors, symptoms, and treatment.

Dealing with prognostic uncertainty: the role of prognostic models and websites for patients with advanced cancer

PURPOSE OF REVIEW

To provide an updated overview of prognostic models in advanced cancer and highlight the role of prognostic calculators.

RECENT FINDINGS

In the advanced cancer setting, many important healthcare decisions are driven by a patient's prognosis. However, there is much uncertainty in formulating prognosis, particularly in the era of novel cancer therapeutics. Multiple prognostic models have been validated for patients seen by palliative care and have a life expectancy of a few months or less, such as the Palliative Performance Scale, Palliative Prognostic Score, Palliative Prognostic Index, Objective Prognostic Score, and Prognosis in Palliative Care Study Predictor. However, these models are seldom used in clinical practice because of challenges related to limited accuracy when applied individually and difficulties with model selection, computation, and interpretation. Online prognostic calculators emerge as tools to facilitate knowledge translation by overcoming the above challenges. For example, www.predictsurvival.com provides the output for seven prognostic indexes simultaneously based on 11 variables.

SUMMARY

Prognostic models and prognostic websites are currently available to augment prognostication in the advanced cancer setting. Further studies are needed to examine their impact on prognostic accuracy, confidence, and clinical outcomes.

Association Between Heart Rate and Reversibility of the Symptom, Refractoriness to Palliative Treatment, and Survival in Dyspneic Cancer Patients

CONTEXT

Dyspnea is one of the most distressing symptoms for terminally ill cancer patients and a predictor of poor prognosis. Identification of simple clinical signs, such as heart rate, indicating clinical course of each patient is of value.

OBJECTIVES

To explore the potential association between heart rate and reversibility of the symptom, treatment response to palliative intervention, and survival in terminally ill cancer patients with dyspnea at rest.

METHODS

This is a secondary analysis of a multicenter prospective cohort study of patients with advanced cancer to validate multiple prognostic tools. In the patients with dyspnea at rest at the baseline, we examined a potential association between heart rate and the reversibility of dyspnea and refractoriness to palliative treatment using logistic regression analysis. Survivals were compared using the Cox proportional hazards model among four groups with different levels of the heart rate (≤74, 75-84, 85-97, and ≥98).

RESULTS

A total of 2298 patients were enrolled, and 418 patients (18%) had dyspnea at rest. Reversibility of dyspnea was significantly higher in the patients with lower heart rate (P for trend = 0.008), and the refractoriness to palliative treatment tended to be higher in the patients with higher heart rate (P for trend = 0.101). The median survival for each heart rate quartile groups was significantly higher in the lower heart rate group (24 vs. 21 vs. 14 vs. 9 days; heart rate ≤74, 75-84, 85-97, and ≥98, respectively; log-rank P < 0.001).

CONCLUSION

Heart rate may help clinicians to make the prediction of the patient's clinical course more accurate.

PALLIA-10, a screening tool to identify patients needing palliative care referral in comprehensive cancer centers: A prospective multicentric study (PREPA-10)

Purpose

The identification and referral of patients in need of palliative care should be improved. The French society for palliative support and care recommended to use the PALLIA‐10 questionnaire and its score greater than 3 to refer patients to palliative care. We explored the use of the PALLIA‐10 questionnaire and its related score in a population of advanced cancer patients.

Methods

This prospective multicentric study is to be conducted in authorized French comprehensive cancer centers on hospitalized patients on a given day. We aimed to use the PALLIA‐10 score to determine the proportion of palliative patients with a score >3. Main secondary endpoints were to determine the proportion of patients already managed by palliative care teams at the study date or referred to palliative care in six following months, the prevalence of patients with a score greater than 5, and the overall survival using the predefined thresholds of 3 and 5.

Results

In 2015, eighteen French cancer centers enrolled 840 patients, including 687 (82%) palliative patients. 479 (69.5%) patients had a score >3, 230 (33.5%) had a score >5, 216 (31.4%) patients were already followed‐up by a palliative care team, 152 patients were finally referred to PC in the six subsequent months.

