Perspectives, Preferences, Care Practices, and Outcomes Among Older and Middle-Aged Patients With Late-Stage Cancer

Trends in use of intensive care during hospitalizations at the end-of-life among older adults with advanced cancer

BACKGROUND

High-intensity end-of-life (EOL) care, marked by admission to intensive care units (ICUs) or in-hospital death, can be costly and burdensome. Recent trends in use of ICUs, life-sustaining treatments (LSTs), and noninvasive ventilation (NIV) during EOL hospitalizations among older adults with advanced cancer and patterns of in-hospital death are unknown.

METHODS

We used SEER-Medicare data (2003-2017) to identify beneficiaries with advanced solid cancer (summary stage 7) who died within 3 years of diagnosis. We identified EOL hospitalizations (within 30 days of death), classifying them by increasing intensity of care into: (1) without ICU; (2) with ICU but without LST (invasive mechanical ventilation, tracheostomy, gastrostomy, acute dialysis) or NIV; (3) with ICU and NIV but without LST; and (4) with ICU and LST use. We constructed a multinomial regression model to evaluate trends in risk-adjusted hospitalization, overall and across hospitalization categories, adjusting for sociodemographics, cancer characteristics, comorbidities, and frailty. We evaluated trends in in-hospital death across categories.

RESULTS

Of 226,263 Medicare beneficiaries with advanced cancer, 138,305 (61.1%) were hospitalized at EOL [Age, Mean (SD):77.9(7.1) years; 45.5% female]. Overall, EOL hospitalizations remained high throughout, from 78.1% (95% CI: 77.4, 78.7) in 2004 to 75.5% (95% CI: 74.5, 76.2) in 2017. Hospitalizations without ICU use decreased from 49.3% (95% CI: 48.5, 50.2) to 35.0% (95% CI: 34.2, 35.9) while hospitalizations with more intensive care increased, from 23.7% (95% CI: 23.0, 24.4) to 28.7% (95% CI: 27.9, 29.5) for ICU without LST or NIV, 0.8% (95% CI: 0.6, 0.9) to 3.8% (95% CI: 3.4, 4.1) for ICU with NIV but without LST, and 4.3% (95% CI: 4.0, 4.7) to 8.0% (95% CI: 7.5, 8.5) for ICU with LST use. Among those who experienced in-hospital death, the proportion receiving ICU care increased from 46.5% to 65.0%.

CONCLUSIONS

Among older adults with advanced cancer, EOL hospitalization rates remained stable from 2004-2017. However, intensity of care during EOL hospitalizations increased as evidenced by increasing use of ICUs, LSTs, and NIV.

Spending Analysis of Machine Learning-Based Communication Nudges in Oncology

BACKGROUND

Serious illness conversations (SICs) in the outpatient setting may improve mood and quality of life among patients with cancer and decrease aggressive end-of-life care. Interventions informed by behavioral economics may increase rates of SICs between oncology clinicians and patients, but the impact of these interventions on end-of-life spending is unknown.

METHODS

This study is a secondary analysis of a stepped-wedge cluster randomized, controlled trial that involved nine medical oncology practices and their high-risk patients at a large academic institution between June 2019 and April 2020. The study included 1187 patients who were identified by a machine-learning algorithm as high risk of 180-day mortality and who died by December 2020. The patients were randomly assigned to standard of care (controls) or to a behavioral intervention designed to increase clinician-initiated SICs. We abstracted spending - defined as inflation-adjusted costs for acute care (inpatient plus emergency room), office/outpatient care, intravenous systemic therapy, other therapy (e.g., radiation), long-term care, and hospice - from the institution's accounting system, and we captured spending at inpatient, outpatient, and pharmacy settings. To evaluate intervention impacts on spending, we used a two-part model, first using logistic regression to model zero versus nonzero spending and second using generalized linear mixed models with gamma distribution and log-link function to model daily mean spending in the last 180days of life. Models were adjusted for clinic and wedge fixed effects, and they were clustered at the oncologist level. For all patients with at least one SIC within 6 months of death, we also calculated their mean daily spending before and after SIC.

RESULTS

Median age at death was 68years (interquartile range, 15.5), 317 patients (27%) were Black or of ethnicities other than white, and 448 patients (38%) had an SIC. The intervention was associated with lower unadjusted mean daily spending in the last 6 months of life for the intervention group versus controls ($377.96 vs. $449.92; adjusted mean difference, -$75.33; 95% confidence interval, -$136.42 to -$14.23; P=0.02), translating to $13,747 total adjusted savings per decedent and $13 million in cumulative savings across all decedents in the intervention group. Compared with controls, patients in the intervention group incurred lower mean daily spending for systemic therapy (adjusted difference, -$44.59; P=0.001), office/outpatient care (-$9.62; P=0.001), and other therapy (-$8.65; P=0.04). The intervention was not associated with differences in end-of-life spending for acute care, long-term care, or hospice. Results were consistent for spending in the last 1 and 3 months of life and after adjusting for age, race, and ethnicity. For patients with SICs, mean daily spending decreased by $37.92 following the first SIC ($329.87 vs. $291.95).

CONCLUSIONS

A machine learning-based, behaviorally informed intervention to prompt SICs led to end-of-life savings among patients with cancer, driven by decreased systemic therapy and outpatient spending. (Funded by the Penn Center for Precision Medicine and the National Institutes of Health; ClinicalTrials.gov number, NCT03984773.).

Regional differences in the effects of healthy aging on depressive symptoms: a Korean longitudinal study of aging (2006-2020)

Background

Depression is a widely prevalent, often recurrent condition. To analyze the regional differences in depressive symptoms over time, we investigated urban-rural differences in change in depression over time in South Korea and the association between healthy aging and depressive symptoms among middle-aged and older adults.

Methods

Data collected in the Korean Longitudinal Study of Aging, from 2006 to 2020, of adult participants aged ≥45 years without depressive symptoms were analyzed. Healthy aging was defined under five principal components: absence of chronic disease, good physical function, normal cognitive function, active social engagement, and good psychological adaptation. Depressive symptoms were measured using the short version of the Center for Epidemiologic Studies Depression Scale. Using the Andersen-Gill model for recurrent time-to-event, we examined the effect of healthy aging on depressive symptoms, with a subgroup analysis based on the residential area.

Results

Of the 7,708 participants, 78.2% lived in urban areas and 39.4% achieved healthy aging. In 2008, rural residents had a higher incidence of depressive symptoms (rural 11.8%; urban 8.9%); however, after 2016, the depressive symptoms of urban residents gradually increased (rural 6.4%; urban 12.1%). Unhealthy aging (adjusted hazard ratio = 3.04, 95% confidence interval: 2.72-3.39) and urban residence (adjusted hazard ratio = 1.15, 95% confidence interval: 1.06-1.24) were risk factors for depressive symptoms. The subgroup analysis revealed that individuals who did not achieve healthy aging had an increased risk of depressive symptoms, regardless of their residential area (hazard ratio [95% confidence interval]: urban, 3.13 [2.75-3.55]; rural 2.59 [2.05-3.28]).

Conclusion

As urbanization accelerates, urban residents have a higher risk of depressive symptoms than rural residents. Healthy aging is an essential factor in reducing depressive symptoms. To achieve healthy aging, appropriate interventions and policies that target the middle-aged adults and gradually extend to older adults are needed, considering individual and regional factors.

Prioritizing Outcome Measures for Value-Based Healthcare: Physicians' Perspectives in Saudi Arabia

OBJECTIVES

To inform the stepwise transformation to value-based healthcare in Saudi Arabia, we assess physicians' priorities for measuring general patient outcomes. This is done as an initial step toward the implementation of disease-specific outcome sets.

METHODS

A cross-sectional, electronic self-administered questionnaire-based study among physicians in 6 hospitals in Saudi Arabia was conducted between March 2022 and May 2022. Purposive sampling was used to select hospitals and physicians. The questionnaire included 30 health outcomes taken from about 60 disease-specific outcome sets. These were classified into 6 domains per the Outcome Measures Hierarchy Framework of Michael Porter. The physicians were asked to prioritize outcomes in each domain by their order of importance. The Relative Importance Index (RII) and multivariate binary logistic regression were used to analyze the priorities and to relate them to physicians' characteristics.

RESULTS

A total of 204 physicians completed the questionnaire accounting for 40% response rate. The top priority outcomes per domain were overall survival (RII 89.4%); quality of life (RII 92.4%); time to treatment (RII 90.8%); incidence of adverse effects (RII 72.9%); need for retreatment (RII 80.5%); and incidence of hospital-acquired infections (RII 89.3%). Regression analysis revealed that physician seniority is a characteristic associated with physicians' perceptions of the importance of measuring health outcomes (highest odds ratio 2.693; 95% CI 1.501-4.833; P = .001).

CONCLUSION

Establishing a general set of the most important outcomes that applies to all patients, including survival and mortality, quality of life, adverse events, and complications, need to be considered in the early stages of hospitals' transformation to value-based healthcare.

