Prevalence and predictors of high-intensity end-of-life care among adolescents and young adults with cancer in Ontario: a population-based study using the IMPACT cohort.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 10559-10559
Author(s):  
Hallie Coltin ◽  
Adam Rapoport ◽  
Chenthila Nagamuthu ◽  
Nancy N. Baxter ◽  
Paul C. Nathan ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Young Adults ◽  
End Of Life ◽  
Rural Areas ◽  
High Intensity ◽  
Early Period ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Eol Care ◽  
The Impact

10559 Background: End-of-life (EOL) care in adolescents and young adults (AYA) with cancer is poorly characterized, though this group may be at risk of elevated rates of high-intensity (HI) care and consequently, increased EOL suffering. Few population-based studies exist, and are limited by incomplete clinical information. AYA care patterns can vary by locus of care (LOC – pediatric v. adult), but LOC disparities in AYA EOL care are unstudied. Methods: We conducted a retrospective decedent population-based cohort study of all Ontario AYA diagnosed between 15-21 years of age with 6 prevalent primary cancers between 1992-2012, who died ≤5 years from diagnosis. Chart-abstracted clinical data were linked to health services data. The primary composite outcome (HI-EOL care) included any of: intravenous chemotherapy ≤14 days from death; > 1 emergency department visit ≤30 days from death; or > 1 hospitalization or intensive care unit (ICU) admission ≤30 days from death. Secondary outcomes included measures of the most invasive (MI) EOL care: mechanical ventilation ≤14 days from death, and death in the ICU. Factors associated with HI-EOL were examined. Results: Of 483 patients, 292 (60.5%) experienced HI-EOL care, 98 (20.3%) were mechanically ventilated ≤14 days from death, and 110 (22.8%) died in the ICU. Patients with hematological malignancies (v. solid tumors) were at greatest risk of HI-EOL care (OR, 2.3; 95CI, 1.5-3.5, p < 0.01), mechanical ventilation (OR, 5.4; 95CI, 3.0-9.7, p < 0.01), and death in an ICU (OR, 4.9; 95CI, 2.8-8.5, p < 0.01). AYA who died in a pediatric center were substantially more likely to experience MI-EOL measures compared to those dying in adult centers (mechanical ventilation, OR 3.2, 95CI 1.3-7.6, p = 0.01). Assessment of interactions showed LOC-based disparities widening over the study period (ICU death in pediatric v. adult centres: early period OR 0.9, 95CI 0.3-2.9, p = 0.91; late period OR 3.3, 95CI 1.2-9.2, p = 0.02; interaction term p = 0.04). AYA living in rural areas were also at higher risk of experiencing mechanical ventilation (OR, 2.0; 95CI, 1.0-3.8, p = 0.04) and death in ICU (OR, 2.1; 95CI, 1.1-4.0, p = 0.02). Conclusions: AYA with cancer experience high rates of HI-EOL care, with patients in pediatric centers and those living in rural areas at highest risk of MI-EOL care. Our study is the first to identify LOC-based disparities in AYA EOL care. Future studies should explore mechanisms underlying these disparities, including potential differences in palliative care services.

Impact of Palliative Care Involvement on End-of-Life Care Patterns Among Adolescents and Young Adults With Cancer: A Population-Based Cohort Study

2021 ◽  
pp. JCO.20.03698
Author(s):  
Alisha Kassam ◽  
Abha Gupta ◽  
Adam Rapoport ◽  
Amirrtha Srikanthan ◽  
Rinku Sutradhar ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Palliative Care ◽  
Young Adults ◽  
End Of Life ◽  
Population Level ◽  
Hematologic Malignancies ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Eol Care ◽  
The Impact

