Diagnostic accuracy of the palliative prognostic score in hospitalized patients with advanced cancer

Preliminary results regarding automated identification of patients with a limited six-month survival prognosis using nursing assessment in uro-oncology patients

INTRODUCTION

Contrary to current recommendations, palliative co-management of tumor patients often occurs late in daily clinical practice. Palliative care specialist (PCS) co-management should be considered at the latest after a 6-month prognosis has been presumed. Therefore, identifying patients with a limited prognosis is a reasonable measure.

METHODS

Patients were identified using a screening tool for limited prognosis, which combined their tumor stage and data from the nursing anamnesis. In this retrospective study, a monocentric cohort of patients with urological malignancies-UICC (Union for International Cancer Control) stages III and IV - were enrolled from March to December 2019, with a 6-month follow-up period ending in May 2020.

RESULTS

Most patients were male and suffered from prostate cancer. Patients with uro-oncological tumors dying within 6 months correlated significantly with the presence of repeated hospitalizations within three months, pain on admission, malnutrition, impaired breathing and reduced mobility (P < 0.001). The test was fair in quality (AUC 0.727) at a cut-point of five; a sensitivity of 97% and a specificity of 25% were obtained. The PPV was 0.64 and NPV was 0.82.

DISCUSSION/CONCLUSION

We specifically identified the predictors of limited prognosis in urological cancer patients across several entities using an automated scoring system based on tumor stage and data from the nursing anamnesis. Therefore, we recognized hospitalization as an important transition point and determined nurses to be valuable partners in identifying unmet palliative care needs without additional technical, personnel or financial effort.

[DNVF Memorandum: Health Services Research in the Last Year of Life]

This memorandum outlines current issues concerning health services research on seriously ill and dying people in the last year of their lives as well as support available for their relatives. Patients in the last phase of life can belong to different disease groups, they may have special characteristics (e. g., people with cognitive and complex impairments, economic disadvantage or migration background) and be in certain phases of life (e. g., parents of minor children, (old) age). The need for a designated memorandum on health services research in the last year of life results from the special situation of those affected and from the special features of health services in this phase of life. With reference to these special features, this memorandum describes methodological and ethical specifics as well as current issues in health services research and how these can be adequately addressed using quantitative, qualitative and mixed methods. It has been developed by the palliative medicine section of the German Network for Health Services Research (DNVF) according to the guidelines for DNVF memoranda.

Comparison of Objective Prognostic Score and Palliative Prognostic Score performance in inpatients with advanced cancer in Japan and Korea

OBJECTIVE

Accurate prognostication is important for patients and their families to prepare for the end of life. Objective Prognostic Score (OPS) is an easy-to-use tool that does not require the clinicians' prediction of survival (CPS), whereas Palliative Prognostic Score (PaP) needs CPS. Thus, inexperienced clinicians may hesitate to use PaP. We aimed to evaluate the accuracy of OPS compared with PaP in inpatients in palliative care units (PCUs) in three East Asian countries.

METHOD

This study was a secondary analysis of a cross-cultural, multicenter cohort study. We enrolled inpatients with far-advanced cancer in PCUs in Japan, Korea, and Taiwan from 2017 to 2018. We calculated the area under the receiver operating characteristics (AUROC) curve to compare the accuracy of OPS and PaP.

RESULTS

A total of 1,628 inpatients in 33 PCUs in Japan and Korea were analyzed. OPS and PaP were calculated in 71.7% of the Japanese patients and 80.0% of the Korean patients. In Taiwan, PaP was calculated for 81.6% of the patients. The AUROC for 3-week survival was 0.74 for OPS in Japan, 0.68 for OPS in Korea, 0.80 for PaP in Japan, and 0.73 for PaP in Korea. The AUROC for 30-day survival was 0.70 for OPS in Japan, 0.71 for OPS in Korea, 0.79 for PaP in Japan, and 0.74 for PaP in Korea.

SIGNIFICANCE OF RESULTS

Both OPS and PaP showed good performance in Japan and Korea. Compared with PaP, OPS could be more useful for inexperienced physicians who hesitate to estimate CPS.

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.

Is spiritual well-being related to survival time of inpatients with advanced cancer? An East Asian cohort study

OBJECTIVES

It has been suggested that psychosocial factors are related to survival time of inpatients with cancer. However, there are not many studies examining the relationship between spiritual well-being (SWB) and survival time among countries. This study investigated the relationship between SWB and survival time among three East Asian countries.

METHODS

This international multicenter cohort study is a secondary analysis involving newly admitted inpatients with advanced cancer in palliative care units in Japan, South Korea, and Taiwan. SWB was measured using the Integrated Palliative Outcome Scale (IPOS) at admission. We performed multivariate analysis using the Cox proportional hazards model to identify independent prognostic factors.

RESULTS

A total of 2,638 patients treated at 37 palliative care units from January 2017 to September 2018 were analyzed. The median survival time was 18.0 days (95% confidence interval [CI] 16.5-19.5) in Japan, 23.0 days (95% CI 19.9-26.1) in Korea, and 15.0 days (95% CI 13.0-17.0) in Taiwan. SWB was a significant factor correlated with survival in Taiwan (hazard ratio [HR] 1.27; 95% CI 1.01-1.59; p = 0.04), while it was insignificant in Japan (HR 1.10; 95% CI 1.00-1.22; p = 0.06), and Korea (HR 1.02; 95% CI 0.77-1.35; p = 0.89).

