Impact of cancer on the risk of unplanned 30-day readmissions.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 6581-6581
Author(s):  
Alexander Qian ◽  
Edmund Qiao ◽  
Vinit Nalawade ◽  
Nikhil V. Kotha ◽  
Rohith S. Voora ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Hospital Admissions ◽  
Reference Group ◽  
Cancer Site ◽  
Cancer Type ◽  
Logistic Regression Models ◽  
Increased Risk ◽  
Initial Hospitalization ◽  
The Impact

6581 Background: Hospital readmission are associated with unfavorable patient outcomes and increased costs to the healthcare system. Devising interventions to reduce risks of readmission requires understanding patients at highest risk. Cancer patients represent a unique population with distinct risk factors. The purpose of this study was to define the impact of a cancer diagnosis on the risks of unplanned 30-day readmissions. Methods: We identified non-procedural hospital admissions between January through November 2017 from the National Readmission Database (NRD). We included patients with and without a cancer diagnosis who were admitted for non-procedural causes. We evaluated the impact of cancer on the risk of 30-day unplanned readmissions using multivariable mixed-effects logistic regression models. Results: Out of 18,996,625 weighted admissions, 1,685,099 (8.9%) had record of a cancer diagnosis. A cancer diagnosis was associated with an increased risk of readmission compared to non-cancer patients (23.5% vs. 13.6%, p < 0.001). However, among readmissions, cancer patients were less likely to have a preventable readmission (6.5% vs. 12.1%, p < 0.001). When considering the 10 most common causes of initial hospitalization, cancer was associated with an increased risk of readmission for each of these 10 causes (OR range 1.1-2.7, all p < 0.05) compared to non-cancer patients admitted for the same causes. Compared to patients aged 45-64, a younger age was associated with increased risk for cancer patients (OR 1.29, 95%CI [1.24-1.34]) but decreased risk for non-cancer patients (OR 0.65, 95%CI [0.64-0.66]). Among cancer patients, cancer site was the most robust individual predictor for readmission with liver (OR 1.47, 95%CI [1.39-1.55]), pancreas (OR 1.36, 95%CI [1.29-1.44]), and non-Hodgkin’s lymphoma (OR 1.35, 95%CI [1.29-1.42]) having the highest risk compared to the reference group of prostate cancer patients. Conclusions: Cancer patients have a higher risk of 30-day readmission, with increased risks among younger cancer patients, and with individual risks varying by cancer type. Future risk stratification approaches should consider cancer patients as an independent group with unique risks of readmission.

Impact of precancer multimorbidity clusters on survival and functional outcomes after cancer in older patients.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 291-291 ◽  
Author(s):  
Kelly Kenzik ◽  
Joshua Richman ◽  
Erin E. Kent ◽  
Maria Pisu ◽  
Smita Bhatia
Keyword(s):  
Cancer Patients ◽  
Survey Data ◽  
Cancer Diagnosis ◽  
Functional Impairment ◽  
Regression Models ◽  
Poverty Level ◽  
Risk Of Death ◽  
Increased Risk ◽  
After Cancer ◽  
The Impact

291 Background: While multimorbidity clustering is a significant problem in older adults, the impact of clusters present prior to cancer on post-diagnosis survival and function is unknown. We used SEER-Medicare Health Outcomes Survey data for 4583 cancer patients to address this research gap. Methods: Patients with prostate (1741), breast (BC: 1345), colorectal (CRC: 904) and lung (593) cancer with pre- and post-diagnosis survey data were included. Surveys assessed comorbidity and activities of daily living (ADLs). Previously defined multimorbidity clusters were cardiovascular disease (CVD), skeletal, metabolic, pulmonary + major depressive disorder (MDD), and gastrointestinal (GI) + MDD. Cox regression models estimated hazard ratios (HR) for death after cancer diagnosis. Among those without pre-cancer ADL impairment, modified Poisson regression models estimated relative risk (RR) for developing post-cancer functional impairment (ADL ≤ 4). Models controlled for age, race, education, poverty level, stage, and treatment (radiation, surgery). Results: Median age at cancer diagnosis was 74y (65-103). Post-diagnosis mortality: After 6y median follow-up, mortality was 30%; 5y survival was 74%.Prostate, BC and CRC patients with pre-diagnosis CVD clusters were at increased risk of death compared to those without CVD cluster (HR 1.9, 2.0, 1.7, respectively, p < 0.05). Compared to those without the cluster, prostate and BC patients with metabolic cluster were at increased risk (HR 1.7, 1.9, respectively, p < 0.05) and prostate cancer patients with pulmonary conditions + MDD or GI + MDD (HR 1.9, 2.1, respectively, p < 0.05) were at increased risk. Post-diagnosis functional impairment: Prevalence of moderate functional impairment at a median of 1y after cancer diagnosis was 31%. Prostate, lung, and CRC survivors with GI + MDD had a significant RR of developing impairment (RR 1.8, 1.8, and 1.7, p < 0.001). For BC patients, those with skeletal cluster had a 2.1 RR (p < 0.001). Conclusions: Specific multimorbidity clusters prior to cancer are associated with post-cancer mortality and ADL impairment and identify at-risk groups where interventions can be instituted to decrease morbidity and mortality.

