Accuracy of Oncologists' Life-Expectancy Estimates Recalled by Their Advanced Cancer Patients: Correlates and Outcomes

Outcomes of prognostication in people living with advanced cancer: A qualitative study to inform a Core Outcome Set

BACKGROUND

Studies of prognostication in advanced cancer use a wide range of outcomes and outcome measures, making it difficult to compare these studies and their findings. Core Outcome Sets facilitate comparability and standardisation between studies and would benefit future prognostic research. This qualitative study, the second step in a wider study developing such a Core Outcome Set, aimed to explore the perceptions and experiences of patients with advanced cancer, informal caregivers, and clinicians regarding the potential outcomes to assess the impact of prognostication.

METHODS

We conducted semi-structured interviews with patients living with advanced cancer (n = 8), informal caregivers (n = 10), and clinicians (n = 10) recruited from palliative care services across three sites in London, United Kingdom. Interviews were conducted in-person, via telephone, or video conferencing, and were audio-recorded. Data were analysed using framework analysis. Findings were compared with outcomes identified in a previously published systematic review.

RESULTS

We identified 33 outcomes, 16 of which were not previously reported in the literature. We grouped these outcomes into 10 domains, nine from the COMET taxonomy, plus a tenth domain (spiritual/religious/existential functioning/wellbeing) which we added further to the previous systematic review. These findings highlighted discrepancies between the priorities of existing research and those of stakeholders. Novel outcomes highlight the more personal and emotional impacts of prognostication, whilst other outcomes confirm the relevance of survival length, depression, anxiety, pain, hope dynamics, emotional distress, and the quality of patient-clinician relationships for assessing the impact of prognostication.

CONCLUSIONS

This study offers valuable insights into outcomes which matter to key stakeholders, particularly patients and informal caregivers, highlights discrepancies between their priorities and those identified in previous studies, and underscores the need for a patient-centred approach in research and clinical practice in prognostication in advanced cancer. This work will contribute to developing a Core Outcome Set for assessing the impact of prognostication in advanced cancer.

How accurate is clinical prognostication by oncologists during routine practice in a general hospital and can it be improved by a specific prognosis training programme: a prospective interventional study

OBJECTIVES

Oncologists need competence in clinical prognostication to deliver appropriate care to patients with cancer. Most studies on prognostication have been restricted to patients in palliative care settings. This paper investigates (1) the prognostic accuracy of physicians regarding a broad cohort of patients with cancer with a median life expectancy of >2 years and (2) whether a prognosis training can improve prognostication.

DESIGN

Prospective single-centre study comprising 3 phases, each lasting 1 month.

SETTING

Large teaching hospital, department of oncology and haematology, Germany.

PARTICIPANTS

18 physicians with a professional experience from entry level to 34 years. 736 patients with oncological and malignant haematological diseases.

INTERVENTIONS

Baseline prognostication abilities were recorded during an 'untrained' phase 1. As an intervention, a specific prognosis-training programme was implemented prior to phases 2 and 3. In phase 3, physicians had to provide additional estimates with the inclusion of electronic prognostic tools.

OUTCOME MEASURES

Prognostic estimates (PE) were collected using 'standard' surprise question (SQ), 'probabilistic' SQ (both for short-term prognostication up to 6 months) and clinician prediction of survival (CPS) (for long-term prognostication). Estimated prognoses were compared with observed survival. Phase 1 was compared with phases 2 and 3.

RESULTS

We included 2427 PE for SQ, 1506 for CPS and 800 for probabilistic SQ. Median OS was 2.5 years. SQ accuracy improved significantly (p<0.001) from 72.6% in phase 1 to 84.3% in phase 3. Probabilistic SQ in phase 3 showed 83.1% accuracy. CPS accuracy was 25.9% and could not be significantly improved. (Electronic) prognostic tools-used alone-performed significantly worse (p<0.0005) than physicians and-used by the clinicians-did not improve their performance.

CONCLUSION

A specific prognosis-training programme could improve short-term and intermediate-term prognostication. Improvement of long-term prognostication was not possible. Inexperienced residents as well as experienced oncologists benefited from training.