PURPOSE Evidence suggests that adolescents and young adults (AYAs) with cancer (defined as age 15-39 years) receive high-intensity (HI) medical care at the end-of-life (EOL). Previous population-level studies are limited and lack information on the impact of palliative care (PC) provision. We evaluated prevalence and predictors of HI-EOL care in AYAs with cancer in Ontario, Canada. A secondary aim was to evaluate the impact of PC physicians on the intensity of EOL care in AYAs. METHODS A retrospective decedent cohort of AYAs with cancer who died between 2000 and 2017 in Ontario, Canada, was assembled using a provincial registry and linked to population-based health care data. On the basis of previous studies, the primary composite measure HI-EOL care included any of the following: intravenous chemotherapy < 14 days from death, more than one emergency department visit, and more than one hospitalization or intensive care unit admission < 30 days from death. Secondary measures included the most invasive (MI) EOL care (eg, mechanical ventilation < 14 days from death) and PC physician involvement. We determined predictors of outcomes using appropriate regression models. RESULTS Of 7,122 AYAs, 43.8% experienced HI-EOL care. PC physician involvement (odds ratio [OR], 0.57; 95% CI, 0.51 to 0.63) and older age at death (OR, 0.60; 95% CI, 0.48 to 0.74) were associated with a lower risk of HI-EOL care. AYAs with hematologic malignancies were at highest risk for HI and MI-EOL care. PC physician involvement substantially reduced the odds of mechanical ventilation at EOL (OR, 0.36; 95% CI, 0.30 to 0.43). CONCLUSION A large proportion of AYAs with cancer experience HI-EOL care. Our study provides strong evidence that PC physician involvement can help mitigate the risk of HI and MI-EOL care in AYAs with cancer.

Patterns of intensity of end-of-life care for adolescents and young adults with cancer: A population-based study.

2016 ◽  
Vol 34 (26_suppl) ◽  
pp. 132-132 ◽  
Author(s):  
Emily E. Johnston ◽  
Elysia Marie Alvarez ◽  
Olga Saynina ◽  
Lee Sanders ◽  
Smita Bhatia ◽  
...  
Keyword(s):  
Young Adults ◽  
End Of Life ◽  
Solid Tumors ◽  
Health Planning ◽  
Hematologic Malignancies ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Secondary Neoplasms ◽  
Factors Associated ◽  
Eol Care

132 Background: Cancer is the leading cause of non-accidental death amongst adolescents and young adults (AYA), aged 15-39, in the U.S. It is critical to understand end of life (EOL) care of AYA cancer decedents, including use of medically intense interventions like intubation. Although desired by some, most patients prefer a natural death. We sought to determine rates of medically intense interventions at end of life for AYA cancer decedents and associated factors. Methods: Using the California Office of Statewide Health Planning and Development private administrative database linked to death certificates, we performed a retrospective population based analysis of patients aged 15-39 with cancer who died between 2000-2010. We used previously defined administrative codes indicative of intense EOL care: intubation, CPR, hospital re-admission, and ICU admission in the last 30 days of life, and location of death. The frequencies of each intense item were calculated and multivariate logistic regression was used to determine clinical (including treatment at specialty center vs non) and socio-demographic factors associated with each item and receipt of ≥ 2 items. Results: The 8,978 AYA cancer decedents were 46% non-Hispanic white, 29% Hispanic, 10% non-Hispanic black, 11% Asian; 21% had hematologic malignancies, 70% had solid tumors, and 9% had secondary neoplasms; 58% were hospitalized only at non-specialty centers in the last 6 months of life. 62% received ≥ 1 medically intense EOL care intervention, and 32% received > 2. Factors associated with > 2 intense EOL care interventions were: non-Hispanic black (OR 1.38, 95% CI 1.16-1.65), Hispanics (1.19, 1.06-1.35), Asians (1.30, 1.10-1.52); those sometimes (2.19, 1.87-2.56) or never (1.44, 1.26-1.65) seen at specialty centers; hematologic malignancies (1.77, 1.57-2.00 ref grp: solid tumors) whereas secondary malignancies were not associated with > 2 intense markers (0.68, 0.56-0.83). Conclusions: Nearly two-thirds of the AYA cancer decedents received medically intense EOL interventions and disparities exist in receipt of such care. Further research needs to determine if the disparities are due to healthcare system, patient preference, or other factors.

scholarly journals End-of-Life Intensity for Adolescents and Young Adults With Cancer: A Californian Population-Based Study That Shows Disparities