The PALLIA‐10 score appeared as a reliable predictive (adjusted OR_Ref≤3: 1.9 [1.17‐3.16] and 3.59 [2.18‐5.91]) and prognostic (adjusted HR_Ref≤3 = 1.58 [95%CI 1.20‐2.08] and 2.18 [95%CI 1.63‐2.92]) factor for patients scored 4‐5 and >5, respectively.

Conclusion

The PALLIA‐10 questionnaire is an easy‐to‐use tool to refer cancer inpatients to palliative care in current practice. However a score greater than 5 using the PALLIA‐10 questionnaire would be more appropriate for advanced cancer patients hospitalized in comprehensive cancer center.

PROgnostic Model for Advanced Cancer (PRO-MAC)

OBJECTIVE

To develop and validate a simple prognostic tool for early prediction of survival of patients with advanced cancer in a tertiary care setting.

DESIGN

Prospective cohort study with 2 years' follow-up.

SETTING

Single tertiary teaching hospital in Singapore.

PARTICIPANTS

The study includes consecutive patients diagnosed with advanced cancer who were referred to a palliative care unit between 2013 and 2015 (N=840). Data were randomly split into training (n=560) and validation (n=280) sets.

RESULTS

743 (88.5%) patients died with a mean follow-up of 97.0 days (SD 174.0). Cox regression modelling was used to build a prognostic model, cross-validating with six randomly split dataset pairs. Predictor variables for the model included functional status (Palliative Performance Scale, PPS V.2), symptoms (Edmonton Symptom Assessment System, ESASr), clinical assessment (eg, the number of organ systems with metastasis, serum albumin and total white cell count level) and patient demographics. The area under the receiver operating characteristic curve using the final averaged prognostic model was between 0.69 and 0.75. Our model classified patients into three prognostic groups, with a median survival of 79.0 days (IQR 175.0) for the low-risk group (0-1.5 points), 42.0 days (IQR 75.0) for the medium-risk group (2.0-5.5 points), and 15.0 days (IQR 28.0) for the high-risk group (6.0-10.5 points).

CONCLUSIONS

PROgnostic Model for Advanced Cancer (PRO-MAC) takes into account patient and disease-related factors and identify high-risk patients with 90-day mortality. PPS V.2 and ESASr are important predictors. PRO-MAC will help physicians identify patients earlier for supportive care, facilitating multidisciplinary, shared decision-making.

Prognostication in advanced cancer: update and directions for future research

The objective of this review is to provide an update on prognostication in patients with advanced cancer and to discuss future directions for research in this field. Accurate prognostication of survival for patients with advanced cancer is vital, as patient life expectancy informs many important personal and clinical decisions. The most common prognostic approach is clinician prediction of survival (CPS) using temporal, surprise, or probabilistic questions. The surprise and probabilistic questions may be more accurate than the temporal approach, partly by limiting the time frame of prediction. Prognostic models such as the Glasgow Prognostic Score (GPS), Palliative Performance Scale (PPS), Palliative Prognostic Score (PaP), Palliative Prognostic Index (PPI), or Prognosis in Palliative Care Study (PiPS) predictor model may augment CPS. However, care must be taken to select the appropriate tool since prognostic accuracy varies by patient population, setting, and time frame of prediction. In addition to life expectancy, patients and caregivers often desire that expected treatment outcomes and bodily changes be communicated to them in a sensible manner at an appropriate time. We propose the following 10 major themes for future prognostication research: (1) enhancing prognostic accuracy, (2) improving reliability and reproducibility of prognosis, (3) identifying the appropriate prognostic tool for a given setting, (4) predicting the risks and benefits of cancer therapies, (5) predicting survival for pediatric populations, (6) translating prognostic knowledge into practice, (7) understanding the impact of prognostic uncertainty, (8) communicating prognosis, (9) clarifying outcomes associated with delivery of prognostic information, and (10) standardizing prognostic terminology.

Low Transthyretin Levels Predict Poor Prognosis in Cancer Patients in Palliative Care Settings

OBJECTIVES

Although transthyretin (TTR) is a nutritional indicator and is influenced by systemic inflammation, it may be a good prognostic indicator for cancer patients in palliative care settings. This study investigates the correlation between low TTR levels and survival among cancer patients in palliative care settings.