SIGNIFICANCE OF RESULTS

SWB on admission was associated with survival in patients with advanced cancer in Taiwan but not Japan or Korea. The findings suggest the possibility of a positive relationship between spiritual care and survival time in patients with far advanced cancer.

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.

The accuracy of clinician predictions of survival in the Prognosis in Palliative care Study II (PiPS2): A prospective observational study

BACKGROUND

Prognostic information is important for patients with cancer, their families, and clinicians. In practice, survival predictions are made by clinicians based on their experience, judgement, and intuition. Previous studies have reported that clinicians' survival predictions are often inaccurate. This study reports a secondary analysis of data from the Prognosis in Palliative care Study II (PiPS2) to assess the accuracy of survival estimates made by doctors and nurses.

METHODS AND FINDINGS

Adult patients (n = 1833) with incurable, locally advanced or metastatic cancer, recently referred to palliative care services (community teams, hospital teams, and inpatient palliative care units) were recruited. Doctors (n = 431) and nurses (n = 777) provided independent prognostic predictions and an agreed multi-professional prediction for each patient. Clinicians provided prognostic estimates in several formats including predictions about length of survival and probability of surviving to certain time points. There was a minimum follow up of three months or until death (whichever was sooner; maximum follow-up 783 days). Agreed multi-professional predictions about whether patients would survive for days, weeks or months+ were accurate on 61.9% of occasions. The positive predictive value of clinicians' predictions about imminent death (within one week) was 77% for doctors and 79% for nurses. The sensitivity of these predictions was low (37% and 35% respectively). Specific predictions about how many weeks patients would survive were not very accurate but showed good discrimination (patients estimated to survive for shorted periods had worse outcomes). The accuracy of clinicians' probabilistic predictions (assessed using Brier's scores) was consistently better than chance, improved with proximity to death and showed good discrimination between groups of patients with different survival outcomes.

CONCLUSIONS

Using a variety of different approaches, this study found that clinicians predictions of survival show good discrimination and accuracy, regardless of whether the predictions are about how long or how likely patients are to survive. Accuracy improves with proximity to death. Although the positive predictive value of estimates of imminent death are relatively high, the sensitivity of such predictions is relatively low. Despite limitations, the clinical prediction of survival should remain the benchmark against which any innovations in prognostication are judged.

STUDY REGISTRATION

ISRCTN13688211. http://www.isrctn.com/ISRCTN13688211.

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.

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.

Comparison of the accuracy of clinicians' prediction of survival and Palliative Prognostic Score: an East Asian cross-cultural study

PURPOSE

No study has been conducted to compare the clinicians' prediction of survival (CPS) with Palliative Prognostic Scores (PaP) across countries. We aimed to compare the performance of the CPS in PaP (PaP-CPS), the PaP without the CPS, and the PaP total scores in patients with advanced cancer in three East Asian countries.

METHODS

We compared the discriminative accuracy of the three predictive models (the PaP-CPS [the score of the categorical CPS of PaP], the PaP without the CPS [sum of the scores of only the objective variables of PaP], and the PaP total score) in patients admitted to palliative care units (PCUs) in Japan, Korea, and Taiwan. We calculated the area under the receiver operating characteristic curve (AUROC) for 30-day survival to compare the discriminative accuracy of these three models.

RESULTS

We analyzed 2,072 patients from three countries. The AUROC for the PaP total scores was 0.84 in patients in Japan, 0.76 in Korea, and 0.79 in Taiwan. The AUROC of the PaP-CPS was 0.82 in patients in Japan, 0.75 in Korea, and 0.78 in Taiwan. The AUROC of the PaP without the CPS was 0.75 in patients in Japan, 0.66 in Korea, and 0.67 in Taiwan.

CONCLUSION

The PaP total scores and the PaP-CPS consistently showed similar discriminative accuracy in predicting 30-day survival in patients admitted to PCUs in Japan, Korea, and Taiwan. It may be sufficient for experienced clinicians to use the CPS alone for estimating the short-term survival (less than one month) of patients with far-advanced cancer. The PaP may help to improve prognostic confidence and further reduce subjective variations.

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).

Validation of the Simplified Palliative Prognostic Index to Predict Survival for Advanced Cancer Patients in Home Hospice Setting

Background

The simplified Palliative Prognostic Index (sPPI) substitutes a single item from the Communication Capacity Scale (CCS) for the delirium item of the original PPI. This study aimed to examine the validity of the sPPI for patients with advanced cancer in a home-based hospice care setting.

Methods

This study included 75 patients with advanced cancer who received home-based hospice care. We used medical records maintained by professional hospice nurses who had visited the patients in their homes. Based on their sPPI score, patients were divided into three groups—A (<4), B (≥4 and <6), and C (≥6)—to compare survival. Further, we investigated the sPPI’s accuracy using the area under the receiver operating characteristic curve (AUC) and sensitivity and specificity for 3- and 6-week survival. We used three sPPIs including different substitutions for the delirium item (two methods using the CCS and one using the Korean Nursing Delirium Screening Scale).