scholarly journals National Cancer Diagnosis Audit: avoidable delays to diagnosis

2019 ◽  
Vol 69 (suppl 1) ◽  
pp. bjgp19X703073
Author(s):  
Ruth Swann ◽  
Georgios Lyratzopoulos ◽  
Greg Rubin ◽  
Elizabeth Pickworth ◽  
Sean McPhail
Keyword(s):  
Cancer Diagnosis ◽  
Cancer Type ◽  
Logistic Regression Models ◽  
Patient Demographics ◽  
Cancer Types ◽  
General Practices ◽  
Diagnostic Interval ◽  
Reported Data ◽  
The Impact

BackgroundA prolonged time taken to diagnose cancer can lead to poorer survival and reduced quality of life. Characterising avoidable delays to a patient’s diagnosis could help to direct quality improvement initiatives aimed at enhancing patient safety and ultimately patient outcomes.AimTo assess the validity of data on avoidable delays collected as part of the English National Cancer Diagnosis Audit (NCDA) and to estimate the predictors of avoidable delays to diagnosis by patient demographics and cancer type.MethodParticipating general practices (n = 439; 5% practices) submitted primary care data on patients (n = 17 042) diagnosed with cancer in 2014 in England. GPs reported delays to the diagnosis that they considered avoidable. Quantile regression was used to understand the impact of an avoidable delay on the diagnostic interval. Logistic regression models were used to investigate the factors associated with avoidable delay.ResultsThe GP recorded an avoidable delay to cancer diagnosis in 24% of cases (n = 3372). The median diagnostic interval was 57 days longer in patients where an avoidable delay was recorded. Results have shown significant associations between avoidable delay and certain cancer types (odds ratio [OR] 1.73 for stomach versus lung cancer) and an increasing number of comorbidities (OR 1.43 for patients with ≥3 versus 0).ConclusionGP-reported data showed a longer diagnostic interval in patients thought to have had an avoidable delay to their diagnosis, indicating construct validity of the data collected. Data from the NCDA is being used to better understand avoidable delays to diagnosis, and identify possible solutions for improving the diagnostic pathway in some cases.

scholarly journals 633Poorly controlled diabetes is a predictor of colorectal cancer survival

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Ming Li ◽  
David Roder
Keyword(s):  
Colorectal Cancer ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Cancer Survival ◽  
Epidemiological Studies ◽  
Colorectal Cancer Survival ◽  
Increased Risk ◽  
History Of ◽  
Colorectal Cancer Patients ◽  
The Impact

Abstract Background Epidemiological studies have shown diabetes associated with increased risk of colorectal cancer. This study investigates the impact of a pre-cancer diabetes-related hospitalization record on colorectal cancer survival. Methods A retrospective cohort of 13190 colorectal cancer patients recorded on the South Australian Cancer Registry in 2003-2013 were examined. Diabetes-related hospitalization histories were obtained using linked inpatient data. Colorectal cancer deaths were available for 2003-2013. The association of survival from colorectal cancer with diabetes-related hospitalization history was assessed using competing risk analysis, adjusting for sociodemographic factors and cancer stage at diagnosis. Results 2765 patients with colorectal cancer (26.5%) had a history of hospital admission for diabetic complications, the most common being multiple complications (32%), followed by kidney and eye complications. The 5- and 10-year cancer survival probabilities were 63% and 56% in those with a diabetes complication history, significantly lower than 66% and 60% for patients without these complications (adjusted sub hazard ratio 1.11, 95% CI 1.02-1.20). Risk of colorectal cancer death was lower when theses diabetes-related hospitalizations were earlier than the year of cancer diagnosis - i.e., adjusted SHR 0.80, 95% CI 0.66-0.97 for 3-5 and 0.76, 95% CI 0.59-0.98 for 6+ years before the cancer diagnosis compared with same-year hospitalizations. Conclusions Colorectal cancer patients with a history of diabetes-related hospitalization have poorer survival, particularly if these hospitalizations were in the same year as the cancer diagnosis. Key messages Poorly controlled diabetes histories predict increased risk of colorectal cancer mortality.