Associations of prognostic-awareness-transition patterns with end-of-life care in cancer patients' last month

PURPOSE

Cancer patients heterogeneously develop prognostic awareness, and end-of-life cancer care has become increasingly aggressive to the detriment of patients and healthcare sustainability. We aimed to explore the never-before-examined associations of prognostic-awareness-transition patterns with end-of-life care.

METHODS

Prognostic awareness was categorized into four states: (1) unknown and not wanting to know; (2) unknown but wanting to know; (3) inaccurate awareness; and (4) accurate awareness. We examined associations of our previously identified three prognostic-awareness-transition patterns during 334 cancer patients' last 6 months (maintaining accurate prognostic awareness, gaining accurate prognostic awareness, and maintaining inaccurate/unknown prognostic awareness) and end-of-life care (cardiopulmonary resuscitation, intensive care unit care, mechanical ventilation, chemotherapy/immunotherapy, and hospice care) in cancer patients' last month by multivariate logistic regressions.

RESULTS

Cancer patients in the maintaining-accurate-prognostic-awareness and gaining-accurate-prognostic-awareness groups had significantly lower odds of cardiopulmonary resuscitation (adjusted odds ratio [95% confidence interval]: 0.22 [0.06-0.78]; and 0.10 [0.01-0.97], respectively) but higher odds of hospice care (3.44 [1.64-7.24]; and 3.28 [1.32-8.13], respectively) in the last month than those in the maintaining inaccurate/unknown prognostic awareness. The maintaining-accurate-prognostic-awareness group had marginally lower odds of chemotherapy or immunotherapy received than the gaining-accurate-prognostic-awareness group (0.58 [0.31-1.10], p = .096]). No differences in intensive care unit care and mechanical ventilation among cancer patients in different prognostic-awareness-transition patterns were observed.

CONCLUSION

End-of-life care received in cancer patients' last month was associated with the three distinct prognostic-awareness-transition patterns. Cancer patients' accurate prognostic awareness should be facilitated earlier to reduce their risk of receiving aggressive end-of-life care, especially for avoiding chemotherapy/immunotherapy close to death.

TRIAL REGISTRATION

ClinicalTrials.gov:NCT01912846.

Longitudinal patient-reported outcomes and survival among early-stage non-small cell lung cancer patients receiving stereotactic body radiotherapy

BACKGROUND AND PURPOSE

The study objective was to determine whether longitudinal changes in patient-reported outcomes (PROs) were associated with survival among early-stage, non-small cell lung cancer (NSCLC) patients undergoing stereotactic body radiation therapy (SBRT).

MATERIALS AND METHODS

Data were obtained from January 2015 through March 2020. We ran a joint probability model to assess the relationship between time-to-death, and longitudinal PRO measurements. PROs were measured through the Edmonton Symptom Assessment Scale (ESAS). We controlled for other covariates likely to affect symptom burden and survival including stage, tumor diameter, comorbidities, gender, race/ethnicity, relationship status, age, and smoking status.

RESULTS

The sample included 510 early-stage NSCLC patients undergoing SBRT. The median age was 73.8 (range: 46.3-94.6). The survival component of the joint model demonstrates that longitudinal changes in ESAS scores are significantly associated with worse survival (HR: 1.04; 95% CI: 1.02-1.05). This finding suggests a one-unit increase in ESAS score increased probability of death by 4%. Other factors significantly associated with worse survival included older age (HR: 1.04; 95% CI: 1.03-1.05), larger tumor diameter (HR: 1.21; 95% CI: 1.01-1.46), male gender (HR: 1.87; 95% CI: 1.36-2.57), and current smoking status (HR: 2.39; 95% CI: 1.25-4.56).

CONCLUSION

PROs are increasingly being collected as a part of routine care delivery to improve symptom management. Healthcare systems can integrate these data with other real-world data to predict patient outcomes, such as survival. Capturing longitudinal PROs-in addition to PROs at diagnosis-may add prognostic value for estimating survival among early-stage NSCLC patients undergoing SBRT.

[Re-visiting the Pronopall score ten years later: A multicenter retrospective study]

INTRODUCTION

The Pronopall score, which distinguishes 3 prognostic groups in patients with advanced cancer, was initially proposed in 2008 and validated in a study published in 2018 but including patients between 2009 and 2010. Since the last decade, cancer management and therapeutic options have progressed. The objective of this study was to confirm the value of this score in patients with digestive and thoracic cancer.

METHODS

From July 2019 to November 2020, this retrospective multi-center study included patients with digestive or thoracic cancers who fulfilled the same inclusion criteria as those used in the initial study, and in whom the Pronopall score could be calculated using its four variables (albumin serum level, LDH level, ECOG score, number of metastatic sites). Survival curves were analyzed using the Kaplan-Meier method.

RESULTS

One hundred patients were included. According to the Pronopall score, patients were separated into group A (score 8-10, 7 patients), group B (score 4-7, 41 patients) and group C (score 0-3, 52 patients). Median overall survival was 73 days, CI [17-129], 228 days, CI [128-328] and 575 days, CI [432-718] for groups A, B and C, respectively. Survival at 2 months was 28 % for population A, 61 % for population B, and 94 % for population C.

CONCLUSION

This study confirms that the Pronopall score still allows clinically relevant discrimination of patients, score C being associated with a good prognosis compared to scores A and B.

Chemotherapy After Diagnosis of Malignant Bowel Obstruction is Associated with Superior Survival for Medicare Patients with Advanced Malignancy

Background

Although malignant bowel obstruction (MBO) often is a terminal event, systemic therapies are advocated for select patients to extend survival. This study aimed to evaluate factors associated with receipt of chemotherapy after MBO and to determine whether chemotherapy after MBO is associated with survival.

Methods

This retrospective cohort study investigated patients 65 years of age or older with metastatic gastrointestinal, gynecologic, or genitourinary cancers who were hospitalized with MBO from 2008 to 2012 using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database. Fine and Gray models were used to identify factors associated with receipt of chemotherapy accounting for the competing risk of death. Cox models identified factors associated with overall survival.

Results

Of the 2983 MBO patients, 39% (n = 1169) were treated with chemotherapy after MBO. No differences in receipt of chemotherapy between the surgical and medical patients were found in the univariable analysis (subdistribution hazard ratio [SHR], 0.96; 95% confidence interval [CI], 0.86–1.07; p = 0.47) or multivariable analysis (SHR, 1.12; 95% CI, 1.00–1.26; p = 0.06). Older age, African American race, medical comorbidities, non-colorectal and non-ovarian cancer diagnoses, sepsis, ascites, and intensive care unit stays were inversely associated with receipt of chemotherapy after MBO (p < 0.05). Chemotherapy with surgery was associated with longer survival than surgery (adjusted hazard ratio [aHR], 2.97; 95% CI, 2.65–3.34; p < 0.01) or medical management without chemotherapy (aHR, 4.56; 95% CI, 4.04–5.14; p < 0.01). Subgroup analyses of biologically diverse cancers (colorectal, pancreatic, and ovarian) showed similar results, with greater survival related to chemotherapy (p < 0.05).

Conclusions

Chemotherapy plays an integral role in maximizing oncologic outcome for select patients with MBO. The data from this study are critical to optimizing multimodality care for these complex patients.

Supplementary Information

The online version contains supplementary material available at 10.1245/s10434-021-09831-0.

Examining the ability of the Cancer and Aging Research Group tool to predict toxicity in older men receiving chemotherapy or androgen-receptor-targeted therapy for metastatic castration-resistant prostate cancer

BACKGROUND

Because multiple treatments are available for metastatic castrate-resistant prostate cancer (mCRPC) and most patients are elderly, the prediction of toxicity risk is important. The Cancer and Aging Research Group (CARG) tool predicts chemotherapy toxicity in older adults with mixed solid tumors, but has not been validated in mCRPC. In this study, its ability to predict toxicity risk with docetaxel chemotherapy (CHEMO) was validated, and its utility was examined in predicting toxicity risk with abiraterone or enzalutamide (A/E) among older adults with mCRPC.

METHODS

Men aged 65+ years were enrolled in a prospective observational study at 4 Canadian academic cancer centers. All clinically relevant grade 2 to 5 toxicities over the course of treatment were documented via structured interviews and chart review. Logistic regression was used to identify predictors of toxicity.

RESULTS

Seventy-one men starting CHEMO (mean age, 73 years) and 104 men starting A/E (mean age, 76 years) were included. Clinically relevant grade 3+ toxicities occurred in 56% and 37% of CHEMO and A/E patients, respectively. The CARG tool was predictive of grade 3+ toxicities with CHEMO, which occurred in 36%, 67%, and 91% of low, moderate, and high-risk groups (P = .003). Similarly, grade 3+ toxicities occurred among A/E users in 23%, 48%, and 86% with low, moderate, and high CARG risk (P < .001). However, it was not predictive of grade 2 toxicities with either treatment.

CONCLUSIONS

There is external validation of the CARG tool in predicting grade 3+ toxicity in older men with mCRPC undergoing CHEMO and demonstrated utility during A/E therapy. This may aid with treatment decision-making.

Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial

Importance

Serious illness conversations (SICs) are structured conversations between clinicians and patients about prognosis, treatment goals, and end-of-life preferences. Interventions that increase the rate of SICs between oncology clinicians and patients may improve goal-concordant care and patient outcomes.