METHODS

This was a sub-analysis of a prospective, multicenter cohort study. Patients who had advanced-stage cancer and who were newly referred to palliative care services were eligible to participate; however, those receiving anti-tumor therapy were excluded. Survival analyses were performed to clarify predictors of poor prognosis.

RESULTS

A total of 144 patients were enrolled (45.1% female; median age, 72 years). Cox regression analysis revealed that low TTR levels (<10.9 mg/l) (hazard ratio 1.74, P = 0.025), poor muscle power (1.71, P = 0.045), and fatigue (1.89, P = 0.024) were predictors of poor prognosis. Median survival in patients with low TTR levels (<10.9 mg/l) was 26 days, which was significantly shorter than those with high TTR levels (≥10.9 mg/l) (50 days; P < 0.001).

CONCLUSION

Low TTR levels may be indicators for poor prognosis among cancer patients in palliative care settings.

The Prognosis in Palliative care Study II (PiPS2): study protocol for a multi-centre, prospective, observational, cohort study

BACKGROUND

More accurate methods of prognostication are likely to lead to improvements in the quality of care of patients approaching the ends of their lives. The Prognosis in Palliative care Scales (PiPS) are prognostic models of survival. The scores are calculated using simple clinical data and observations. There are two separate PiPS models; PiPS-A for patients without blood test results and PiPS-B for patients with blood test results. Both models predict whether a patient is likely to live for "days", "weeks" or "months" and have been shown to perform as well as clinicians' estimates of survival. PiPS-B has also been found to be significantly better than doctors' estimates of survival. We report here a protocol for the validation of PiPS and for the evaluation of the accuracy of other prognostic tools in a new, larger cohort of patients with advanced cancer.

METHODS

This is a national, multi-centre, prospective, observational cohort study, aiming to recruit 1778 patients via palliative care services across England and Wales. Eligible patients have advanced, incurable cancer and have recently been referred to palliative care services. Patients with or without capacity are included in the study. The primary outcome is the accuracy of PiPS predictions and the difference in accuracy between these predictions and the clinicians' estimates of survival; with PiPS-B being the main model of interest. The secondary outcomes include the accuracy of predictions by the Palliative Prognostic Index (PPI), Palliative Performance Scale (PPS), Palliative Prognostic score (PaP) and the Feliu Prognostic Nomogram (FPN) compared with actual patient survival and clinicians' estimates of survival. A nested qualitative sub-study using face-to-face interviews with patients, carers and clinicians is also being undertaken to assess the acceptability of the prognostic models and to identify barriers and facilitators to clinical use.

DISCUSSION

The study closed to recruitment at the end of April 2018 having exceeded the required sample size of 1778 patients. The qualitative sub-study is nearing completion. This demonstrates the feasibility of recruiting large numbers of participants to a prospective palliative care study.

TRIAL REGISTRATION

ISRCTN13688211 (registration date: 28/06/2016).

A review of systemic anticancer therapy in disease palliation

BACKGROUND

Systemic anticancer therapy (SACT) is a collective term to describe the growing number of differing therapies used in malignancy to achieve palliation. Improving symptoms, quality of life (QOL) and where possible quantity of life are the goals of these treatments.

SOURCES OF DATA

A comprehensive literature review was undertaken using Medline, Embase and the Cochrane database.

AREAS OF AGREEMENT

The use of palliative SACT can lead to increases in symptom control, QOL and survival. The breadth of treatable cancers has increased along with the number of therapeutic options.

AREAS OF CONTROVERSY

The increasing use of SACT in the last weeks of life and the lack of consistency about the terms Supportive Care/Best Supportive Care in the trial setting.

GROWING POINTS

Integration between oncology and other palliative services leads to better outcomes.

AREAS TIMELY FOR DEVELOPING RESEARCH

Improved prognostication tools to elucidate which patients will benefit from SACT.

C-reactive protein, symptoms and activity of daily living in patients with advanced cancer receiving palliative care

BACKGROUND

The association between C-reactive protein (CRP) level, symptoms, and activities of daily living (ADL) in advanced cancer patients is unclear.