2017 ◽  
Vol 13 (9) ◽  
pp. e770-e781 ◽  
Author(s):  
Emily E. Johnston ◽  
Elysia Alvarez ◽  
Olga Saynina ◽  
Lee Sanders ◽  
Smita Bhatia ◽  
...  
Keyword(s):  
Young Adults ◽  
End Of Life ◽  
High Intensity ◽  
End Of Life Care ◽  
Hematologic Malignancies ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Hospital Death ◽  
Life Care ◽  
Patient Goals

Purpose: Cancer is the leading cause of nonaccidental death among adolescents and young adults (AYAs). High-intensity end-of-life care is expensive and may not be consistent with patient goals. However, the intensity of end-of-life care for AYA decedents with cancer—especially the effect of care received at specialty versus nonspecialty centers—remains understudied. Methods: We conducted a retrospective, population-based analysis with the California administrative discharge database that is linked to death certificates. The cohort included Californians age 15 to 39 years who died between 2000 and 2011 with cancer. Intense end-of-life interventions included readmission, admission to an intensive care unit, intubation in the last month of life, and in-hospital death. Specialty centers were defined as Children’s Oncology Group centers and National Cancer Institute–designated comprehensive cancer centers. Results: Of the 12,938 AYA cancer decedents, 59% received at least one intense end-of-life care intervention, and 30% received two or more. Patients treated at nonspecialty centers were more likely than those at specialty-care centers to receive two or more intense interventions (odds ratio [OR], 1.46; 95% CI, 1.32 to 1.62). Sociodemographic and clinical factors associated with two or more intense interventions included minority race/ethnicity (Black [OR, 1.35, 95% CI, 1.17 to 1.56]; Hispanic [OR, 1.24; 95% CI, 1.12 to 1.36]; non-Hispanic white: reference), younger age (15 to 21 years [OR, 1.36; 95% CI, 1.19 to 1.56; 22 to 29 years [OR,1.26; 95% CI,1.14 to 1.39]; ≥ 30 years: reference), and hematologic malignancies (OR, 1.53; 95% CI, 1.41 to 1.66; solid tumors: reference). Conclusion: Thirty percent of AYA cancer decedents received two or more high-intensity end-of-life interventions. In addition to sociodemographic and clinical characteristics, hospitalization in a nonspecialty center was associated with high-intensity end-of-life care. Additional research is needed to determine if these disparities are consistent with patient preference.

Predictors of and Trends in High-Intensity End-of-Life Care Among Children With Cancer: A Population-Based Study Using Health Services Data

2017 ◽  
Vol 35 (2) ◽  
pp. 236-242 ◽  
Author(s):  
Alisha Kassam ◽  
Rinku Sutradhar ◽  
Kimberley Widger ◽  
Adam Rapoport ◽  
Jason D. Pole ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Health Services ◽  
High Intensity ◽  
Hematologic Malignancies ◽  
Population Based ◽  
Children With Cancer ◽  
Eol Care ◽  
Related Mortality

Purpose Children with cancer often receive high-intensity (HI) medical care at the end-of-life (EOL). Previous studies have been limited to single centers or lacked detailed clinical data. We determined predictors of and trends in HI-EOL care by linking population-based clinical and health-services databases. Methods A retrospective decedent cohort of patients with childhood cancer who died between 2000 and 2012 in Ontario, Canada, was assembled using a provincial cancer registry and linked to population-based health-care data. Based on previous studies, the primary composite measure of HI-EOL care comprised any of the following: intravenous chemotherapy < 14 days from death; more than one emergency department visit; and more than one hospitalization or intensive care unit admission < 30 days from death. Secondary measures included those same individual measures and measures of the most invasive (MI) EOL care (eg, mechanical ventilation < 14 days from death). We determined predictors of outcomes with appropriate regression models. Sensitivity analysis was restricted to cases of cancer-related mortality, excluding treatment-related mortality (TRM) cases. Results The study included 815 patients; of these, 331 (40.6%) experienced HI-EOL care. Those with hematologic malignancies were at highest risk (odds ratio, 2.5; 95% CI, 1.8 to 3.6; P < .001). Patients with hematologic cancers and those who died after 2004 were more likely to experience the MI-EOL care (eg, intensive care unit, mechanical ventilation, odds ratios from 2.0 to 5.1). Excluding cases of TRM did not substantively change the results. Conclusion Ontario children with cancer continue to experience HI-EOL care. Patients with hematologic malignancies are at highest risk even when excluding TRM. Of concern, rates of the MI-EOL care have increased over time despite increased palliative care access. Linking health services and clinical data allows monitoring of population trends in EOL care and identifies high-risk populations for future interventions.