Results

The median survival was 60–61 days for group A, 27–30 days for group B, and 12–16 days for group C. The difference in survival was significant (P<0.05). The AUC was 0.814–0.867 for 3-week survival and 0.736–0.779 for 6-week survival. For 3- and 6-week survival, prognostic prediction showed sensitivities of 76.2%–90.9% and 76.3%–86.8%, and specificities of 64.2%–88.7% and 51.4%–70.3%, respectively.

Conclusion

The sPPI, which is measured by professional hospice nurses, has acceptable validity to predict survival for patients with advanced cancer in a home hospice setting in South Korea.

A Prognostic Model to Facilitate Palliative Care Referral in Oncology Outpatients

Purpose

We aimed to develop a prognostic model to assist palliative care referral at least 3 months before death in advanced cancer patients treated at an outpatient medical oncology clinic.

Materials and Methods

In this prospective cohort study, a total of 200 patients were enrolled at a tertiary cancer center in South Korea. The major eligibility criterion was an expected survival of less than a year as estimated by their oncologists. We analyzed the influences of known prognostic factors along with chemotherapy status, mid-arm circumference, and triceps skinfold thickness on survival time.

Results

The mean age of the patients was 64.5 years, 36% were female, and the median survival time was 7.6 months. In the multivariate analysis, we found six significant factors related to poor survival: a poor Eastern Cooperative Oncology Group (ECOG) performance status (≥ 2), not undergoing chemotherapy, anorexia, a low lymphocyte level (< 12%), a high lactate dehydrogenase (LDH) level (≥ 300 IU/L), and a low mid-arm circumference (< 23 cm). We developed a prognostic model (score, 0–8.0) to predict 3-month survival based on the multivariate analysis. Patients who scored ≥ 4.0 points had a short survival of less than 3 months (p < 0.001). The discriminating ability of the prognostic model using the area under the receiver operating characteristic curve was 0.88.

Conclusion

The prognostic model using ECOG performance status, chemotherapy status, anorexia, lymphocytes, LDH, and mid-arm circumference can predict 3-month survival in medical oncology outpatients. It can alert oncologists to refer patients to palliative care specialists before it is too late.

Recomendaciones bioéticas para la pandemia, una perspectiva personalista

La emergencia sanitaria por la pandemia del covid-19 puso en evidencia limitaciones en los sistemas de salud a nivel mundial, lo que hizo necesario un marco bioético que brinde herramientas para orientar la toma de decisiones de los profesionales de la salud ante la escasez de recursos sanitarios. Modelos bioéticos como el principialismo, el utilitarismo y la bioética centrada en la persona buscan enfocar las decisiones clínicas con base en el respeto de los derechos y la dignidad de las personas, a fin de salvaguardar la práctica médica. La bioética centrada en la persona brinda un enfoque dirigido hacia el respeto de su dignidad en situaciones de urgencia sanitaria, para evitar dar un sentido material al hombre. Se requieren criterios de decisión para afrontar los conflictos bioéticos presentes en la práctica clínica, que reduzcan la carga legal, emocional y ética de la toma de decisiones en situaciones de pandemia.

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.

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.

Prognostic tools or clinical predictions: Which are better in palliative care?

PURPOSE

The Palliative Prognostic (PaP) score; Palliative Prognostic Index (PPI); Feliu Prognostic Nomogram (FPN) and Palliative Performance Scale (PPS) have all been proposed as prognostic tools for palliative cancer care. However, clinical judgement remains the principal way by which palliative care professionals determine prognoses and it is important that the performance of prognostic tools is compared against clinical predictions of survival (CPS).

METHODS

This was a multi-centre, cohort validation study of prognostic tools. Study participants were adults with advanced cancer receiving palliative care, with or without capacity to consent. Key prognostic data were collected at baseline, shortly after referral to palliative care services. CPS were obtained independently from a doctor and a nurse.

RESULTS

Prognostic data were collected on 1833 participants. All prognostic tools showed acceptable discrimination and calibration, but none showed superiority to CPS. Both PaP and CPS were equally able to accurately categorise patients according to their risk of dying within 30 days. There was no difference in performance between CPS and FPN at stratifying patients according to their risk of dying at 15, 30 or 60 days. PPI was significantly (p<0.001) worse than CPS at predicting which patients would survive for 3 or 6 weeks. PPS and CPS were both able to discriminate palliative care patients into multiple iso-prognostic groups.

CONCLUSIONS

Although four commonly used prognostic algorithms for palliative care generally showed good discrimination and calibration, none of them demonstrated superiority to CPS. Prognostic tools which are less accurate than CPS are of no clinical use. However, prognostic tools which perform similarly to CPS may have other advantages to recommend them for use in clinical practice (e.g. being more objective, more reproducible, acting as a second opinion or as an educational tool). Future studies should therefore assess the impact of prognostic tools on clinical practice and decision-making.

Predictive Factors of Death on Hospitalization in Patients With Advanced Cancer in Palliative Care

BACKGROUND

Prognostic assessment is essential to plan the care of patients with advanced cancer in palliative care.

OBJECTIVE

Thus, this study aims to assess the predictors of death in inpatients with advanced cancer in palliative care.

METHODS

This is a clinical, observational cohort study with patients aged >20 years, of both genders, evaluated within 48 hours of the first hospitalization. The independent variables were tumor location, nutritional risk [through the Patient-Generated Subjective Global Assessment (PG-SGA) short form], laboratory tests [C-reactive protein and albumin] and Karnofsky Performance Status (KPS). Logistic regression analyses were performed.