METHODS

Secondary data analysis of a multicenter prospective cohort study consisted of 2426 advanced cancer patients referred to palliative care settings was conducted to examine the cross-sectional relationships between CRP level, symptoms, and ADL disabilities. Laboratory data, symptoms, ADL, and manual muscle testing (MMT) results were obtained at baseline. Participants were divided into four groups: low (CRP < 1 mg/dl), moderate (1 = < CRP <5 mg/dl), high (5 = < CRP < 10 mg/dl), and very high CRP (10 mg/dl = < CRP). The proportions of eight symptoms, five ADL disabilities, and three categories of MMT according to the CRP groups were tested by chi-square tests. Multiple-adjusted odd ratios (ORs) were calculated by using ordinal logistic regression after adjustment for age, gender, site of primary cancer, metastatic disease, performance status, chemotherapy, and setting of care.

RESULTS

A total of 1702 patients were analysed. Positive rates of symptoms and ADL disabilities increased with increasing CRP level. In the very high-CRP group, rates of positivity for anorexia, fatigue, and weight loss were 89.8%, 81.0%, and 79.2%, respectively, and over 70% of patients received assistance for bathing, dressing, going to the toilet, and transfer. The grade of MMT also deteriorated with increasing CRP level. Adjusted ORs for the accumulated symptoms significantly increased with increasing CRP level in the moderate-CRP, high-CRP, and very high-CRP groups [1.6 (95% confidence interval 1.2-2.0), P < 0.001; 2.5 (1.9-3.2), P < 0.001; 3.5 (2.7-4.6), P < 0.001, respectively]. Adjusted ORs for the accumulated ADL disabilities significantly increased in the very high-CRP groups [2.1 (1.5-2.9), P < 0.001].

CONCLUSIONS

Associations between CRP level, symptoms, and ADL were observed in advanced cancer patients receiving palliative care.

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.

A systematically structured review of biomarkers of dying in cancer patients in the last months of life; An exploration of the biology of dying

BACKGROUND

The Neuberger review made a number of recommendations to improve end of life care, including research into the biology of dying. An important aspect of the biology of dying is the identification of biomarkers as indices of disease processes. Biomarkers have the potential to inform the current, limited understanding of the dying process and assist clinicians in recognising dying, in particular how to distinguish dying from reversible acute deterioration.

OBJECTIVES

To critically appraise the literature on biological factors that may be used as prognostic indicators in advanced cancer patients and to identify candidate biomarkers of the dying process that can be measured serially in cancer patients' bodily fluids.

METHODS

A systematically structured review was conducted using three electronic databases. A hand search of six peer-reviewed journals and conference abstracts was also conducted. Studies reporting prognostic biomarkers in cancer patients with a median survival of ≤90 days and post-mortem studies were included. Final levels of evidence and recommendations were made using the Evidence Based Medicine modified GRADE system.

RESULTS

30 articles were included. Seven prognostic biological factors demonstrated Grade A evidence (lymphocyte count, white blood cell count, serum C-reactive protein, albumin, sodium, urea and alkaline phosphatase). An additional eleven prognostic factors were identified with Grade B evidence (platelet count, international normalised ratio, serum vitamin B12, prealbumin, bilirubin, cholesterol, aspartate aminotransferase, alanine transaminase, lactate dehydrogenase, pseudocholinesterase and urate). A number of biomarkers were specifically identified in the last two weeks of life but limitations exist. No post-mortem studies met the inclusion criteria.

CONCLUSION

The biology of dying is an important area for future research, with the evidence focused on signs, symptoms and prognostic factors. This review identifies a number of common themes shared amongst advanced cancer patients and highlights candidate biomarkers which may be indicative of a common biological process to dying.

Adding items that assess changes in activities of daily living does not improve the predictive accuracy of the Palliative Prognostic Index

BACKGROUND

Changes in activities of daily living in cancer patients may predict their survival. The Palliative Prognostic Index is a useful tool to evaluate cancer patients, and adding an item about activities of daily living changes might improve its predictive value.

AIM

To clarify whether adding an item about activities of daily living changes improves the accuracy of Palliative Prognostic Index.

DESIGN

Multicenter prospective cohort study.

SETTING

A total of 58 palliative care services in Japan.