Objective

To determine the effect of a clinician-directed intervention integrating machine learning mortality predictions with behavioral nudges on motivating clinician-patient SICs.

Design, Setting, and Participants

This stepped-wedge cluster randomized clinical trial was conducted across 20 weeks (from June 17 to November 1, 2019) at 9 medical oncology clinics (8 subspecialty oncology and 1 general oncology clinics) within a large academic health system in Pennsylvania. Clinicians at the 2 smallest subspecialty clinics were grouped together, resulting in 8 clinic groups randomly assigned to the 4 intervention wedge periods. Included participants in the intention-to-treat analyses were 78 oncology clinicians who received SIC training and their patients (N = 14 607) who had an outpatient oncology encounter during the study period.

Interventions

(1) Weekly emails to oncology clinicians with SIC performance feedback and peer comparisons; (2) a list of up to 6 high-risk patients (≥10% predicted risk of 180-day mortality) scheduled for the next week, estimated using a validated machine learning algorithm; and (3) opt-out text message prompts to clinicians on the patient's appointment day to consider an SIC. Clinicians in the control group received usual care consisting of weekly emails with cumulative SIC performance.

Main Outcomes and Measures

Percentage of patient encounters with an SIC in the intervention group vs the usual care (control) group.

Results

The sample consisted of 78 clinicians and 14 607 patients. The mean (SD) age of patients was 61.9 (14.2) years, 53.7% were female, and 70.4% were White. For all encounters, SICs were conducted among 1.3% in the control group and 4.6% in the intervention group, a significant difference (adjusted difference in percentage points, 3.3; 95% CI, 2.3-4.5; P < .001). Among 4124 high-risk patient encounters, SICs were conducted among 3.6% in the control group and 15.2% in the intervention group, a significant difference (adjusted difference in percentage points, 11.6; 95% CI, 8.2-12.5; P < .001).

Conclusions and Relevance

In this stepped-wedge cluster randomized clinical trial, an intervention that delivered machine learning mortality predictions with behavioral nudges to oncology clinicians significantly increased the rate of SICs among all patients and among patients with high mortality risk who were targeted by the intervention. Behavioral nudges combined with machine learning mortality predictions can positively influence clinician behavior and may be applied more broadly to improve care near the end of life.

Trial Registration

ClinicalTrials.gov Identifier: NCT03984773.

Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer

Importance

Machine learning (ML) algorithms can identify patients with cancer at risk of short-term mortality to inform treatment and advance care planning. However, no ML mortality risk prediction algorithm has been prospectively validated in oncology or compared with routinely used prognostic indices.

Objective

To validate an electronic health record-embedded ML algorithm that generated real-time predictions of 180-day mortality risk in a general oncology cohort.

Design, Setting, and Participants

This prognostic study comprised a prospective cohort of patients with outpatient oncology encounters between March 1, 2019, and April 30, 2019. An ML algorithm, trained on retrospective data from a subset of practices, predicted 180-day mortality risk between 4 and 8 days before a patient's encounter. Patient encounters took place in 18 medical or gynecologic oncology practices, including 1 tertiary practice and 17 general oncology practices, within a large US academic health care system. Patients aged 18 years or older with outpatient oncology or hematology and oncology encounters were included in the analysis. Patients were excluded if their appointment was scheduled after weekly predictions were generated and if they were only evaluated in benign hematology, palliative care, or rehabilitation practices.

Exposures

Gradient-boosting ML binary classifier.

Main Outcomes and Measures

The primary outcome was the patients' 180-day mortality from the index encounter. The primary performance metric was the area under the receiver operating characteristic curve (AUC).

Results

Among 24 582 patients, 1022 (4.2%) died within 180 days of their index encounter. Their median (interquartile range) age was 64.6 (53.6-73.2) years, 15 319 (62.3%) were women, 18 015 (76.0%) were White, and 10 658 (43.4%) were seen in the tertiary practice. The AUC was 0.89 (95% CI, 0.88-0.90) for the full cohort. The AUC varied across disease-specific groups within the tertiary practice (AUC ranging from 0.74 to 0.96) but was similar between the tertiary and general oncology practices. At a prespecified 40% mortality risk threshold used to differentiate high- vs low-risk patients, observed 180-day mortality was 45.2% (95% CI, 41.3%-49.1%) in the high-risk group vs 3.1% (95% CI, 2.9%-3.3%) in the low-risk group. Integrating the algorithm into the Eastern Cooperative Oncology Group and Elixhauser comorbidity index-based classifiers resulted in favorable reclassification (net reclassification index, 0.09 [95% CI, 0.04-0.14] and 0.23 [95% CI, 0.20-0.27], respectively).

Conclusions and Relevance

In this prognostic study, an ML algorithm was feasibly integrated into the electronic health record to generate real-time, accurate predictions of short-term mortality for patients with cancer and outperformed routinely used prognostic indices. This algorithm may be used to inform behavioral interventions and prompt earlier conversations about goals of care and end-of-life preferences among patients with cancer.

Older Adults' Experiences of Goals in Health: A Systematic Review and Metasynthesis

Objective: To synthesize older adults' experiences and perceptions of goal setting and pursuit within health systems. Methods: Six databases were searched to May 2019 using a combination of MeSH and free text terms. Included papers were written in English and reported original qualitative research for participants aged 65 years and older. Participant quotes from the results sections of included studies were gathered for thematic analysis and synthesis. Results: Initial search yielded 9,845 articles, and 134 were identified for full-text review. Fifteen papers were included in the final synthesis. Two main themes were identified: enablers (intrinsic and extrinsic) and barriers (personal and system). Conclusion: Older adults' self-belief is the strongest enabler for goal activities, enhanced by a personalized coaching approach from health staff. Conversely, inconsistent goal terminology confuses patients and reduces engagement. Likewise, fatigue has profound physical and cognitive impact on patients' ability to engage and participate in goals.

Illness and prognostic understanding in patients with hematologic malignancies

It is critical for patients with hematologic malignancies to have an accurate understanding of their illness and prognosis to make informed treatment decisions. Illness and prognostic understanding have primarily been studied in patients with solid tumors, however, data in patients with hematologic malignancies are rapidly growing. Patients with hematologic malignancies often face a unique and unpredictable illness trajectory with the possibility of cure persisting even in relapsed and refractory settings. These patients often require intensive therapies such as high-dose chemotherapy, hematopoietic stem cell transplantation (HCT), or CAR T-cell therapy, which carry with them significant risk of morbidity, mortality, and prognostic uncertainty. In this review article, we first described the current literature on illness and prognostic understanding in patients with hematologic malignancies including 1) patients' varying desire for prognostic information; (2) patients' prognostic misperceptions, (3) the association between patients' prognostic understanding and their psychological outcomes; and (4) barriers to prognostic understanding. Next, we examined insights gained from the literature about illness and prognostic understanding in patients with solid tumors to guide our understanding of the research gaps in hematologic malignancies. Future studies are needed to better delineate the longitudinal relationship between prognostic understanding, psychological distress, and coping in patients with hematologic malignancies. Strategies such as communicating effectively about prognosis, cultivating adaptive coping in the face of a terminal prognosis, and integrating specialty palliative care for patients with hematologic malignancies have the potential to improve patients' prognostic understanding and their quality of life and care.

Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer

Importance

Machine learning algorithms could identify patients with cancer who are at risk of short-term mortality. However, it is unclear how different machine learning algorithms compare and whether they could prompt clinicians to have timely conversations about treatment and end-of-life preferences.

Objectives

To develop, validate, and compare machine learning algorithms that use structured electronic health record data before a clinic visit to predict mortality among patients with cancer.

Design, Setting, and Participants

Cohort study of 26 525 adult patients who had outpatient oncology or hematology/oncology encounters at a large academic cancer center and 10 affiliated community practices between February 1, 2016, and July 1, 2016. Patients were not required to receive cancer-directed treatment. Patients were observed for up to 500 days after the encounter. Data analysis took place between October 1, 2018, and September 1, 2019.

Exposures

Logistic regression, gradient boosting, and random forest algorithms.

Main Outcomes and Measures

Primary outcome was 180-day mortality from the index encounter; secondary outcome was 500-day mortality from the index encounter.

Results

Among 26 525 patients in the analysis, 1065 (4.0%) died within 180 days of the index encounter. Among those who died, the mean age was 67.3 (95% CI, 66.5-68.0) years, and 500 (47.0%) were women. Among those who were alive at 180 days, the mean age was 61.3 (95% CI, 61.1-61.5) years, and 15 922 (62.5%) were women. The population was randomly partitioned into training (18 567 [70.0%]) and validation (7958 [30.0%]) cohorts at the patient level, and a randomly selected encounter was included in either the training or validation set. At a prespecified alert rate of 0.02, positive predictive values were higher for the random forest (51.3%) and gradient boosting (49.4%) algorithms compared with the logistic regression algorithm (44.7%). There was no significant difference in discrimination among the random forest (area under the receiver operating characteristic curve [AUC], 0.88; 95% CI, 0.86-0.89), gradient boosting (AUC, 0.87; 95% CI, 0.85-0.89), and logistic regression (AUC, 0.86; 95% CI, 0.84-0.88) models (P for comparison = .02). In the random forest model, observed 180-day mortality was 51.3% (95% CI, 43.6%-58.8%) in the high-risk group vs 3.4% (95% CI, 3.0%-3.8%) in the low-risk group; at 500 days, observed mortality was 64.4% (95% CI, 56.7%-71.4%) in the high-risk group and 7.6% (7.0%-8.2%) in the low-risk group. In a survey of 15 oncology clinicians with a 52.1% response rate, 100 of 171 patients (58.8%) who had been flagged as having high risk by the gradient boosting algorithm were deemed appropriate for a conversation about treatment and end-of-life preferences in the upcoming week.