Comparing Clinician Estimates versus a Statistical Tool for Predicting Risk of Death within 45 Days of Admission for Cancer Patients

OBJECTIVES

 While clinical practice guidelines recommend that oncologists discuss goals of care with patients who have advanced cancer, it is estimated that less than 20% of individuals admitted to the hospital with high-risk cancers have end-of-life discussions with their providers. While there has been interest in developing models for mortality prediction to trigger such discussions, few studies have compared how such models compare with clinical judgment to determine a patient's mortality risk.

METHODS

 This study is a prospective analysis of 1,069 solid tumor medical oncology hospital admissions (n = 911 unique patients) from February 7 to June 7, 2022, at Memorial Sloan Kettering Cancer Center. Electronic surveys were sent to hospitalists, advanced practice providers, and medical oncologists the first afternoon following a hospital admission and they were asked to estimate the probability that the patient would die within 45 days. Provider estimates of mortality were compared with those from a predictive model developed using a supervised machine learning methodology, and incorporated routine laboratory, demographic, biometric, and admission data. Area under the receiver operating characteristic curve (AUC), calibration and decision curves were compared between clinician estimates and the model predictions.

RESULTS

 Within 45 days following hospital admission, 229 (25%) of 911 patients died. The model performed better than the clinician estimates (AUC 0.834 vs. 0.753, p < 0.0001). Integrating clinician predictions with the model's estimates further increased the AUC to 0.853 (p < 0.0001). Clinicians overestimated risk whereas the model was extremely well-calibrated. The model demonstrated net benefit over a wide range of threshold probabilities.

CONCLUSION

 The inpatient prognosis at admission model is a robust tool to assist clinical providers in evaluating mortality risk, and it has recently been implemented in the electronic medical record at our institution to improve end-of-life care planning for hospitalized cancer patients.

Human Connection: Oncologist Characteristics and Behaviors Associated With Therapeutic Bonding With Latino Patients With Advanced Cancer

PURPOSE

Therapeutic alliances (TAs) between oncologists and patients are bonds characterized by mutual caring, trust, and respect. We here relate oncologist characteristics and behaviors to TA among Latino and non-Latino patients with advanced cancer.

METHODS

Participants included non-Latino oncologists (n = 41) and their Latino (n = 67) and non-Latino White (n = 90) patients with advanced cancer who participated in Coping with Cancer III, a multisite, US-based prospective cohort study of Latino/non-Latino disparities in end-of-life cancer care, conducted 2015-2019. Oncologist characteristics included age, sex, race, institution type, Spanish language proficiency, familismo practice style (emphasis on family) and clinical etiquette behaviors. Patient-reported TA was assessed using the average score of six items from The Human Connection scale. Hierarchical linear modeling (HLM) estimated effects of oncologist characteristics on TA.

RESULTS

Of 157 patients, a majority were female (n = 92, 58.6%) and age younger than 65 years (n = 95, 60.5%). Most oncologists were male (n = 24, 58.5%), non-Latino White (n = 25, 61%), and age 40 years and older (n = 25, 61%). An adjusted HLM in the full sample showed that Latino patient ethnicity was associated with significantly lower TA (β = -.25; P < .001). In an adjusted stratified HLM for TA, among Latino patients, oncologist familismo practice style (β = .19; P = .012), preference using first names (β = .25; P = .023), and greater Spanish fluency (β = .11; P < .001) were positively associated with TA. In contrast, familismo practice style had no impact on TA for non-Latino White patients.

CONCLUSION

Latino patients with advanced cancer had worse TAs with their oncologists versus non-Latino patients. Modifiable oncologist behaviors may be targeted in an intervention designed to improve the patient-physician relationship between oncologists and their Latino patients with advanced cancer.

What outcomes do studies use to measure the impact of prognostication on people with advanced cancer? Findings from a systematic review of quantitative and qualitative studies

BACKGROUND

Studies evaluating the impact of prognostication in advanced cancer patients vary in the outcomes they measure, and there is a lack of consensus about which outcomes are most important.

AIM

To identify outcomes previously reported in prognostic research with people with advanced cancer, as a first step towards constructing a core outcome set for prognostic impact studies.