PARTICIPANTS

Patients aged >20 years diagnosed with locally extensive or metastatic cancer (including hematological neoplasms) who had been admitted to palliative care units, were receiving care by hospital-based palliative care teams, or were receiving home-based palliative care. Palliative care physicians recorded clinical variables at the first assessment and followed up patients 6 months later.

RESULTS

A total of 2425 subjects were recruited and 2343 of these had analyzable data. The C-statistic of the original Palliative Prognostic Index was 0.801, and those of modified Palliative Prognostic Indices ranged from 0.793 to 0.805 at 3 weeks. For 6-week survival predictions, the C-statistic of the original Palliative Prognostic Index was 0.802, and those of modified Palliative Prognostic Indices ranged from 0.791 to 0.799. The weighted kappa of the original Palliative Prognostic Index was 0.510, and those of modified Palliative Prognostic Indices ranged from 0.484 to 0.508.

CONCLUSION

Adding items about activities of daily living changes to the Palliative Prognostic Index did not improve prognostic value in advanced cancer patients.

Prospective Validation of the Objective Prognostic Score for Advanced Cancer Patients in Diverse Palliative Settings

CONTEXT

Prognostication is an essential part of palliative care to aid decision making and negotiate goals of care. The Objective Prognostic Score (OPS) is an easy-to-use prognosticating tool to predict survival among far-advanced cancer patients in palliative care units (PCUs) in Korea.

OBJECTIVES

This study aimed to prospectively validate the OPS for advanced cancer patients in the palliative care teams (PCTs), PCUs, and home-based palliative care (HPC) in Japan.

METHODS

This was a substudy of a multicenter prospective cohort study that was conducted to validate and compare prognostic tools among advanced cancer patients in Japan. Participants' survival was calculated according to OPS 3 as a cutoff for predicting survival of less than three weeks. Overall accuracy and area under the receiver operator characteristic curves of OPS 3 were calculated for PCT, PCU, and HPC, respectively.

RESULTS

A total of 1146 cases (PCTs 441, PCUs 519, and HPCs 186 cases) were included in final analyses. The overall accuracy of OPS 3 for predicting three-week survival ranged from 0.70 to 0.78 across diverse palliative care settings. The c-statistics ranged from 0.742 to 0.808 across three settings. Participants in the PCT showed the highest overall accuracy and c-statistics for OPS.

CONCLUSION

The OPS can be used for prognostication among advanced cancer patients in PCT, PCU, and HPC settings.

Clinical Implications of C-Reactive Protein as a Prognostic Marker in Advanced Cancer Patients in Palliative Care Settings

CONTEXT

Plasma C-reactive protein (CRP) levels are elevated in patients with advanced cancer.

OBJECTIVES

To investigate CRP as a prognostic marker in palliative settings.

METHODS

This multicenter prospective cohort study comprised 2426 patients. Laboratory data were obtained at baseline, and all patients were followed until death or six months after their enrollment. A total of 1511 patients were eligible for the analyses. They were divided into four groups: low-CRP (CRP < 1 mg/dL), moderate-CRP (1 ≤ CRP <5 mg/dL), high-CRP (5 ≤ CRP <10 mg/dL), and very high-CRP (10 mg/dL ≤ CRP) groups. Survival was investigated by the Kaplan-Meier method with the log-rank test. The 30-, 60-, and 90-day mortality rates were tested by Chi-squared tests. Univariate- and multivariate-adjusted hazard ratios (HRs) and 95% CIs in each group were calculated using Cox proportional hazard models.

RESULTS

Survival rate decreased and mortality rate increased with increasing CRP level. The differences in survival and 30-, 60-, and 90-day mortality rates among the groups were statistically significant (P < 0.001). Baseline CRP level was significantly associated with a higher risk of mortality after adjustment for age, gender, primary tumor site, metastasis, chemotherapy, Eastern Cooperative Oncology Group Performance Status, and setting of care (moderate-CRP: HR 1.47 [95% CI 1.24-1.73], high-CRP: HR 2.09 [95% CI 1.74-2.50], and very high-CRP: HR 2.55 [95% CI 2.13-3.05] vs. low-CRP).