Conclusions and Relevance

In this cohort study, machine learning algorithms based on structured electronic health record data accurately identified patients with cancer at risk of short-term mortality. When the gradient boosting algorithm was applied in real time, clinicians believed that most patients who had been identified as having high risk were appropriate for a timely conversation about treatment and end-of-life preferences.

Health System and Beneficiary Costs Associated With Intensive End-of-Life Medical Services

IMPORTANCE

Despite recommendations to reduce intensive medical treatment at the end of life, many patients with cancer continue to receive such services.

OBJECTIVE

To quantify expected beneficiary and health system costs incurred in association with receipt of intensive medical services in the last month of life.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used data collected nationally from Medicare and the Veterans Health Administration for care provided in fiscal years 2010 to 2014. Participants were 48 937 adults aged 66 years or older who died of solid tumor and were continuously enrolled in fee-for-service Medicare and the Veterans Health Administration in the 12 months prior to death. The data were analyzed from February to August 2019.

EXPOSURES

American Society of Clinical Oncology metrics regarding medically intensive services provided in the last month of life, including hospital stay, intensive care unit stay, chemotherapy, 2 or more emergency department visits, or hospice for 3 or fewer days.

MAIN OUTCOMES AND MEASURES

Costs in the last month of life associated with receipt of intensive medical services were evaluated for both beneficiaries and the health system. Costs were estimated from generalized linear models, adjusting for patient demographics and comorbidities and conditioning on geographic region.

RESULTS

Of 48 937 veterans who received care through the Veterans Health Administration and Medicare, most were white (90.8%) and male (98.9%). More than half (58.9%) received at least 1 medically intensive service in the last month of life. Patients who received no medically intensive service generated a mean (SD) health system cost of $7660 ($1793), whereas patients who received 1 or more medically intensive services generated a mean (SD) health system cost of $23 612 ($5528); thus, the additional financial consequence to the health care system for medically intensive services was $15 952 (95% CI, $15 676-$16 206; P < .001). The biggest contributor to these differences was $21 093 (95% CI, $20 364-$21 689) for intensive care unit stay, while the smallest contributor was $3460 (95% CI, $2927-$3880) for chemotherapy. Mean (SD) expected beneficiary costs for the last month of life were $133 ($50) for patients with no medically intensive service and $1257 ($408) for patients with at least 1 medically intensive service (P < .001).

CONCLUSIONS AND RELEVANCE

Given the low income of many elderly patients in the United States, the financial consequences of medically intensive services may be substantial. Costs of medically intensive services at the end of life, including patient financial consequences, should be considered by both physicians and families.

Extent and Determinants of Terminally Ill Cancer Patients' Concordance Between Preferred and Received Life-Sustaining Treatment States: An Advance Care Planning Randomized Trial in Taiwan

CONTEXT

Promoting patient value-concordant end-of-life care is a priority in health care systems but has rarely been examined in randomized clinical trials.

OBJECTIVES

To examine the effectiveness of an advance care planning intervention in facilitating concordance between cancer patients' preferred and received life-sustaining treatment (LST) states and to explore modifiable factors facilitating or impeding such concordance.

METHODS

Terminal cancer patients (N = 460) were randomly assigned 1:1 to the experimental and control arms of a randomized clinical trial, with 430 deceased participants comprising the final sample. States of preferred LSTs (cardiopulmonary resuscitation, intensive care unit care, chest compression, intubation with mechanical ventilation, intravenous nutrition, and nasogastric tube feeding) and LSTs received in the last month were examined by hidden Markov modeling. Concordance and its modifiable predictors were evaluated by kappa and multivariate logistic regression, respectively.

RESULTS

We identified three LST-preference states (uniformly preferring LSTs, rejecting LSTs except intravenous nutrition support, and mixed LST preferences) and three received LST states (uniformly receiving LSTs, received intravenous nutrition only, and selectively receiving LSTs). Concordance was not significantly higher in the experimental than the control arm (kappa [95% CI]: 0.126 [0.032, 0.221] vs. 0.050 [-0.028, 0.128]; arm difference: odds ratio [95% CI]: 1.008 [0.675, 1.5001]). Preferred-received LST-state concordance was facilitated by accurate prognostic awareness, better quality of life, and more depressive symptoms, whereas concordance was impeded by more anxiety symptoms.

CONCLUSIONS

Our advance care planning intervention did not facilitate concordance between terminally ill cancer patients' preferred and received LST states, but patient value-concordant end-of-life care may be facilitated by interventions to cultivate accurate prognostic awareness, improve quality of life, support depressive patients, and clarify anxious patients' overexpectations of LST efficacy.

Anticancer Therapy at the End of Life: Lessons From a Community Cancer Institute

INTRODUCTION

Studies have shown aggressive cancer care at the end of life is associated with decreased quality of life, decreased median survival, and increased cost of care. This study describes the patients most likely to receive systemic anticancer therapy at the end of life in a community cancer institute.

MATERIALS AND METHODS

We performed a retrospective cohort study of 201 patients who received systemic anticancer therapy in our institution and died between July 2016 and April 2017. Data collected included primary malignancy, hospice enrollment, healthcare utilization, Oncology Care Model (OCM) enrollment, and clinical assessments at last office visit prior to a treatment decision before death. We defined our outcome variable as the receipt of anticancer treatment in the last 14 days of a patient's life. We evaluated 20 clinical exposure variables with respect to the outcome classes. Risk ratios along with their associated confidence intervals and P values were calculated. Significance was determined using the Benjamini-Hochberg procedure to account for multiple testing.

RESULTS

Of the 201 patients who died of cancer, 36 (17%) received anticancer therapy within the last 14 days of life. Several risk factors were significantly positively associated with receiving anticancer therapy at the end of life including hospitalization within 30 days of end of life, number of hospitalizations per patient (≥2), death in hospital, enrollment in OCM, and a diagnosis of hematologic malignancy.

CONCLUSION

Our findings demonstrate those enrolled in the OCM and those with hematologic malignancies have a higher risk of receiving anticancer therapy in the last 14 days of life. These observations highlight the need for better identifying the needs of high-risk patients and providing good quality care throughout the disease trajectory to better align end-of-life care with patients' wishes.

An Individualized, Interactive Intervention Promotes Terminally Ill Cancer Patients' Prognostic Awareness and Reduces Cardiopulmonary Resuscitation Received in the Last Month of Life: Secondary Analysis of a Randomized Clinical Trial

CONTEXT/OBJECTIVE

Half of advanced cancer patients do not have accurate prognostic awareness (PA). However, few randomized clinical trials (RCTs) have focused on facilitating patients' PA to reduce their life-sustaining treatments at end of life (EOL). To address these issues, we conducted a double-blinded RCT on terminally ill cancer patients.

METHODS

Experimental-arm participants received an individualized, interactive intervention tailored to their readiness for advanced care planning and prognostic information. Control-arm participants received a symptom-management educational treatment. Effectiveness of our intervention in facilitating accurate PA and reducing life-sustaining treatments received, two secondary RCT outcomes, was evaluated by intention-to-treat analysis using multivariate logistic regression.

RESULTS

Participants (N = 460) were randomly assigned 1:1 to experimental and control arms, each with 215 participants in the final sample. Referring to 151-180 days before death, experimental-arm participants had significantly higher odds of accurate PA than control-arm participants 61-90, 91-120, and 121-150 days before death (adjusted odds ratio [95% CI]: 2.04 [1.16-3.61], 1.94 [1.09-3.45], and 1.93 [1.16-3.21], respectively), but not one to 60 days before death. Experimental-arm participants with accurate PA were significantly less likely than control-arm participants without accurate PA to receive cardiopulmonary resuscitation (CPR) (0.16 [0.03-0.73]), but not less likely to receive intensive care unit care and mechanical ventilation in their last month.

CONCLUSION

Our intervention facilitated cancer patients' accurate PA early in their dying trajectory, reducing the risk of receiving CPR in the last month. Health care professionals should cultivate cancer patients' accurate PA early in the terminal-illness trajectory to allow them sufficient time to make informed EOL-care decisions to reduce CPR at EOL.