RESULTS

Eighty-two patients were evaluated, whose mean age was 61.8 (± 13.2) years. Forty-nine (59.8%) patients died during hospitalization, among which the majority had KPS of 30-40% (p-value = 0.043), higher means of the total score of the PG-SGA (p-value = 0.050) and lower serum albumin concentrations (p-value = 0.011). According to the multivariate model, tumor location in the gastrointestinal (GI) tract (OR: 1.73; 95% CI: 1.57-1.94), 30-40% KPS (OR: 1.29; 95% CI: 1.07-1.63) and albumin concentrations <3.5 g/dL (OR: 4.65; 95% CI: 1.22-17.7) were independent factors associated with an increased chance of death from hospitalization.

CONCLUSION

Presenting an advanced tumor with localization in the GI tract, KPS ≤40% and serum albumin concentration <3.5 g/dL at admission were predictors of death in inpatients under palliative care.

Validation of the Palliative Prognostic Index, Performance Status-Based Palliative Prognostic Index and Chinese Prognostic Scale in a home palliative care setting for patients with advanced cancer in China

BACKGROUND

The predictive value of the prognostic tool for patients with advanced cancer is uncertain in mainland China, especially in the home-based palliative care (HPC) setting. This study aimed to compare the accuracy of the Palliative Prognostic Index (PPI), the Performance Status-Based Palliative Prognostic Index (PS-PPI), and the Chinese Prognosis Scale (ChPS) for patients with advanced cancer in the HPC setting in mainland China.

METHODS

Patients with advanced cancer admitted to the hospice center of Yuebei People's Hospital between January 2014 and December 2018 were retrospectively calculated the scores according to the three prognostic tools. The Kaplan-Meier method was used to compare survival times among different risk groups. Receiver operating characteristic curve analysis was used to assess the predictive value. The accuracy of 21-, 42- and 90-day survival was compared among the three prognostic tools.

RESULTS

A total of 1863 patients were included. Survival time among the risk groups of all prognostic tools was significantly different from each other except for the PPI. The AUROC of the ChPS was significantly higher than that of the PPI and PS-PPI for 7-, 14, 21-, 42-, 90-, 120-, 150- and 180-day survival (P < 0.05). The AUROC of the PPI and PS-PPI were not significantly different from each other (P > 0.05).

CONCLUSIONS

The ChPS is more suitable than the PPI and PS-PPI for advanced cancer patients in the HPC setting. More researches are needed to verify the predictive value of the ChPS, PPI, and PS-PPI in the HPC setting in the future.

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.

High mortality rate in cancer patients with symptoms of COVID-19 with or without detectable SARS-COV-2 on RT-PCR

Background

Cancer patients presenting with COVID-19 have a high risk of death. In this work, predictive factors for survival in cancer patients with suspected SARS-COV-2 infection were investigated.

Methods

PRE-COVID-19 is a retrospective study of all 302 cancer patients presenting to this institute with a suspicion of COVID-19 from March 1st to April 25th 2020. Data were collected using a web-based tool within electronic patient record approved by the Institutional Review Board. Patient characteristics symptoms and survival were collected and compared in SARS-COV-2 real-time or reverse-transcriptase PCR (RT-PCR)–positive and RT-PCR–negative patients.

Results

Fifty-five of the 302 (18.2%) patients with suspected COVID-19 had detectable SARS-COV-2 with RT-PCR in nasopharyngeal samples. RT-PCR–positive patients were older, had more frequently haematological malignancies, respiratory symptoms and suspected COVID-19 pneumonia of computed tomography (CT) scan. However, respectively, 38% and 20% of SARS-COV-2 RT-PCR–negative patients presented similar respiratory symptoms and CT scan images. Thirty of the 302 (9.9%) patients died during the observation period, including 24 (80%) with advanced disease. At the median follow-up of 25 days after the first symptoms, the death rate in RT-PCR–positive and RT-PCR–negative patients were 21% and 10%, respectively. In both groups, independent risk factors for death were male gender, Karnofsky performance status <60, cancer in relapse and respiratory symptoms. Detection of SARS-COV-2 on RT-PCR was not associated with an increased death rate (p = 0.10). None of the treatment given in the previous month (including cytotoxics, PD1 Ab, anti-CD20, VEGFR2…) correlated with survival. The survival of RT-PCR–positive and –negative patients with respiratory symptoms and/or COVID-19 type pneumonia on CT scan was similar with a 18.4% and 19.7% death rate at day 25. Most (22/30, 73%) cancer patients dying during this period were RT-PCR negative.

Conclusion

The 30-day death rate of cancer patients with or without documented SARS-COV-2 infection is poor, but the majority of deaths occur in RT-PCR–negative patients.

Impact of Accuracy of Survival Predictions on Quality of End-of-Life Care Among Patients With Metastatic Cancer Who Receive Radiation Therapy

PURPOSE:

For patients treated with palliative radiation, we examined the association between life expectancy predictions by radiation oncologists and aggressive end-of-life care.