DESIGN

A systematic review was conducted and analysed in two subsets: one qualitative and one quantitative. (PROSPERO ID: CRD42022320117; 29/03/2022).

DATA SOURCES

Six databases were searched from inception to September 2022. We extracted data describing (1) outcomes used to measure the impact of prognostication and (2) patients' and informal caregivers' experiences and perceptions of prognostication in advanced cancer. We classified findings using the Core Outcome Measures in Effectiveness Trials (COMET) initiative taxonomy, along with a narrative description. We appraised retrieved studies for quality, but quality was not a basis for exclusion.

RESULTS

We identified 42 eligible studies: 32 quantitative, 6 qualitative, 4 mixed methods. We extracted 70 outcomes of prognostication in advanced cancer and organised them into 12 domains: (1) survival; (2) psychiatric outcomes; (3) general outcomes; (4) spiritual/religious/existential functioning/wellbeing, (5) emotional functioning/wellbeing; (6) cognitive functioning; (7) social functioning; (8) global quality of life; (9) delivery of care; (10) perceived health status; (11) personal circumstances; and (12) hospital/hospice use.

CONCLUSION

Outcome reporting and measurement varied markedly across the studies. A standardised approach to outcome reporting in studies of prognosis is necessary to enhance data synthesis, improve clinical practice and better align with stakeholders' priorities.

Giving information strategically and transparently: A pilot trial of the Oncolo-GIST intervention to promote patients' prognostic understanding

PURPOSE

Most patients with cancer lack the prognostic understanding necessary to make informed decisions. We tested the feasibility and acceptability of the Oncolo-GIST ("Giving Information Strategically and Transparently, GIST") intervention and explored its associations with patients' improved prognostic understanding.

METHODS

The Oncolo-GIST intervention distills prognostic discussions into easy-to-understand talking points. Patients with metastatic cancers that progressed on ≥1 line of chemotherapy and not expected to survive 12 months (n = 31) were recruited from October 2020 through November 2022. We compared patients who discussed their progressive scans with an oncologist trained in the GIST technique or not (i.e., usual care). A primary outcome was prognostic understanding (e.g., patients reporting a life-expectancy of months) assessed within a week of the scan discussion visit.

RESULTS

Oncologists (n = 4) appeared receptive to the Oncolo-GIST intervention and scored nearly perfectly on post-training tests of material mastery after a < 2-h tutorial. Post-scan discussion visit, 100% of patients who met with an Oncolo-GIST-trained clinician understood that their cancer was considered incurable (a 31% improvement from pre-visit) compared with 91% of patients meeting with usual care oncologists (an 18% improvement); 33% of patients who met with an Oncolo-GIST-trained oncologist understood that they likely had months, not years, compared to 18% in the usual care group. No statistically significant differences emerged for these changes, nor for therapeutic alliance, anxiety, or depression scores between groups.

CONCLUSION

Oncolo-GIST appears to be an easily learned approach to improve prognostic understanding that neither undermines therapeutic alliances nor increases patients' anxiety or depressive symptoms. Efficacy testing in a larger trial is warranted.

Machine learning models for 180-day mortality prediction of patients with advanced cancer using patient-reported symptom data

PURPOSE

The objective of the current study was to develop and test the performances of different ML algorithms which were trained using patient-reported symptom severity data to predict mortality within 180 days for patients with advanced cancer.

METHODS

We randomly selected 630 of 689 patients with advanced cancer at our institution who completed symptom PRO measures as part of routine care between 2009 and 2020. Using clinical, demographic, and PRO data, we trained and tested four ML algorithms: generalized regression with elastic net regularization (GLM), extreme gradient boosting (XGBoost) trees, support vector machines (SVM), and a single hidden layer neural network (NNET). We assessed the performance of algorithms individually as well as part of an unweighted voting ensemble on the hold-out testing sample. Performance was assessed using area under the receiver-operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The starting cohort of 630 patients was randomly partitioned into training (n = 504) and testing (n = 126) samples. Of the four ML models, the XGBoost algorithm demonstrated the best performance for 180-day mortality prediction in testing data (AUROC = 0.69, sensitivity = 0.68, specificity = 0.62, PPV = 0.66, NPV = 0.64). Ensemble of all algorithms performed worst (AUROC = 0.65, sensitivity = 0.65, specificity = 0.62, PPV = 0.65, NPV = 0.62). Of individual PRO symptoms, shortness of breath emerged as the variable of highest impact on the XGBoost 180-mortality prediction (1-AUROC = 0.30).

