Quality of End-of-Life in Cancer Patients With Dementia: Using A Nationwide Inpatient Database

End of life care for people with dementia and comorbid cancer: recent studies and research gaps

PURPOSE OF REVIEW

This narrative review examines recent research on end of life (EOL) care for people with dementia and comorbid cancer, highlighting the complexity and challenge of providing effective EOL care for this group and areas of interest for future research.

RECENT FINDINGS

People with cancer and dementia and their family/supporters have more complex care and support needs at EOL that are less well met than those of older adults with cancer alone, including questionable use of aggressive EOL care interventions, poorer access to specialist palliative care teams and poor pain management. Those diagnosed with dementia at the same time as, or after their cancer diagnosis, are at greater risk of aggressive EOL care and EOL cancer treatment and care plans that are not able to meet their care needs as dementia progresses.

SUMMARY

There is a lack of research on EOL care for people with cancer and dementia. There is little understanding of what good care for this population looks like and if and how EOL care can best meet the needs of people with cancer and dementia or their carers/supporters. More research is needed to inform improved care for this population.

Dementia Incidence in Survivors of Multiple Myeloma: A National Case-Control Study Conducted in Korea (The CAREMM-2106 Study)

BACKGROUND

Dementia, a growing global health issue, affects older adults and specific groups like long-term cancer survivors. The link between cancer survival and dementia is debated. Multiple myeloma (MM), a common blood cancer in older adults, is often linked with cognitive issues. This study investigated dementia incidence in long-term MM survivors using Korean national data.

METHODS

A retrospective case-control study used data from the Korea National Health Insurance Service (KNHIS), covering about 50 million Koreans. Patients diagnosed with MM between 2009 and 2020 formed the case cohort, while the control cohort included matched individuals without MM using propensity-score matching. Analyzing baseline characteristics, comorbidities, and socioeconomic status, the primary outcome was dementia incidence identified via ICD-10 codes. Statistical methods included Kaplan-Meier plots, cause-specific and Fine-Gray subdistribution hazard models, and a 3-year landmark analysis for immortal time bias.

RESULTS

The study included 33,864 patients, with 16,932 in each cohort. The overall cumulative dementia incidence was lower in the MM cohort compared to controls. However, in the first 3 years, MM patients had a higher dementia risk (HR: 1.711, 95% CI, 1.562-1.874) than controls. After 3 years, the risk significantly decreased (HR: 0.625, 95% CI, 0.560-0.696). Age-specific analysis showed a consistent pattern, particularly among MM patients aged 70-79, where dementia risk increased post-3 years.

CONCLUSION

This study reveals a lower long-term dementia risk in MM survivors compared to non-MM individuals. Further prospective studies are needed to confirm these findings and explore the underlying mechanisms.

Good Death and Quality of End-of-Life Care in Patients with Coexisting Cancer and Dementia: Perspective of Bereaved Families

Background

Patients with coexisting cancer and dementia often have complex health care needs and face challenges in achieving a good death.

Objectives

To evaluate good death achievement and end-of-life (EOL) care in patients with coexisting cancer and dementia from the perspective of bereaved families.

Design

Cross-sectional nationwide postal survey.

Setting/Subjects

Bereaved families of patients with cancer who died in hospice and palliative care units across Japan.

Measurements

Bereaved families completed an anonymous, self-reported questionnaire. Their perspective on achieving a good death was assessed using the Good Death Inventory (GDI) (total score: 18-126). The Revised Care Evaluation Scale-short version (CES2) was used to assess EOL care (total score: 10-60). We examined the Brief Grief Questionnaire (BGQ) (total score: 0-10) and Patient Health Questionnaire 9 (PHQ9) (total score: 0-27).

Results

Data from 670 participants were analyzed, including 83 (12.4%) bereaved families of patients with coexisting cancer and dementia. No statistical differences were observed in the total GDI score for 18 items (dementia comorbidity vs. nondementia comorbidity groups, mean ± standard deviation, respectively, 78.4 ± 17.7 vs. 80.0 ± 15.5, adjusted [adj] P = 0.186), CES2 score (49.70 ± 9.22 vs. 48.82 ± 8.40, adj P = 0.316), BGQ score (3.40 ± 2.41 vs. 4.36 ± 2.28, adj P = 0.060), and PHQ9 score (4.67 ± 4.71 vs. 5.50 ± 5.37, adj P = 0.788).

Conclusions

GDI, CES2, BGQ, and PHQ9 scores did not differ significantly between groups, regardless of the presence of dementia in hospice and palliative care units. Patients with coexisting cancer and dementia can achieve a good death by high-quality EOL care.

