Anxiety and depression after cancer diagnosis: Prevalence rates by cancer type, gender, and age

2012 ◽  
Vol 141 (2-3) ◽  
pp. 343-351 ◽  
Author(s):  
Wolfgang Linden ◽  
Andrea Vodermaier ◽  
Regina MacKenzie ◽  
Duncan Greig
Keyword(s):  
Cancer Diagnosis ◽  
Anxiety And Depression ◽  
Cancer Type ◽  
Prevalence Rates ◽  
Gender And Age ◽  
After Cancer

scholarly journals Financial Insolvency as a Risk Factor for Early Mortality Among Patients With Cancer

2016 ◽  
Vol 34 (9) ◽  
pp. 980-986 ◽  
Author(s):  
Scott D. Ramsey ◽  
Aasthaa Bansal ◽  
Catherine R. Fedorenko ◽  
David K. Blough ◽  
Karen A. Overstreet ◽  
...  
Keyword(s):  
Risk Factor ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Cancer Diagnosis ◽  
Financial Distress ◽  
Cancer Type ◽  
Patients With Cancer ◽  
Hazard Ratios ◽  
Stage Disease ◽  
After Cancer

Purpose Patients with cancer are more likely to file for bankruptcy than the general population, but the impact of severe financial distress on health outcomes among patients with cancer is not known. Methods We linked Western Washington SEER Cancer Registry records with federal bankruptcy records for the region. By using propensity score matching to account for differences in several demographic and clinical factors between patients who did and did not file for bankruptcy, we then fit Cox proportional hazards models to examine the relationship between bankruptcy filing and survival. Results Between 1995 and 2009, 231,596 persons were diagnosed with cancer. Patients who filed for bankruptcy (n = 4,728) were more likely to be younger, female, and nonwhite, to have local- or regional- (v distant-) stage disease at diagnosis, and have received treatment. After propensity score matching, 3,841 patients remained in each group (bankruptcy v no bankruptcy). In the matched sample, mean age was 53.0 years, 54% were men, mean income was $49,000, and majorities were white (86%), married (60%), and urban (91%) and had local- or regional-stage disease at diagnosis (84%). Both groups received similar initial treatments. The adjusted hazard ratio for mortality among patients with cancer who filed for bankruptcy versus those who did not was 1.79 (95% CI, 1.64 to 1.96). Hazard ratios varied by cancer type: colorectal, prostate, and thyroid cancers had the highest hazard ratios. Excluding patients with distant-stage disease from the models did not have an effect on results. Conclusion Severe financial distress requiring bankruptcy protection after cancer diagnosis appears to be a risk factor for mortality. Further research is needed to understand the process by which extreme financial distress influences survival after cancer diagnosis and to find strategies that could mitigate this risk.

Social support as predictor of anxiety and depression in cancer caregivers six months after cancer diagnosis: A longitudinal study

2020 ◽  
Vol 29 (5-6) ◽  
pp. 996-1002
Author(s):  
Francisco García‐Torres ◽  
Marcin Jacek Jabłoński ◽  
Ángel Gómez Solís ◽  
Juan Antonio Moriana ◽  
Maria José Jaén‐Moreno ◽  
...  
Keyword(s):  
Social Support ◽  
Longitudinal Study ◽  
Cancer Diagnosis ◽  
Anxiety And Depression ◽  
Cancer Caregivers ◽  
After Cancer

scholarly journals New onset of type 2 diabetes as a complication after cancer diagnosis: A systematic review

2020 ◽  
Author(s):  
Ara Jo ◽  
Lisa Scarton ◽  
LaToya J. O'Neal ◽  
Samantha Larson ◽  
Nancy Schafer ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Cancer Diagnosis ◽  
After Cancer ◽  
New Onset

Echocardiography for the 10-year prediction of cardiomyopathy in long-term survivors of childhood cancer

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J.M Leerink ◽  
H.J.H Van Der Pal ◽  
E.A.M Feijen ◽  
P.G Meregalli ◽  
M.S Pourier ◽  
...  
Keyword(s):  
Childhood Cancer ◽  
Median Time ◽  
Cancer Diagnosis ◽  
Predictive Value ◽  
Validation Cohort ◽  
Funding Source ◽  
Derivation Cohort ◽  
After Cancer ◽  
Radiotherapy Dose