scholarly journals Risk of Suicide After a Cancer Diagnosis in England: A Population-Based Study

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 228s-228s
Author(s):  
K. Henson ◽  
R. Brock ◽  
J. Charnock ◽  
B. Wickramasinghe ◽  
O. Will ◽  
...  
Keyword(s):  
At Risk ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Suicide Risk ◽  
Population Level ◽  
Population Based ◽  
Psychological Support ◽  
Cancer Type ◽  
Increased Risk ◽  
Icd 10

Background: Previous research has identified an increased risk of suicide among cancer patients, however this has not been investigated at a population level in England. Those subgroups of patients most at risk need to be identified to ensure appropriate access to psychological support. Aim: To examine the variation in suicide risk among individuals diagnosed with cancer in England. Methods: We identified 4,453,547 individuals (21 million person-years at risk) aged 18 to 99 years at diagnosis of cancer during 1995 to 2015 from the national cancer registry, and followed them up until 31 August 2017. The outcomes of interest were both suicide and open verdicts (ICD-10 X60-X84, Y87.0, Y10-Y34 [excluding Y33.9, Y87.2]). Population-based expected deaths were as published by ONS [2]. We calculated standardized mortality ratios (SMRs) and absolute excess risks (AERs), and explored variation in suicide risk by cancer type, age at death, sex, deprivation, ethnicity, and years since cancer diagnosis. Results: 2352 cancer patients died by suicide. This was 0.08% of all deaths. The overall SMR for suicide was 1.19 (95% CI 1.14-1.24) and AER per 10,000 person-years was 0.18 (0.13-0.22). The risk was highest among individuals diagnosed with mesothelioma, with a 4.34-fold risk corresponding to 4.00 extra deaths per 10,000 person-years. This was followed by pancreatic (3.94-fold), esophageal (2.53-fold), lung (2.52-fold), and stomach (2.14-fold) cancer (all significantly elevated). Suicide risk was highest in the first 6 months following cancer diagnosis (SMR: 2.64 [2.42-2.89]), but a significantly increased risk persisted for 2 years (SMR: 1.21 [1.08-1.35]). Conclusion: Despite low numbers, the elevated risk of suicide in patients with certain cancers is a concern, representing potentially preventable deaths. The increased risk in the first 6 months after diagnosis, which is consistent with previous studies, highlights unmet needs for psychological support delivered alongside cancer diagnosis and treatment. Our findings suggest a need for improved risk stratification across cancer services, followed by targeted psychological support.

scholarly journals Australian Experiences of Out-of-Pocket Costs and Financial Burden Following a Cancer Diagnosis: A Systematic Review

2021 ◽  
Vol 18 (5) ◽  
pp. 2422
Author(s):  
Annie Bygrave ◽  
Kate Whittaker ◽  
Christine Paul ◽  
Elizabeth A. Fradgley ◽  
Megan Varlow ◽  
...  
Keyword(s):  
Systematic Review ◽  
Cancer Patients ◽  
Low Income ◽  
Cancer Care ◽  
Financial Burden ◽  
Secondary Outcome ◽  
Cancer Type ◽  
Increased Risk ◽  
The Impact ◽  
Out Of Pocket Costs

