Accuracy of Clinicians’ Prediction of Survival and Prognostic Factors Indicative of Survival: a Systematic Review

End-of-life discussions in residential care homes improves symptom control: a national register study

BACKGROUND

In Europe, residential care homes (RCHs) rather than hospitals are the most common care facilities for the older adult and the place where most deaths occur in this age group. There is a lack of knowledge regarding end-of-life (EOL) discussions and how they correlate with symptoms and symptom relief.

OBJECTIVE

The aim was to examine the correlation between EOL discussions and symptom occurrence, symptom relief and prescriptions or PRN drugs against symptoms for care home residents.

METHODS

All expected deaths at RCHs from 1 October 2015 to 31 December 2016 and registered in the Swedish Register of Palliative Care were included. Univariate and multivariate logistic regression were used to compare the RCH residents, or their family members, who had received documented EOL discussions with a physician (the EOL discussion group) and the non-EOL discussion group.

RESULTS

The EOL discussion group (n=17 071) had a higher prevalence of pain, nausea, anxiety, death rattles and shortness of breath reported, compared with the non-EOL discussion group (n=4164). Those with symptoms were more often completely relieved and had more often been prescribed PRN drugs against that symptom in the EOL discussion group. All differences remained significant when adjusting for age, time living in unit and cause of death.

CONCLUSION

The results indicate that EOL discussions are correlated with higher prevalence of symptoms, but also with better symptom relief and prescription of symptom drugs PRN when symptomatic. A possible explanation for this is that the EOL discussion can work as an opportunity to discuss symptoms and treatment for symptom relief.

A-qCPR risk score screening model for predicting 1-year mortality associated with hospice and palliative care in the emergency department

BACKGROUND

Evaluating the need for palliative care and predicting its mortality play important roles in the emergency department.

AIM

We developed a screening model for predicting 1-year mortality.

DESIGN

A retrospective cohort study was conducted to identify risk factors associated with 1-year mortality. Our risk scores based on these significant risk factors were then developed. Its predictive validity performance was evaluated using area under receiving operating characteristic analysis and leave-one-out cross-validation.

SETTING AND PARTICIPANTS

Patients aged 15 years or older were enrolled from June 2015 to May 2016 in the emergency department.

RESULTS

We identified five independent risk factors, each of which was assigned a number of points proportional to its estimated regression coefficient: age (0.05 points per year), qSOFA ⩾ 2 (1), Cancer (4), Eastern Cooperative Oncology Group Performance Status score ⩾ 2 (2), and Do-Not-Resuscitate status (3). The sensitivity, specificity, positive predictive value, and negative predictive value of our screening tool given the cutoff larger than 3 points were 0.99 (0.98-0.99), 0.31 (0.29-0.32), 0.26 (0.24-0.27), and 0.99 (0.98-1.00), respectively. Those with screening scores larger than 9 points corresponding to 64.0% (60.0-67.9%) of 1-year mortality were prioritized for consultation and communication. The area under the receiving operating characteristic curves for the point system was 0.84 (0.83-0.85) for the cross-validation model.

CONCLUSIONS

A-qCPR risk scores provide a good screening tool for assessing patient prognosis. Routine screening for end-of-life using this tool plays an important role in early and efficient physician-patient communications regarding hospice and palliative needs in the emergency department.

How palliative care professionals deal with predicting life expectancy at the end of life: predictors and accuracy

PURPOSE

To assess the accuracy of hospice staff in predicting survival of subjects admitted to hospice, exploring the factors considered most helpful by the hospice staff to accurately predict survival.

METHODS

Five physicians and 11 nurses were asked to predict survival at admission of 827 patients. Actual and predicted survival times were divided into ≤ 1 week, 2-3 weeks, 4-8 weeks, and ≥ 2 months and the accuracy of the estimates was calculated. The staff members were each asked to score 17 clinical variables that guided them in predicting survival and we analyzed how these variables impacted the accuracy.

RESULTS

Physicians' and nurses' accuracy of survival of the patients was 46% and 40% respectively. Survival was underestimated in 20% and 12% and overestimated in 34% and 48% of subjects. Both physicians and nurses considered metastases, comorbidities, dyspnea, disability, tumor site, neurological symptoms, and confusion very important in predicting patients' survival with nurses assigning more importance to intestinal symptoms and pain too. All these factors, with the addition of cough and/or bronchial secretions, were associated with physicians' greater accuracy. In the multivariable models, intestinal symptoms and confusion continued to be associated with greater predictive accuracy. No factors appreciably raised nurses' accuracy.

CONCLUSIONS

Some clinical symptoms rated as relevant by the hospice staff could be important for predicting survival. However, only intestinal symptoms and confusion significantly improved the accuracy of physicians' predictions, despite the high prevalence of overestimated survival.

An online international comparison of thresholds for triggering a negative response to the "Surprise Question": a study protocol

BACKGROUND

The Surprise Question (SQ) "would I be surprised if this patient were to die in the next 12 months?" has been suggested to help clinicians, and especially General Practitioners (GPs), identify people who might benefit from palliative care. The prognostic accuracy of this approach is unclear and little is known about how GPs use this tool in practice. Are GPs consistent, individually and as a group? Are there international differences in the use of the tool? Does including the alternative Surprise Question ("Would I be surprised if the patient were still alive after 12 months?") alter the response? What is the impact on the treatment plan in response to the SQ? This study aims to address these questions.

METHODS

An online study will be completed by 600 (100 per country) registered GPs. They will be asked to review 20 hypothetical patient vignettes. For each vignette they will be asked to provide a response to the following four questions: (1) the SQ [Yes/No]; (2) the alternative SQ [Yes/No]; (3) the percentage probability of dying [0% no chance - 100% certain death]; and (4) the proposed treatment plan [multiple choice]. A "surprise threshold" for each participant will be calculated by comparing the responses to the SQ with the probability estimates of death. We will use linear regression to explore any differences in thresholds between countries and other clinician-related factors, such as years of experience. We will describe the actions taken by the clinicians and explore the differences between groups. We will also investigate the relationship between the alternative SQ and the other responses. Participants will receive a certificate of completion and the option to receive feedback on their performance.

DISCUSSION

This study explores the extent to which the SQ is consistently used at an individual, group, and national level. The findings of this study will help to understand the clinical value of using the SQ in routine practice.

TRIAL REGISTRATION

Clinicaltrials.gov NCT03697213 (05/10/2018). Prospectively registered.

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.