Advance Care Planning Improves Psychological Symptoms But Not Quality of Life and Preferred End-of-Life Care of Patients With Cancer

Background: This study was conducted to examine whether a longitudinal advance care planning (ACP) intervention facilitates concordance between the preferred and received life-sustaining treatments (LSTs) of terminally ill patients with cancer and improves quality of life (QoL), anxiety symptoms, and depressive symptoms during the dying process. Patients and Methods: Of 795 terminally ill patients with cancer from a medical center in Taiwan, 460 were recruited and randomly assigned 1:1 to the experimental and control arms. The experimental arm received an interactive ACP intervention tailored to participants’ readiness to engage in this process. The control arm received symptom management education. Group allocation was concealed, data collectors were blinded, and treatment fidelity was monitored. Outcome measures included 6 preferred and received LSTs, QoL, anxiety symptoms, and depressive symptoms. Intervention effectiveness was evaluated by intention-to-treat analysis. Results: Participants providing data had died through December 2017. The 2 study arms did not differ significantly in concordance between the 6 preferred and received LSTs examined (odds ratios, 0.966 [95% CI, 0.653–1.428] and 1.107 [95% CI, 0.690–1.775]). Participants who received the ACP intervention had significantly fewer anxiety symptoms (β, −0.583; 95% CI, −0.977 to −0.189; P= .004) and depressive symptoms (β, −0.533; 95% CI, −1.036 to −0.030; P= .038) compared with those in the control arm, but QoL did not differ. Conclusions: Our ACP intervention facilitated participants’ psychological adjustment to the end-of-life (EoL) care decision-making process, but neither improved QoL nor facilitated EoL care honoring their wishes. The inability of our intervention to improve concordance may have been due to the family power to override patients’ wishes in deeply Confucian doctrine–influenced societies such as Taiwan. Nevertheless, our findings reassure healthcare professionals that such an ACP intervention does not harm but improves the psychological well-being of terminally ill patients with cancer, thereby encouraging physicians to discuss EoL care preferences with patients and involve family caregivers in EoL care decision-making to eventually lead to patient value–concordant EoL cancer care.

The perils of medico-legal advocacy in ICU conflicts at the end of life: A qualitative study of what happens when advocacy and best interests collide

An unexplored aspect of conflicts and conflict resolution in the ICU at EOL is the role of advocacy in both medicine and law.

GOAL

Qualitative study to explore perspectives of SDM/patient lawyers on issues of advocacy at EOL to better understand conflicts and resolution processes.

METHODS

Purposive sampling with criterion and snowball techniques were used to recruit 11 experienced lawyers for semi-structured interviews. Interviews explored respondents' beliefs, views, and experiences with conflicts; were audio-recorded, coded inductively and iteratively following interpretive analysis. Recurring themes were identified using NVivo Qualitative Software.

RESULTS

We interviewed 11 participants and achieved conceptual saturation. Participants identified insufficient advocacy and overaggressive advocacy as major contributors to the initiation of ICU conflicts and the inhibition of resolution processes before and after the legal system is engaged. These breakdowns in advocacy contribute to challenges when conflicts arise, leading to prolongation of conflict-resolution processes and to outcomes that sometimes reflect the goals of legal advocacy rather than patient-centred goals.

CONCLUSION

This study explores legal perspective of conflict at EOL and how these perspectives can be used to inform the development of better approaches to conflict resolution.

Factors Predisposing Terminally Ill Cancer Patients' Preferences for Distinct Patterns/States of Life-Sustaining Treatments Over Their Last Six Months

CONTEXT

High-quality end-of-life (EOL) care depends on thoroughly assessing terminally ill patients' preferences for EOL care and tailoring care to individual needs. Studies on predictors of EOL-care preferences were primarily cross-sectional and assessed preferences for multiple life-sustaining treatments (LSTs), making clinical applications difficult.

OBJECTIVE/METHODS

We examined factors predisposing cancer patients (N = 303) to specific LST-preference states (life-sustaining preferring, comfort preferring, uncertain, and nutrition preferring) derived from six LSTs (cardiopulmonary resuscitation, intensive care unit care, chest compression, intubation with mechanical ventilation, intravenous nutrition, and tube feeding) in patients' last six months by multilevel multinomial logistic regression.

RESULTS

Participants with accurate prognostic awareness and physician-patient EOL-care discussions were less likely to be in life-sustaining-preferring, uncertain, and nutrition-preferring states than in the comfort-preferring state. Better quality of life (QOL) and more depressive symptoms predisposed participants to be less likely to be in the uncertain than in the comfort-preferring state. Membership in the nutrition-preferring rather than the comfort-preferring state was significantly higher for participants in the state of moderate symptom distress with severe functional impairment than in the state of mild symptom distress with high functioning.

CONCLUSION

Accurate prognostic awareness, physician-patient EOL-care discussions, QOL, depressive symptoms, and symptom-functional states predisposed terminally ill cancer patients to distinct LST-preference states. Clinicians should cultivate patients' accurate prognostic awareness and facilitate EOL-care discussions to foster realistic expectations of LST efficacy at EOL. Clinicians should enhance patients' QOL to reduce uncertainty in EOL-care decision making and provide adequate psychological support to those with more depressive symptoms who prefer comfort care only.

Creating space to discuss end-of-life issues in cancer care

OBJECTIVES

Analyze entire oncology clinical visits and examine instances in which oncologists have to break the bad news that patients' treatments are no longer effective.

METHODS

Using conversation analysis we examine 128 audio recorded conversations between terminal cancer patients, their caregivers, and oncologists.

RESULTS

When oncologists break the bad news that a patient's treatment is no longer effective, they often use a conversational device we call an "exhausted current treatment" (ECT) statement, which avoids discussing prognosis in favor of further discussing treatment options. Analysis suggests that improving and prioritizing patient-centered care and shared decision making is possible if we first understand the social organization of clinical visits.

CONCLUSIONS

ECT statements and their movement towards discussing treatment options means that opportunities are bypassed for patients and caregivers to process or discuss scan results, and their prognostic implications.

PRACTICE IMPLICATIONS

When oncologists and patients, by fixating on treatment options, bypass opportunities to discuss the meaning of scan results, they fail to realize other goals associated with prognostic awareness. Talking about what scans mean may add minutes to that part of the clinic visit, but can create efficiencies that conserve overall time. We recommend that oncologists, after delivering scan news, ask, "Would you like discuss what this means?".

How I treat elderly patients with plasma cell dyscrasias

Plasma cell dyscrasias are a rare heterogeneous group of hematological disorders which are more prevalent in the older part of the population. The introduction of novel agents, improved understanding of disease biology and better supportive management have improved outcomes considerably and in the era of the aging population the question of how to best manage older patients with plasma cell dyscrasias has never been more relevant. Data on how to treat these patients comes mostly from subgroup analysis as they are underrepresented in clinical trials. This review will cover issues, available evidence and recommendations relevant to diagnosis and management of the older patients with Multiple Myeloma (MM), Waldenstrom Macroglobulinemia (WM) and systemic AL Amyloidosis. What will become increasingly evident is the need to develop and establish the use of disease-specific geriatric assessment (GA) tools. Frailty status assessment using GA tools and moving away from making decisions based merely on chronological age will allow setting clear treatment goals and consequently achieving an optimum balance between effectiveness and toxicity for this complex and heterogeneous group of patients.

Theories of Health Care Decision Making at the End of Life: A Meta-Ethnography

The aim of this meta-ethnography is to appraise the types and uses of theories relative to end-of-life decision making and to develop a conceptual framework to describe end-of-life decision making among patients with advanced cancers, heart failure, and amyotrophic lateral sclerosis (ALS) and their caregivers or providers. We used PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases to extract English-language articles published between January 2002 and April 2015. Forty-three articles were included. The most common theories included decision-making models ( n = 14) followed by family-centered ( n = 11) and behavioral change models ( n = 7). A conceptual framework was developed using themes including context of decision making, communication and negotiation of decision making, characteristics of decision makers, goals of decision making, options and alternatives, and outcomes. Future research should enhance and apply these theories to guide research to develop patient-centered decision-making programs that facilitate informed and shared decision making at the end of life among patients with advanced illness and their caregivers.

Treatment of Multiple Myeloma in Elderly Patients: A Review of Literature and Practice Guidelines

Multiple myeloma (MM) is a clonal disorder of malignant plasma cells that comprises approximately 10% of hematologic malignancies. With median age of 66 at the time of presentation, multiple myeloma is predominantly a disease of the elderly. The availability of new combination regimens and the enhanced safety of autologous hematopoietic stem cell transplant has increased the treatment options for elderly patients with multiple myeloma. We provide a summary of data supporting the current management of elderly patients with newly diagnosed multiple myeloma.

Factors associated with the time to first palliative care consultation in Lebanese cancer patients

INTRODUCTION

Early palliative care is recommended for cancer patients. However, palliative care consults (PCC) are often delayed in Lebanon. The aim of this study was to identify the factors associated with timing of PCC and their impact on the place of death.

METHODS

This is a retrospective, single institution, study conducted at Hotel Dieu de France University Hospital in Lebanon. The clinical and demographic characteristics of oncology patients who received PCC were obtained. Cox and logistic regression models were used to evaluate the factors determining the time to first PCC and location of death, respectively.