(1) Background: This systematic review was conducted to identify cancer patient experiences, and the impact of out-of-pocket costs and financial burden in Australia. (2) Methods: A systematic review, following the Preferring Reporting Items for Systematic Reviews and Meta-Analyses, was conducted. Cumulative Index of Nursing and Allied Health Literature and PubMed were searched. The primary outcome was financial burden among cancer patients and their families in Australia. The secondary outcome was out-of-pocket costs associated with cancer care and treatment within the population sample, and the impact of financial burden. (3) Results: Nineteen studies were included, covering more than 70,000 Australians affected by cancer. Out-of-pocket costs varied by cancer type and ranged from an average of AUD 977 for breast cancer and lymphoedema patients to AUD 11,077 for prostate cancer patients. Younger aged patients (≤65 years), Aboriginal and Torres Strait Islander people, people in rural and/or remote areas, households with low income, those who were unemployed and people with private health insurance were at increased risk of experiencing out-of-pocket costs, financial burden or a combination of both. (4) Conclusions: Australians diagnosed with cancer frequently experience financial burden, and the health and financial consequences are significant. Focusing efforts on the costs of care and options about where to have care within the context of informed decisions about cancer care is necessary.

scholarly journals COVID-19 increases age- and sex-controlled 21-day fatality rates for patients with melanoma, hematologic malignancies, uterine cancer, or kidney cancer

2021 ◽  
Author(s):  
Haiquan Li ◽  
Edwin Baldwin ◽  
Xiang Zhang ◽  
Colleen Kenost ◽  
Wenting Luo ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Kidney Cancer ◽  
Distant Metastasis ◽  
Uterine Cancer ◽  
Hematologic Malignancies ◽  
Hazard Ratio ◽  
Cancer Type ◽  
Increased Risk ◽  
Cancer Types ◽  
The Impact

AbstractIntroductionPrior research has reported an increased risk of fatality for cancer patients, but most studies investigated the risk by comparing cancer patients to non-cancer patients among COVID-19 infections. Only a few studies have compared the impact of a COVID-19 infection to non-infection with matched cancer patients and types.Methods & MaterialsWe conducted survival analyses of 4,606 cancer patients with COVID-19 test results from March 16 to October 11, 2020 in UK Biobank and estimated the overall hazard ratio of fatality with and without COVID-19 infection. We also examined the hazard ratios of thirteen specific cancer types with at least 100 patients.ResultsCOVID-19 resulted in an overall hazard ratio of 7.76 (95% CI: [5.78, 10.40], p<10−10) by studying the survival rate of 4,606 cancer patients for 21-days after the tests. The hazard ratio was shown to vary among cancer type, with over a 10-fold increase in fatality rate (false discovery rate≤0.02) for melanoma, hematologic malignancies, uterine cancer, and kidney cancer using a stratified analysis on each of the cancer types. Although COVID-19 imposed a higher risk for localized cancers compared to distant metastasis ones, those of distant metastasis yielded higher fatality rates due to their multiplicative effects.ConclusionThe results highlight the importance of timely care for localized and hematological cancer patients and the necessity to vaccinate uninfected patients as soon as possible, particularly for the cancer types influenced most by COVID-19.

scholarly journals Myelodysplastic Syndromes and Acute Myeloid Leukemia in Prostate Cancer Patients after Radiotherapy, a Population-Based Study

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3295-3295
Author(s):  
Rong Wang ◽  
Amer M. Zeidan ◽  
Pamela R Soulos ◽  
James B. Yu ◽  
Amy J. Davidoff ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Prostate Cancer Diagnosis ◽  
Myeloid Malignancies ◽  
Increased Risk ◽  
The Impact