CONCLUSION

Our findings support ML models driven by patient-reported symptom severity as accurate predictors of short-term mortality in patients with advanced cancer, highlighting the opportunity to integrate these models prospectively into future studies of goal-concordant care.

Awareness of Disease Status Among Patients With Cancer: An Integrative Review

BACKGROUND

As the quality of cancer care improves, oncology patients face a rapidly increasing number of treatment options. Thus, it is vital that they are full and active partners in the treatment decision-making process. Awareness of disease status has been investigated in the literature; it has been inconsistently conceptualized and operationalized.

OBJECTIVE

The aim of this integrative review was to develop a conceptual definition and model of the awareness of disease status among patients with cancer.

METHODS

Whittemore and Knafl's integrative review methodology guided this article. We obtained data through a systematic search of 8 databases. Key terms utilized were awareness, perception, truth disclosure, diagnosis, prognosis, terminal illness, status, neoplasm, and metastasis. Dates through January 2020 were searched to capture all relevant articles. Sixty-nine articles met inclusion criteria.

RESULTS

The integrative review methodology guided the development of a conceptual definition and model. The concept of "awareness of disease status" was defined as the individual patient's understanding of being diagnosed and treated for cancer based on the multifactorial components of individual patient characteristics and contextually driven communication practices of healthcare providers. This understanding is dynamic and changes throughout the disease trajectory.

CONCLUSION

These findings will inform consistency in the literature. Such consistency may improve person-centered clinical communication, care planning practices, and, ultimately, cancer-related outcomes.

IMPLICATIONS FOR PRACTICE

With a greater understanding of the complexity of patients' awareness of disease status, nurses will be able to guide their patients to make informed decisions throughout their disease trajectory.

All-Cause Mortality Risk Prediction in Older Adults with Cancer: Practical Approaches and Limitations

PURPOSE OF REVIEW

The prediction of all-cause mortality is an important component of shared decision-making across the cancer care continuum, particularly in older adults with limited life expectancy, for whom there is an increased risk of over-diagnosis and treatment.

RECENT FINDINGS

Currently, several international societies recommend the use of all-cause mortality risk prediction tools when making decisions regarding screening and treatment in geriatric oncology. Here, we review some practical aspects of the utilization of those tools and dissect the characteristics of those most employed in geriatric oncology, highlighting both their advantages and their limitations.

How Should Cost-Informed Goals of Care Decisions Be Facilitated at Life's End?

Interventions near patients' deaths in the United States are often expensive, burdensome, and inconsistent with patients' goals and preferences. For patients and their loved ones to make informed care decisions, physicians must share adequate information about prognoses, prospective benefits and harms of specific interventions, and costs. This commentary on a case discusses strategies for sharing such information and suggests that properly designed advance care planning incentives can help improve communication and decision sharing.

Oncology nurse perceptions about life expectancy discussions: a cross-sectional study exploring what patients want to know, and why doctors don't disclose

Background: Sensitive and patient-centred discussion about life expectancy has clear benefits for patients with advanced cancer and their families. The perceptions of oncology nurses about disclosure of life expectancy, and the barriers to disclosure, have rarely been explored. Objectives/Aims/Hypotheses: To examine oncology nurses' perceptions of the: (1) proportion of patients with advanced cancer who want, receive and understand estimates of life expectancy; (2) reasons why doctors may not provide estimates of life expectancy. Design: Cross-sectional survey. Methods: Australian oncology nurses who were members of a professional society or worked at a participating metropolitan cancer centre were emailed a link to an anonymous online survey. Participants provided socio-demographic characteristics and their perceptions about the proportion of patients with advanced cancer who (a) want, (b) are provided with, (c) receive and (d) understand estimates of life expectancy, as well as the reasons estimates of life expectancy may not be provided. Results: A total of 104 nurses participated. While 51% of nurses perceived that most patients (>75%) want to be provided with an estimate of their life expectancy, 63% of nurses reported that <50% of patients were provided with an estimate. Further, 85% of nurses indicated that <50% of patients understand the estimate. The most frequent reason nurses perceived doctors did not provide an estimate of life expectancy was because the doctor didn't have an accurate idea of life expectancy (80.8%). Almost one-fifth of nurses (18.3%) thought that doctors did not provide estimates because they felt it was not their responsibility to do so. Conclusions: Strategies to ensure a patient-centred approach to life expectancy discussions with patients with advanced cancer are urgently needed. Impact statement: Oncology nurses perceive that many patients with advanced cancer are not provided with an accurate estimate of their life expectancy and few understand the information provided to them.