RESULTS

Two hundred and ten patients were included in our analyses with a median age of 69 years (range 22-92 years). The median survival times were: overall survival 18.7 months, time to first PCC 17.9 months, and survival post-PCC 0.6 months. Among patients who were followed-up at home, the median time spent at home was 0.6 months. Late PCC were associated with a childless status (HR = 0.57, 95%CI = 0.37-0.86, p = 0.007), awareness of the diagnosis (HR = 0.64, 95%CI = 0.45-0.91, p = 0.013), and lack of palliative home care (HR = 0.42, 95%CI = 0.25-0.65, p < 0.001). Older patients (OR = 1.03, 95%CI = 1.01-1.05, p = 0.026) and those who had been followed up at home during the PCC (OR = 160.56, 95%CI = 21.39-1205.50, p < 0.001) were significantly more likely to have died at home as opposed to the hospital.

DISCUSSION

Cancer patients often receive PCC only shortly before their death. PCC for Lebanese cancer patients were found to be significantly delayed in patients that are childless, knowledgeable of their diagnosis, and lack home palliative care.

Approaches to decision-making among late-stage melanoma patients: a multifactorial investigation

Purpose

The treatment decisions of melanoma patients are poorly understood. Most research on cancer patient decision-making focuses on limited components of specific treatment decisions. This study aimed to holistically characterize late-stage melanoma patients’ approaches to treatment decision-making in order to advance understanding of patient influences and supports.

Methods

(1) Exploratory analysis of longitudinal qualitative data to identify themes that characterize patient decision-making. (2) Pattern analysis of decision-making themes using an innovative method for visualizing qualitative data: a hierarchically-clustered heatmap. Participants were 13 advanced melanoma patients at a large academic medical center.

Results

Exploratory analysis revealed eight themes. Heatmap analysis indicated two broad types of patient decision-makers. “Reliant outsiders” relied on providers for medical information, demonstrated low involvement in decision-making, showed a low or later-in-care interest in clinical trials, and expressed altruistic motives. “Active insiders” accessed substantial medical information and expertise in their networks, consulted with other doctors, showed early and substantial interest in trials, demonstrated high involvement in decision-making, and employed multiple decision-making strategies.

Conclusion

We identified and characterized two distinct approaches to decision-making among patients with late-stage melanoma. These differences spanned a wide range of factors (e.g., behaviors, resources, motivations). Enhanced understanding of patients as decision-makers and the factors that shape their decision-making may help providers to better support patient understanding, improve patient-provider communication, and support shared decision-making.

Development and Application of a Machine Learning Approach to Assess Short-term Mortality Risk Among Patients With Cancer Starting Chemotherapy

IMPORTANCE

Patients with cancer who die soon after starting chemotherapy incur costs of treatment without the benefits. Accurately predicting mortality risk before administering chemotherapy is important, but few patient data-driven tools exist.

OBJECTIVE

To create and validate a machine learning model that predicts mortality in a general oncology cohort starting new chemotherapy, using only data available before the first day of treatment.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study of patients at a large academic cancer center from January 1, 2004, through December 31, 2014, determined date of death by linkage to Social Security data. The model was derived using data from 2004 through 2011, and performance was measured on nonoverlapping data from 2012 through 2014. The analysis was conducted from June 1 through August 1, 2017. Participants included 26 946 patients starting 51 774 new chemotherapy regimens.

MAIN OUTCOMES AND MEASURES

Thirty-day mortality from the first day of a new chemotherapy regimen. Secondary outcomes included model discrimination by predicted mortality risk decile among patients receiving palliative chemotherapy, and 180-day mortality from the first day of a new chemotherapy regimen.

RESULTS

Among the 26 946 patients included in the analysis, mean age was 58.7 years (95% CI, 58.5-58.9 years); 61.1% were female (95% CI, 60.4%-61.9%); and 86.9% were white (95% CI, 86.4%-87.4%). Thirty-day mortality from chemotherapy start was 2.1% (95% CI, 1.9%-2.4%). Among the 9114 patients in the validation set, the most common primary cancers were breast (21.1%; 95% CI, 20.2%-21.9%), colorectal (19.3%; 95% CI, 18.5%-20.2%), and lung (18.0%; 95% CI, 17.2%-18.8%). Model predictions were accurate for all patients (area under the curve [AUC], 0.940; 95% CI, 0.930-0.951). Predictions for patients starting palliative chemotherapy (46.6% of regimens; 95% CI, 45.8%-47.3%), for whom prognosis is particularly important, remained highly accurate (AUC, 0.924; 95% CI, 0.910-0.939). To illustrate model discrimination, patients were ranked initiating palliative chemotherapy by model-predicted mortality risk, and observed mortality was calculated by risk decile. Thirty-day mortality in the highest-risk decile was 22.6% (95% CI, 19.6%-25.6%); in the lowest-risk decile, no patients died. Predictions remained accurate across all primary cancers, stages, and chemotherapies, even for clinical trial regimens that first appeared in years after the model was trained (AUC, 0.942; 95% CI, 0.882-1.000). The same model also performed well for prediction of 180-day mortality (AUC for all patients, 0.870 [95% CI, 0.862-0.877]; highest- vs lowest-risk decile mortality, 74.8% [95% CI, 72.7%-77.0%] vs 0.2% [95% CI, 0.01%-0.4%]). Predictions were more accurate than estimates from randomized clinical trials of individual chemotherapies or the Surveillance, Epidemiology, and End Results data set.

CONCLUSIONS AND RELEVANCE

A machine learning algorithm using electronic health record data accurately predicted short-term mortality among patients starting chemotherapy. Further research is necessary to determine the generalizability and feasibility of applying this algorithm in clinical settings.

Recent advances in the management of multiple myeloma: clinical impact based on resource-stratification. Consensus statement of the Asian Myeloma Network at the 16th international myeloma workshop

Predicated on our improved understanding of the disease biology, we have seen remarkable advances in the management of multiple myeloma over the past few years. Recently approved drugs have radically transformed the treatment paradigm and improved survivals of myeloma patients. The progress has necessitated revision of the diagnostic criteria, risk-stratification and response definition. The huge disparities in economy, healthcare infrastructure and access to novel drugs among different Asian countries will hinder the delivery of optimum myeloma care to patients managed in resource-constrained environments. In the light of the tremendous recent changes and evolution in myeloma management, it is timely that the resource-stratified guidelines from the Asian Myeloma Network be revised to provide updated recommendations for Asia physicians practicing under various healthcare reimbursement systems. This review will highlight the most recent advances and our recommendations on how they could be integrated in both resource-abundant and resource-constrained facilities.

Preferences for Life-Sustaining Treatments Examined by Hidden Markov Modeling Are Mostly Stable in Terminally Ill Cancer Patients' Last Six Months of Life

CONTEXT

Stability of life-sustaining treatment (LST) preferences at end of life (EOL) has not been well established for terminally ill cancer patients nor have transition probabilities been explored between different types of preferences.

OBJECTIVE

We assessed the stability of cancer patients' LST preferences at EOL by identifying distinct LST preference states and examining the probability of each state transitioning to other states between consecutive time points.

METHODS

Stability of LST preferences (cardiopulmonary resuscitation, intensive care unit [ICU] care, cardiac massage, intubation with mechanical ventilation, intravenous nutrition support, and nasogastric tube feeding) was examined among 303 cancer patients in their last six months by hidden Markov modeling.

RESULTS

Six distinct LST preference states (initial size) were identified: uniformly preferring (8.3%), uniformly rejecting (33.8%), and uniformly uncertain about (20.5%) LST, favoring intravenous nutrition support but rejecting other treatments (19.9%), and favoring (3.6%) or uncertain about (14.0%) nutrition support and ICU care while rejecting other treatments. Shifts between LST preference states were relatively small between any two time points (transition probability of staying at the same state was 92.1% to 97.5%), except for the state characterized by uncertainty about nutrition support and ICU care while rejecting other treatments, in which 8.3% of patients shifted LST preferences toward uniform uncertainty at a subsequent assessment.

CONCLUSIONS

Our patients' LST preferences remained stable without prominent shifts toward preferring less aggressive LSTs even when death approached. Clarifying patients' understanding and expectations about LST efficacy and tailoring interventions to the unique needs of patients in each state may provide personalized EOL care.

Life values of elderly people suffering from incurable cancer: A literature review

OBJECTIVE

Due to aging Western societies, older patients suffering from incurable cancer will present themselves more often to health care professionals. To be of service to these severely ill elderly patients, more knowledge is needed on which life values are guiding them through their last phases of life. This review aims to describe which life values play an important part in the lives of elderly people suffering from incurable cancer.

METHODS

We conducted a literature review with a structured search to identify empirical studies (January 1950-February 2016) using six databases.

RESULTS

The analysis of thirty articles resulted in the extensive description of eight life values: comfort, continuity, humility, dignity, honesty, optimism, hope and preparedness.

CONCLUSION

Elderly patients suffering from incurable cancer use the abovementioned life values to give meaning to a life interrupted by disease. Furthermore, these values will play a role in communication and decision-making.

PRACTICE IMPLICATIONS

Knowledge about life values can help professionals discuss and clarify personal preferences with elderly patients suffering from incurable cancer, contributing to more personalized care and treatment. Communication should focus on to what extent patient empowerment, life-prolonging treatment and the involvement of the patient's supporting systems suit the wishes of these patients.