CONCLUSION

Clear dose-effect relationships between elevated CRP levels and prognoses indicate that CRP could be useful in predicting prognoses in patients with advanced cancer.

Validation of the Simplified Palliative Prognostic Index Using a Single Item From the Communication Capacity Scale

CONTEXT

Although the Palliative Prognostic Index (PPI) is a reliable and validated tool to predict the survival of terminally ill cancer patients, all clinicians cannot always precisely diagnose delirium.

OBJECTIVES

The primary aim of this study was to examine the predictive value of a simplified PPI. In the simplified PPI, a single item from the Communication Capacity Scale was substituted for the delirium item of the original.

METHODS

This multicenter prospective cohort study was conducted in Japan from September 2012 through April 2014 and involved 16 palliative care units, 19 hospital-based palliative care teams, and 23 home-based palliative care services. Palliative care physicians recorded clinical variables at the first assessment and followed up patients six months later.

RESULTS

A total of 2425 subjects were recruited; 2343 had analyzable data. The C-statistics of the original and simplified PPIs were 0.801 and 0.800 for three week and 0.800 and 0.781 for six-week survival predictions, respectively. The sensitivity and specificity for survival predictions using the simplified PPI were 72.9% and 67.6% (for three week) and 80.3% and 61.8% (for six week), respectively.

CONCLUSION

The simplified PPI showed essentially the same predictive value as the original PPI and is an alternative when clinicians have difficulties in diagnosing delirium.

The Accuracy of Physicians' Clinical Predictions of Survival in Patients With Advanced Cancer

CONTEXT

Accurate prognoses are needed for patients with advanced cancer.

OBJECTIVES

To evaluate the accuracy of physicians' clinical predictions of survival (CPS) and assess the relationship between CPS and actual survival (AS) in patients with advanced cancer in palliative care units, hospital palliative care teams, and home palliative care services, as well as those receiving chemotherapy.

METHODS

This was a multicenter prospective cohort study conducted in 58 palliative care service centers in Japan. The palliative care physicians evaluated patients on the first day of admission and followed up all patients to their death or six months after enrollment. We evaluated the accuracy of CPS and assessed the relationship between CPS and AS in the four groups.

RESULTS

We obtained a total of 2036 patients: 470, 764, 404, and 398 in hospital palliative care teams, palliative care units, home palliative care services, and chemotherapy, respectively. The proportion of accurate CPS (0.67-1.33 times AS) was 35% (95% CI 33-37%) in the total sample and ranged from 32% to 39% in each setting. While the proportion of patients living longer than CPS (pessimistic CPS) was 20% (95% CI 18-22%) in the total sample, ranging from 15% to 23% in each setting, the proportion of patients living shorter than CPS (optimistic CPS) was 45% (95% CI 43-47%) in the total sample, ranging from 43% to 49% in each setting.

CONCLUSION

Physicians tend to overestimate when predicting survival in all palliative care patients, including those receiving chemotherapy.

Survival prediction for advanced cancer patients in the real world: A comparison of the Palliative Prognostic Score, Delirium-Palliative Prognostic Score, Palliative Prognostic Index and modified Prognosis in Palliative Care Study predictor model

PURPOSE

The aim of this study was to investigate the feasibility and accuracy of the Palliative Prognostic Score (PaP score), Delirium-Palliative Prognostic Score (D-PaP score), Palliative Prognostic Index (PPI) and modified Prognosis in Palliative Care Study predictor model (PiPS model).

PATIENTS AND METHODS

This multicentre prospective cohort study involved 58 palliative care services, including 19 hospital palliative care teams, 16 palliative care units and 23 home palliative care services, in Japan from September 2012 to April 2014. Analyses were performed involving four patient groups: those treated by palliative care teams, those in palliative care units, those at home and those receiving chemotherapy.

RESULTS

We recruited 2426 participants, and 2361 patients were finally analysed. Risk groups based on these instruments successfully identified patients with different survival profiles in all groups. The feasibility of PPI and modified PiPS-A was more than 90% in all groups, followed by PaP and D-PaP scores; modified PiPS-B had the lowest feasibility. The accuracy of prognostic scores was ⩾69% in all groups and the difference was within 13%, while c-statistics were significantly lower with the PPI than PaP and D-PaP scores.