Pediatric Palliative Care

OBJECTIVE/METHODS

Pediatric Palliative Care (PPC) is a multidisciplinary medical subspecialty focused on the care of children with serious illnesses and terminal diagnoses. Providers impact the care of children from the perinatal stage through adolescence/young adulthood and help patients and families face diagnoses such as complex chronic disease and malignancy. This article describes these unique populations and distinct areas of current PPC research.

RESULTS

Unique aspects of PPC include a high level of prognostic uncertainty, symptom burden, pediatric, and surrogate advance care planning, hope in the face of prognostic challenges, care of children at end of life, concurrent care, staff support, sibling support, and bereavement.

CONCLUSION

PPC's evolution from an extension of hospice into a continuum of support for families and staff caring for children with serious illnesses is exemplified in both qualitative and quantitative research. The literature proves the value that PPC can provide to families, hospitals, and communities. PPC is evolving from a supportive service into a uniquely beneficial, collaborative, educational, and interdisciplinary specialty that improves outcomes for all involved.Plain Language Summary (PLS)Pediatric Palliative Care (PPC) is a service provided to all children with serious illness as a way of addressing suffering. Populations served by PPC range from those not yet born to patients preparing for adulthood. The serious illnesses they face range from chronic disease to cancer. Over the last 20 years research has explored the unique aspects of the pediatric experience of serious illness, including prognostic uncertainty, concurrent care, symptom management, advance care planning, hope, family experience of illness, care at the end of life, staff support, and bereavement.As the number of patients who would benefit from PPC services rapidly expands nationally and worldwide, PPC teams provide education and skills training for their colleagues in primary and subspecialty fields. Hospitals benefit from PPC through improved patient experience, family-centered care, and staff support. Communities are served by PPC that occurs in and out of the hospital.Research in PPC provides guidance for challenging questions in care and has resulted in an increasingly robust body of work. PPC providers have skills of advanced communication training, hope in the face of uncertainty, targeted and personalized symptom management, and a diverse understanding of quality of life. These skills help support decision-making and establish strong connections between providers and families.The field of PPC has a distinct skillset to support families who face serious illness. This article helps medical and psychosocial providers visualize how PPC is evolving from what has often been explained to families as an added layer of support into a uniquely beneficial, collaborative, and interdisciplinary service.

Development of the Oncolo-GIST ("Giving Information Strategically & Transparently") Intervention Manual for Oncologist Skills Training in Advanced Cancer Prognostic Information Communication

CONTEXT

Patient prognostic understanding is improved by oncologists' discussions of life expectancy. Most patients deem it important to discuss prognosis with their oncologists, but a minority of cancer patients within months of death report that they had such a discussion with their oncologist.

OBJECTIVES

To query stakeholders about their perspectives on the clinical approach and utility of an Oncolo-GIST manualized communication intervention, designed to enhance oncologists' ability to convey the gist of prognostic information simply, clearly, and effectively in the setting of progressing solid tumors and limited life expectancy.

METHODS

We obtained and analyzed feedback on the intervention from solid tumor oncology clinicians and bereaved family caregivers, soliciting opinions on the clinical approach taken in the videos, acceptability and likely impact of the instructions, and specific phrases recommended in the manual.