The impact of specialized palliative care on cancer patients' health-related quality of life: a systematic review and meta-analysis

PURPOSE

Specialized palliative care (SPC) is currently underutilized or provided late in cancer care. The aim of this systematic review and meta-analysis is to critically evaluate the impact of SPC on patients' health-related quality of life (HRQoL).

METHODS

Five databases were searched through June 2016. Randomized controlled trials (RCTs) and prospective studies using a pre- and post- assessment of HRQoL were included. The PRISMA reporting statement was followed. Criteria from available checklists were used to evaluate the studies' quality. A meta-analysis followed using random-effect models separately for RCTs and non-RCTs.

RESULTS

Eleven studies including five RCTs and 2939 cancer patients published between 2001 and 2014 were identified. There was improved HRQoL in patients with cancer following SPC especially in symptoms like pain, nausea, and fatigue as well as improvement of physical and psychological functioning. Less or no improvements were observed in social and spiritual domains. In general, studies of inpatients showed a larger benefit from SPC than studies of outpatients whereas patients' age and treatment duration did not moderate the impact of SPC. Methodological shortcomings of included studies include high attrition rates, low precision, and power and poor reporting of control procedures.

CONCLUSIONS

The methodological problems and publication bias call for higher-quality studies to be designed, funded, and published. However, there is a clear message that SPC is multi-disciplinary and aims at palliation of symptoms and burden in line with current recommendations.

Illness Understanding of Oncology Patients in a Community-Based Cancer Institute

PURPOSE

Several studies have demonstrated that patients have a poor understanding of prognosis, survival, and effectiveness of chemotherapy, particularly in the setting of advanced cancer. This study examines oncology patients' understanding of their illness based on accurate reporting of stage at diagnosis and knowledge of cancer status (ie, free of cancer or in remission v active disease).

MATERIALS AND METHODS

Two hundred eight patients with cancer previously treated at our large community-based cancer institute participated in the Consumer-Based Cancer Care Value Index field survey. Electronic medical record documentation of stage at diagnosis and cancer status was compared with patients' self-reported responses. Concordance of responses and variables influencing discordance were evaluated.

RESULTS

In 51.0% of patients, self-reported cancer stage matched the abstracted stage, with the highest concordance in patients with advanced cancer (72%) versus patients with stage I to III disease (36.4% to 61.5%). Unexpectedly, discordance was lower among patients with advanced cancer compared with patients with stage I to III cancer ( P = .0528). Patients who were concordant for cancer stage at diagnosis were significantly more likely to be female ( P = .001), be younger than age 65 years ( P = .01), have an income > $60,000 ( P = .03), and have more education ( P = .02). In 64.4% of patients, self-reported cancer status (ie, free of cancer or in remission v active disease) matched the abstracted status. Nearly 30% of patients were not sure about their status, even when they were free of cancer or in remission.

CONCLUSION

Our findings confirm that more than one quarter of patients with advanced cancer have poor illness understanding and highlight that an even greater number of patients with early stage I to III cancer have poor illness understanding. These observations highlight the need to improve illness understanding for patients across the entire cancer continuum.

If We Don't Ask, Our Patients Might Never Tell: The Impact of the Routine Use of a Patient Values Assessment

PURPOSE

Good communication can be associated with better end-of-life outcomes. The US Oncology Network developed and tested a Values Assessment (VA) for facilitating advance care planning (ACP). The results of the first 1,268 patients are reported.

METHODS

The VA consists of 10 questions of the format "How valuable is it to me to…" (eg, "...know that I am not a burden to my family, friends, or helpers?"). Responses were on a four-point scale from unsure to very valuable. VA data on 1,286 patients with metastatic cancer from April 1, 2013, to July 31, 2015, were extracted from the electronic health record, including demographics, diagnosis, stage, chemotherapy, and outcomes (hospice enrollment, place of death). These demographics were compared by using the χ² or Fisher's exact test or the Wilcoxon rank sum test for continuous variables.

RESULTS

A total of 1,268 patients completed the VA (56.7% were ≥ 65 years of age, 57.8% completed advance directives [ADs]). There were 438 deaths of which 308 had a place of death or a hospice enrollment recorded. Of these, 78% died at home or inpatient hospice; 14.6% died in the hospital. Hospice enrollment with ADs was 76.1% and without, 60.9%. Median length of stay in hospice was 21 days with ADs versus 12.5 days without. Chemotherapy in the last 14 days of life was 8.8% with ADs and 15.5% without. The VA was well accepted by patients.

CONCLUSION

A VA as a routine part of practice is feasible and scalable. It facilitates ACP discussions that lead to ADs. The results suggest that VA and ACP lead to less-aggressive care at the end of life.

End-of-Life Care Matters: Palliative Cancer Care Results in Better Care and Lower Costs

This article reviews the current state of end‐of‐life care, analyzes the clinical and financial impact of palliative care, and proposes areas of future research and development.

Clinical significance and predicting indicators of post-cancer-treatment survival in terminally ill patients with ovarian cancer

AIM

Women with ovarian cancer (OC) often experience relapse and receive further repetitive chemotherapy. The objective of this study was to overview the remaining survival time after the final chemotherapy and to examine influential clinicopathologic indicators in those patients.

METHODS

The medical charts of deceased OC patients who had died of the disease between 2003 and 2012 were retrospectively reviewed. We investigated post-cancer-treatment survival (PCS) defined as the interval between the date of the final chemotherapy and death.

RESULTS

In all, 77 patients were enrolled. Three patients (3.9%) had received chemotherapy in the last 2 weeks. Eight (10.4%), 28 (36.4%), and 44 (57.2%) patients had received chemotherapy in the last 30, 60, and 90 days, respectively. There were no differences in either survival after recurrence or overall survival between the shorter (<75 days) and longer (≥75 days) PCS groups. On the other hand, patients in the shorter PCS group had significantly fewer chances of referral to a hospice or home-care than those in the latter group (P = 0.035). In multivariable analysis, a poorer performance status, an elevated white blood cell count, and a higher C-reactive protein value were significantly correlated with a shorter PCS (P = 0.004, 0.006 and 0.027, respectively).

CONCLUSION

Half of the patients received chemotherapy within 75 days of death and we did not identify any survival benefit in patients who received chemotherapy near the end of life. We should provide information to patients about their prognosis and discuss the timing of withdrawal from chemotherapy from the early stage of their recurrence.

Preferences for Aggressive End-of-life Care and Their Determinants Among Taiwanese Terminally Ill Cancer Patients

BACKGROUND

Studies on factors influencing preferences for aggressive end-of-life (EOL) care have focused predominantly on preferred goals of EOL and seldom comprehensively incorporate patients' predisposing, enabling, and need factors into their analyses.

OBJECTIVE

The aim of this study was to investigate the determinants of preferences for a wide range of aggressive EOL care from the aforementioned factors.

METHODS

A cross-sectional survey was conducted using a convenience sample of 2329 terminally ill cancer patients recruited from 23 hospitals throughout Taiwan.

RESULTS

Among these Taiwanese terminally ill cancer patients, 8.2% preferred prolonging life as their goal for EOL care. When combining those who wanted and those who were undecided as wanting that specific treatment, 27.9% preferred cardiopulmonary resuscitation when their life was in danger, and 36.0%, 27.3%, 24.3%, and 26.7% preferred to receive care at intensive care unit, cardiac massage, intubation, and mechanical ventilation support, respectively. Those at risk of preferring aggressive EOL care were men, younger than 45 years, married, diagnosed within 6 months, and with comorbidity and their physician had not accurately disclosed their prognosis or discussed EOL care issues to/with them.

CONCLUSIONS

Few Taiwanese terminally ill cancer patients preferred to prolong life as their goal for EOL care, cardiopulmonary resuscitation when their life was in danger, and life-sustaining treatments at EOL. Preferences for aggressive EOL care are determined by patients' predisposing, enabling, and need factors.

IMPLICATIONS FOR PRACTICE

Terminally ill cancer patients at risk of preferring aggressive EOL care should receive interventions to help them appropriately weigh the burdens and benefits of such aggressive treatments.

Do-not-resuscitate orders in cancer patients: a review of literature

Discussing do-not-resuscitate (DNR) orders is part of daily hospital practice in oncology departments. Several medical factors and patient characteristics are associated with issuing DNR orders in cancer patients. DNR orders are often placed late in the disease process. This may be a cause for disagreements between doctors and between doctors and patients and may cause for unnecessary treatments and admissions. In addition, DNR orders on itself may influence the rest of the medical treatment for patients. We present recommendations for discussing DNR orders and medical futility in practice through shared decision-making. Prospective studies are needed to investigate in which a patient's cardiopulmonary resuscitation (CPR) is futile and whether or not DNR orders influence the medical care of patients.

End-of-life care preferences of nursing home residents: Results of a cross-sectional study

BACKGROUND

Palliative care services were not available in nursing homes in Singapore. Project CARE (Care At the end-of-life for Residents in homes for the Elderly) was a pilot programme that aimed to promote advance care planning and improve end-of-life care in nursing homes.

AIM

We aimed to examine end-of-life care preferences among nursing home residents, and identify factors associated with preference for medical intervention, cardiopulmonary resuscitation and place of death.