MATERIALS AND METHODS:

We included decedents from a study that assessed the ability of oncologists to predict survival of patients with metastatic cancer who received radiation. We identified patients who died within 12 months of study enrollment to assess accuracy of predictions. Aggressive end-of-life care was defined by the National Quality Forum, ASCO Quality Oncology Practice Initiative metrics, and advanced radiation modalities in the last month of life. Survival predictions were categorized as follows: correct (< 12 months), 12 to 18 months, 18 to 24 months, and more than 24 months. We assessed association between prediction and aggressive end-of-life care using a generalized estimation equation.

RESULTS:

Of 489 decedents, we identified 467 encounters with survival estimates. Overall, 156 decedents (32%) met at least one metric of aggressive end-of-life care. Factors associated with aggressive end-of-life care included younger age, female sex, primary cancer diagnosis, no brain metastases, and private insurance. In each encounter when an oncologist predicted survival, 363 predictions (78%) were correct (< 12 months), 54 (11%) incorrectly predicted 12 to 18 months, 27 (6%) predicted 18 to 24 months, and 23 (5%) predicted more than 24 months. Compared with patients who had encounters that had correct survival predictions, patients predicted to live more than 24 months were more likely to meet at least one metric of aggressive end-of-life care (odds ratio, 2.55; 95% CI, 1.09 to 5.99; P = .03).

CONCLUSION:

Inaccurate survival predictions by oncologists are associated with more aggressive end-of-life care for patients with advanced cancer.

Korean Physicians' Perspectives on Prognostication in Palliative Care: A Qualitative Study

BACKGROUND

Prognostication is an essential component of palliative care for patients with advanced cancer but also poses challenges. Little is known about physicians' perspectives on prognostication and prognostic tools used in palliative care practice in Eastern countries.

OBJECTIVES

To explore Korean physicians' perspectives and experiences with prognostication in their palliative care practices.

METHODS

Semi-structured interviews were conducted in Korea in 11 palliative care physicians. A constant comparative and grounded theory approach was used to derive themes from interview transcripts.

RESULTS

Participants on average had 6.4 (SD = 4.5, range 0.5-15) years of hospice and palliative care experience. We identified 4 main themes about prognostication: (1) the importance of prognostication (to help patients and their families prepare for death, to determine the appropriate time of transition to hospice care, to facilitate appropriate decision making, and to facilitate communication with patients and their families); (2) difficulties of prognostication (discomfort estimating the exact date of death); (3) basis of prognostication (clinical prediction of survival as well as prognostic scores); and (4) areas for further research (need for a simpler scoring system or parameters to predict survival with greater certainty).

CONCLUSION

Palliative care physicians in Korea reported similar perceptions about the role and challenges inherent in prognostication compared to clinicians in Western cultures. However, they emphasize the need to predict final days to keep families with dying patients, reflecting family-centered aspects of Asian culture. They reported frustrations with inaccurate prognostication schemas and called for the development of simpler, more accurate predictors as a focus of future research.

Evaluation of frequency of Clinical Symptoms and Signs within Six Months Prior to Death in Patients with Advanced Solid Cancers

This retrospective study documented the frequency of the clinical symptoms and signs that increase in advanced cancer patients as they move toward death in order to create a sum score and correlate it with survival. Of 572 adult patients who were treated in four selected hospitals and who died in 1998 and 1999, data at six, three, and one month(s) prior to death was available for 257. The results showed that the number of symptoms and certain clinical findings accelerated toward death, increasing the sum score. Younger patients obtained higher sum scores at one month prior to death than did elderly ones (p=0.014); this suggests that elderly patients die at a point where they show less worsening in their clinical condition than do younger patients. The score was independent of cancer type or gender. The results of this analysis provide data for further development of a clinical tool to predict long-term survival in palliative care settings.

A Patient-Reported Outcome Instrument to Assess Symptom Burden and Predict Survival in Patients with Advanced Cancer: Flipping the Paradigm to Improve Timing of Palliative and End-of-Life Discussions and Reduce Unwanted Health Care Costs

BACKGROUND

Discussions regarding palliative care and end-of-life care issues are frequently delayed past the time of usefulness, resulting in unwanted medical care. We sought to develop a patient-reported outcome (PRO) instrument that allows patients to voice their symptom burdens and facilitate timing of discussions.

SUBJECTS, MATERIALS, AND METHODS

A seven-item PRO instrument (Cota Patient Assessed Symptom Score-7 item [CPASS-7]) covering physical performance status, pain, burden, and depression was administered (September 2015 through October 2016) with correlation to overall survival, correcting for time to complete survey since diagnosis.

RESULTS

A total of 1,191 patients completed CPASS-7 at a median of 560 days following the diagnosis of advanced cancer. Of these patients, 49% were concerned that they could not do the things they wanted; 35% reported decreased performance status. Financial toxicity was reported by 39% of patients, with family burdens noted in 25%. Although depression was reported by 15%, 43% reported lack of pleasure. Pain was reported by 33%. The median CPASS-7 total symptom burden score was 16 (possible 0-112). With a median follow-up of 15 months from initial survey, 46% had died. Patients with symptom burden scores <29 and ≥29 had a 6-month overall survival rate of 87% and 67%, respectively, and 12-month survival rates of 72% and 50%. A one-point score increase resulted in a 1.8% increase in expected hazard.

CONCLUSION

Patients with advanced cancer with higher levels of symptom burden, as self-reported on the CPASS-7, had inferior survival. The PRO facilitates identification of patients appropriate for reassessment of treatment goals and potentially palliative and end-of-life care in response to symptom burden concerns.