Abstract Background: Radiation is a known risk factor for myeloid malignancies. Approximately 1.4% of prostate cancer patients who undergo radiotherapy and survive >10 years will develop a secondary cancer. However, the impact of radiotherapy on the development of second myeloid malignancies among prostate cancer patients is unclear. Methods: We performed a retrospective cohort study of elderly prostate cancer patients (diagnosed with clinical stages T1-T3 at the age of 66-99 years during 1999-2009) using the linked Surveillance, Epidemiology and End Results (SEER) - Medicare database. Patients who received chemotherapy after prostate cancer diagnosis or had radiotherapy for prostate cancer recurrence were excluded. We searched Medicare claims and SEER records to identify incident myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) diagnoses after prostate cancer diagnosis. Patients were followed from the diagnosis of prostate cancer through the diagnosis of a second malignancy, death or end of study (12/31/2010 for prostate cancer patients diagnosed in 1999-2003, and 12/31/2012 for those diagnosed in 2004-2011), whichever came first. Competing risk analysis was conducted to assess the impact of radiotherapy on the development of second MDS/AML, compared with surgery. Death and developing a second malignancy other than MDS/AML were considered competing events. Competing risks regression models were performed using the Fine and Gray method to provide estimates of hazard ratios (HRs). Age at prostate diagnosis, race, Elixhauser comorbidity score excluding anemia, history of anemia, disability function score (in quartiles), stage of prostate cancer, and year of prostate cancer diagnosis were adjusted for in the multivariate model. Results: A total of 32,212 prostate cancer patients were included, with a median follow-up of 4.91 years. Patients who received surgery (n = 17,503) were younger than those who underwent radiotherapy (n = 14,709). Intensity-modulated radiotherapy (IMRT) was the most common type of radiotherapy received (n = 8,813, 59.9%; median follow-up: 3.91 years), followed by brachytherapy (n = 3,201, 21.8%; median follow-up: 5.67 years) and external beam radiotherapy (EBRT, n = 2,695, 18.3%; median follow-up: 7.84 years). We observed 158 incident cases of MDS/AML (123 MDS cases and 35 AML cases) after the diagnosis of prostate cancer. The median time to develop MDS/AML was 3.30 (range: 0.20-9.77) years. In the multivariate model, compared with prostate cancer patients who received surgery only, patients who underwent radiotherapy had a significantly increased risk of developing second MDS/AML (HR = 1.54, 95% confidence interval [CI]: 1.09-2.11). When the analysis was stratified by specific radiation modality, increased risk of second MDS/AML was observed in each group, but the increase only reached statistical significance in the IMRT group (HR = 1.66, 95% CI: 1.09-2.52) (Table). We also conducted a separate analysis of the 123 patients who developed MDS. In the unadjusted model, compared with prostate cancer patients who received surgery only, patients who underwent any type of radiotherapy, EBRT, or IMRT had significantly increased risk of MDS. However, after adjusting for other factors, the magnitude of the effect diminished, and the effect was no longer statistically significant (Table). CONCLUSIONS: Our findings suggest that radiotherapy for prostate cancer increases the risk of MDS/AML, and the impact may differ by radiation modality. Additional studies with longer follow-up are needed to further clarify the role of radiotherapy in the development of subsequent myeloid malignancies. Table 1. Risk of Second MDS/AML after Radiotherapy among Prostate Cancer Patients Second cancerof interest Unadjusted Adjusted n (%) HR (95% CI) p HR (95% CI) p MDS/AML (n=158) Surgery 60 (0.34) 1.00 1.00 Radiotherapy 98 (0.67) 1.94 (1.41-2.68) <.01 1.54 (1.09-2.17) 0.01 Brachytherapy 19 (0.59) 1.58 (0.94-2.64) 0.08 1.35 (0.80-2.27) 0.26 EBRT 29 (1.08) 2.13 (1.36-3.34) <.01 1.51 (0.91-2.50) 0.11 IMRT 50 (0.57) 2.02 (1.39-2.93) <.01 1.66 (1.09-2.52) 0.02 MDS (n=123) Surgery 49 (0.28) 1.00 1.00 Radiotherapy 74 (0.50) 1.80 (1.25-2.58) <.01 1.43 (0.97-2.12) 0.07 Brachytherapy 15 (0.47) 1.53 (0.86-2.73) 0.20 1.32 (0.74-2.35) 0.35 EBRT 24 (0.89) 2.17 (1.33-3.54) <.01 1.53 (0.87-2.70) 0.14 IMRT 35 (0.40) 1.72 (1.11-2.65) 0.01 1.43 (0.88-2.33) 0.15 Disclosures Yu: 21st-Century Oncology LLC: Research Funding. Davidoff:Celgene: Consultancy, Research Funding. Gore:Celgene: Consultancy, Research Funding. Gross:21st-Century Oncology LLC: Research Funding; Medtronic: Research Funding; Johnson and Johnson: Research Funding. Ma:Incyte Corp: Consultancy; Celgene Corp: Consultancy.