DESIGN AND SETTING/PARTICIPANTS

A cross-sectional study using data from advance care planning discussions was conducted from September 2009 to April 2012 across seven nursing homes. The advance care planning discussion was conducted with the resident (with a prognosis of 6 months or 1 year), their families and staff from the nursing home and hospital.

RESULTS

A total of 600 residents and their families completed the advance care planning discussion. Majority (93.2%) preferred not to proceed with cardiopulmonary resuscitation, 52.3% opted for limited additional intervention at the nursing home with escalation to the hospital if necessary and 77.0% preferred to die at the nursing home. Residents 85+ years (relative risk ratio: 3.34, 95% confidence interval: 1.13-9.93, p = 0.030) were more likely to prefer medical intervention at the nursing home only. No associations were found with the preference for cardiopulmonary resuscitation. Residents who were single, or who were Christians or Catholics (adjusted odds ratio: 2.09, 95% confidence interval: 1.04-4.19, p = 0.039), were more likely to prefer to die at the nursing home.

CONCLUSION

Preferences for medical interventions in nursing homes provide support to extend palliative care services to nursing homes, which may benefit residents who are older, single, or Christians or Catholics.

Skilled nursing facility placement in hospitalized elderly patients with colon cancer

BACKGROUND

The current study sought to determine predictive risk factors and inpatient resource utilization associated with discharge to skilled nursing facility (SNF) in hospitalized elderly patients with colon cancer.

MATERIALS AND METHODS

Inpatient data from U.S. community hospital discharges from 2003 to 2011 was analyzed in a retrospective cohort study using the Healthcare Cost and Utilization Project, National Inpatient Sample (HCUP-NIS). Subjects included hospitalized postoperative colon cancer patients over age of 65 (N = 98,797).

RESULTS

The proportion of elderly colon cancer patients discharged to a SNF increased by 16.67% from 2003 to 2011 (18-21%). Elderly patients discharged to a SNF had increased hospitalization costs (+$10,293.70, p < 0.01) compared to elderly colon cancer patients discharged home. Hospitalization predictive risk factors associated with SNF placement include age above 75 (OR, 4.07; 95% CI, 3.90, 4.25; p < 0.01), paralysis (OR, 3.60; 95% CI, 3.06-4.23; p < 0.01), length of stay (LOS) 10 days or more (OR, 3.00; 95% CI, 2.88-3.13; p < 0.01), psychoses (OR, 2.91; 95% CI, 2.56-3.32; p < 0.01), and neurological disorders (OR, 2.34; 95% CI, 2.17-2.52; p < 0.01).

CONCLUSIONS

Despite increased costs and worse clinical outcomes associated with SNF placement, over 40% increase of hospital discharge to SNF should be anticipated from this population over the next 20 years. Neurologic and psychiatric comorbidities have significantly negative clinical impacts and increase the likelihood of colon cancer patients' discharge to a SNF.

Factors Influencing Chemotherapy Goal Perception in Newly Diagnosed Cancer Patients

Cancer patients who start receiving chemotherapy have difficulty in understanding the state of their disease, the prognosis, and the purpose of treatment. We used a survey to evaluate the extent of perception of chemotherapy goal among cancer patients. Two hundred sixteen cancer patients who received chemotherapy for the first time participated in the study. The presence of depression and anxiety was assessed using the "Hospital Anxiety and Depression Scale" (HAD). The consistency between the patients' perception of the chemotherapy goal and the physician's perception was described as "right," and the inconsistency was described as "wrong." Among the patients who participated in the survey, 53.2 % (n = 115) were receiving adjuvant treatment and 46.8 % (n = 101) were receiving palliative treatment for metastatic disease. The rate of right and wrong perception of the chemotherapy goal was 51.9 % (n = 108) and 32.2 % (n = 67), respectively, and the rate of confused patients was 18.9 % (n = 41). The level of education was shown to be the only parameter involved in accurate perception of the treatment purpose (hazard ratio (HR) = 0.444, p = 0.025, 95 % confidence interval (CI) 0.219-0.903). In this study, there was a 51.9 % consistency between the physician's perception and that of the patient regarding the purpose of treatment. We demonstrated that the level of education was the unique factor in accurate perception of chemotherapy goal among cancer patients.

Early supportive medication use and end-of-life care among Medicare beneficiaries with advanced breast cancer

PURPOSE

A randomized controlled trial of cancer patients has linked early supportive care with improved hospice use and less-aggressive end-of-life care. In practice, the early use of supportive interventions and potential impact on end-of-life care are poorly understood. We sought to describe early use of medications to treat common breast cancer symptoms (pain, insomnia, anxiety, and depression) and to assess the relationship between early use of these treatments and end-of-life care.

METHODS

Secondary analysis of 2006-2012 SEER-Medicare data was performed. Women included had stage IV breast cancer and died within the observation period. We used modified Poisson regression to assess the relationship between supportive medication use in the 90 days post-diagnosis and several end-of-life care measures (hospice use, in-hospital death, chemotherapy receipt within 14 days of death, ICU admission, or >1 hospitalization or emergency department/ED visit 30 days before death).

RESULTS

Among the 947 women included, 68 % of women used at least one supportive medication in the 90 days following their diagnosis: 60.3 % used opioid pain medications and 28.3 % received non-opioid psychotropic medications. Early use of any supportive medications was not associated with end-of-life care. Similarly, we found no differences in end-of-life care between opioid pain medication users and non-users. However, we found that non-opioid psychotropic medication users were less likely to receive chemotherapy in the last 14 days of life (aRR 0.33, 95 % CI 0.12-0.88).

CONCLUSIONS

Non-opioid psychotropic use was associated with some aspects of end-of-life care. Future research should consider alternative measures of palliative and supportive care use using administrative data sources.

Impact of high self-perceived burden to others with preferences for end-of-life care and its determinants for terminally ill cancer patients: a prospective cohort study

BACKGROUND/OBJECTIVE

Self-perceived burden to others (SPB) is a major concern of terminally ill cancer patients and is frequently factored into end-of-life (EOL) care decision-making. However, changes in and determinants of SPB and its longitudinal impact on preferences for EOL care over the dying process have not been investigated. Our study was aimed at filling this gap in knowledge.

METHODS

A convenience sample of 325 cancer patients was followed until death. High SPB was identified as scoring >20 on the Self-perceived Burden Scale. Preferences for EOL care included EOL-care goals, life-sustaining treatments, and hospice care. Factors potentially precipitating/minimizing patients' high SPB included demographics, disease characteristics and burden, and social support and were examined by multivariate logistic regression modeling with the generalized estimating equation.

RESULTS

Prevalence of high SPB increased as death approached (51.78%, 58.26%, 62.66%, and 65.38% for 181-365, 91-180, 31-90, and 1-30 days before death, respectively). High SPB was precipitated by women, younger age, having inadequate financial resources, without religious affiliation, and suffering from severe symptom distress and heavy functional dependence but was independent of time proximity to patient death, disease characteristics, and social support. Furthermore, high SPB was not associated with EOL-care preferences, whether aggressive life-sustaining treatments or hospice care.

CONCLUSIONS

High SPB was prevalent among terminally ill cancer patients but independent of preferences for EOL care. Cancer patients' SPB may be lessened by adequate symptom relief to facilitate functional independence. These strategies to ease SPB may improve the quality of death and dying. Copyright © 2016 John Wiley & Sons, Ltd.

Preferences for Life-Sustaining Treatments and Associations With Accurate Prognostic Awareness and Depressive Symptoms in Terminally Ill Cancer Patients' Last Year of Life

CONTEXT

The stability of life-sustaining treatment (LST) preferences at end of life (EOL) has been established. However, few studies have assessed preferences more than two times. Furthermore, associations of LST preferences with modifiable variables of accurate prognostic awareness, physician-patient EOL care discussions, and depressive symptoms have been investigated in cross-sectional studies only.

OBJECTIVES

To explore longitudinal changes in LST preferences and their associations with accurate prognostic awareness, physician-patient EOL care discussions, and depressive symptoms in terminally ill cancer patients' last year.

METHODS

LST preferences (cardiopulmonary resuscitation, intensive care unit [ICU] care, intubation, and mechanical ventilation) were measured approximately every two weeks. Changes in LST preferences and their associations with independent variables were examined by hierarchical generalized linear modeling with logistic regression.

RESULTS

Participants (n = 249) predominantly rejected cardiopulmonary resuscitation, ICU care, intubation, and mechanical ventilation at EOL without significant changes as death approached. Patients with inaccurate prognostic awareness were significantly more likely than those with accurate understanding to prefer ICU care, intubation, and mechanical ventilation than to reject these LSTs. Patients with more severe depressive symptoms were less likely to prefer ICU care and to be undecided about wanting ICU care and mechanical ventilation than to reject such LSTs. LST preferences were not associated with physician-patient EOL care discussions, which were rare in our sample.

CONCLUSION

LST preferences are stable in cancer patients' last year. Facilitating accurate prognostic awareness and providing adequate psychological support may counteract the increasing trend for aggressive EOL care and minimize emotional distress during EOL care decisions.