Timely identification of patients in need of palliative care using the Double Surprise Question: A prospective study on outpatients with cancer

Integrating Palliative Care Into the Management of Genitourinary Malignancies

Palliative care (PC) plays a critical role in managing the difficulties associated with genitourinary malignancies. Its primary aim is to improve the overall health of patients, provide support to both patients and their caregivers, and help individuals to navigate the complex decisions about treatment and end-of-life care. PC takes a holistic approach to patient care, recognizing that genitourinary malignancies affect multiple aspects of a person's life. By addressing physical, emotional, social, and spiritual needs, PC aims to provide comprehensive support that is consistent with the patient's values and preferences. The goal is to optimize comfort, minimize distress, and enhance the patient's quality of life throughout the course of the illness. PC is not a one-off intervention, but an ongoing source of support. This article aims to provide a thorough overview of the critical elements involved in addressing the challenges posed by genitourinary cancers, emphasizing the importance of palliative interventions. We will highlight the multifaceted aspects of care and explore strategies to optimize the overall well-being of patients throughout the course of treatment for genitourinary malignancies.

Are specialist-provided end-of-life scenarios key to initiation of advance care planning in primary care? A mixed-methods study

OBJECTIVES

Specialist-provided end-of-life scenarios (SP-EOLS) may improve advance care planning (ACP) implementation in primary care by helping overcome barriers such as uncertain prognosis and poor interprofessional collaboration. We aimed to explore the current use and potential impact of SP-EOLS on ACP in Dutch primary care.

METHODS

We performed a mixed-methods study. From patients discussed in a hospital-based academic palliative care multidisciplinary team meeting between 2016 and 2019 and died, we collected primary care electronic medical records data on SP-EOLS, actual EOLS, and ACP initiation and applied descriptive and comparative analyses. Subsequently, we interviewed general practitioners (GPs) and thematically analyzed the transcripts.

RESULTS

In 69.7% of 66 reviewed patient files, SP-EOLS were found. In patients whose GP had received SP-EOLS, ACP conversations were more often reported (92.0 vs. 61.0%, p = 0.006). From 11 GP interviews, we identified 4 themes: (1) SP-EOLS guide GPs, patients, and relatives when dealing with an uncertain future perspective; (2) SP-EOLS provide continuity of care between primary and secondary/tertiary care; (3) SP-EOLS should be tailored to the individual patient; and (4) SP-EOLS need to be personalized and uniformly transferred to GPs.

SIGNIFICANCE OF RESULTS

SP-EOLS may facilitate ACP conversations by GPs. They have the potential to help overcome existing barriers to ACP implementation by providing guidance and supporting interprofessional collaboration. Future research should focus on improving SP-EOLS and tailor them to the needs of all end users, focusing on improving their effect on ACP conversations.

Should the Surprise Question be Used as a Prognostic Tool for People With Life-limiting Illnesses?

The surprise question screening tool ("Would I be surprised if this person died within the next 12 months?") was initially developed to identify possible palliative care needs. One controversial topic regarding the surprise question is whether it should be used as a prognostic tool (predicting survival) for patients with life-limiting illnesses. In this "Controversies in Palliative Care" article, three groups of expert clinicians independently answered this question. All experts provide an overview of current literature, practical advice, and opportunities for future research. All experts reported on the inconsistency of the prognostic capabilities of the surprise question. Two of the three expert groups felt that the surprise question should not be used as a prognostic tool due to these inconsistencies. The third expert group felt that the surprise question should be used as a prognostic tool, particularly for shorter time frames. The experts all highlighted that the original rationale for the surprise question was to trigger a further conversation about future treatment and a potential shift in the focus of the care, identifying patients who many benefit from specialist palliative care or advance care planning; however, many clinicians find this discussion a difficult one to initiate. The experts agreed that the benefit of the surprise question comes from its simplicity: a one-question tool that requires no specific information about the patient's condition. More research is needed to better support the application of this tool in routine practice, particularly in noncancer populations.

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.

External Validation and User Experiences of the ProPal-COPD Tool to Identify the Palliative Phase in COPD

Background

Difficulty predicting prognosis is a major barrier to timely palliative care provision for patients with COPD. The ProPal-COPD tool, combining six clinical indicators and the Surprise Question (SQ), aims to predict 1-year mortality as a proxy for palliative care needs. It appeared to be a promising tool for healthcare providers to identify patients with COPD who could benefit from palliative care.

Objective

To externally validate the ProPal-COPD tool and to assess user experiences.