RESULTS

Twenty stakeholders (9 clinicians, 11 caregivers) participated. All agreed that oncologists should broach prognosis with patients, balancing honesty and sensitivity. Participants also advocated for oncologists to involve interprofessional team members (e.g., nurses, social workers) when serious mental health concerns arose. After the research team's discussion of the stakeholder feedback, the manual was modified to include or exclude preferred language and approaches.

CONCLUSION

The Oncolo-GIST intervention was characterized as simple and potentially effective at conveying prognoses to advanced cancer patients. Future research should determine if this approach to medical communication, which distills the essence of prognostic messages clearly and simply, is associated with improvements in patients' prognostic understanding.

Pre-treatment expectations of patients with spinal metastases: what do we know and what can we learn from other disciplines? A systematic review of qualitative studies

Background

Little is known about treatment expectations of patients with spinal metastases undergoing radiotherapy and/or surgery. Assuming that patients with spinal metastases share characteristics with patients who had spinal surgery for non-cancer related conditions and with advanced cancer patients, we performed a systematic review to summarize the literature on patient expectations regarding treatment outcomes of spinal surgery and advanced cancer care.

Methods

A comprehensive search was performed in MEDLINE, EMBASE and PsycINFO for studies between 2000 and sep-2019. Studies including adult patients (> 18 years), undergoing spinal surgery or receiving advanced cancer care, investigating patients’ pre-treatment expectations regarding treatment outcomes were included. Two independent reviewers screened titles, abstracts and full-texts, extracted data and assessed methodological quality.

Results

The search identified 7343 articles, of which 92 were selected for full-text review. For this review, 31 articles were included. Patients undergoing spinal surgery had overly optimistic expectations regarding pain and symptom relief, they underestimated the probability of functional disability, and overestimated the probability of (complete) recovery and return to work. Studies highlighted that patients feel not adequately prepared for surgery in terms of post-treatment expectations. Similarly, advanced cancer patients receiving palliative treatment often had overly optimistic expectations regarding their survival probability and cure rates.

Conclusions

Patients tend to have overly optimistic expectations regarding pain and symptom relief, recovery and prognosis following spinal surgery or advanced cancer care. Pretreatment consultation about the expected pain and symptom relief, recovery and prognosis may improve understanding of prognosis, and promote and manage expectations, which, in turn, may lead to better perceived outcomes.

Trial registration

PROSPERO registration number: CRD42020145151.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-020-07683-7.

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.

Predicting 5- and 10-Year Mortality Risk in Older Adults With Diabetes

OBJECTIVE

Several diabetes clinical practice guidelines suggest that treatment goals may be modified in older adults on the basis of comorbidities, complications, and life expectancy. The long-term benefits of treatment intensification may not outweigh short-term risks for patients with limited life expectancy. Because of the uncertainty of determining life expectancy for individual patients, we sought to develop and validate prognostic indices for mortality in older adults with diabetes.

RESEARCH DESIGN AND METHODS

We used a prevalence sample of veterans with diabetes who were aged ≥65 years on 1 January 2006 (N = 275,190). Administrative data were queried for potential predictors that included patient demographics, comorbidities, procedure codes, laboratory values and anthropomorphic measurements, medication history, and previous health service utilization. Logistic least absolute shrinkage and selection operator regressions were used to identify variables independently associated with mortality. The resulting odds ratios were then weighted to create prognostic indices of mortality over 5 and 10 years.

RESULTS

Thirty-seven predictors of mortality were identified: 4 demographic variables, prescriptions for insulin or sulfonylureas or blood pressure medications, 6 biomarkers, previous outpatient and inpatient utilization, and 22 comorbidities/procedures. The prognostic indices showed good discrimination, with C-statistics of 0.74 and 0.76 for 5- and 10-year mortality, respectively. The indices also demonstrated excellent agreement between observed outcome and predictions, with calibration slopes of 1.01 for both 5- and 10-year mortality.

CONCLUSIONS

Prognostic indices obtained from administrative data can predict 5- and 10-year mortality in older adults with diabetes. Such a tool may enable clinicians and patients to develop individualized treatment goals that balance risks and benefits of treatment intensification.