IMPLICATIONS FOR PRACTICE

A seven-item patient-reported outcome (PRO) instrument was administered to 1,191 patients with advanced cancers. Patients self-reporting higher levels of physical and psychological symptom burden had inferior overall survival rates. High individual item symptom PRO responses should serve as a useful trigger to initiate supportive interventions, but when scores indicate global problems, discussions regarding end-of-life care might be appropriate.

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).

Decline of Physical Activity in Terminally Ill Patients Could Be Useful for Predicting Short-Term Survival

BACKGROUND

Although it is recommended that all terminally ill patients receive advance care planning (ACP), this is occasionally challenging because of the difficulty in predicting survival. There are some indexes for predicting survival, but few are accurate, especially at the terminal stages of illness.

METHODS

Twenty-two patients at the terminal stages of cancer were retrospectively analyzed. We assessed their physical activity and condition using activities of daily living (ADL) scores for 1 month before the death. The ADL scores included 7 items: walking, bathing, grooming, dressing, eating, transferring, and toileting.

RESULTS

Survival time after the first decline of physical activity was calculated (median: 13 days, 95% confidence interval [95% CI]: 5.6-20.4 days). Survival time after the second (median: 5 days, 95% CI: 0-10.9 days), third (median: 5 days, 95% CI: 0-13.4 days), and fourth (median time: 1 day, 95% CI: not applicable due to small size) decline of physical activity was also calculated.

CONCLUSION

Change in physical activity seems helpful for estimating survival time, especially at the end of life, and this index could be useful for coordinating final ACP.

Integration and activity of hospital-based palliative care consultation teams: the INSIGHT multicentric cohort study

BACKGROUND

Hospital-based Palliative Care Consultation Teams (PCCTs) have a consulting role to specialist services at their request. Referral of patients is often late. Early palliative care in oncology has shown its effectiveness in improving quality of life, thereby questioning the "on request" model of PCCTs. Whether this evidence changed practice is unknown. This multicentre prospective cohort study aims to describe the activity and integration of PCCTs at the patient level.

METHODS

For consecutive patients newly referred to participating PCCTs, the team collected the following data: circumstances of first referral, problems identified, number of interventions, patient's survival after first evaluation and place of death.

RESULTS

Seventeen PCCTs based in university hospitals in Paris area, recruited 744 newly referred adult patients, aged 72 ± 15 years, 52% males, and 504(68%) with cancer as primary diagnosis. After 6 months, 548(74%) had died. At first evaluation, 12% patients were outpatients, 88% were inpatients. Symptoms represented the main reasons for referral and problems identified; 79% of patients had altered performance status; 24% encountered the PCCT only once. Median survival (1st-3rd quartile) after first evaluation by the PCCT was 22 (5-82) days for overall patients, and respectively 31 (8-107) days and 9 (3-34) days for cancer versus noncancer patients (p < 0.0001). Place of death was acute care hospital for 51.7% patients, and home or Palliative Care Unit for 35%. Patients referred earlier died more often in PCU.

CONCLUSION

The study provides original data showing a still late referral to the PCCTs in France. Cancer patients represent their predominant activity. The integrated palliative care model seems to emerge besides the "on request" model which originally characterised their missions.

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.

Continuous Deep Sedation: A Proposal for Performing More Rigorous Empirical Research

Continuous deep sedation until death (CDS) is a type of palliative sedation therapy, and it has recently become a focus of intense debate. Marked inconsistencies in intervention procedures (i.e., what is CDS?) and unstandardized descriptions of patient backgrounds lead to difficulty in comparing the results in the literature. The primary aim of this article was to propose a conceptual framework to perform empirical studies on CDS. We propose the definition of CDS using the intervention protocol. As there are two types of CDS proposed in world-wide literature, we recommend to prepare two types of intervention protocol for CDS: "continuous deep sedation as a result of proportional sedation" (gradual CDS) and "continuous deep sedation to rapidly induce unconsciousness" (rapid CDS). In addition, we recommend that researchers characterize study patients' general condition using a validated prognostic tool, Prognosis in Palliative Care Study predictor model-A. Using this conceptual framework, we can compare the outcomes following the same exposures among homogenous patients throughout the world. This article proposes a provisional definition of two types of CDS. Defining CDS using the intervention protocol and describing patient backgrounds using validated prognostic tools enable comparisons and interpretations of empirical research about CDS. More empirical studies are urgently needed.

Post-Discharge Survival Outcomes of Patients with Advanced Cancer from the University of Texas MD Anderson Cancer Center Investigational Cancer Therapeutics (Phase I Trials) Inpatient Unit

BACKGROUND

Patients with advanced cancer who progress on standard therapy are potential candidates for phase I clinical trials. Due to their aggressive disease and complex comorbid conditions, these patients often need inpatient admission. This study assessed the outcomes of such patients after they were discharged to hospice care.

PATIENTS AND METHODS

We performed a retrospective analysis of patients with solid tumor malignancies who were discharged to hospice care from the inpatient service.

RESULTS

One hundred thirty-three patients were included in the study cohort. All patients had metastatic disease and an Eastern Cooperative Oncology Group performance status ≥3. The median survival after discharge to hospice from an inpatient setting was 16 days, with a survival rate of 5% at 3 months after discharge. The median survival after the last cancer treatment was 46 days, with survival of 17% at 3 months, and 5% at 6 months. Patients with lactate dehydrogenase (LDH) >618 IU/L had a median post-discharge survival of 11 days versus 20 days for patients with LDH ≤618 IU/L.