Methods

Patients admitted with an acute exacerbation COPD were recruited across 10 hospitals. Demographics, clinical characteristics and survival status were collected. Sensitivity, specificity, positive and negative predictive values of the tool using two cut-off values were calculated. Also, predictive properties of the SQ were calculated. In monitoring meetings and interviews, healthcare providers shared their experiences with the tool. Transcripts were deductively coded using six user experience domains: Acceptability, Satisfaction, Credibility, Usability, User-reported adherence and Perceived impact.

Results

A total of 523 patients with COPD were included between May 2019 and August 2020, of whom 100 (19.1%) died within 12 months. The ProPal-COPD tool had an AUC of 0.68 and a low sensitivity (55%) and moderate specificity (74%) for predicting 1-year all-cause mortality. Using a lower cut-off value, sensitivity was higher (74%), but specificity lower (46%). Sensitivity and specificity of the SQ were 56% and 73%, respectively (AUC 0.65). However, healthcare providers generally appreciated using the tool because it increased awareness of the palliative phase and provided a shared understanding of prognosis, although they considered its outcome not always correct.

Conclusion

The accuracy of the ProPal-COPD tool to predict 1-year mortality is limited, although screening patients with its indicators increases healthcare providers' awareness of palliative care needs and encourages them to timely initiate appropriate care.

Palliative Care in Advanced Alzheimer's Disease Dementia: Evaluation of the Answers Given by Caregivers and Physicians to the Accuracy of Surprise Question, as a Prognostic Tool

Introduction: Alzheimer's disease (AD) dementia is the sixth leading cause of death in the United States. The surprise question (SQ) "Would you be surprised if this patient were to die within the next 12 months?" was used to identify death-risk patients, who could benefit from palliative care. Objective: To examine the prognostic accuracy of the SQ by physicians and caregivers in outpatients with AD dementia. Methods: This is a longitudinal and prospective study involving 101 patients along 1 year, applying the SAS 9.2 software and adopting a .05 P-value to assess the variables that influenced answers to the accuracy of SQ using the chi-square test. Results: 27 patients (26.7%) died during the follow-up. When caregivers answered the SQ, it presented a 51.8% sensitivity (CI 31.9 - 71.3), a 66.7% negative predictive value (20.7 - 63.6), a 56.2% specificity (CI 29.8 - 80.2), and a 40.9% positive predictive value of (CI 43.0 - 85.4) with a 53.4% accuracy (CI 38.5 - 68.4). When physicians answered, the SQ had an 88.8% sensitivity (CI 70.8 - 97.6), a 40% negative predictive value (CI 5.2 - 85.3), a 12.5% specificity (CI 1.5 - 38.3), a 63.1% positive predictive value (CI 45.9 - 78.1) with a 60.4% accuracy (CI 45.8 - 75). Conclusion: SQ remains a good tool with high sensitivity for the identification of patients with advanced AD dementia when presented to the attending physician for planning palliative advanced care with accuracy of 60.4% and caregivers' accuracy of 53.4%.

The utility of the surprise question: A useful tool for identifying patients nearing the last phase of life? A systematic review and meta-analysis

BACKGROUND

The surprise question is widely used to identify patients nearing the last phase of life. Potential differences in accuracy between timeframe, patient subgroups and type of healthcare professionals answering the surprise question have been suggested. Recent studies might give new insights.

AIM

To determine the accuracy of the surprise question in predicting death, differentiating by timeframe, patient subgroup and by type of healthcare professional.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Electronic databases PubMed, Embase, Cochrane Library, Scopus, Web of Science and CINAHL were searched from inception till 22nd January 2021. Studies were eligible if they used the surprise question prospectively and assessed mortality. Sensitivity, specificity, negative predictive value, positive predictive value and c-statistic were calculated.

RESULTS

Fifty-nine studies met the inclusion criteria, including 88.268 assessments. The meta-analysis resulted in an estimated sensitivity of 71.4% (95% CI [66.3-76.4]) and specificity of 74.0% (95% CI [69.3-78.6]). The negative predictive value varied from 98.0% (95% CI [97.7-98.3]) to 88.6% (95% CI [87.1-90.0]) with a mortality rate of 5% and 25% respectively. The positive predictive value varied from 12.6% (95% CI [11.0-14.2]) with a mortality rate of 5% to 47.8% (95% CI [44.2-51.3]) with a mortality rate of 25%. Seven studies provided detailed information on different healthcare professionals answering the surprise question.

CONCLUSION

We found overall reasonable test characteristics for the surprise question. Additionally, this study showed notable differences in performance within patient subgroups. However, we did not find an indication of notable differences between timeframe and healthcare professionals.