Outcomes of COVID-19 in cancer patients: Report from the National COVID Cohort Collaborative (N3C).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1500-1500
Author(s):  
Noha Sharafeldin ◽  
Jing Su ◽  
Vithal Madhira ◽  
Qianqian Song ◽  
Eileen Lee ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Average Length ◽  
Clinical Severity ◽  
Diagnostic Code ◽  
Cancer Type ◽  
Patients With Cancer ◽  
Increased Risk ◽  
All Cause Mortality ◽  
The Impact ◽  
Representative Cohort

1500 Background: The impact of COVID-19 has disproportionately affected every aspect of cancer care and research—from introducing new risks for patients to disrupting the delivery of treatment and continuity of research. Variation in risk of adverse clinical outcomes in COVID-19 patients by cancer type has been reported from relatively small cohorts. Gaps in understanding effects of COVID-19 on cancer patients can be addressed through the study of a well-constructed representative cohort. The NCATS’ National COVID Cohort Collaborative (N3C) is a centralized data resource representing the largest multi-center cohort of COVID-19 cases and controls nationwide. We aimed to construct and characterize the cohort of cancer patients within N3C and identify risk factors for all-cause mortality from COVID-19. Methods: From the harmonized N3C clinical dataset, we used 3,295,963 patients from 39 medical US centers to construct a cancer patient cohort. We restricted analyses to adults ≥18 yo with a COVID-19 positive PCR or antigen test or ICD-10-CM diagnostic code for COVID-19 between 1/1/2020 and 2/14/2021. We followed N3C definitions where each lab-confirmed positive patient has one single index encounter. A modified WHO Clinical Progression Scale was used to determine clinical severity. All analyses were performed in the N3C Data Enclave on the Palantir platform. Results: A total of 372,883 adult patients with cancer were identified from the N3C cohort; 54,642 (14.7%) were COVID-19 positive. Most common represented cancers were skin (11.5%), breast (10.2%), prostate (8%), and lung cancer (5.6%). Mean age of COVID-19 positive patients was 61.6 years (SD 16.7), 47.3% over 65yo, 53.7% females, 67.2% non-Hispanic White, 21.0% Black, and 7.7% Hispanic or Latino. A total of 14.6% were current or former smokers, 22.3% had a Charlson Comorbidity Index (CCI) score of 0, 4.6% score of 1 and 28.1% score of 2. Among hospitalized COVID-19 positive patients, average length of stay in the hospital was 6 days (SD 23.1 days), 7.0% patients had died while in their initial COVID-19 hospitalization, 4.5% required invasive ventilation, and 0.1% extracorporeal membrane oxygenation. Survival probability was 86.4% at 10 days and 63.6% at 30 days. Older age over 65yo (Hazard ratio (HR) = 6.1, 95%CI: 4.3, 8.7), male gender (HR = 1.2, 95%CI: 1.1, 1.2), a CCI score of 2 or more (HR = 1.15, 95%CI: 1.1, 1.2), and acute kidney injury during hospitalization (HR = 1.3, 95%CI: 1.2, 1.4) were associated with increased risk of all-cause mortality. Conclusions: Using the N3C cohort we assembled the largest nationally representative cohort on patients with cancer and COVID-19 to date. We identified demographic and clinical factors associated with increased all-cause mortality in cancer patients. Full characterization of the cohort will provide further insights on the effects of COVID-19 on cancer outcomes and the ability to continue specific cancer treatments.

Attention to diet, exercise, and weight in the oncology clinic: Results of a national patient survey.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10549-10549
Author(s):  
Jennifer A. Ligibel ◽  
Lori J. Pierce ◽  
Catherine M. Bender ◽  
Tracy E Crane ◽  
Christina Marie Dieli-Conwright ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Online Survey ◽  
Early Stage ◽  
Cancer Type ◽  
Breast Cancer Patients ◽  
Related Factors ◽  
Increased Risk ◽  
Diet And Exercise ◽  
To Receive