CONCLUSIONS

Patients with metastatic cancer participating in phase I trials who have poor performance status and require inpatient admission have a very short survival after discharge to hospice. A high LDH level predicts an even shorter survival.

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

Background

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

Objectives

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

Data Sources

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

Eligibility Criteria

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

Study Appraisal and Synthesis Methods

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

Results

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

Limitations

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

Conclusion

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

Implications of Key Findings

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

Clinician prediction of survival versus the Palliative Prognostic Score: Which approach is more accurate?

BACKGROUND

Clinician prediction of survival (CPS) has low accuracy in the advanced cancer setting, raising the need for prediction models such as the palliative prognostic (PaP) score that includes a transformed CPS (PaP-CPS) and five clinical/laboratory variables (PaP-without CPS). However, it is unclear if the PaP score is more accurate than PaP-CPS, and whether PaP-CPS helps to improve the accuracy of PaP score. We compared the accuracy among PaP-CPS, PaP-without CPS and PaP-total score in patients with advanced cancer.

PATIENTS AND METHODS

In this prospective study, PaP score was documented in hospitalised patients seen by palliative care. We compared the discrimination of PaP-CPS versus PaP-total and PaP-without CPS versus PaP-total using four indices: concordance statistics, area under the receiver-operating characteristics curve (AUC), net reclassification index and integrated discrimination improvement for 30-day survival and 100-day survival.

RESULTS

A total of 216 patients were enrolled with a median survival of 109 d (95% confidence interval [CI] 71-133 d). The AUC for 30-day survival was 0.57 (95% CI 0.47-0.67) for PaP-CPS, 0.78 (95% CI 0.7-0.87) for PaP-without CPS, and 0.73 (95% CI 0.64-0.82) for PaP-total score. PaP-total was significantly more accurate than PaP-CPS according to all four indices for both 30-day and 100-day survival (P < 0.001). PaP-without CPS was significantly more accurate than PaP-total for 30-day survival (P < 0.05).

CONCLUSION

We found that PaP score was more accurate than CPS, and the addition of CPS to the prognostic model reduced its accuracy. This study highlights the limitations of clinical gestalt and the need to use objective prognostic factors and models for survival prediction.

A Patient-Reported Outcome Instrument to Facilitate Timing of End-of-Life Discussions among Patients with Advanced Cancers

BACKGROUND

Honoring the wishes of cancer patients is a responsibility of oncologists; however, end-of-life care (EOLC) discussions are frequently delayed past the point of usefulness.

OBJECTIVE

To develop a patient-reported outcome (PRO) screening tool that facilitates timing of EOLC discussions.

DESIGN

A seven-item PRO instrument covering four clinical and personhood domains [performance status, pain, burden (financial and family), and depression] was administered to patients with advanced malignancies undergoing noncurative therapy. The PRO instrument included the patient's assessment of the importance of each domain. Results were correlated with the oncologist's assessment of appropriateness of continuing aggressive therapy.

SETTING/SUBJECTS

Four hundred thirty-three patients fully completed the PRO instrument between February and March 2015 at a single outpatient cancer center.

RESULTS

There was a difference (p < 0.0001) in median scores among cohorts deemed by their oncologists appropriate to continue noncurative treatments versus patients whose physicians were contemplating or actively engaged in EOLC discussions. The scores for the four individual domains also differed among cohorts. An upper threshold score comprising 46% of patients deemed appropriate to curtail treatment (but inclusive of only 26% of patients deemed appropriate to continue) was determined, facilitating identification of patients for EOLC discussions.

CONCLUSIONS

A seven-item patient-centric PRO instrument was able to separate advanced malignancy patients into cohorts who their physicians deemed were at differing stages in their cancer journey with increasing needs for advance care planning. A study to determine if the threshold scores identified in this pilot correlate with palliative/EOL consultation frequency and patient survival is underway.

Neutrophil-Lymphocyte Ratio Predicts Survival in Terminal Cancer Patients

BACKGROUND

Neutrophil-lymphocyte count ratio (NLR) is a prognostic factor in cancer, although its prognostic significance in terminally ill cancer patients is not clear.

OBJECTIVE

We investigated the association of NLR with survival in patients with terminal cancer.

METHODS

We retrospectively investigated 205 consecutive patients with terminal cancer admitted to a palliative care unit during 2014.

RESULTS

The median value of NLR was 9.7. In univariable analysis, NLR of 10 or more was significantly associated with shorter survival and NLR further discriminated survival of each palliative prognostic index (PPI) group. In multivariable analysis, increased NLR (≥10) was associated with shorter survival (hazards ratio [HR] 1.54, p<0.005), along with poor performance status (HR 1.55, p < 0.011), high PPI score (HR 1.59, p<0.003), and hyperbilirubinemia (HR 1.84, p < 0.001).

CONCLUSION

Our results suggest that elevated NLR was an independent prognostic factor for poor survival in patients with terminal cancer.