Patterns of intensity of end of life care for adolescents and young adults with cancer: A population based study.

2016 ◽  
Vol 34 (15_suppl) ◽  
pp. e21518-e21518
Author(s):  
Emily E. Johnston ◽  
Elysia Marie Alvarez ◽  
Olga Saynina ◽  
Lee Sanders ◽  
Smita Bhatia ◽  
...  
Keyword(s):  
Young Adults ◽  
End Of Life ◽  
End Of Life Care ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Life Care ◽  
Population Based Study

The validity of algorithms using health administrative data in identifying cancer-related events in adolescents and young adults: A population-based study using the IMPACT cohort.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18168-e18168
Author(s):  
Jason D Pole ◽  
Paul C. Nathan ◽  
Nancy N. Baxter ◽  
Cindy Lau ◽  
Corinne Daly ◽  
...  
Keyword(s):  
Young Adults ◽  
Administrative Data ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Administrative Databases ◽  
Time Interval ◽  
Cancer Outcomes ◽  
Health Administrative Data ◽  
Chart Abstraction ◽  
The Impact

e18168 Background: Despite the importance of estimating population level cancer outcomes, most registries do not collect critical events such as relapse and progression. Attempts to use health administrative data to identify these events have focused on older adults and have been mostly unsuccessful. We developed and tested administrative data-based algorithms in a population-based cohort of adolescents and young adults (AYA) with cancer. Methods: We identified all Ontario AYA 15-21 years of age diagnosed with leukemia, lymphoma, sarcoma, or testicular cancer between 1992 and 2012. Chart abstraction was used to determine the end of initial treatment (EOIT) date and subsequent cancer-related events (progression, relapse, second cancer). Linkage to population-based administrative databases identified fee and procedure codes indicating cancer treatment or palliative care. Algorithms that determined EOIT based a time interval free of treatment-associated codes, and new cancer-related events based on billing codes, were compared to chart abstracted data. Results: The cohort comprised 1,404 patients. Time periods free of treatment-associated codes did not validly identify EOIT dates; using subsequent codes to identify new cancer events was thus associated with low sensitivity (56.2%). However, using administrative data codes that occurred after the EOIT date based on chart abstraction, the first cancer-related event was identified with excellent validity (sensitivity 87.0%, specificity 93.3%, PPV 81.5%, negative predictive value 95.5%). Conclusions: While administrative data alone did not validly identify cancer-related events, using administrative data in combination with chart collected EOIT dates was associated with excellent validity. The collection of EOIT dates by cancer registries would significantly expand the potential of administrative data linkage to assess cancer outcomes.

scholarly journals Outcome Among Adolescents and Young Adults with Acute Myeloid Leukemia at Pediatric Versus Adult Centers: A Population-Based Study Using the IMPACT Cohort

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4749-4749
Author(s):  
Sumit Gupta ◽  
Nancy Baxter ◽  
Jason Pole ◽  
Cindy Lau ◽  
Rinku Sutradhar ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Young Adults ◽  
Acute Lymphoblastic Leukemia ◽  
Myeloid Leukemia ◽  
Conflicts Of Interest ◽  
Lymphoblastic Leukemia ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
The Impact ◽  
Acute Myeloid