10549 Background: Obesity and related factors are increasingly associated with increased risk of developing and dying from cancer. The American Society of Clinical Oncology (ASCO) conducted a survey of cancer patients to assess their experience in receiving recommendations and referrals related to weight, diet and exercise as a part of their cancer care. Methods: An online survey was distributed to potential participants between March and June 2020 via ASCO channels and patient advocacy organizations, with an estimated reach of over 25,000 individuals. Eligibility criteria included being 18 years, living in the US, and having been diagnosed with cancer. Logistic regression was used to determine factors associated with recommendation and referral patterns. Results: In total, 2419 individuals responded to the survey. Most respondents were female (75.5%), 61.8% had an early-stage malignancy, 38.2% had advanced disease, and 49.0% were currently receiving treatment. Breast cancer was the most common cancer type (36.0%). Average BMI was 25.8 kg/m2. The majority of respondents consumed £2 servings of fruits and vegetables per day (50.9%) and exercised £2 times per week (50.4%). Exercise was addressed at most or some oncology visits in 57.5% of respondents, diet in 50.7%, and weight in 28.4%. Referrals were less common: 14.9% of respondents were referred to an exercise program, 25.6% to a dietitian and 4.5% to a weight management program. In multiple regression analyses, racial and ethnicity minority respondents were more likely to receive advice about diet (Odds Ratio [OR] 1.92, 95% CI 1.56-2.38) and weight (OR 1.64, 95% CI 1.23-2.17) compared to non-Hispanic whites, individuals diagnosed with cancer in the past 5 yrs (vs > 5 yrs) were more likely to receive advice about exercise (OR 1.48, 95% CI 1.23-1.79), and breast cancer patients were more likely to receive advice about exercise (OR 1.37, 95% CI 1.11-1.68) and weight (OR 1.46, 95% CI 1.03-2.07) than other cancer patients. Overall, 74% of survey respondents had changed their diet or exercise after cancer diagnosis. Respondents reporting that their oncologist spoke to them about increasing exercise or eating healthier foods were more likely to report a change in behavior than those whose oncologists did not (exercise: 79.6% vs 69.0%, P < 0.001; diet 81.1% vs 71.4%, P < 0.001). Respondents whose oncologist had spoken to them about exercise were more likely to exercise > 2 times per week compared to respondents whose oncologists did not address exercise (53.5% vs 44.1%, P < 0.001). Conclusions: In a national survey of oncology patients, slightly more than half of respondents reported attention to diet and exercise during oncology visits. Provider recommendations for diet and exercise were associated with positive changes in these behaviors. Additional attention to diet and exercise as part of oncology visits is needed to help support healthy lifestyle change in cancer patients.

Impact of cancer on emergency department outcomes.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18618-e18618
Author(s):  
Alexander S. Qian ◽  
Edmund M. Qiao ◽  
Vinit Nalawade ◽  
Rohith S. Voora ◽  
Nikhil V. Kotha ◽  
...  
Keyword(s):  
Emergency Department ◽  
Risk Stratification ◽  
Hospital Mortality ◽  
Hospital Admission ◽  
Cancer Patients ◽  
Metastatic Cancer ◽  
Inpatient Admission ◽  
Cancer Site ◽  
Patients With Cancer ◽  
Increased Risk

e18618 Background: Cancer patients frequently utilize the Emergency Department (ED) for a variety of diagnoses, both related and unrelated to their cancer. Patients with cancer have unique risks related to their cancer and treatment which could influence ED-related outcomes. A better understanding of these risks could help improve risk-stratification for these patients and help inform future interventions. This study sought to define the increased risks cancer patients face for inpatient admission and hospital mortality among cancer patients presenting to the ED. Methods: From the National Emergency Department Sample (NEDS) we identified patients with and without a diagnosis of cancer presenting to the ED between 2016 and 2018. We used International Classification of Diseases, version 10 (ICD10-CM) codes to identify patients with cancer, and to identify patient’s presenting diagnosis. Multivariable mixed-effects logistic regression models assessed the influence of cancer diagnoses on two endpoints: hospital admission from the ED, and inpatient hospital mortality. Results: There were 340 million weighted ED visits, of which 8.3 million (2.3%) occurred in patients with a cancer diagnosis. Compared to non-cancer patients, patients with cancer had an increased risk of inpatient admission (64.7% vs. 14.8%; p < 0.0001) and hospital mortality (4.6% vs. 0.5%; p < 0.0001). Factors associated with both an increased risk of hospitalization and death included older age, male gender, lower income level, discharge quarter, and receipt of care in a teaching hospital. We identified the top 15 most common presenting diagnoses among cancer patients, and among each of these diagnoses, cancer patients had increased risks of hospitalization (odds ratio [OR] range 2.0-13.2; all p < 0.05) and death (OR range 2.1-14.4; all p < 0.05) compared to non-cancer patients with the same diagnosis. Within the cancer patient cohort, cancer site was the most robust individual predictor associated with risk of hospitalization or death, with highest risk among patients with metastatic cancer, liver and lung cancers compared to the reference group of prostate cancer patients. Conclusions: Cancer patients presenting to the ED have high risks for hospital admission and death when compared to patients without cancer. Cancer patients represent a distinct population and may benefit from cancer-specific risk stratification or focused interventions tailored to improve outcomes in the ED setting.

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