CONCLUSION

The PaP score, D-PaP score, PPI and modified PiPS model provided distinct survival groups for patients in the three palliative care settings and those receiving chemotherapy. The PPI seems to be suitable for routine clinical use for situations where rough estimates of prognosis are sufficient and/or patients do not want invasive procedure. If clinicians can address more items, the modified PiPS-A would be a non-invasive alternative. In cases where blood samples are available or those requiring more accurate prediction, the PaP and D-PaP scores and modified PiPS-B would be more appropriate.

Surprise Questions for Survival Prediction in Patients With Advanced Cancer: A Multicenter Prospective Cohort Study

BACKGROUND

Predicting the short-term survival in cancer patients is an important issue for patients, family, and oncologists. Although the prognostic accuracy of the surprise question has value in 1-year mortality for cancer patients, the prognostic value for short-term survival has not been formally assessed. The primary aim of the present study was to assess the prognostic value of the surprise question for 7-day and 30-day survival in patients with advanced cancer.

PATIENTS AND METHODS

The present multicenter prospective cohort study was conducted in Japan from September 2012 through April 2014, involving 16 palliative care units, 19 hospital-based palliative care teams, and 23 home-based palliative care services.

RESULTS

We recruited 2,425 patients and included 2,361 for analysis: 912 from hospital-based palliative care teams, 895 from hospital palliative care units, and 554 from home-based palliative care services. The sensitivity, specificity, positive predictive value, and negative predictive value of the 7-day survival surprise question were 84.7% (95% confidence interval [CI], 80.7%-88.0%), 68.0% (95% CI, 67.3%-68.5%), 30.3% (95% CI, 28.9%-31.5%), and 96.4% (95% CI, 95.5%-97.2%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for the 30-day surprise question were 95.6% (95% CI, 94.4%-96.6%), 37.0% (95% CI, 35.9%-37.9%), 57.6% (95% CI, 56.8%-58.2%), and 90.4% (95% CI, 87.7%-92.6%), respectively.

CONCLUSION

Surprise questions are useful for screening patients for short survival. However, the high false-positive rates do not allow clinicians to provide definitive prognosis prediction.

IMPLICATIONS FOR PRACTICE

The findings of this study indicate that clinicians can screen patients for 7- or 30-day survival using surprise questions with 90% or more sensitivity. Clinicians cannot provide accurate prognosis estimation, and all patients will not always die within the defined periods. The screened patients can be regarded as the subjects to be prepared for approaching death, and proactive discussion would be useful for such patients.

Glasgow prognostic score predicts prognosis for cancer patients in palliative settings: a subanalysis of the Japan-prognostic assessment tools validation (J-ProVal) study

PURPOSE

The Glasgow prognostic score (GPS), which uses C-reactive protein and albumin levels, is a good predictor of prognosis in cancer patients undergoing anti-tumor therapy. The objective of this study was to investigate the correlation between GPS and survival among cancer patients in palliative settings, as findings in such populations have not been well described.

METHODS

This was a subanalysis of a multicenter, prospective, cohort study in patients who were adults, diagnosed with advanced cancer, and first referred to palliative care service in Japan. Patients who were not receiving anti-tumor therapy and who had undergone laboratory examinations were eligible. Clinical features were analyzed to investigate prognostic factors.

RESULTS

A total of 1160 patients were enrolled (41.6 % female; median age, 72 years). The independent predictors were Eastern Cooperative Oncology Group performance status (ECOG PS) score of 4 (hazard ratio (HR), 1.54), liver metastasis (HR, 1.21), dyspnea (HR, 1.35), edema (HR, 1.25), prognostic performance index (HR, 1.56), neutrophil-lymphocyte ratio (HR, 1.43), and GPS of 2 (HR, 1.36). The sensitivity and specificity for 3-week prognosis of a GPS of 2 were 0.879 and 0.410. Median survival time with GPS of 0, 1, and 2 was 58 days (95 % confidence interval, 48-81), 43 days (37-50), and 21 days (19-24), respectively (log-rank test, p < 0.001).

CONCLUSION

The GPS was a good prognostic indicator for cancer patients in palliative settings.