Background: Survival outcomes among adolescents and young adults (AYA) with acute myeloid leukemia (AML) remain poor. In AYA with acute lymphoblastic leukemia, outcomes differ between patients treated in pediatric vs. adult centers. This has not been well evaluated in AML. We therefore compared outcomes between AYA with AML treated at pediatric vs. adult centers using a population-based clinical database. In addition, we determined other predictors of outcome within this population. Methods: The IMPACT Cohort comprises all Ontario, Canada AYA aged 15-21 years diagnosed with one of six common cancers (including AML) between 1992-2012. Detailed demographic, disease, treatment, and outcome data were collected through chart abstraction and validated by content experts. Locus of cancer care (LOC - pediatric vs. adult center) was determined based on where the majority of therapy was delivered in the first three months after diagnosis. Linkage to population-based health administrative data identified additional cancer events (second cancers, relapse, death). Event-free (EFS) and overall survival (OS) were determined using Kaplan-Meier methods. The impact of LOC on EFS and OS was determined using multivariable Cox proportional hazard models, adjusting for demographic, disease, and treatment variables. Events included disease progression, relapse, death, and second malignancies. Results: Among 140 AYA with AML, 89 (63.6%) received therapy at an adult center. AYA treated in pediatric centers were younger than those treated at adult centers (median 16 years vs. 19 years; p<0.001) and were more likely to live in higher-income neighborhoods [37/51 (72.5%) vs. 47/89 (52.8%); p=0.02]. Disease markers such as presenting white blood cell count and AML subtype did not differ by LOC. The 5-year EFS and OS for the whole cohort were 35.0%±4.0% and 53.6%±4.2%. Neither EFS nor OS differed by LOC (Table 1). In multivariable analyses adjusting for disease characteristics, LOC was not predictive of either EFS [adult vs. pediatric center hazard ratio (HR) 1.3, 95thconfidence interval (CI) 0.8-2.2, p=0.27] or OS (HR 1.0, CI 0.6-1.6, p=0.97). AYA with AML living in rural areas however experienced significantly inferior outcomes as compared to their urban counterparts (EFS: HR 2.5, CI 1.3-4.7, p=0.005; OS: HR 2.0, CI 1.1-3.8, p=0.04). Conclusions: In this population-based cohort, outcomes did not differ between AYA with AML treated at pediatric vs. adult centers, unlike what has been previously shown in AYA with acute lymphoblastic leukemia. However, rural AYA experienced substantially inferior outcomes than urban AYA, suggesting that even within a universal single payer system of healthcare, socioeconomic disparities persist in this population. Disclosures No relevant conflicts of interest to declare.

scholarly journals Barriers to Optimal End-of-Life Care for Adolescents and Young Adults With Cancer: Bereaved Caregiver Perspectives

2021 ◽  
Vol 19 (5) ◽  
pp. 528-533
Author(s):  
Jennifer W. Mack ◽  
Erin R. Currie ◽  
Vincent Martello ◽  
Jordan Gittzus ◽  
Asisa Isack ◽  
...  
Keyword(s):  
Young Adults ◽  
End Of Life ◽  
Family Caregivers ◽  
Emotional Support ◽  
Poor Prognosis ◽  
Care Delivery ◽  
Qualitative Interviews ◽  
Adolescents And Young Adults ◽  
Eol Care

Background: Adolescents and young adults (AYAs; aged 15–39 years) with cancer frequently receive intensive measures at the end of life (EoL), but the perspectives of AYAs and their family members on barriers to optimal EoL care are not well understood. Methods: We conducted qualitative interviews with 28 bereaved caregivers of AYAs with cancer who died in 2013 through 2016 after receiving treatment at 1 of 3 sites (University of Alabama at Birmingham, University of Iowa, or University of California San Diego). Interviews focused on ways that EoL care could have better met the needs of the AYAs. Content analysis was performed to identify relevant themes. Results: Most participating caregivers were White and female, and nearly half had graduated from college. A total of 46% of AYAs were insured by Medicaid or other public insurance; 61% used hospice, 46% used palliative care, and 43% died at home. Caregivers noted 3 main barriers to optimal EoL care: (1) delayed or absent communication about prognosis, which in turn delayed care focused on comfort and quality of life; (2) inadequate emotional support of AYAs and caregivers, many of whom experienced distress and difficulty accepting the poor prognosis; and (3) a lack of home care models that would allow concurrent life-prolonging and palliative therapies, and consequently suboptimal supported goals of AYAs to live as long and as well as possible. Delayed or absent prognosis communication created lingering regret among some family caregivers, who lost the opportunity to support, comfort, and hold meaningful conversations with their loved ones. Conclusions: Bereaved family caregivers of AYAs with cancer noted a need for timely prognostic communication, emotional support to enhance acceptance of a poor prognosis, and care delivery models that would support both life-prolonging and palliative goals of care. Work to address these challenges offers the potential to improve the quality of EoL care for young people with cancer.

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