The characteristics of patients who discontinue their dying process - an observational study at a single university hospital centre

Background

End-of-life integrated care plans are used as structuring tools for the care of the dying. A widely adopted example is the Liverpool Care Pathway for the Dying Patient (LCP). Recently, several concerns were raised about LCP care, such as a worry that diagnosis of dying might be leading to a self-fulfilling trajectory, including hastening of death. However, data on rates of discontinuation of LCP care are lacking. In an observational study, we therefore investigated the incidence, features and trajectory of patients who were discontinued from the LCP. We hypothesised that (1) it is common to discontinue patients from the LCP, (2) quality of life does not decrease for discontinued LCP patients, and (3) discontinued patients live longer than patients who remain within LCP care.

Methods

All adult patients who were diagnosed as dying in a German university hospital specialized palliative care unit were included in 2013 and 2014. Actuarial estimation of survival prognostication tools and a number of quality of life indicators were used for data collection. Survival time was analysed using Kaplan-Meier estimates. Group differences in quality of life were tested using multivariate analysis of variance.

Results

159 patients were included in a digital version of the LCP. 15 patients (9.4 %) were discontinued later. Quality of life did not decrease for discontinued patients during LCP care (p = 0.16). LCP discontinued patients lived significantly longer than the remaining LCP subgroup (difference of means 296 hours, 95 % confidence interval 105.5 to 451.5 hours; difference of survival function estimates p < 0.0001).

Conclusions

When patients are diagnosed as dying, death is not the inevitable outcome of an end-of-life integrated care plan such as the LCP. Instead, it is common to discontinue the LCP care. Regular careful interprofessional assessments are important for identifying those patients who need to be discontinued from their end-of-life care plan. In this study, we found no evidence for harm by the LCP. We conclude that a correctly applied integrated care plan can be useful to provide good and safe care for the dying.

Trial registration

Internal Clinical Trial Register of the Medical Faculty, Heinrich Heine University Düsseldorf, No. 2015053680 (22 May 2015).

Prognostication of Survival in Patients With Advanced Cancer: Predicting the Unpredictable?

BACKGROUND

Prognosis is a key driver of clinical decision-making. However, available prognostication tools have limited accuracy and variable levels of validation.

METHODS

Principles of survival prediction and literature on clinician prediction of survival, prognostic factors, and prognostic models were reviewed, with a focus on patients with advanced cancer and a survival rate of a few months or less.

RESULTS

The 4 principles of survival prediction are (a) prognostication is a process instead of an event, (b) prognostic factors may evolve over the course of the disease, (c) prognostic accuracy for a given prognostic factor/ tool varies by the definition of accuracy, the patient population, and the time frame of prediction, and (d) the exact timing of death cannot be predicted with certainty. Clinician prediction of survival is the most commonly used approach to formulate prognosis. However, clinicians often overestimate survival rates with the temporal question. Other clinician prediction of survival approaches, such as surprise and probabilistic questions, have higher rates of accuracy. Established prognostic factors in the advanced cancer setting include decreased performance status, delirium, dysphagia, cancer anorexia-cachexia, dyspnea, inflammation, and malnutrition. Novel prognostic factors, such as phase angle, may improve rates of accuracy. Many prognostic models are available, including the Palliative Prognostic Score, the Palliative Prognostic Index, and the Glasgow Prognostic Score.

CONCLUSIONS

Despite the uncertainty in survival prediction, existing prognostic tools can facilitate clinical decision-making by providing approximated time frames (months, weeks, or days). Future research should focus on clarifying and comparing the rates of accuracy for existing prognostic tools, identifying and validating novel prognostic factors, and linking prognostication to decision-making.

Multidisciplinary Prognostication Using the Palliative Prognostic Score in an Australian Cancer Center

CONTEXT

Accurate prognostication is important in oncology and palliative care. A multidisciplinary approach to prognostication provides a novel approach, but its accuracy and application is poorly researched. In this study, we describe and analyze our experience of multidisciplinary prognostication in palliative care patients with cancer.

OBJECTIVES

To assess our accuracy of prognostication using multidisciplinary team prediction of survival (MTPS) alone and within the Palliative Prognostic (PaP) Score.

METHODS

This retrospective study included all new patients referred to a palliative care consultation service in a tertiary cancer center between January 2010 and December 2011. Initial assessment data for 421 inpatients and 223 outpatients were analyzed according to inpatient and outpatient groups to evaluate the accuracy of prognostication using MTPS alone and within the PaP score (MTPS-PaP) and their correlation with overall survival.

RESULTS

Inpatients with MTPS-PaP group A, B, and C had a median survival of 10.9, 3.4, and 0.7 weeks, respectively, and a 30-day survival probability of 81%, 40%, and 10%, respectively. Outpatients with MTPS-PaP group A and B had a median survival of 17.3 and 5.1 weeks, respectively, and a 30-day survival probability of 94% and 50%, respectively. MTPS overestimated survival by a factor of 1.5 for inpatients and 1.2 for outpatients. The MTPS-PaP score correlated better than MTPS alone with overall survival.

CONCLUSION

This study suggests that a multidisciplinary team approach to prognostication within routine clinical practice is possible and may substitute for single clinician prediction of survival within the PaP score without detracting from its accuracy. Multidisciplinary team prognostication can assist treating teams to recognize and articulate prognosis, facilitate treatment decisions, and plan end-of-life care appropriately. PaP was less useful in the outpatient setting, given the longer survival interval of the outpatient palliative care patient group.