Predicting mortality in patients diagnosed with advanced dementia presenting at an acute care hospital: the PROgnostic Model for Advanced DEmentia (PRO-MADE)

BACKGROUND

Challenges in prognosticating patients diagnosed with advanced dementia (AD) hinders timely referrals to palliative care. We aim to develop and validate a prognostic model to predict one-year all-cause mortality (ACM) in patients with AD presenting at an acute care hospital.

METHODS

This retrospective cohort study utilised administrative and clinical data from Tan Tock Seng Hospital (TTSH). Patients admitted to TTSH between 1st July 2016 and 31st October 2017 and identified to have AD were included. The primary outcome was ACM within one-year of AD diagnosis. Multivariable logistic regression was used. The PROgnostic Model for Advanced Dementia (PRO-MADE) was internally validated using a bootstrap resampling of 1000 replications and externally validated on a more recent cohort of AD patients. The model was evaluated for overall predictive accuracy (Nagelkerke's R² and Brier score), discriminative [area-under-the-curve (AUC)], and calibration [calibration slope and calibration-in-the-large (CITL)] properties.

RESULTS

A total of 1,077 patients with a mean age of 85 (SD: 7.7) years old were included, and 318 (29.5%) patients died within one-year of AD diagnosis. Predictors of one-year ACM were age > 85 years (OR:1.87; 95%CI:1.36 to 2.56), male gender (OR:1.62; 95%CI:1.18 to 2.22), presence of pneumonia (OR:1.75; 95%CI:1.25 to 2.45), pressure ulcers (OR:2.60; 95%CI:1.57 to 4.31), dysphagia (OR:1.53; 95%CI:1.11 to 2.11), Charlson Comorbidity Index ≥ 8 (OR:1.39; 95%CI:1.01 to 1.90), functional dependency in ≥ 4 activities of daily living (OR: 1.82; 95%CI:1.32 to 2.53), abnormal urea (OR:2.16; 95%CI:1.58 to 2.95) and abnormal albumin (OR:3.68; 95%CI:2.07 to 6.54) values. Internal validation results for optimism-adjusted Nagelkerke's R², Brier score, AUC, calibration slope and CITL were 0.25 (95%CI:0.25 to 0.26), 0.17 (95%CI:0.17 to 0.17), 0.76 (95%CI:0.76 to 0.76), 0.95 (95% CI:0.95 to 0.96) and 0 (95%CI:-0.0001 to 0.001) respectively. When externally validated, the model demonstrated an AUC of 0.70 (95%CI:0.69 to 0.71), calibration slope of 0.64 (95%CI:0.63 to 0.66) and CITL of -0.27 (95%CI:-0.28 to -0.26).

CONCLUSION

The PRO-MADE attained good discrimination and calibration properties. Used synergistically with a clinician's judgement, this model can identify AD patients who are at high-risk of one-year ACM to facilitate timely referrals to palliative care.

A comparison of end-of-life care patterns between older patients with both cancer and Alzheimer's disease and related dementias versus those with only cancer

INTRODUCTION

Aggressive end-of-life (EOL) care that is not aligned with the preferences of persons with cancer has negative impacts on their quality of life. Alzheimer's disease and related dementias (ADRD) could potentially complicate EOL care planning among persons with cancer. Little is known about the aggressive EOL care patterns among Medicare beneficiaries with both cancer and ADRD.

MATERIALS AND METHODS

A matched retrospective cohort was created using the 2004 to 2016 Surveillance, Epidemiology, End Results-Medicare (SEER-Medicare) data differentiated by beneficiaries' ADRD status. Beneficiaries with breast, lung, colorectal, or prostate cancer who died between January 1, 2005 and December 31, 2016, were included. Six existing domains of aggressive EOL care and one overall indicator were derived. The major predictor was having ADRD comorbidity; other covariates included sex, marital status, census tract poverty indicator, race/ethnicity, metro status, geographic location, Charlson Comorbidity Index (CCI), survival time, cancer site, and histology stage. Multivariable logistic regression models were deployed to estimate the odds of receiving aggressive EOL care.

RESULTS

The study sample was 135,380 people after the one-to-one propensity score matching. The prevalence of aggressive EOL care utilization was slightly lower in beneficiaries with both cancer and ADRD when compared to beneficiaries with cancer only (54% vs. 58%, p < 0.0001). Beneficiaries with both cancer and ADRD were less likely to receive aggressive EOL care (AOR: 0.88, 95% CI: 0.86, 0.90) versus beneficiaries with cancer only. From the multivariable logistic regression model, certain beneficiaries' characteristics were associated with higher odds of receiving aggressive EOL care, such as: beneficiaries belonging to a racial/ethnic minority, a shorter survival time, and a higher CCI score.

DISCUSSION

The combined presence of ADRD and cancer was associated with lower odds of receiving aggressive EOL care compared to the presence of only cancer; however, the prevalence difference between the cohorts was not huge. Future studies could conduct in-depth evaluations of the ADRD's influence on the EOL care utilization.