A Report of Physicians' Beliefs about Physician-Assisted Suicide: A National Study

The goal of this work is to assess the beliefs of US physicians about the national legalization of physician-assisted suicide (PAS). We sent a survey to 1000 randomly chosen physicians from around the US. Our survey indicates that 60% of physicians thought PAS should be legal, and of that 60%, 13% answered "yes" when asked if they would perform the practice if it were legal. Next, 49% of physicians agreed that most patients who seek PAS do so because of pain, and 58% agreed that the current safeguards in place for PAS, in general, are adequate to protect patients. With respect to specific safeguards, 60% disagreed with the statement that physicians who are not psychiatrists are adequately trained to screen for depression in patients seeking PAS, and 60% disagreed with the idea that physicians can predict with certainty whether a patient seeking PAS has 6 months or less to live. Finally, about one-third (30%) of physicians thought that the legalization of PAS would lead to the legalization of euthanasia, and 46% agreed that insurance companies would preferentially cover PAS over possible life-saving treatments if PAS was legalized nationally. Our survey results suggest several conclusions about physicians' beliefs about PAS. The first is that there is a discrepancy between willingness to endorse and willingness to practice PAS. Second, physicians are generally misinformed with regard to why patients seek PAS, and they are uncertain about the adequacy of safeguards. Third, physicians are still wary of the slippery slope with respect to the legalization of PAS nationwide.

Factors associated with physicians' predictions of six-month mortality in critically ill patients

Background

Physician's estimates of a patient's prognosis are an important component in shared decision-making. However, the variables influencing physician's judgments are not well understood. We aimed to determine which physician and patient factors are associated with physicians' predictions of critically ill patients' six-month mortality and the accuracy and confidence of these predictions.

Methods

Prospective cohort study evaluating physicians' predictions of six-month mortality. Using univariate and multivariable generalized estimating equations, we assessed the association between baseline physician and patient characteristics with predictions of six-month death, as well as accuracy and confidence of these predictions.

Results

Our cohort was comprised 300 patients and 47 physicians. Physicians were asked to predict if patients would be alive or dead at six months and to report their confidence in these predictions. Physicians predicted that 99 (33%) patients would die. The key factors associated with both the direction and accuracy of prediction were older age of the patient, the presence of malignancy, being in a medical ICU, and higher APACHE III scores. The factors associated with lower confidence included older physician age, being in a medical ICU and higher APACHE III score.

Conclusions

Patient level factors are associated with predictions of mortality at six months. The accuracy and confidence of the predictions are associated with both physician and patients' factors. The influence of these factors should be considered when physicians reflect on how they make predictions for critically ill patients.

Predicting Life Expectancy for Older Adults with Cancer in Clinical Practice: Implications for Shared Decision-making

PURPOSE OF REVIEW

The calculation of noncancer-specific life expectancy can guide shared decision-making and avoid over- and undertreatment in older adults with cancer. Several factors determine life expectancy, including socio-demographic background, comorbidities, physical performance, and geriatric assessment variables. We present an overview of existing tools to estimate life expectancy, as well as practical examples of how to take into account the patient's noncancer-specific life expectancy when discussing screening decisions, initiation of treatment, and end-of-life care.

RECENT FINDINGS

Life expectancy prognostication has been recently recommended by international societies as part of the initial assessment of all older adults with cancer. Additionally, online resources have been created in order to make life expectancy calculation tools accessible for clinicians. Understanding available methods to estimate life expectancy, as well as how to utilize them, is a fundamental part of geriatric oncology that should be integrated into everyday clinical practice.

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.

Advance Care Planning and End-of-Life Decision Making for Patients with Cancer

OBJECTIVE

To highlight the importance, challenges, and evolution of advance care planning for patients with cancer.

DATA SOURCES

Peer-reviewed journal articles and clinical guidelines.

CONCLUSION

Advance care planning is fundamental to support the personhood of patients with advanced cancer. Patients must be encouraged by physicians and nurses to articulate what matters and provides meaning to them as they live, cope, and receive treatment for their cancer.

IMPLICATIONS FOR NURSING PRACTICE

Nurses can facilitate advance care planning and primary palliative care, to support patients and families to make informed and value-concordant decisions regarding cancer and end-of-life treatments.