Abstract Background Childhood cancer survivors (CCS) treated with anthracyclines and/or chest-directed radiotherapy receive life-long echocardiographic surveillance to detect cardiomyopathy early. Current risk stratification and surveillance frequency recommendations are based on anthracycline- and chest-directed radiotherapy dose. We assessed the added prognostic value of an initial left ventricular ejection fraction (EF) measurement at >5 years after cancer diagnosis. Patients and methods Echocardiographic follow-up was performed in asymptomatic CCS from the Emma Children's Hospital (derivation; n=299; median time after diagnosis, 16.7 years [inter quartile range (IQR) 11.8–23.15]) and from the Radboud University Medical Center (validation; n=218, median time after diagnosis, 17.0 years [IQR 13.0–21.7]) in the Netherlands. CCS with cardiomyopathy at baseline were excluded (n=16). The endpoint was cardiomyopathy, defined as a clinically significant decreased EF (EF<40%). The predictive value of the initial EF at >5 years after cancer diagnosis was analyzed with multivariable Cox regression models in the derivation cohort and the model was validated in the validation cohort. Results The median follow-up after the initial EF was 10.9 years and 8.9 years in the derivation and validation cohort, respectively, with cardiomyopathy developing in 11/299 (3.7%) and 7/218 (3.2%), respectively. Addition of the initial EF on top of anthracycline and chest radiotherapy dose increased the C-index from 0.75 to 0.85 in the derivation cohort and from 0.71 to 0.92 in the validation cohort (p<0.01). The model was well calibrated at 10-year predicted probabilities up to 5%. An initial EF between 40–49% was associated with a hazard ratio of 6.8 (95% CI 1.8–25) for development of cardiomyopathy during follow-up. For those with a predicted 10-year cardiomyopathy probability <3% (76.9% of the derivation cohort and 74.3% of validation cohort) the negative predictive value was >99% in both cohorts. Conclusion The addition of the initial EF >5 years after cancer diagnosis to anthracycline- and chest-directed radiotherapy dose improves the 10-year cardiomyopathy prediction in CCS. Our validated prediction model identifies low-risk survivors in whom the surveillance frequency may be reduced to every 10 years. Calibration in both cohorts Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Dutch Heart Foundation

Abstract MP35: Physical Activity Before and After Cancer Diagnosis and Total and Cause-Specific Mortality

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Paulette D Chandler ◽  
Deirdre Tobias ◽  
Jule E Buring ◽  
I-Min Lee ◽  
Daniel Chasman ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cancer Diagnosis ◽  
Cancer Mortality ◽  
Total Mortality ◽  
Health Study ◽  
Specific Mortality ◽  
Before And After ◽  
After Cancer ◽  
Cvd Mortality

Background: Given the increased prevalence of cancer survivors in the United States, it is imperative to define risk factors for potential reductions in total and cause-specific mortality. Physical activity (PA) represents a promising target for intervention. Design: We prospectively evaluated PA from questionnaires before and after cancer diagnosis with total and cause-specific mortality among 13,297 subjects diagnosed with invasive cancer combined from the Physicians’ Health Study (PHS) (n=6328), Physicians’ Health Study II (PHS II) (n=912), and Women's Health Study (WHS) (n=6057). WHS and PHS participants were free of baseline cancer; PHS II participants reported no active cancer at baseline. We ascertained PA before and after an incident cancer diagnosis based on reports on repeated follow-up questionnaires. Death was ascertained by medical records and death certificates. Cox regression estimated combined hazard ratios (HRs) of mortality by PA adjusted for age, randomized treatments, BMI, and other lifestyle/demographic factors. We evaluated the interaction between PA before and after cancer diagnosis by comparing PA ≤1 versus ≥2 times/wk. Results: The mean follow-up after cancer diagnosis was 8.0, 7.5, and 5.2 y for WHS, PHS, and PHS II, respectively, during which there were 5623 deaths (WHS, 2164; PHS, 3269; PHS II; 190). Higher PA before cancer diagnosis was associated with significantly lower mortality. Compared with PA ≤ once/wk, the HRs (95% CIs) associated with PA 2-4 and >4 times/wk were 0.87 (0.82-0.93) and 0.88 (0.82-0.94) for total mortality; 0.77 (0.63-0.95) and 0.79 (0.62-0.997) for CVD mortality, and 0.90 (0.83-0.98) and 0.90 (0.83-0.98) for cancer mortality. Higher PA after cancer diagnosis was associated with significantly lower total and cancer mortality and non-significantly lower CVD mortality, with HRs (95% CIs) of 0.65 (0.58-0.72) and 0.66 (0.59-0.73) for total mortality; 0.78 (0.59-1.03) and 0.82 (0.61-1.10) for CVD mortality, and 0.66 (0.57-0.77) and 0.64 (0.55-0.74) for cancer mortality. There was a significant interaction of PA before and after cancer diagnosis for total (p int =0.02) and cancer (p int =0.007) mortality, but not CVD mortality (p int =0.38). Conclusions: Greater PA both before and after cancer diagnosis were significantly associated with lower total and cancer mortality. Higher PA before cancer diagnosis was also associated with lower CVD mortality. PA may be an important target for lower mortality after cancer diagnosis.

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.

scholarly journals Correction: The Association of Statin Use after Cancer Diagnosis with Survival in Pancreatic Cancer Patients: A SEER-Medicare Analysis

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0128730 ◽  
Author(s):  
Christie Y. Jeon ◽  
Stephen J. Pandol ◽  
Bechien Wu ◽  
Galen Cook-Wiens ◽  
Roberta A. Gottlieb ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
After Cancer ◽  
Statin Use
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