Ambulatory Advanced Cancer Patients' and Oncologists' Estimates of Life Expectancy Are Associated with Patient Psychological Characteristics But Not Chemotherapy Use

BACKGROUND

Patients with advanced cancer often face distressing decisions about chemotherapy. There are conflicting data on the relationships among perceived prognosis, psychological characteristics, and chemotherapy use, which impair the refinement of decision support interventions.

OBJECTIVE

Clarify the relationships among patient and oncologist estimates of life expectancy for 6 and 12 months, chemotherapy use, and patient psychological characteristics.

DESIGN

Secondary analysis of data from two cross-sectional studies.

SETTING/SUBJECTS

One hundred sixty-six patients with advanced stage cancer recruited from ambulatory cancer clinics.

MEASUREMENTS

All data were obtained at study enrollment. Patients completed the Adult Hope Scale, Hospital Anxiety and Depression Scale, and Life Orientation Test-Revised. Patients and their oncologists provided estimates of surviving beyond 6 and 12 months. Chemotherapy use was determined by chart review.

RESULTS

There were no significant associations between life-expectancy estimates and chemotherapy use nor patient anxiety, depression, hope, or optimism and chemotherapy use. Patients' life expectancy estimates for 12 months and oncologists' for 6 months were associated with higher patient anxiety and depression. Finally, both oncologist and patient estimates of life expectancy for 6 and 12 months were associated with increased levels of trait hope.

CONCLUSION

Advanced cancer patients who provide less optimistic estimates of life expectancy have increased anxiety and depression, but do not use chemotherapy more often. Increased patient trait hope is associated with more favorable oncologist estimates. These findings highlight the need for interventions to support both patients and oncologists as they clarify prognostic expectations and patients cope with the psychological distress of a limited life expectancy.

The interactive effect of advanced cancer patient and caregiver prognostic understanding on patients' completion of Do Not Resuscitate orders

OBJECTIVE

Advanced cancer patients' prognostic understanding is associated with completion of Do Not Resuscitate (DNR) orders, which often represent engagement in advance care planning (ACP). Given caregivers' critical roles in patient decision-making about ACP and end-of-life care, caregivers' prognostic understanding may have a large additive effect. The present study examined the association between the main and interactive effects of advanced cancer patient and caregiver prognostic understanding on DNR order completion.

METHODS

Data were analyzed from a combined dataset of 2 sequential multi-institutional, longitudinal cohort studies of patients with advanced cancer and their informal caregivers (n = 279 dyads) from 2002 to 2008 (Coping with Cancer 1) and 2010 to 2015 (Coping with Cancer 2). Patients' and caregivers' prognostic understanding regarding life-expectancy (≤ 12 months [prognostic understanding], >12 months [lack of prognostic understanding]) was assessed. DNR order completion was assessed through self-report and confirmed through cross-checking with medical records.

RESULTS

Multivariable modeling of the main and interactive effects revealed the interactive effect, but not the individual effects, of patients' and caregivers' prognostic understanding was significantly associated with higher odds of patients' DNR order completion, adjusting for potential confounds (AOR = 5.89, P = 0.04). For dyads in which both the patient and caregiver had prognostic understanding regarding life expectancy of ≤12 months, 70.7% of patients had completed DNR orders compared with 31.6% to 38.9% in which 1 or both lacked prognostic understanding.

CONCLUSIONS

Findings highlight the need for ensuring accurate patient and caregiver prognostic understanding in increasing DNR order completion, which may provide a framework for improving engagement in ACP more broadly.

Palliative care and advance care planning for pancreas and other cancers

The principles of palliative care are fundamental to support and treat the physical, mental, and psychosocial health of patients living with pancreatic cancer. In addition to its proven advantages to help manage disease-related symptoms, improve accurate illness understanding, and enhance the quality of life and survival outcomes for patients with advanced disease, the inclusion of palliative care principles (whether by a specialist or by the primary oncology team) with standard oncologic care strengthens timely and quality advance care planning (ACP). The primary objective of this review article is to underscore the significant value of palliative care integration and ACP in oncology, including but not limited to care at the end of life, with a particular focus on its relevance to patients with advanced pancreatic cancer.